On chromatic number of unit-quadrance graphs (finite Euclidean graphs)

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算术平均牛顿法的英文

算术平均牛顿法的英文

算术平均牛顿法的英文Arithmetic-Geometric Mean Newton's Method.The arithmetic-geometric mean (AGM) Newton's method is an iterative algorithm used in numerical analysis to approximate the solution of equations, particularly those involving transcendental functions. This method is avariant of the classical Newton's method, which uses the tangent line to the function at a given point to approximate the root of the function. The AGM Newton's method incorporates the arithmetic-geometric mean (AGM) iteration, which is itself a fast converging method for computing the square root of a number.Background on Newton's Method:Newton's method is based on the Taylor series expansion of a function. Given a function f(x) and its derivativef'(x), the method starts with an initial guess x0 and iteratively updates the approximation using the formula:x_{n+1} = x_n f(x_n) / f'(x_n)。

The chromatic numbers of random hypergraphs

The chromatic numbers of random hypergraphs
Correspondence to: Benny Sudakov * Research supported in part by a DIMACS Graduate Fellowship for a short term visit and by a Charles Clore Fellowship. † Research supported in part by a DIMACS Graduate Fellowship for a short term visit and forms part of a PH.D. thesis written by the author under the supervision of Prof. N. Alon. ᮊ 1998 John Wiley & Sons, Inc. CCC 1042-9832r98r040381-23
Sciences, Tel Aviv University, Tel Aviv, Israel; e-mail: {krivelev, sudakov}@math.tau.ac.il
Recei¨ed 1 March 1997; accepted 18 March 1998
ABSTRACT: For a pair of integers 1 F ␥ - r, the ␥-chromatic number of an r-uniform hypergraph H s ŽV, E. is the minimal k, for which there exists a partition of V into subsets T1, . . . , Tk such that < e l Ti < F ␥ for every e g E. In this paper we determine the asymptotic behavior of the ␥-chromatic number of the random r-uniform hypergraph HrŽ n, p. for all possible values of ␥ and for all values of p down to p s ⌰Ž nyrq1.. ᮊ 1998 John Wiley & Sons,

计数模型 固定效应

计数模型 固定效应

计数模型固定效应英文回答:Introduction.Count models are a class of statistical models used to analyze count data. Count data is data that can only take on non-negative integer values, such as the number of times a customer visits a store or the number of defects in a product. Count models are used to model the distribution of count data and to make inferences about the underlying process that generated the data.Fixed Effects.Fixed effects are a type of effect in which the effect of a particular factor is assumed to be constant across all observations. In other words, the effect of a fixed effect is not allowed to vary from observation to observation. Fixed effects are typically used to control for the effectsof known factors that are not of interest in the analysis. For example, if you are interested in studying the effect of a new marketing campaign on the number of customers who visit a store, you might include a fixed effect for store location to control for the fact that different stores may have different numbers of customers regardless of the marketing campaign.Poisson Regression.Poisson regression is a type of count model that assumes that the distribution of the count data follows a Poisson distribution. The Poisson distribution is a discrete probability distribution that describes the probability of observing a given number of events in a fixed interval of time or space. The Poisson distribution is often used to model count data that is relatively rare and has a constant mean.Negative Binomial Regression.Negative binomial regression is a type of count modelthat assumes that the distribution of the count data follows a negative binomial distribution. The negative binomial distribution is a discrete probabilitydistribution that describes the probability of observing a given number of successes in a sequence of independent experiments, each of which has a constant probability of success. The negative binomial distribution is often used to model count data that is overdispersed, meaning that the variance of the data is greater than the mean.Zero-Inflated Poisson Regression.Zero-inflated Poisson regression is a type of count model that assumes that the count data is a mixture of a Poisson distribution and a degenerate distribution at zero. The degenerate distribution at zero means that there is a non-zero probability that the count will be zero. Zero-inflated Poisson regression is often used to model count data that has a high proportion of zeros.Fixed Effects in Count Models.Fixed effects can be included in count models to control for the effects of known factors that are not of interest in the analysis. For example, if you are interested in studying the effect of a new marketing campaign on the number of customers who visit a store, you might include a fixed effect for store location to control for the fact that different stores may have different numbers of customers regardless of the marketing campaign.Conclusion.Count models are a powerful tool for analyzing count data. Fixed effects can be included in count models to control for the effects of known factors that are not of interest in the analysis. Poisson regression, negative binomial regression, and zero-inflated Poisson regression are three common types of count models that can be used to model different types of count data.中文回答:计数模型中的固定效应。

光学专业词汇(2)

光学专业词汇(2)

光学专业词汇大全retina视网膜Color Blind色盲weak color色弱Myopia-near-sighted近视Sensitivity to Light感光灵敏度boost推进lag behind落后于Hyperopic-far-sighted远视Dynamic Range动态范围critical fusionfrequency临界融合频率CFF临界闪变频率visual sensation视觉hromaticity Diagram色度图olor Temperature色温SV Model色彩模型hue色度aturation饱和度value纯度IE Model 相干红外能量模式omplementary Colors补色ar Pattern条状图形eat body 热稠化pproximate近似iolet紫罗兰ody Curve人体曲线olor Gamut色阶djacent邻近的ormal illumination法线照明rimary colors红黄蓝三原色olor saturation色饱和度olor Triangle颜色三角olor Notation颜色数标法Color Difference色差V Signal Processing电视信号处理amma Correction图像灰度校正onversion T ables换算表ut of balance失衡obble摇晃ack and forth前后lear(white)panel白光板ibrant震动uzzy失真uantum leap量子越迁VGA(800)600 derive from起源自ulprit犯人ender呈递nhibit抑制,约束tride大幅前进lemish污点bstruction障碍物cratch刮伤ubstance物质实质主旨esidue杂质riteria标准arameter参数djacent邻近的接近的synchrony异步luster串群utually互助得lgorithm运算法则hromatic Aberrations色差ovea小凹isual Acuity视觉灵敏度ontrast Sensitivity对比灵敏度emporal(time)Response反应时间endition表演,翻译nimation活泼又生气host重影arallax视差eficient缺乏的不足的isplay panel显示板G. Narrow Gauge)窄轨距ichroic mirror二色性的双色性的rewster Angle布鲁斯特角olarized Light极化光nternal reflection内反射irefringence 双折射xtinction Ratio 消光系数isalignment 未对准uarter Waveplates四分之一波片lemish污点瑕疵eometric几何学的ipple波纹apacitor电容器arallel平行的他antalum钽金属元素exsiccate使干燥xsiccate油管,软膏urnace炉子炉lectrolytic电解的,由电解产生的odule模数nalog类似物ut of the way不恰当incushion针垫拉ateral侧面得ectangle长方形ixture固定设备ontrol kit工具箱VI connector DVI数局线ertical垂直的horizontal 水平的nterlace隔行扫描ullion竖框直楞awtooth锯齿oggle套索钉eypad数字按键键盘angential切线iagnostic tool诊断工具agittal direction径向的ursor position光标位置ray aberration光线相差eighting factor权种因子ariables变量or now暂时,目前.眼下heck box复选框iry disk艾里斑xit pupil出[射光]瞳ptical path difference光称差ith respect to关于iffraction limited衍射极限avefront aberration波阵面相差pherical aberration球面象差araxial focus傍轴焦点hromatic aberration象差ocal coordinate system局部坐标系统oordinate system坐标系rthogonal直角得,正交的onic sections圆锥截面ccount for解决,得分arabolic reflector拋物面反射镜adius of curvature曲率半径pherical mirror球面镜eometrical aberration几何相差ncident radiation入射辐射lobal coordinate总体坐标n terms of根据按照eflected beam反射束YI= or your information供参考onstructive interference相长干涉hase difference相差chromatic singlet消色差透镜nterferometer干涉仪oundary constraint边界约束,池壁效应adii半径oom lenses变焦透镜eam splitters分束器iscrete不连续的,分离的bjective/ye lens物镜/目镜ainframe主机udimentary根本的,未发展的hotographic照相得摄影得axing繁重的,费力得lgebra代数学rigonometry三角学eometry几何学alculus微积分学hilosophy哲学agrange invariant拉格朗日不变量pherical球的ield information场信息tandard Lens标准透镜efracting Surface折射面stigmatism散光DTV高清晰度电视LV( Digital Light Valve)数码光路真空管,简称数字光阀iffraction grating衍射光珊ield angle张角araxial ray trace equations近轴光线轨迹方称ack focal length后焦距rincipal plane主平面ertex顶点,最高点stigmatism散光,因偏差而造成的曲解或错判edial中间的,平均的ariance不一致onic圆锥的,二次曲线ield of view视野ollimator瞄准仪onvolution回旋.盘旋,卷积uzzy失真,模糊berrated异常的symmetry不对称得ndicative可表示得arabolic拋物线得uffice足够,使满足pecification规格,说明书traightforward易懂的,直接了当的,olidify凝固,巩固.Constraints 约束,限制etrology度量衡ield coverage视场,视野ictate口述, 口授, 使听写, 指令, 指示, 命令, 规定rradiance发光, 光辉,辐照度erial空气得,空中得alide卤化物的onochromatic单色的,单频的olychromatic多色的spherical非球面的pherical球面的lignment列队,结盟ower(透镜放大率quiconvergence 同等收敛FL(effective focal length)有效焦距orkhorse广为应用的设备iconvex两面凸的lobal optimization整体最优化oncave凹得,凹面得ylindrical圆柱得olid model实体模型odulation Transfer Function调制传递函数n the heat of在最激烈的时候rotocol协议,规定riplet三重态anity心智健全inc锌,涂锌的elenide 硒化物,硒醚iscellaneous各色各样混在一起, 混杂的, 多才多艺的ersus与...相对olynomial多项式的oefficient系数xplicit function显函数distinct清楚的,截然不同的manate散发, 发出, 发源udimentary根本的,未发展的ntersection角差点RTE= araxial ray trace equation旁轴光线轨迹方程achromats 消色差透镜ardinal points基本方位eparations分色片ashed虚线low up放大verlay覆盖,覆盖图multiplayer 多层的umidity 湿度loat glass浮法玻璃quare one 出发点,端点quare up to 准备开打,坚决地面对eflecting telescope 反射式望远镜diagnostic tools诊断工具ayout plots规划图odulation transfer function调制转换功能FT快速傅里叶变换oint spread function点传播功能avelength波长ngle角度bsorption吸收ystem aperture系统孔径ens units透镜单位avelength range波长范围inglet lens单业透镜pectrum光谱iffraction grating衍射光栅sphere半球的DE= ens data editor Surface radius of curvature表面曲率半径urface thickness表面厚度aterial type材料种类emi-diameter半径ocal length焦距perture type孔径类型perture value孔径值ield of view视场icrons微米, d, and C=blue hydrogen,yellow helium,red hydrogen lines,primary wavelength主波长equential mode连续模式bject surface物表面he front surface of the lens透镜的前表面top光阑he back surface of the lens透镜的后表面he image surface像表面ymmetric相对称的iconvex两面凸的he curvature is positive if the center of curvature of the surface is to the right of the vertex.It is negative if the center of curvature is to the left of the vertex.如果曲率中心在最高点的右边,曲率值为正,如果曲率中心在最高点的左边,则曲率为负mage plane像平面ay Aberration光线相差angential direction切线方向agittal direction径向araxial focus旁轴的arginal边缘的pherical aberration球面像差ptimization Setup最优化调整ariable变量athematical sense数学角度FE= Merit Function Editor,Adding constraints增加约束ocal length焦矩长度perand操作数he effective focal length有效焦矩rimary wavelength主波长nitiate开始pot diagram位图表iry disk艾里斑xial chromatic aberration轴向色差ith respect to关于至于xit pupil出射光瞳PD= ptical path difference光学路径差iffraction limited衍射极限hromatic aberration色差hromatic focal shift色焦距变换araxial focus傍轴焦点xial spherical aberration轴向球差longitudinal spherical aberration 纵向球差:沿光轴方向度量的球差lateral spherical aberration垂轴球差在过近轴光线像点的垂轴平面内度量的球差coma、omatic aberration彗差eridional coma子午彗差agittal coma弧矢彗差stigmatism像散ocal coordinate system本地坐标系统eridional curvature of field子午场曲agittal curvature of field弧矢场曲ecentered lens偏轴透镜orthogonal直角的垂直的onic section圆锥截面ccount for说明,占有,得分tigmatic optical system无散光的光学系统ewtonian telescope牛顿望远镜arabolic reflector抛物面镜oci焦距hromatic aberration,色差uperpose重迭arabola抛物线pherical mirror球面镜MS=oot Mean Square均方根avefront波阵面pot size光点直径aussian quadrature高斯积分ectangular array矩阵列rid size磨粒度PSF= point Spread Function点扩散函数FT= fast Fourier Transform Algorithm快速傅里叶变换ross Section横截面bscurations昏暗ocal coordinates局部坐标系统ignette把…印为虚光照rrow key键盘上的箭头键efractive折射eflective反射n phase同相的协调的ray tracing光线追迹iffraction principles衍射原理rder effect式样提出的顺序效果nergy distribution能量分配onstructive interference相长干涉ispersive色散的inary optics二元光学hase advance相位提前chromatic single消色差单透镜iffractive parameter衍射参数oom lenses变焦透镜thermalized lenses绝热透镜nterferometers干涉计eam splitter分束器witchable component systems可开关组件系统ommon application通用ymmetry对称oundary constraint边界约束ulti-configuration(MC)MC Editor(MCE)perturbation动乱,动摇ndex accuracy折射率准确性ndex homogeneity折射率同种性ndex distribution折射率分配bbe number离差数esidual剩余的stablishing tolerances建立容差igure of merit质量因子olerance criteria公差标准odulation Transfer Function(MTF)调制传递函数oresight视轴,瞄准线Monte Carlo蒙特卡洛olerance operands误差操作数onic constant圆锥常数stigmatic aberration像散误差echanical tilt机械倾斜,机械倾角olerance Data Editor(TDE)公差资料编辑器ompensator补偿棱镜stimated system performance预估了的系统性能teratively反复的,重迭的tatistical dependence统计相关性equential ray trace model连续光线追迹模型mbed埋葬,埋入ultiple多样的,多重的,若干的on-Sequential Components不连续的组件orner cube角隅棱镜,三面直角透镜ensitivity Analysis灵敏度分析aceted reflector有小面的反射镜mit发射,发出est嵌套verlap交迭uter lens外透镜rute force强力eidel像差系数spect ratio长宽比RA边缘光线角RH边缘光线高度synchronous不同时的,异步Apodization factor变迹因子exapolar六角形ithered高频脉冲衍射调制传递函数(MTF),衍射实部传递函数(RTF),衍射虚部传递函数(ITF),衍射相位传递函数(PTF),方波传递函数(SWM)ogarithmic对数的arity奇偶longitudinal aberrations 纵向像差赛得系数:球差(PHA,I),彗差(OMA,2),像散(STI,3),场曲(CUR,4),畸变(IST,5),轴向色差(LA,L)和横向色差(TR,T).横向像差系数:横向球差(SPH),横向弧矢彗差(SCO),横向子午彗差(TCO),横向弧矢场曲(SFC),横向子午场曲(TFC),横向畸变(DIS)横向轴上色差(LAC)。

