144-149 CSS-V8N4-1555Brief Analysis on Conflicts of Interest of Credit Rating Agencies
TheoreticalAndAppliedFractureMechanics,1992…
Theoretical And Applied Fracture Mechanics, 1992-1993 Bound Issues By G. C. SihIf you are searched for the ebook Theoretical and Applied Fracture Mechanics, 1992-1993 Bound Issues in pdf format, then you have come on tofaithful site. We presented complete variation of this ebook in doc, PDF, ePub, txt, DjVu forms. You may readTheoretical and Applied Fracture Mechanics, 1992-1993 Bound Issues online theoretical-and-applied-fracture-mechanics-1992-1993-bound-issues.pdf either load. Withal, on oursite you may reading guides and other artistic eBooks online, or downloading their. We will invite attention thatour website not store the eBook itself, but we give reference to website where you can load either reading online.If you have must to downloading pdf Theoretical and Applied Fracture Mechanics, 1992-1993 Bound Issues, then you have come on to correctsite. We have Theoretical and Applied Fracture Mechanics, 1992-1993 Bound Issues DjVu, doc, PDF, txt, ePub forms. 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Sih, Theoretical and Applied Mechanics, problems of fracture mechanics.on the finite element analysis of inverse problems - Inverse problems in fracture mechanics 481 G. (1993), Propagation and fracture energy of interface Sih, G.C. (1974),zheng* the state key laboratory for mechanical - in Progress in Fracture Mechanics, G.C. Sih and Theoretical and Applied Fracture Mechanics 18 (1993) Theoretical and Applied Fracture Mechanics 17 (1992)verification of brittle fracture criteria for - Computational Methods in Fracture Mechanics, Acta Mechanica et Automatica, Sih G.C. (1965), Plane Problems of Cracks in Dissimilar Media.: g. c. sih: books, biogs, audiobooks, - Visit 's G. C. Sih Page and shop for all G. C. Sih books. Check out pictures, bibliography, biography and community discussions about G. C. Sihjournal " mechanics of solids" - archive of issues - "Fracture mechanics applied to glass fibre/epoxy matrix interface characterization No. 3, pp. 423-459, 1992. 233. G. C. Papanicolaou and D G. C. Sihtheoretical and applied fracture mechanics | vol - Theoretical and Applied Fracture Mechanics Volume 75, Pages 1-160 (February 2015)citeulike: theoretical and applied fracture - Articles from the last few issues of Theoretical and Applied Fracture Mechanics Elsevier. Search Export Show Details Hide Detailstheoretical and applied fracture mechanics - Theoretical and applied fracture mechanics. Home. WorldCat Home About WorldCat Help Feedback. Search. Search for Library Items Search for Lists Search formathematical research in materials science: - Fluid Mech. 22:13 34. Denn, M. M. 1992. Pp. 45 49 in Theoretical and Applied of Fracture Mechanics in Modern Technology. G. C problems in materialsrigid-plastic and damage behavior in metal - Theoretical and Applied Fracture Mechanics 18 G.C. Sih, Mechanics of Fracture Theoretical and Applied Fracture Mechanics 18 (1) 31-45 (1992). [21] G.C. Sihfinite element analysis of sheet forming processes - H. D. (1990), Finite element analysis of sheet forming Theoretical and Applied Fracture Mechanics, 1993, Theoretical and Applied Fracture Mechanics,theoretical and applied fracture mechanics | - Theoretical and Applied Fracture Mechanics: Aims & Scopes. Theoretical and Applied Fracture Mechanics' aims & scopes have been re-designed to cover both the theoretical and applied fracture mechanics, 1992- - Not 0.0/5. Retrouvez Theoretical and Applied Fracture Mechanics, 1992-1993 Bound Issues et des millions de livres en stock sur Amazon.fr. Achetez neuf ou d'occasionjournal of applied mathematics - J. R. Rice and G. C. Sih, Plane problems of cracks in dissimilar media, Journal of Applied Mechanics I and mode II, Engineering Fracture Mechanics,publications | multi-scale mechanics of materials - The Multi-Scale Mechanics of Materials Group focuses on the following: Publications; You are here. 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Fracture Mechanics fortheoretical and applied fracture mechanics - Genre/Form: Periodicals P riodiques: Additional Physical Format: Online version: Theoretical and applied fracture mechanics (Online) (DLC) 2006233281the effect of matrix microcracks on the - Engineering Fracture Mechanics, 25: 771-778 . (1993). An Analytical Model Asymptotic Approximations to Crack Problems. In: Sih, C.G. (ed.), Mechanics ofrecent developments of fracture mechanics in - G.C. Sih and E.E. Gdoutos (eds), Mechanics and Physics of Energy Theoretical and Applied Fracture Mechanics 17 Recent developments of fracture mechanics in Greece experimental and theoretical fracture mechanics - Experimental and theoretical fracture mechanics applied to fracture only provides lower bound fracture of Crack Problems, edited by G. C. Sih,energy density theory formulation and - The factor S can increase or decrease depending on the direction of the applied theory formulation and interpretation of Mechanics of Fracture, vols - Sihtheoretical and applied fracture mechanics - Theoretical and Applied Fracture Mechanics. The Mechanics and Physics of Fracture part encourages publication of original research on Material damage leading to: g. c. sih: books, biography, blog, - Visit 's G. C. Sih Page and shop for all G. C. Sih books and other G. C. Sih related products (DVD, CDs, Apparel). Check out pictures, bibliography,theor appl fract mech means theoretical and - Theor Appl Fract Mech is the abbreviation for Theoretical and Applied Fracture Mechanicsa micromechanical analysis of the fracture - fracture problems are common and important, Fracture Mechanics: Fundamentals and M., Chen, C. A micromechanical analysis of the fracture properties oftaylor & francis online :: effect of residual - A. N. 1992. Nonclassical Problems of Fracture Mechanics, Theoretical and Applied Fracture Mechanics, 48: M. K. and Sih, G. C. 1975. Mechanics of Fracture.computational methods for fracture in brittle and - Analysis of three-dimensional fracture mechanics problems: , Theoretical and Applied Fracture Mechanics, G. C. Sih, Strain-energytheoretical and applied fracture mechanics - - The online version of Theoretical and Applied Fracture Mechanics at ScienceDirect Finite fracture mechanics is applied to predicting the reduction in foam| | | - Theoretical & Applied Fracture Mechanics Theoretical and Applied Fracture Mechanics, Vol. 19, 1993, G.C. Sih, Th.B. Kermanidis andtheoretical and applied fracture mechanics, 1987 - Theoretical and Applied Fracture Mechanics, 1987 Bound Issues [G. C. Sih] on . *FREE* shipping on qualifying offers.journal of theoretical and applied mechanics - - Topical problems of composite fracture mechanics are formulated. Sih, G. C., P. C. Paris, G. 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中英文检索表达式
中英文检索表达式摘要:一、引言1.中英文检索表达式的概念2.中英文检索表达式的作用二、中英文检索表达式的构建方法1.布尔操作符2.关键词3.短语4.句子三、中英文检索表达式的应用场景1.文献检索2.网页搜索3.数据挖掘四、中英文检索表达式的优缺点1.优点a.高效性b.准确性c.灵活性2.缺点a.依赖语料库b.受限于语法规则c.不能完全理解语义五、中英文检索表达式的发展趋势1.语义理解技术的进步2.大数据和人工智能的推动3.跨语言检索的发展正文:中英文检索表达式是信息检索领域中一个重要的概念,它可以帮助用户在海量的信息中快速找到自己需要的内容。
中英文检索表达式可以理解为一个查询语句,它通过特定的语法规则和检索技巧,描述用户所需信息的关键特征。
在实际应用中,中英文检索表达式广泛应用于文献检索、网页搜索、数据挖掘等领域。
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list of FEM books and articles
Books∙Finite Element Procedures, K. J. Bathe, Prentice Hall, Englewood Cliffs, NJ, 1996.∙The Finite Element Method: Linear Static and Dynamic Finite Element Analysis, T. J.R. Hughes, Prentice Hall, Englewood Cliffs, NJ, 1987.∙The Finite Element Method, 4th ed., Vol. 1, O. C. Zienkiewicz and R. L. Taylor, McGraw-Hill, London, 1989.∙The Finite Element Method, 4th ed., Vol. 2, O. C. Zienkiewicz and R. L. Taylor, McGraw-Hill, London, 1991.∙Finite Elements of Nonlinear Continua, J. T. Oden, McGraw-Hill, New York, 1972.∙Nonlinear Finite Elements for Continua and Structures, 3rd ed., T. Belytschko, W. K.Liu and B. Moran, John Wiley & Sons, Chichester, UK, 2000.∙Finite Elements: their design and performance, R. H. MacNeal, Marcel Dekker, New York, New York, 1994.∙The Finite Element Analysis of Shells - Fundamentals, D. Chapelle and K. J. Bathe, Springer-Verlag, Berlin Heidelberg, 2003.∙Inelastic Analysis of Solids and Structures, M. Kojic and K. J. Bathe, Springer-Verlag, Berlin Heidelberg, 2005.∙Concepts and Applications of Finite Element Analysis, 4th ed., R. D. Cook, D. S.Malkus, M. E. Plesha and R. J. Witt, John Wiley & Sons, NJ, 2002.∙Finite Element Programming, 4th ed., E. Hinton and D. R. J. Owen, Academic Press, London, 1977.∙The Finite Element Method Displayed, G. Dhatt and G. Touzot, John Wiley & Sons, Norwich, 1984.∙Techniques of Finite Elements, B. Irons and S. Ahmad, John Wiley & Sons, New York, 1981.∙An Introduction to the Finite Element Method, 3rd ed., J. N. Reddy, McGraw-Hill, New York, 2006.∙Numerical methods for non-linear problems, Volume 2: Proceedings of the Second International Conference, Universidad Politecnica de Barcelona, Spain, April 9-13, 1984, C.Taylor, E. Hinton and D. R. J. Owen, Pineridge Press, Swansea, UK, 1984.∙An Introduction to Nonlinear Finite Element Analysis, J. N. Reddy, Oxford University Press, New York, 2004.∙Computer Methods in Structural Analysis, J. L. Meek, Chapman & Hall, London, 1991. ∙Finite Element Method: Basic Technique and Implementation, P. Tong and J. N.Rossettos, MIT Press, Cambridge, Mass., 1977.∙Nonlinear Continuum Mechanics for Finite Element Analysis, 2nd ed., J. Bonet and R.D. Wood, Cambridge University Press, UK, 2008.∙Dynamics of Structures, 2nd ed., R. W. Clough and J. Penzien, McGraw-Hill, New York, 1993.∙Dynamics of Structures: Theory and Applications to Earthquake Engineering, 2nd ed.,A. K. Chopra, Prentice Hall, Upper Saddle River, NJ, 2001.∙Introduction to Finite Element Vibration Analysis, M. Petyt, Cambridge University Press, UK, 1990.∙Fundamentals of Structural Dynamics, 2nd ed., R. R. Craig Jr. and A. J. Kurdila, John Wiley & Sons, New Jersey, 2006.∙Matrix Analysis of Structural Dynamics: Applications and Earthquake Engineering, F.Y. Cheng, Marcel Dekker, New York, 2001.∙Structural Dynamics: Theory and Applications, J. W. Tedesco, W. G. McDougal and C.A. Ross, Addison Wesley Longman, California, 1999.∙Structural Dynamics: Theory and Computation, 5th ed., M. Paz and W. Leigh, Springer Science, New York, 2004.∙Fundamentals of Finite Element Analysis, D. V. Hutton, McGraw-Hill, New York, 2004. ∙Analysis and Design of Elastic Beams - Computational Methods, W. D. Pilkey, John Wiley & Sons, NJ, 2002.∙Matrix Analysis of Framed Structures, 3rd ed., W. Weaver Jr. and J. R. Gere, Kluwer Academic Publishers, Massachusetts, 2001.∙Theory of Matrix Structural Analysis, J. S. Przemieniecki, McGraw-Hill, New York, 1968.∙Structural Analysis and Behavior, F. Arbabi, McGraw-Hill, New York, 1991.∙Matrix Structural Analysis, 2nd ed., W. McGuire, R. H. Gallagher and R. D. Ziemian, John Wiley & Sons, MA, 2000.∙Mechanics of Composite Materials, 2nd ed., R. M. Jones, Taylor & Francis, New York, 1999.∙Theory of Plates and Shells, 2nd ed., S. P. Timoshenko and S. Woinowsky-Krieger, McGraw-Hill, New York, 1959.∙Theory of Elasticity, 3rd ed., S. P. Timoshenko and J. N. Goodier, McGraw-Hill, New York, 1970.∙Strength of Materials, J. P. Den Hartog, Dover Publications, New York, 1977.∙Advanced Strength of Materials, J. P. Den Hartog, Dover Publications, New York, 1987.∙Formulas for Stress, Strain and Structural Matrices, 2nd ed., W. D. Pilkey, John Wiley & Sons, NJ, 2005.∙Roark's Formulas for Stress and Strain, 6th ed., W. C. Young, McGraw-Hill, New York, 1989.∙Matrix Computations, 3rd ed., G. H. Golub and C. F. Van Loan, John Hopkins University Press, Baltimore, 1996.∙Programming the Finite Element Method, 3rd ed., I. M. Smith and D. V. Griffiths, John Wiley & Sons, Chichester, UK, 1998.∙An Introduction to the Finite Element Method: Theory, Programming and Applications,E. G. Thompson, John Wiley & Sons, NJ, 2004.∙Applied Finite Element Analysis, L. J. Segerlind, John Wiley & Sons, New York, 1984. ∙Finite Element Analysis with Error Estimators: An Introduction to the FEM and Adaptive Error Analysis for Engineering Students, J. E. Akin, Elsevier Butterworth-Heinemann, MA, 2005.∙Non-linear Finite Element Analysis of Solids and Structures - Volume 1: Essentials, M.A. Crisfield, John Wiley & Sons, Chichester, UK, 1991.∙Non-linear Finite Element Analysis of Solids and Structures - Volume 1: Advanced Topics, M. A. Crisfield, John Wiley & Sons, Chichester, UK, 1997.∙Theory and Problems of Finite Element Analysis, G. R. Buchanan, Schaum's Outline Series, McGraw-Hill, New York, 1995.∙Theories and Applications of Plate Analysis: Classical, Numerical and Engineering Methods, R. Szilard, John Wiley & Sons, NJ, 2004.∙Fundamental Finite Element Analysis and Applications, M. A. Bhatti, John Wiley & Sons, NJ, 2005.∙Advanced Topics in Finite Element Analysis of Structures, M. A. Bhatti, John Wiley & Sons, NJ, 2006.∙Introduction to Finite Elements in Engineering, 3rd ed., T. R. Chandrupatla and A. D.Belegundu, Prentice Hall, 2002.∙The Finite Element Method for Three-dimensional Thermomechanical Applications, G.Dhondt, John Wiley & Sons, Chichester, UK, 2004.∙Classical and Computational Solid Mechanics, Y. C. Fung, P. Tong, World Scientific Co. Pte. Ltd, UK, 2001.Articles∙R. H. MacNeal and R. L. Harder, A Proposed Standard Set of Problems to Test Finite Element Accuracy, Finite Element in Analysis and Design, North Holland, Vol. 1, pp 3-20, 1985.∙K. J. Bathe, Solution Methods of Large Generalized Problems in Structural Engineering, Report UC SESM 71-20, Civil Engineering Department, University of California, Berkeley, 1971.∙K. J. Bathe, H. Ozdemir and E. L. Wilson, Static and Dynamic Geometric and Material Nonlinear Analysis, Report UC SESM 74-4, Civil Engineering Department, University ofCalifornia, Berkeley, 1974.∙K. J. Bathe, Solution Methods for Large Eigenvalue Problems in Structural Engineering, Report UC SESM 71-20, Civil Engineering Department, University of California, Berkeley, 1971.∙ E. N. Dvorkin and K. J. Bathe, A Continuum Mechanics Based Four-Node Shell Element for General Nonlinear Analysis, Engineering Computations, Vol. 1, pp 77-88, 1984.