Stagnation zones for $mathcal{A}$-harmonic functions on canonical domains
Methods for computing Nash equilibria of a location–quantity game
Computers&Operations Research35(2008)3311–3330/locate/cor Methods for computing Nash equilibria of a location–quantity gameM.Elena Sáiz∗,Eligius M.T.HendrixWageningen Universiteit.Hollandseweg1,6706KN Wageningen,The NetherlandsAvailable online4March2007AbstractA two-stage model is described wherefirms take decisions on where to locate their facility and on how much to supply to which market.In such models in literature,typically the market price reacts linearly on supply.Often two competing suppliers are assumed or several that are homogeneous,i.e.,their cost structure is assumed to be identical.The focus of this paper is on developing methods to compute equilibria of the model where more than two suppliers are competing that each have their own cost structure,i.e.,they are heterogeneous.Analytical results are presented with respect to optimality conditions for the Nash equilibria in the two stages. Based on these analytical results,an enumeration algorithm and a local search algorithm are developed tofind equilibria.Numerical cases are used to illustrate the results and the viability of the algorithms.The methodsfind an improvement of a result reported in literature.᭧2007Elsevier Ltd.All rights reserved.Keywords:Iterative algorithms;Networks;Discrete location;Spatial models;Competition;Oligopoly;n-person games n>21.IntroductionMany studies in literature describe a so-called non-cooperative game where competingfirms decide on production locations and supply quantities to markets.To make a game theoretic analysis tractable,often a limited number of suppliers are considered,or alternatively homogeneousfirms and markets are assumed.We focus on situations where companies can be as well similar as not similar.In supply chains,farm cooperatives,etc.,many decisions appear in which preferences cannot be assumed to be homogeneous.Also symmetric behaviour,finite strategy set or a two or few actors setting are strong assumptions in literature.Decisions are influenced by differences on prices or cost(“player”depending)between actors and between the location of the facilities.Our focus is on constructing solution methods for games in which players are:asymmetric,heterogeneous and facing multiple decisions in several stages. Different competitive location models are available in the literature,see for instance the survey papers[1–3]and the references therein.They vary in the ingredients which form the model.For instance,the location space may be the plane,a network or a discrete set.In[4]the idea of a Cournot oligopoly equilibrium was introduced,where twofirms compete on the same market. Due to price reaction of the market on the total quantity offered,a price equilibrium appears.Hotelling[5]added the idea of having a freedom in choice of location,where the possible location area is a simple line in between the markets.A generally applicable concept is that of a Nash equilibrium[6]which is defined by the situation where none of the firms(players)is better off by changing its current(equilibrium)strategy.Because choice of location is usually prior∗Corresponding author.Tel.:+31317485644;fax:+31317485646.E-mail addresses:Elena.Saiz@wur.nl(M.E.Sáiz),Eligius.Hendrix@wur.nl(E.M.T.Hendrix).0305-0548/$-see front matter᭧2007Elsevier Ltd.All rights reserved.doi:10.1016/j.cor.2007.02.0223312M.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–3330to decision on quantities,in the model under consideration,this concept is applied to a supply chain study where two nested levels of decisions are at stake:that of supply quantity and location choice.The corresponding two-stage solution is called a subgame perfect Nash equilibrium.The basis of the model has been introduced by Bullow et al.[7]who consider a game with two markets and twofiter,Farrell and Shapiro[8]studied a game on quantity decisions with one market and nfirms where decisions are simultaneous and products are bbéand Hakimi[9]consider a two-stage location–quantity simultaneous game with m markets and twofirms with linear demand.Sarkar et al.[10]extend these results considering a two-stage static and simultaneous game with m markets and nfirms in a network.They only consider a case with a fixed number offirms entering in the market,i.e.,the quantities offered by eachfirm in all markets are strictly positive. Rhim et al.[11]extend the work in[10]by considering free entry(simultaneous and sequential)with symmetric cost (site specific)and capacity limitations.Their setting is a three-stage game with m markets and nfirms with production capacity and quantity decisions,andfinal stage is the location choice in a network.Recently,Dorta-González et al.[12]apply the Stakelberg equilibrium in a two-stage non-cooperative Cournot game with location and quantity choice with n markets located at the vertices of a network and rfirms.They use the Nash equilibrium concept in the location stage.In all of these studies,cases applied are small,most are symmetric,and no computational experience is reported. This paper extends the studies in[10,11].A two-stage location–quantity game with m markets and nfirms is described. The location space is a network,where the nodes are considered as possible locations for thefirms.Free entry is possible as in[11],i.e.,the number offirms entering the markets is not known in advance,but in our case costs are asymmetric (firm-specific).We provide conditions for the supplying decisions(second-stage of the game).Moreover,asfirms will be affected by the timing and level of entry on the market,properties on how to determine the size of the market are derived.Another difference with the study of Rhim et al.[11]is the procedure on how tofind the equilibrium of the game.We consider not only the possibility of leaving a market but also the possibility of that the supplier moves its facility to another location.Doing so,afirm has to re-think the quantity decision on how much to supply to which markets.By applying the method in the cases of Sarkar et al.[10],a mistake is found in the outcome given in their study. Their reported possible equilibrium appears to be wrong as is shown in Section4.Moreover,a sequential analysis is followed in this paper.It appears that starting with the cheapestfirm,one can successively arrive at the size of each of the markets.When market sizes are determined,the optimum quantities each supplier delivers to each markets they enter can be computed.In Section2,a model is outlined consisting of a non-cooperative game where quantity decisions and location decisions take place.Furthermore,theoretical results concerning the optimum decisions in these models are derived.In Section 3,methods for computing the Nash equilibria on quantity–location decisions and for computing the size of a market are described.A complete enumeration algorithm and a local search procedure are outlined.Numerical illustrations of model and methods can be found in Section4.Finally,Section5discusses the conclusions.2.Location–quantity game:problem formulationThe model describes a two-stage non-cooperative game.In thefirst stage of the game,firms take a simultaneous decision about where to locate a supplying facility in a network,i.e.,eachfirm chooses a location-strategy without knowledge of the strategy chosen by the otherfirms.In the second stage of the game,firms decide about the quantity to be produced at these facilities and how much to supply to each market.The model on quantity decisions and location choice is described by the following notation.Firms are denoted by an index i∈N={1,...,n}and markets are denoted by an index h∈M={1,...,m}each demanding a quantity of a good,depending on its price.In game theory,usually a linear price reaction model is assumed.We will follow this tradition.The demand is fulfilled by the supply of a quantity Q ih from the facility offirm i to market h.The location x i of the facility offirm i determines its marginal production cost c i(x i).The regional dispersion effect comes in when every market appears to be situated at one location and,an important assumption,each supplyfirm can open a facility at only one of the locations.The relations are formalised as follows.Let G=(V,E)be an undirected graph with V and E as its sets of nodes and edges,respectively,|V|=m.Given two nodes v i,v j∈V,d(v i,v j)is the length of a shortest(with respect to the sum of edge lengths)path on G connecting v i and v j.There are m markets located each at one node on the network;there are nfirms that open a facility each at one node with n m.Let x i∈V={v1,...,v m}be the location decision byfirm i on the network.The cost of establishingM.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–33303313 a facility byfirm i at x i is w(x i) 0.The quantity decision matrix Q for allfirms and all markets is given byQ=⎛⎜⎜⎜⎝Q11...Q1h (1)············Q i1···Q ih···Q im ············Q n1···Q nh···Q nm⎞⎟⎟⎟⎠,where the sum of a row indicates the quantity supply byfirm i over all markets h∈{1,...,m},s i= mh=1Q ih andthe sum of a column indicates the quantity supplied by allfirms i∈{1,...,n}to market h,q h= ni=1Q ih.The pricep h(q h)at market h is assumed to depend on the quantity according to the relation:p h(q h)=max{0, h− h q h},q h 0(1) with price parameters h 0, h>0.Notice that h is the price when quantity demanded is zero,and h is the pricereaction parameter of the inverse demand function.The price at market h depends on the quantity decision of allfirms that supply to market h.The nfirms interact over two stages.In thefirst stage,firms simultaneously choose the locations of their facilities, x i,i=1,...,n,vector X=(x1,...,x n)gives the location of thefirms.In the second stage,depending on the location decisions x i,firms choose quantities Q ih to be supplied to markets,which results in the quantity decision matrix Q. The profitfirm i wants to maximise is denoted by i(x i,Q).A strategy forfirm i at market h,[x i,Q ih],comprises a choice of x i for stage1and a choice of Q ih for stage2;a[x i,Q i·],for all markets,where Q i·denotes the row vector(Q i1,...,Q im).The game is solved backwards.First the second stage is solved.Firm i chooses optimally the vector of quantities Q i·=(Q i1,...,Q im),based on what the others deliver and depending on the chosen location x i: Q∗i·=arg maxQ i·i(x i,Q∗(X)).(2)The game can be considered a one-stage problem when matrix Q∗is defined for each location vector X.Nowfirm i chooses a location strategy x∗i such that:x∗i=arg maxx ii(x i,Q∗(X)).The unit transportation cost between the location x i of the facility offirm i and location v h of market h,is represented by t ih=T(d(x i,v h)),where T is concave and increasing in the distance.1The total cost of the location and supply decision offirm i is given byT C i(x i,Q i·)=mh=1t ih Q ih+c i(x i)s i+w(x i)=mh=1t ih Q ih+c i(x i)mh=1Q ih+w(x i)=mh=1(t ih+c i(x i))Q ih+w(x i).For the convenience of notation we represent the total unit cost offirm i at market h by T Cu ih=t ih+c i(x i).Profit is denoted by i and defined asi(x i,Q)=mh=1p h(q h)Q ih−T C i(x i,Q i·).(3)1This assumption also appears on the studies of Lederer and Thisse[13],Labbéand Hakimi[9],Sarkar et al.[10]among others.3314M.E.Sáiz,E.M.T.Hendrix /Computers &Operations Research 35(2008)3311–3330Table 1NotationN,M Set of firms and markets,respectively x i Location of firm i v h Location of market hQ ihQuantity supply by firm i at market h Q i ·=(Q i 1,...,Q im )Quantity decision vector for firm i s i =h ∈M Q ihTotal quantity supplied by firm i q h =i ∈N Q ih Total quantity supply at market h h , hPrice parameters p h (q h )=max {0, h − h q h },q h 0Price at market ht ih =T (d(x i ,v h ))Unit transportation costw(x i )Cost of establishing a centre at x i c i (x i )Marginal production cost T Cu ih =t ih +c i (x i )Total unit costT C i (x i ,Q i ·)Total cost of location and supplyi (x i ,Q)Profit for firm i depending on location and quantitiesPrice at market h is given by Eq.(1).Firms determine quantities for the markets to maximise profit.Substituting the price relation of the markets into (3)givesi (x i ,Q)=m h =1max ⎡⎣ h − h nj =1Q jh ,0⎤⎦Q ih −T C i (x i ,Q i ·).(4)Table 1summarises the notation used.In Section 2.1,properties are given of the equilibrium prices and quantities depending on the location decision of the firms.Section 2.2describes the criterion for selecting optimal location decisions,X ∗,based on the optimal quantity decisions,Q ∗(X).2.1.Quantity decisionThe Nash equilibrium is the solution concept used in the quantity-stage of the game.From (2),the Nash elements of the Q matrix can be determined by an iterative process.Nash equilibrium quantities shipped by firm i to market h follow from the first order condition optimising (4)over Q ih :Q ∗ih =max 0, h − h nj =1,j =i Q ∗jh−t ih −c i (x i )2 h .(5)This means that the equilibrium quantity Q ∗ih can be either 0or positive.In the remaining we will study for which firmsthe quantity Q ∗ih is positive and derive the exact quantity.First,we distinguish for each market h between two groups:A h with firms delivering to h ,Q ∗ih >0;and A h =N \A h with firms not delivering to h ,Q ∗ih =0:Q ∗ih >0for i ∈A h ,Q ∗ih =0for i ∈A h .Proposition 1provides the equilibrium quantity for each firm i ∈A h .Proposition 1.Let A h be the set of firms which supply market h ,|A h |=k h .The positive equilibrium quantities aregiven byQ ∗ih = h −k h (c i (x i )+t ih )+j ∈A h \{i }(c j (x j )+t j )(k h h(6)with Q ∗ih >0∀i ∈A h .Q ∗ih depends on production and transportation cost of the active suppliers .M.E.Sáiz,E.M.T.Hendrix /Computers &Operations Research 35(2008)3311–33303315Proof.From Eq.(5)follows for i ∈A hQ ∗ih =h −t ih −c i (x i )2 h −12j ∈A h \{i }Q ∗jh .(7)Let a ih =( h −t ih −c i (x i ))/(2 h ),then (7)can be written asQ ∗ih=a ih −12j ∈A h \{i }Q ∗jh .In vector notation⎛⎜⎜⎜⎝Q ∗1h ···Q ∗ih ···Q ∗k h h ⎞⎟⎟⎟⎠=⎛⎜⎜⎜⎝a 1h ···a ih ···a k h h ⎞⎟⎟⎟⎠−12[1k h 1k h −I ]⎛⎜⎜⎜⎝Q ∗1h ···Q ∗ih ···Q ∗k h h⎞⎟⎟⎟⎠,Q ∗h =a h −12[1k h 1k h −I ]Q ∗h ,where 1k h is the all ones vector and I is the k h ×k h unit matrix.By linear algebra,IQ ∗h =a h −12(1k h 1 k h −I )Q ∗h ,a h =12[1k h 1 k h +I ]Q ∗h ,then,Q ∗h can be written asQ ∗h =B −1a h ,(8)where B is the k h ×k h matrixB =12[1k h 1k h +I ]having the following form:B =⎛⎜⎜⎜⎜⎜⎜⎜⎝1...1/2...1/2........................1/2...1/2 (1)···1/2···1/2························1/2···1/2···1⎞⎟⎟⎟⎟⎟⎟⎟⎠.The inverse matrix can be derived to be,B −1=2I −1k h +11k h 1 k h ,B −1=2⎛⎜⎜⎜⎜⎜⎜⎜⎝k h /k h +1···−1/k h +1···−1/k h +1························−1/k h +1···−1/k h +1···k h /k h +1···−1/k h +1···−1/k h +1························−1/k h +1···−1/k h +1···k h /k h +1⎞⎟⎟⎟⎟⎟⎟⎟⎠.3316M.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–3330 The equivalence of Eqs.(5)and(6)for each market h now follows from(8):Q∗h =B−1a h=2I−1k h1kh1 kha h=2⎛⎜⎜⎜⎜⎜⎜⎜⎝k h/k h+1···−1/k h+1···−1/k h+1························−1/k h+1···−1/k h+1···k h/k h+1···−1/k h+1···−1/k h+1························−1/k h+1···−1/k h+1···k h/k h+1⎞⎟⎟⎟⎟⎟⎟⎟⎠⎛⎜⎜⎜⎝a1h···a ih···a kh h⎞⎟⎟⎟⎠and for eachfirm i we obtainQ∗ih=2k hk h+1a ih−2k h+1j∈A h\{i}a jh=2k h k h+1 h−t ih−c i(x i)2 h−2k h+1j∈A h\{i}h−(t jh+c j(x j))2 h=2k h h−2k h(t ih+c i(x i))2(k h h−(k h−1) h(k h h+j∈A h\{i}t jh+c j(x j)(k h h= h−k h(t ih+c i(x i))+j∈A h\{i}(t jh+c j(x j))(k h+1) hwhich corresponds to Eq.(6).Consequently,the total quantity supplied to market h isq∗h=j∈A h Q∗jh=1(k h+1) h⎛⎝kh h−j∈A h(c j(x j)+t jh)⎞⎠,(9)which means that higher average marginal cost and transportation costs decrease the total quantity supplied.The optimal price at each market can now be derived by substituting(9)into(1):p∗h=1k h+1⎛⎝h+j∈A h(c j(x j)+t jh)⎞⎠.(10)Optimal prices at each market proportionally rise with average marginal cost and transportation cost over thefirms supplying the market.Higher costs leads to a higher equilibrium price and lower costs leads to higher quantity supplied. In order to have any delivery at market h in(9)a necessary condition is that∃j∈N such that T Cu jh< h.From Proposition1also follows the result for the symmetric case.Theorem1.Let unitary costs be symmetric(the same)for all the suppliers at market h.If unitary costs are lower than h,all the suppliers will enter the market.Proof.Let the nfirms entering the market have the same cost,T Cu1h=T Cu2h=···=T Cu nh=Cu h and Cu h< h, the optimal quantity and price can be derived from Eqs.(6)and(10),Q∗ih= h−nT Cu ih+nj=1,j=iT Cu jh(n+1) h=h−Cu h(n+1) h>0andp∗h= h− h q h= h− h n h−Cu h(n+1) h=h+nCu hn+1.M.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–33303317 Corollary2.Let unitary costs be symmetric(the same)for all the suppliers at market h.If unitary costs are higher than h,no suppliers will enter the market.From Proposition1can also be derived when afirm would be interested to enter market h,given that a set offirms A h is already delivering.Proposition2.Let A h be a set offirms supplying market h.Afirm i is interested in supplying market h if T Cu ih<p∗h. Proof.Follows from the partial derivative of i with respect to Q∗ih for Q∗ih=0.Proposition3.In the optimum Q∗,∀i∈A h,T Cu ih<p∗h.Proof.From Eq.(10)the equilibrium price isp∗h=1k h+1⎛⎝h+j∈A h(c j(x j)+t jh)⎞⎠=1k h+1⎛⎝h+j∈A hT Cu jh⎞⎠.From Eq.(6)equilibrium quantities are given byQ∗ih= h−k h(c i(x i)+t ih)+j∈A h\{i}(c j(x j)+t j)(k h+1) h= h−k h T Cu ih+j∈A h\{i}T Cu jh+T Cu ih−T Cu ih(k h+1) h= h−(k h+1)T Cu ih+j∈A h\{i}T Cu jh+T Cu ih(k h+1) h= h−(k h+1)T Cu ih+j∈A hT Cu jh(k h+1) h= h+j∈A hT Cu jh(k h+1) h−(k h+1)T Cu ih(k h+1) h=p∗hh−T Cu ihh=p∗h−T Cu ihh.From Eq.(6),at equilibrium Q∗ih>0∀i∈A h,(p∗h−T Cu ih)/ h>0such that p∗h>T Cu ih. Consequently,for i∈A hc i(x i)+t ih<1|A h|+1⎛⎝h+j∈A h[c j(x j)+t jh]⎞⎠.For all j/∈A h,Q∗jh=0andc j(x j)+t jh1h⎛⎝h+i∈A h[c i(x i)+t ih]⎞⎠.Proposition4.The relation between thefirm with the highest total unit costs in the active set,i∈A h,with anyfirm j∈A h which is not entering the market isT Cu ih< h+r∈A hT Cu rh|A h|+1T Cu jh.3318M.