科技词汇-光学专业英语

科技词汇-光学专业英语

retina视网膜Color Blind色盲weak color色弱Myopia-near-sighted近视Sensitivity to Light感光灵敏度boost推进lag behind落后于Hyperopic-far-sighted远视Dynamic Range动态范围critical fusionfrequency临界融合频率CFF临界闪变频率visual sensation视觉hromaticity Diagram色度图olor Temperature色温SV Model色彩模型hue色度aturation饱和度value纯度IE Model 相干红外能量模式omplementary Colors补色ar Pattern条状图形eat body 热稠化pproximate近似iolet紫罗兰ody Curve人体曲线olor Gamut色阶djacent邻近的ormal illumination法线照明rimary colors红黄蓝三原色olor saturation色饱和度olor Triangle颜色三角olor Notation颜色数标法Color Difference色差V Signal Processing电视信号处理amma Correction图像灰度校正onversion Tables换算表ut of balance失衡obble摇晃ack and forth前后lear(white)panel白光板ibrant震动uzzy失真uantum leap量子越迁VGA(800)600 derive from起源自ulprit犯人ender呈递nhibit抑制,约束tride大幅前进lemish污点bstruction障碍物cratch刮伤ubstance物质实质主旨esidue杂质riteria标准arameter参数djacent邻近的接近的synchrony异步luster串群utually互助得lgorithm运算法则hromatic Aberrations色差ovea小凹isual Acuity视觉灵敏度ontrast Sensitivity对比灵敏度emporal(time)Response反应时间endition表演,翻译nimation活泼又生气host重影arallax视差eficient缺乏的不足的isplay panel显示板G. Narrow Gauge)窄轨距ichroic mirror二色性的双色性的rewster Angle布鲁斯特角olarized Light极化光nternal reflection内反射irefringence 双折射xtinction Ratio 消光系数isalignment 未对准uarter Waveplates四分之一波片lemish污点瑕疵eometric几何学的ipple波纹apacitor电容器arallel平行的他antalum钽金属元素exsiccate使干燥xsiccate油管,软膏urnace炉子炉lectrolytic电解的,由电解产生的odule模数nalog类似物ut of the way不恰当incushion针垫拉ateral侧面得ectangle长方形ixture固定设备ontrol kit工具箱VI connector DVI数局线ertical垂直的horizontal 水平的nterlace隔行扫描ullion竖框直楞awtooth锯齿oggle套索钉eypad数字按键键盘angential切线iagnostic tool诊断工具agittal direction径向的ursor position光标位置rayaberration光线相差eighting factor权种因子ariables变量or now暂时,目前.眼下heck box复选框iry disk艾里斑xit pupil出[射光]瞳ptical path difference光称差ith respect to关于iffraction limited衍射极限avefront aberration波阵面相差pherical aberration球面象差araxial focus傍轴焦点hromatic aberration象差ocal coordinate system局部坐标系统oordinate system坐标系rthogonal直角得,正交的onic sections圆锥截面ccount for解决,得分arabolic reflector物面反射镜adius of curvature曲率半径pherical mirror球面镜eometrical aberration几何相差ncident radiation入射辐射lobal coordinate总体坐标n terms of根据按照eflected beam反射束YI= or your information供参考onstructive interference相长干涉hase difference相差chromatic singlet消色差透镜nterferometer干涉仪oundary constraint边界约束,池壁效应adii半径oom lenses变焦透镜eam splitters分束器iscrete不连续的,分离的bjective/ye lens物镜/目镜ainframe主机udimentary根本的,未发展的hotographic照相得摄影得axing繁重的,费力得lgebra代数学rigonometry三角学eometry几何学alculus微积分学hilosophy哲学agrange invariant拉格朗日不变量pherical球的ield information场信息tandard Lens标准透镜efracting Surface折射面stigmatism散光DTV高清晰度电视LV( Digital Light Valve)数码光路真空管,简称数字光阀iffraction grating衍射光珊ield angle张角araxial ray trace equations近轴光线轨迹方称ack focal length后焦距rincipal plane主平面ertex顶点,最高点stigmatism散光,因偏差而造成的曲解或错判edial中间的,平均的ariance不一致onic圆锥的,二次曲线ield of view视野ollimator瞄准仪onvolution回旋.盘旋,卷积uzzy失真,模糊berrated异常的symmetry不对称得ndicative可表示得arabolic物线得uffice足够,使满足pecification规格,说明书traightforward易懂的,直接了当的,olidify凝固,巩固.Constraints 约束,限制etrology度量衡ield coverage视场,视野ictate口述, 口授, 使听写,指令, 指示, 命令, 规定rradiance发光, 光辉,辐照度erial空气得,空中得alide卤化物的onochromatic单色的,单频的olychromatic多色的spherical非球面的pherical球面的lignment列队,结盟ower(透镜放大率quiconvergence 同等收敛FL(effective focal length)有效焦距orkhorse广为应用的设备iconvex两面凸的lobal optimization整体最优化oncave凹得,凹面得ylindrical圆柱得olid model实体模型odulation Transfer Function 调制传递函数n the heat of在最激烈的时候rotocol协议,规定riplet三重态anity心智健全inc锌,涂锌的elenide 硒化物,硒醚iscellaneous各色各样混在一起, 混杂的, 多才多艺的ersus与...相对olynomial多项式的oefficient系数xplicit function显函数distinct清楚的,截然不同的manate散发, 发出, 发源udimentary根本的,未发展的ntersection角差点RTE= araxial ray trace equation旁轴光线轨迹方程achromats 消色差透镜ardinal points基本方位eparations分色片ashed虚线low up放大verlay覆盖,覆盖图multiplayer 多层的umidity 湿度loat glass浮法玻璃quare one 出发点,端点quare up to 准备开打,坚决地面对eflecting telescope 反射式望远镜diagnostic tools诊断工具ayout plots规划图odulation transfer function调制转换功能FT快速傅里叶变换oint spread function点传播功能avelength波长ngle角度bsorption吸收ystem aperture系统孔径ens units透镜单位avelength range波长范围inglet lens单业透镜pectrum光谱iffraction grating衍射光栅sphere半球的DE= ens data editor Surfaceradius of curvature表面曲率半径urface thickness表面厚度aterial type材料种类emi-diameter半径ocal length焦距perture type孔径类型perture value孔径值ield of view视场icrons微米, d, and C=blue hydrogen,yellow helium,red hydrogen lines,primary wavelength主波长equential mode连续模式bject surface物表面he front surface of the lens透镜的前表面top光阑he back surface of the lens透镜的后表面he image surface像表面ymmetric相对称的iconvex两面凸的he curvature is positive if thecenter of curvature of thesurface is to the right of the vertex.It is negative if the center of curvature is to the left of the vertex.如果曲率中心在最高点的右边,曲率值为正,如果曲率中心在最高点的左边,则曲率为负mage plane像平面ay Aberration光线相差angential direction切线方向agittal direction径向araxial focus旁轴的arginal边缘的pherical aberration球面像差ptimization Setup最优化调整ariable变量athematical sense数学角度FE= Merit Function Editor, Adding constraints增加约束ocal length焦矩长度perand操作数he effective focal length有效焦矩rimary wavelength主波长nitiate开始pot diagram位图表iry disk艾里斑xial chromatic aberration轴向色差ith respect to关于至于xit pupil出射光瞳PD= ptical path difference光学路径差iffraction limited衍射极限hromatic aberration色差hromatic focal shift色焦距变换araxial focus傍轴焦点xial spherical aberration轴向球差longitudinal sphericalaberration 纵向球差:沿光轴方向度量的球差lateral spherical aberration垂轴球差在过近轴光线像点的垂轴平面内度量的球差coma、omatic aberration彗差eridional coma子午彗差agittal coma弧矢彗差stigmatism像散ocal coordinate system本地坐标系统eridional curvature of field子午场曲agittal curvature of field弧矢场曲ecentered lens偏轴透镜orthogonal直角的垂直的onic section圆锥截面ccount for说明,占有,得分tigmatic optical system无散光的光学系统ewtonian telescope牛顿望远镜arabolic reflector抛物面镜oci焦距hromatic aberration,色差uperpose重迭arabola抛物线pherical mirror球面镜MS=oot Mean Square均方根avefront波阵面pot size光点直径aussian quadrature高斯积分ectangular array矩阵列rid size磨粒度PSF= point Spread Function 点扩散函数FT= fast Fourier Transform Algorithm快速傅里叶变换ross Section横截面bscurations昏暗ocal coordinates局部坐标系统ignette把…印为虚光照rrow key键盘上的箭头键efractive折射eflective反射n phase同相的协调的ray tracing光线追迹iffraction principles衍射原理rder effect式样提出的顺序效果nergy distribution能量分配onstructive interference相长干涉ispersive色散的inary optics二元光学hase advance相位提前chromatic single消色差单透镜iffractive parameter衍射参数oom lenses变焦透镜thermalized lenses绝热透镜nterferometers干涉计eam splitter分束器witchable componentsystems可开关组件系统ommon application通用ymmetry对称oundary constraint边界约束ulti-configuration(MC)MCEditor(MCE)perturbation动乱,动摇ndex accuracy折射率准确性ndex homogeneity折射率同种性ndex distribution折射率分配bbe number离差数esidual剩余的stablishing tolerances建立容差igure of merit质量因子olerance criteria公差标准odulation TransferFunction(MTF)调制传递函数oresight视轴,瞄准线Monte Carlo蒙特卡洛olerance operands误差操作数onic constant圆锥常数stigmatic aberration像散误差echanical tilt机械倾斜,机械倾角olerance Data Editor(TDE)公差资料编辑器ompensator补偿棱镜stimated systemperformance预估了的系统性能teratively反复的,重迭的tatistical dependence统计相关性equential ray trace model连续光线追迹模型mbed埋葬,埋入ultiple多样的,多重的,若干的on-Sequential Components不连续的组件orner cube角隅棱镜,三面直角透镜ensitivity Analysis灵敏度分析aceted reflector有小面的反射镜mit发射,发出est嵌套verlap交迭uter lens外透镜rute force强力eidel像差系数spect ratio长宽比RA边缘光线角RH边缘光线高度synchronous不同时的,异步Apodization factor变迹因子exapolar六角形ithered高频脉冲衍射调制传递函数(MTF),衍射实部传递函数(RTF),衍射虚部传递函数(ITF),衍射相位传递函数(PTF),方波传递函数(SWM)ogarithmic对数的arity奇偶longitudinal aberrations 纵向像差赛得系数:球差(PHA,I),彗差(OMA,2),像散(STI,3),场曲(CUR,4),畸变(IST,5),轴向色差(LA,L)和横向色差(TR,T).横向像差系数:横向球差(SPH),横向弧矢彗差(SCO),横向子午彗差(TCO),横向弧矢场曲(SFC),横向子午场曲(TFC),横向畸变(DIS)横向轴上色差(LAC)。

超几何分布的英语

超几何分布的英语

超几何分布的英语Here is an essay on the topic of the hypergeometric distribution, written in English with more than 1000 words. The title and any additional instructions have been omitted as requested.The hypergeometric distribution is a discrete probability distribution that describes the number of successes in a sequence of n draws from a finite population without replacement. In other words, it models the probability of obtaining a certain number of items with a desired characteristic from a finite population, given that the population is not replenished after each draw. This distribution is particularly useful in situations where the population size is relatively small, and the sampling is done without replacement, such as in quality control, survey sampling, and experimental design.The hypergeometric distribution is characterized by three parameters: the population size (N), the number of items with the desired characteristic in the population (K), and the number of items drawn from the population (n). The probability mass function (PMF) of the hypergeometric distribution is given by the formula:P(X = x) = (C(K, x) * C(N-K, n-x)) / C(N, n)where:- X is the random variable representing the number of items with the desired characteristic in the n draws- x is the observed value of X- C(a, b) is the binomial coefficient, which represents the number of ways to choose b items from a itemsThe hypergeometric distribution is related to the binomial distribution, but the key difference is that in the binomial distribution, the trials are independent and the probability of success remains constant, whereas in the hypergeometric distribution, the trials are not independent and the probability of success changes with each draw.One of the main applications of the hypergeometric distribution is in quality control. Suppose a manufacturer has produced a batch of N items, and K of them are defective. The manufacturer wants to inspect a sample of n items to determine the quality of the batch. The hypergeometric distribution can be used to calculate the probability of finding x defective items in the sample, which can help the manufacturer make decisions about the batch.Another application of the hypergeometric distribution is in survey sampling. Suppose a researcher wants to estimate the proportion ofa certain characteristic in a population, but the population size is relatively small. The researcher can draw a sample of n individuals from the population and use the hypergeometric distribution to calculate the probability of observing a certain number of individuals with the desired characteristic.The hypergeometric distribution also has applications in experimental design. For example, in a clinical trial, researchers may want to compare the effectiveness of a new drug to a placebo. The researchers can assign participants to the treatment or control group using a hypergeometric distribution, which ensures that the number of participants in each group is balanced.One of the key properties of the hypergeometric distribution is that it is a discrete distribution, meaning that the random variable X can only take on integer values. This property makes the distribution particularly useful in situations where the population size is finite and the sampling is done without replacement.Another important property of the hypergeometric distribution is that it is unimodal, meaning that the probability mass function has a single peak. The location of the peak depends on the values of the three parameters (N, K, and n), and the distribution can be left-skewed, right-skewed, or symmetric depending on the values of these parameters.The hypergeometric distribution also has several special cases. For example, when the population size N is large compared to the sample size n, the hypergeometric distribution approaches the binomial distribution. Similarly, when the number of items with the desired characteristic K is small compared to the population size N, the hypergeometric distribution approaches the Poisson distribution.In addition to its applications in quality control, survey sampling, and experimental design, the hypergeometric distribution has also been used in other areas, such as genetics, ecology, and finance. For example, in genetics, the hypergeometric distribution can be used to model the probability of observing a certain number of mutations in a gene sequence, while in ecology, it can be used to model the probability of observing a certain number of species in a sample of a habitat.Overall, the hypergeometric distribution is a powerful and versatile probability distribution that has numerous applications in a wide range of fields. Its ability to model the probability of success in a finite population without replacement makes it a valuable tool for researchers and practitioners in many different domains.。

The dispersion equation for a wave number of the electromagnetic wave in a random medium of

The dispersion equation for a wave number of the electromagnetic wave in a random medium of

Introduction
Under certain conditions the electrochemical anodization of metals leads to the formation of the oxide layer with parallel cylindrical pores on the surface of metal. The radius of the cylinders is much less than the thickness of the layer. These oxide films are used as corrosion-protective, strengthening, decorative coatings and attract much attention in microelectronics, in particular, for the creation of non-linear and active thin-film elements, and also for substrates of large hybrid microcircuits. Porous oxides are perspective for multilevel systems of interconnections. In dependence on the conditions of anodization and kind of metal it is possible to obtain films with different degree of ordering in pore placement of pores. The placement of pores is maximally chaotic when the pores are placed randomly and could be overlapped. The overlapping pores form the cavities of complex configurations. The placement of pores is maximally ordered, when the points of the cylinder axes intersection with the plane perpendicular to the axes lay in the nodes of some lattice, for example a hexagonal one. An investigation of the optical properties of oxide films allows to find a degree of pores ordering. If the wavelength is much larger than the radius of pores, the optical properties of the porous layer can be described by the effective refractive index. This index is to be found from the dispersion equations. The dispersion equation for the effective refractive index of the system of parallel nonoverlapping cylindrical fibres in media was deduced in the work [1]. The equation allows to describe the optical properties of the layer with the regular pores placement. In present work we obtain the dispersion equation for a medium with chaotic distribution of pores (the pores are located randomly and can be overlapped). We also analyse an influence of regularity on the effective refractive index.