∙ E. L. Wilson, Structural Analysis of Axisymmetric Solids, AIAA Journal, Vol. 3, No. 12, 1965, pp 2269-2274.∙ E. L. Wilson, Elastic Dynamic Response of Axisymmetric Structures, Report UC SEMM 69-02, Civil Engineering Department, University of California, Berkeley, 1969.∙ D. Chapelle and K. J. Bathe, Fundamental Considerations for the Finite Element Analysis of Shell Structures, Computers & Structures, Vol 66, No. 1, 1998, pp 19-36∙ D. Chapelle and K. J. Bathe, The mathematical shell model underlying general shell elements, Int. J. Numer. Meth. Engng., Vol 48, 2000, pp 289-313∙T. J. R. Hughes, R. L. Taylor and W. Kanoknukulchai, A Simple and Efficient Finite Element for Plate Bending, International Journal for Numerical Methods in Engineering, Vol.11, 1977, pp 1529-1543.∙T. J. R. Hughes and M. Cohen, The 'Heterosis' Finite Element for Plate Bending, Computers & Structures, Vol. 9, 1978, pp 445-450.∙T. J. R. Hughes and T. E. Tezduyar, Finite Elements Based Upon Mindlin Plate Theory With Particular Reference to the Four-Node Bilinear Isoparametric Element, Journal of Applied Mechanics, Vol. 48, 1981, pp 587-596.∙K. J. Bathe and Lee-Wing Ho, A Simple and Effective Element for Analysis of General Shell Structures, Computers & Structures, Vol 13, 1981, pp 673-681∙K. J. Bathe, A. Iosilevich and D. Chapelle, An evaluation of the MITC shell elements, Computers & Structures, Vol 75, 2000, pp 1-30∙S. F. Pawsey, The Analysis of Moderately Thick to Thin Shells by the Finite Element Method, Report UC SESM 70-12, Civil Engineering Department, University of California,Berkeley, 1977.∙J. P. Hollings and E. L. Wilson, 3-9 Node Isoparametric Planar or Axisymmetric Finite Element, Report UC SEMM 78-03, Civil Engineering Department, University of California, Berkeley, 1969.∙R. J. Melosh, Basis for Derivation of Matrices for the Direct Stiffness Method, AIAA Journal, Vol. 1, No. 7, 1963, pp 1631-1637.∙ B. M. Irons, Engineering Applications of Numerical Integration in Stiffness Methods, AIAA Journal, Vol. 4, No. 11, 1966, pp 2035-2037.∙ E.L. Wilson, A. Der Kiureghian, E.P. Bayo, Short Communications A Replacement for the SRSS Method in Seismic Analysis, Earthquake Engineering and Structural Dynamics, Vol.9, 1981, pp 187–194.∙J. S. Archer, Consistent Matrix Formulations for Structural Analysis Using Finite-Element Techniques, AIAA Journal, Vol. 3, No. 10, 1965, pp 1910-1918.。
HRAC-Classification of Herbicides According to Mod
Classification of Herbicides According to Mode of ActionFarmers, advisors and researchers should know which herbicides are best suited to combat specific resistant weeds. To support the use of herbicides suitable for resistance management the enclosed classification of herbicides is proposed.The herbicides are classified alphabetically according to their target sites, modes of action, similarity of induced symptoms or chemical classes.If different herbicide groups share the same mode or site of action only one letter is used. In the case of photosynthesis inhibitors subclasses C1, C2 and C3 indicate different binding behaviour at the binding protein D1 or different classes. Bleaching can be caused by different ways. Accordingly subgroups F1, F2 and F3 are introduced. Growth inhibition can be induced by herbicides from subgroups K1, K2 and K3. Herbicides with unknown modes or sites of action are classified in group Z as "unknown" until they can be grouped exactly.Classification of HerbicidesIn order to avoid confusion with I and O categories J and Q are omitted. New herbicides will be classified in the respective groups or in new groups (R, S, T...).Since the system was in part developed in co-operation with the "Weed Science Society of America (WSSA)" new herbicides should be categorised jointly by HRAC and WSSA.For reference the numerical system of the WSSA is listed, too.The aim of HRAC is to create a uniform classification of herbicide modes of action in as many countries as possible.Such a classification system can be useful for many instances but there are cases where weeds exhibit multiple resistance across many of the groups listed and in these cases the key may be of limited value.The system itself is not based on resistance risk assessment but can be used by the farmer or advisor as a tool to choose herbicides in different mode of action groups, so that mixtures or rotations of active ingredients can be planned.For a figure of the chemical groups involved each HRAC Group, click on the letter in the table below. A synoptic graphic of the HRAC groups is also available.The WSSA and HRAC systems differ in minor ways. Herbicides in italics are listed on the HRAC classification system but are not listed on the WSSA classification.January 2005 HRAC: Herbicide classificationRemarks:According to information and comments following herbicides are classified in the January 2005 version in HRAC (WSSA) groups:B (2): cancelled: #9; #9; procarbazone Approved ISO name: propoxycarbazone E (14): cancelled: pyrazogyl Approved name: pyraclonil。
CRITICAL ANALYSIS
CRITICAL ANALYSISA critical analysis paper asks the writer to make an argument about a particular book, essay, movie, etc. The goal is two fold: one, identify and explain the argument that the author is making, and two, provide your own argument about that argument. One of the key directions of these assignments is often to avoid/minimize summary – you are not writing a book report, but evaluating the author’s argument.Potential points of criticismSometimes it can seem intimidating to “criticize” a b ook or article; after all, they are professors and experienced policymakers. However, part of this exercise is to expose the fact that even though these authors are highly qualified, they are still advancing an argument and providing evidence--their aim is to persuade you that their argument is true, not to just present facts. Once you recognize that these authors are making arguments, you can analyze whether or not you find their argument compelling. Following are some possible questions you could ask to evaluate arguments:• Theoretical questions – How does the author understand the situation? What is his/her theoretical background? How would this influence their view of the situation?• Definitional questions - Are all the concepts in the text clear? Does the author define a concept vaguely to allow it to travel across different situations? If a concept can relate two seemingly different situations, is the concept meaningful?• Evidence questions:- Does the author’s evidence support their argument? Do they have enough specific evidence to prove the more general point?- Does the author under-emphasize or ignore evidence that is contrary to their argument? - Is the evidence credible? Can you identify a bias in the evidence?Was the study done by a political action committee, and environmental NGO, or a non- partisan research group? How might a group affiliation or funding influence the outcome of research?• Implication/Policy relevance questions – What are the implications of this argument? Are those implications positive or negative? How has the author dealt with this issue? • Other approaches:Is the author’s argument consistent throughout the book? Or, does the conclusion seem to offer a different argument than he/she presented in the introduction?Does the author’s background have important implications for their argument?Do the specific language choices of the author betray a certain ideology or bias, or frame the argument in a certain way?Structuring a Critical Analysis PaperMost critical analysis papers begin with a short summary of the work and then dive in to the argument. Since most of these paper assignments are short, it is important to be concise in all parts of your analysis. Writing an outline (and following it) is crucial to remain focused on your argument and avoid summary or irrelevant description. Following is a sample outline for a critical analysis paper:I. Introductiona. Identify the work being criticizedb. Present thesis – argument about the workc. Preview your argument – what are the steps you will take to prove yourargumentII. Short summary of the worka. Does not need to be comprehensive – present only what the reader needs toknow to understand your argumentIII. Your argumenta. Your argument will likely involve a number of sub-arguments –mini-theses youprove to prove your larger argument true. For example, if your thesis was that the author’s presumption that the world will soon face a “clash of civilizations” isflawed because he inadequately specifies his key concept, civilizations, you might prove this by:i. Noting competing definitions of civilizationsii. Identifying how his examples do not meet the example of civilizationsiii. Argue that civilization is so broad and non-specific that it is not usefulb. This should be the bulk of the paper – Your professor wants to read yourargument about the work, not a summary.IV. Conclusiona. Reflect on how you have proven your argument.b. Point out the importance of your argumentFinal Reminders• Even though you are potentially only referring to one source, you still need to cite your information, using either parenthetical citation or footnotes/endnotes.• Double check the assignment to make sure you have covered all the points that yourprofessor has asked.。
Chassis_Web
CHASSISFEV ChassisReliable Partner in Chassis DevelopmentSOPRelease2FEV Chassis Applications and ActivitiesCompliance Prototype WorkshopValidationFEV Chassis Resources5Test Facilities: W orkshop with divided areas, allowing confidentiality for each customer P rivate test track for initial evaluation of test vehicles M easurement equipment for all relevant vehicle dynamic parameters, such as: Steering wheel angle Steering wheel torque A ll 6 DOF for the complete vehicle (position, speed and acceleration) Brake pedal force and travel A dditional equipment for measuring force, displacement or acceleration regarding any desired component or system of the vehicleCAE:ADAMS/ADAMS Car, Motion View Nastran, Ansys Hypermesh, I-DEAS Matlab/SimulinkDesign Of Experiments (DOE)In-house code for quick and easy set-upFEV ChassisBenchmarks and Target SettingTo support these efforts, a variety of test tracks and general purpose roads are located near Aachen, Germany, including the German Autobahn and the famous Nürburgring.FEV ChassisTire Test Competence CenterWell proven test procedures Fundamental tire knowledge for making the right decisionsNürburgring – …The green hell“FEV ChassisFrom Concept to SOPFEV ChassisFrom Subjective Impressions to Objective Parameters Driving ManeuversFEV ChassisMechatronicsAll Wheel Steering Active DampingABS/ESPFEV ChassisNoise Vibration Harshness (NVH)© V o l k s w a g e n A GFEV ChassisSimulationScreenshot: ADAMS-SoftwareFEV ChassisWorkshops and Training15Based on deep knowledge of vehicle dynamics and market requirements, FEV organizes workshops under a variety of conditions that are suited to fit your company’s needs.Scheid Motorsport Racing Team in actionBodyFront axle Rear axleFull vehicle。
asymptotic analysis缩写
asymptotic analysis缩写
Asymptotic Analysis 的意思是 "极限分析",指的是在算法或
数学模型中,当样本数量趋近于无穷大时,所计算的结果或估计值趋
向于某个确定的极限值,通常称为无穷大极限或无穷级数。
这种分析方法常用于对连续函数、概率分布等进行分析和估计。
例如,在数学中,当函数 $f(x)$ 在 $x=a$ 处取得极小值时,可
以通过引入 $a$ 的无穷大来估计 $f(x)$ 的值。
这个估计值可以表示为 $f(a) approx lim_{x to a^-} f(x)$。
其中,$lim_{x to a^-} f(x)$ 表示当 $x$ 趋近于 $a$ 时,$f(x)$ 的值趋近于某个值,这个值称为极限值。
Asymptotic Analysis 是一种重要的数学分析方法,可以帮助研究者更好地理解并预测复杂系统的性能和行为,尤其是在当样本数量趋近于无穷大时,系统的行为可能会表现出非常惊人的规律和特性。
Analyse
Le centre d’appels Contact +ELEMENTS DE CORRECTION (à rédiger)Le pilotage d’une organisation1.Caractérisez l’organisation selon les critères suivants : type d’entreprise, taille, statutjuridique, nationalité, ressources, champ d’action, mode de coordination. (5 points)(remarque : faites apparaître les sous-titres, soulignez-les et rédigez ensuite)Type d’entreprise : C’est une entreprise de service, des donneurs d’ordre lui sous-traitent leurs contacts clientèle. Taille : Il s’agit d’une Petite entreprise pour le secteur puisqu’elle a un Effectif de 11 salariésStatut juridique : Contact+ a choisi la SARL (société à responsabilité limitée) comme forme juridique Nationalitéet Champ d’action : De nationalitéfrançaise, elle est située dans le département du Nord. Elle propose ses services au niveau national et européen (Belgique).Centre d’appel (vente à distance)Ses Ressources sont:-financières : Capital de 45 000 €-matérielles : plateforme téléphonique organisée en bureaux paysagers et équipée de 18 postes avec serveur CTI-humaines : 10 téléconseillers polyvalents dont 3 parlent flamand, une responsable d’équipe et le dirigeant de l’entreprise.Mode de coordination : supervision directe2. Présentez les menaces et opportunités de l’environnement. (3 points)(remarque : rédigez, pour chaque question, une phrase d’introduction qui reprend les éléments de la question)Identifier les menaces et les opportunités de l’environnement consiste à procéder au diagnosticconcurrentiel. (5 points)Dans le cadre d’un questionnement progr essif cette question vient compléter la précédente. En effet, elle invi te les élèves à repérer les forces et faiblesses de l’entreprise qui permettent de dégager l’avantage concurrentiel.Avantage concurrentiel : sur la stratégie de niche choisie par M. Lourme, il dispose d’un service personnalisé (chaque téléconseiller est l’interlocuteur unique po ur les clients du donneur d’ordre) et de qualité.4. Identifiez les objectifs stratégiques de M. Lourme et justifiez leur pertinence. (4 points)Cette question a pour objectif de repérer dans un document l’objectif principal du dirigeant qui se décline en sous-objectifs. Il ne s’agit pas simplement de lister les objectifs mais de montre r la cohérence par rapport à l’analyse effectuée dans les questions précédentes.L’objectif de M. Lourme est de développer les appels sortants. Ceci pour 2 raisons : -ils correspondent àun service àforte valeur ajoutée et représentent seulement 40 % de son CA pour 2005.