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–3330Proof.Thefirst inequality follows from T Cu ih<p h and is satisfied by anyfirm in the active set A h.The last inequality is satisfied by anyfirm j∈A h following from T Cu jh p h.Proposition4shows thatmax i∈A h T Cu ih<p h minj∈A hT Cu jh.This is used in the algorithms in Section3to determine the number of activefirms|A h|.Firms are ordered on the basis of total unit costs,such that T Cu(1)h T Cu(2)h ··· T Cu(n)h.The rule that is used is the following:(1)initialise p= ,|A|=0;(2)while T Cu(k)<p,(k)enters the market and the price is updated.More details of the algorithms are given in Section3.Let M i be the set of markets in whichfirm i is active,M i={h∈M|i∈A h}.The total quantity supplied by each firm iss i=h∈M i Q∗ih=h∈M ih−k h(c i(x i)+t ih)+j∈A h\{i}(c j(x j)+t jh)(k h+1) h.Total cost for eachfirm isT C i=h∈M i (c i(x i)+t ih)h+j∈A h\{i}(c j(x j)+t jh)−k h(c i(x i)+t ih)(k h+1) h+w(x i).Using(6)and(9),thefinal payoff for eachfirm given location vector X is i(X)=h∈M i(p∗h−(c i(x i)+t ih)Q∗ih−w(x i)=h∈M i [ h+j∈A h(c j(x j)+t jh)−(k h+1)(c i(x i)+t ih)]2(k h+1)2 h−w(x i)=h∈M i [ h+j∈A h\{i}(c j(x j)+t jh)−n(c i(x i)+t ih)]2(k h+1)2 h−w(x i)=h∈M ih(Q∗ih)2−w(x i).Concluding,the optimum Q∗ih,q∗h and p∗h in Eqs.(6),(9)and(10),respectively,is a Nash equilibrium for the competitive second stage of the game given location vector X.2.2.Location decisionGiven the optima of the second stage,focus is on thefirst stage of the game.Considering the equilibrium supply quantity choice in the second stage,Q∗(X),eachfirm i maximises the profit function i by selecting a location on the network.Firms locate at one of the nodes of the network.We assume that severalfirms can be located at the same site. At equilibrium,no other location decision is better off for eachfirm.The strategy X∗=(x∗1,...,x∗n)is a Nash equilibrium if for eachfirm i,x∗i is the best response to the strategies specified by the n−1otherfirms:i(x∗i,Q∗(X∗)) i(x i,Q∗(ˆX))withˆX=(x∗1,...,x i,...,x∗n)∀x ifor every feasible strategy x i.That is,x∗i solvesmaxx ii(x i,Q∗(ˆX)).The method and algorithms used to select optimal locations and quantities for thefirms are described in Section3.M.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–33303319 3.Methods for computing Nash quantities and Nash locationsThe results of Section2can be used tofind equilibria of the two level game.A procedure is described that solves the quantity game given a location configuration.This procedure can be used in algorithms tofind equilibria for the location decision.The idea is to do a global search tofind all Nash equilibria.Global search methods include complete(enumerative)search strategies and stochastic search algorithms(pure random search,multistart among others,see[14]).First,we describe an algorithm that systematically enumerates all location possibilities,for which equilibrium quantities are computed.After that,it tries to detect which location vectors correspond to a Nash equilibrium by checking whether it is better for afirm to relocate its facility.Notice that all m n location configurations are generated. This is called a full enumeration.Second,a multistart algorithm based on an application of Teitz and Bart location–allocation heuristic is described (see[15]).2Efficiency and effectiveness are discussed in comparison to the complete enumeration algorithm.The enumeration algorithm is sketched in“Algorithm for searching equilibria”(Algorithm1)which calls iteratively to a subroutine called QUANTITY.This procedure computes the Nash equilibrium quantities for each location vector based on the size of the market and equilibrium price(line4in Algorithm1).Once the optimal quantities have been determined,the subroutine called PROFIT computes the profit for thefirms at all the possible location vectors based on Nash quantities(line5).The output is the profit(payoff)matrix .Finally,a subroutine determining the Nash equilibria on location decisions,called EQUILIBRIA(line7),is described.Algorithm1.Algorithm for searching Nash equilibria.Require:Number offirms n;number of markets m;parameters and ;distance matrix d(v i,v j);marginal costs c i(x i),opening costs w(x i)Ensure:Nash equilibria of the non-cooperative game1:L←m n all possible locations2:Generate location matrix with rows X l iteratively3:for each location l do4:Q∗l←Q UANTITY(X l)5: ∗l←P ROFIT(X l,Q∗l)6:end for7:E∗←E QUILIBRIA( ∗)3.1.Procedure Quantity for computing Nash equilibrium on quantitiesProcedure QUANTITY is called by Algorithm1for each of the possible locationAlgorithm2.Quantity(X):procedure to compute Nash equilibrium quantities,Q∗.Require:location vector X and global variablesEnsure:Nash equilibrium Quantity decisions:Q∗1:procedure Q UANTITY(X,and global variables)2:for h∈M do3:T Cu·h←t·h+c(X) Total unit cost4:ST Cu·h←S ORT(T Cu·h) Order thefirms on total unit costs5:[k h,p h]←S IZE M ARKET(ST Cu·h, h,k h,p h,A h)6:Q∗·h←O PT Q(ST Cu·h,p h, h, h,k h,A h)7:end for8:end procedure2We thank an anonymous referee for inviting us to consider this algorithm.3320M.E.Sáiz,E.M.T.Hendrix/Computers&Operations Research35(2008)3311–3330vectors for the suppliers.Every time the procedure is called,total unit costs are computed for eachfirm at each market and ordered,T Cu(1)h,...,T Cu(n)h(SORT in line4).Results derived in Section2.1are applied to compute optimal quantities.The computation generates these by the following two procedures:(1)Procedure SIZEMARKET(Algorithm3):this procedure determines the size of the active set A h(Proposition4)and the equilibrium price p∗h;(2)Procedure OPTQ(Algorithm4):this procedure computes optimal quantities forfirms entering the market h.FromEq.(6)(Proposition1)and depending on the asymmetry of thefirms,the methodfinds the optimal quantities for the activefirms.3.2.Algorithm location stageIn the location-stage,the problem is to maximise profit by selecting a node where to locate the facility in the network.Given n supplierfirms and m markets,the feasible set X has L=m n elements.A Nash equilibrium can be identified for thefirst stage game by testing each element of X in the following way.Consider location vector X l=(x l1,...,x li,...,x ln).Note thatAlgorithm3.SizeMarket((T C, ,k,p,A):procedure to determine the size k of market h and equilibrium price p.Require:Total unitary costs T C,Ensure:Size and price of market h:k,p;and active set,A1:procedure S IZE M ARKET(T C, ,k,p,A)2:p← Initial price at the market3:k←0 Initial size of the market4:while k n and T C k+1<p do5:k←k+1;6:p← +kj=1T C j(k+1);7:end while8:end procedureAlgorithm4.OptQ(T C,p, , ,k,A):procedure to compute the optimal quantities forfirms at market h. Require:Total unitary costs T C,price at market,p,parameters , and sizeof the market,k,active set,AEnsure:Optimal quantities:Q∗1:procedure OptQ(T C,p, , ,k,A)2:if k==0then3:Q←0∀i4:else5:for i∈A do6:Q i←− −(k+1)T C i+ kj=1T C j(k+1)7:end for8:for i∈A=N\A do9:Q i←−0;10:end for11:end if12:end procedureit is possible that x li=x lj for i=j∈N.For eachfirm,one should test whetherfirm i located at x li is better off leaving its current location choosing another,x ki∈V with k=l and k L.For this,one should check the profit of thefirm at。
伍德里奇stata编程题第三章
第一节:介绍1.1 什么是Stata编程?Stata编程是指利用Stata软件进行程序设计和编写,以实现特定的数据分析、处理和可视化功能。
1.2 为什么要学习Stata编程?Stata编程可以提高数据处理和分析的效率,减少重复工作,提高数据分析的稳定性和可重复性。
通过编程,可以实现更复杂的数据分析和统计模型,提高专业水平。
1.3 本章内容概述本章将介绍伍德里奇stata编程题第三章的主要内容,包括Stata基本编程语法和常用编程技巧,帮助读者掌握Stata编程的基本原理和方法,从而应用于实际数据分析和研究工作中。
第二节:Stata基本编程语法2.1 Stata编程环境概述Stata编程环境包括Stata软件和Stata编程语言。
Stata软件是一款专业的统计分析软件,广泛应用于学术研究和经济管理领域;Stata编程语言是一种用于控制和操作Stata软件的代码语言,具有简单、灵活和强大的特点。
2.2 Stata编程语法基础Stata编程语法包括变量定义、数据导入、数据处理、图表绘制等基本操作,需要掌握Stata的基本命令和函数,了解Stata编程的基本原理和逻辑。
2.3 Stata编程实例演练通过实际案例演练,介绍Stata编程的基本语法和常用操作,帮助读者理解和掌握Stata编程的应用方法和技巧。
第三节:常用Stata编程技巧3.1 数据处理技巧介绍Stata中常用的数据处理技巧,包括数据清洗、变量操作、数据合并、数据重塑等操作方法,帮助读者提高数据处理的效率和准确性。
3.2 统计分析技巧介绍Stata中常用的统计分析技巧,包括描述统计分析、回归分析、方差分析等方法,帮助读者实现复杂的统计分析和建模需求。
3.3 图表绘制技巧介绍Stata中常用的图表绘制技巧,包括散点图、折线图、柱状图等图表类型,帮助读者设计和绘制专业的统计图表。
第四节:Stata编程实战应用4.1 实战案例分析通过实际案例分析,介绍Stata编程在实际数据分析和研究工作中的应用,帮助读者了解Stata编程的实际应用场景和操作流程。
ansys常见错误
ansys常见错误ansys分析出现问题NO.0052some contact elements overlap with the other contact element which can cause over constraint. 这是由于在同一实体上,即有绑定接触(MPC)的定义,又有刚性区或远场载荷(MPC)的定义,操作中注意在定义刚性区或远场载荷时避免选择不必要的DOF自由度,以消除过约束NO.0053Shape testing revealed that 450 of the 1500 new or modified elements violate shape warning limits.是什么原因造成的呢?单元网格质量不够好尽量,用规则化网格,或者再较为细密一点NO.0054在用Area Fillet对两空间曲面进行倒角时出现以下错误:Area 6 offset could not fully converge to offset distance 10. Maximum error between the two surfaces is 1% of offset distance.请问这是什么错误?怎么解决?其中一个是圆柱接管表面,一个是碟形封头表面。
ansys的布尔操作能力比较弱。
如果一定要在ansys里面做的话,那么你试试看先对线进行倒角,然后由倒角后的线形成倒角的面。
建议最好用UG、PRO/E这类软件生成实体模型然后导入到ansysNO.0055There are 21 small equation solver pivot terms.; SOLID45 wedges are recommended only in regions of relatively lowstress gradients.第一个问题我自己觉得是在建立contact时出现的错误,但自己还没有改正过来;第二个也不知道是什么原因。
FLUENT入门一般问题集锦
Fluent经典问题1对于刚接触到FLUENT新手来说,面对铺天盖地的学习资料和令人难读的FLUENT help,如何学习才能在最短的时间内入门并掌握基本学习方法呢?答:学习任何一个软件,对于每一个人来说,都存在入门的时期。
认真勤学是必须的,什么是最好的学习方法,我也不能妄加定论,在此,我愿意将我三年前入门FLUENT心得介绍一下,希望能给学习FLUENT的新手一点帮助。
由于当时我需要学习FLUENT来做毕业设计,老师给了我一本书,韩占忠的《FLUENT流体工程仿真计算实例与应用》,当然,学这本书之前必须要有两个条件,第一,具有流体力学的基础,第二,有FLUENT安装软件可以应用。
然后就照着书上二维的计算例子,一个例子,一个步骤地去学习,然后学习三维,再针对具体你所遇到的项目进行针对性的计算。
不能急于求成,从前处理器GAMBIT,到通过FLUENT进行仿真,再到后处理,如TECPLOT,进行循序渐进的学习,坚持,效果是非常显著的。
如果身边有懂得FLUENT的老师,那么遇到问题向老师请教是最有效的方法,碰到不懂的问题也可以上网或者查找相关书籍来得到答案。
另外我还有本《计算流体动力学分析》王福军的,两者结合起来学习效果更好。
2 CFD计算中涉及到的流体及流动的基本概念和术语:理想流体和粘性流体;牛顿流体和非牛顿流体;可压缩流体和不可压缩流体;层流和湍流;定常流动和非定常流动;亚音速与超音速流动;热传导和扩散等。
3在数值模拟过程中,离散化的目的是什么?如何对计算区域进行离散化?离散化时通常使用哪些网格?如何对控制方程进行离散?离散化常用的方法有哪些?它们有什么不同?首先说一下CFD的基本思想:把原来在时间域及空间域上连续的物理量的场,如速度场,压力场等,用一系列有限个离散点上的变量值的集合来代替,通过一定的原则和方式建立起关于这些离散点上场变量之间关系的代数方程组,然后求解代数方程组获得场变量的近似值。
物流专业术语
物流专业术语范围本标准确定了物流活动中的基本概念术语、物流作业术语、物流技术装备与设施术语、物流管理术语及其定义.本标准适用于物流及相关领域的信息处理和信息交换,亦适用于相关的法规、文件;引用标准下列标准所包含的条文,通过在本标准中引用而构成为本标准的条文;本标准出版时,所示版本均为有效;所有标准都会被修订,使用本标准的各方应探讨使用下列标准最新版本的可能性;GB/T 1992--1985 集装箱名词术语neq ISO 830:1981GB/T 4122;1--1996 包装术语基础CB/T 17271--1998 集装箱运输术语中文索引AABC分类管理....................................6.9安全库存.......................................4.16B班轮运输.......................................5.34搬运...........................................4.22包装...........................................4.25保管...........................................4.12保税仓库.......................................5.5报关...........................................5.40报关行.........................................5.41C仓库...........................................5.1仓库布局.......................................6.4.仓库管理.......................................6.3叉车...........................................5.19储存...........................................4.11船务代理.......................................5.36D大陆桥运输.....................................5.33单元装卸.......................................4.24第三元物流.....................................3.25电子订货系统...................................6.10电子数据交换...................................3.31定量订货方式...................................6.7定牌包装.......................................4.27定期订货方式...................................6.8定制物流.......................................3.26堆码...........................................4.21F发货区.........................................5.14废弃物物流.....................................3.19分拣...........................................4.37G公路集装箱中转站...............................5.28 供应链.........................................3.29供应链管理.....................................6.21供应商库存.....................................6.26供应物流.......................................3.15共同配送.......................................4.35国际多式联运...................................5.32国际货物运输保险...............................5.39 国际货运代理...................................5.37国际铁路联运...................................5.31国际物流.......................................3.24H海关监管货物...................................5.7换算箱.........................................5.24回收物流.......................................3.18货场...........................................5.16货垛...........................................4.20货架...........................................5.17J集货...........................................4.39集装化.........................................4.31集装箱.........................................5.23集装箱货运站...................................5.29.集装箱码头.....................................5.30集装箱运输.....................................4.7集装运输.......................................4.6计算局付诸订货系统.............................6.25 监管仓库.......................................5.6拣选...........................................4.38检验...........................................4.43进出口商品检验.................................5.42 经常库存.......................................4.15经济订货批量...................................6.6K控湿储存区.....................................5.11.库存...........................................4.14库存控制.......................................6.5库存周期.......................................4.17.库房...........................................5.8快速反应.......................................6.22L冷藏区.........................................5.9冷冻区.........................................5.10冷链...........................................4.42理货...........................................5.38立体仓库.......................................5.3联合运输.......................................4.2连续库存补充计划...............................6.24 料棚...........................................5.15零库存技术.....................................6.13.流通加工.......................................4.41绿色物流.......................................3.20M门到门.........................................4.8P配送...........................................4.34配送需要计划...................................6.17 配送中心.......................................4.36配送资源计划...................................6.18 拼箱货.........................................4.10Q企业物流.......................................3.21企业资源计划...................................6.20 前置期或提前期.............................4.18全集装箱船.....................................5.26S散装化.........................................5.32社会物流.......................................3.22生产物流.......................................3.16收货区.........................................5.13输送区.........................................5.20甩挂运输.......................................4.5T特种货物集装箱.................................5.25铁路集装箱.....................................5.27. 托盘...........................................5.18托盘包装.......................................4.30 W温度可控区.....................................5.12 无形损耗.......................................3.33 物料需要计划...................................6.15 物流...........................................3.2物流成本.......................................3.7.物流成本管理...................................6.14. 物流单证.......................................3.13 物流管理.......................................3.8物流活动.......................................3.3物流技术.......................................3.6物流联盟.......................................3.14 物流模数.......................................3.5物流企业.......................................3.12 物流网络.......................................3.10 物流信息.......................................3.11 物流战略.......................................6.1物流战略管理...................................6.2. 物流中心.......................................3.9物流资源计划...................................6.19. 物流作业.......................................3.4物品...........................................3.1物品储备.......................................4.13. X箱式车.........................................5.22销售包装.......................................4.26 销售物流.......................................3.17 虚拟仓库.......................................5.4虚拟物流.......................................3.27Y业务外包.......................................6.27 有效客户反应...................................6.23 有形损耗.......................................3.32 运输...........................................4.1运输包装.......................................4.29. Z增值物流服务...................................3.28 整箱货.........................................4.9直达运输.......................................4.3直接换装.......................................4.33制造资源计划...................................6.16中性包装.......................................4.28中转运输.......................................4.4装卸...........................................4.23准时制.........................................6.11准时制物流.....................................6.12自动导引车.....................................5.21自动化仓库.....................................5.2租船运输.......................................5.35组配...........................................4.40英文索引AABC classification......................................6.9 Article.................................................3.1Article reserves........................................4.13 Assembly................................................4.40 Automatic guided vehicle AGV .........................5.21 Automatic warehouse.....................................5.3.BBar code................................................3.30Boned warehouse.........................................5.6Box car.................................................5.22CCargo under custom's supervision........................5.8 Chill space.............................................5.9Cold chain..............................................4.42 Combined transport......................................4.2 Commodity inspection....................................5.42 Computer assisted ordering CAO .......................6.25 Container...............................................5.23 Container freight station CFS ........................5.29 Container terminal......................................5.30 Container transport.....................................4.7 Containerization........................................4.31 Containerized transport.................................4.6 Continuous replenishment program CRP .................6.24 Conveyor................................................5.20Cross docking...........................................4.33 Customized