GMAT数学术语

GMAT数学术语

retail price 零售价 /per capita 每人 cent 美分/penny 一美分硬币 nickel 5美分硬币 /dime 一角硬币 dozen 打(12个) / score 廿 (20个) Centigrade 摄氏/Fahrenheit 华氏 quart 夸脱/ gallon 加仑
proper fraction 真分数 improper fraction 假分数 mixed number 带分数 vulgar /common fraction 普通分数 simple fraction 简分数 complex fraction 繁分数 numerator 分子 denominator 分母 common denominator 公分母 quarter 四分之一 ordinary /decimal scale 十进制 tens 十位 , units 个位 tenths unit 十分位
central angle 圆心角 interior angle 内角 exterior angle 外角 acute angle 锐角 obtuse angle 钝角 trigonometry 三角学 equilateral triangle 等边三角形 scalene triangle 不等边三角形 isoscele oblique 斜三角形 inscribed triangle 内接三角形
几何-坐标
arm 直角三角形的股 hypotenuse 斜边 included side 夹边 Pythagorean theorem 勾股定理 leg 三角形的直角边 median(三角形的)中线 base底边,底数 opposite 直角三角形中的对边 cross section 横截面 vertex (复数形式vertices)顶点 tangent 切线的 complex plane 复平面

RN-coding of numbers definition and some properties

RN-coding of numbers definition and some properties
Laboratoire de l’Informatique du Parallélisme
École Normale Supérieure de Lyon Unité Mixte de Recherche CNRS-INRIA-ENS LYON-UCBL no 5668
RN-coding of numbers: definition and some properties
Peter Kornerup , Jean-Michel Muller
October 2004
Research Report No 2004-43
École Normale Supérieure de Lyon
46 Allée d’Italie, 69364 Lyon Cedex 07, France Téléphone : +33(0)4.72.72.80.37 Télécopieur : +33(0)4.72.72.80.80 Adresse électronique : lip@ens-lyon.fr
RN-coding of numbers: definition and some properties
Peter Kornerup , Jean-Michel Muller October 2004
Abstract We define RN-codings as radix-β signed representations of numbers for which rounding to the nearest is always identical to truncation. After giving characterizations of such representations, we investigate some of their properties, and we suggest algorithms for conversion to and from these codings. Keywords: Computer arithmetic, number systems

Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease trans

Reproduction  numbers and sub-threshold endemic equilibria for compartmental models of disease trans