-la concurrence internationale sur les coûts est moins exacerbée sur les appels sortants que sur les appels entrants à faible valeur ajoutée.Cet objectif stratégique se décline en 3 sous objectifs :-développer le secteur associatif, encore peu présent dans son portefeuille de clients sauf pour la gestion de numéro spécial. Ce secteur utilise de plus en plus la téléphonie pour convaincre ou informer des adhérents-développer un nouveau service : prospection de clientèle flamande. Ce service correspond àun besoin d’entreprises françaises n’ayant pas les compétences linguistiques.-obtenir une certification qualité (Qualiserv). Cette certification s’avère néces saire pour renforcer l’image de l’entreprise.5. Analysez les résultats de l’opération ASSUR. Expliquez et justifiez les actions correctrices décidées par M. Lourme. (3 points).La performance des 3 téléconseillers est mesurée à partir de critère productivité ? Des obj ectifs opérationnels sont fixés pour l’ensemble de l’équipe.Analyse des résultats :-objectif de 30 % de RDV facturés par rapport aux rendez-vous pris est atteint puisque le taux est de 40%.Cela signifie que les RDV pris sont de qualité.-Les 2 autres objectifs ne sont pas atteints : seulement 6 % au lieu de 20 % pour le taux de RDV pris sur les appels émis et 2.5 % au lieu de 10 %pour les RDV facturés sur les appels émis.-On constate aussi une disparité des performances par salarié : les performances de Maude sont inférieures aux autres. Son taux de RDV pris sur les appels émis est quasiment identique à celui de Leila (qui est la plus performante) mais son taux de RDV facturés / RDV pris est très faible. Cela signifie que ses rendez-vous pris ne sont pas de bonne qualité. Le besoin du client n’a pas été assez cerné.Actions correctrices de M. Lourme :-retravailler sur l’argumentaire et modifier les plages horaires d’appel dans le but d’améliorer l’objectif de RDV pris/appels émis-améliorer la connaissance du produit pour obtenir une meilleure performance sur le taux de RDV facturés / appels émis-ses actions sont collectives, alors que les performances individuelles sont inégales. Maude a des résultats nettement moins satisfaisants que ses collègues. M. Lourme a choisi des actions correctrices collectives peut-être pour renforcer l’esprit d’équipe sur une mission. Cependant la mise en évidence de la performance satisfaisante d’un salarié peut être source de motivation (on pense à Leila).。
SpatialAnalyzer User Manual
131L eica T -ScanInterfaceHardware SetupThis Quick-start guide can be used for the initial setup of the Leica T-Scan5 system for operation within SA in conjunction with either an AT960 or AT901. ■Set up the unit following the manufacturer’s directions. The AT960 users the MCA-47 cable between the T-Scan and Tracker controller’s signal port (the trigger port is not used). The AT901 uses the MCA-36 cable which has a dual end for the tracker sig-nal line and trigger connections . A single network cable should be connected from the computer to the t-scan controller and a second Ethernet cable connects the tracker and t-scan system along with a signal cable (Figure 3-119).Figure 3-119. A T901CableConfiguration ■Ensure that you have the T-Scan License key to operate the sys-tem.■Ensure that you have the USB drive containing the *.mtx and*.emsys fi les (calibration fi les) which should also contain theLeica setup manuals and a version of the required software (T-Scan Collect or T-Scan Interface and TwinCat Engineering).Tracker Confi gurationThe T-Scan target defi nition must be defi ned on the tracker controller.The procedure to do so depends on the tracker type:■AT960 Confi guration:1. Open Tracker Pilot, and connect to the AT960 using the “Ad-vanced” permissions (if you need the current Tracker Pilot youcan browse directly to http://192.168.0.1 (or the trackers IP)and download Tracker Pilot from the controller).2. Go to targets and ensure the T-Scan is defi ned. If not use theImport Targets button and browse to the *.emsys fi le for thet-scan provided on the USB disk.3. Once defi ned Exit Tracker Pilot.■AT901 Confi guration:1. Open the Emscon TransferTool, enter the tracker IP and pressTest.2. In the Transfer to emScon section press Parameter File andbrowse to the *.emsys fi le for the t-scan provided on the USBdisk.3. Save and ExitSoftware Setup and Initial confi gurationDownload and install the current version of T-Scan Collect which canbe found on our website here:https:///ftp/SA/Install/Driver%20Downloads/Laser%20Trackers/Leica/TScan5/The current version is: T-Scan Collection 10.3.7.39Directory Setup:1. Determine if you have a license key for either the T-Scan In-terface or the full T-Scan Collect Software (Either one or theother should be installed as require but not both), and installthe correct one on your machine.2. Transfer the *.mtx fi les from the USB drive to the T-Scan direc-tory. T-Scan looks for the fi les in a particular spot (C:\Program-Data\Steinbichler\T-SCAN\Calibration) you will need to buildthe Calibration directory and place the fi les in this folder.132TScanCol.ini Edit Process:1. Within the C:\ProgramData\Steinbichler\T-SCAN\T-SCAN In-terface 10.30\ folder (or T-Scan Collect 10.3 folder) you willfi nd a fi le called “TScanCol.ini”. Open and edit this fi le as fol-lows (it’s a long fi le so scroll through it to the correct section):2. Verify the Specifi c IP address of your tracker (192.168.0.1 bydefault)3. Enter the TrackerInterfaceType (EMSCON for AT901 or LMF forAT960)4. Enter the ScannerAlignmentBaseName (such as LLS1100271).This number is on the front of the T-Scan.5. Enter the AMSNETID for the T-Scan Controller. W hich should beprinted on the front of the controller (Such as 5.29.142.116.1.1)6. Once complete save and close the TScanCol.ini fi le (see Figure3-120).Figure 3-120. T ScanCol.ini fileInitial Network Confi guration:1. Confi gure your local area network connection as follows:2. Go to Control Panel> Network and Internet> Network andSharing Center3. Open the Local Area Network Connection properties (ensurethe cable is connected to the T-Scan Controller if you don’tsee it)4. Go to the properties for the Internet Protocol Version 4 (TCP/IPv4)1335. Set the IP address to a static IP and use the following IP:10.168.2.2XX (enter 201-250 only) and subnet 255.255.255.0.TwinCAT Software:1. Install the TwinCAT Engineering Software (which will managethe dual network communication between the tracker andthe T-SCAN system). This software should be available on yourUSB drive, and is also on our webpage here:https:///ftp/SA/Install/Driver%20Downloads/Laser%20Trackers/Leica/TScan5/The current version is: TC31-ADS-Setup.3.1.4020.32.exe2. From the Windows task bar launch the TwinCAT System Man-ager and select Change AMS NetID and confi gure it to talk tothe T-Scan Controller. This will require a system restart (Figure3-121).Figure 3-121. S etting the AMSNetID to talk to your controller.3. Return to the TwinCAT Confi g Mode in the windows start menuand select Router>Edit Routes then choose Add...(see Figure3-122):134135Figure 3-122. T winCAT SystemManager and Target Selection.4. Perform a Broadcast Search and look for the AMS NetID of thecontroller which should show up on the network list. When it does, select it and select Add Route (see Figure 3-123):Figure 3-123. R outeSelection5. Enter the Login Information. The login selection depends onthe controller you have (Figure 3-124).Figure 3-124. T-Scan controllertypes.For Rev 2.0 controllers by default you will enter “Administrator” for theUser and “1” for the password, and make sure that the TwinCAD 2.xPassword Format is unchecked (Figure 3-125) ArrayFigure 3-125. R ev 2.0 passwordentry.For Rev 1.x controls leave both the User and the Password blank butcheck the TwinCAT 2.x Password Format check box. Then Press Okay.The route should then be displayed and marked with an X in theroute’s selection dialog(Figure 3-126).136137Figure 3-126. C onnected statusdisplay.Final Network Setup1. Return to properties for the Internet Protocol Version 4 (TCP/IPv4)2. Press Advanced and add a second IP (for the tracker). En-ter 192.168.0.XXX (enter 2-250 for the IP), again using 255.255.255.0 for the subnet mask(see Figure 3-127).Figure 3-127. N etwork Confi gu-ration settings138 3. Click OK and close out of all dialogs and exit out of the net-work Sharing Center when done.You can double check that you have a successful connection to both the T-Scan Controller and the Tracker and that the system is ready to go by opening T-Scan Collect directly. Once you see the Status indi-cator in the bottom right report a green connected status for both devices you can close T-Scan Collect and connect within SA.Running the T-Scan Interface in SA:1. Add the Instrument (Instrument>Add…) and choose the ap-propriate Leica Tracker (AT901 or AT960)2. Start the Interface through the menu Instrument>Run Inter-face Module and choose Leica TScan. (Do not connect using the Laser Tracker Interface) (see Figure 3-128):Figure 3-128.F g re r e 312882T-Scan Interface in SA:When you start the Leica T-Scan interface it will automatically con-nect to either T-Scan Collect or the T-Scan Interface which will run in the background. The T-Scan interface in SA is designed to be as sim-ple as possible while providing full control (see Figure 3-129):Figure 3-129.F igure 3-129. T-Scan Interface■Collection and Cloud Name control is provided and a newcloud name will be incremented automatically with each sepa-rate scan.■ A progress report will be displayed in the connection window■T-Scan control is provided through the Settings button. Con-trol for both the TS50 and the new Tscan5 is available in sec-tions in the left hand column, the following Tscan5 controls areprovided:■Exposure Time can be set manually from 0.25 to 20.0 mil-liseconds■Line Width Set can be set from 0-12 (0=100%, 12=40%).This reduces the width of the line as you increase the integervalue (set as an integer for scripting purposes).■Refl ection Filter intensity setting (1 = Standard, 2 = Low, 3= Medium, 4 = High). Again this value is set as a simple integerfor easy scripting control.T-Scan MP Controls SA:Leica T-ScanIncrement Group/Cloud Name Increment the Current Group/Cloud Name by 1. This name is used for clouds when scanning.Is Laser Locked Succeeds if the laser is locked. Fails if not.Set Scan Point To Point Distance []Set Point to Point Distance to that designated by [] mm ([] notpart of string)Set Scan Line To Line Distance []Set Line to Line Distance to that designated by [] mm ([] not partof string)139140(Figure 3-130).3. Figure 3-130. S tarting the LeicaAutomation Interface.In the Connect dialog, select the tracker you’d like to connectto (Figure 3-131).141CHAPTER 3 ■ MEASURING WITH LASER TRACKERS 4. Figure 3-131. C onnecting to atracker.The Leica AIC Driver interface will appear, automatically con-nect to the AIC, and immediately be ready to use. Note that the AIC Driver will detect the current AI Controller’s connec-tion to hardware at the Multiplexer--it is the T-Scan in this case (Figure 3-132).Figure 3-132. T he AIC Driverwindow.Using the InterfaceEach tracker in use requires an assigned IP address and collection/in-dex, which indicates which instrument in the SA fi le is associated with the corresponding hardware. Use the radio button to switch between diff erent trackers.SPATIALANALYZER USER MANUALAll settings appropriate to the current device will be automaticallyset. Measurement parameters can be set via Measurement Plans.■The R ecord Position button is used to teach positions for auto-matically locking on the T-Scan via an MP command. TheCollection::Group::Target name is used for the storage of theauto-lock position in SA.■The Release Motors button will release the motors on the activetracker so that it can be pointed by hand.■The Find Refl ector button will initiate a search for a refl ector in or-der to lock onto the selected device. The distance fi eld next tothis button is used to provide the controller with an idea onhow far to search for the refl ector based on its distance fromthe tracker.Running the AIC Driver In Automation ModeThe Program I/O button is used to program the digital I/O signals forAutomation Mode. In this mode, the AIC Interface expects to receivesignals from the robot, and will send signals to the robot, for hand-shaking. The Program I/O button allows communication between theAIC interface and the device with which it is working--typically a ro-bot. You can defi ne the meaning for up to 6 input channels coming infrom the robot, and up to 3 channels going out to the robot (Figure3-133).Figure 3-133. P rogramming theI/O.A series of Instrument Operational Check Measurement Plancommand strings are available for interacting with the AIC in automa-tion mode. Refer to the “MP Command Reference” document for de-tails.142。
latent class model