logistics....................................3.26 Customs broker..........................................5.41 Customs declaration.....................................5.40Cycle stock.............................................4.15D Distribution............................................4.34 Distribution center.....................................4.36 Distribution logistics..................................3.17 Distribution processing.................................4.41 Distribution requirements planning DRP ...............6.17 Distribution resource planning DRP II ................6.18 Door-to-door............................................4.8Drop and pull transport.................................4.5EEconomic order quantity EOQ ..........................6.6 Efficient customer response ECR ......................6.23 Electronic data interchange EDI ......................3.31 Electronic order system EOS ..........................6.10 Enterprise resource planning ERP .....................6.20 Environmental logistics.................................3.20 Export supervised warehouse.............................5.7 External logistics......................................3.22FFixed-interval system FIS ............................6.8Fixed-quantity system FQS ............................6.7Fork lift truck.........................................5.19Freeze space............................................5.10Full container load FCL ..............................4.9Full container ship.....................................5.26 G Goods collection........................................4.39Goods shed..............................................5.15Goods shelf.............................................5.17Goods stack.............................................4.20Goods yard..............................................5.16HHanding/carrying........................................4.22 Humidity controlled space...............................5.11IIn bulk.................................................4.32Inland container depot..................................5.28 Inspection..............................................4.43 Intangible loss.........................................3.33Internal logistics......................................3.21 International freight forwarding agent..................5.37 International logistics.................................3.24 International multimodal transport......................5.32 International through railway transport.................5.31 International transportation cargo insurance............5.39Inventory...............................................4.14 Inventory control.......................................6.5 Inventory cycle time....................................4.17JJoint distribution......................................4.35Just in time JIT .....................................6.11Just-in-time logistics..................................6.12 LLand bridge transport...................................5.33Lead-time ..............................................4.18Less than container load LCL .........................4.10 Liner transport.........................................5.34 Loading and unloading ..................................4.23 Logistics...............................................3.2Logistics activity......................................3.3Logistics alliance......................................3.14 Logistics center........................................3.9 Logistics cost..........................................3.7Logistics cost control..................................6.14 Logistics documents.....................................3.13 Logistics enterprise....................................3.12 Logistics information...................................3.11 Logistics management....................................3.8 Logistics modulus.......................................3.5 Logistics network.......................................3.10 Logistics operation.....................................3.4 Logistics resource planning LRP ......................6.19 Logistics strategy......................................6.1 Logistics strategy management...........................6.2 Logistics technology....................................3.6MManufacturing resource planning MRP II ...............6.16 Material requirements planning MRP ...................6.15 Military logistics......................................3.23NNeutral packing.........................................4.28OOrder cycle time........................................4.19Order picking...........................................4.38 Outsourcing.............................................6.27PPackage/packaging.......................................4.25 Packing of nominated brand..............................4.27 Pallet..................................................5.18 Palletizing.............................................4.30QQuick response QR ....................................6.22RRailway container yard..................................5.27 Receiving space.........................................5.13 Returned logistics......................................3.18SSafety stock............................................4.16Sales package...........................................4.26 Shipping agency.........................................5.36 Shipping by chartering..................................5.35 Shipping space..........................................5.14 Sorting.................................................4.37Specific cargo container................................5.25 Stacking................................................4.21 Stereoscopic warehouse..................................5.4 Storage.................................................4.12 Storehouse..............................................5.2 Storing.................................................4.11Supply chain............................................3.29 Supply chain management SCM ..........................6.21 Supply logistics........................................3.15T Tally...................................................5.38Tangible loss...........................................3.32 Temperature controlled space............................5.12 Third-part logistics TPL .............................3.25 Through transport.......................................4.3 Transfer transport......................................4.4 Transport package.......................................4.29 Transportation..........................................4.1 Twenty-feet equivalent unit TEU ......................5.24 UUnit loading and unloading..............................4.24VValue-added logistics service...........................3.28 Vendor managed inventory VMI .........................6.26 Virtual logistics.......................................3.27Virtual warehouse.......................................5.5W Warehouse...............................................5.1 Warehouse layout........................................6.4 Warehouse management....................................6.3ZZero-inventory technology...............................6.133.基本概念术语3.1 物品article经济活动中涉及到实体流动的物质资料3.2 物流logistics物品从供应地向接收地的实体流动过程;根据实际需要,将运输、储存、装卸、搬运、包装、流通加工、配送、信息处理等基本功能实施有机结合;3.3 物流活动logistics activity物流诸功能的实施与管理过程;3.4 物流作业logistics operation实现物流功能时所进行的具体操作活动;3.5 物流模数logistics modulus物流设施与设备的尺寸基准;3.6 物流技术logistics technology物流活动中所采用的自然科学与社会科学方面的理论、方法,以及设施、设备、装置与工艺的总称;3.7 物流成本logistics cost物流活动中所消耗的物化劳动和活劳动的货币表现;3.8 物流管理logistics management为了以最低的物流成本达到用户所满意的服务水平,对物流活动进行的计划、组织、协调与控制;3.9 物流中心logistics center从事物流活动的场所或组织,应基本符合以下要求:a 主要面向社会服务;b物流功能健全;c完善的信息网络;d辐射范围大;e少品种、大批量;f存储\吞吐能力强;g物流业务统一经营、管理;3.10 物流网络logistics network物流过程中相互联系的组织与设施的集合;3.11 物流信息logistics information反映物流各种活动内容的知识、资料、图像、数据、文件的总称;3.12 物流企业logistics enterprise从事物流活动的经济组织;3.13 物流单证logistics documents物流过程中使用的所有单据、票据、凭证的总称;3.14 物流联盟logistics alliance两个或两个以上的经济组织为实现特定的物流目标而采取的长期联合与合作;3.15 供应物流supply logistics为生产企业提供原材料、零部件或其他物品时,物品在提供者与需求者之间的实体流动; 3.16 生产物流production logistics生产过程中,原材料、在制品、半成品、产成品等,在企业内部的实体流动;3.17销售物流distribution logistics生产企业、流通企业出售商品时,物品在供与需方之间的实体流动;3.18 回收物流returned logistics不合格物品的返修、退货以及周转使用的包装容器从需方返回到供方所形成的物品实体流动;3.19 废弃物物流waste material logistics将经济活动中失去原有使用价值的物品,根据实际需要进行收集、分类、加工、包装、搬运、储存等,并分送到专门处理场所时形成的物品实体流动;3.20 绿色物流environmental logistics在物流过程中抑制物流对环境造成危害的同时,实现对物流环境的净化,使物流资料得到最充分利用;3.21 企业物流internal logistics企业内部的物品实体流动;3.22 社会物流external logistics企业外部的物流活动的总称;3.23 军事物流military logistics用于满足军队平时与战时需要的物流活动;3.24 国际物流international logistics不同国家地区之间的物流;3.25 第三方物流third-part logistics TPL由供方与需方以外的物流企业提供物流服务的业务模式;3.26 定制物流customized logistics根据用户的特定要求而为其专门设计的物流服务模式;3.27 虚拟物流virtual logistics以计算机网络技术进行物流运作与管理,实现企业间物流资源共享和优化配置的物流方式; 3.28 增值物流服务value-added logistics service在完成物流基本功能基础上,根据客户需要提供的各种延伸业务活动;3.29 供应链supply chain生产及流通过程中,涉及将产品或服务提供给最终用户活动的上游与下游企业,所形成的网链结构;3.30 条码bar code由一组规则排列的条、空及字符组成的,用以表示一定信息的代码;同义词:条码符号bar code symbolGB/T 4122.1-1996中4.173.31 电子数据交换electronic data interchange EDI通过电子方式,采用标准化的格式,利用计算机网络进行结构数据的传输和交换;3.32 有形消耗tangible loss可见或可测量出来的物理性损失、消耗;3.33 无形消耗intangible loss由于科学技术进步而引起的物品贬值;物流作业术语4.1 运输transportation用设备和工具,将物品从一地点向另一地点运送的物流活动;其中包括集货、分配、搬运、中转、装入、卸下、分散等一系列操作; GB/T 4122.1-1996中4.174.2 联合运输combined transport一次委托,由两家以上运输企业或用两种以上运输方式共同将某一批物品运送到目的的运输方式;4.3 直达运输through transport物品由发运地到接收地,中途不需要换装和在储存场所停滞的一种运输方式;4.4中转运输transfer transport物品由生产地运达最终使用地,中途经过一次以上落地并换装的一种运输方式;4.5 甩挂运输drop and pull transport用牵引车拖带挂车至目的地,将挂车甩下后,换上新的挂车运往另一个目的地的运输方式; 4.6 集装运输containerized transport使用集装器具或利用捆扎方法,把裸装物品、散粒物品、体积较小的成件物品,组合成为一定规格的集装单元进行的运输;4.7 集装箱运输container transport以集装箱为单元进行货物运输的一种货运方式; GB/T17271-1998中3.2.14.8 门到门door-to-door承运人在托运人的工厂或仓库整箱接货,负责运抵收货人的工厂或仓库整箱交货;GB/T 17271-1998中3.2.14.9 整箱货full container load FCL一个集装箱装满一个托运人同时也是一个收货人的工厂或仓库整箱交货;GB/T 17271-1998中3.2.4.24.10 拼箱货less than container load LCL一个集装箱装入多个托运人或多个收货人的货物;GB/T 17271-1998中3.2.4.34.11 储存storing保护、管理、贮藏物品; GB/T 4122.1-1996中4.24.12 保管storage对物品进行保存及对其数量、质量进行管理控制活动;4.13 物品储存article reserves储存起来以备急需的物品;有当年储存、长期储存、战略储备之分;4.14 库存inventory处于储存状态的物品;广义的库存还包括处于制造加工状态和运输状态的物品;4.15 经常库存cycle stock在正常的经营环境下,企业为满足日常需要而建立的库存;4.16 安全库存safety stick为了防止由于不确定性因素如大量突发性订货、交货期突然延期等而准备的缓冲库存; 4.17 库存周期inventory cycle time在一定范围内,库存物品从入库到出库的平均时间;4.18 前置期或提前期lead time从发出订货单到货物的时间间隔;4.19 订货处理周期order cycle time从收到订货单到将所订货物发运出去的时间间隔;4.20 货垛goods stack为了便于保管和装卸、运输,按一定要求分门别类堆放在一起的一批物品;4.21 堆码stacking将物品整齐、规则地摆放成货垛的作业;4.22 搬运handing/carrying在同一场所内,对物品进行水平移动为主的物流作业;4.23 装卸loading and unloading物品在指定地点以人力或机械装入运输设备或卸下; GB/T 4122.1-1996中4.54.24 单元装卸unit loading and unloading用托盘、容器或包装物见小件或散装物品集成一定质量或体积的组合件,以便利用机械进行作业的装卸方式;4.25 包装package/packaging为在流通过程中保护产品、方便储运、促进销售,按一定技术方面而采用的容器、材料及辅助物等的总体名称;也指为了达到上述目的而采用容器、材料和辅助物的过程中施加一定技术方法等的操作活动; GB/T 4122.1-1996中2.14.26 销售包装sales package又称内包装,是直接接触商品进入零售网点和消费者或用户直接见面的包装;4.27 定牌包装packing of nominated brand买方要求卖方在出口商品/包装上使用买方指定的牌名或商标的做法;4.28 中性包装neutral packing在出口商品及其内外包装上都不注明生产国别的包装;4.29 运输包装transport package以满足运输贮存要求为主要目的的包装;它具有保障产品的安全,方便储运装卸,加速交接、点验等作用; GB/T 4122.1-1996中2.54.30 托盘包装palletizing以托盘为承载物,将包装件或产品堆码在托盘上,通过捆扎、裹包或胶粘等方法加以固定,形成一个搬运单元,以便用机械设备搬运; GB/T 4122.1-1996中2.174.31 集装化containerization用集装器具或采用捆扎方法,把物品组成标准规格的单元货件,以加快装卸、搬运、储存、运输等物流活动;4.32 散装化containerization用专门机械、器具进行运输、装卸的散装物品在某个物流范围内,不用任何包装,长期固定采用吸扬、抓斗等机械、器具进行装卸、运输、储存的作业方式;4.33 直接换装cross docking物品在物流环节中,不经过中间仓库或站点,直接从一个运输工具换载到另一个运输工具的物流衔接方式;4.34 配送distribution在经济合理区域范围内,根据用户要求,对物品进行拣选、加工、包装、分割、组配等作业,并按时送达指定地点的物流活动;4.35 共同配送joint distribution由多个企业联合组织实施的配送活动;4.36 配送中心distribution center从事配送业务的物流场所或组织,应基本符合下列要求:a 主要为特定的用户服务;b 配送功能健全;c 完善的信息网络;d 辐射范围小;e 多品种、小批量;f 以配送为主,储存为辅;4.37 分拣sorting将物品按品种、出入库先后顺序进行分门别类推放的作业;4.38 拣选order picking按订单或出库单的要求,从储存场所选出物品,并放置指定地点的作业;4.39 集货goods collection将分散的或小批量的物品集中起来,以便进行运输、配送的作业;4.40 组配assembly配送前,根据物品的流量、流向及运输工具的载质量和容积,组织安排物品装载的作业; 4.41 流通加工distribution processing物品在从生产地到使用地的过程中,根据需要施加包装、分割、计量、分拣、刷标志、拴标签、组装等简单作业的总称;4.42 冷链cold chain为保持新鲜食品及冷冻食品等的品质,使其在从生产到消费的过程中,始终处于低温状态的配有专门设备的物流网络;4.43 检验inspection根据合同或标准,对标的物品的品质、数量、包装等进行检查、验收的总称;物流技术装备与设施术语5.1 仓库warehouse保管、储存物品的建筑物和场所的总称;5.2 库房storehouse有屋顶和围护结构,供储存各种物品的封闭式建筑物;5.3 自动化仓库automatic warehouse由电子计算机进行管理和的控制,不需人工搬运作业,而实现收发作业的仓库;5.4立体仓库stereoscopic warehouse采用高层货架配以货箱或托盘储存货物,用巷道队垛起重机及其他机械进行作业的仓库; 5.5 虚拟仓库virtual warehouse建立在计算机和网络通讯技术基础上,进行物品储存、保管和远程控制的物流设施;可实现不同状态、空间、时间、货主的有效调度和统一管理; 5.6保税仓库boned warehouse经海关批准,在海关监管下,专供存放未办理关税手续而入境或过境货物的场所;5.7 出口监管仓库export supervised warehouse经海关批准,在海关监管下,存放已按规定领取了出口货物许可证或批件,已对外买断结汇并向海关办完全部出口海关手续的货物的专用仓库;5.8 海关监管货物cargo under custom's supervision在海关批准范围内接受海关查验的进出口、过境、转运、通关货物,以及保税货物和其他尚未办结海关手续的进出境货物;5.9 冷藏区chill space仓库的一个区域,其温度保持在0'C~10.C范围内;5.10 冷冻区freeze space仓库的一个区域,其温度保持在0'C以下;5.11 控湿储存区humidity controlled space仓库内配有湿度调制设备,使内部湿度可调的库房区域;5.12 温度可控区temperature controlled space温度可根据需要调整在一定范围内的库房区域;5.13 收货区receiving space到库物品入库前核对检查及进库准备的地区;5.14 发货区shipping space物品集中待运地区;5.15 料棚goods shed供储存某些物品的简易建筑物,一般没有或只有部分围壁;5.16 货场goods yard用于存放某些物品的露天场地;5.17 货架goods shelf用支架、隔板或托架组成的立体储存货物的设施;5.18 托盘pallet用于集装、堆放、搬运和运输的放置作为单元负荷的货物和制品的水平平台装置;GB/T 4122.1-1996中4.275.19 叉车fork lift truck具有各种叉具,能够对货物进行升降和移动以及装卸作业的搬运车辆;5.20 输送机conveyor对物品进行连续运送的机械;5.21 自动导引车automatic guided vehicle AGV能够自动行驶到指定地点的无轨搬运车辆;5.22 箱式车box car除具备普通车的一切机械性能外,还必须具备全封闭的箱式车身和便于装卸作业的车门; 5.23 集装箱container是一种运输设备,应满足下列要求:a 具有足够的强度,可长期反复使用;b 适于一种或多种运输方式运送,途中转运时,箱内货物不需换装;c 具有快速装卸和搬运的装置,特别便于从一种运输方式转移到另一种运输方式;d 便于货物装满和卸空;e 具有1立方米及以上的容积;集装箱这一术语不包括车辆和一般包装; GB/T 1992-1985中1.15.24 换算箱twenty-feet equivalent unit TEU又称标准箱;Twenty-feet equivalent unit TEU以20英尺集装箱作为换算单位;GB/T 17271-1998中3.2.4.85.25 特种货物集装箱specific cargo container用以装运特种物品用的集装箱; GB/T 4122.1-1996中1.15.26 全集装箱船full container ship舱内设有固定式或活动式的格栅结构,舱盖上和甲板上设置固定集装箱的系紧装置, 便于集装箱左翼及定位的船舶;GB/T GB/T17271-1998中3.1.1.15.27 铁路集装箱场railway container yard进行集装箱承运、交付、装卸、堆存、装拆箱、门到门作业,组织集装箱专列等作业的场所;GB/T GB/T17271-1998中3.1.3.65.28 公路集装箱中转站inland container depot具有集装箱中转运输与门到门运输和集装箱货物的拆箱、装箱、仓储和接取、送达、装卸、堆存的场所;GB/T GB/T17271-1998中3.1.3.95.29 集装箱货运站container freight station CFS拼箱货物拆箱、装箱、办理交接的场所;5.30 集装箱码头container terminal专供停靠集装箱船、装卸集装箱用的码头;GB/T GB/T 17271-1998中3.1.2.25.31 国际铁路联运international through railway transport使用一份统一的国际铁路联运票据,由跨国铁路承运人办理两国或两国以上铁路的全程运输,并承担运输责任的一种连贯运输方式;5.32 国际多式联运international multimodal transport按照多式联运合同,以至少两种不同的运输方式,由多式联运经营人将货物从一国境内的接管地点运至另一国境内指定交付地点的货物运输;5.33 大陆桥运输land bridge transport用横贯大陆的铁路或公路作为中间桥梁,将大陆两端的海洋运输连接起来的连贯运输方式; 5.34 班轮运输liner transport在固定的航线上,以既定的港口顺序,按照事先公布的船期表航行的水上运输方式;5.35 租船运输shipping by chartering根据协议,租船人向船舶所有人租凭船舶用于货物运输,并按商定运价,向船舶所有人支付运费或租金的运输方式;5.36 船务代理shipping agency根据承运人的委托,代办与船舶进出有关的业务活动;5.37 国际货运代理international freight forwarding agent接受进出口货物收货人、发货人的委托,以委托人或自己的名义,为委托人办理国际货物运输及相关业务,并收取劳务报酬的经济组织;5.38 理货tally货物装卸中,对照货物运输票据进行的理点数、计量、检查残缺、指导装舱积载、核对标记、检查包装、分票、分标志和现场签证等工作;5.39 国际货物运输保险international transportation cargo insurance在国际贸易中,以国际运输中的货物为保险标的的保险,以对自然灾害和意外事故所造成的财产损失获得补偿;5.40 报关customs declaration由进出口货物的收发货人或其代理人向海关办理进出境手续的全过程;5.41 报关行customs broker专门代办进出境保管业务的企业;5.42 进出口商品检验commodity inspection确定进出口商品的品质、规格、重量、数量、包装、安全性能、卫生方面的指标及装运技术和装运条件等项目实施检验和鉴定,以确定其是否与贸易合同、有关标准规定一致,是否符合进出口国有关法律和行政法规的规定;简称"商检";物流管理术语6.1 物流战略logistics strategy为寻求物流的可持续发展,就物流发展目标以及达成目标的途径与手段而制定的长远性、全局性的规划与谋略;6.2 物流战略管理logistics strategy management物流组织根据已制定的物流战略,付诸实施和控制的过程;6.3 仓库管理warehouse management对库存物品和仓库设施及其布局等进行规划、控制的活动;6.4仓库布局warehouse layout在一定区域或库区内,对仓库的数量、规模、地理位置和仓库设施、道路等各要素进行科学规划和总体设计;6.5 库存控制inventory control在保障供应的前提下,使库存物品的数量最少进行的有效管理的技术经济措施;6.6 经济订货批量economic order quantity EOQ通过平衡采购进货成本和保管仓储成本核算,以实现总库存成本最低的最佳订货量;6.7定量订货方式fixed-quantity system FQS当库存量下降到预定的最低的库存数量订货点时,按规定数量一般以经济订货批量为标准进行订货补充的一种库存管理方式;6.8 定期订货方式fixed-quantity system FIS按预先确定的订货间隔期间进行订货补充的一种库存管理方式;6.9 ABC分类管理ABC classification将库存物品按品种和占用资金的多少分为特别重要的库存A类、一般重要的库存B类和不重要的库存C类三个等级,然后针对不同等级分别进行管理与控制;6.10 电子订货系统Electronic order system EOS不同组织间利用通讯网络和终端设备以在线联结方式进行订货作业与订货信息交换的体系; 6.11 准时制just in time JIT在精确测定生产各工艺环节作业效率的前提下按订单准确的计划,消除一切无效作业与浪费为目标的一种管理模式;6.12 准时制物流just-in-time logistics一种建立在JIT管理理念基础上的现代物流方式;6.13 零库存技术zero-inventory logistics在生产与流通领域按照JIT组织物资供应,使整个过程库存最小化的技术的总称;6.14 物流成本管理logistics cost control对物流相关费用进行的计划、协调与控制;6.15 物料需要计划material requirements planning MRP一种工业制造企业内的物资计划管理模式;根据产品结构各层次物品的从属和数量关系,以每个物品为计划对象,以完工日期为时间基准倒排计划,按提前期长短区别各个物品下达计划时间的先后顺序;6.16 制造资源计划manufacturing resource planning MRP II从整体最优的角度出发,运用科学的方法,对企业的各种制造资源和企业生产经营各环节实行合理有效地计划、组织、控制和协调,达到既能连续均衡生产,又能最大限度地降低各种物品的库存量,进而提高企业经济效益的管理方法;6.17 配送需要计划distribution requirements planning DRP一种既保证有效地满足市场需要,又使得物流资源配置费用最省的计划方法,是MRP原理与方法在物品配送中的运用;6.18 配送资源计划distribution resource planning DRP II一种企业内物品配送计划系统管理模式;是在DRP的基础上提高各环节的物流能力,达到系统优化运行的目的;6.19 物流资源计划logistics resource planning LRP以物流为基础手段,打破生产与流通界限,集成制造资源计划、分销需要计划以及功能计划而形成的物资资源优化配置方法;6.20 企业资源计划enterprise resource planning ERP在MRP II 的基础上,通过反馈的物流和反馈的信息流、资金流,把客户需要和企业内部的生产经营活动以及供应商的资源整合在一起,体现完全按用户需要进行经营管理的一种全新的管理方法;6.21 供应链管理supply chain management SCM利用计算机网络技术全面规划供应链中的商流、物流、信息流、资金流等,并进行计划、组织、协调与控制;6.22 快速反映Quick response QR物流企业面对多品种、小批量的买方市场,不是储备了"产品",而是准备了各种"要素",在用户提出要求时,能以最快速度抽取"要素",及时"组装",提供所需服务或产品;6.23 有效客户反映efficient customer responseECR以满足顾客要求和最大限度降低物流过程费用为原则,能及时做出准确反应,使提供的物品供应或服务流程最佳化的一种供应链管理战略;6.24 连续库存补充计划continuous replenishment program CRP利用及时准确的销售时点信息确定已销售的商品数量,根据零售商或批发商的库存信息和预先规定的库存补充程序确定发货补充数量和配送时间的计划方法;6.25 计算机付诸订货系统computer assisted ordering CAO基于库存和客户需要信息,利用计算机进行自动订货管理的系统;6.26 供应商管理库存vendor managed inventory VMI供应商等上游企业基于其下游客户的生产经营、库存信息,对下游客户的库存进行管理与控制;6.27 业务外包outsourcing企业为了获得不单纯利用不、内部资源更多的竞争优势,将其非核心业务交由合作企业完成; 资料来源:http://vip.6to23/our56/study/html/tjzl/wlbz/wlglsy.htm。
DS2208数字扫描器产品参考指南说明书
-05 Rev. A
6/2018
Rev. B Software Updates Added: - New Feedback email address. - Grid Matrix parameters - Febraban parameter - USB HID POS (formerly known as Microsoft UWP USB) - Product ID (PID) Type - Product ID (PID) Value - ECLevel
-06 Rev. A
10/2018 - Added Grid Matrix sample bar code. - Moved 123Scan chapter.
-07 Rev. A
11/2019
Added: - SITA and ARINC parameters. - IBM-485 Specification Version.
No part of this publication may be reproduced or used in any form, or by any electrical or mechanical means, without permission in writing from Zebra. This includes electronic or mechanical means, such as photocopying, recording, or information storage and retrieval systems. The material in this manual is subject to change without notice.