Reproduction numbers and sub-threshold endemicequilibria for compartmental models of disease transmissionP.van den Driesschea,1,James Watmough b,*,2aDepartment of Mathematics and Statistics,University of Victoria,Victoria,BC,Canada V8W 3P4b Department of Mathematics and Statistics,University of New Brunswick,Fredericton,NB,Canada E3B 5A3Received 26April 2001;received in revised form 27June 2001;accepted 27June 2001Dedicated to the memory of John JacquezAbstractA precise definition of the basic reproduction number,R 0,is presented for a general compartmental disease transmission model based on a system of ordinary differential equations.It is shown that,if R 0<1,then the disease free equilibrium is locally asymptotically stable;whereas if R 0>1,then it is unstable.Thus,R 0is a threshold parameter for the model.An analysis of the local centre manifold yields a simple criterion for the existence and stability of super-and sub-threshold endemic equilibria for R 0near one.This criterion,together with the definition of R 0,is illustrated by treatment,multigroup,staged progression,multistrain and vector–host models and can be applied to more complex models.The results are significant for disease control.Ó2002Elsevier Science Inc.All rights reserved.Keywords:Basic reproduction number;Sub-threshold equilibrium;Disease transmission model;Disease control1.IntroductionOne of the most important concerns about any infectious disease is its ability to invade a population.Many epidemiological models have a disease free equilibrium (DFE)at whichtheMathematical Biosciences 180(2002)29–48/locate/mbs*Corresponding author.Tel.:+1-5064587323;fax:+1-5064534705.E-mail addresses:pvdd@math.uvic.ca (P.van den Driessche),watmough@unb.ca (J.Watmough).URL:http://www.math.unb.ca/$watmough.1Research supported in part by an NSERC Research Grant,the University of Victoria Committee on faculty research and travel and MITACS.2Research supported by an NSERC Postdoctoral Fellowship tenured at the University of Victoria.0025-5564/02/$-see front matter Ó2002Elsevier Science Inc.All rights reserved.PII:S0025-5564(02)00108-630P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–48population remains in the absence of disease.These models usually have a threshold parameter, known as the basic reproduction number,R0,such that if R0<1,then the DFE is locally as-ymptotically stable,and the disease cannot invade the population,but if R0>1,then the DFE is unstable and invasion is always possible(see the survey paper by Hethcote[1]).Diekmann et al.[2]define R0as the spectral radius of the next generation matrix.We write down in detail a general compartmental disease transmission model suited to heterogeneous populations that can be modelled by a system of ordinary differential equations.We derive an expression for the next generation matrix for this model and examine the threshold R0¼1in detail.The model is suited to a heterogeneous population in which the vital and epidemiological parameters for an individual may depend on such factors as the stage of the disease,spatial position,age or behaviour.However,we assume that the population can be broken into homo-geneous subpopulations,or compartments,such that individuals in a given compartment are indistinguishable from one another.That is,the parameters may vary from compartment to compartment,but are identical for all individuals within a given compartment.We also assume that the parameters do not depend on the length of time an individual has spent in a compart-ment.The model is based on a system of ordinary equations describing the evolution of the number of individuals in each compartment.In addition to showing that R0is a threshold parameter for the local stability of the DFE, we apply centre manifold theory to determine the existence and stability of endemic equilib-ria near the threshold.We show that some models may have unstable endemic equilibria near the DFE for R0<1.This suggests that even though the DFE is locally stable,the disease may persist.The model is developed in Section2.The basic reproduction number is defined and shown to bea threshold parameter in Section3,and the definition is illustrated by several examples in Section4.The analysis of the centre manifold is presented in Section5.The epidemiological ramifications of the results are presented in Section6.2.A general compartmental epidemic model for a heterogeneous populationConsider a heterogeneous population whose individuals are distinguishable by age,behaviour, spatial position and/or stage of disease,but can be grouped into n homogeneous compartments.A general epidemic model for such a population is developed in this section.Let x¼ðx1;...;x nÞt, with each x i P0,be the number of individuals in each compartment.For clarity we sort the compartments so that thefirst m compartments correspond to infected individuals.The distinc-tion between infected and uninfected compartments must be determined from the epidemiological interpretation of the model and cannot be deduced from the structure of the equations alone,as we shall discuss below.It is plausible that more than one interpretation is possible for some models.A simple epidemic model illustrating this is given in Section4.1.The basic reproduction number can not be determined from the structure of the mathematical model alone,but depends on the definition of infected and uninfected compartments.We define X s to be the set of all disease free states.That isX s¼f x P0j x i¼0;i¼1;...;m g:In order to compute R0,it is important to distinguish new infections from all other changes inpopulation.Let F iðxÞbe the rate of appearance of new infections in compartment i,Vþi ðxÞbe therate of transfer of individuals into compartment i by all other means,and VÀi ðxÞbe the rate oftransfer of individuals out of compartment i.It is assumed that each function is continuously differentiable at least twice in each variable.The disease transmission model consists of non-negative initial conditions together with the following system of equations:_x i¼f iðxÞ¼F iðxÞÀV iðxÞ;i¼1;...;n;ð1Þwhere V i¼VÀi ÀVþiand the functions satisfy assumptions(A1)–(A5)described below.Sinceeach function represents a directed transfer of individuals,they are all non-negative.Thus,(A1)if x P0,then F i;Vþi ;VÀiP0for i¼1;...;n.If a compartment is empty,then there can be no transfer of individuals out of the compartment by death,infection,nor any other means.Thus,(A2)if x i¼0then VÀi ¼0.In particular,if x2X s then VÀi¼0for i¼1;...;m.Consider the disease transmission model given by(1)with f iðxÞ,i¼1;...;n,satisfying con-ditions(A1)and(A2).If x i¼0,then f iðxÞP0and hence,the non-negative cone(x i P0, i¼1;...;n)is forward invariant.By Theorems1.1.8and1.1.9of Wiggins[3,p.37]for each non-negative initial condition there is a unique,non-negative solution.The next condition arises from the simple fact that the incidence of infection for uninfected compartments is zero.(A3)F i¼0if i>m.To ensure that the disease free subspace is invariant,we assume that if the population is free of disease then the population will remain free of disease.That is,there is no(density independent) immigration of infectives.This condition is stated as follows:(A4)if x2X s then F iðxÞ¼0and VþiðxÞ¼0for i¼1;...;m.The remaining condition is based on the derivatives of f near a DFE.For our purposes,we define a DFE of(1)to be a(locally asymptotically)stable equilibrium solution of the disease free model,i.e.,(1)restricted to X s.Note that we need not assume that the model has a unique DFE. Consider a population near the DFE x0.If the population remains near the DFE(i.e.,if the introduction of a few infective individuals does not result in an epidemic)then the population will return to the DFE according to the linearized system_x¼Dfðx0ÞðxÀx0Þ;ð2Þwhere Dfðx0Þis the derivative½o f i=o x j evaluated at the DFE,x0(i.e.,the Jacobian matrix).Here, and in what follows,some derivatives are one sided,since x0is on the domain boundary.We restrict our attention to systems in which the DFE is stable in the absence of new infection.That is, (A5)If FðxÞis set to zero,then all eigenvalues of Dfðx0Þhave negative real parts.P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–4831The conditions listed above allow us to partition the matrix Df ðx 0Þas shown by the following lemma.Lemma 1.If x 0is a DFE of (1)and f i ðx Þsatisfies (A1)–(A5),then the derivatives D F ðx 0Þand D V ðx 0Þare partitioned asD F ðx 0Þ¼F 000 ;D V ðx 0Þ¼V 0J 3J 4;where F and V are the m Âm matrices defined byF ¼o F i o x j ðx 0Þ !and V ¼o V i o x jðx 0Þ !with 16i ;j 6m :Further ,F is non-negative ,V is a non-singular M-matrix and all eigenvalues of J 4have positive real part .Proof.Let x 02X s be a DFE.By (A3)and (A4),ðo F i =o x j Þðx 0Þ¼0if either i >m or j >m .Similarly,by (A2)and (A4),if x 2X s then V i ðx Þ¼0for i 6m .Hence,ðo V i =o x j Þðx 0Þ¼0for i 6m and j >m .This shows the stated partition and zero blocks.The non-negativity of F follows from (A1)and (A4).Let f e j g be the Euclidean basis vectors.That is,e j is the j th column of the n Ân identity matrix.Then,for j ¼1;...;m ,o V i o x jðx 0Þ¼lim h !0þV i ðx 0þhe j ÞÀV i ðx 0Þh :To show that V is a non-singular M-matrix,note that if x 0is a DFE,then by (A2)and (A4),V i ðx 0Þ¼0for i ¼1;...;m ,and if i ¼j ,then the i th component of x 0þhe j ¼0and V i ðx 0þhe j Þ60,by (A1)and (A2).Hence,o V i =o x j 0for i m and j ¼i and V has the Z sign pattern (see Appendix A).Additionally,by (A5),all eigenvalues of V have positive real parts.These two conditions imply that V is a non-singular M-matrix [4,p.135(G 20)].Condition (A5)also implies that the eigenvalues of J 4have positive real part.Ã3.The basic reproduction numberThe basic reproduction number,denoted R 0,is ‘the expected number of secondary cases produced,in a completely susceptible population,by a typical infective individual’[2];see also [5,p.17].If R 0<1,then on average an infected individual produces less than one new infected individual over the course of its infectious period,and the infection cannot grow.Conversely,if R 0>1,then each infected individual produces,on average,more than one new infection,and the disease can invade the population.For the case of a single infected compartment,R 0is simply the product of the infection rate and the mean duration of the infection.However,for more complicated models with several infected compartments this simple heuristic definition of R 0is32P.van den Driessche,J.Watmough /Mathematical Biosciences 180(2002)29–48insufficient.A more general basic reproduction number can be defined as the number of new infections produced by a typical infective individual in a population at a DFE.To determine the fate of a‘typical’infective individual introduced into the population,we consider the dynamics of the linearized system(2)with reinfection turned off.That is,the system _x¼ÀD Vðx0ÞðxÀx0Þ:ð3ÞBy(A5),the DFE is locally asymptotically stable in this system.Thus,(3)can be used to de-termine the fate of a small number of infected individuals introduced to a disease free population.Let wi ð0Þbe the number of infected individuals initially in compartment i and letwðtÞ¼w1ðtÞ;...;w mðtÞðÞt be the number of these initially infected individuals remaining in the infected compartments after t time units.That is the vector w is thefirst m components of x.The partitioning of D Vðx0Þimplies that wðtÞsatisfies w0ðtÞ¼ÀV wðtÞ,which has the unique solution wðtÞ¼eÀVt wð0Þ.By Lemma1,V is a non-singular M-matrix and is,therefore,invertible and all of its eigenvalues have positive real parts.Thus,integrating F wðtÞfrom zero to infinity gives the expected number of new infections produced by the initially infected individuals as the vector FVÀ1wð0Þ.Since F is non-negative and V is a non-singular M-matrix,VÀ1is non-negative[4,p.137 (N38)],as is FVÀ1.To interpret the entries of FVÀ1and develop a meaningful definition of R0,consider the fate of an infected individual introduced into compartment k of a disease free population.The(j;k)entry of VÀ1is the average length of time this individual spends in compartment j during its lifetime, assuming that the population remains near the DFE and barring reinfection.The(i;j)entry of F is the rate at which infected individuals in compartment j produce new infections in compartment i. Hence,the(i;k)entry of the product FVÀ1is the expected number of new infections in com-partment i produced by the infected individual originally introduced into compartment k.Fol-lowing Diekmann et al.[2],we call FVÀ1the next generation matrix for the model and set R0¼qðFVÀ1Þ;ð4Þwhere qðAÞdenotes the spectral radius of a matrix A.The DFE,x0,is locally asymptotically stable if all the eigenvalues of the matrix Dfðx0Þhave negative real parts and unstable if any eigenvalue of Dfðx0Þhas a positive real part.By Lemma1, the eigenvalues of Dfðx0Þcan be partitioned into two sets corresponding to the infected and uninfected compartments.These two sets are the eigenvalues of FÀV and those ofÀJ4.Again by Lemma1,the eigenvalues ofÀJ4all have negative real part,thus the stability of the DFE is determined by the eigenvalues of FÀV.The following theorem states that R0is a threshold parameter for the stability of the DFE.Theorem2.Consider the disease transmission model given by(1)with fðxÞsatisfying conditions (A1)–(A5).If x0is a DFE of the model,then x0is locally asymptotically stable if R0<1,but un-stable if R0>1,where R0is defined by(4).Proof.Let J1¼FÀV.Since V is a non-singular M-matrix and F is non-negative,ÀJ1¼VÀF has the Z sign pattern(see Appendix A).Thus,sðJ1Þ<0()ÀJ1is a non-singular M-matrix;P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–483334P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–48where sðJ1Þdenotes the maximum real part of all the eigenvalues of the matrix J1(the spectral abscissa of J1).Since FVÀ1is non-negative,ÀJ1VÀ1¼IÀFVÀ1also has the Z sign pattern.Ap-plying Lemma5of Appendix A,with H¼V and B¼ÀJ1¼VÀF,we have ÀJ1is a non-singular M-matrix()IÀFVÀ1is a non-singular M-matrix:Finally,since FVÀ1is non-negative,all eigenvalues of FVÀ1have magnitude less than or equal to qðFVÀ1Þ.Thus,IÀFVÀ1is a non-singular M-matrix;()qðFVÀ1Þ<1:Hence,sðJ1Þ<0if and only if R0<1.Similarly,it follows thatsðJ1Þ¼0()ÀJ1is a singular M-matrix;()IÀFVÀ1is a singular M-matrix;()qðFVÀ1Þ¼1:The second equivalence follows from Lemma6of Appendix A,with H¼V and K¼F.The remainder of the equivalences follow as with the non-singular case.Hence,sðJ1Þ¼0if and only if R0¼1.It follows that sðJ1Þ>0if and only if R0>1.ÃA similar result can be found in the recent book by Diekmann and Heesterbeek[6,Theorem6.13].This result is known for the special case in which J1is irreducible and V is a positive di-agonal matrix[7–10].The special case in which V has positive diagonal and negative subdiagonal elements is proven in Hyman et al.[11,Appendix B];however,our approach is much simpler(see Section4.3).4.Examples4.1.Treatment modelThe decomposition of fðxÞinto the components F and V is illustrated using a simple treat-ment model.The model is based on the tuberculosis model of Castillo-Chavez and Feng[12,Eq.(1.1)],but also includes treatment failure used in their more elaborate two-strain model[12,Eq.(2.1)].A similar tuberculosis model with two treated compartments is proposed by Blower et al.[13].The population is divided into four compartments,namely,individuals susceptible to tu-berculosis(S),exposed individuals(E),infectious individuals(I)and treated individuals(T).The dynamics are illustrated in Fig.1.Susceptible and treated individuals enter the exposed com-partment at rates b1I=N and b2I=N,respectively,where N¼EþIþSþT.Exposed individuals progress to the infectious compartment at the rate m.All newborns are susceptible,and all indi-viduals die at the rate d>0.Thus,the core of the model is an SEI model using standard inci-dence.The treatment rates are r1for exposed individuals and r2for infectious individuals. However,only a fraction q of the treatments of infectious individuals are successful.Unsuc-cessfully treated infectious individuals re-enter the exposed compartment(p¼1Àq).The diseasetransmission model consists of the following differential equations together with non-negative initial conditions:_E¼b1SI=Nþb2TI=NÀðdþmþr1ÞEþpr2I;ð5aÞ_I¼m EÀðdþr2ÞI;ð5bÞ_S¼bðNÞÀdSÀb1SI=N;ð5cÞ_T¼ÀdTþr1Eþqr2IÀb2TI=N:ð5dÞProgression from E to I and failure of treatment are not considered to be new infections,but rather the progression of an infected individual through the various compartments.Hence,F¼b1SI=Nþb2TI=NB B@1C CA and V¼ðdþmþr1ÞEÀpr2IÀm Eþðdþr2ÞIÀbðNÞþdSþb1SI=NdTÀr1EÀqr2Iþb2TI=NB B@1C CA:ð6ÞThe infected compartments are E and I,giving m¼2.An equilibrium solution with E¼I¼0has the form x0¼ð0;0;S0;0Þt,where S0is any positive solution of bðS0Þ¼dS0.This will be a DFE if and only if b0ðS0Þ<d.Without loss of generality,assume S0¼1is a DFE.Then,F¼0b100;V¼dþmþr1Àpr2Àm dþr2;givingVÀ1¼1ðdþmþr1Þðdþr2ÞÀm pr2dþr2pr2m dþmþr1and R0¼b1m=ððdþmþr1Þðdþr2ÞÀm pr2Þ.A heuristic derivation of the(2;1)entry of VÀ1and R0are as follows:a fraction h1¼m=ðdþmþr1Þof exposed individuals progress to compartment I,a fraction h2¼pr2=ðdþr2Þof infectious individuals re-enter compartment E.Hence,a fractionh1of exposed individuals pass through compartment I at least once,a fraction h21h2passthroughat least twice,and a fraction h k 1h k À12pass through at least k times,spending an average of s ¼1=ðd þr 2Þtime units in compartment I on each pass.Thus,an individual introduced into com-partment E spends,on average,s ðh 1þh 21h 2þÁÁÁÞ¼s h 1=ð1Àh 1h 2Þ¼m =ððd þm þr 1Þðd þr 2ÞÀm pr 2Þtime units in compartment I over its expected lifetime.Multiplying this by b 1gives R 0.The model without treatment (r 1¼r 2¼0)is an SEI model with R 0¼b 1m =ðd ðd þm ÞÞ.The interpretation of R 0for this case is simpler.Only a fraction m =ðd þm Þof exposed individuals progress from compartment E to compartment I ,and individuals entering compartment I spend,on average,1=d time units there.Although conditions (A1)–(A5)do not restrict the decomposition of f i ðx Þto a single choice for F i ,only one such choice is epidemiologically correct.Different choices for the function F lead to different values for the spectral radius of FV À1,as shown in Table 1.In column (a),treatment failure is considered to be a new infection and in column (b),both treatment failure and pro-gression to infectiousness are considered new infections.In each case the condition q ðFV À1Þ<1yields the same portion of parameter space.Thus,q ðFV À1Þis a threshold parameter in both cases.The difference between the numbers lies in the epidemiological interpretation rather than the mathematical analysis.For example,in column (a),the infection rate is b 1þpr 2and an exposed individual is expected to spend m =ððd þm þr 1Þðd þr 2ÞÞtime units in compartment I .However,this reasoning is biologically flawed since treatment failure does not give rise to a newly infected individual.Table 1Decomposition of f leading to alternative thresholds(a)(b)Fb 1SI =N þb 2TI =N þpr 2I 0000B B @1C C A b 1SI =N þb 2TI =N þpr 2I m E 000B B @1C C A Vðd þm þr 1ÞE Àm E þðd þr 2ÞI Àb ðN ÞþdS þb 1SI =N dT Àr 1E Àqr 2I þb 2TI =N 0B B @1C C A ðd þm þr 1ÞE ðd þr 2ÞI Àb ðN ÞþdS þb 1SI =N dT Àr 1E Àqr 2I þb 2TI =N 0B B @1C C A F0b 1þpr 200 0b 1þpr 2m 0 V d þm þr 10Àm d þr 2d þm þr 100d þr 2 q (FV À1)b 1m þpr 2mðd þm þr 1Þðd þr 2Þffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffib 1m þpr 2mðd þm þr 1Þðd þr 2Þs 36P.van den Driessche,J.Watmough /Mathematical Biosciences 180(2002)29–484.2.Multigroup modelIn the epidemiological literature,the term‘multigroup’usually refers to the division of a het-erogeneous population into several homogeneous groups based on individual behaviour(e.g., [14]).Each group is then subdivided into epidemiological compartments.The majority of mul-tigroup models in the literature are used for sexually transmitted diseases,such as HIV/AIDS or gonorrhea,where behaviour is an important factor in the probability of contracting the disease [7,8,14,15].As an example,we use an m-group SIRS-vaccination model of Hethcote[7,14]with a generalized incidence term.The sample model includes several SI multigroup models of HIV/ AIDS as special cases[8,15].The model equations are as follows:_I i ¼X mj¼1b ijðxÞS i I jÀðd iþc iþ iÞI i;ð7aÞ_S i ¼ð1Àp iÞb iÀðd iþh iÞS iþr i R iÀX mj¼1b ijðxÞS i I j;ð7bÞ_Ri¼p i b iþc i I iþh i S iÀðd iþr iÞR i;ð7cÞfor i¼1;...;m,where x¼ðI1;...;I m;S1;...;S m;R1;...;R mÞt.Susceptible and removed individu-als die at the rate d i>0,whereas infected individuals die at the faster rate d iþ i.Infected in-dividuals recover with temporary immunity from re-infection at the rate c i,and immunity lasts an expected1=r i time units.All newborns are susceptible,and a constant fraction b i are born into each group.A fraction p i of newborns are vaccinated at birth.Thereafter,susceptible individuals are vaccinated at the rate h i.The incidence,b ijðxÞdepends on individual behaviour,which determines the amount of mixing between the different groups(see,e.g.,Jacquez et al.[16]). The DFE for this model isx0¼ð0;...;0;S01;...;S0m;R01;...;R0mÞt;whereS0 i ¼b i d ið1Àp iÞþr iðÞd iðd iþh iþr iÞ;R0 i ¼b iðh iþd i p iÞd iðd iþh iþr iÞ:Linearizing(7a)about x¼x0givesF¼S0i b ijðx0ÞÂÃandV¼½ðd iþc iþ iÞd ij ;where d ij is one if i¼j,but zero otherwise.Thus,FVÀ1¼S0i b ijðx0Þ=ðd iÂþc iþ iÞÃ:P.van den Driessche,J.Watmough/Mathematical Biosciences180(2002)29–4837For the special case with b ij separable,that is,b ijðxÞ¼a iðxÞk jðxÞ,F has rank one,and the basic reproduction number isR0¼X mi¼1S0ia iðx0Þk iðx0Þd iþc iþ i:ð8ÞThat is,the basic reproduction number of the disease is the sum of the‘reproduction numbers’for each group.4.3.Staged progression modelThe staged progression model[11,Section3and Appendix B]has a single uninfected com-partment,and infected individuals progress through several stages of the disease with changing infectivity.The model is applicable to many diseases,particularly HIV/AIDS,where transmission probabilities vary as the viral load in an infected individual changes.The model equations are as follows(see Fig.2):_I 1¼X mÀ1k¼1b k SI k=NÀðm1þd1ÞI1;ð9aÞ_Ii¼m iÀ1I iÀ1Àðm iþd iÞI i;i¼2;...;mÀ1;ð9bÞ_Im¼m mÀ1I mÀ1Àd m I m;ð9cÞ_S¼bÀbSÀX mÀ1k¼1b k SI k=N:ð9dÞThe model assumes standard incidence,death rates d i>0in each infectious stage,and thefinal stage has a zero infectivity due to morbidity.Infected individuals spend,on average,1=m i time units in stage i.The unique DFE has I i¼0,i¼1;...;m and S¼1.For simplicity,define m m¼0. Then F¼½F ij and V¼½V ij ,whereF ij¼b j i¼1;j6mÀ1;0otherwise;&ð10ÞV ij¼m iþd i j¼i;Àm j i¼1þj;0otherwise:8<:ð11ÞLet a ij be the(i;j)entry of VÀ1.Thena ij¼0i<j;1=ðm iþd iÞi¼j;Q iÀ1k¼jm kQ ik¼jðm kþd kÞj<i:8>>><>>>:ð12ÞThus,R0¼b1m1þd1þb2m1ðm1þd1Þðm2þd2Þþb3m1m2ðm1þd1Þðm2þd2Þðm3þd3ÞþÁÁÁþb mÀ1m1...m mÀ2ðm1þd1Þ...ðm mÀ1þd mÀ1Þ:ð13ÞThe i th term in R0represents the number of new infections produced by a typical individual during the time it spends in the i th infectious stage.More specifically,m iÀ1=ðm iÀ1þd iÀ1Þis the fraction of individuals reaching stage iÀ1that progress to stage i,and1=ðm iþd iÞis the average time an individual entering stage i spends in stage i.Hence,the i th term in R0is the product of the infectivity of individuals in stage i,the fraction of initially infected individuals surviving at least to stage i,and the average infectious period of an individual in stage i.4.4.Multistrain modelThe recent emergence of resistant viral and bacterial strains,and the effect of treatment on their proliferation is becoming increasingly important[12,13].One framework for studying such sys-tems is the multistrain model shown in Fig.3,which is a caricature of the more detailed treatment model of Castillo-Chavez and Feng[12,Section2]for tuberculosis and the coupled two-strain vector–host model of Feng and Velasco-Hern a ndez[17]for Dengue fever.The model has only a single susceptible compartment,but has two infectious compartments corresponding to the two infectious agents.Each strain is modelled as a simple SIS system.However,strain one may ‘super-infect’an individual infected with strain two,giving rise to a new infection incompartment。

数值分析中常用数学词汇英中文对照翻译.

数值分析中常用数学词汇英中文对照翻译.