Latent Class ModelsbyJay Magidson, Ph.D.Statistical Innovations Inc.Jeroen K. Vermunt, Ph.D.Tilburg University, the NetherlandsOver the past several years more significant books have been published on latent class and other types of finite mixture models than any other class of statistical models. The recent increase in interest in latent class models is due to the development of extended computer algorithms, which allow today's computers to perform latent class analysis on data containing more than just a few variables. In addition, researchers are realizing that the use of latent class models can yield powerful improvements over traditional approaches to cluster, factor, regression/segmentation, as well as to multivariable biplots and related graphical displays.What are Latent Class Models?Traditional models used in regression, discriminant and log-linear analysis contain parameters that describe only relationships between the observed variables. Latent class (LC) models (also known as finite mixture models) differ from these by including one or more discrete unobserved variables. In the context of marketing research, one will typically interpret the categories of these latent variables, the latent classes, as clusters or segments (Dillon and Kumar 1994; Wedel and Kamakura 1998). In fact, LC analysis provides a powerful new tool to identify important market segments in target marketing. LC models do not rely on the traditional modeling assumptions which are often violated in practice (linear relationship, normal distribution, homogeneity). Hence, they are less subject to biases associated with data not conforming to model assumptions. In addition, LC models have recently been extended (Vermunt and Magidson, 2000a, 2000b) to include variables of mixed scale types (nominal, ordinal, continuous and/or count variables) in the same analysis. Also, for improved cluster or segment description the relationship between the latent classes and external variables (covariates) can be assessed simultaneously with the identification of the clusters. This eliminates the need for the usual second stage of analysis where a discriminant analysis is performed to relate the cluster results to demographic and other variables.Kinds of Latent Class ModelsThree common statistical application areas of LC analysis are those that involve1)clustering of cases,2)variable reduction and scale construction, and3)prediction.This paper introduces the three major kinds of LC models:•LC Cluster Models,•LC Factor Models,•LC Regression Models.Our illustrative examples make use of the new computer program (Vermunt and Magidson, 2000b) called Latent GOLD®.LC Cluster ModelsThe LC Cluster model:•identifies clusters which group together persons (cases) who share similar interests/values/characteristics/behavior,•includes a K-category latent variable, each category representing a cluster. Advantages over traditional types of cluster analysis include:•probability-based classification: Cases are classified into clusters based upon membership probabilities estimated directly from the model,•variables may be continuous, categorical (nominal or ordinal), or counts or any combination of these,•demographics and other covariates can be used for cluster description.Typical marketing applications include:•exploratory data analysis,•development of a behavioral based and other segmentations of customers and prospects.Traditional clustering approaches utilize unsupervised classification algorithms that group cases together that are "near" each other according to some ad hoc definition of "distance". In the last decade interest has shifted towards model-based approaches which use estimated membership probabilities to classify cases into the appropriate cluster. The most popular model-based approach is known as mixture-model clustering, where each latent class represents a hidden cluster (McLachlan and Basford, 1988). Within the marketing research field, this method is sometimes referred to as “latent discriminant analysis” (Dillon and Mulani, 1999). Today's high-speed computers make these computationally intensive methods practical.For the general finite mixture model, not only continuous variables, but also variables that are ordinal, nominal or counts, or any combination of these can be included. Also, covariates can be included for improved cluster description.As an example, we used the LC cluster model to develop a segmentation of current bank customers based upon the types of accounts they have. Separate models were developed specifying different numbers of clusters and the model selected was the one that had the lowest BIC statistic.This criteria resulted in 4 segments which were named:1)Value Seekers (15% of customers),2)Conservative Savers (35% of customers),3)Mainstreamers (40% of customers),4)Investors (10% of customers).For each customer, the model gave estimated membership probabilities for each segment based on their account mix. The resulting segments were verified to be very homogeneous and to differ substantially from each other not only with respect to their mix of accounts, but also with respect to demographics, and profitability. In addition, examination of survey data among the sample of customers for which customer satisfaction data were obtained found some important attitudinal and satisfaction differences between the segments as well. Value seekers were youngest and a high percentage were new customers. Basic savers were oldest.Investors were the most profitable customer segment by far. Although only 10% of all customers, they accounted for over 30% of the bank’s deposits. Survey data pinpointed the areas of the bank with which this segment was least satisfied and a LC regression model (see below) on follow-up data related their dissatisfaction to attrition. The primary uses of the survey data was to identify reasons for low satisfaction and to develop strategies of improving satisfaction in the manner that increased retention.This methodology of segmenting based on behavioral information available on all customers offers many advantages over the common practice of developing segments from survey data and then attempting to allocate all customers to the different clusters. Advantages of developing a segmentation based on behavioral data include:•past behavior is known to be the best predictor of future behavior,•all customers can be assigned to a segment directly, not just the sample for which survey data is available,•improved reliability over segmentations based on attitudes, demographics, purchase intent and other survey variables (when segment membership is based on survey data,a large amount of classification error is almost always present for non-surveyedcustomers) .LC Factor ModelsThe LC Factor model:•identifies factors which group together variables sharing a common source of variation,•can include several ordinal latent variables, each of which contains 2 or more levels,•is similar to maximum likelihood factor analysis in that its use may be exploratory or confirmatory and factors may be assumed to be correlated or uncorrelated(orthogonal).Advantages over traditional factor analysis are:•factors need not be rotated to be interpretable,•factor scores are obtained directly from the model without imposing additional assumptions,•variables may be continuous, categorical (nominal or ordinal), or counts or any combination of these,•extended factor models can be estimated that include covariates and correlated residuals.Typical marketing applications include:•development of composite variables from attitudinal survey items,•development of perceptual maps and other kinds of biplots which relate product and brand usage to behavioral and attitudinal measures and to demographics,•estimation of factor scores,•direct conversion from factors to segments.The conversion of ordinal factors to segments is straightforward. For example, consider a model containing 2 dichotomous factors. In this case, the LC factor model provides membership classification probabilities directly for 4 clusters (segments) based on the classification of cases as high vs. low on each factor: segment 1 = (low, low); segment 2 = (low, high); segment 3 = (high, low) and segment 4 = (high, high). Magidson and Vermunt (2000) found that LC factor models specifying uncorrelated factors often fit data better than comparable cluster models (i.e., cluster models containing the same number of parameters).Figure 1 provides a bi-plot in 2-factor space of lifestyle interests where the horizontal axis represents the probability of being high on factor 1 and the vertical axis the probability of being high on factor 2. The variable AGE was included directly in the LC Factor model as a covariate and therefore shows up in the bi-plot to assist in understanding the meaning of the factors. For example, we see that persons aged 65+ are most likely to be in the (low, high) segment, as are persons expressing an interest in sewing. As a group, their (mean) factor scores are (Factor 1, Factor 2) = (.06, .67).Since these factor scores have a distinct probabilistic interpretation, this bi-plot represents an improvement over traditional biplots and perceptual maps (see Magidson and Vermunt 2000). Individual cases can also be plotted based on their factor scores.Figure 1: Bi-plot for life-style dataThe factor model can also be used to deal with measurement and classification errors in categorical variables. It is actually equivalent to a latent trait (IRT) model without the requirement that the traits be normally distributed.LC Regression ModelsThe LC Regression model, also known as the LC Segmentation model:• is used to predict a dependent variable as a function of predictors,• includes an R-category latent variable, each category representing a homogeneous population (class, segment),• different regressions are estimated for each population (for each latent segment),• classifies cases into segments and develops regression models simultaneously.Advantages over traditional regression models include:• relaxing the traditional assumption that the same model holds for all cases (R=1)allows the development of separate regressions to be used to target each segment,• diagnostic statistics are available to determine the value for R,Factor10.00.20.40.60.8 1.0Factor21.00.80.60.40.20.0AGECAMPINGHUNTINGFISHINGWINESKNITTINGSEWINGFITNESSTENNISGOLFSKIBIKINGBOATINGGARDENTRAVEL 18-2425-3435-4445-5455-6465+camp huntfish wines knit sew fitness tennis golf ski bikeboat gardentravel•for R > 1, covariates can be included in the model to improve classification of each case into the most likely segment.Typical marketing applications include:•customer satisfaction studies: identify particular determinants of customer satisfaction that are appropriate for each customer segment,•conjoint studies: identify the mix of product attributes that appeal to different market segments,•more generally: identify segments that differ from each other with respect to some dependent variable criterion.Like traditional regression modeling, LC regression requires a computer program. As LC regression modeling is relatively new, very few programs currently exist. Our comparisons between LC regression and traditional linear regression are based on the particular forms of LC regression that are implemented in the Latent GOLD® program. For other software see Wedel and DeSarbo (1994) and Wedel and Kamakura (1998). Typical regression programs utilize ordinary least squares estimation in conjunction with a linear model. In particular, such programs are based on two restrictive assumptions about data that are often violated in practice:1)the dependent variable is continuous with prediction error normally distributed,2)the population is homogeneous - one model holds for all cases.LC regression as implemented in the Latent GOLD® program relaxes these assumptions: 1) it accommodates dependent variables that are continuous, categorical (binary, polytomous nominal or ordinal), binomial counts, or Poisson counts,2) the population needs not be homogeneous (i.e., there may be multiple populations as determined by the BIC statistic).One potential drawback for LC models is that there is no guarantee that the solution will be the maximum likelihood solution. LC computer programs typically employ the EM or Newton Raphson algorithm which may converge to a local as opposed to a global maximum. Some programs provide randomized starting values to allow users to increase the likelihood of converging to a global solution by starting the algorithm at different randomly generated starting places. An additional approach is to use Bayesian prior information in conjunction with randomized starting values which eliminates the possibility of obtaining boundary (extreme) solutions and reduces the chance of obtaining local solutions. Generally speaking, we have achieved good results using 10 randomized starting values and small Bayes constants (the default option in the Latent GOLD program).In addition to using predictors to estimate separate regression model for each class, covariates can be specified to refine class descriptions and improve classification of cases into the appropriate latent classes. In this case, LC regression analysis consists of 3 simultaneous steps:1)identify latent classes or hidden segments2)use demographic and other covariates to predict class membership, and3)classify cases into the appropriate classes/segmentsDependent variables may also include repeated/correlated observations of the kind often collected in conjoint marketing studies where persons are asked to rate different product profiles. Below is an example of a full factorial conjoint study designed to assist in the determination of the mix of product attributes for a new product.Conjoint Case StudyIn this example, 400 persons were asked to rate each of 8 different attribute combinations regarding their likelihood to purchase. Hence, there are 8 records per case; one record for each cell in this 2x2x2 conjoint design based on the following attributes:•FASHION (1 = Traditional; 2 = Modern),•QUALITY (1 = Low; 2 = High),•PRICE (1 = Lower; 2 = Higher) .The dependent variable (RATING) is the rating of purchase intent on a five-point scale. The three attributes listed above are used as predictor variables in the model and the following demographic variables are used as covariates:•SEX (1 = Male; 2 = Female),•AGE (1 = 16-24; 2 = 25-39; 3 = 40+).The goal of a traditional conjoint study of this kind is to determine the relative effects of each attribute in influencing one’s purchase decision; a goal attained by estimating regression (or logit) coefficients for these attributes. When the LC regression model is used with the same data, a more general goal is attained. First, it is determined whether the population is homogeneous or whether there exists two or more distinct populations (latent segments) which differ with respect to the relative importance placed on each of the three attributes. If multiple segments are found, separate regression models are estimated simultaneously for each. For example, for one segment, price may be found to influence the purchase decision, while a second segment may be price insensitive, but influenced by quality and modern appearance.We will treat RATING as an ordinal dependent variable and estimate several different models to determine the number of segments (latent classes). We will then show how this methodology can be used to describe the demographic differences between these segments and to classify each respondent into the segment which is most appropriate. We estimated one- to four-class models with and without covariates. Table 1 reports the obtained test results. The BIC values indicate that the three-class model is the best model (BIC is lowest for this model) and that the inclusion of covariates significantly improves the model.Table 1: Test results for regression models for conjoint dataModelLog-likelihood BIC-valueNumber ofparametersWithout covariatesOne segment-440288467Two segments-4141831915Three segments-4087831223Four segments-4080834631With covariatesTwo segments-4088828418Three segments-4036824629Four segments-4026829340The parameter estimates of the three-class model with covariates are reported in Tables 2 and 3 and 4. As can be seen from the first row of Table 2, segment 1 contains about 50% of the subjects, segment 2 contains about 25% and segment 3 contains the remaining 25%. Examination of class-specific probabilities shows that overall, segment 1 is least likely to buy (only 5% are Very Likely to buy) and segment 3 is most likely (21% are Very Likely to buy).