Mesh Smoothing Method Based on Local Wave Analysis

As the mesh models usually contain noise data,it is necessary to eliminate the noises and smooth the mesh.But existed methods always lose geometric features during the smoothing process.Hence,the noise is considered as a kind of random signal with high frequency,and then the mesh model smoothing is operated with signal processing theory.Local wave analysis is used to deal with geometric signal,and then a novel mesh smoothing method based on the local wave is proposed.The proposed method includes following steps：Firstly,analyze the principle of local wave decomposition for 1D signal,and expand it to 2D signal and 3D spherical surface signal processing;Secondly,map the mesh to the spherical surface with parameterization,resample the spherical mesh and decompose the spherical signals by local wave analysis;Thirdly,propose the coordinate smoothing and radical radius smoothing methods,the former filters the mesh points＇ coordinates by local wave,and the latter filters the radical radius from their geometric center to mesh points by local wave;Finally,remove the high-frequency component of spherical signal,and obtain the smooth mesh model with inversely mapping from the spherical signal.Several mesh models with Gaussian noise are processed by local wave based method and other compared methods.The results show that local wave based method can obtain better smoothing performance,and reserve more original geometric features at the same time.

Analytical Criteria for Local Activity of CNN with Two Ports and Application to Smoothed Chua's Circuit

Presents analytic criteria for the local activity theory in two-port cellularneural network (CNN) cells with four local state variables, and gives the application to a smoothedChua's circuit (SCC) CNN with two-port and I 5 S 15 arrays. The bifurcation diagrams of the SCC CNNshow that they are completely the same as those of an SCC CNN with one-port calculated earlier;which do not exist locally passive domain. The evolution of the patterns of the state variables ofthe SCC CNN is stimulated. Oscillatory patterns, chaotic patterns, or divergent patterns may emergeif the selected cell parameters are located in the locally active unstable domains but nearby theedge of chaos domain.

Asymptotic-norming and Locally Asymptotic-norming Property of Banach Spaces

The relationship between some smoothness and weak asymptotic-norming properties of dual Banach space X is studied. The main results are the following. Suppose that X is weakly sequential complete Banach space, then X is Frechet differentiable if and only if X has B （X）- ANP -I, X is quasi-Frechet differentiable if and only if X has B（X）- ANP -H and X is very smooth if and only if X has B（X）- ANP -Ⅱ. A new local asymptotic-norming property is also introduced, and the relationship among this one and other local asymptotic-norming properties and some topological properties is discussed. In addition, this paper gives a negative answer to the open question raised by Hu and Lin in Bull. Austral. Math. Soc,45,1992.

SMOOTHING NEWTON ALGORITHM FOR THE CIRCULAR CONE PROGRAMMING WITH A NONMONOTONE LINE SEARCH

In this paper, we present a nonmonotone smoothing Newton algorithm for solving the circular cone programming(CCP) problem in which a linear function is minimized or maximized over the intersection of an affine space with the circular cone. Based on the relationship between the circular cone and the second-order cone(SOC), we reformulate the CCP problem as the second-order cone problem(SOCP). By extending the nonmonotone line search for unconstrained optimization to the CCP, a nonmonotone smoothing Newton method is proposed for solving the CCP. Under suitable assumptions, the proposed algorithm is shown to be globally and locally quadratically convergent. Some preliminary numerical results indicate the effectiveness of the proposed algorithm for solving the CCP.

EFFICIENT ESTIMATION OF FUNCTIONAL-COEFFICIENT REGRESSION MODELS WITH DIFFERENT SMOOTHING VARIABLES

In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective.

Smoothness加强的全局和局部显著目标检测

显著目标检测是计算机视觉的重要组成部分。针对基于对比度的方法存在的前景和背景容易被误检的问题,提出Smoothness加强的全局和局部显著目标检测的方法。在全局对比度检测过程中引入中心先验知识,在局部对比度检测过程中引入Compactness特征,再使用Smoothness特征加强全局的显著性及局部的显著性,最后将全局显著图和局部显著图进行线性融合。在MSRA-1000、ECSSD数据集上的评估中,该算法有更高的准确率,在CSSD数据集上能和最先进算法相媲美。实验表明,从全局和局部两个角度出发的显著性检测的方法能够有效的互补,Smoothness能够有效加强前景和背景的差异性,并且有效纠正一些误检现象,从而取得更好的结果。

Mechanisms mediating cholinergic antral circular smooth muscle contraction in rats