数值分析中常用数学词汇英中文对照abbreviation 简写符号;简写absolute error 绝对误差absolute value 绝对值accelerate 加速accumulation 累积accuracy 准确度act on 施于action 作用; 作用力add 加addition 加法addition formula 加法公式addition law 加法定律additive property 可加性adjoint matrix 伴随矩阵algebra 代数algebraic 代数的algebraic equation 代数方程algebraic expression 代数式algebraic fraction 代数分式;代数分数式algebraic inequality 代数不等式algebraic number 代数数algebraic operation 代数运算algorithm 算法系统; 规则系统alternating series 交错级数alternative hypothesis 择一假设; 备择假设; 另一假设analysis 分析;解析angle 角anti-clockwise direction 逆时针方向;返时针方向anti-derivative 反导数; 反微商anti-logarithm 逆对数;反对数anti-symmetric 反对称approach 接近;趋近approximate value 近似值approximation 近似;略计;逼近Arabic system 阿刺伯数字系统arbitrary 任意arbitrary constant 任意常数arc 弧arc-cosine function 反余弦函数arc-sin function 反正弦函数arc-tangent function 反正切函数area 面积argument (1论证; (2辐角argument of a function 函数的自变量arithmetic 算术array 数组; 数组ascending order 递升序ascending powers of X X 的升幂assumption 假定;假设asymmetrical 非对称asymptote 渐近augmented matrix 增广矩阵average 平均;平均数;平均值axiom 公理back substitution 回代base (1底;(2基;基数basis 基belong to 属于bias 偏差;偏倚billion 十亿binary number 二进数binary operation 二元运算binary system 二进制binomial 二项式bisection method 分半法;分半方法boundary condition 边界条件boundary line 界(线;边界bounded 有界的bounded above 有上界的;上有界的bounded below 有下界的;下有界的bounded function 有界函数bounded sequence 有界序列brace 大括号bracket 括号breadth 阔度calculation 计算calculator 计算器;计算器calculus (1 微积分学; (2 演算cancel 消法;相消Cartesian coordinates 笛卡儿坐标category 类型;范畴centre 中心;心chain rule 链式法则chance 机会change of base 基的变换change of variable 换元;变量的换characteristic equation 特征(征方程characteristic function 特征(征函数characteristic root 特征(征根chart 图;图表check digit 检验数位checking 验算circle 圆classification 分类clockwise direction 顺时针方向clockwise moment 顺时针力矩closed convex region 闭凸区域closed interval 闭区间coefficient 系数cofactor 余因子; 余因式coincide 迭合;重合collection of terms 并项collinear 共线collinear planes 共线面column (1列;纵行;(2 柱column matrix 列矩阵column vector 列向量combination 组合common denominator 同分母;公分母common difference 公差common divisor 公约数;公约common factor 公因子;公因子common multiple 公位数;公倍comparable 可比较的complement 余;补余completing the square 配方complex number 复数complex number plane 复数平面complex root 复数根component 分量composite function 复合函数; 合成函数computation 计算computer 计算机;电子计算器concept 概念conclusion 结论condition 条件conditional 条件句;条件式conjugate 共轭constant 常数constant of integration 积分常数constraint 约束;约束条件continuity 连续性continuous function 连续函数contradiction 矛盾converge 收敛convergence 收敛性convergent 收敛的convergent iteration 收敛的迭代convergent sequence 收敛序列convergent series 收敛级数convex 凸convexity 凸性coordinate 坐标corollary 系定理; 系; 推论correspondence 对应counter clockwise direction 逆时针方向;返时针方向counter example 反例counting 数数;计数criterion 准则critical point 临界点critical region 临界域cirtical value 临界值cube 正方体;立方;立方体cubic 三次方;立方;三次(的 cubic equation 三次方程cubic roots of unity 单位的立方根cumulative 累积的curve 曲线decimal 小数decimal place 小数位decimal point 小数点decimal system 十进制definite integral 定积分definition 定义degree (1 度; (2 次degree of a polynomial 多项式的次数degree of accuracy 准确度degree of ODE 常微分方程次数delete 删除; 删去denary number 十进数denominator 分母dependence (1相关; (2应变derivable 可导derivative 导数determinant 行列式diagonal 对角线diagonal matrix 对角矩阵difference 差difference equation 差分方程differentiable 可微differential 微分differential coefficient 微商; 微分系数differential equation 微分方程differential mean value theorem 微分中值定理differentiate 求...的导数differentiation 微分法digit 数字dimension 量; 量网; 维(数direction 方向; 方位discontinuity 不连续性discontinuous 间断(的;连续(的; 不连续(的discontinuous point 不连续点discrete 分立; 离散distance 距离diverge 发散divergence 发散(性divergent 发散的divergent iteration 发散性迭代divergent sequence 发散序列divide 除dividend (1被除数;divisible 可整除division 除法division algorithm 除法算式divisor 除数;除式;因子dot 点dot product 点积echelon form 梯阵式echelon matrix 梯矩阵eigenvalue 本征值eigenvector 本征向量element 元素elementary row operation 基本行运算elimination 消法elimination method 消去法;消元法empty set 空集equivalent 等价(的error 误差error estimate 误差估计error term 误差项estimate 估计;估计量evaluate 计值exact 真确exact solution 准确解;精确解;真确解exact value 法确解;精确解;真确解example 例expand 展开experiment 实验;试验experimental 试验的exponent 指数exponential function 指数函数express…in terms of… 以………表达extreme point 极值点extreme value 极值extremum 极值factor 因子;因式;商factor method 因式分解法factorial 阶乘factorization 因子分解;因式分解fallacy 谬误FALSE 假(的falsehood 假值finite 有限finite sequence 有限序列first derivative 一阶导数first order differential equation 一阶微分方程fixed point 不动点fixed point iteration method 不动点迭代法for all X 对所有X for each /every X 对每一Xform 形式;型format 格式;规格formula(formulae 公式fraction 分数;分式function 函数fundamental theorem of calculus 微积分基本定理Gaussian elimination 高斯消去法general form 一般式;通式general solution 通解;一般解general term 通项given 给定;已知global 全局; 整体global maximum 全局极大值; 整体极大值global minimum 全局极小值; 整体极小值gradient (1斜率;倾斜率;(2梯度graph 图像;图形;图表graphical method 图解法graphical representation 图示;以图样表达graphical solution 图解growth 增长higher order derivative 高阶导数horizontal 水平的;水平hypothesis 假设identity 等(式identity matrix 恒等矩阵if and only if/iff 当且仅当;若且仅若if…, then 若….则;如果…..则illustration 例证;说明image 像点;像imaginary number 虚数implicit function 隐函数imply 蕴涵;蕴含improper integral 广义积分; 非正常积分increase 递增;增加indefinite integral 不定积分independence 独立;自变inequality 不等式;不等inequality sign 不等号infinite 无限;无穷infinite sequence 无限序列;无穷序列infinite series 无限级数;无穷级数infinitesimal 无限小;无穷小infinity 无限(大;无穷(大initial approximation 初始近似值initial condition 原始条件;初值条件initial value 初值;始值initial-value problem 初值问题inner product 内积input 输入integer 整数integral 积分integrate 积;积分;......的积分integration 积分法integration by parts 分部积分法integration by substitution 代换积分法;换元积分法interchange 互换intermediate value theorem 介值定理interpolating polynomial 插值多项式interpolation 插值interval 区间intuition 直观invalid 失效;无效invariance 不变性invariant (1不变的;(2不变量;不变式inverse 反的;逆的inverse function 反函数;逆函数inverse matrix 逆矩阵inverse problem 逆算问题invertible 可逆的invertible matrix 可逆矩阵iterate (1迭代值; (2迭代iteration 迭代iterative method 迭代法known 己知Lagrange interpolating polynomial 拉格朗日插值多项代leading coefficient 首项系数leading diagonal 主对角线lemma 引理limit 极限limit of sequence 序列的极限line of best-fit 最佳拟合line segment 线段linear 线性;一次linear convergence 线性收敛性linear differeantial equation 线性微分方程linear equation 线性方程;一次方程linear equation in two unknowns 二元一次方程;二元线性方程linearly dependent 线性相关的linearly independent 线性无关的local maximum 局部极大(值local minimum 局部极小(值logic 逻辑long division method 长除法loop 回路lower bound 下界lower triangular matrix 下三角形矩阵Maclaurin expansion 麦克劳林展开式magnitude 量;数量;长度;大小mantissa 尾数matrix 阵; 矩阵matrix addition 矩阵加法matrix equation 矩阵方程matrix multiplication 矩阵乘法matrix operation 矩阵运算maximize 极大maximum absolute error 最大绝对误差mean value theorem 中值定理method of completing square 配方法method of interpolation 插值法; 内插法method of least squares 最小二乘法; 最小平方法method of substitution 代换法;换元法method of successive substitution 逐次代换法; 逐次调替法minimize 极小minus 减modulus of a complex number 复数的模monomial 单项式multiple 倍数multiple root 多重根multiplication 乘法multiplicity 重数multiplier 乘数;乘式multiply 乘mutually independent 独立; 互相独立mutually perpendicular lines 互相垂直n factorial n阶乘n th derivative n阶导数n th root n次根;n次方根n the root of unity 单位的n次根natural logarithm 自然对数necessary and sufficient condition 充要条件necessary condition 必要条件negative 负neighborhood 邻域Newton-Cote's rule 牛顿- 高斯法则Newton-Raphson's method 牛顿- 纳逊方法Newton's formula 牛顿公式Newton's method 牛顿方法non-linear 非线性non-linear equation 非线性方程non-negative 非负的non-singular (1满秩的; (2非奇异的non-singular matrix 满秩矩阵non-trivial 非平凡的non-zero 非零norm 模方; 范数normal (1垂直的;正交的;法线的(2正态的(3正常的;正规的normalize 正规化normalized form 标准型notation 记法;记号null 零; 空null set 空集null vector 零向量number 数numerator 分子numerical method 计算方法;数值法objective function 目标函数octant 卦限odd function 奇函数one-to-one 一个对一个one-one correspondence 一一对应operation 运算order of a matrix 矩阵的阶ordinary differential equation 常微分方程origin 原点orthogonal 正交orthogonality 正交性 outcome 结果 output 输出 parameter 参数;参变量parametric equation 参数方程 partition 分割; 划分 periodic function 周期函数permutation 排列 perpendicular 垂线;垂直(于 phase 相; 位相 pivot 支点 plot 绘图plus 加 point 点 polynomial 多项式 polynomial equation 多项式方程 positive 正 post-multiply 后乘; 自右乘 premultiply 前乘; 自左乘 prime 素 product 乘积;积 proper integral 正常积分 property 性质 quadratic convergence 二阶收敛性 quadratic formula 二次公式 quadratic function 二次函数 quadratic inequality 二次不等式 quadrature 求积法 quadrilateral 四边形 quotient 商;商式 quotient rule 商法则 R.H.S 右 rank 秩 rate of convergence 收敛率 ratio 比 ; 比率 rational function 有理函数 real number 实数 real part 实部 real root 实根 reciprocal 倒数 rectangle 长方形;矩形 recurrence formula 递推公式 recurrent 循环的 recurring decimal 循环小数 reduce 简化 region 区域 region of convergency 收敛区域 regular 正;规则 relative error 相对误差 remainder term 余项root 根 rotation 旋转 rounded number 舍数 rounding(off 舍入;四舍五入 row 行;棋行 row vector 行向量; 行矢量 rule 规则;法(则 satisfy 满足;适合 scalar 纯量; 无向量, 标量 scalar matrix 纯量矩阵 scale 比例尺;标度;图尺 scientific notation 科学记数法 secant (1正割; (2割线 secant method 正割法 second derivative 二阶导数 second order ordinary differential equation 二阶常微分方程 sentence 句;语句 sequence 序列series 级数 set 集 shaded portion 有阴影部分 shape 形状 shear 位移 side 边;侧 sign 符号;记号 signed number 有符号数 significant figure 有效数字 signum 正负号函数similar 相似 simplify 简化 Simpson's integral 森逊积分 Simpson's rule 森逊法则singular 奇的 singular matrix 奇异矩阵; 不可逆矩阵 span 生成 square (1平方;(2正方形 square bracket 方括号square matrix 方(矩阵 stability 稳度 stationary 平稳 stationary point 平稳点; 逗留点; 驻点 straight line 直线 subset 子集 substitute 代入 substitution 代入; 代入法subtract 减 subtraction 减法 successive approximation 逐次逼近法 successive derivative 逐次导数 successive differentiation 逐次微分法 sufficiency 充份性 sufficient and necessary condition 充要条件 sufficient condition 充份条件 sufficiently close 充份接近suffix 下标 sum 和 summation 求和法; 总和 symbol 符号; 记号 symmetry 对称; 对称性Taylor’s expansion 泰勒展开式 term 项 transpose 移项;转置 transpose of matrix 倒置矩阵;转置矩阵 trapezium 梯形 trapezoidal integral 梯形积分 trapezoidal rule 梯形法则 trial 试;试验 triangle 三角形 triangular matrix 三角矩阵 trigonometric equation 三角方程 trigonometric function 三角函数 triple 三倍 trivial solution 平凡解truncation error 截断误差 undefined 未下定义(的 undetermined coefficient 待定系数unequal 不等 unique solution 唯一解 uniqueness 唯一性 unit 单位 unit area 单位面积unit circle 单位圆 unknown 未知数;未知量 upper bound 上界 upper limit 上限 upper triangular matrix 上三角形矩阵 validity 真确性; 有效性 variable 变项;变量;元;变元;变数 vector 向量; 矢量 vector function 向量函数; 矢量函数 vector product 矢量积; 矢量积 vector space 向量空间 verify 证明;验证 weight (1重量;(2权 weighted average, weighted mean 加权平均数 without loss of generality 不失一般性 x-axis x 轴x-coordinate x 坐标 x-intercept x 轴截距 y-axis y 轴 y-coordinate y 坐标 y-intercept y轴截距 zero 零 zero factor 零因子 zero matrix 零矩阵 zero vector 零向量 zeros of a function 函数零值。

计量经济学中英文词汇对照

计量经济学中英文词汇对照

Controlled experiments Conventional depth Convolution Corrected factor Corrected mean Correction coefficient Correctness Correlation coefficient Correlation index Correspondence Counting Counts Covaห้องสมุดไป่ตู้iance Covariant Cox Regression Criteria for fitting Criteria of least squares Critical ratio Critical region Critical value
Asymmetric distribution Asymptotic bias Asymptotic efficiency Asymptotic variance Attributable risk Attribute data Attribution Autocorrelation Autocorrelation of residuals Average Average confidence interval length Average growth rate BBB Bar chart Bar graph Base period Bayes' theorem Bell-shaped curve Bernoulli distribution Best-trim estimator Bias Binary logistic regression Binomial distribution Bisquare Bivariate Correlate Bivariate normal distribution Bivariate normal population Biweight interval Biweight M-estimator Block BMDP(Biomedical computer programs) Boxplots Breakdown bound CCC Canonical correlation Caption Case-control study Categorical variable Catenary Cauchy distribution Cause-and-effect relationship Cell Censoring