TD信息元素详解
信息元素功能性定义作者:李欣目录目录 (1)信息元素功能性定义 (11)1 核心网信息元素 (11)1.1 CN Information elements (11)1.2 CN Domain System Information (11)1.3 CN Information info (11)1.4 IMEI (11)1.5 IMSI (GSM-MAP) (11)1.6 Intra Domain NAS Node Selector (11)1.7 Location Area Identification (12)1.8 NAS message (12)1.9 NAS system information (GSM-MAP) (12)1.10 Paging record type identifier (12)1.11 PLMN identity (12)1.12 PLMN Type (12)1.13 P-TMSI (GSM-MAP) (12)1.14 RAB identity (12)1.15 Routing Area Code (12)1.16 Routing Area Identification (13)1.17 TMSI (GSM-MAP) (13)2 UTRAN 移动信息元素 (13)2.1 Cell Access Restriction (13)2.2 Cell identity (13)2.3 Cell selection and re-selection info for SIB3/4 (13)2.4 Cell selection and re-selection info for SIB11/12 (13)2.5 Mapping Info (14)2.6 URA identity (14)3 UE 信息元素 (14)3.1 Activation time (14)3.2 Capability Update Requirement (14)3.3 Cell update cause (15)3.4 Ciphering Algorithm (15)3.5 Ciphering mode info (15)3.6 CN domain specific DRX cycle length coefficient (15)3.7 CPCH Parameters (15)3.8 C-RNTI (15)3.9 DRAC system information (15)3.10 Void (16)3.11 Establishment cause (16)3.12 Expiration Time Factor (16)3.13 Failure cause (16)3.14 Failure cause and error information (16)3.15 Initial UE identity (16)3.16 Integrity check info (16)3.17 Integrity protection activation info (17)3.18 Integrity protection Algorithm (17)3.19 Integrity protection mode info (17)3.20 Maximum bit rate (17)3.21 Measurement capability (17)3.22 Paging cause (17)3.23 Paging record (17)3.24 PDCP capability (17)3.25 Physical channel capability (18)3.26 Protocol error cause (18)3.27 Protocol error indicator (18)3.28 RB timer indicator (18)3.29 Redirection info (18)3.30 Re-establishment timer (18)3.31 Rejection cause (18)3.32 Release cause (18)3.33 RF capability FDD (19)3.34 RLC capability (19)3.35 RLC re-establish indicator (19)3.36 RRC transaction identifier (19)3.37 Security capability (19)3.38 START (19)3.39 Transmission probability (19)3.40 Transport channel capability (20)3.41 UE multi-mode/multi-RAT capability (20)3.42 UE radio access capability (20)3.43 UE Timers and Constants in connected mode (21)3.44 UE Timers and Constants in idle mode (21)3.45 UE positioning capability (21)3.46 URA update cause (21)3.47 U-RNTI (21)3.48 U-RNTI Short (21)3.49 UTRAN DRX cycle length coefficient (21)3.50 Wait time (21)3.51 UE Specific Behavior Information 1 idle (21)3.52 UE Specific Behavior Information 1 interRAT (22)4 无线承载信息元素 (22)4.0 Default configuration identity (22)4.1 Downlink RLC STATUS info (22)4.2 PDCP info (22)4.3 PDCP SN info (22)4.4 Polling info (22)4.5 Predefined configuration identity (23)4.6 Predefined configuration value tag (23)4.7 Predefined RB configuration (23)4.8 RAB info (23)4.9 RAB info Post (23)4.10 RAB information for setup (23)4.11 RAB information to reconfigure (24)4.12 NAS Synchronization indicator (24)4.13 RB activation time info (24)4.14 RB COUNT-C MSB information (24)4.15 RB COUNT-C information (24)4.16 RB identity (24)4.17 RB information to be affected (24)4.18 RB information to reconfigure (25)4.19 RB information to release (25)4.20 RB information to setup (25)4.21 RB mapping info (25)4.22 RB with PDCP information (25)4.23 RLC info (25)4.24 Signaling RB information to setup (26)4.25 Transmission RLC Discard (26)5 传输信道信息元素 (26)5.1 Added or Reconfigured DL TrCH information (26)5.2 Added or Reconfigured UL TrCH information (27)5.3 CPCH set ID (27)5.4 Deleted DL TrCH information (27)5.5 Deleted UL TrCH information (27)5.6 DL Transport channel information common for all transport channels (27)5.7 DRAC Static Information (27)5.8 Power Offset Information (28)5.9 Predefined TrCH configuration (28)5.10 Quality Target (28)5.11 Semi-static Transport Format Information (28)5.12 TFCI Field 2 Information (28)5.13 TFCS Explicit Configuration (28)5.14 TFCS Information for DSCH (TFCI range method) (29)5.15 TFCS Reconfiguration/Addition Information (29)5.16 TFCS Removal Information (29)5.17 Void (29)5.18 Transport channel identity (29)5.19 Transport Format Combination (TFC) (29)5.20 Transport Format Combination Set (29)5.21 Transport Format Combination Set Identity (29)5.22 Transport Format Combination Subset (29)5.23 Transport Format Set (29)5.24 UL Transport channel information common for all transport channels (30)6 物理信道信息元素 (30)6.1 AC-to-ASC mapping (30)6.2 AICH Info (30)6.3 AICH Power offset (30)6.4 Allocation period info (30)6.5 Alpha (30)6.6 ASC Setting (30)6.7 Void (31)6.8 CCTrCH power control info (31)6.9 Cell parameters Id (31)6.10 Common timeslot info (31)6.11 Constant value (31)6.12 CPCH persistence levels (31)6.13 CPCH set info (31)6.14 CPCH Status Indication mode (31)6.15 CSICH Power offset (32)6.16 Default DPCH Offset Value (32)6.17 Downlink channelisation codes (32)6.18 Downlink DPCH info common for all RL (32)6.19 Downlink DPCH info common for all RL Post (32)6.20 Downlink DPCH info common for all RL Pre (32)6.21 Downlink DPCH info for each RL (32)6.22 Downlink DPCH info for each RL Post (33)6.23 Downlink DPCH power control information (33)6.24 Downlink information common for all radio links (33)6.25 Downlink information common for all radio links Post (33)6.26 Downlink information common for all radio links Pre (33)6.27 Downlink information for each radio link (33)6.28 Downlink information for each radio link Post (33)6.29 Void (33)6.30 Downlink PDSCH information (33)6.31 Downlink rate matching restriction information (34)6.32 Downlink Timeslots and Codes (34)6.33 DPCH compressed mode info (34)6.34 DPCH Compressed Mode Status Info (34)6.35 Dynamic persistence level (34)6.36 Frequency info (34)6.37 Individual timeslot info (35)6.38 Individual Timeslot interference (35)6.39 Maximum allowed UL TX power (35)6.40 Void (35)6.41 Midamble shift and burst type (35)6.42 PDSCH Capacity Allocation info (35)6.43 PDSCH code mapping (36)6.44 PDSCH info (36)6.45 PDSCH Power Control info (36)6.46 PDSCH system information (36)6.47 PDSCH with SHO DCH Info (36)6.48 Persistence scaling factors (36)6.49 PICH Info (36)6.50 PICH Power offset (37)6.51 PRACH Channelisation Code List (37)6.52 PRACH info (for RACH) (37)6.53 PRACH partitioning (37)6.54 PRACH power offset (37)6.55 PRACH system information list (37)6.56 Predefined PhyCH configuration (38)6.57 Primary CCPCH info (38)6.58 Primary CCPCH info post (38)6.59 Primary CCPCH TX Power (38)6.60 Primary CPICH info (38)6.61 Primary CPICH Tx power (38)6.62 Primary CPICH usage for channel estimation (38)6.63 PUSCH info (38)6.64 PUSCH Capacity Allocation info (38)6.65 PUSCH power control info (39)6.66 PUSCH system information (39)6.67 RACH transmission parameters (39)6.68 Radio link addition information (39)6.69 Radio link removal information (39)6.70 SCCPCH Information for FACH (39)6.71 Secondary CCPCH info (39)6.72 Secondary CCPCH system information (40)6.73 Secondary CPICH info (40)6.74 Secondary scrambling code (40)6.75 SFN Time info (40)6.76 SSDT cell identity (40)6.77 SSDT information (40)6.78 STTD indicator (40)6.79 TDD open loop power control (41)6.80 TFC Control duration (41)6.81 TFCI Combining Indicator (41)6.82 TGPSI (41)6.83 Time info (41)6.84 Timeslot number (41)6.85 TPC combination index (41)6.86 TSTD indicator (41)6.87 TX Diversity Mode (41)6.88 Uplink DPCH info (41)6.89 Uplink DPCH info Post (42)6.90 Uplink DPCH info Pre (42)6.91 Uplink DPCH power control info (42)6.92 Uplink DPCH power control info Post (42)6.93 Uplink DPCH power control info Pre (42)6.94 Uplink Timeslots and Codes (42)6.95 Uplink Timing Advance (42)6.96 Uplink Timing Advance Control (43)7 测量信息元素 (43)7.1 Additional measurements list (43)7.2 Cell info (43)7.3 Cell measured results (43)7.4 Cell measurement event results (44)7.5 Cell reporting quantities (44)7.6 Cell synchronization information (44)7.7 Event results (44)7.8 FACH measurement occasion info (45)7.9 Filter coefficient (45)7.10 HCS Cell re-selection information (45)7.11 HCS neighboring cell information (45)7.12 HCS Serving cell information (45)7.13 Inter-frequency cell info list (46)7.14 Inter-frequency event identity (46)7.15 Inter-frequency measured results list (46)7.16 Inter-frequency measurement (46)7.17 Inter-frequency measurement event results (47)7.18 Inter-frequency measurement quantity (47)7.19 Inter-frequency measurement reporting criteria (47)7.20 Inter-frequency measurement system information (47)7.21 Inter-frequency reporting quantity (47)7.22 Inter-frequency SET UPDATE (48)7.23 Inter-RAT cell info list (48)7.24 Inter-RAT event identity (48)7.25 Inter-RAT info (48)7.26 Inter-RAT measured results list (48)7.27 Inter-RAT measurement (49)7.28 Inter-RAT measurement event results (49)7.29 Inter-RAT measurement quantity (49)7.30 Inter-RAT measurement reporting criteria (49)7.31 Inter-RAT measurement system information (50)7.32 Inter-RAT reporting quantity (50)7.33 Intra-frequency cell info list (50)7.34 Intra-frequency event identity (50)7.35 Intra-frequency measured results list (50)7.36 Intra-frequency measurement (50)7.37 Intra-frequency measurement event results (51)7.38 Intra-frequency measurement quantity (51)7.39 Intra-frequency measurement reporting criteria (51)7.40 Intra-frequency measurement system information (51)7.41 Intra-frequency reporting quantity (52)7.42 Intra-frequency reporting quantity for RACH reporting (52)7.43 Maximum number of reported cells on RACH (52)7.44 Measured results (52)7.45 Measured results on RACH (52)7.46 Measurement Command (52)7.47 Measurement control system information (53)7.48 Measurement Identity (53)7.49 Measurement reporting mode (53)7.50 Measurement Type (53)7.51 Measurement validity (53)7.52 Observed time difference to GSM cell (53)7.53 Periodical reporting criteria (53)7.54 Primary CCPCH RSCP info (54)7.55 Quality measured results list (54)7.56 Quality measurement (54)7.57 Quality measurement event results (54)7.58 Quality measurement reporting criteria (54)7.59 Quality reporting quantity (54)7.60 Reference time difference to cell (54)7.61 Reporting Cell Status (55)7.62 Reporting information for state CELL_DCH (55)7.63 SFN-SFN observed time difference (55)7.64 Time to trigger (55)7.65 Timeslot ISCP info (55)7.66 Traffic volume event identity (55)7.67 Traffic volume measured results list (55)7.68 Traffic volume measurement (55)7.69 Traffic volume measurement event results (56)7.70 Traffic volume measurement object (56)7.71 Traffic volume measurement quantity (56)7.72 Traffic volume measurement reporting criteria (56)7.73 Traffic volume measurement system information (56)7.74 Traffic volume reporting quantity (56)7.75 UE internal event identity (56)7.76 UE internal measured results (57)7.77 UE internal measurement (57)7.78 UE internal measurement event results (57)7.79 UE internal measurement quantity (57)7.80 UE internal measurement reporting criteria (57)7.81 Void (58)7.82 UE Internal reporting quantity (58)7.83 UE Rx-Tx time difference type 1 (58)7.84 UE Rx-Tx time difference type 2 (58)7.85 UE Transmitted Power info (58)7.86 UE positioning Ciphering info (58)7.87 UE positioning Error (58)7.88 UE positioning GPS acquisition assistance (59)7.89 UE positioning GPS almanac (59)7.90 UE positioning GPS assistance data (59)7.91 UE positioning GPS DGPS corrections (59)7.92 UE positioning GPS ionospheric model (59)7.93 UE positioning GPS measured results (59)7.94 UE positioning GPS navigation model (60)7.95 UE positioning GPS real-time integrity (60)7.96 UE positioning GPS reference time (60)7.97 UE positioning GPS UTC model (61)7.98 UE positioning IPDL parameters (61)7.99 UE positioning measured results (61)7.100 UE positioning measurement (61)7.101 UE positioning measurement event results (61)7.102 Void (62)7.103 UE positioning OTDOA assistance data for UE-assisted (62)7.104 Void (62)7.105 UE positioning OTDOA measured results (62)7.106 UE positioning OTDOA neighbor cell info (62)7.107 UE positioning OTDOA quality (63)7.108 UE positioning OTDOA reference cell info (63)7.109 UE positioning position estimate info (64)7.110 UE positioning reporting criteria (64)7.111 UE positioning reporting quantity (64)7.112 T ADV info (65)8 其它信息元素 (65)8.1 BCCH modification info (65)8.2 BSIC (65)8.3 CBS DRX Level 1 information (65)8.4 Cell Value tag (65)8.5 Inter-RAT change failure (65)8.6 Inter-RAT handover failure (66)8.7 Inter-RAT UE radio access capability (66)8.8 Void (66)8.9 MIB Value tag (66)8.10 PLMN Value tag (66)8.11 Predefined configuration identity and value tag (66)8.12 Protocol error information (66)8.13 References to other system information blocks (66)8.14 References to other system information blocks and scheduling blocks (67)8.15 Rplmn information (67)8.16 Scheduling information (67)8.17 SEG COUNT (67)8.18 Segment index (67)8.19 SIB data fixed (67)8.20 SIB data variable (67)8.21 SIB type (67)8.22 SIB type SIBs only (67)9 ANSI-41 Information elements (68)10 Multiplicity values and type constraint values (68)信息元素功能性定义消息是由多个信息元素组合而成,信息元素根据其功能的不同划分为:核心网域信息元素、UTRAN 移动信息元素、UE 信息元素、无线承载信息元素、传输信道信息元素、物理信道信息元素和测量信息元素。
Parallel and Distributed Computing and Systems
Proceedings of the IASTED International ConferenceParallel and Distributed Computing and SystemsNovember3-6,1999,MIT,Boston,USAParallel Refinement of Unstructured MeshesJos´e G.Casta˜n os and John E.SavageDepartment of Computer ScienceBrown UniversityE-mail:jgc,jes@AbstractIn this paper we describe a parallel-refinement al-gorithm for unstructuredfinite element meshes based on the longest-edge bisection of triangles and tetrahedrons. This algorithm is implemented in P ARED,a system that supports the parallel adaptive solution of PDEs.We dis-cuss the design of such an algorithm for distributed mem-ory machines including the problem of propagating refine-ment across processor boundaries to obtain meshes that are conforming and non-degenerate.We also demonstrate that the meshes obtained by this algorithm are equivalent to the ones obtained using the serial longest-edge refine-ment method.Wefinally report on the performance of this refinement algorithm on a network of workstations.Keywords:mesh refinement,unstructured meshes,finite element methods,adaptation.1.IntroductionThefinite element method(FEM)is a powerful and successful technique for the numerical solution of partial differential equations.When applied to problems that ex-hibit highly localized or moving physical phenomena,such as occurs on the study of turbulence influidflows,it is de-sirable to compute their solutions adaptively.In such cases, adaptive computation has the potential to significantly im-prove the quality of the numerical simulations by focusing the available computational resources on regions of high relative error.Unfortunately,the complexity of algorithms and soft-ware for mesh adaptation in a parallel or distributed en-vironment is significantly greater than that it is for non-adaptive computations.Because a portion of the given mesh and its corresponding equations and unknowns is as-signed to each processor,the refinement(coarsening)of a mesh element might cause the refinement(coarsening)of adjacent elements some of which might be in neighboring processors.To maintain approximately the same number of elements and vertices on every processor a mesh must be dynamically repartitioned after it is refined and portions of the mesh migrated between processors to balance the work.In this paper we discuss a method for the paral-lel refinement of two-and three-dimensional unstructured meshes.Our refinement method is based on Rivara’s serial bisection algorithm[1,2,3]in which a triangle or tetrahe-dron is bisected by its longest edge.Alternative efforts to parallelize this algorithm for two-dimensional meshes by Jones and Plassman[4]use randomized heuristics to refine adjacent elements located in different processors.The parallel mesh refinement algorithm discussed in this paper has been implemented as part of P ARED[5,6,7], an object oriented system for the parallel adaptive solu-tion of partial differential equations that we have devel-oped.P ARED provides a variety of solvers,handles selec-tive mesh refinement and coarsening,mesh repartitioning for load balancing,and interprocessor mesh migration.2.Adaptive Mesh RefinementIn thefinite element method a given domain is di-vided into a set of non-overlapping elements such as tri-angles or quadrilaterals in2D and tetrahedrons or hexahe-drons in3D.The set of elements and its as-sociated vertices form a mesh.With theaddition of boundary conditions,a set of linear equations is then constructed and solved.In this paper we concentrate on the refinement of conforming unstructured meshes com-posed of triangles or tetrahedrons.On unstructured meshes, a vertex can have a varying number of elements adjacent to it.Unstructured meshes are well suited to modeling do-mains that have complex geometry.A mesh is said to be conforming if the triangles and tetrahedrons intersect only at their shared vertices,edges or faces.The FEM can also be applied to non-conforming meshes,but conformality is a property that greatly simplifies the method.It is also as-sumed to be a requirement in this paper.The rate of convergence and quality of the solutions provided by the FEM depends heavily on the number,size and shape of the mesh elements.The condition number(a)(b)(c)Figure1:The refinement of the mesh in using a nested refinement algorithm creates a forest of trees as shown in and.The dotted lines identify the leaf triangles.of the matrices used in the FEM and the approximation error are related to the minimum and maximum angle of all the elements in the mesh[8].In three dimensions,the solid angle of all tetrahedrons and their ratio of the radius of the circumsphere to the inscribed sphere(which implies a bounded minimum angle)are usually used as measures of the quality of the mesh[9,10].A mesh is non-degenerate if its interior angles are never too small or too large.For a given shape,the approximation error increases with ele-ment size(),which is usually measured by the length of the longest edge of an element.The goal of adaptive computation is to optimize the computational resources used in the simulation.This goal can be achieved by refining a mesh to increase its resolution on regions of high relative error in static problems or by re-fining and coarsening the mesh to follow physical anoma-lies in transient problems[11].The adaptation of the mesh can be performed by changing the order of the polynomi-als used in the approximation(-refinement),by modifying the structure of the mesh(-refinement),or a combination of both(-refinement).Although it is possible to replace an old mesh with a new one with smaller elements,most -refinement algorithms divide each element in a selected set of elements from the current mesh into two or more nested subelements.In P ARED,when an element is refined,it does not get destroyed.Instead,the refined element inserts itself into a tree,where the root of each tree is an element in the initial mesh and the leaves of the trees are the unrefined elements as illustrated in Figure1.Therefore,the refined mesh forms a forest of refinement trees.These trees are used in many of our algorithms.Error estimates are used to determine regions where adaptation is necessary.These estimates are obtained from previously computed solutions of the system of equations. After adaptation imbalances may result in the work as-signed to processors in a parallel or distributed environ-ment.Efficient use of resources may require that elements and vertices be reassigned to processors at runtime.There-fore,any such system for the parallel adaptive solution of PDEs must integrate subsystems for solving equations,adapting a mesh,finding a good assignment of work to processors,migrating portions of a mesh according to anew assignment,and handling interprocessor communica-tion efficiently.3.P ARED:An OverviewP ARED is a system of the kind described in the lastparagraph.It provides a number of standard iterativesolvers such as Conjugate Gradient and GMRES and pre-conditioned versions thereof.It also provides both-and -refinement of meshes,algorithms for adaptation,graph repartitioning using standard techniques[12]and our ownParallel Nested Repartitioning(PNR)[7,13],and work mi-gration.P ARED runs on distributed memory parallel comput-ers such as the IBM SP-2and networks of workstations.These machines consist of coarse-grained nodes connectedthrough a high to moderate latency network.Each nodecannot directly address a memory location in another node. In P ARED nodes exchange messages using MPI(Message Passing Interface)[14,15,16].Because each message has a high startup cost,efficient message passing algorithms must minimize the number of messages delivered.Thus, it is better to send a few large messages rather than many small ones.This is a very important constraint and has a significant impact on the design of message passing algo-rithms.P ARED can be run interactively(so that the user canvisualize the changes in the mesh that results from meshadaptation,partitioning and migration)or without directintervention from