AIM:To investigate the pathway(s)mediating rat antral circular smooth muscle contractile responses to the cholinomimetic agent,bethanechol and the subtypes of muscarinic receptors mediating the cholinergic contraction. METHODS:Circular smooth muscle strips from the antrum of Sprague-Dawley rats were mounted in muscle baths in Krebs buffer.Isometric tension was recorded.Cumulative concentration-response curves were obtained for(+)-cis- dioxolane(cD),a nonspecific muscarinic agonist,at 10^(-8)- 10^(-4)mol/L,in the presence of tetrodotoxin(TTX,10^(-7)mol/L). Results were normalized to cross sectional area.A repeat concentration-response curve was obtained after incubation of the muscle for 90 min with antagonists for M1(pirenzepine), M2(methoctramine)and M3(darifenadn)muscarinic receptor subtypes.The sensitivity to PTX was tested by the ip injection of 100 mg/kg of PTX 5 d before the experiment.The antral circular smooth muscles were removed from PTX-treated and non-treated rats as strips and dispersed smooth muscle cells to identify whether PTX-linked pathway mediated the contractility to bethanechol. RESULTS:A dose-dependent contractile response observed with bethanechol,was not affected by TTx.The pretreatment of rats with pertussis toxin decreased the contraction induced by bethanechol.Lack of calcium as well as the presence of the L-type calcium channel blocker,nifedipine,also inhibited the cholinergic contraction,with a reduction in response from 2.5±0.4 g/mm^2 to 1.2±0.4 g/mm^2(P<0.05).The dose- response curves were shifted to the right by muscarinic antagonists in the following order of affinity:darifenacin (M_3)>methocramine(M_2)>pirenzepine(M_1). CONCLUSION:The muscarinic receptors-dependent contraction of rat antral circular smooth muscles was linked to the signal transduction pathway(s)involving pertussis-toxin sensitive GTP-binding proteins and to extracellular calcium via L-type voltage gated calcium channels.The presence of the residual contractile response after the treatment with nifedipine,suggests that an additional pathway could mediate the cholinergic contraction.The involvement of more than one muscarinic receptor(functionally predominant type 3 over type 2)also suggests more than one pathway mediating the cholinergic contraction in rat antrum.

K-very Smooth Banach Spaces

We introduce the notion of K-very smoothness which is a generalization of very smoothness in Banach spaces. A necessary and sufficient condition for a Banach space to be K-very smooth is obtained. We also consider some relations between K-very smoothness and other geometrical notions.

Solving Smooth Generalized Equations Using Modified Gauss-Type Proximal Point Method

Consider X and Y are two real or complex Banach spaces. We introduce and study a modified Gauss-type proximal point algorithm (in short modified G-PPA) for solving the generalized equations of the form 0 ∈h(x) + H(x), where h : X → Y is a smooth function on Ω ⊆X and H : X ⇉2Y is a set valued mapping with closed graph. When H is metrically regular and under some sufficient conditions, we analyze both semi-local and local convergence of the modified G-PPA. Moreover, the convergence results of the modified G-PPA are justified by presenting a numerical example.

Tapping New Trends to Restart Local Economies

AFTER China brought the COVID-19 epidemic under control,shops in many cities began to extend their business hours and set up outdoor shopping places;night markets have become busy again.During the process,the country is trying to tap various new trends to help the reopening of local economies safely and smoothly.

五轴线性刀路的局部能量光顺及奇异避免方法

针对现行五轴加工中存在的路径拐角处平动轴减速过度,奇异区域旋转轴角度变化剧烈的问题,以AC双转台五轴机床为研究对象,提出一种满足机床运动学约束的路径优化方法。该方法首先以刀心点光顺前后最大许用偏移量作为约束,利用转角向量和双弦弓高进行建模,寻求微小线段拐角处局部能量最优解。并对奇异范围内部和边缘的刀轴矢量点二次规划,使得矢量末端刚好绕过单位球面上的奇异区域,极大地保留原有加工特性。通过结合三角函数加减速控制算法,对优化效果进行评估。仿真结果表明:该路径优化方法在拟合偏差与弓高误差均没有超过许用值的同时,平均进给速度提升了10.64%,而且能有效避免加工中奇异现象的发生。可见本文所提出的方法在提高五轴加工效率和加工质量等方面具有较高的理论意义和实际应用价值。

基于多标签语义分割的硬笔字笔画提取

汉字作为中华文化的载体,因其复杂的结构区别于其他文字.笔画作为汉字的基本单元,在硬笔字评价中起到至关重要的作用.正确提取笔画,是硬笔字评价的首要步骤.现有的笔画提取方法多数是基于规则的,由于汉字的复杂性,这些规则通常无法顾及所有特征,且在评价时无法根据笔顺等信息与模板字笔画匹配.为了解决这些问题,该文将笔画提取转化为多标签语义分割问题,提出了多标签语义分割模型(M-TransUNet),利用深度卷积模型以汉字为单位任务进行训练,保留了笔画原有结构,避免了笔画段组合的二义性,同时得到了硬笔字的笔顺,有利于笔画评价等下游任务.由于硬笔字图像只分为前景和背景,没有额外颜色信息,所以更容易产生FP(false positive)分割噪声.为解决此问题,本文还提出了一种针对笔画分割结果的局部平滑策略(local smooth strategy on stroke,LSSS),淡化噪声的影响.最后,本文对M-TransUNet的分割性能以及效率进行了实验,证明了本文算法在很小性能损失的情况下,极大地提升了效率.同时对LSSS算法进行了实验,证明其在FP噪声消除的有效性.