♦Table 2: Profile outputClass 1Class 2Class 3Segment Size0.490.260.25RatingVery Unlikely0.210.100.05Not Very Likely0.430.200.12Neutral0.200.370.20Somewhat Likely0.100.210.43Very Likely0.050.110.21♦Table 3: Beta's or parameters of model for dependent variableClass 1Class 2Class 3Wald p-value Wald(=)p-value Fashion 1.97 1.140.04440.19 4.4e-95191.21 3.0e-42Quality0.040.85 2.06176.00 6.5e-38132.33 1.8e-29Price-1.04-0.99-0.94496.38 2.9e-1070.760.68The beta parameter for each predictor is a measure of the influence of that predictor on RATING. The beta effect estimates under the column labeled Class 1 suggest that segment 1 is influenced in a positive way by products for which FASHION = Modern (beta = 1.97) and in negative way by PRICE = Higher (beta = -1.04), but not by QUALITY (beta is approximately 0). We also see that segment 2 is influenced by all 3 attributes, having a preference for those product choices that are modern (beta = 1.14), high quality (beta = .85) and lower priced (beta = -0.99). Members of segment 3 preferhigh quality (beta = 2.06) and the lower (beta = -.94) product choices, but are not influenced by FASHION.Note that PRICE has more or less the same influence on all three segments. The Wald (=) statistic indicates that the differences in these beta effects across classes are not significant (the p-value = .68 which is much higher than .05, the standard level for assessing statistical significance). This means that all 3 segments exhibit price sensitivity to the same degree. This is confirmed when we estimate a model in which this effect is specified to be class-independent. The p-value for the Wald statistic for PRICE is2.9x10-107 indicating that the amount of price sensitivity is highly significant.With respect to the effect of the other two attributes we find large between-segment differences. The predictor FASHION has a strong influence on segment 1, a less strong effect on segment 2, and virtually no effect on segment 3. QUALITY has a strong effect on segment 3, a less strong effect on segment 2, and virtually no effect on segment 1. The fact that the influence of FASHION and QUALITY differs significantly between the 3 segments is confirmed by the significant p-values associated with the Wald(=) statistics for these attributes. For example, for FASHION, the p-value = 3.0x10-42.The beta parameters of the regression model can be used to name the latent segments. Segment 1 could be named the “Fashion-Oriented” segment, segment 3 the “Quality-Oriented” segment, and segment 2 is the segment that takes into account all 3 attributes in their purchase decision.♦Table 4: Gamma's: parameters of model for latent distributionClass 1Class 2Class 3Wald p-valueSexMale-0.560.71-0.1524.47 4.9e-6Female0.56-0.710.15Age16-250.84-0.59-0.2453.098.1e-1126-40-0.320.59-0.2740+-0.520.010.51The parameters of the (multinomial logit) model for the latent distribution appear in Table 4. These show that females have a higher probability of belonging to the “Fashion-oriented” segment (segment 1), while males more often belong to segment 2. The Age effects show that the youngest age group is over-represented in the “Fashion-oriented”segment, while the oldest age group is over-represented in the “Quality oriented”Segment.ConclusionsWe introduced three kinds of LC models and described applications of each that are of interest in marketing research, survey analysis and related fields. It was shown that LC analysis can be used as a replacement for traditional cluster analysis techniques, as a factor analytic tool for reducing dimensionality, and as a tool for estimating separate regression models for each segment. In particular, these models offer powerful new approaches for identifying market segments.BIOSJay Magidson is founder and president of Statistical Innovations, a Boston based consulting, training and software development firm specializing in segmentation modeling. His clients have included A.C. Nielsen, Household Finance, and National Geographic Society. He is widely published on the theory and applications of multivariate statistical methods, and was awarded a patent for a new innovative graphical approach for analysis of categorical data. He taught statistics at Tufts and Boston University, and is chair of the Statistical Modeling Week workshop series. Dr. Magidson designed the SPSS CHAID™ and GOLDMineR® programs, and is the co-developer (with Jeroen Vermunt) of Latent GOLD®.Jeroen Vermunt is Assistant Professor in the Methodology Department of the Faculty of Social and Behavioral Sciences, and Research Associate at the Work and Organization Research Center at Tilburg University in the Netherlands. He has taught a variety of courses and seminars on log-linear analysis, latent class analysis, item response models, models for non-response, and event history analysisall over the world, as well as published extensively on these subjects. Professor Vermunt is developer of the LEM program and co-developer (with Jay Magidson) of Latent GOLD® .ReferencesDillon, W.R., and Kumar, A. (1994). Latent structure and other mixture models in marketing: An integrative survey and overview. R.P. Bagozzi (ed.), Advanced methods of Marketing Research, 352-388,Cambridge: Blackwell Publishers.Dillon, W.R.. and Mulani, N. (1989) LADI: A latent discriminant model for analyzing marketing research data. Journal of Marketing Research, 26, 15-29.Magidson J., and Vermunt, J.K. (2000), Latent Class Factor and Cluster Models, Bi-plots and Related Graphical Displays. Submitted for publication.McLachlan, G.J., and Basford, K.E. (1988). Mixture models: inference and application to clustering. New York: Marcel Dekker.Vermunt, J.K. & Magidson, J. (2000a). “Latent Class Cluster Analysis”, chapter 3 in J.A. Hagenaars and A.L. McCutcheon (eds.), Advances in Latent Class Analysis. Cambridge University Press.Vermunt, J.K. & Magidson, J. (2000b). Latent GOLD 2.0 User's Guide. Belmont, MA: Statistical Innovations Inc.Wedel, M., and DeSarbo, W.S (1994). A review of recent developments in latent class regression models. R.P. Bagozzi (ed.), Advanced methods of Marketing Research, 352-388, Cambridge: Blackwell Publishers. Wedel, M., and Kamakura, W.A. (1998). Market segmentation: Concepts and methodological foundations. Boston: Kluwer Academic Publishers.。
countermeasure analysis
Countermeasure AnalysisIntroductionCountermeasure analysis is a crucial process in various domains to identify and assess potential threats or risks and develop effective strategies to mitigate them. This article aims to comprehensivelydiscuss the concept of countermeasure analysis, its importance, and the steps involved in conducting a successful analysis.Importance of Countermeasure Analysis1.Identifying vulnerabilities: Countermeasure analysis helps inidentifying vulnerabilities and weaknesses present in systems,processes, or strategies. By analyzing potential threats and risks, organizations can proactively address these vulnerabilities andenhance their overall security.2.Risk mitigation: Countermeasure analysis enables organizations todevelop and implement effective strategies to mitigate potentialrisks. It helps in reducing the impact of threats and ensures thecontinuity of operations.3.Cost savings: By identifying vulnerabilities and implementingappropriate countermeasures, organizations can significantlyreduce the potential financial losses associated with securitybreaches or other risks. Countermeasure analysis helps inoptimizing resource allocation and minimizing unnecessary expenses.pliance with regulations: Countermeasure analysis helpsorganizations to comply with industry-specific regulations andstandards. It ensures that appropriate security measures are inplace to protect sensitive information, customer data, and meetlegal requirements.Steps Involved in Countermeasure AnalysisCountermeasure analysis involves several interconnected steps that collectively contribute to assessing risks and implementing effective mitigation strategies. These steps include:1. Identify Potential Threats and RisksTo begin with, it is essential to identify and assess potential threats and risks that may impact the organization. This can be achieved through:a) Risk AssessmentConduct a thorough risk assessment to identify internal and external factors that may pose a threat. This includes analyzing previoussecurity incidents, evaluating the business environment, considering technological advancements, and staying updated with industry trends.b) Vulnerability AssessmentPerform a vulnerability assessment to identify weaknesses or vulnerabilities in systems, networks, or processes. This involves analyzing the security infrastructure, conducting penetration testing, and assessing the effectiveness of existing security measures.2. Analyze Potential ImpactOnce potential threats and vulnerabilities are identified, it is necessary to analyze their potential impact on the organization. This includes:a) Impact AssessmentEvaluate the potential consequences of each identified threat on the organization’s operations, reputation, and financial stability. Assess the severity of the impact to prioritize countermeasure implementation.b) Risk PrioritizationRank the identified risks based on their potential impact and likelihood of occurrence. This helps in determining the order of countermeasure implementation based on their significance.3. Develop Countermeasure StrategiesAfter understanding the risks and their potential impact, organizations need to develop effective countermeasure strategies to mitigate the identified risks. This involves:a) Risk Mitigation PlanningDevelop a detailed plan to address each identified risk. This includes defining the desired outcome, assigning responsibilities, setting timelines, and determining the required resources for implementing countermeasures.b) Evaluate Countermeasure OptionsExplore various countermeasure options and evaluate their suitability based on the organization’s requirements, budget, and technical feasibility. Consider factors such as cost-effectiveness, ease of implementation, and long-term sustainability.c) Implementation PlanningCreate an implementation plan outlining the steps required to deploy the chosen countermeasures effectively. Define clear milestones, allocate necessary resources, and establish monitoring mechanisms to ensure successful implementation.4. Monitor and ReviewCountermeasure analysis doesn’t end with the implementation of strategies. It is crucial to continuously monitor and review the effectiveness of the implemented countermeasures. This includes:a) Regular EvaluationRegularly evaluate the implemented countermeasures to ensure they are functioning as intended. Monitor security incidents, conduct audits, and gather feedback from stakeholders to identify any gaps or areas for improvement.b) Continuous ImprovementBased on the evaluation results, make necessary adjustments or enhancements to the countermeasures. Implement lessons learned from previous incidents or emerging security trends to strengthen the overall security posture of the organization.ConclusionCountermeasure analysis plays a pivotal role in ensuring the security and stability of organizations. By identifying potential threats, assessing their impact, and implementing effective strategies, organizations can proactively mitigate risks. This comprehensive approach aids in preventing security incidents, saving costs, and complying with regulations. Regular monitoring and continuous improvement further enhance the effectiveness of countermeasures, ensuring the organization is well-prepared to address evolving risks in today’s dyna mic threat landscape.。
deficiency analysis -回复