the user.The user controls the systemthrough a GUI in a distinguished node called the coordina-tor,.This node collects information from all the other processors(such as its elements and vertices).This tool uses OpenGL[17]to permit the user to view3D meshes from different angles.Through the coordinator,the user can also give instructions to all processors such as specify-ing when and how to adapt the mesh or which strategy to use when repartitioning the mesh.In our computation,we assume that an initial coarse mesh is given and that it is loaded into the coordinator.The initial mesh can then be partitioned using one of a num-ber of serial graph partitioning algorithms and distributed between the processors.P ARED then starts the simulation. Based on some adaptation criterion[18],P ARED adapts the mesh using the algorithms explained in Section5.Af-ter the adaptation phase,P ARED determines if a workload imbalance exists due to increases and decreases in the num-ber of mesh elements on individual processors.If so,it invokes a procedure to decide how to repartition mesh el-ements between processors;and then moves the elements and vertices.We have found that PNR gives partitions with a quality comparable to those provided by standard meth-ods such as Recursive Spectral Bisection[19]but which(b)(a)Figure2:Mesh representation in a distributed memory ma-chine using remote references.handles much larger problems than can be handled by stan-dard methods.3.1.Object-Oriented Mesh RepresentationsIn P ARED every element of the mesh is assigned to a unique processor.V ertices are shared between two or more processors if they lie on a boundary between parti-tions.Each of these processors has a copy of the shared vertices and vertices refer to each other using remote ref-erences,a concept used in object-oriented programming. This is illustrated in Figure2on which the remote refer-ences(marked with dashed arrows)are used to maintain the consistency of multiple copies of the same vertex in differ-ent processors.Remote references are functionally similar to standard C pointers but they address objects in a different address space.A processor can use remote references to invoke meth-ods on objects located in a different processor.In this case, the method invocations and arguments destined to remote processors are marshalled into messages that contain the memory addresses of the remote objects.In the destina-tion processors these addresses are converted to pointers to objects of the corresponding type through which the meth-ods are invoked.Because the different nodes are inher-ently trusted and MPI guarantees reliable communication, P ARED does not incur the overhead traditionally associated with distributed object systems.Another idea commonly found in object oriented pro-gramming and which is used in P ARED is that of smart pointers.An object can be destroyed when there are no more references to it.In P ARED vertices are shared be-tween several elements and each vertex counts the number of elements referring to it.When an element is created, the reference count of its vertices is incremented.Simi-larly,when the element is destroyed,the reference count of its vertices is decremented.When the reference count of a vertex reaches zero,the vertex is no longer attached to any element located in the processor and can be destroyed.If a vertex is shared,then some other processor might have a re-mote reference to it.In that case,before a copy of a shared vertex is destroyed,it informs the copies in other processors to delete their references to itself.This procedure insures that the shared vertex can then be safely destroyed without leaving dangerous dangling pointers referring to it in other processors.Smart pointers and remote references provide a simple replication mechanism that is tightly integrated with our mesh data structures.In adaptive computation,the struc-ture of the mesh evolves during the computation.During the adaptation phase,elements and vertices are created and destroyed.They may also be assigned to a different pro-cessor to rebalance the work.As explained above,remote references and smart pointers greatly simplify the task of creating dynamic meshes.4.Adaptation Using the Longest Edge Bisec-tion AlgorithmMany-refinement techniques[20,21,22]have been proposed to serially refine triangular and tetrahedral meshes.One widely used method is the longest-edge bisec-tion algorithm proposed by Rivara[1,2].This is a recursive procedure(see Figure3)that in two dimensions splits each triangle from a selected set of triangles by adding an edge between the midpoint of its longest side to the opposite vertex.In the case that makes a neighboring triangle,,non-conforming,then is refined using the same algorithm.This may cause the refinement to prop-agate throughout the mesh.Nevertheless,this procedure is guaranteed to terminate because the edges it bisects in-crease in length.Building on the work of Rosenberg and Stenger[23]on bisection of triangles,Rivara[1,2]shows that this refinement procedure provably produces two di-mensional meshes in which the smallest angle of the re-fined mesh is no less than half of the smallest angle of the original mesh.The longest-edge bisection algorithm can be general-ized to three dimensions[3]where a tetrahedron is bisected into two tetrahedrons by inserting a triangle between the midpoint of its longest edge and the two vertices not in-cluded in this edge.The refinement propagates to neigh-boring tetrahedrons in a similar way.This procedure is also guaranteed to terminate,but unlike the two dimensional case,there is no known bound on the size of the small-est angle.Nevertheless,experiments conducted by Rivara [3]suggest that this method does not produce degenerate meshes.In two dimensions there are several variations on the algorithm.For example a triangle can initially be bisected by the longest edge,but then its children are bisected by the non-conforming edge,even if it is that is not their longest edge[1].In three dimensions,the bisection is always per-formed by the longest edge so that matching faces in neigh-boring tetrahedrons are always bisected by the same com-mon edge.Bisect()let,and be vertices of the trianglelet be the longest side of and let be the midpoint ofbisect by the edge,generating two new triangles andwhile is a non-conforming vertex dofind the non-conforming triangle adjacent to the edgeBisect()end whileFigure3:Longest edge(Rivara)bisection algorithm for triangular meshes.Because in P ARED refined elements are not destroyed in the refinement tree,the mesh can be coarsened by replac-ing all the children of an element by their parent.If a parent element is selected for coarsening,it is important that all the elements that are adjacent to the longest edge of are also selected for coarsening.If neighbors are located in different processors then only a simple message exchange is necessary.This algorithm generates conforming meshes: a vertex is removed only if all the elements that contain that vertex are all coarsened.It does not propagate like the re-finement algorithm and it is much simpler to implement in parallel.For this reason,in the rest of the paper we will focus on the refinement of meshes.5.Parallel Longest-Edge RefinementThe longest-edge bisection algorithm and many other mesh refinement algorithms that propagate the refinement to guarantee conformality of the mesh are not local.The refinement of one particular triangle or tetrahedron can propagate through the mesh and potentially cause changes in regions far removed from.If neighboring elements are located in different processors,it is necessary to prop-agate this refinement across processor boundaries to main-tain the conformality of the mesh.In our parallel longest edge bisection algorithm each processor iterates between a serial phase,in which there is no communication,and a parallel phase,in which each processor sends and receives messages from other proces-sors.In the serial phase,processor selects a setof its elements for refinement and refines them using the serial longest edge bisection algorithms outlined earlier. The refinement often creates shared vertices in the bound-ary between adjacent processors.To minimize the number of messages exchanged between and,delays the propagation of refinement to until has refined all the elements in.The serial phase terminates when has no more elements to refine.A processor informs an adjacent processor that some of its elements need to be refined by sending a mes-sage from to containing the non-conforming edges and the vertices to be inserted at their midpoint.Each edge is identified by its endpoints and and its remote ref-erences(see Figure4).If and are sharedvertices,(a)(c)(b)Figure4:In the parallel longest edge bisection algo-rithm some elements(shaded)are initially selected for re-finement.If the refinement creates a new(black)ver-tex on a processor boundary,the refinement propagates to neighbors.Finally the references are updated accord-ingly.then has a remote reference to copies of and lo-cated in processor.These references are included in the message,so that can identify the non-conforming edge and insert the new vertex.A similar strategy can be used when the edge is refined several times during the re-finement phase,but in this case,the vertex is not located at the midpoint of.Different processors can be in different phases during the refinement.For example,at any given time a processor can be refining some of its elements(serial phase)while neighboring processors have refined all their elements and are waiting for propagation messages(parallel phase)from adjacent processors.waits until it has no elements to refine before receiving a message from.For every non-conforming edge included in a message to,creates its shared copy of the midpoint(unless it already exists) and inserts the new non-conforming elements adjacent to into a new set of elements to be refined.The copy of in must also have a remote reference to the copy of in.For this reason,when propagates the refine-ment to it also includes in the message a reference to its copies of shared vertices.These steps are illustrated in Figure4.then enters the serial phase again,where the elements in are refined.(c)(b)(a)Figure5:Both processors select(shaded)mesh el-ements for refinement.The refinement propagates to a neighboring processor resulting in more elements be-ing refined.5.1.The Challenge of Refining in ParallelThe description of the parallel refinement algorithm is not complete because refinement propagation across pro-cessor boundaries can create two synchronization prob-lems.Thefirst problem,adaptation collision,occurs when two(or more)processors decide to refine adjacent elements (one in each processor)during the serial phase,creating two(or more)vertex copies over a shared edge,one in each processor.It is important that all copies refer to the same logical vertex because in a numerical simulation each ver-tex must include the contribution of all the elements around it(see Figure5).The second problem that arises,termination detection, is the determination that a refinement phase is complete. The serial refinement algorithm terminates when the pro-cessor has no more elements to refine.In the parallel ver-sion termination is a global decision that cannot be deter-mined by an individual processor and requires a collabora-tive effort of all the processors involved in the refinement. Although a processor may have adapted all of its mesh elements in,it cannot determine whether this condition holds for all other processors.For example,at any given time,no processor might have any more elements to re-fine.Nevertheless,the refinement cannot terminate because there might be some propagation messages in transit.The algorithm for detecting the termination of parallel refinement is based on Dijkstra’s general distributed termi-nation algorithm[24,25].A global termination condition is reached when no element is selected for refinement.Hence if is the set of all elements in the mesh currently marked for refinement,then the algorithmfinishes when.The termination detection procedure uses message ac-knowledgments.For every propagation message that receives,it maintains the identity of its source()and to which processors it propagated refinements.Each prop-agation message is acknowledged.acknowledges to after it has refined all the non-conforming elements created by’s message and has also received acknowledgments from all the processors to which it propagated refinements.A processor can be in two states:an inactive state is one in which has no elements to refine(it cannot send new propagation messages to other processors)but can re-ceive messages.If receives a propagation message from a neighboring processor,it moves from an inactive state to an active state,selects the elements for refinement as spec-ified in the message and proceeds to refine them.Let be the set of elements in needing refinement.A processor becomes inactive when:has received an acknowledgment for every propa-gation message it has sent.has acknowledged every propagation message it has received..Using this definition,a processor might have no more elements to refine()but it might still be in an active state waiting for acknowledgments from adjacent processors.When a processor becomes inactive,sends an acknowledgment to the processors whose propagation message caused to move from an inactive state to an active state.We assume that the refinement is started by the coordi-nator processor,.At this stage,is in the active state while all the processors are in the inactive state.ini-tiates the refinement by sending the appropriate messages to other processors.This message also specifies the adapta-tion criterion to use to select the elements for refinement in.When a processor receives a message from,it changes to an active state,selects some elements for refine-ment either explicitly or by using the specified adaptation criterion,and then refines them using the serial bisection algorithm,keeping track of the vertices created over shared edges as described earlier.When itfinishes refining its ele-ments,sends a message to each processor on whose shared edges created a shared vertex.then listens for messages.Only when has refined all the elements specified by and is not waiting for any acknowledgment message from other processors does it sends an acknowledgment to .Global termination is detected when the coordinator becomes inactive.When receives an acknowledgment from every processor this implies that no processor is re-fining an element and that no processor is waiting for an acknowledgment.Hence it is safe to terminate the refine-ment.then broadcasts this fact to all the other proces-sors.6.Properties of Meshes Refined in ParallelOur parallel refinement algorithm is guaranteed to ter-minate.In every serial phase the longest edge bisectionLet be a set of elements to be refinedwhile there is an element dobisect by its longest edgeinsert any non-conforming element intoend whileFigure6:General longest-edge bisection(GLB)algorithm.algorithm is used.In this algorithm the refinement prop-agates towards progressively longer edges and will even-tually reach the longest edge in each processor.Between processors the refinement also propagates towards longer edges.Global termination is detected by using the global termination detection procedure described in the previous section.The resulting mesh is conforming.Every time a new vertex is created over a shared edge,the refinement propagates to adjacent processors.Because every element is always bisected by its longest edge,for triangular meshes the results by Rosenberg and Stenger on the size of the min-imum angle of two-dimensional meshes also hold.It is not immediately obvious if the resulting meshes obtained by the serial and parallel longest edge bisection al-gorithms are the same or if different partitions of the mesh generate the same refined mesh.As we mentioned earlier, messages can arrive from different sources in different or-ders and elements may be selected for refinement in differ-ent sequences.We now show that the meshes that result from refining a set of elements from a given mesh using the serial and parallel algorithms described in Sections4and5,re-spectively,are the same.In this proof we use the general longest-edge bisection(GLB)algorithm outlined in Figure 6where the order in which elements are refined is not spec-ified.In a parallel environment,this order depends on the partition of the mesh between processors.After showing that the resulting refined mesh is independent of the order in which the elements are refined using the serial GLB al-gorithm,we show that every possible distribution of ele-ments between processors and every order of parallel re-finement yields the same mesh as would be produced by the serial algorithm.Theorem6.1The mesh that results from the refinement of a selected set of elements of a given mesh using the GLB algorithm is independent of the order in which the elements are refined.Proof:An element is refined using the GLBalgorithm if it is in the initial set or refinementpropagates to it.An element is refinedif one of its neighbors creates a non-conformingvertex at the midpoint of one of its edges.Therefinement of by its longest edge divides theelement into two nested subelements andcalled the children of.These children are inturn refined by their longest edge if one of their edges is non-conforming.The refinement proce-dure creates a forest of trees of nested elements where the root of each tree is an element in theinitial mesh and the leaves are unrefined ele-ments.For every element,let be the refinement tree of nested elements rooted atwhen the refinement procedure terminates. Using the GLB procedure elements can be se-lected for refinement in different orders,creating possible different refinement histories.To show that this cannot happen we assume the converse, namely,that two refinement histories and generate different refined meshes,and establish a contradiction.Thus,assume that there is an ele-ment such that the refinement trees and,associated with the refinement histories and of respectively,are different.Be-cause the root of and is the same in both refinement histories,there is a place where both treesfirst differ.That is,starting at the root,there is an element that is common to both trees but for some reason,its children are different.Be-cause is always bisected by the longest edge, the children of are different only when is refined in one refinement history and it is not re-fined in the other.In other words,in only one of the histories does have children.Because is refined in only one refinement his-tory,then,the initial set of elements to refine.This implies that must have been refined because one of its edges became non-conforming during one of the refinement histo-ries.Let be the set of elements that are present in both refinement histories,but are re-fined in and not in.We define in a similar way.For each refinement history,every time an ele-ment is refined,it is assigned an increasing num-ber.Select an element from either or that has the lowest number.Assume that we choose from so that is refined in but not in.In,is refined because a neigh-boring element created a non-conforming ver-tex at the midpoint of their shared edge.There-fore is refined in but not in because otherwise it would cause to be refined in both sequences.This implies that is also in and has a lower refinement number than con-。
ABAQUS常见问题汇总
ABAQUS 常见问题汇总 - 2.0 版
目录 点击小节标题,可以跳到相应的内容(有些 WORD 版本可能需要按住 ctrl 键)
0. ABAQUS 入门资料.......................................................................................................................... 4
6.1 ABAQUS 安装方法 ................................................................................................................. 12 6.2 ABAQUS 显示异常(无法显示栅格、显卡冲突、更改界面颜色).......................................... 21 6.3 Document 无法搜索................................................................................................................. 21 6.4 磁盘空间不足 ........................................................................................................................... 22 6.5 Linux 系统................................................................................................................................ 22 6.6 死机后恢复模型 ....................................................................................................................... 23
ssd1963ql9使用手册