A bound for the game chromatic number of graphs

A bound for the game chromatic number of graphs

The game chromatic number of graphsXuding ZhuDepartment of Applied MathematicsNational Sun Yat-sen University,Taiwanzhu@.twAbstractSuppose G=(V,E)is a graph.The game chromatic number of G is defined through a two-person game:the colouring game.Given a graph G and a set C of colours,Alice and Bob,with Alice playingfirst,take turns in playing the game.Each play by either player consists of colouring an uncoloured vertex of G with a colour from C.Both players need to respect the rule that no adjacent vertices should receive the same colour.The game ends if no more moves are possible,that is,either all vertices are coloured,or there are still uncoloured vertices but none of the uncoloured vertices can be coloured by a legal colour. If all the vertices are coloured,then Alice wins the game.Otherwise Bob is the winner.So Alice’s goal is to produce a proper colouring of G,and Bob’s goal is to prevent this from happening.If both player use their optimal strategy,then the winner of the game is determined by the graph G and the number of colours in C.The game chromatic numberχg(G)of G is the least number of colours needed so that Alice has a winning strategy for the colouring game on G.The restriction of this colouring game for planar graphs was invented about 25years ago by Steven J.Brams,and was published by Martin Gardner in his column“Mathematical Games”in Scientific American in1981.It remained unnoticed by the graph-theoretic community until ten years later,when it was reinvented by Hans L.Bodlaender in a wider context of general graphs.Since then the problem has attracted attention of some graph theoretic community and has been analyzed in combinatorial journals.There are many results and also many open problems.It is known that forests have game chromatic number at most4,outerplanar graphs have game chromatic number at most7,partial k-trees have game chromatic number at most3k+2,planar graphs have game chromatic number at most17.In this talk,I explain one strategy used by Alice for playing the colouring game.All the above mentioned upper bound are proved by this strategy or refinement of this strategy.References[1]H.L.Bodlaender,On the complexity of some colouring games,International Jour-nal of Foundations of Computer Science2(1991),133-148.[2]L.Cai,K.Lih and W.Wang,Game colouring number of planar graphs without4-cycles,preprint,2001.[3]L.Cai and X.Zhu,Game chromatic index of k-degenerate graphs,J.Graph Theory36(2001),no.3,144–155.[4]T.Dinski and X.Zhu,A bound for the game chromatic number of graphs,DiscreteMathematics196(1999),109-115.[5]C.L.Dunn,Extensions of a simple competitive graph colouring algorithm,Ph.D.dissertation,Arizona State University,2002.[6]C.L.Dunn and H.A.Kierstead,A simple competitive graph colouring algorithmII,manuscript,2001.[7]C.L.Dunn and H.A.Kierstead,A simple competitive graph colouring algorithmIII,manuscript,2001.[8]U.Faigle,U.Kern,H.A.Kierstead and W.T.Trotter,On the game chromaticnumber of some classes of graphs,Ars Combin.35(1993),143–150.[9]D.Guan and X.Zhu,The game chromatic number of outerplanar graphs,J.GraphTheory30(1999),67-70.[10]W.He,X.Hou,K.Lih,J.Shao,W.Wang and X.Zhu,Edge-partitions of planargraphs and their game colouring numbers,Journal of Graph Theory,41(2002), 307-317.[11]H.A.Kierstead,A simple competitive graph colouring algorithm,binatorialTheory(B)78(2000),57-68.[12]H.A.Kierstead and W.T.Trotter,Planar graph colouring with an uncooperativepartner,J.Graph Theory18(1994),no.6,569–584.[13]H.A.Kierstead and W.T.Trotter,Competitive colourings of oriented graphs,Electronic J.of Combinatorics,8(2001),Research Paper12,15pp.[14]H.A.Kierstead and Zs.Tuza,Marking games and the oriented game chromaticnumber of partial k-trees,Graphs and Combinatorics,to appear.[15]H.A.Kierstead and D.Yang,Very asymmetric marking games,manuscript,2002.[16]H.A.Kierstead and D.Yang,Orderings on graphs and game colouring number,manuscript,2002.[17]J.Neˇs etˇr il and E.Sopena,On the oriented game chromatic number,Electronic J.of Combinatorics,8(2001),Research Paper14,153pp.[18]J.Wu and X.Zhu,Lower bounds for the game colouring number of planar graphsand partial k-trees,preprint,2003.[19]X.Zhu,The game colouring number of planar graphs,binatorial Theory(B)75(1999),245-258.[20]X.Zhu,Game colouring number of pseudo partial k-trees,Discrete Mathematics215(2000),245-262.[21]X.Zhu,Refined activation strategy for the colouring game,preprint,2003.。

科技词汇 光学专业英语

科技词汇 光学专业英语

retina视网膜Color Blind色盲weak color色弱Myopia-near-sighted近视Sensitivity to Light感光灵敏度boost推进lag behind落后于Hyperopic-far-sighted远视Dynamic Range动态范围critical fusion frequency临界融合频率CFF临界闪变频率visual sensation视觉hromaticity Diagram色度图olor Temperature色温SV Model色彩模型hue色度aturation饱和度value纯度IE Model 相干红外能量模式omplementary Colors补色ar Pattern条状图形eat body 热稠化pproximate近似iolet紫罗兰ody Curve人体曲线olor Gamut色阶djacent邻近的ormal illumination法线照明rimary colors红黄蓝三原色olor saturation色饱和度olor Triangle颜色三角olor Notation颜色数标法Color Difference色差V Signal Processing电视信号处理amma Correction图像灰度校正onversion Tables换算表ut of balance失衡obble摇晃ack and forth前后lear(white)panel白光板ibrant震动uzzy失真uantum leap量子越迁VGA(800)600 derive from起源自ulprit犯人ender呈递nhibit抑制,约束tride大幅前进lemish污点bstruction障碍物cratch刮伤ubstance物质实质主旨esidue杂质riteria标准arameter参数djacent邻近的接近的synchrony异步luster串群utually互助得lgorithm运算法则hromatic Aberrations色差ovea小凹isual Acuity视觉灵敏度ontrast Sensitivity对比灵敏度emporal(time)Response反应时间endition表演,翻译nimation活泼又生气host重影arallax视差eficient缺乏的不足的isplay panel显示板G. Narrow Gauge)窄轨距ichroic mirror二色性的双色性的rewster Angle布鲁斯特角olarized Light极化光nternal reflection内反射irefringence 双折射xtinction Ratio 消光系数isalignment 未对准uarter Waveplates四分之一波片lemish污点瑕疵eometric几何学的ipple波纹apacitor电容器arallel平行的他antalum钽金属元素exsiccate使干燥xsiccate油管,软膏urnace炉子炉lectrolytic电解的,由电解产生的odule模数nalog类似物ut of the way不恰当incushion针垫拉ateral侧面得ectangle长方形ixture固定设备ontrol kit工具箱VI connector DVI数局线ertical垂直的horizontal 水平的nterlace隔行扫描ullion竖框直楞awtooth锯齿oggle套索钉eypad数字按键键盘angential切线iagnostic tool诊断工具agittal direction径向的ursor position光标位置rayaberration光线相差eighting factor权种因子ariables变量or now暂时,目前.眼下heck box复选框iry disk艾里斑xit pupil出[射光]瞳ptical path difference光称差ith respect to关于iffraction limited衍射极限avefront aberration波阵面相差pherical aberration球面象差araxial focus傍轴焦点hromatic aberration象差ocal coordinate system局部坐标系统oordinate system坐标系rthogonal直角得,正交的onic sections圆锥截面ccount for解决,得分arabolic reflector?物面反射镜adius of curvature曲率半径pherical mirror球面镜eometrical aberration几何相差ncident radiation入射辐射lobal coordinate总体坐标n terms of根据按照eflected beam反射束YI= or your information供参考onstructive interference相长干涉hase difference相差chromatic singlet消色差透镜nterferometer干涉仪oundary constraint边界约束,池壁效应adii半径oom lenses变焦透镜eam splitters分束器iscrete不连续的,分离的bjective/ye lens物镜/目镜ainframe主机udimentary根本的,未发展的hotographic照相得摄影得axing繁重的,费力得lgebra代数学rigonometry三角学eometry几何学alculus微积分学hilosophy哲学agrange invariant拉格朗日不变量pherical球的ield information场信息tandard Lens标准透镜efracting Surface折射面stigmatism散光DTV高清晰度电视LV( Digital Light Valve)数码光路真空管,简称数字光阀iffraction grating衍射光珊ield angle张角araxial ray trace equations近轴光线轨迹方称ack focal length后焦距rincipal plane主平面ertex顶点,最高点stigmatism散光,因偏差而造成的曲解或错判edial中间的,平均的ariance不一致onic圆锥的,二次曲线ield of view视野ollimator瞄准仪onvolution回旋.盘旋,卷积uzzy失真,模糊berrated异常的symmetry不对称得ndicative可表示得arabolic?物线得uffice足够,使满足pecification规格,说明书traightforward易懂的,直接了当的,olidify凝固,巩固.Constraints 约束,限制etrology度量衡ield coverage视场,视野ictate口述, 口授, 使听写,指令, 指示, 命令, 规定rradiance发光, 光辉,辐照度erial空气得,空中得alide卤化物的onochromatic单色的,单频的olychromatic多色的spherical非球面的pherical球面的lignment列队,结盟ower(透镜放大率quiconvergence 同等收敛FL(effective focal length)有效焦距orkhorse广为应用的设备iconvex两面凸的lobal optimization整体最优化oncave凹得,凹面得ylindrical圆柱得olid model实体模型odulation TransferFunction调制传递函数n the heat of在最激烈的时候rotocol协议,规定riplet三重态anity心智健全inc锌,涂锌的elenide 硒化物,硒醚iscellaneous各色各样混在一起, 混杂的, 多才多艺的ersus与...相对olynomial多项式的oefficient系数xplicit function显函数distinct清楚的,截然不同的manate散发, 发出, 发源udimentary根本的,未发展的ntersection角差点RTE= araxial ray trace equation旁轴光线轨迹方程achromats 消色差透镜ardinal points基本方位eparations分色片ashed虚线low up放大verlay覆盖,覆盖图multiplayer 多层的umidity 湿度loat glass浮法玻璃quare one 出发点,端点quare up to 准备开打,坚决地面对eflecting telescope 反射式望远镜diagnostic tools诊断工具ayout plots规划图odulation transfer function 调制转换功能FT快速傅里叶变换oint spread function点传播功能avelength波长ngle角度bsorption吸收ystem aperture系统孔径ens units透镜单位avelength range波长范围inglet lens单业透镜pectrum光谱iffraction grating衍射光栅sphere半球的DE= ens data editor Surface radius of curvature 表面曲率半径urface thickness表面厚度aterial type材料种类emi-diameter半径ocal length焦距perture type孔径类型perture value孔径值ield of view视场icrons微米, d, and C=blue hydrogen,yellow helium,red hydrogen lines,primary wavelength主波长equential mode连续模式bject surface物表面he front surface of the lens透镜的前表面top光阑he back surface of the lens透镜的后表面he image surface像表面ymmetric相对称的iconvex两面凸的he curvature is positive ifthe center of curvature ofthe surface is to the rightof the vertex.It is negative if the centerof curvature is to the left ofthe vertex.如果曲率中心在最高点的右边,曲率值为正,如果曲率中心在最高点的左边,则曲率为负mage plane像平面ay Aberration光线相差angential direction切线方向agittal direction径向araxial focus旁轴的arginal边缘的pherical aberration球面像差ptimization Setup最优化调整ariable变量athematical sense数学角度FE= Merit Function Editor,Adding constraints增加约束ocal length焦矩长度perand操作数he effective focal length有效焦矩rimary wavelength主波长nitiate开始pot diagram位图表iry disk艾里斑xial chromatic aberration轴向色差ith respect to关于至于xit pupil出射光瞳PD= ptical path difference光学路径差iffraction limited衍射极限hromatic aberration色差hromatic focal shift色焦距变换araxial focus傍轴焦点xial spherical aberration轴向球差longitudinal sphericalaberration 纵向球差:沿光轴方向度量的球差lateral spherical aberration垂轴球差在过近轴光线像点的垂轴平面内度量的球差coma、omatic aberration彗差eridional coma子午彗差agittal coma弧矢彗差stigmatism像散ocal coordinate system本地坐标系统eridional curvature of field子午场曲agittal curvature of field弧矢场曲ecentered lens偏轴透镜orthogonal直角的垂直的onic section圆锥截面ccount for说明,占有,得分tigmatic optical system无散光的光学系统ewtonian telescope牛顿望远镜arabolic reflector抛物面镜oci焦距hromatic aberration,色差uperpose重迭arabola抛物线pherical mirror球面镜MS=oot Mean Square均方根avefront波阵面pot size光点直径aussian quadrature高斯积分ectangular array矩阵列rid size磨粒度PSF= point Spread Function点扩散函数FT= fast Fourier Transform Algorithm快速傅里叶变换ross Section横截面bscurations昏暗ocal coordinates局部坐标系统ignette把…印为虚光照rrow key键盘上的箭头键efractive折射eflective反射n phase同相的协调的ray tracing光线追迹iffraction principles衍射原理rder effect式样提出的顺序效果nergy distribution能量分配onstructive interference相长干涉ispersive色散的inary optics二元光学hase advance相位提前chromatic single消色差单透镜iffractive parameter衍射参数oom lenses变焦透镜thermalized lenses绝热透镜nterferometers干涉计eam splitter分束器witchable componentsystems可开关组件系统ommon application通用ymmetry对称oundary constraint边界约束ulti-configuration(MC)MCEditor(MCE)perturbation动乱,动摇ndex accuracy折射率准确性ndex homogeneity折射率同种性ndex distribution折射率分配bbe number离差数esidual剩余的stablishing tolerances建立容差igure of merit质量因子olerance criteria公差标准odulation TransferFunction(MTF)调制传递函数oresight视轴,瞄准线Monte Carlo蒙特卡洛olerance operands误差操作数onic constant圆锥常数stigmatic aberration像散误差echanical tilt机械倾斜,机械倾角olerance Data Editor(TDE)公差资料编辑器ompensator补偿棱镜stimated systemperformance预估了的系统性能teratively反复的,重迭的tatistical dependence统计相关性equential ray trace model连续光线追迹模型mbed埋葬,埋入ultiple多样的,多重的,若干的on-Sequential Components不连续的组件orner cube角隅棱镜,三面直角透镜ensitivity Analysis灵敏度分析aceted reflector有小面的反射镜mit发射,发出est嵌套verlap交迭uter lens外透镜rute force强力eidel像差系数spect ratio长宽比RA边缘光线角RH边缘光线高度synchronous不同时的,异步Apodization factor变迹因子exapolar六角形ithered高频脉冲衍射调制传递函数(MTF),衍射实部传递函数(RTF),衍射虚部传递函数(ITF),衍射相位传递函数(PTF),方波传递函数(SWM)ogarithmic对数的arity奇偶longitudinal aberrations 纵向像差赛得系数:球差(PHA,I),彗差(OMA,2),像散(STI,3),场曲(CUR,4),畸变(IST,5),轴向色差(LA,L)和横向色差(TR,T).横向像差系数:横向球差(SPH),横向弧矢彗差(SCO),横向子午彗差(TCO),横向弧矢场曲(SFC),横向子午场曲(TFC),横向畸变(DIS)横向轴上色差(LAC)。