部分线性变系数空间自回归模型的惩罚轮廓拟最大似然方法

主要研究了部分线性变系数空间自回归模型的变量选择问题。结合拟最大似然方法、局部线性光滑方法以及一类非凸罚函数,提出了一个变量选择方法用于同时选择该模型的参数部分中重要解释变量和估计相应的非零参数。大量模拟研究表明,所提出的变量选择方法具有满意的有限样本性质,并且关于空间权矩阵的稀疏度、空间相关强度、系数函数的复杂度以及误差分布的非正态性非常稳健。特别地,当样本容量较大且罚函数选择合适时,即使解释变量的相关性较强或者模型中含有较多不重要解释变量,所提出的变量选择方法仍然具有比较满意的有限样本性质。通过分析波士顿房屋价格数据考察了所提出的变量选择方法的实际应用效果。

基于区域调光算法的车载液晶显示技术研究及应用

为了提升传统车载液晶显示器的能效和显示质量,提出一种应用于车载液晶显示器的区域调光算法。将输入的RGB色彩模式转换为YUV色彩模式以提取像素点亮度数据,并依照背光分区对应的图像子区域提取亮度数据。采用分区背光模糊-扩散模拟LED背光源在背光模组中传播时的扩散过程,得到各像素点的背光亮度数据,并据此通过液晶像素进行精确补偿得到最终调光图像。仿真结果显示,该方法在图像信息熵、图像细节增强和峰值信噪比3个评价方法上,优于其他区域调光算法的增强效果。同时在样机实验中,平均整体能耗降低了20.7%。表明该算法能够在提高显示质量的同时合理降低车载显示器的整机功耗,对各类车载显示器都具有良好的适用性。

基于RRT算法的移动机器人安全光滑路径生成

在多障碍物复杂工厂环境中,针对快速探索随机树算法(RRT)生成的路径存在冗余点、贴近障碍物且存在锯齿状转折的问题,改进得到了安全-光滑RRT(Safe-SmoothRRT)路径规划算法。首先,引入目标偏置策略;其次,该算法利用融合目标点引力思想的新节点扩展方式以及改进的近邻点度量策略以减少树的盲目扩展,提高生长的目标性;随后,引入节点安全约束,将安全节点加入树中;改进路径简化方法,剔除冗余点的同时兼顾了安全性;最后通过B样条局部平滑来改善路径的平滑性。在MATLAB仿真实验中分别与标准RRT算法、自适应目标偏向性RRT算法和改进RRT算法相比,在平均路径长度方面最大下降了7.1%,在平均有效节点数方面最大下降了64.1%,且所得路径始终与障碍物保持一定的安全距离,结果表明改进算法有效提升了路径的光滑性和安全性。

局部特征引导标签平滑与优化的井下弱特征人员重识别

煤矿井下低照度、强光扰、高粉尘等环境条件,以及井下人员服装的相似性和脸部落煤现象,导致井下弱特征人员重识别困难。现有人员重识别方法仅提取全局特征,未充分考虑局部特征,使得井下人员重识别准确率较低。针对上述问题,提出了一种局部特征引导标签平滑与优化的井下弱特征人员重识别方法。该方法首先通过卷积神经网络提取井下人员图像的全局特征与局部特征;然后利用k最近邻相似性计算全局特征和局部特征的互补性得分,来衡量全局特征和局部特征的相似程度;最后根据特征互补性得分对局部特征进行标签平滑及对全局特征进行标签优化,即动态调整每个局部特征的权重,以改进每个局部特征的标签,并对局部特征的预测结果进行汇总,利用更可靠的信息来完善标签以作为全局特征的标签,从而减少图像噪声并增强特征识别能力。实验结果表明,该方法在公开数据集和包含井下人员图像的自建数据集上的平均精度均值(mAP)、第一匹配正确率(Rank-1)和平均逆置负样本惩罚率(mINP)总体优于主流人员重识别方法,具有良好的泛化性和鲁棒性,能有效实现井下弱特征人员重识别。