7.1 MCU INTERFACE .................................................................................................................................................16 7.1.1 6800 Mode ..................................................................................................................................................16 7.1.2 8080 Mode ..................................................................................................................................................16 7.1.3 Register Pin Mapping .................................................................................................................................16 7.1.4 Pixel Data Format ......................................................................................................................................16 7.1.5 Tearing Effect Signal (TE) ..........................................................................................................................17 7.2 SYSTEM CLOCK GENERATION .............................................................................................................................18 7.3 FRAME BUFFER....................................................................................................................................................19 7.4 SYSTEM CLOCK AND RESET MANAGER ...............................................................................................................19 7.5 LCD CONTROLLER ..............................................................................................................................................20 7.5.1 Display Format ...........................................................................................................................................20 7.5.2 General Purpose Input/Output (GPIO) ......................................................................................................20
IBM SPSS Statistics Version 28 授权用户许可管理员指南说明书
To push to the local desktops running Windows
Because IBM SPSS Statistics installations are compatible with Microsoft Windows Installer (MSI), you can push an installation to the end-user desktop computers.
stable diffusion 大模型命名规则
Stable Diffusion大模型命名规则一、引言Stable Diffusion大模型是深度学习领域的重要成果之一,广泛应用于计算机视觉、自然语言处理等领域。
为了更好地理解和应用Stable Diffusion大模型,本文将详细介绍其命名规则。
二、命名规则概述Stable Diffusion大模型的命名规则主要包括两部分:模型名称和版本号。
模型名称通常由“Stable Diffusion”和一系列后缀组成,用于描述模型的特定功能或应用场景。
版本号则用于标识模型的迭代更新和改进。
三、模型名称基本名称:Stable Diffusion功能后缀:根据模型的具体功能和应用场景,可以在基本名称后面添加相应的后缀。
例如,“Stable Diffusion for Image Generation”表示该模型主要用于图像生成,“Stable Diffusion for Language Understanding”表示该模型主要用于自然语言理解。
场景后缀:根据模型的应用场景,可以在基本名称后面添加相应的后缀。
例如,“Stable Diffusion for Autonomous Driving”表示该模型主要用于自动驾驶,“Stable Diffusion for Medical Imaging”表示该模型主要用于医学影像处理。
四、版本号格式:版本号通常采用三位数字表示,例如“1.0.0”、“2.1.3”等。
更新规则:当模型进行迭代更新或改进时,会在版本号后面添加相应的后缀。
例如,“1.0.0-beta”表示该版本为测试版,“1.0.0-final”表示该版本为正式版。
兼容性:在更新版本时,需要确保新版本与旧版本兼容,以避免对现有应用场景产生影响。
五、总结通过以上的介绍,我们可以看出Stable Diffusion大模型的命名规则比较简单明了。
模型名称用于描述模型的特定功能或应用场景,版本号用于标识模型的迭代更新和改进。
在每个单元格中所有绝对偏差都是常量。 无法计算莱文 f 统计。
在每个单元格中所有绝对偏差都是常量,这其实就是著名的偏差-方差折中问题(bias-variance tradeoff),是机器学习算法中最常见的问题之一。
在机器学习算法中,我们通常会用训练集来训练模型,然后用测试集来验证模型的泛化性能。
如果模型在训练集上表现很好,但在测试集上表现很差,那么就说明模型存在过拟合(overfitting)的问题,即训练集上的噪声或异常数据被模型所学习了,从而导致了测试集上的表现不佳。
而如果模型在训练集上表现很差,在测试集上同样表现不佳,那么就说明模型存在欠拟合(underfitting)的问题,即模型过于简单,无法拟合训练集和测试集的数据。
为了解决这个问题,我们可以采用一些技巧,如交叉验证、正则化等来调整模型,在偏差和方差之间找到一个平衡点,使得模型的泛化性能得到最大化。
无法计算莱文f 统计,是指在输入数据中存在频率为0的元素,从而导致无法计算莱文f 统计。
莱文f 统计是一种用来评估文本相似度的方法,通常用于搜索引擎、文本分类、信息检索等领域。
它基于n-gram模型,将文本分成n个连续的字母或单词组合,然后统计它们出现的频率。
它的本质是一种基于距离的度量方法,可以用来计算两个文本之间的相似度,从而实现文本分类等任务。
然而,当输入数据中存在频率为0的元素时,无法计算莱文 f 统计,因为0不能作为分母,从而导致结果无法计算。
在实际应用中,机器学习算法和文本相似度算法经常被用来解决各种问题,如自然语言处理、计算机视觉、语音识别等。
例如,在自然语言处理领域,我们可以用机器学习算法来训练情感分析模型,用于判断一段话的情感倾向;还可以用文本相似度算法来搜索相关文档或句子,从而实现信息检索。
而在计算机视觉领域,我们可以用机器学习算法来训练图像分类模型,用于区分不同的物体;还可以用文本相似度算法来比较两幅图像之间的相似度,从而实现图像搜索。
总之,在每个单元格中所有绝对偏差都是常量是机器学习算法和文本相似度算法中最重要的问题之一。
stable diffusion中的随机数
稳定扩散中的随机数是指在稳定的扩散过程中,随机数在其中发挥的作用。
稳定扩散是指在一定条件下,随机数的扩散过程趋于稳定,不会出现剧烈的波动或突变。
随机数在稳定扩散中的作用十分重要,它不仅影响着扩散的速度和路径,还直接影响着系统的稳定性和可预测性。
研究稳定扩散中的随机数,对于理解扩散过程的规律和提高预测的准确性具有重要意义。
1. 随机数的分布特性在稳定扩散中,随机数的分布特性对扩散过程的稳定性和可预测性具有重要影响。
通常情况下,随机数的分布可以用概率密度函数来描述。
常见的随机数分布包括正态分布、指数分布、泊松分布等。
不同的分布特性会导致随机扩散过程的不同规律,因此需要对随机数的分布特性进行深入研究。
2. 随机数的生成方法稳定扩散中的随机数通常需要借助计算机来进行生成。
常见的随机数生成方法包括伪随机数和真随机数。
伪随机数是通过确定性算法生成的随机数序列,其随机性是有限的。
真随机数则是通过物理过程生成的随机数,具有更高的随机性和不确定性。
选择合适的随机数生成方法对于稳定扩散的模拟和预测具有重要意义。
3. 随机数的影响因素稳定扩散中随机数的影响因素包括扩散介质的性质、外部环境的影响以及扩散过程中的相互作用等。
不同的影响因素会对随机数的分布特性和生成方法产生重要影响,进而影响整个扩散过程的稳定性和可预测性。
4. 随机数的模拟与验证稳定扩散中随机数的模拟与验证是研究的重点之一。
借助计算机模拟技术,可以对稳定扩散过程中的随机数进行模拟和仿真,以验证理论模型的有效性和预测准确性。
通过大量的模拟实验和验证,可以探索随机数对于稳定扩散的影响规律,并提出相应的改进和优化方案。
5. 随机数的应用稳定扩散中的随机数在很多领域都具有重要的应用价值。
例如在地理信息系统中,随机扩散模型可以用于预测空气污染物的扩散路径和范围;在金融领域,随机扩散模型可以用于分析股票价格的波动趋势和风险预测等。
研究稳定扩散中的随机数不仅有助于深入理解扩散的规律,还具有较高的应用前景。
symmetric difference符号
symmetric difference符号在数学和计算机科学中,对称差(或称对称差集、对称差异)是一个重要的概念,特别是在集合论和图论中。
今天,我们将深入探讨这个概念及其在各种应用中的表现。
在集合论中,两个集合A和B的对称差,记作A △ B,是一个集合,它是由既属于A又属于B的元素组成,同时也包括了A和B两个集合各自的全部元素,但不包括那些只属于其中一个集合的元素。
换句话说,A △ B包含了A和B的所有元素,但去掉了那些只属于一个集合的元素。
1. **数据压缩**:在数据压缩中,对称差集是一个重要的概念。
当我们有两个集合A和B时,如果我们将A和B的共同元素压缩为一个新的数据流,同时保留A和B的全部元素信息,那么这种方法就减少了数据的冗余。
2. **网络流理论**:在网络流理论中,对称差集是一个重要的工具。
通过分析网络中的节点和边,我们可以找到哪些节点或边可以构成一个对称差集,从而优化网络性能。
3. **图形学**:在图形学中,对称差集的概念也被广泛应用。
当我们需要处理复杂的图形结构时,可以通过分析图形中的对称差集来简化计算。
有多种方法可以计算对称差集,其中最常用的是使用集合运算。
具体来说,我们可以通过将A和B两个集合相减得到结果。
也就是说,A △ B = A - B ∪ B - A。
这种方法简单易行,且结果准确。
**四、总结**对称差集是一个重要的数学和计算机科学概念,它在数据压缩、网络流理论、图形学等多个领域都有广泛的应用。
通过深入理解对称差集的概念和计算方法,我们可以更好地理解和应用这些领域的知识。
总的来说,对称差集是一个非常有用的工具,它可以帮助我们更有效地处理和分析各种复杂的数据和图形。
r语言蒙特卡洛跨层中介效应置信区间的代码
R语言蒙特卡洛跨层中介效应置信区间的代码1.蒙特卡洛方法的介绍蒙特卡洛方法是一种基于随机抽样的统计计算方法,通过大量的随机抽样来模拟概率分布或计算复杂的数学问题。
在研究中介效应时,蒙特卡洛方法可以用来估计中介效应的置信区间,特别是在跨层中介效应的研究中。
2.R语言中的蒙特卡洛跨层中介效应代码在R语言中,可以使用现有的包来进行蒙特卡洛跨层中介效应的计算。
其中,mediation包和boot包是两个常用的包,可以帮助我们进行中介效应的蒙特卡洛模拟,并计算出置信区间。
下面我将向你演示一个简单的代码示例:# 首先安装并加载相关的R包install.packages("mediation")install.packages("boot")library(mediation)library(boot)# 设置模拟参数n <- 100 # 样本量B <- 1000 # 模拟次数# 模拟数据set.seed(123) # 设置随机种子,以确保结果的可复现性x <- rnorm(n) # 模拟自变量m <- 0.5*x + rnorm(n) # 模拟中介变量y <- 0.7*m + 0.3*x + rnorm(n) # 模拟因变量# 进行蒙特卡洛模拟mediate_model <- mediate(m, y, x, sims = B) # 计算中介效应CI <- boot(mediate_model, sims = "parametric", level = 0.95)# 计算置信区间# 输出结果summary(mediate_model)CI在这段代码中,我们首先安装并加载了mediation和boot两个包,然后设置了模拟参数n和B。
接下来,我们使用rnorm函数模拟了自变量x、中介变量m和因变量y,并利用mediate函数和boot函数分别计算了中介效应和置信区间。
MicroDIMM设计规范
4.20.12 - 214-Pin DDR2 SDRAM Unbuffered MicroDIMM DesignSpecificationPC2-4200/PC2-3200 DDR2 Unbuffered MicroDIMM Reference Design SpecificationRevision 0.526,April, 2004Contents1. Product Description (3)Product Family Attributes (3)Raw Card Summary (3)2. Environmental Requirements (4)Absolute Maximum Ratings (4)3. Architecture (4)Pin Description (4)Input/Output Functional Description (5)DDR2 SDRAM MicroDIMM Pinout (6)Block Diagram x16 2Ranks Raw Card A (7)Block Diagram x16 1Rank Raw Card B (8)4. Component Details (9)x16 Ballout for 256Mb, 512Mb, 1Gb, 2Gb and 4Gb DDR2 SDRAMs (Top View) (9)DDR2 SDRAM FBGA Component Specifications (9)Reference SPD Component Specifications (9)SPD Component DC Electrical Characteristics (9)5. Unbuffered MicroDIMM Details (10)DDR2 SDRAM Module Configurations (Reference Designs) (10)Input Loading Matrix (10)DDR2 MicroDIMM Gerber File Releases (11)Example Raw Card Component Placement (12)6. MicroDIMM Wiring Details (13)Signal Groups (13)General Net Structure Routing Guidelines (13)Explanation of Net Structure Diagrams (13)Differential Clock Net Structures (14)Data Net Structures (16)Control Net Structures S[1:0], CKE[1:0], ODT[1:0] (18)Address/Control Net Structures Ax, BAx, RAS, CAS, WE (19)Cross Section Recommendations (21)Test Points (22)7. Serial Presence Detect Definition (23)Serial Presence Detect Data Example (23)8. Product Label (26)9. MicroDIMM Mechanical Specifications (27)1. Product DescriptionThis reference specification defines the electrical and mechanical requirements for the PC2-4200 memory module, a 214-pin, 267 MHz clock (533 MT/s data rate), 64-bit wide, Unbuffered Synchronous Double Data Rate 2(DDR2) DRAM Micro Dual In-Line Memory Module (DDR2 SDRAM MicroDIMMs). It also defines a slower version, the PC2-3200, using 200MHz clock (400 MT/s data rate) DDR2 SDRAMs. These DDR2 SDRAM MicroDIMMs are intended for use as main memory when installed in systems such as mobile per-sonal computers.Reference design examples are included which provide an initial basis for Unbuffered MicroDIMM designs. Any modifications to these reference designs must meet all system timing, signal integrity and thermal requirements for 267 MHz clock rate support. Other designs are acceptable, and all Unbuffered DDR2MicroDIMM implementations must use simulations and lab verification to ensure proper timing requirements and signal integrity in the design.Raw Card SummaryProduct Family AttributesAttribute:Values:Notes:MicroDIMM Organizationx 64MicroDIMM Dimensions (nominal)30 mm high, 54.0mm wide MicroDIMM Types Supported Unbuffered Pin Count214SDRAMs Supported 256 Mb, 512 Mb, 1 Gb, 2 Gb, 4 GbCapacity128 MB, 256 MB, 512 MB, 1 GB, 2GB, 4 GB Serial Presence DetectConsistent with JEDEC Rev. 1.0Voltage Options, Nominal1.8 V V DD 1.8 V V DD Q1.8 V to 3.3 V V DD SPD 1InterfaceSSTL_18Note 1: V DD SPD is not tied to V DD or V DD Q on the DDR2 MicroDIMM.Raw CardNumber of DDR2 SDRAMsSDRAM OrganizationNumber of RanksA 8x162B4x1612. Environmental RequirementsPC2-4200 DDR2 SDRAM Unbuffered MicroDIMMs are intended for use in mobile computing environments that have limited capacity for heat dissipation.3. ArchitectureAbsolute Maximum RatingsSymbol ParameterRating Units Notes T OPR Operating Temperature (ambient) 0 to +65°C 1H OPR Operating Humidity (relative) 10 to 90%1T STG Storage Temperature-50 to +100°C 1H STGStorage Humidity (without condensation) 5 to 95%1Barometric Pressure (operating & storage)105 to 69kPa1, 21.Stresses greater than those listed may cause permanent damage to the device. This is a stress rating only, and device functional operation at or above the conditions indicated is not implied. Exposure to absolute maximum rating conditions for extended periods may affect reliability.2.Up to 9850 ft.Pin DescriptionCK[1:0] Clock Inputs, positive line 2 DQ[63:0] Data Input/Output 64CK[1:0]Clock inputs, negative line 2DM[7:0] Data Masks 8CKE[1:0]Clock Enables 2DQS[7:0]Data strobes8RAS Row Address Strobe 1DQS[7:0]Data strobes complement8CAS Column Address Strobe 1WE Write Enable 1NC,TESTLogic Analyzer specific test pin (No connecton MicroDIMM1S[1:0]Chip Selects2A[9:0],A[15:11]Address Inputs15V DD Core and I/O Power 15A10/AP Address Input/Autoprecharge 1V SS Ground56BA[2:0] SDRAM Bank Address 3V REF Input/Output Reference 1ODT[1:0]On-die termination control2V DD SPD SPD Power1SCL Serial Presence Detect (SPD)Clock Input1RFU Reserved for future use 12 SDA SPD Data Input/Output 1 NCNo connect4SA[1:0]SPD address2Total:214Input/Output Functional DescriptionSymbol Type Polarity FunctionCK0/CK0, CK1/CK1InputCrosspointThe system clock inputs. All address and command lines are sampled on the cross point of therising edge of CK and falling edge of CK. A Delay Locked Loop (DLL) circuit is driven from theclock inputs and output timing for read operations is synchronized to the input clock.RFU pins for 2 CK pairs reserved.CKE[1:0]Input Active High Activates the DDR2 SDRAM CK signal when high and deactivates the CK signal when low. By deactivating the clocks, CKE low initiates the Power Down mode or the Self Refresh mode. RFU pins for 2 CKEs reserved.S[1:0]Input Active Low Enables the associated DDR2 SDRAM command decoder when low and disables the com-mand decoder when high. When the command decoder is disabled, new commands are ignored but previous operations continue. Rank 0 is selected by S0; Rank 1 is selected by S1. Ranks are also called "Physical banks". RFU pins for 2 Ss reserved.RAS, CAS,WE Input Active Low When sampled at the cross point of the rising edge of CK and falling edge of CK CAS, RAS, and WE define the operation to be executed by the SDRAM.BA[2:0]Input—Selects which DDR2 SDRAM internal bank of four or eight is activated.ODT[1:0]Input Active High Asserts on-die termination for DQ, DM, DQS, and DQS signals if enabled via the DDR2SDRAM mode register. RFU pins for 2 ODTs reserved.A[9:0],A10/AP, A[15:11]Input—During a Bank Activate command cycle, defines the row address when sampled at the crosspoint of the rising edge of CK and falling edge of CK. During a Read or Write command cycle,defines the column address when sampled at the cross point of the rising edge of CK and fall-ing edge of CK. In addition to the column address, AP is used to invoke autoprecharge opera-tion at the end of the burst read or write cycle. If AP is high, autoprecharge is selected andBA0-BAn defines the bank to be precharged. If AP is low, autoprecharge is disabled. During aPrecharge command cycle, AP is used in conjunction with BA0-BAn to control which bank(s) toprecharge. If AP is high, all banks will be precharged regardless of the state of BA0-BAninputs. If AP is low, then BA0-BAn are used to define which bank to precharge.DQ[63:0]In/Out—Data Input/Output pins.DM[7:0]Input Active High The data write masks, associated with one data byte. In Write mode, DM operates as a byte mask by allowing input data to be written if it is low but blocks the write operation if it is high. In Read mode, DM lines have no effect.DQS[7:0], DQS[7:0]In/Out CrosspointThe data strobes, associated with one data byte, sourced with data transfers. In Write mode,the data strobe is sourced by the controller and is centered in the data window. In Read mode,the data strobe is sourced by the DDR2 SDRAMs and is sent at the leading edge of the datawindow. DQS signals are complements, and timing is relative to the crosspoint of respectiveDQS and DQS. If the module is to be operated in single ended strobe mode, all DQS signalsmust be tied on the system board to VSS and DDR2 SDRAM mode registers programmedappropriately.V DD, V DD SPD,V SSSupply—Power supplies for core, I/O, Serial Presence Detect, and ground for the module.SDA In/Out—This is a bidirectional pin used to transfer data into or out of the SPD EEPROM. A resistor must be connected to V DD to act as a pull up.SCL Input—This signal is used to clock data into and out of the SPD EEPROM. A resistor may be con-nected from SCL to V DD to act as a pull up.SA[1:0]Input—Address pins used to select the Serial Presence Detect base address. RFU pins for 2nd SPD reserved.NC,TEST In/Out—The TEST pin is reserved for bus analysis tools and is not connected on normal memory mod-ules (MicroDIMMs)..DDR2 SDRAM MicroDIMM PinoutPin #LowerSidePin#UpperSidePin#LowerSidePin#UpperSidePin#LowerSidePin#UpperSidePin#LowerSidePin#UpperSide1V REF108V SS28DQS2135Vss55BA0162BA182DQ43189DQ47 2V SS109DQ429Vss136DQ2856WE163RAS83V SS190V SS 3DQ0110DQ530DQ18137DQ2957V DD164V DD84DQ48191DQ52 4DQ1111V SS31DQ19138Vss58RFU(S2)165S085DQ49192DQ535V SS112DM032Vss139DQS359RFU(ODT2)166ODT086V SS193V SS6DQS0113V SS33DQ24140DQS360CAS167A1387RFU(CK3)194CK17DQS0114DQ634DQ25141Vss61V DD168V DD88RFU(CK3)195CK18V SS115DQ735Vss142DQ3062S1169RFU(S3)89V SS196V SS9DQ2116V SS36DM3143DQ3163ODT1170RFU(ODT3)90DM6197DQS610DQ3117DQ1237Vss144Vss64V DD171V DD91V SS198DQS6 11V SS118DQ1338DQ26145NC,TEST65NC172NC92DQ50199V SS 12DQ8119V SS39DQ27146V DD66V SS173V SS93DQ51200DQ54 13DQ9120DM140Vss147CKE167DQ32174DQ3694V SS201DQ5514V SS121V SS41NC148RFU(CKE3)68DQ33175DQ3795DQ56202V SS15RFU(CK2)122CK042V DD149V DD69V SS176V SS96DQ57203DQ6016RFU(CK2)123CK043CKE0150A1570DQS4177DM497V SS204DQ6117V SS124V SS44RFU(CKE2)151A1471DQS4178V SS98DQS7205V SS18DQS1125DQ1445V DD152V DD72V SS179DQ3899DQS7206DM7 19DQS1126DQ1546BA2153A1273DQ34180DQ39100V SS207V SS 20V SS127V SS47A11154A974DQ35181V SS101DQ58208DQ62 21DQ10128DQ2048A7155A875V SS182DQ44102DQ59209DQ63 22DQ11129DQ2149V DD156V DD76DQ40183DQ45103V SS210V SS 23Vss130Vss50A5157A677DQ41184V SS104SDA211SA0 24DQ16131DM251A4158A378V SS185DQS5105SCL212RFU(*1) 25DQ17132Vss52A2159A179DM5186DQS5106NC213SA1 26Vss133DQ2253V DD160V DD80V SS187V SS107V DD SPD214RFU(*2) 27DQS2134DQ2354A10/AP161A081DQ42188DQ46Note: NC = No Connect; NC,TEST(pin 145) is for bus analysis tool and is not connected on normal memory modules. (*1) = SA0 for 2nd SPD, (*2) = SA1 for 2nd SPD.Block Diagram: Raw Card Version A (Populated as 2 ranks of x16 SDRAMs)Block Diagram: Raw Card Version B (Populated as 1 rank of x16 SDRAMs)#Unless otherwise noted, resistorand V DD Q values are 22 Ω ± 5%DQ wiring may differ from that described in this drawing;however, DQ/DM/DQS/DQS relationships are maintained as shown8pFLoad CapacitorsA0-AN RAS CAS WEmatching on ± 0.5pFBA0-BA23.0Ω±5%4. Component Detailsx16 Ballout for 256Mb, 512Mb, 1Gb, 2Gb and 4Gb DDR2 SDRAMs (Top View) 123789NC NC A NC NCBCVDD NC VSS D VSSQ UDQS VDDQ UDQ6VSSQ UDM E UDQS VSSQ UDQ7 VDDQ UDQ1VDDQ F VDDQ UDQ0VDDQ UDQ4VSSQ UDQ3G UDQ2VSSQ UDQ5VDD NC VSS H VSSQ LDQS VDDQ LDQ6VSSQ LDM J LDQS VSSQ LDQ7 VDDQ LDQ1VDDQ K VDDQ LDQ0VDDQ LDQ4VSSQ LDQ3L LDQ2VSSQ LDQ5 VDDL VREF VSS M VSSDL CK VDD CKE WE N RAS CK ODT BA2BA0BA1P CAS CSA10A1R A2A0VDD VSS A3A5T A6A4A7A9U A11A8VSS VDD A12A14V A15A13WYNC NC AA NC NCDDR2 SDRAM FBGA Component SpecificationsThe DDR2 SDRAM components used with this DIMM design specification are intended to be consistent with JEDEC MO-207 DK-Z and DL-Z.Reference SPD Component SpecificationsThe Serial Presence Detect EEPROMs have their own power pin, V DD SPD, so that they can be programmed or read without powering up the rest of the module. The wide voltage range permits use with 1.8V, 2.5V or 3.3V serial buses.SPD Component DC Electrical CharacteristicsSymbol Parameter Min Max UnitsV DD SPD Core Supply Voltage 1.7 3.6V5. Unbuffered MicroDIMM DetailsDDR2 SDRAM Module Configurations (Reference Designs)Raw Card MicroDIMMCapacityMicroDIMMOrganizationSDRAMDensitySDRAMOrganization# ofSDRAMs# ofRanksSDRAMPackage Type# of banks inSDRAM# Address bitsrow/colA256 MB32 M x 64256 Mbit16 M x 1682FBGA413/9 A512 MB64 M x 64512 Mbit32 M x 1682FBGA413/10 A 1 GB128 M x 64 1 Gbit64 M x 1682FBGA813/10 A 2 GB256 M x 64 2 Gbit128 M x 1682FBGA814/10 A 4 GB512 M x 64 4 Gbit256 M x 1682FBGA8TBDRaw Card MicroDIMMCapacityMicroDIMMOrganizationSDRAMDensitySDRAMOrganization# ofSDRAMs# ofRanksSDRAMPackage Type# of banks inSDRAM# Address bitsrow/colB128 MB16 M x 64256 Mbit16 M x 1641FBGA413/9 B256 MB32 M x 64512 Mbit32 M x 1641FBGA413/10 B512 MB64 M x 64 1 Gbit64 M x 1641FBGA813/10B 1 GB128 M x 64 2 Gbit128 M x 1641FBGA814/10B 2 GB256 M x 64 4 Gbit256 M x 1641FBGA8TBD Input Loading MatrixSignal NamesInputDeviceR/C A R/C BClock (CKn, CKn )SDRAM42 CKEn/Sn/ODTn SDRAM44 Addr/RAS/CAS/BA/WE SDRAM84 DQn/DQSn/DQSn/DMn SDRAM21 SCL/SDA/SAn EEPROM11DDR2 MicroDIMM Gerber File ReleasesReference design file updates will be released as needed. This specification will reflect the most recent design files, but may be updated to reflect clarifications to the specification only; in these cases, the design files will not be updated. The following table outlines the most recent design file releasesNote: Future design file releases will include both a date and a revision label. All changes to the design file are also documented within the ‘read-me’ file.Raw Card SpecificationRevisionApplicable Design File NotesA0.5A0 B0.5B0Example Raw Card Component PlacementThe component layout for Raw Cards A, and B are similar. In the case of Raw Card B, DDR2 SDRAMs will be included on the front side of the card; however, passive components are on both sides of the board. This example is for reference only; refer to JEDEC standard MO-TBD for details.6. MicroDIMM Wiring DetailsSignal GroupsThis specification categorizes SDRAM timing-critical signals into four groups whose members have identical loadings and routings. The following table summarizes the signals contained in each group..Signal Group Signals In Group PageClocks for Unbuffered MicroDIMM CK [1:0], CK [1:0]14, 15Data, Data Mask, Data Strobe DQ [63:0], DM[7:0], DQS[7:0], DQS[7:0]16, 17Select, Clock Enable, ODT S [1:0], CKE [1:0], ODT[1:0]18Address/Control Ax, BAx, RAS, CAS, WE19, 20General Net Structure Routing GuidelinesNet structures and lengths must satisfy signal quality and setup/hold time requirements for the memory inter-face. Net structure diagrams for each signal group are shown in the following sections. Each diagram is accompanied by a trace length table that lists the minimum and maximum allowable lengths for each trace segment and/or net.The general routing recommendations are as follows. Other stackups and layouts are possible that meet the electrical characteristics.•Route all signal traces using appropriate trace width(e.g: 0.075mm) and enough spacing(e.g: 0.15mm) between adjacent traces considering cross talk effect.•Route clocks as much as possible using the inner layers.