deficiency analysis -回复Deficiency Analysis in Healthcare: Identifying and Addressing Health-related DeficienciesIntroduction:Deficiency analysis in healthcare is an essential process that helps identify and address health-related shortcomings to improve patient outcomes and enhance the overall quality of care. This article aims to provide a step-by-step guide on how deficiency analysis is conducted, its significance in healthcare, and strategies for addressing deficiencies effectively.Step 1: Identify the Deficiency:The first step in deficiency analysis is to identify the specific area or aspect of healthcare that requires examination. This may include processes, procedures, practices, or systems that are not meeting the expected standards or causing adverse outcomes. For example, it could involve identifying deficiencies in infection control protocols, medication management, patient safety measures, or documentation practices. By identifying the deficiencies,healthcare organizations can focus their efforts on improving these areas to enhance patient care.Step 2: Gathering Data and Information:Once the deficiency is identified, the next step is to collect and analyze relevant data and information. This may involve reviewing patient records, interviewing healthcare professionals, observing workflows, and conducting surveys or audits. By gathering comprehensive data, healthcare organizations can better understand the root causes of deficiencies and develop targeted strategies for improvement.Step 3: Analyze and Evaluate the Deficiency:In this step, the collected data and information are analyzed and evaluated to identify the underlying causes of the deficiency. This analysis helps to understand whether the deficiency is systemic, process-related, or caused by human error. For instance, if there is a high incidence of medication errors, the analysis may reveal that inadequate training or communication gaps contribute to the problem. By evaluating the deficiency thoroughly, healthcareorganizations can tailor their improvement strategies accordingly.Step 4: Prioritize and Develop Improvement Strategies:After analyzing the deficiency, the next step is to prioritize areas for improvement and develop strategies to address them effectively. This may involve identifying short-term and long-term goals, implementing evidence-based best practices, and involving multidisciplinary teams to ensure comprehensive solutions. For example, if deficiencies in infection control are identified, strategies may include staff education and training on proper hand hygiene practices, improvement in environmental cleaning protocols, and implementation of surveillance systems to monitor infections.Step 5: Implement and Monitor Improvement Efforts:With improvement strategies in place, the next step is to implement them and closely monitor their effectiveness. This may involve training healthcare professionals, updating policies and procedures, and conducting regular audits or evaluations. By monitoring improvement efforts, healthcare organizations can ensure that the deficiency is being addressed, and progress isbeing made towards achieving the desired outcomes. This step is crucial for continuous quality improvement in healthcare.Step 6: Evaluate the Effectiveness of the Improvement Strategies:Once improvement strategies have been implemented, it is essential to evaluate their effectiveness. This evaluation may involve analyzing data to determine if the deficiency has reduced, comparing outcomes before and after the implementation of improvement strategies, and seeking feedback from patients and healthcare professionals. By evaluating the effectiveness of improvement strategies, healthcare organizations can identify areas that require further refinement or identify new deficiencies that may have arisen.Step 7: Continuous Quality Improvement:Deficiency analysis is an ongoing process in healthcare. It is crucial to recognize that deficiencies can change over time, and new challenges may emerge. Therefore, it is important for healthcare organizations to adopt a culture of continuous quality improvement. This involves regular re-evaluation of practices andprocesses, fostering a culture of learning, and actively seeking feedback from patients and healthcare professionals to ensure deficiencies are promptly addressed.Conclusion:Deficiency analysis plays a vital role in improving healthcare outcomes and enhancing patient care. By identifying, analyzing, and addressing deficiencies, healthcare organizations can create safer and more effective environments for patients and staff. Through a systematic process that involves data collection, analysis, and continuous improvement efforts, deficiencies can be proactively identified and effectively managed. Taking these steps will ultimately lead to improved healthcare quality and patient satisfaction.。
authenticity of this analysis -回复
authenticity of this analysis -回复…authenticity of this analysis“这个主题的文篇题目的应该是:"对于这个分析是否真实可信的解析"。
引言:在信息时代,我们经常接触各种分析报告和论文。
然而,究竟如何判断一个分析的真实可信性呢?本文将从分析的来源、数据收集和分析方法、结果解释和学术背景等方面分析,以帮助读者判断一个分析是否真实可靠。
一、分析来源:分析的来源是评估其真实可信性的重要因素之一。
首先,我们需要了解该分析由何人或机构提供,这决定了其专业性和可靠性。
如果来源是一个权威的学术机构、研究机构或者有公信力的媒体机构,那么这个分析的真实性会更高。
其次,我们需要考察该来源的声誉和信誉。
这可以通过搜索该机构或个人的背景资料、发表的其他文章或报告以及被引用的次数来进行评估。
如果该机构或个人在领域内有很高的声誉,那么这个分析也更有可能是真实可信的。
二、数据收集与分析方法:一个分析的真实可信性也取决于其数据收集和分析方法。
首先,我们需要了解分析是基于什么样的数据来源。
如果数据来自权威的研究机构、统计局或者公共数据库,那么这个分析的可靠性就会更高。
其次,我们需要了解分析的数据收集是否经过专业和科学的方法,例如样本的选择是否具有代表性、数据采集是否遵循严格的标准等。
如果数据收集过程经过合理的设计和实施,那么分析的真实性也就有了更高的保证。
对于分析方法,我们需要评估其是否严谨和适用于所研究的问题。
根据不同的领域和研究目的,有各种不同的分析方法,例如统计分析、质性研究、案例分析等。
如果分析方法符合学术标准并且被同行评审机构验证过,那么分析的真实可靠性会更高。
三、结果解释:分析的结果解释也是衡量其真实可信性的一个重要方面。
我们需要评估结果解释是否合理、客观且基于实证。
如果分析的结果解释是建立在充足的证据和数据基础上的,而非主观臆断或推测,那么这个分析的真实性就会更高。
google analyze评分标准
google analyze评分标准Google Analyze(谷歌分析)是谷歌推出的一款网站分析工具,可以帮助网站管理员深入了解自己的网站访问者和用户行为。
Google Analyze评分标准涉及多个方面,包括数据准确性、功能全面性、用户友好性、报告灵活性、数据可视化等等。
以下将从这些方面对Google Analyze的评分标准进行详细阐述。
首先,数据准确性是Google Analyze评分的重要因素之一。
作为网站分析工具,数据的准确性对于网站管理员来说至关重要。
Google Analyze通过使用跟踪代码收集数据,确保数据的准确性和完整性。
它能够跟踪访问者的行为,如访问页面、停留时间、页面跳转等等。
同时,Google Analyze还提供了多种报告和过滤选项,使管理员可以根据需要筛选和分析数据,提高数据的准确性。
其次,功能全面性也是Google Analyze评分的重要考量因素之一。
Google Analyze拥有许多功能,如实时数据追踪、转化追踪、多渠道追踪、事件追踪以及受众分析等等。
这些功能能够帮助管理员深入了解访问者的行为和网站的表现,并根据这些数据进行优化。
例如,通过实时数据追踪,管理员可以实时了解当前的网站流量情况,及时做出决策。
而通过转化追踪,管理员可以了解到转化路径的各个环节,找出转化率低的地方并进行优化。
此外,Google Analyze评分还要考量用户友好性。
Google Analyze的用户界面简洁明了,操作简单易懂。
其中的报告、过滤、设置等功能都可以通过直观的界面进行操作,不需要用户过多的技术知识。
此外,Google Analyze还提供了大量的帮助文档和教程,用户只要遇到问题就可以通过这些资源进行查找解决方案。
报告灵活性也是Google Analyze评分的重要考量因素之一。
Google Analyze提供了多种报告选项,用户可以根据需要选择不同的报告类型。
例如,管理员可以选择查看访问者来源的报告,了解网站的流量来源;或者选择设备报告,了解网站在不同设备上的表现。
analyze英式写法 -回复
analyze英式写法-回复以下是一篇关于以英式写法分析的1500-2000字文章。
标题:分析英式写法:探索其特点、历史背景与影响因素引言:英式写法是指英国英语中应用的一种语法、拼写及用词方法。
随着全球化的发展,英式写法影响了英语使用者的写作和交流方式。
本文将一步一步回答有关英式写法的问题,深入探索其特点、历史背景以及影响因素。
正文:一、什么是英式写法?英式写法是指英国英语中特有的一些特点,包括语法、拼写和用词方面的区别。
它在英国以及英联邦国家如加拿大、澳大利亚等被广泛使用。
二、英式写法的特点有哪些?1.拼写差异:英式写法与美式写法在拼写上存在一些差异,如英式中“color”写作“colour”,“theater”写作“theatre”。
这种差异可以追溯到历史上英式语言的发展和标准化过程。
2.语法结构:英式写法在语法上有一些独特之处。
例如,英式中的第三人称单数动词形式一般以“-s”结尾,如“he speaks”;而美式则通常为“-es”,如“he speaks”。
3.单词用法:英国英语与美国英语在某些单词用法上也存在差异。
例如,“biscuit”在英式中是指甜点心,而在美式中通常是指饼干。
三、英式写法的历史背景是什么?英式写法的历史背景可以追溯到英国的殖民时期。
英国在18世纪和19世纪通过殖民活动将英国的语言和文化传播到世界各地。
这种传播包括英式写法的特点和规范。
随着英国的统治和英语的广泛使用,英式写法成为标准并且在整个英联邦影响力甚大。
四、英式写法的影响因素有哪些?1.教育体系:英式写法在英国教育体系中得到广泛应用。
学校和大学通常强调英式写法的规范,从而培养了学生的习惯并影响他们的写作风格。
2.媒体文化:英国的媒体文化对英式写法的影响也不容忽视。
英国出版的书籍、报纸和杂志都遵循英式写法的规范,这种影响力也传播到其他国家。
3.文化认同:使用英式写法可以增强某些人的英国文化认同感。
一些英语学习者或非英语母语者可能选择使用英式写法以更好地适应英国文化环境。
Brief Analysis on Translation of Chinese Dish Names
Brief Analysis on Translation of Chinese Dish Names作者:周莹莹来源:《校园英语》 2020年第20期文/周莹莹【Abstract】With China’s increasing foreign exchange activities, Chinesefood culture plays an increasingly important role. Chinese dish names reflect the rich culinary culture of the Chinese nation. Therefore, the proper translation of these dishes is of great significance to the development of Chinese cuisine.【Key words】Chinese dish names; Translation methods【作者简介】周莹莹(1993.11.08-),女,汉族,乾县人,长安大学外国语学院外国语言学及应用语言学专业,硕士研究生,研究方向:翻译学。
1. IntroductionChinese food culture is an important part of Chinese culture in cooking and leisure. With the further development of China, Chinese food culture attractspeople from all over the world with its unique charm. More and more international friends like to travel to China and enjoy delicious Chinese dishes. Therefore, itis necessary to introduce our food culture to other countries in the world.2. The Characteristics of Chinese DishesThe name of Chinese dishes is often composed of the founder, origin orhistorical allusions of the dish. The difference of eastern and western foodculture leads to the naming of dishes with its own characteristics. The naming method of Chinese food dishes not only carries the flavor characteristics and cooking skills of Chinese food for thousands of years in the form of language, but also contains profound Chinese culture, such as myths, folk customs, historical literature, religious beliefs, etc. The naming styles of dishes in China, they are usually divided into realistic and freehand style.3. Suggested Methods for Chinese Dish Names Translation3.1 Literal TranslationLiteral translation is widely used in translation activities in various fields. Literal translation based on raw materials directly reflects the various main materials and auxiliary materials used in the dishes through the name of the dishes. Taking the English translation of “脆皮鸡” as an example, translating it into “crispy chicken” is also a good embodiment of the literal translation method applied to the translation of dishes. Therefore, when translating dishes into English, we must make good use of literal translation and show the essence of any Chinese dishes to foreign friends to the greatest extent.3.2 TransliterationTransliteration refers to expressing the source language with similar sounds during the translation process. For some traditional foods with Chinese characteristics and accepted by foreigners, in accordance with the principle of promoting Chinese language and Chinese catering culture, transliteration should be adopted. For example, “中国饺子” is more appropriate to directly use Chinese pinyin “Jiaozi”. [3] Similar examples include “炒面(Chow Mein)”, “重庆小面(Chhongqing Noodles)”.3.3 Free TranslationIn China, many dishes are named after auspicious words, symbolizing good luck and wishes. If we translate them literally, foreigners who do not understand Chinese cultural background will be confused when they hear the name of the dish. In this case, the free translation method can help explain the ingredients and preparation methods of the dishes, and can fully convey the cultural charm behind the dish name. For example, “蚂蚁上树” translated as “Vermicelli with spicy minced pork”.4. ConclusionChin ese cuisine is an important part of the history of China’s excellent traditional culture. The quality of the English translation of Chinese cuisine names directly affects the audience’s impression of Chinese culture. Therefore, when translating the names of Chinese dishes, the contents of the dishes information should be fully considered to promote more fields of Chinese culture to the world.References:[1]熊四智.中国人的饮食奥秘[M].郑州:河南人民出版社,1992.[2]朱莉.中国菜名的特点与文化可译性实践[J].宁波大学学报,2011 (4).[3]黄芳.中餐菜单译法研究[J].中国科技译,2007(1):40-42.。
Bliss Analysis
Bliss AnalysisJeffrey Stults & Thomas Smith17 September 20021 Plot and Structure“Bliss” contains all of the elements of plot: exposition, rising action, climax, falling action, and resolution. It is divided into four parts. The exposition occurs in the first two sections, the rising action occurs mostly in the third section, and the climax, falling action, and resolution all occur in the last section. The main conflict is within Bertha, striving to understand how she is connected to Pearl Fulton. The exposition exposes Bertha’s blissful nature. It also uses Little B and the Nanny in a parallel manner to highlight more of Bertha’s character. Most of the dinner party is the rising action. Bertha feels that there is some sort of connection between her and Miss Fulton, once during the eating, and later looking at the pear tree.The climax occurs when Bertha sees Pearl and Harry embracing. At that moment, she understands that Harry is the connection between them. Immediately following the climax everyone finishes leaving, and Harry and Berth are left together, ending that falling action and moving into the resolution, where “the pear tree was as lovely as ever and as full of flower”. Bertha pointed out her link to the pear tree, and its continuing on shows that Bertha will continue on, either in her literal form or in Little B.2 Language and StyleMansfield uses hyperbole extensively in her story. The ludicrously positive images, such as “in her bosom there was still that bright glowing place--that shower of little sparks coming from it,” (424) reinforce the reader’s perception of Bertha as disgustingly cheerful. Along with the sparkle images, Mansfield uses many comparisons with fruit and other foods, e.g. “a strange sheen as though it had been dipped in milk,” (425).The hyperbole is not used as often in the last section, which is also more negative in its content than the previous sections. The language reflects the content.3 ThemeThe theme of “Bliss” is that, as Thomas Gray relates in his poem “Ode on a Distant Prospect of Eton College,” “where ignorance is bliss, ’Tis folly to be wise.” (ll. 99-100) This theme is first suggested by the title of the work, since ‘bliss’ is not an everyday word, and has connotations of spaciness. It is confirmed when the reader finds that the plot pivots on a fact that Bertha does not know until the end: Harry is cheating on her. She could have figured it out, had she wanted to: “For the first time in her life Bertha Young desired her husband. [...] It had worried her dreadfully at first to find that she was so cold, but after a time it had not seemed to m atter.” (p. 431). Why did it not matter? Bertha never asked herself. She was much happier not knowing--ignorance is bliss.4 Irony and SymbolIrony is abundantly present in “Bliss.” The principal irony of the story is that Bertha wants Harry to like Miss Fulton (“ ‘Oh, Harry, don’t dislike her.’ ”, 431), but he already does: “His lips said: ‘I adore you.’ ” Also, Bertha thinks that “Pearl Fulton[...] was feeling just what she was feeling,” but little does she know that the emotion that they finally share is desire for Harry.There are several significant symbols in the story. First, Bertha “seemed to see on her eyelids the lovely pear tree with its wide open blossoms as a symbol of her own life.” (427).The cats are also symbolic. Miss Fulton is explicitly compared to the grey cat (432), and earlier, “The sight of [the cats], so intent and so quick, gave Bertha a curious shiver.” (427). Miss Fulton is also intent and quick in her stalking of Harry. Furthermore, Pearl Fulton is often described as being silver, and silver and grey are very similar colors. The grey cat is an obvious symbol.The story’s focus on the pear tree makes little sense without a symbolic interpretation of it, so symbolism is important to the story.5 CharacterNumerous characters are introduced. With the exception of Bertha, all of them are static. Little B, the Nanny, Mr. and Mrs. Norman Knight, and Eddie Warren are also all minor characters. Little B highlights the negative aspects of (Big) Bertha, while Little B’s Nanny represents the controlling aspects of Bertha’s life. The Knights and Eddie both further the pseudo-intellectual image evinced throughout the story.There are two static but major characters, Harry and Pearl Fulton. Together they destroy Bertha’s illusionary lifestyl e through the climactic scene of them embracing. Harry turns out to be a cheater, albeit one that is clever enough not to be caught by the blissfully blind Bertha. Pearl Fulton is sly about her intentions, causing Bertha to even think “ ‘Oh, Harry, don’t dislike her.’ ” (431). In reality, Harry is having an affair with the little vermin whose heart is full of evil.Bertha is blissful. She seems almost ditzy in her everyday transactions, such as acquiring fruit for the dinner. Furthermore, her personality is subservient; it allows the Nanny to dictate what can be done with Little B. It is only when she sees her husband obviously cheating on her with someone that she had brought into the household that she becomes disillusioned with her blissful state and awakens to reality.6 SettingAs a whole, the setting helps to reinforce the pseudo-intellectual image from the story. The broad positioning is in London, as explicitly mentioned “ ‘I believe London is simply teeming...’ ” (430). In addition the author’s background is given as being a resident of London, leading one to infer that she would write about that which is familiar to her. Some British terminology also shows through the language used, such as ‘perambulator.’The house is a nicer, more upper class dwelling. It would have a garden, allowing the pear tree symbol to be included without sacrificing the realism. However, contrasting with the upper class nature is that none of the characters are ever mentioned as having titles, so none of them are of the true upper class.The time period is early 20th century. Mention is made of coffee makers and taxis, so there are at least electricity and mass transit services. However, after World War II the large manor houses in the cities largely disappeared, limiting the time period to earlier in the 20th century.7 Point of View‘Bliss’ is written in third person limited omnis cient. The reader knows only what Bertha knows, making the surprise discovery of adultery just as dramatic for the reader as it is for Bertha. The limited nature also brings the reader only into Bertha’s thoughts, drawing the reader closer to Bertha and turning her into a character for which more sympathy is felt. Further, seeing only Bertha’s perspective, from the reliable narrator, creates a less morally ambiguous situation by not clouding the reader’s perception with the rationalizations of other conflicting characters。
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ISSN 1712-8056[Print]ISSN 1923-6697[Online] Canadian Social ScienceV ol. 8, No. 4, 2012, pp. 144-149DOI:10.3968/j.css.1923669720120804.1555Brief Analysis on Conflicts of Interest of Credit Rating AgenciesZHANG Lu [a],*; XING Yanyan [b][a]Doctor of Law Science, School of Political Science and Law, Hebei University, Baoding, Hebei, China.[b]Master of Law, Finance and Economics School of Law, Tianjin University, Tianjin, China.*Corresponding author.Received 20 May 2012; accepted 4 August 2012AbstractWith the outbreak of the current US financial crisis and European sovereign debt crisis, the current credit rating system has indicated various problems, and especially the conflicts of interest are becoming more and more obvious. Based on the issuer-pays mode, this article analyzes the causes of such conflicts of interest from the angle of regulation of fiduciaries, including international regulation, and puts forward suggestions on solution of such conflicts.Key words: Rating agency; Conflicts of interest; Fiduciary; RegulationZHANG Lu, XING Yanyan (2012). Brief Analysis on Conflicts o f I n t e r e s t o f C r e d i t R a t i n g A g e n c i e s. C a n a d i a n S o c i a l Science , 8(4), 144-149. Available from /index.php/css/article/view/j.css.1923669720120804.1555 DOI: /10.3968/j.css.1923669720120804.1555.The role of credit rating agencies as “gate keeper” of the market has been challenged since the occurrence of the subprime mortgage crisis in 2008. Those agencies gave virtual high ratings on subprime mortgages and such structured financing products as CDOs, which accelerated the burst of subprime mortgage bubble and the crisis. After the outbreak of the crisis, those irresponsible agencies considerably lowered the ratings of such kinds of products, which resulted in market panic and increasingmarket fluctuations, which in turn led to the formation of the “procyclical effect” of financial crisis, and spread of the subprime crisis (Krugman, 2010). Why did the function of rating agencies as the “gate keeper” of market fail to work? Though we may not attribute all liabilities for this crisis to those agencies, what was shown in the crisis, for example, moral hazard and conflicts of interest, does disable such agencies to keep their objectivity and independence. Especially, the conflicts of interest are the main cause for loss by rating agencies of their independence.1. EVOLVEMENT OF CONFLICTS OF INTEREST 1 OF CREDIT RATING AGENCIESThe credit rating industry emerged after Moody’s conducted the primary credit rating on railway bonds in 1909. At the beginning, credit rating was for free, which lasted until the year of 1968 when the top three credit rating agencies collected charges from investors for the information related to credit ratings they provided. At that time, thanks to single kind of clients and financial products of credit rating agencies, there were almost no conflicts of interest. However, such charging mode easily generated “free-riders” and moral hazards. Moody’s and Fitch Ratings started to collect charges from issuers after 1968; in other words, securities issuers should pay credit rating agencies for credit ratings on their securities. Currently, the charges paid by issuers account for most part of the revenues of main credit rating agencies. The documents of SEC’s hearing on November 21, 2002 indicated that 90 percent of the revenues of Moody’s was from credit rating charges paid by issuers and the remaining 10 percent from research and data service it provided; similarly, among the1Conflicts of interest means when serving two or more interest groups, an agency may sacrifice the interest of one group for more gains of the others; or there are conflicted interests between a service provider and its clients. What we discuss here refers to the first meaning.ZHANG Lu; XING Yanyan (2012). Canadian Social Science, 8(4), 144-149revenues of Fitch Ratings, 90 percent came from issuers and about 10 percent from payment by investors (YING & ZHANG, 2006). In such issuer-pays mode, credit rating agencies play two roles as the “issuers’ seller” and the “investors’ agent” at the same time, who collect charges from the entities to be rated while disclosing securities risks to investors. In such way, the original principal-agent relationship is distorted and the potential of conflicts of interest rises.Since credit rating on bonds relates to issuers, investors and regulators, who may have different interests, and credit rating agencies also play different roles, when their interests are inconsistent in certain situations, conflicts of interest may be inevitable (NIE, 2011). The working mechanism of conflicts of interest in the issuer-pays mode is as follows:A credit rating agency collects data and information for detailed investigation and analysis on an entity to be rated; → the credit rating agency determines the credit rating of the entity; → the credit rating agency releases the credit rating on the entity to investors; → investors decide whether to invest in the entity based on the credit rating at their own discretion and regulators supervise the entity based on the credit rating; → the investment of investors impacts the financing scale and cost of the entity; → the credit rating agency receives credit rating charges from the rated entity (as well as the fees paid by some investors for journals published and provided by the credit rating agency) ( LI, LI & Shao, 2009).In such a pay mode, credit rating agencies serve three interest groups -- issuers, investors and regulators, whose interest conflicts. Specifically, the value of credit rating agencies for investors and regulators lies in their provision of an accurate and reliable rating to disclose credit risks of different financial products; while for issuers, credit rating agencies imply they are able to give them the “access permit” to capital market. Usually, credit rating agencies sacrifice the interests of investors and regulators to meet the needs of issuers in rating.The revenue of credit rating agencies in the issuer-pays mode is mainly from issuers and the intent of issuers to pay those agencies depends on whether they may be granted a satisfactory rating (XU, 2011). Accordingly, the pursuit for economic benefits and market share is enough to motivate credit rating agencies to give higher ratings on the securities of issuers. Based on what analyzed above, there are conflicts of interest among issuers and investors and regulators in the issuer-pays mode. Since the intervention of media is a necessary factor for sharpening of conflicts, we may analyze the causes for such intensification in two respects. 2.C A U S E S F O R C O N F L I C T S O FI N T E R E S T O F C R E D I T R AT I N G AGENCIESThe US Dodd-Frank Wall Street Reform and Consumer Protection Act 2010 (hereinafter referred to as the Dodd-Frank Act) provides: credit rating agencies shall be subject to the “expert liability” as applied to auditors and securities analysts. As “gate keeper” of the financial market, securities analysts, auditors and credit rating agencies are responsible for providing consulting services to investors, and since they have the duty of a good administrator, they are collectively called “fiduciaries”. Consequently, they shall assume the duty of care and fiduciary duty as “expert liabilities”.The duty of care is a legal principle derived from cases of common law of Anglo-American law system. According to Oxford Dictionary of Law, it refers to “the legal obligation to take reasonable care to avoid causing damage”.In German scholar Engisch’s opinion, the duty of care shall be discharged in three respects: (1) to restrain from any dangerous acts, that is, prudently avoid any acts that may incur any infringement of legal interests; (2) to take actions at stake, that is, make any action or omission necessary to avoid any damages from any acts that may incur any possible infringement of legal interests; and (3) to discharge the obligation to obey the law, that is, think over the dangerousness of an act to be done and make a correct judgment (Liu, 2002, p. 50-53). The duty of care of rating agencies is mainly as follows: (1) to avoid infringing upon the interest of every party in rating; (2) to observe laws and disciplines; and (3) to remain prudent and objective in rating.The fiduciary duty is a key concept in trust. In terms of company law, it means that directors, senior officials and controlling shareholders of a company are prohibited from using the resources of the company or its partners to pursue their personal interests. Specifically, first, directors may not get benefits by taking advantages of their positions; and second, directors may neither commit bribery nor take any secret interest or other benefits promised. Accordingly, the fiduciary duty of rating agencies means those agencies may neither pursue their own interest or damage others’ interests nor abuse their power and function to commit bribery.Fiduciaries shall discharge their duty of care and fiduciary duty. Rating agencies, especially, are required to stick to the principles of objectiveness, integrity and prudence and try their best to avoid conflicts of interest. This subprime crisis, however, reveals that rating agencies abused their power and breached their fiduciary duty in rating, which brought huge damages to investors. Breach by fiduciaries of their duties is considered as the main cause for intensification of conflicts of interest of rating agencies.Brief Analysis on Conflicts of Interest of Credit Rating Agencies2.1 Fiduciaries’ BreachBased on the issuer-pays mode, breach by fiduciaries of their duty of care and fiduciary duty is manifested as follows.Firstly, in terms of charge payers, rating agencies adopting the issuer-pays mode are likely to be lured. For instance, the investigation findings of US Senate released in 2010 stated by quoting an email of an employee of Standard & Poor’s that “it is necessary to hold meetings to discuss adjustment of the rating standards for mortgage-related securities to avoid loss of our clients”; and in another email, this employee complained that “we have to color subprime and Alt-A mortgages to keep our market share” (Feng, 2010, p.6).There is the possibility that rating agencies fail to discharge their duty of care as fiduciaries and give false high ratings to issuers at the cost of investors’ interest due to economic considerations.Secondly, in terms of charging standards, rating agencies collect pro rata charges according to financing size. Usually, such charges equal to 0.2-0.3 percent of the income from issuance mainly based on the size of issuance and complexity of business (Chen, 2009, p.53). For a securities issuance, a high rating may reduce the cost of an issuer and contribute to the success of issuance; hence, a higher rating requires higher charges. Though such false ratings increase the proceeds of issuers and rating agencies, they damage the interest of investors. In such situation, rating agencies breach their fiduciary duty as fiduciaries since they pursue their own benefits at the expense of others.Thirdly, in terms of persons performing ratings, they often have direct or indirect relationship with the entities to be rated, for example, by holding any security of such entities, serving as a part-time worker of those entities, especially as senior officers (for instance, Clifford L. Alexander, Moody’s former president, once served as the president of WorldCom for 19 years and when the rating on WorldCom by the market lowered to below investment grade, Moody’s rating on it remained above investment grade) (Chu, 2011, p.73-76), or committing bribery. As a result, the objectiveness of rating results is in question.From the aforesaid analysis, it may be said the main cause for intensification of conflicts is the collusion of rating agencies and issuers, which damages the interest of