稀布线性阵列优化布阵研究

稀布线性阵列优化布阵研究

目录
3.4.2 奇数对称直线阵列的布阵 ................................................................. 26 3.4.3 奇数对称直线阵列的仿真结果 ......................................................... 27 3.5 偶数对称直线阵列综合 ............................................................................... 32 3.5.1 偶数对称直线阵列适应度函数 ......................................................... 32 3.5.2 偶数对称直线阵列的布阵 ................................................................. 33 3.5.3 偶数对称直线阵列的仿真结果 ......................................................... 34 3.6 总结 ............................................................................................................... 37 第四章 基于凸优化技术的稀布阵列合成 ............................................................... 38 4.1 引言 ............................................................................................................... 38 4.2 压缩感知基本原理 ....................................................................................... 38 4.3 基于凸优化技术的线阵综合 ....................................................................... 39 4.4 阵列天线性能分析 ....................................................................................... 41 4.5 总结 ............................................................................................................... 44 第五章 总结与展望 ................................................................................................... 45 5.1 论文总结 ....................................................................................................... 45 5.2 未来展望 ....................................................................................................... 45 参考文献 ..................................................................................................................... 47 攻读学位期间取得的研究成果 ................................................................................. 52 致谢 ............................................................................................................................. 53 个人简况及联系方式 ................................................................................................. 54 承诺书 ......................................................................................................................... 55 学位论文使用授权声明 ............................................................................................. 55

Molex MXS连接器商品说明书

Molex MXS连接器商品说明书

NOTES:1. MATERIALS: HOUSING: LIQUID CRYSTAL POLYMER (LCP) GLASS-FILLED, UL94V-0 TERMINALS: HIGH PERFORMANCE COPPER ALLOY2. FINISH: SELECTIVE GOLD IN SIGNAL AND U-SHIELD CONTACT AREA ONLY. SELECTIVE TIN ON PCB TAILS. NICKEL OVERALL.3. PARTS ARE MAKED WITH THE PART NUMBER, "MXS", AND A DATECODE.DATECODE FORMAT: 2 DIGIT YEAR, 3 DIGIT DAY (YYDDD), AND 2 DIGIT HOUR, MINUTE & SECONDS (HHMMSS).4. REFER TO MOLEX PRODUCT SPECIFICATION 1735109000-PS_PS FOR PERFORMANCE SPECIFICATIONS.5. PRODUCT WILL BE PACKAGED PER: 1736101000PDD_PK.6. MATES WITH IMPULSE DC RAF (RIGHT ANGLE FEMALE) UNGUIDED NUMBER: SEE TABLE.7. APPLICATION SPECIFICATION: 1735109997-AS_PS.8. REFER TO IMPULSE PCB ROUTING GUIDE 1735109999-AS_PS FOR ANTIPAD,ROUTING RECOMMENDATIONS, BACKDRILL, AND ADDITIONAL PCB INFORMATION.CA57.6REFERENCE19.10.62X8.5437.435.0MIN BOARD1.00TAIL LENGTH1.3012.07(CUTAWAY)2.37PIN T16PIN A116 COLUMN PART SHOWNPART NUMBER "MXS" DATECODE SEE NOTE 3MATERIAL NUMBER NUMBER OF COLUMNS NUMBER OF DIFFERENTIAL PAIRS DIMENSION "A"DIMENSION "B"DIMENSION "C"DIMENSION "D"ORTHOGONALORIENTATIONMATING DC RAF PART NUMBER PTH's173625-280586422.814.0024.015.4890°173540-70080.31MM 173625-2205129630.822.0032.023.4890°173631-10120.31MM 173625-24051411234.826.0036.027.4890°173620-10160.31MM 173625-26051612838.830.0040.031.4890°173505-10160.31MM 173625-280686422.814.0024.015.4890°173540-70480.26MM 173625-2206129630.822.0032.023.4890°173631-10520.26MM 173625-24061411234.826.0036.027.4890°173620-10560.26MM 173625-26061612838.830.0040.031.4890°173505-10560.26MM(SHIELD LENGTH)6.50+0.20-0.10REFERENCE25.52PITCH2.00PIN A1REFERENCE22.92 DIVISIONAL SYMBOLSFUNCTIONAL SYMBOLS =0=0=CURRENT REV DESC: ADD 0.26MM COMPLIANT PARTNUMBERSEC NO:675528DRWN:JMENDOZA012021/06/15CHK'D:JMENDOZA012021/09/01APPR:JMENDOZA012021/09/01THIS DRAWING CONTAINS INFORMATION THAT IS PROPRIETARY TO MOLEX ELECTRONIC TECHNOLOGIES, LLC AND SHOULD NOT BE USED WITHOUT WRITTEN PERMISSION DIMENSION UNITS SCALE mm 3:1GENERAL TOLERANCES (UNLESS SPECIFIED)ANGULAR TOL±0.5 °4 PLACES±3 PLACES ±2 PLACES±0.13IMPULSE 8 PAIRORTHO DIRECT RAM - 90° - 2MM UNGUIDEDPRODUCT CUSTOMER DRAWINGDOCUMENT NUMBERDOC TYPE DOC PART REVISIONMML LKKJJHHG GFFEEDDCC BBDETAIL A SCALE 7:1ADKEEP-OUT ZONE SEE NOTE 1TYPICAL2.003.20 3.201.615.471.995.5335.20MAXIMUM 2.702X2.60UNPLATED SCREW HOLE2X2.45±0.05⌀PTH (32 HOLES PER COLUMN)0.31±0.05⌀⌖⌀0.10⌖⌀0.10(FULLY MATED)26.00ORTHO DIRECT RAM HOLE PATTERN(CONNECTOR SIDE)DC RAFREAR (NON-CONNECTOR SIDE)32.132X 8.38EVEN COLUMN DIMENSIONSODD COLUMN DIMENSIONS 0.002.204.006.208.0010.2012.0014.2016.0018.2020.0022.2024.0026.2028.00 1.003.205.007.209.0011.2013.0015.2017.0019.2021.0023.2025.0027.2029.001.003.205.007.209.0011.2013.0015.2017.0019.2021.0023.2025.0027.2029.002.004.206.008.2010.0012.2014.0016.2018.0020.2022.0024.2026.0028.20GND H1G1GND GND D1C1GND GND K1J1GND GND P1N1GND GND F1E1GND GND M1L1GND GND B1A1GNDR1GND GND M2L2GND GND K2J2GND GND P2N2GND GND H2G2GND GND GND D2C2GND GND B2A2GNDGND F2E2GND DC RAF PIN A1PIN T1PIN A1SIGNAL VIA GROUND VIAPCB EDGEDC RAF FIRST GND PIN0.31 SIGNAL & GROUND PTH's16 COLUMN PART SHOWNNOTES1. THESE DIMENSIONS REPRESENT THE AREA NEEDED TOACCOMMODATE CONNECTOR INSERTION AND REPAIR ON THE PCB. THIS IS REFERRED TO AS THE "CONNECTOR KEEP OUT ZONE" AND DOES NOT REPRESENT THE ACTUAL PERIMETER OF THE DC RAF PIN A1DIVISIONAL SYMBOLSFUNCTIONAL SYMBOLS =0=0=CURRENT REV DESC: ADD 0.26MM COMPLIANT PARTNUMBERSEC NO:675528DRWN:JMENDOZA012021/06/15CHK'D:JMENDOZA012021/09/01APPR:JMENDOZA012021/09/01THIS DRAWING CONTAINS INFORMATION THAT IS PROPRIETARY TO MOLEX ELECTRONIC TECHNOLOGIES, LLC AND SHOULD NOT BE USED WITHOUT WRITTEN PERMISSION DIMENSION UNITS SCALE mm 3:1GENERAL TOLERANCES (UNLESS SPECIFIED)ANGULAR TOL±0.5 °4 PLACES±3 PLACES ±2 PLACES±0.13IMPULSE 8 PAIRORTHO DIRECT RAM - 90° - 2MM UNGUIDEDPRODUCT CUSTOMER DRAWINGDOCUMENT NUMBERDOC TYPE DOC PART REVISIONLLKKJJHHGGFFEEDDCC BBDETAIL C SCALE 7:1ADKEEP-OUT ZONE SEE NOTE 1TYPICAL2.003.20 3.201.615.471.995.5335.20MAXIMUM 2.702X2.60⌖⌀0.10UNPLATED SCREW HOLE2X2.45±0.05⌀⌖⌀0.10GROUND PTH (16 HOLES PER COLUMN)0.31±0.05⌀(FULLY MATED)26.00ORTHO DIRECT RAM HOLE PATTERN(CONNECTOR SIDE)DC RAFREAR (NON-CONNECTOR SIDE)32.132X 8.38EVEN COLUMN DIMENSIONSODD COLUMN DIMENSIONS 0.002.204.006.208.0010.2012.0014.2016.0018.2020.0022.2024.0026.2028.00 1.003.205.007.209.0011.2013.0015.2017.0019.2021.0023.2025.0027.2029.001.003.205.007.209.0011.2013.0015.2017.0019.2021.0023.2025.0027.2029.002.004.206.008.2010.0012.2014.0016.2018.0020.2022.0024.2026.0028.20GND H1G1GND GND D1C1GND GND K1J1GND GND P1N1GND GND F1E1GND GND M1L1GND GND B1A1GNDR1GND GND M2L2GND GND K2J2GND GND P2N2GND GND H2G2GND GND GND D2C2GND GND B2A2GNDGND F2E2GND DC RAF PIN A1PIN T1PIN A1SIGNAL VIA GROUND VIAPCB EDGEDC RAF FIRST GND PIN0.26 SIGNAL PTH's & 0.31 GROUND PTH's16 COLUMN PART SHOWNNOTES1. THESE DIMENSIONS REPRESENT THE AREA NEEDED TOACCOMMODATE CONNECTOR INSERTION AND REPAIR ON THE PCB. THIS IS REFERRED TO AS THE "CONNECTOR KEEP OUT ZONE" AND DOES NOT REPRESENT THE ACTUAL PERIMETER OF THE DC RAF PIN A1⌖⌀0.10SIGNAL PTH (16 HOLES PER COLUMN)0.26±0.05⌀DIVISIONAL SYMBOLSFUNCTIONAL SYMBOLS =0=0=CURRENT REV DESC: ADD 0.26MM COMPLIANT PARTNUMBERSEC NO:675528DRWN:JMENDOZA012021/06/15CHK'D:JMENDOZA012021/09/01APPR:JMENDOZA012021/09/01THIS DRAWING CONTAINS INFORMATION THAT IS PROPRIETARY TO MOLEX ELECTRONIC TECHNOLOGIES, LLC AND SHOULD NOT BE USED WITHOUT WRITTEN PERMISSION DIMENSION UNITS SCALE mm 3:1GENERAL TOLERANCES (UNLESS SPECIFIED)ANGULAR TOL±0.5 °4 PLACES±3 PLACES ±2 PLACES±0.13IMPULSE 8 PAIRORTHO DIRECT RAM - 90° - 2MM UNGUIDEDPRODUCT CUSTOMER DRAWINGDOCUMENT NUMBERDOC TYPE DOC PART REVISIONLLKKJJHHGGFFEEDDCC BBMATED DIMENSIONSREFERENCE3.0REFERENCE35.9REFERENCE95.48 PAIR X 16 COLUMN ORTHO DIRECT RAM8 PAIR X 16 COLUMNDC RAFORTHO PIN MAPPING(DC RAF - ORTHO DIRECT RAM)T1-T2T2-R1T3-P2T4-N1T5-M2T6-L1T7-K2T8-J1T9-H2T10-G1T11-F2T12-E1T13-D2T14-C1T15-B2T16-A1R1-R2R2-T1R3-N2R4-P1R5-L2R6-M1R7-J2R8-K1R9-G2R10-H1R11-E2R12-F1R13-C2R14-D1R15-A2R16-B1P1-T4P2-R3P3-P4P4-N3P5-M4P6-L3P7-K4P8-J3P9-H4P10-G3P11-F4P12-E3P13-D4P14-C3P15-B4P16-A3N1-R4N2-T3N3-N4N4-P3N5-L4N6-M3N7-J4N8-K3N9-G4N10-H3N11-E4N12-F3N13-C4N14-D3N15-A4N16-B3M1-T6M2-R5M3-P6M4-N5M5-M6M6-L5M7-K6M8-J5M9-H6M10-G5M11-F6M12-E5M13-D6M14-C5M15-B6M16-A5L1-R6L2-T5L3-N6L4-P5L5-L6L6-M5L7-J6L8-K5L9-G6L10-H5L11-E6L12-F5L13-C6L14-D5L15-A6L16-B5K1-T8K2-R7K3-P8K4-N7K5-M8K6-L7K7-K8K8-J7K9-H8K10-G7K11-F8K12-E7K13-D8K14-C7K15-B8K16-A7J1-R8J2-T7J3-N8J4-P7J5-L8J6-M7J7-J8J8-K7J9-G8J10-H7J11-E8J12-F7J13-C8J14-D7J15-A8J16-B7H1-T10H2-R9H3-P10H4-N9H5-M10H6-L9H7-K10H8-J9H9-H10H10-G9H11-F10H12-E9H13-D10H14-C9H15-B10H16-A9G1-R10G2-T9G3-N10G4-P9G5-L10G6-M9G7-J10G8-K9G9-G10G10-H9G11-E10G12-F9G13-C10G14-D9G15-A10G16-B9F1-T12F2-R11F3-P12F4-N11F5-M12F6-L11F7-K12F8-J11F9-H12F10-G11F11-F12F12-E11F13-D12F14-C11F15-B12F16-A11E1-R12E2-T11E3-N12E4-P11E5-L12E6-M11E7-J12E8-K11E9-G12E10-H11E11-E12E12-F11E13-C12E14-D11E15-A12E16-B11D1-T14D2-R13D3-P14D4-N13D5-M14D6-L13D7-K14D8-J13D9-H14D10-G13D11-F14D12-E13D13-D14D14-C13D15-B14D16-A13C1-R14C2-T13C3-N14C4-P13C5-L14C6-M13C7-J14C8-K13C9-G14C10-H13C11-E14C12-F13C13-C14C14-D13C15-A14C16-B13B1-T16B2-R15B3-P16B4-N15B5-M16B6-L15B7-K16B8-J15B9-H16B10-G15B11-F16B12-E15B13-D16B14-C15B15-B16B16-A15A1-R16A2-T15A3-N16A4-P15A5-L16A6-M15A7-J16A8-K15A9-G16A10-H15A11-E16A12-F15A13-C16A14-D15A15-A16A16-B15PIN MAPA1R16THIS SHEET IS FOR128 DIFFERENTIAL PAIRS ONLYDIVISIONAL SYMBOLSFUNCTIONAL SYMBOLS =0=0=CURRENT REV DESC: ADD 0.26MM COMPLIANT PARTNUMBERSEC NO:675528DRWN:JMENDOZA012021/06/15CHK'D:JMENDOZA012021/09/01APPR:JMENDOZA012021/09/01THIS DRAWING CONTAINS INFORMATION THAT IS PROPRIETARY TO MOLEX ELECTRONIC TECHNOLOGIES, LLC AND SHOULD NOT BE USED WITHOUT WRITTEN PERMISSION DIMENSION UNITS SCALE mm 2:1GENERAL TOLERANCES (UNLESS SPECIFIED)ANGULAR TOL±0.5 °4 PLACES±3 PLACES ±2 PLACES±0.13IMPULSE 8 PAIRORTHO DIRECT RAM - 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90° - 2MM UNGUIDEDPRODUCT CUSTOMER DRAWINGDOCUMENT NUMBERDOC TYPE DOC PART REVISIONLLKKJJHHGGFFEED DCC BBORTHO PIN MAPPING(DC RAF - ORTHO DIRECT RAM)H1-T2H2-R1H3-P2H4-N1H5-M2H6-L1H7-K2H8-J1H9-H2H10-G1H11-F2H12-E1H13-D2H14-C1H15-B2H16-A1G1-R2G2-T1G3-N2G4-P1G5-L2G6-M1G7-J2G8-K1G9-G2G10-H1G11-E2G12-F1G13-C2G14-D1G15-A2G16-B1F1-T4F2-R3F3-P4F4-N3F5-M4F6-L3F7-K4F8-J3F9-H4F10-G3F11-F4F12-E3F13-D4F14-C3F15-B4F16-A3E1-R4E2-T3E3-N4E4-P3E5-L4E6-M3E7-J4E8-K3E9-G4E10-H3E11-E4E12-F3E13-C4E14-D3E15-A4E16-B3D1-T6D2-R5D3-P6D4-N5D5-M6D6-L5D7-K6D8-J5D9-H6D10-G5D11-F6D12-E5D13-D6D14-C5D15-B6D16-A5C1-R6C2-T5C3-N6C4-P5C5-L6C6-M5C7-J6C8-K5C9-G6C10-H5C11-E6C12-F5C13-C6C14-D5C15-A6C16-B5B1-T8B2-R7B3-P8B4-N7B5-M8B6-L7B7-K8B8-J7B9-H8B10-G7B11-F8B12-E7B13-D8B14-C7B15-B8B16-A7A1-R8A2-T7A3-N8A4-P7A5-L8A6-M7A7-J8A8-K7A9-G8A10-H7A11-E8A12-F7A13-C8A14-D7A15-A8A16-B7THIS SHEET IS FOR64 DIFFERENTIAL PAIRS ONLYMATED DIMENSIONSREFERENCE3.0REFERENCE19.9REFERENCE79.48 PAIR X 8 COLUMN ORTHO DIRECT RAMPIN MAPR8A14 PAIR X 16 COLUMNDC RAFDIVISIONAL SYMBOLSFUNCTIONAL SYMBOLS =0=0=CURRENT REV DESC: ADD 0.26MM COMPLIANT PARTNUMBERSEC NO:675528DRWN:JMENDOZA012021/06/15CHK'D:JMENDOZA012021/09/01APPR:JMENDOZA012021/09/01THIS DRAWING CONTAINS INFORMATION THAT IS PROPRIETARY TO MOLEX ELECTRONIC TECHNOLOGIES, LLC AND SHOULD NOT BE USED WITHOUT WRITTEN PERMISSION DIMENSION UNITS SCALE mm 2:1GENERAL TOLERANCES (UNLESS SPECIFIED)ANGULAR TOL±0.5 °4 PLACES±3 PLACES ±2 PLACES±0.13IMPULSE 8 PAIRORTHO DIRECT RAM - 90° - 2MM UNGUIDEDPRODUCT CUSTOMER DRAWINGDOCUMENT NUMBERDOC TYPE DOC PART REVISIONLLKKJ JHHGGFFEED DCC BB。