•Test points are required.Explanation of Net Structure DiagramsThe net structure routing diagrams provide a reference design example for each raw card version. These designs provide an initial basis for unbuffered MicroDIMM designs. The diagrams should be used to deter-mine individual signal wiring on a MicroDIMM for any supported configuration. Only transmission lines (repre-sented as cylinders and labeled with trace length designators “TL”) represent physical trace segments. All other lines are zero in length. To verify MicroDIMM functionality, a full simulation of all signal integrity and tim-ing is required. The given net structures and trace lengths are not inclusive for all solutions.Once the net structure has been determined, the permitted trace lengths for the net structure can be read from the table below each net structure routing diagram. Some configurations require the use of multiple net structure routing diagrams to account for varying load quantities on the same signal. All diagrams define one load as one DDR2 SDRAM input unless mentioned. It is highly recommended that the net structure routing data in this document be simulated by the user.Differential Clock Net Structures CK[1:0], CK[1:0]DDR2 SDRAM clock signals must be carefully routed to meet the following requirements:•Signal quality •Rise/Fall time•Cross point of the differential pair in the SDRAM •JEDEC-compatible reference delays•Minimal segment length differences (less than 2.54mm total) between clocks of the same functionClock Net Wiring (Raw card A)Clock Routing Trace Lengths (Raw card A)Raw card TL0 Outer TL1 Inner TL2 Inner TL3 Outer TL4 Inner TL5 Outer Notes Min Max Min Max Min Max Min Max Min Max Min Max A2.02.36.26.77.78.13.84.36.37.90.70.911.All distances are given in millimeters and must be kept within a tolerance of ± 0.8 millimeter.TL0MicroDIMM ConnectorTL1TL2TL3TL3CK CKSDRAM SDRAMTL5TL2TL3TL3SDRAMSDRAMTL5R = 200 Ω± 5%R = 200 Ω± 5%TL4TL4Clock Net Wiring (Raw card B)Clock Routing Trace Lengths (Raw card B)Raw card TL0 Outer TL1 Inner TL2 Inner TL3 Outer TL4 Outer Notes Min Max Min Max Min Max Min Max Min Max B2.02.318.218.47.78.13.84.31.52.011.All distances are given in millimeters and must be kept within a tolerance of ± 0.8 millimeter.TL0MicroDIMM ConnectorTL1TL2TL3CK CKSDRAMTL2TL3SDRAMR = 200 Ω± 5%R = 200 Ω± 5%TL4TL4Data Net StructuresDQ[63:0], DM[7:0], DQS[7:0], DQS[7:0]Special attention has been paid to balancing the data nets within a DDR2 SDRAM, within a particularMicroDIMM, and across the MicroDIMM family. Data nets have been placed in order to bound the data strobe nets. Because data travels with the data strobe, the placement of the strobe in the middle of the narrow win-dow aids in data timing. Although it is not necessary to ensure consistent delays between SDRAMs and/or card types, doing so facilitates system design, system simulation, and DIMM specifications. It is recommend to maintain consistent delays for all nets as described in the following tables.Net Structure Routing for DQ[63:0], DM[7:0], DQS[7:0], DQS[7:0] (Raw card A)Trace Lengths for DQ[63:0], DM[7:0], DQS[7:0], DQS[7:0] (Raw card A)Raw card TL0 Outer TL1 Outer TL2 Outer TotalR1Ohms Notes Min Max Min Max Min Max Min Max A1.04.618.720.92.93.125.325.5221,2,3,41.All distances are given in millimeters and must be kept within a tolerance of ± 0.8 millimeter.2.Total Min and Total Max refer to the min and max respectively of TL0 + TL1 + TL2.3.TL0 and TL1 of Raw Card A is adjusted to compensate for the delay caused by vias on DQ nets. Traces with one via are assumed to have 1.6mm additional length. Traces with two vias are assumed to have 3.2mm additional length.4.These signals must be referenced to ground.TL0MicroDIMM Connector22 Ω ± 5%TL2SDRAM PinTL2SDRAM PinTL1Net Structures Routing for DQ[63:0], DM[7:0], DQS[7:0], DQS[7:0] (Raw card B )Trace Lengths for DQ[63:0], DM[7:0], DQS[7:0], DQS[7:0] (Raw card B )Raw cardTL0 Outer TL1 OuterTotalR1Ohms Notes Min Max Min Max Min Max B1.04.621.723.925.325.5221,2,3,41.All distances are given in millimeters and must be kept within a tolerance of ± 0.8 millimeter.2.Total Min and Total Max refer to the min and max respectively of TL0 + TL1.3.TL0 and TL1 of Raw Card B is adjusted to compensate for the delay caused by via on DQ nets.Traces with one via are assumed to have 1.6mm additional length. Traces with two vias are assumed to have 3.2mm additional length.4.These signals must be referenced to ground.TL0MicroDIMM Connector22 Ω ± 5%SDRAM PinTL1Control Net Structures S [1:0], CKE[1:0], ODT[1:0] (Raw cards A, B)Net Structure Routing for Control Net Structures S [1:0], CKE[1:0], ODT[1:0] (Raw cards A, B)Trace Lengths for Control Net Structures S [1:0], CKE[1:0], ODT[1:0] (Raw cards A, B)TL0 OuterTL1 Outer/Inner TL2 Inner TL3 Inner TL4 Outer Notes Raw CardMin Max Min Max Min Max Min Max Min Max A 1.0 4.622.029.116.017.5 6.57.1 2.7 4.21,2,3B1.04.622.029.116.017.56.57.12.74.21,2,31. All distances are given in mm and should be kept within a tolerance of ± 0.8 mm2. TL0 and TL1 are adjusted to compensate for the delay caused by via. Traces with one via are assumed to have 1.6mm additional length. Traces with two vias are assumed to have3.2mm additional length.3. These signals must be referenced to VDD.TL0MicroDIMM ConnectorTL2TL23.0 Ω ± 5%TL1TL3TL3TL4SDRAM PinTL4SDRAM PinTL4SDRAM PinTL3TL3TL4SDRAM PinAddress/Control Net Structures Ax, BAx, RAS, CAS, WE (Raw card A ).Net Structure Routing for Address/Control Net Structures Ax, BAx, RAS, CAS, WE (Raw card A )Trace Lengths for Address/Control Net Structures Ax, BAx, RAS, CAS, WE (Raw card A )TL0 OuterTL1 Outer/Inner TL2 Inner TL3 inner TL4 Outer Notes Raw CardMin Max Min Max Min Max Min Max Min Max A1.04.622.029.116.017.56.57.11.08.31,2,31. All distances are given in mm and should be kept within a tolerance of ± 0.8 mm2. TL0 and TL1 are adjusted to compensate for the delay caused by via. Traces with one via are assumed to have 1.6mm additional length. Traces with two vias are assumed to have3.2mm additional length. 3. These signals must be referenced to VDD.TL0MicroDIMM ConnectorTL4SDRAM PinTL2TL23.0 Ω ± 5%TL1TL3TL3TL4SDRAM PinTL4SDRAM PinTL4SDRAM PinTL4SDRAM PinTL3TL3TL4SDRAM Pin TL4SDRAM PinTL4SDRAM PinAddress/Control Net Structures Ax, BAx, RAS, CAS, WE (Raw card B).Net Structure Routing for Address/Control Net Structures Ax, BAx, RAS, CAS, WE (Raw card B)Trace Lengths for Address/Control Net Structures Ax, BAx, RAS, CAS, WE (Raw card B)TL0 OuterTL1 Outer/Inner TL2 Inner TL3 inner TL4 Outer TL5 Outer Notes Raw CardMin Max Min Max Min Max Min Max Min Max Min Max B1.04.622.029.116.017.56.57.11.08.33.04.01,2,31. All distances are given in mm and should be kept within a tolerance of ± 0.8 mm2. TL0 and TL1 are adjusted to compensate for the delay caused by via. Traces with one via are assumed to have 1.6mm additional length. Traces with two vias are assumed to have3.2mm additional length.3. These signals must be referenced to VDD.TL0MicroDIMM ConnectorTL2TL23.0 Ω ± 5% TL1TL3TL3TL4SDRAM PinTL4SDRAM PinTL4SDRAM PinTL3TL3TL4SDRAM PinTL58pF ± 0.5pFCross Section RecommendationsAn example of the DDR2 MicroDIMM printed circuit board design uses six-layers of glass epoxy material. PCBs should contain full plane layers for reference plane. The reference planes can be divided so adjacent signal layers maintain a constant Vss or Vdd reference. All data group signals are referenced to Vss and all address/command are referenced to Vdd. The required board impedance is 60 Ω± 10%.PCB Electrical SpecificationsParameter Min Max UnitsTrace velocity: S0 (outer layers) 5.5 6.7ps/mmTrace velocity: S0 (inner layers) 6.57.6ps/mmTrace impedance: Z0 (all layers)5466OhmsExample Layer Stackup for 0.075mm width traceTest PointsAll DDR2 components are in BGA packages which makes the package pads inaccessible for probing during-system development. The DDR2 MicroDIMMs have test points identified to make initial evaluation easier. In some cases test pads have been added and in other cases existing vias are used as test points. An effort has been made to provide testability on some signals in all signal groups but 100% coverage is not possible.Raw Card A Test Points Example(Front View)DQ22CK0-CK1-DQS at resistor pack.CK0CK1DQ7DQ44DQ52DQ28Raw Card B Test Points Example(Front View)BA2DQ22CK0-CK1-A7A3A12A10A9A14S0-A11A6BA0A2BA1CKE0A15A5A1CAS-ODT0RAS-WE-DQS at resistor pack.CK0CK1DQ7DQ44DQ52A13A0A4A8DQ28DQ367. Serial Presence Detect DefinitionThe Serial Presence Detect (SPD) function MUST be implemented on the PC2-4200 DDR2 SDRAM Unbuf-fered MicroDIMM. The component used and the data contents must adhere to the most recent version of the JEDEC DDR2 SDRAM SPD Specifications. Please refer to this document for all technical specifications and requirements of the serial presence detect devices.The following table is intended to be an example of a typical PC2-4200 MicroDIMM. SPD values indicating different MicroDIMM performance characteristics will be utilized based on specific characteristics of the SDRAMs or MicroDIMMs. This example assumes:•Module Organization: 512MB•Device Composition: 32Mx16•Device Package: FBGA•Module Physical Ranks: 2•CAS latency: 4(DDR2-533), 3(DDR2-400)Serial Presence Detect Data Example (Part 1 of 3)Byte # (dec)Byte #(hex)DescriptionSPD Entry ValueSerial PDData Entry(Hexadecimal)NotesDDR2-533DDR2-400DDR2-533DDR2-400000Number of Serial PD Bytes written during production128801 101Total Number of Bytes in Serial PD device256082202Fundamental Memory Type (FPM, EDO, SDRAM,DDR, DDR2, ...)DDR2 SDRAM08303Number of Row Addresses on Assembly130D 404Number of Column Addresses on Assembly100A505Number of DIMM RanksModule height:30mm, Planar,card on card: no,2Ranks61606Data Width of this Assembly x6440 707Reserved Undefined00 808Voltage Interface Level of this assembly SSTL 1.8V05909SDRAM Cycle Time at maximum supported CASlatency (CL), CL = X3.75ns 5.00ns3D503100A SDRAM Access from Clock+/-0.50ns+/-0.50ns5050110B DIMM configuration type (Non-parity, or ECC)Non-Parity00120C Refresh Rate/Type7.8us/SR823,4 130D Primary SDRAM Width x1610140E Error Checking SDRAM Width NA00150F Reserved Undefined001.This will typically be programmed as 128 bytes.2.This will typically be programmed as 256 bytes.3.From Data sheet.4.High order bit is self refresh "flag". If set to "1", the assembly supports self refresh.5.These are optional, in accordance with JEDEC specification.1610SDRAM device attributes: Burst lengths supported4,80C1711SDRAM device attributes: Number of Banks onSDRAM device40431812SDRAM device attributes: CAS Latency4310083 1913Reserved Undefined000 2014DIMM type information MicroDIMM082115SDRAM Module Attributes Normal DIMM002216SDRAM device attributes: General no optional aspect002317Minimum Clock Cycle at CLX -1Undefined FF32418Maximum Data Access Time (t AC) from Clock at CLX -1Undefined FF32519Minimum Clock Cycle Time at CLX-2Undefined FF3261A Maximum Data Access Time (t AC) from Clockat CLX-2Undefined FF3271B Minimum Row Precharge Time (t RP)15.0ns15.0ns3C3C3 281C Minimum Row Active to Row Active delay (t RRD)7.5ns7.5ns1E1E3 291D Minimum RAS to CAS delay (t RCD)15.0ns15.0ns3C3C3 301E Minimum Active to Precharge Time (t RAS)45.0ns45.0ns2D2D3 311F Module Rank Density256MB403220Address and Command input Setup Time BeforeClock (t IS)0.60ns0.60ns606033321Address and Command input Hold Time After Clock(t IH)0.60ns0.60ns606033422Data Input Setup Time Before Clock (t DS)0.35ns0.35ns35353 3523Data Input Hold Time After Clock (t DH)0.35ns0.35ns35353 3624Write recovery time (t WR)15.0ns15.0ns3C3C3 3725Internal write to read command delay (t WTR)7.5ns10ns1E283 3826Internal read to precharge command delay (t RTP)7.5ns7.5ns1E1E3 3927Memory analysis probe characteristics Undefined004028Reserved Undefined004129SDRAM device minimum active to active/auto refreshtime (t RC)60.0ns60.0ns3C3C3422A SDRAM device minimum auto-refresh to active/autorefresh command period (t RFC)105.0ns105.0ns69693Serial Presence Detect Data Example (Part 2 of 3)Byte # (dec)Byte #(hex)DescriptionSPD Entry ValueSerial PDData Entry(Hexadecimal)NotesDDR2-533DDR2-400DDR2-533DDR2-4001.This will typically be programmed as 128 bytes.2.This will typically be programmed as 256 bytes.3.From Data sheet.4.High order bit is self refresh "flag". If set to "1", the assembly supports self refresh.5.These are optional, in accordance with JEDEC specification.。
iso 0.0-18.1 一个用来进行等距回归的包说明书
Package‘Iso’October12,2022Version0.0-18.1Date2019-06-05Title Functions to Perform Isotonic RegressionAuthor Rolf Turner<********************.nz>Maintainer Rolf Turner<********************.nz>Depends R(>=1.7.0)Description Linear order and unimodal order(univariate)isotonic regression;bivariate isotonic regressionwith linear order on both variables.LazyData trueLicense GPL(>=2)URL /~rolf/NeedsCompilation yesRepository CRANDate/Publication2020-05-2605:13:34UTCR topics documented:biviso (2)pava (4)ufit (6)vigour (8)Index91biviso Bivariate isotonic regression.DescriptionBivariate isotonic regression with respect to simple(increasing)linear ordering on both variables.Usagebiviso(y,w=NULL,eps=NULL,eps2=1e-9,ncycle=50000,fatal=TRUE,warn=TRUE)Argumentsy The matrix of observations to be isotonized.It must of course have at least two rows and at least two columns.w A matrix of weights,greater than or equal to zero,of the same dimension as y.If left NULL then w is created as a matrix all of whose entries are equal to1.eps Convergence criterion.The algorithm is deemed to have converged if each en-try of the output matrix,after the completion of the current iteration,does notdiffer by more than eps from the corresponding entry of the matrix after thecompletion of the previous iteration.If this argument is not supplied it defaultsto sqrt(.Machine$double.eps).eps2Criterion used to determine whether isotonicity is“violated”,whence whether (further)application of the“pool adjacent violators”procedure is required.ncycle The maximum number of cycles of the iteration procedure.Must be at least2 (otherwise an error is given).If the procedure has not converged after ncycleiterations then an error is given.(See below.)fatal Logical scalar.Should the function stop if the subroutine returns an error code other than0or4?If fatal is FALSE then output is returned by the functioneven if there was a“serious”fault.One can set fatal=FALSE to inspect thevalues of the objective matrix at various interim stages prior to convergence.See Examples.warn Logical scalar.Should a warning be produced if the subroutine returns a value of ifault equal to4(or to any other non-zero value when fatal has been setto FALSE)?DetailsSee the paper by Bril et al.,(References)and the references cited therein for details.ValueA matrix of the same dimensions as y containing the corresponding isotonic values.It has anattribute icycle equal to the number of cycles required to achieve convergence of the algorithm.Error MessagesThe subroutine comprising Algorithm AS206produces an error code ifault with values from0 to6The meaning of these codes is as follows:•0:No error.•1:Convergence was not attained in ncycle cycles.•2:At least one entry of w was negative.•3:Either nrow(y)or ncol(y)was less than2.•4:A near-zero weight less than delta=0.00001was replaced by delta.•5:Convergence was not attained and a non-zero weight was replaced by delta.•6:All entries of w were less than delta.If ifault==4a warning is given.All of the other non-zero values of ifault result in an error being given.WARNINGThis function appears not to achieve exact isotonicity,at least not quite.For instance one can do: set.seed(42)u<-matrix(runif(400),20,20)iu<-biviso(u)any(apply(iu,2,is.unsorted))and get TRUE.It turns out that columns13,14,and16of iu have exceptions to isotonicity. E.g.six of the values of diff(iu[,13])are less than zero.However only one of these is less than sqrt(.Machine$double.eps),and then only“marginally”smaller.So some of these negative values are“numerically different”from zero,but not by much.The largest in magnitude in this example,from column16,is-2.217624e-08—which is probably not of“practical importance”.Note also that this example occurs in a very artificial context in which there is no actual isotonic structure underlying the data.Author(s)Rolf Turner<********************.nz>/~rolfReferencesBril,Gordon;Dykstra,Richard;Pillers Carolyn,and Robertson,Tim;Isotonic regression in two independent variables;Algorithm AS206;JRSSC(Applied Statistics),vol.33,no.3,pp.352-357, 1984.See Alsopava()pava.sa()ufit()4pavaExamplesx<-1:20y<-1:10xy<-outer(x,y,function(a,b){a+b+0.5*a*b})+rnorm(200)ixy<-biviso(xy)set.seed(42)u<-matrix(runif(400),20,20)v<-biviso(u)progress<-list()for(n in1:9)progress[[n]]<-biviso(u,ncycle=50*n,fatal=FALSE,warn=FALSE)pava Linear order isotonic regression.DescriptionThe“pool adjacent violators algorithm”(PA V A)is applied to calculate the isotonic regression of a set of data,with respect to the usual increasing(or decreasing)linear ordering on the indices.Usagepava(y,w,decreasing=FALSE,long.out=FALSE,stepfun=FALSE)pava.sa(y,w,decreasing=FALSE,long.out=FALSE,stepfun=FALSE)Argumentsy Vector of data whose isotonic regression is to be calculated.w Optional vector of weights to be used for calculating a weighted isotonic regres-sion;if w is not given,all weights are taken to equal1.decreasing Logical scalar;should the isotonic regression be calculated with respect to de-creasing(rather than increasing)order?long.out Logical argument controlling the nature of the value returned.stepfun Logical scalar;if TRUE a step function representation of the isotonic regression is returned.DetailsThe function pava()uses dynamically loading of a fortran subroutine"pava"to effect the computa-tions.The function pava.sa()("sa"for"stand-alone")does all of the computations in raw R.Thus pava.sa()could be considerably slower for large data sets.The x values for the step function returned by these functions(if stepfun is TRUE)are thought of as being1,2,...,n=length(y).The knots of the step function are the x values(indices)following changes in the y values(i.e.the starting indices of the level sets,except for thefirst level set).The y value corresponding to thefirst level set is the“left hand”value of y or yleft.The step function is formed using the default arguments of stepfun().In particular it is right continuous.pava5 ValueIf long.out is TRUE then the result returned consists of a list whose components are:y thefitted valuesw thefinal weightstr a set of indices made up of the smallest index in each level set,which thus"keeps track"of the level sets.h a step function which represents the results of the isotonic regression.Thiscomponent is present only if stepfun is TRUE.If long.out is FALSE and stepfun is TRUE then only the step function is returned.If long.out and stepfun are both FALSE then only the vector offitted values is returned.Author(s)Rolf Turner<********************.nz>/~rolfReferencesRobertson,T.,Wright,F.T.and Dykstra,R.L.(1988).Order Restricted Statistical Inference.Wiley, New York.See Alsoufit()stepfun()biviso()Examples#Increasing order:y<-(1:20)+rnorm(20)ystar<-pava(y)plot(y)lines(ystar,type= s )#Decreasing order:z<-NULLfor(i in4:8){z<-c(z,rep(8-i+1,i)+0.05*(0:(i-1)))}zstar<-pava(z,decreasing=TRUE)plot(z)lines(zstar,type= s )#Using the stepfunction:zstar<-pava(z,decreasing=TRUE,stepfun=TRUE)plot(z)plot(zstar,add=TRUE,verticals=FALSE,pch=20,col.points="red")ufit Unimodal isotonic regression.DescriptionA"divide and conquer"algorithm is applied to calculate the isotonic regression of a set of data,fora unimodal order.If the mode of the unimodal order is not specified,then the optimal(in terms ofminimizing the error sum of squares)unimodalfit is calculated.Usageufit(y,lmode=NULL,x=NULL,w=NULL,lc=TRUE,rc=TRUE,type=c("raw","stepfun","both"))Argumentsy Vector of data whose isotonic regression is to be calculated.lmode Gives the location of the mode if this is specified;if the location is not specified, then all possible modes are tried and that one giving the smallest error sum ofsquares is used.x A largely notional vector of x values corresponding to the data vector y;the value of the mode must be given,or will be calculated in terms of these x values.Conceptually the model is y=m(x)+E,where m()is a unimodal function withmode at lmode,and where E is random"error".If x is not specified,it defaultsto an equi-spaced sequence on[0,1].w Optional vector of weights to be used for calculating a weighted isotonic regres-sion;if w is not given,all weights are taken to equal1.lc Logical argument;should the isotonization be left continuous?If lc==FALSE then the value of the isotonization just before the mode is set to NA,which causesline plots to have a jump discontinuity at(just to the left of)the mode.Thedefault is lc=TRUE.rc Logical argument;should the isotonization be right continuous?If rc==FALSE then the value of the isotonization just after the mode is set to NA,which causesline plots to have a jump discontinuity at(just to the right of)the mode.Thedefault is rc=TRUE.type String specifying the type of the output;see“Value”.May be abbreviated. DetailsDynamically loads fortran subroutines"pava","ufit"and"unimode"to do the actual work.ValueIf type=="raw"then the value is a list with components:x The argument x if this is specified,otherwise the default value.y Thefitted values.lmode The argument lmode if this is specified,otherwise the value of lmode which is found to minimize the error sum of squares.mse The mean squared error.If type=="both"then a component h which is the step function representation of the isotonic regression is added to the foregoing list.If type=="stepfun"then only the step function representation h is returned.Author(s)Rolf Turner<********************.nz>/~rolfReferencesMureika,R.A.,Turner,T.R.and Wollan,P.C.(1992).An algorithm for unimodal isotonic re-gression,with application to locating a maximum.University of New Brunswick Department of Mathematics and Statistics Technical Report Number92–4.Robertson,T.,Wright,F.T.and Dykstra,R.L.(1988).Order Restricted Statistical Inference.Wiley, New York.Shi,Ning-Zhong.(1988)A test of homogeneity for umbrella alternatives and tables of the level mun.Statist.—Theory Meth.vol.17,pp.657–670.Turner,T.R.,and Wollan,P.C.(1997)Locating a maximum using isotonic puta-tional Statistics and Data Analysis vol.25,pp.305–320.See Alsopava()biviso()Examplesx<-c(0.00,0.34,0.67,1.00,1.34,1.67,2.00,2.50,3.00,3.50,4.00,4.50,5.00,5.50,6.00,8.00,12.00,16.00,24.00)y<-c(0.0,61.9,183.3,173.7,250.6,238.1,292.6,293.8,268.0,285.9,258.8,297.4,217.3,226.4,170.1,74.2,59.8,4.1,6.1)z<-ufit(y,x=x,type="b")plot(x,y)lines(z,col="red")plot(z$h,do.points=FALSE,col.hor="blue",col.vert="blue",add=TRUE)8vigour vigour vigourDescriptionGrowth vigour of stands of spruce trees in New Brunswick,Canada.Usagedata("vigour")FormatA data frame with23observations(rows).Thefirst column is the year of observation(1965to1987inclusive).The otherfive columns are observations on the vigour of growth of the given stand in each of the years.DetailsThe stands each had different initial tree densities.It was expected that vigour would initially increase(as the trees increased in size)and then level off and start to decrease as the growing trees encroached upon each others’space and competed more strongly for resources such as moisture, nutrients,and light.It was further expected that the position of the mode of the vigour observations would depend upon the initial densities.SourceThese data were collected and generously made available by Kirk Schmidt who was at the time of collecting the data a graduate student in the Department of Forest Engineering at the University of New Brunswick,Fredericton,New Brunswick,Canada.The data were collected as part of his research for his Master’s degree(supervised by Professor Ted Needham)at the University of New Brunswick.See Schmidt(1993).ReferencesK.D.Schmidt(1993).Development of a precommercial thinning guide for black spruce.Thesis (M.Sc.F.),University of New Brunswick,Faculty of Forestry.Examplesmatplot(vigour[,1],vigour[,2:6],main="Growth vigour of stands of New Brunswick spruce",xlab="year",ylab="vigour",type="b")Index∗datasetsvigour,8∗nonlinearbiviso,2pava,4ufit,6∗regressionbiviso,2pava,4ufit,6biviso,2,5,7pava,3,4,7pava.sa,3stepfun,5ufit,3,5,6vigour,89。