血清镁离子浓度与直肠癌患者谷氨酰转肽酶的关系

直肠癌患者血清镁离子(Mg^(2+))浓度对γ-谷氨酰转肽酶(γ-GT)的影响尚不明确,收集分析临床数据,Mg^(2+)浓度不呈正态分布(D=0.737,P<0.05),按照中位数分组,比较不同组间临床病理特征的差异,用局部加权散点平滑(LOWESS)、分段线性回归方法,拟合血清Mg^(2+)浓度与γ-GT的关系。结果发现,与Mg^(2+)浓度小于0.92 mmol/L组的直肠癌患者比较,Mg^(2+)浓度≥0.92 mmol/L组的γ-GT和血清总胆固醇较高(P均<0.05)。LOWESS的结果表明,原始数据中血清Mg^(2+)浓度的两个变化点分别为0.92 mmol/L和0.99 mmol/L,自然对数转换的数据中血清Mg^(2+)浓度的另外两个变化点分别为-0.167和-0.01。利用原始数据建立的两段线性回归模型表明,血清Mg^(2+)浓度的变化点为0.98 mmol/L,Mg^(2+)浓度<0.98 mmol/L对γ-GT有正向影响,Mg^(2+)≥0.98 mmol/L时有负向影响。另一个使用自然对数转换数据的两段线性回归模型显示,血清Mg^(2+)浓度的变化点为0.01,其中Mg^(2+)浓度的自然对数<0.01对γ-GT有正向影响,当Mg^(2+)浓度的自然对数≥0.01时则有负向影响。用原始数据LOWESS回归的2个拐点,即0.92 mmol/L和0.99 mmol/L的Mg^(2+)浓度,进行三段线性回归分析,结果显示,<0.980 mmol/L的Mg^(2+)浓度,对γ-GT的影响是正向的,且与<0.929 mmol/L的Mg^(2+)浓度区间的系数不同,影响程度不同,而在≥0.980 mmol/L的Mg^(2+)浓度区间,对γ-GT的影响是负向的,此外,用对数转换数据LOWESS的2个拐点进行的三段线性回归,也显示Mg^(2+)浓度的自然对数以-0.020为分界点时,对γ-GT的影响方向是相反的,但三段线性回归模型均没有统计学意义,总之,具有较高Mg^(2+)浓度的直肠癌患者,其γ-GT的水平也较高,Mg^(2+)浓度对γ-GT的影响存在拐点效应,为γ-GT的关联因素研究提供了基础。

局部高斯均差变分保边图像平滑算法

针对图像平滑过程中无法保留细节的问题,提出了基于局部高斯均差变分的保边图像平滑算法。首先,通过统计学分析建立局部高斯均差变分算子。其可以衡量局部梯度与高斯滤波处理后的梯度差异,区分结构和纹理。其次,构建局部高斯均差变分平滑模型,由稀疏求解得到初始平滑图像。最后,针对复杂纹理图像存在纹理残留的问题,提出孤立噪声去除模型。模型通过自适应窗口设定像素值,在不影响结构的前提下去除初始平滑图像中的纹理残留。通过主观、客观实验,与经典的算法对比,证明该算法有更高质量的平滑结果。评价指标整体提升了0.7%。通过压缩伪影去除、HDR色调映射、图像去雾和拉普拉斯金字塔加速的扩展实验,验证该算法在不同视觉任务上的适用性和效率可提升性。

多变流器互联交直流微网集群一致性功率协同控制

为增强多变流器互联交直流微网集群系统运行稳定性、可靠性及控制灵活性,本文提出一种一致性功率协同控制策略。控制系统包含互联变流器(DC-DC、DC-AC)柔性控制和交、直流微电网下垂控制等。互联DC-AC和DC-DC均采用双环控制,外环将一致性耦合控制和功率分配环节相结合,内环分别采用虚拟同步控制和移相控制。本文所提控制方法,系统仅基于就地量测频率或直流电压等信息,可同时实现子系统间功率协同互济、多互联变流器功率分配及多运行模式自适应平滑切换等目标。最后通过PSCAD/EMTDC仿真模型对所提方法的有效性进行了验证。

Joint training with local soft attention and dual cross-neighbor label smoothing for unsupervised person re-identification

Existing unsupervised person re-identification approaches fail to fully capture thefine-grained features of local regions,which can result in people with similar appearances and different identities being assigned the same label after clustering.The identity-independent information contained in different local regions leads to different levels of local noise.To address these challenges,joint training with local soft attention and dual cross-neighbor label smoothing(DCLS)is proposed in this study.First,the joint training is divided into global and local parts,whereby a soft attention mechanism is proposed for the local branch to accurately capture the subtle differences in local regions,which improves the ability of the re-identification model in identifying a person’s local significant features.Second,DCLS is designed to progressively mitigate label noise in different local regions.The DCLS uses global and local similarity metrics to semantically align the global and local regions of the person and further determines the proximity association between local regions through the cross information of neighboring regions,thereby achieving label smoothing of the global and local regions throughout the training process.In extensive experiments,the proposed method outperformed existing methods under unsupervised settings on several standard person re-identification datasets.