Length estimation in 3-D using cube quantization

Length estimation in 3-D using cube quantization
y
Amnon Jonas and Nahum Kiryatiy
Currently with RDC Communications Ltd., P.O.Box 34233, Jerusalem 91341, Israel To whom correspondence should be addressed
Length Estimation in 3-D Using Cube Quantization
Department of Electrical Engineering Technion - Israel Institute of Technology Haifa 32000, Israel
ct
1
1 Introduction
Suppose that a continuous curve in three dimensional space has been quantized and is given in digital form, e.g. as a 3-D chain code. Can the length of the original continuous curve be recovered? Since information is lost in the digitization process, the answer is no. Each digital curve could have been obtained from an in nite number of continuous curves. Unique reconstruction, and length recovery, are thus impossible. Had the set of continuous curves that have the same digital representation been roughly similar in shape and length, the original length could have been estimated to be some average of the lengths of continuous curves in that set. However, in such a set there are continuous curves that exhibit sub-voxel fractal behavior that is not captured by the digitization process. The existence of such curves, including curves of in nite length, precludes meaningful length estimation by set averaging. In any practical image analysis system quantization must be su ciently ne to capture the essential shapes of objects to be analyzed (at the relevant scale). Then, for practical purposes, curves can be considered smooth except at a small number of corners. If the curves can be assumed to be nearly straight in small neighborhoods around most of the digital curve points, meaningful length estimation becomes possible. The 2-D length estimation problem has received considerable attention. Relatively recent references are 4, 14]. The standard approach to length estimation is to classify the chain code elements according to certain criteria, and estimate the length as a weighted sum of the number of chain elements in each class. Once the classi cation criteria are selected, the corresponding weights are designed to yield unbiased and in some sense optimal estimates of the length of straight lines. Unbiasedness for straight lines implies that when applied to general curves with varying tangent orientations, local length estimation errors are likely to cancel out, and excellent total length estimation can be expected. The increasing importance of three dimensional shape analysis in medical imaging, range image processing, navigation and other domains has recently led to interest in the development of length estimators for digitized 3-D curves. The few estimators that have been suggested are based on 26-directional chain code representation of the digital curve. That representation provides natural classi cation of the chain code links to three classes, which is very convenient for length estimation. Certain methods 1, 3] rely on global properties of digital straight lines and are thus applicable only to straight lines and cannot be extended to estimating the length of general curves. The work of Verwer 18] deals with the design of local weights for distance transformations. Kiryati and Szekely 15] have however observed that in 3-D, the shortest digital path between two voxels obtained by a search algorithm in a chamfer distance transformation is not necessarily a digital straight line (i.e., the digitization of a continuous straight line) that passes through two voxels. This leads to a fundamental di erence between the design of length estimators and of local weights for Euclidean distance transformations 2

nucleon number英文定义

nucleon number英文定义

nucleon number英文定义Nucleon Number: Definition and SignificanceThe nucleon number, also known as the mass number, is a concept in nuclear physics that defines the total number of nucleons (protons and neutrons) present in the atomic nucleus of an atom. It is an essential parameter that characterizes each specific isotope of an element, distinguishing one from another.In simple terms, the nucleon number represents the sum of protons and neutrons in an atomic nucleus. Protons have a positive charge, while neutrons have no charge. Both play a crucial role in atomic stability and determine the chemical properties of an element. The nucleon number, symbolized by the letter A, is usually written as a superscript preceding the chemical symbol of an element.For example, let's consider the isotope Carbon-12. The nucleon number of Carbon-12 is 12 because it has six protons (which determines its atomic number) and six neutrons. The atomic number, on the other hand, refers to the number of protons in an atom and is denoted by the letter Z. In this case, the atomic number of Carbon is 6.The nucleon number holds significant importance in various areas of nuclear physics and chemistry. Here are a few key points to illustrate its significance:1. Isotopes: Isotopes are atoms of the same element that have different nucleon numbers due to varying numbers of neutrons in their nuclei. Isotopes possess similar chemical properties but may differ in their physical properties, such as mass and radioactivity. The nucleon number allows scientists to differentiate between isotopes of an element.2. Nuclear Stability: The nucleon number plays a crucial role in determining the stability of an atomic nucleus. Generally, stable isotopes have a balanced ratio of protons to neutrons, while unstable isotopes may undergo radioactive decay due to an imbalance. The nucleon number helps scientists understand the stability and decay of atomic nuclei.3. Nuclear Reactions: Nucleon numbers are vital in nuclear reactions, such as fission and fusion. Fission involves the splitting of an atomic nucleus into smaller fragments, releasing a significant amount of energy. The nucleon numbers of the reacting nuclei and the resulting fragments determine the feasibility and outcome of nuclear reactions.4. Nuclear Binding Energy: The nucleon number affects the nuclear binding energy, which is the energy required to break apart a nucleus into its constituent nucleons. The binding energy per nucleon determines the stability of an atom. Elements with higher binding energy per nucleon are more stable.5. Atomic Mass: The nucleon number is directly related to the atomic mass. Although protons and neutrons have slightly different masses, the nucleon number provides an estimate of an atom's mass. However, it is important to note that the atomic mass may vary slightly due to the presence of isotopes and their relative abundances.In conclusion, the nucleon number, or mass number, is an essential parameter in nuclear physics that defines the total number of protons and neutrons in an atomic nucleus. It distinguishes one isotope of an element from another and plays a crucial role in determining nuclear stability, reactions, and binding energy. Understanding the nucleon number helps scientists unravel the intricate nature of atomic nuclei and their properties.。

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Abstract The quadrance between two points A1 = (x1 , y1 ) and A2 = (x2 , y2 ) is the number Q(A1 , A2 ) = (x1 − x2 )2 + (y1 − y2 )2 . Let q be an odd prime power and Fq be the 2 , and finite field with q elements. The unit-quadrance graph Dq has the vertex set Fq 2 are adjacent if and only if Q(A , A ) = 1. Let χ(F 2 ) be the chromatic X, Y ∈ Fq 1 2 q 1 / 2 2) number of graph Dq . In this note, we will show that q (1/2 + o(1)) χ(Fq q (1/2 + o(1)). As a corollary, we have a construction of triangle-free graphs Dq of order q 2 with χ(Dq ) ≥ q/2 for infinitely many values of q .
3
Proof of Theorem 1
The lower bound is straigtforward from Lemmas 4 and 5. We have λ1 = q ± 1 since Dq is a (q ± 1)-regular graph. Lemma 4 gives us λ∗ ≥ −q 1/2 . Hence χ(Dq ) ≥ 1 + q±1 = q 1/2 (1 + o(1)). 1 / 2 q
1
Introduction
In [3], Wildberger introduces a remarkable new approach to trigonometry and Euclidean geometry by replace distance by quadrance and angle by spread, thus allowing the development of Euclidean geometry over any field. The following definition follows from [3]. Definition 1 The quadrance Q(A1 , A2 ) between the points A1 = (x1 , y1 ), and A2 = (x2 , y2 ) in Fq2 is the number Q(A1 , A2 ) := (x2 − x1 )2 + (y2 − y1 )2 . This approach motives the question of finding chromatic number of unit-quadrance graph over any field. Note that in usual 2-dimensional Euclidean space R2 then the quadrance between A1 , A2 is unit if and only if the distance between A1 , A2 is unit. Let q be an odd prime power and Fq be the finite field with q elements. The unitquadrance graph Dq has the vertex set Fq2 , and X, Y ∈ Fq2 are adjacent if and only if Q(A1 , A2 ) = 1. This graph (or so-called finite Euclidean graph) was also studied by Medrano et al in [2]. Recall that the graph Dq is a regular graph with degree ∆(Dq ) = q − (−1)(q−1)/2 (see [2]). Let χ(Fq2 ) be the chromatic number of graph Dq . The main result of this note is the following theorem. 1
i∈Fq i∈Fq
{−χ(i) + χ(−i + t) − χ(i(−i + t))} χ(i2 (−1 + =0,t
χ(−1 + ti−1 )
= q + χ(−1) + χ(0) = q + (−1)(q−1)/2 .
2
But we have 4 if i is square and − i + t is not square, (1 − χ(i)) (1 + χ(−i + t)) = 2 if i = t. 0 otherwise. Thus, 4Aq + 2 = q + (−1)(q−1)/2 or Aq = (q + (−1)(q−1)/2 − 2)/4 ≥ 1. This concludes the proof of the lemma. Lemma 3 Suppose that q ≥ 5 is a prime power. Let a ∈ Fq such that a2 + 1 is not square. There exist t ∈ Fq∗ such that if A is in the line y = ax + i and B is in the line y = ax + i + t then Q(A, B ) = 1 for any i ∈ Fq . Proof Suppose that X = (x, ax + i) and Y = (y, ay + i + t) then Q(X, Y ) = (x − y )2 + (a(x − y ) + t)2 = (a2 + 1)(x − y )2 + 2a(x − y )t + t2 . If Q(X, Y ) = 1 then a2 + 1 = [(a2 + 1)(x − y ) + at]2 + t2 . From Lemma 2, there exists i ∈ Fq∗ such that i is square but −i + a2 + 1 is not. Hence, we can choose t such that t2 = i. This concludes the proof of the theorem. In [2], Medrano et al. give a general bound for eigvenvalue of Dq . Lemma 4 ([2]) Let λ = ∆(Dq ) be any eigenvalue of graph Dq then |λ| ≤ q 1/2 . The following result which is due to Hoffman gives us a connection between the chromatic number and eigenvalues of a graph. Lemma 5 ([1]) Let G be any graph with the largest and least eigenvalues are λ1 and λ∗ . Then λ1 χ(G) ≥ 1 − . λ∗
On chromatic number of unit-quadrance graphs (finite Euclidean graphs)
arXiv:math/0510092v1 [math.CO] 5 Oct 2005
Le Anh Vinh School of Mathematics University of New South Wales Sydney 2052 NSW
Theorem 1 Suppose that q = pn > 3 where p is an odd prime number then q 1/2 (1/2 + o(1)) χ(Fq2 ) pn + pn − 1 = q (1/2 + o(1)). 2
2
Some Lemmas
In order to prove Theoreom 1, we need some lemmas. Lemma 1 Suppose that a ∈ Fq such that a2 + 1 is not square in Fq . For any A = B in the line y = ax + i then Q(A, B ) = 1. Proof Suppose that A = (x1 , ax1 + i) and B = (x2 , ax2 + i) for some x1 = x2 ∈ Fq . We have Q(A, B ) = (a2 + 1)(x1 − x2 )2 = 1 since a2 + 1 is not square in Fq . The lemma follows. Recall that a (multiplicative) character of Fq is a homomorphism from Fq∗ , the multiplicative group of the non-zero elements of Fq , to the multiplicative group of complex numbers with modulus 1. The identically 1 function is the principal character of Fq and is denoted χ0 . Since xq−1 = 1 for every x ∈ Fq∗ we have χq−1 = χ0 for every character χ. A character χ is of order d if χd = χ0 and d is the smallest positive integer with this property. By convention, we extend a character χ to the whole of Fq by putting χ(0) = 0. The quadratic (residue) character is defined by χ(x) = x(q−1)/2 . Equivalently, χ is 1 on square, 0 at 0 and −1 otherwise. It is easy to see that i∈Fq χ(i) = 0. We have the following lemma. Lemma 2 Suppose that t is not a square in Fq . Then there exists a square number i ∈ Fq∗ such that −i + t is not a square in Fq . Proof Let Aq be the number of i ∈ Fq∗ such that i is square but −i + t is not. Consider the sum (1 − χ(i)) (1 + χ(−i + t)) = q +
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