investors and makes rating agencies lose the accuracy, independence and objectiveness of their ratings.2.2 Lack of Effective RegulationCredit rating agencies always enjoy a special status in law. If the breach by rating agencies as fiduciaries in the issuer-pays mode is mainly ascribed to the conflicts of interest, the lack of effective legal regulation may be the catalyzer.Firstly, the regulation of conflicts of interest fails to touch the core issue. The IOSCO’s CRA Code of Conduct 2004 requires, with respect to independence and management of conflicts of interest, that rating agencies and analysts maintain procedural and substantive independence and objectiveness and the key elements for rating shall be risk-related factors. However, it does not mention the core issue of linkage between charging standards and rating grades. In addition, though it launches several measures for regulating rating, the Dodd-Frank Act does not make explicit provisions on the key issue of conflicts of interest of rating agencies, but only requires the controller general to explore an alternative business mode for rating agencies’ charge collection and submit a report within 18 months after implementation of the Act. Therefore, there is still no law to deal with the regulation of conflicts of interest of rating agencies so far.Secondly, rating agencies are usually exempted from legal liabilities. In the course of bond rating history over 100 years in the US, there were only two cases concerning lawsuit by investors against rating agencies, and even if those agencies were prosecuted, they were decided to bear few liabilities finally (Zhang & Tan, 2011, p.29-33).It is because credit rating agencies are protected by exemption provisions of the Second Amendment to the Constitution of the USA and Section 11 “Civil Liabilities on Account of False Registration Statement” of the Securities Act of 1933, as rating results are legally deemed as an “opinion”, which is of no legal force but only for reference by investors (Fang & Liang, 2011, p.85).Unless rating agencies have any purposive behaviors in rating, they may not take any legal liabilities. Though the Dodd-Frank Act provides for the expert liability of rating agencies, saying that investors may lodge a private lawsuit against credit rating agencies if they “knowingly or recklessly failed to conduct a reasonable investigation of the rated security with respect to the factual elements relied upon by its own methodology for evaluating credit risk”, there is still a long way for investors to safeguard their legitimate rights.Thirdly, the top three credit rating agencies make monopoly and lack regulation. Though those agencies are incorporated as non-government organizations in name and boost “accuracy, independence, objectiveness and prudence”, there is a game of various interests. Basically, those international credit rating agencies mainly stay in a primitive situation where US regulators have the say. For instance, US regulators prescribe that unless it obtains a rating report from one or even two recognized credit rating agencies, an issuer may be not be permitted to issue its bonds, but who is a recognized credit rating agency is totally subject to such regulators.3. SUGGESTIONS ON REGULATION OF CONFLICTS OF INTERESTAs conflicts of interest of credit rating agencies root in the issuer-pays mode, such mode shall be reformed to reduce conflicts. Since the financial crisis, how to make a reformZHANG Lu; XING Yanyan (2012). Canadian Social Science, 8(4), 144-149in the credit rating industry has been frequently discussed by scholars and experts. Facing the existing charging mode, some scholars have questioned the reasonableness of existence of rating agencies and others proposed an investor-pays mode. The SEC also held a round-table conference on April 15, 2009, in which then Chairman Schapiro advised rating agencies to adopt new business mode to take investors as the final clients and hence make their interest consistent with investors. A government-pays mode was also proposed with a view to effectively solving the conflicts of interest.We believe, firstly, the credit rating industry has proved the reasonableness of its existence through its long development. It has become an important part of the capital market and is capable to reduce information asymmetry; therefore, it plays a significant role in the financial market. Secondly, to adopt the investor-pays mode is unreasonable, since such mode easily leads to “free riders”, which may bring adverse impacts on the industry in a long term. Finally, the government-pays mode is improper, as government is also the issuer of some bonds and such mode may generate conflicts of interest and even corruption.Though scholars and experts have been discussing different pay modes, the existing one cannot be replaced in a short time. Therefore, we hold that emphasis shall be placed on regulation of conflicts of interests when exploring new modes. Legislative measures for the charge collection system may be adopted to avoid conflicts of interest in respect of institution and executor.3.1 Enhancement of Regulation on Fiduciaries and Improvement of Internal Governance of Rating AgenciesAs fiduciaries, credit rating agencies is expected to maintain independence and objectiveness in credit rating. This subprime crisis and European sovereign debt crisis, however, revealed those agencies’ ineffective internal policies on prevention of conflicts of interest and poor procedural execution and breach of their fiduciary duty. Thus, the fiduciary regulation shall be strengthened and the internal governance of rating agencies shall be improved.Firstly, fiduciary regulation shall be enhanced. Rating agencies, as fiduciaries, bear the duty of care and fiduciary duty to investors and issuers and shall conduct an equal and objective credit rating and may not damage the interest of any party, but actually, they did breach their duties and sacrificed the interest of investors. Why? It is because there is no effective regulation and punishment. We believe we may, by reference to the practice and experience of financial intermediaries including auditors and securities analysts, work out criteria for career management of credit raters and supervise the professional activities of credit rater. Such criteria may be legally promulgated to be of mandatory force and those who violate the criteria may be subject to legal liabilities. Or we may have a try to make observance of those criteria by credit raters as part of their yearly performance assessment and link it with their incomes. Due to our knowledge limitation, specific methods need to be discussed separately.Secondly, an independent director system shall be established. At least half of members of the board of a rating agency shall be directors independent from the agency and the number of such directors shall be no less than two. Independent directors shall include users of the rating results and they may not receive any consulting fees or other compensations from the rating agency they serve. Those who associated with the rating agency or its affiliated organs shall be deemed disqualified for an independent director. Meanwhile, when an independent director has any interest in a rating, he/she may not participate in such rating. Moreover, the compensation of independent directors may bear no relationship with the performance of the rating agency.Thirdly, the conflicts of interest arising from marketing shall be eliminated. Credit rating agencies are advised to establish and execute a “firewall system” to separate marketing personnel from those who engage in rating analysis to avoid any influence on objectiveness of rating. In case of failure of rating agencies to carry out such system, competent authorities may impose severe punishment like revocation of their license on them. Furthermore, rating agencies may make a reform of their compensation system, unlink compensation and rating grade, and set up a sound system to avoid conflicts of interest.3.2 Strengthening of Legislative Regulation Loose regulation is considered as an objective cause for rating agencies’ loss of their independence and objectiveness. Consequently, strengthening legislative regulation is always the focus of regulation in the industry. Though the Dodd-Frank Act of 2010 provide regulation rules for rating agencies in 9 parts at institutional and legal level, we hold it is insufficient and the following aspects may be incorporated in legislation.Firstly, the nature of rating results is legally ambiguous. Since rating agencies are considered as publishers or underwriters in the US, rating results are only deemed as opinions, comments or goods, which exempt rating agencies from legal liabilities.There in no legal liabilities of rating agencies in US’s legal system, though Dodd-Frank Act provides that rating agencies shall be subject to legal liabilities and public regulation in the similar way as apply to auditors, securities analysts and investment banks. The Act abolishes Rule 436 (g), which means rating agencies have to bear the expert liability as specified in Section 11 of the Securities Act of 1933. However, this provision only clarifies the liabilities of rating agencies, but not indicates the legal status ofBrief Analysis on Conflicts of Interest of Credit Rating Agenciesrating results. The nature of rating results shall be legally identified to clarify legal liabilities concerned.Secondly, Dodd-Frank Act provides that rating agencies shall bear “expert liability” and adds private right of action, saying that “in the case of an action … it shall be sufficient …that the complaint state with particularity facts giving rise to a strong inference that the credit rating agency knowingly or recklessly failed to conduct a reasonable investigation of the rated security with respect to the factual elements relied upon by its own methodology for evaluating credit risk”. But what causes may be used by investors and who may take the burden of proof?We believe that such cases may be dealt with as infringement, since there is causality among rating agencies’ breach, existence of knowing or reckless conduct, damages incurred to investors due to rating results, false rating results and loss to investors, which are constituents of an action of infringement.As to burden of proof, we hold that though according to general tort theories, the burden to prove financial loss of investors and false rating results shall be taken by plaintiff, it is very difficult to let investors as the plaintiff to provide evidences in judicial practice. To reduce burden of proof and protect investors, rating agencies may be required to prove the objectiveness of their rating result, which is derived from analysis of different information, and that the loss to investors does not caused by their reliance on rating results, or the rating agencies may assume the legal liabilities for loss of proceedings. Article 173 of the Securities Law of China provides that where a securities service agency formulates and generates any auditing report, asset appraisal report, financial advising report, credit rating report or legal opinions for securities business activities, it shall be diligent and responsible…In the case of any false record, misleading statement or material omission in such documents, which brings any loss to any other person, the securities service agency shall bear the joint and several liabilities together with the relevant issuer and listed company, unless it may prove it has no fault. Actually, those provisions stipulate the legal liabilities of credit rating agencies, but they are only provisions in principle, irrelevant to regulation of conflicts of interest. Consequently, we hold the legislative regulation on burden of proof in actions involving conflicts of interest of rating agencies shall be further enhanced.Finally, as to the monopoly of top three credit rating agencies, it is suggested to develop local rating agencies. For example, the EU is enthusiastically creating their own credit rating agencies to end the monopoly of the top three agencies. As far as the role of credit rating agencies in global economy is concerned, credit rating agencies are imbued with strong political overtones and often abuse their special position to seek for their national interest. Since credit rating agencies are expected to be immune to political influence and become an independent “gate keeper” of the financial industry in a real sense, we believe we may reinforce global financial cooperation to set up a super-national credit rating agency adopting the membership system, the ratings made by whom will be of public confidence force, and branches may be established in member countries.CONCLUSIONIn China, due to late start of the credit rating industry, corresponding regulation framework and systems are simple, but with the improvement of the financial system, the business scope and functions of credit rating have been considerably expanded. Facing increasing conflicts of interest arising from the issuer-pays mode, more provisions on credit rating have been promulgated by different departments. For example, Article 41 of the Interim Measures for Administration of Credit Rating Business in the Securities Market by China Securities Regulatory Commission provides that “where a securities credit rating agency contravenes the challenge system or the prevention system of conflicts of interest, it may be ordered to make a correction, warned, and imposed penalties equal to the amount of more than RMB 10,000 and less than RMB 30,000; the officials and other employees who bear direct responsibilities shall be warned and imposed penalties equal to the amount of more than RMB 10,000 and less than RMB 30,000. In any severe situation or in case the credit rating agency refuses to make a correction, it shall be punished in accordance with paragraph 3 of Article 226 of the Securities Law”. However, such legal documents, at a low level and without a system, contain inconsistent provisions, which are only made in principle, less mandatory and punitive. 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