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a r X i v :0801.4678v 1 [m a t h .A P ] 30 J a n 2008STAGNATION ZONES FOR A -HARMONIC FUNCTIONS ONCANONICAL DOMAINSVLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINEN Abstract.We study stagnation zones of A -harmonic functions on canonical do-mains in the Euclidean n -dimensional space.Phragmen-Lindel¨o f type theorems are proved.1.IntroductionIn this article we investigate solutions of the A -Laplace equation on canonical domains in the n -dimensional Euclidean space.Suppose that D is a domain in R n ,and let f :D →R be a function.For s >0,a subset ∆⊂D is called s -zone (stagnation zone with the deviation s )of f ,if there exists a constant C such that the difference between C and the function f is smaller than s on ∆.We may,for example,consider difference in the sense of the Euclidean distance,f (x )−C C (∆)=sup x ∈∆|f (x )−C |<s ,the L p-normf (x )−C L p (∆)=∆|f (x )−C |p d H n1/p<s ,or the Sobolev normf (x ) W 1p(∆)=∆|∇f (x )|p d H n1/p<s ,where H d is the d -dimensional Hausdorffmeasure in R n .For discussion about the history of the question,recent results and applications,see [SS06,SS07].Some estimates of stagnation zone sizes for solutions of the A -Laplace equation on locally Lipschitz surfaces and behaviour of solutions in stagnation zones,were given in [Mik07].In this paper we consider solutions of the A -Laplace equation in subdomains of R n of a special form.In two-dimensional case,such domains are2VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENsectors and strips.In higher dimensions,they are conical and cylindrical regions. The special form of domains allows us to obtain more precise results.Below we study stagnation zones of generalized solutions of the A-Laplace equationdiv A(x,∇f)=0(see[HKM93])with boundary conditions of types(see definitions1.7and1.11below):A(x,∇f),n =0,x∈∂D\Gon canonical domains in the Euclidean n-dimensional space,where G is a closed subset of∂D.We will prove Phragm´e n-Lindel¨o f type theorems for solutions of the A-Laplace equation with such boundary conditions.Canonical domains.Let n≥2.Fix an integer k,1≤k≤n,and setd k(x)= k i=1x2i 1/2.We call the setB k(t)={x∈R n:d k(x)<t}a k-ball andΣk(t)={x∈R n:d k(x)=t}a k-sphere in R n.In particular,the symbolΣk(0)denotes the k-sphere with the radius0,i.e.the setΣk(0)= x=(x1,...,x k,...,x n):x k+1=...=x n=0 .For every0<k<n we setp k(x)= n j=k+1x2j 1/2.andΣ∗k(t)={x∈R n:p k(x)=t},t≥0.Let0<α<β<∞befixed,and letD kα,β={x∈R n:α<p k(x)<β}.For k=n−1we also assume that x n>0.Then for k=n−1the D n−1α,βis the a layerbetween two parallel hyperplanes,and for1≤k<n−1the boundary of the domain D kα,βconsists of two coaxial cylindrical surfaces.The intersectionsΣk(t)∩D kα,βare precompact for all t>0.Thus,the functions d k(x)are exhaustion functions for D kα,β.STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS3Figure:D11,2(left)and D21,2in R3.Structure conditions.Let D be a subdomain of R n and letA(x,ξ):D the functionA(x,ξ):R n→R nis defined and continuous with respect toξ.We assume that the functionx→A(x,ξ)is measurable in the Lebesgue sense for allξ∈R n and(1.1)A(x,λξ)=λ|λ|p−2A(x,ξ),λ∈R\{0},p≥1.Suppose that for a.e.x∈D and for allξ∈R n the following properties hold:(1.2)ν1|ξ|p≤ ξ,A(x,ξ) ,|A(x,ξ)|≤ν2|ξ|p−1with p≥1and some constantsν1,ν2>0.We consider the equation(1.3)div A(x,∇f)=0.An important special case of(1.3)is the Laplace equation∆f=ni=1∂2f4VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENFrequencies.Fix t ≥0and p ≥1.Let O be an open subset of Σ∗k (t )(with respect to the relative topology of Σ∗k (t )),and let P be a nonempty closed subset of ∂O .We let(1.4)λp,P (O )=infuO|∇u |p d H n −1O )with(1.5)u |P =0,andn is the unit normal vector to ∂O .If P =∂O we call λp (O )≡λp,P (O )the first frequency of the order p ≥1of the set O .If P =∂O the quantity λp,P (O )is the third frequency .The second frequency is the following quantity:(1.6)µp (O )=sup CinfuO|∇u |p d H n −1O ).Seealso Pˆo lya and Szeg¨o [PS51],Lax[Lax57].Generalized boundary conditions.Let ϕ:D ⊂R n →R be a locally Lipschitz function.We denote by D b (ϕ)the set of all points x ∈D at which ϕdoes not have the differential.Let U ⊂D be a subset and let ∂′U =∂U \∂D be its boundary with respect to D .If ∂′U is (H n −1,n −1)-rectifiable,then it has locally finite perimeter in the sense of De Giorgi and H n −1-almost everywhere on ∂U ,an unit normal vectorU ∩n =0,x ∈∂D \G ,STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS5 if for every subdomain U∈(G,D),(1.9)H n−1 ∂′U∩D b(f) =0,and for every locally Lipschitz functionϕ:n d H n−1= U A(x,∇f),∇ϕ d H n.Heren =0,x∈∂D\G,if for every subdomain U∈(G,D)with(1.9),and for every locally Lipschitz function ϕ:n d H n−1= U A(x,∇f),∇(ϕf) d H n.In the case of a smooth boundary∂D,and f∈C2(D),the relation(1.10)implies (1.3)with(1.8)everywhere on∂D\G.This requirement(1.13)implies(1.3)with (1.12)on∂D\G.See[Mik06,Section7.2.1].The surface integrals exist by(1.9).Indeed,this assumption guarantees that∇f(x) exists H n−1-a.e.on∂′U.The assumption that U∈(G,U)implies existence of a normal vectorn is defined andfinite a.e.on∂′U.2.Saint-Venant principleIn this section,we will prove the Saint-Venant principle for solutions of the A-Laplace equation on canonical domains.Let0<k<n.Fix a domain D=D kα,β∩B k(t0)with t0>0and0<α<β<∞. We write P={x∈∂D:p k(x)=α}and Q={x∈∂D:p k(x)=β}and G=P∪Q. Let t,τ∈(α,β),t<τ,and∆k(t,τ)={x∈D:t<p k(x)<τ}.For s≥0we setσk(s)= x∈∆k(0,∞):p k(x)=s .2.1.Theorem.Letα<τ′<τ′′<β.If f:D→R is a generalized solution of(1.3) with the generalized boundary condition(1.8)on∂D\G,then the inequality(2.2)I1(t,τ′)+C1(t)/ν1≤ I1(t,τ′′)+C1(t)/ν1 exp −ν16VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENholds for all t∈(α,τ′].If f:D→R is a generalized solution of(1.3)with the generalized boundary con-dition(1.12)then(2.3)I1(t,τ′)+C2(t)/ν1≤ I1(t,τ′′)+C2(t)/ν1 exp −ν1U\G→R be a locally Lipschitz function.By(1.13)we haveϕf A(x,∇f),∂′∆k(t,τ)n=∇p k(x)for x∈σk(τ)andSTAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS7 whereC2(t)= σk(t)f A(x,∇f),∇p k(x) d H n−1.Note that we may also choose(2.6)˜C2(τ)=− σk(τ)f A(x,∇f),∇p k(x) d H n−1,to obtain an inequality similar to(2.5).Next we will estimate the right side of(2.5).By(1.2)and the H¨o lder inequalityσk(τ)f A(x,∇f),∇p k(x) d H n−1≤ σk(τ)|f||A(x,∇f)|d H n−1≤ν2 σk(τ)|f||∇f|p−1d H n−1≤ν2 σk(τ)|f|p d H n−1 1/p σk(τ)|∇f|p d H n−1 (p−1)/p. We note that the surfacesσk(τ)are parallel to∂D kα,β.By using(1.4)we may write (2.7) σk(τ)|f|p d H n−1≤λ−1p,Z f(τ)(σk(τ)) σk(τ)|∇f|p d H n−1andσk(τ)f A(x,∇f),∇p k(x) d H n−1 ≤ν2λ−1/p p,Z f(τ)(σk(τ)) σk(τ)|∇f|p d H n−1. By(2.5)and the Fubini theoremν1I1(t,τ)+C2(t)≤ν2λ−1/pp,Z f(τ)(σk(τ))dI1ν2λ1/pp,Z f(τ)(σk(τ))≤dI1ν1 .By integrating this differential inequality we haveexp ν1I1(t,τ′)+C2(t)/ν18VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINEN for arbitraryτ′,τ′′∈(α,β)withτ′<τ′′.We have shown that (2.8)I1(t,τ′)+C2(t)/ν1≤ I1(t,τ′′)+C2(t)/ν1 exp −ν1n d H n−1=0.For an arbitrary constant C,we get from this and(1.10) (2.9) σk(t)∪σk(τ)(f−C) A(x,∇f),STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS9 and by(2.10)we haveν1I1(t,τ)+C1(t)≤ν2µ−1p(σk(τ)) σk(τ)|∇f|p d H n−1orν1I1(t,τ)+C1(t)≤ν2µ−1p(σk(τ))dI1ν2τ′′τ′µp(σk(τ))dτ .3.Stagnation zonesNext we apply the Saint-Venant principle to obtain information about stagnation zones of generalized solutions of the equation(1.3).Wefirst consider zones with respect to the Sobolev norm.Other results of this type follow immediately from well-known imbedding theorems.Stagnation zones with respect to the W1p-norm.We rewrite(2.2)and(2.3)in another form.Fix D kα,β.Letp∗k(x)=p k(x)−α+β2we have−β∗<p∗k(x)<β∗,and we denoteD∗,kβ∗={x∈R n:−β∗<p∗k(x)<β∗}.Let t0>0and−β∗<τ′≤τ′′<β∗.We write(3.2)∆∗,k(τ′,τ′′)={x∈B k(t0):τ′<p∗k(x)<τ′′}andI2(τ′,τ′′)= ∆∗,k(τ′,τ′′)|∇f|p d H n.10VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENLet 0<τ′<τ′′<β∗.By (2.3)we have for t ∈(−τ,τ)I 2(t,τ′)+C 4(t )/ν1≤ I 2(t,τ′′)+C 4(t )/ν1 exp−ν1ν2−τ′−τ′′λ1/pp,Z ∗f(τ)(σ∗,k (τ))dτ,where (3.4)σ∗,k (s )={x ∈∆∗,k (−∞,∞):p ∗k (x )=s }.By adding these inequalities and noting that C 4(t )+˜C4(t )=0we obtain I 2(−τ′,t )+I 2(t,τ′)≤ I 2(−τ′′,t )+I 2(t,τ′′)×max exp −ν1ν2τ′′τ′λ1/pp,Z ∗f (τ)(σ∗,k (τ))dτ.Thus we have the estimate (3.5)I 2(−τ′,τ′)≤I 2(−τ′′,τ′′)×max exp−ν1ν2τ′′τ′λ1/pp,Z ∗f(τ)(σ∗,k (τ))dτ.Similarly,from (2.2)we obtain (3.6)I 2(−τ′,τ′)≤I 2(−τ′′,τ′′)×max exp−ν1ν2τ′′τ′µp (σ∗,k (τ))dτ.From this we obtain the following theorem on stagnation W 1p -zones:3.7.Theorem.Let t 0>0,β>α>0,and let −β∗<τ′≤τ′′<β∗where β∗is as in(3.1).If f is a solution of (1.3)on D =D ∗,kβ∗∩B k (t 0)with the generalized boundarySTAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS11 condition(1.8)on∂D\G,where G={x∈∂D:p∗k(x)=±β∗}and max exp −ν1ν2τ′′ τ′µp(σ∗,k(τ))dτ <s1/p,or a solution of(1.3)on D with the generalized boundary condition(1.12)on∂D\G andmax exp −ν1ν2τ′′ τ′λ1/p p,Z∗f(τ)(σ∗,k(τ))dτ <s1/p,then the subdomain∆∗,k(−τ′,τ′)is a s-zone with respect to the W1p-norm i.e.,∆∗,k(−τ′,τ′)|∇f|p d H n<s,where∆∗,k is as in(3.2).Stagnation zones with respect to the L p-norm.Let t0>0,β>α>0,and let −β∗<τ′≤τ′′<β∗whereβ∗is as in(3.1).Denote by C5(k,p,α,β,t0)the best constant of the imbedding theorem from W1p(D∗,kβ∗)to L p(D∗,kβ∗),i.e.in the inequalityg−CL p(D∗,kβ∗)≤C5(k,p,α,β,t0) gW1p(D∗,kβ∗).The domains D∗,kβ∗∩B k(t0)are convex and such a constant C5exists(see Maz’ya[Maz85]or[AF03,p.85]).In this case we obtain from(3.5),(3.6)(3.8) f−C pL p(∆∗,k(−τ′,τ′))≤C p5(k,p,β∗−τ′′,β∗+τ′′,t0)I2(−τ′′,τ′′)×max exp −ν1ν2τ′′ τ′λ1/p p,Z∗f(τ)(σ∗,k(τ))dτ , and(3.9) f−C pL p(∆∗,kτ′)≤C p5(k,p,β∗−τ′′,β∗+τ′′,t0)I2(−τ′′,τ′′)×max exp −ν1ν2τ′′ τ′µp(σ∗,k(τ))dτ .These relations can be used to obtain information about stagnation zones with respect to the L ly,we have:12VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINEN3.10.Theorem.If f is a solution of(1.3)on D=D∗,kβ∗∩B k(t0)with the generalizedboundary condition(1.8)(or(1.12))on∂D\G,where G={x∈∂D:p∗k(x)=±β∗},and the right side of(3.8)(or(3.9))is smaller than s>0,then the domain ∆∗,k(−τ′,τ′)is a stagnation zone with the deviation s p in the sense of the L p-norm on D.Stagnation zones for bounded,uniformly continuous functions.Let t0>0,β>α>0,and let−β∗<τ′≤τ′′<β∗whereβ∗is as in(3.1).As above,denote by C6(k,p,α,β,t0)the best constant of the imbedding theorem from W1p(D∗,kβ∗)to C(D∗,kβ∗),i.e.in the inequality(3.11) g−CC(D∗,kβ∗)≤C6(k,p,α,β,t0) gW1p(D∗,kβ∗).A domain D∗,kβ∗is convex and hence(3.11)holds for p>n(see Maz’ya[Maz85]or[AF03,p.85]).In this case from(3.5),(3.6)we obtain(3.12) f−C C(∆∗,k(−τ′,τ′))≤C p6(k,p,β∗−τ′,β∗+τ′,t0)I2(−τ′′,τ′′)×max exp −ν1ν2τ′′ τ′λ1/p p,Z∗f(τ)(σ∗,k(τ))dτ , and(3.13) f−C C(∆∗,k(−τ′,τ′))≤C p6(k,p,β∗−τ′,β∗+τ′,t0)I2(−τ′′,τ′′)×max exp −ν1ν2τ′′ τ′µp(σ∗,k(τ))dτ .These relations can be used to obtain theorems about stagnation zones for bounded uniformly continuous functions.3.14.Theorem.If f is a solution of(1.3),p>n,on D=D∗,kβ∗∩B k(t0)with thegeneralized boundary condition(1.8)(or(1.12))on∂D\G where G={x∈∂D: p∗k(x)=±β∗},and the right side of(3.12)(or(3.13))is smaller than s>0,then the domain∆∗,k(−τ′,τ′)is a stagnation zone with the deviation s in the sense of the norm · C0(∆∗,k(−τ′,τ′)).4.Other applicationsNext we prove Phragm´e n-Lindel¨o f type theorems for the solutions of the A-Laplace equation with boundary conditions(1.8)and(1.12).STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS13Estimates for W1p -norms.Let t0>0,β>α>0,and let beβ∗is as in(3.1).First we will prove some estimates of the W1p-norm of a solution.Let f be a solutionof(1.3)on D∗,kβ∗with the generalized boundary condition(1.8)on∂D\G.Fix0<τ′<τ′′<β∗and estimate f W1p (∆∗,k(−τ′,τ′)).Letψ:[τ′,τ′′]→(0,∞)be a Lipschitz function such that (4.1)ψ(τ′)=1,ψ(τ′′)=0.We choose(4.2)φ(t)= 1for|t|<τ′,ψ(|t|)forτ′≤|t|≤τ′′. The functionϕ(x)=φ(p∗k(x))is admissible in Definition1.7forU=∆∗,k(−τ′′,τ′′).As in(2.9)we may by(1.10)writeσ∗,k(−τ′′)∪σ∗,k(τ′′)φp(p∗k(x))(f−C) A(x,∇f),14VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENand by the H¨o lder inequality∆∗,k(−τ′′,τ′′)φp−1(p∗k(x))|f−C||∇f|p−1|∇φ(p∗k(x))|d H n= ∆∗,k(−τ′′,τ′′)φp−1(p∗k(x))|∇f|p−1|φ′(p∗k(x))||f−C|d H n≤ ∆∗,k(−τ′′,τ′′)φp(p∗k(x))|∇f|p d H n (p−1)/p ∆∗,k(−τ′′,τ′′)|φ′(p∗k(x))|p|f−C|p d H n 1/p From this inequality and(4.3)we obtainνp1 ∆∗,k(−τ′,τ′)φp(p∗k(x))|∇f|p d H n≤p pνp2 ∆∗,k(−τ′′,τ′′)|φ′(p∗k(x))|p|f−C|p d H n. Becauseφ(p∗k(x))≡1on∆∗,k(−τ′,τ′)we have the following inequality: (4.4)νp1 ∆∗,k(−τ′,τ′)|∇f|p d H n≤p pνp2∆∗,k(−τ′′,τ′′)\∆∗,k(−τ′,τ′)|ψ′(p∗k(x))|p|f−C|p d H n. Next we willfindminψ∆∗,k(−τ′′,τ′′)\∆∗,k(−τ′,τ′)|ψ′(p∗k(x))|p|f−C|p d H n,where the minimum is taken over allψin(4.2).We have∆∗,k(−τ′′,τ′′)\∆∗,k(−τ′,τ′)|ψ′(p∗k(x))|p|f−C|p d H n=−τ′−τ′′|ψ′(τ)|p dτ σ∗,k(τ)|f(x)−C|p d H n−1+τ′′τ′|ψ′(τ)|p dτ σ∗,k(τ)|f(x)−C|p d H n−1STAGNATION ZONES FOR A -HARMONIC FUNCTIONS ON CANONICAL DOMAINS 15and (4.5)minψ∆∗,k (−τ′′,τ′′)\∆∗,k (−τ′,τ′)|ψ′(p ∗k (x ))|p |f (x )−C |p d Hn≤minψ−τ′−τ′′|ψ′(τ)|p dτσ∗,k (τ)|f (x )−C |p d H n −1+minψτ′′τ′|ψ′(τ)|p dτσ∗,k (τ)|f (x )−C |p d H n −1≡A 1+A 2.Because by the H¨o lder inequality 1≤τ′′ τ′|ψ′(τ)|dτp≤τ′′ τ′|ψ′(τ)|p dτσ∗,k (τ)|f (x )−C |p d H n −1×τ′′τ′dτσ∗,k (τ)|f (x )−C |p d H n −11/(1−p ) p −1,we have τ′′τ′dτσ∗,k (τ)|f (x )−C |p d H n −11/(1−p ) 1−p≤τ′′τ′|ψ′(τ)|p dτσ∗,k (τ)|f (x )−C |p d H n −1,and henceA 2≥τ′′τ′dτσ∗,k (τ)|f (x )−C |p d H n −11/(1−p ) 1−p .It is easy to see that here the equality holds for a special choice of ψ.ThusA 2=τ′′τ′dτσ∗,k (τ)|f (x )−C |p d H n −11/(1−p ) 1−p.16VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINEN Similarly,A1= −τ′ −τ′′dτ σ∗,k(τ)|f(x)−C|p d H n−1 1/(1−p) 1−p.From(4.5)we obtain|ψ′(p∗k(x))|p|f−C|p d H nminψ∆∗,k(−τ′′,τ′′)\∆∗,k(−τ′,τ′)≤ −τ′ −τ′′dτ σ∗,k(τ)|f(x)−C|p d H n−1 1/(1−p) 1−p+ τ′′ τ′dτ σ∗,k(τ)|f(x)−C|p d H n−1 1/(1−p) 1−p. By using(4.4)we obtain the inequality:p−p ν1STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS17 Similarly,for solutions of the A-Laplace equation with the boundary condition (1.12)we may prove thatp−p ν118VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENBy using(3.6)we obtain from this the inequality:I2(−τ′,τ′)≤C7max −τ′′ −τ′′−1dτ σ∗,n−1(τ)|f(x)−C|p d H n−1 1/(1−p) 1−p,τ′′+1dτ σ∗,n−1(τ)|f(x)−C|p d H n−1 1/(1−p) 1−pτ′′×max exp −ν1ν2τ′′ τ′µp(σ∗,n−1(τ))dτ . We observe that in this case(4.8)µp σ∗,n−1(τ) ≡µp σn−1(0) ,and henceτ′′µp σ∗,n−1(τ) dτ=µp σn−1(0) (τ′′−τ′).τ′It follows that(4.9)I2(−τ′,τ′)≤C7max −τ′′ −τ′′−1dτ σ∗,n−1(τ)|f(x)−C|p d H n−1 1/(1−p) 1−p,τ′′+1dτ σ∗,n−1(τ)|f(x)−C|p d H n−1 1/(1−p) 1−pτ′′×exp −ν1STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS19 Similarly for a solution f of(1.3)with(1.1)and(1.2),satisfying the boundary condition(1.12)we may write(4.11)I2(−τ′,τ′)≤C7max −τ′′ −τ′′−1dτ σ∗,n−1(τ)|f(x)|p d H n−1 1/(1−p) 1−p,τ′′+1dτ σ∗,n−a(τ)|f(x)|p d H n−1 1/(1−p) 1−pτ′′×max exp −ν1ν2τ′′ τ′λ1/p p,Z∗f(τ)(σ∗,n−1(τ))dτ . However here we do not have any identity similar to(4.8).We have:4.12.Theorem.Let t0>0,and let f:B n−1(t0)→R be a generalized solution of (1.3)with(1.1)and(1.2)satisfying the boundary condition(1.12)onΣn−1(t0).If the right side of(4.11)tends to0asτ′′→∞,then f≡0on the cylinder B n−1(t0)If f(x)=0everywhere on the boundaryΣn−1(t0)of the cylinder,then an identity similar to(4.8)holds in the following form:(4.13)λ1/p p(σ∗,n−1(τ))≡λ1/p p(σn−1(0))(λ).As above,wefind(4.14)I2(−τ′,τ′)≤C7max −τ′′ −τ′′−1dτ σ∗,n−1(τ)|f(x)|p d H n−1 1/(1−p) 1−p,τ′′+1dτ σ∗,n−1(τ)|f(x)|p d H n−1 1/(1−p) 1−pτ′′×exp −ν120VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENPhragm´e n-Lindel¨o f type theorems II.We prove Phragm´e n-Lindel¨o f type theo-rems for canonical domains of an arbitrary form.Let1≤k<n−1and let t0>0 befixed.We consider a domainD=B k(t0)= x=(x1,...,x k,x k+1,...,x n):d k(x)<t0 .Let f be a generalized solution of(1.3)with(1.1)and(1.2)satisfying the boundary condition(1.8)onΣk(t0)= x∈R n:d k(x)<t0 .Fixτ0>0.Letτ0<τ′<τ′′<∞.By(4.6)we may writeD k0,τ′|∇f|p d H n≤C8 τ′′ τ′dτ σk(τ)|f(x)−C|p d H n−1 1/(1−p) 1−p,where C8=C7/2.As in(3.6)we obtain from(2.2)the estimateD k0,τ|∇f|p d H n≤ D k0,τ′|∇f|p d H n exp −ν1ν2τ′τ0µp(σk(τ))dτ .The inequality(4.16)holds for arbitrary constant C and everyτ′′>τ′.Thus the following statement holds:4.17.Theorem.Let t0>0,and let f:B k(t0)→R be a generalized solution of(1.3) with(1.1)and(1.2)satisfying the boundary condition(1.8)onΣk(t0),1≤k<n−1. If for a constant C the right side of(4.16)tends to0asτ′,τ′′→+∞,then f≡const on B k(t0).STAGNATION ZONES FOR A-HARMONIC FUNCTIONS ON CANONICAL DOMAINS21 In the case if f satisfies(1.3)with(1.1),(1.2)and the boundary condition(1.12) onΣk(t0),then we have(4.18) D k0,τ0|∇f|p d H n≤C8 τ′′ τ′dτ σk(τ)|f(x)|p d H n−1 1/(1−p) 1−p×exp −ν122VLADIMIR M.MIKLYUKOV,ANTTI RASILA,AND MATTI VUORINENReferences[AF03]R.Adams and J.Fournier:Sobolev spaces,2nd ed.Pure and Applied Mathematics 140,Academic Press,New York,2003.[Fed69]H.Federer:Geometric measure theory.Die Grundlehren der math.Wiss.Vol.153, Springer-Verlag,Berlin-Heidelberg-New York,1969.[HKM93]J.Heinonen,T.Kilpel¨a inen and O.Martio:Nonlinear potential theory of degen-erate elliptic equations,Clarendon Press,Oxford,1993.[Lax57]x:A Phragm´e n-Lindel¨o f Theorem in Harmonic Analysis and Its Application to Some Questions in the Theory of Elliptic Equations,Communications on Pure andApplied Mathematics,v.X,1957,361–389.[Maz85]V.G.Maz’ya:Sobolev Spaces.Springer Series in Soviet Mathematics,Springer-Verlag, Berlin-New York,1985.[Mik81]V.M.Miklyukov:Asymptotic properties of subsolutions of quasilinear equations of elliptic type and mappings with bounded distortion(in Russian).Mat.Sb.11(1980),42–66;English SR Sb.v.39(1981),37–60.[Mik06]V.M.Miklyukov:Introduction to Nonsmooth Analysis(in Russian),Volgograd,izd-vo VolGU,2006,284pp.ISBN5-9669-0209-7.[Mik07]V.M.Miklyukov:Stagnation Zones of A-Solutions,Memory I.N.Vekua,Georgian Math.J.14(2007),no.3,519–531.[OY77]O.A.Ole˘ınik and G.A.Yosifian:Boundary value problems for second order elliptic equations in unbounded domains and Saint-Venant’s principle.Ann.Scuola Norm.Sup.Pisa Cl.Sci.(4)4(1977),no.2,269–290.[PS51]G.Pˆo lya and G.Szeg¨o:Isoperimetric inequalities in mathematical physics.Princeton University Press,Princeton,1951.[SS06]Proceedings of the seminar’Superslow processes’,Issue1,Ed.prof.V.M.Miklyukov, Volgograd State University,2006,184pp.ISBN5-9669-0163-5.[SS07]Proceedings of the seminar’Superslow processes’,Issue2,Ed.prof.V.M.Miklyukov, Volgograd State University,2007,172pp.。