Pseudo-Semi-Overlap Functions-Based Fuzzy Rough Sets Applied to Image Edge Extraction

As an extension of overlap functions, pseudo-semi-overlap functions are a crucial class of aggregation functions. Therefore, (I, PSO)-fuzzy rough sets are introduced, utilizing pseudo-semi-overlap functions, and further extended for applications in image edge extraction. Firstly, a new clustering function, the pseudo-semi-overlap function, is introduced by eliminating the symmetry and right continuity present in the overlap function. The relaxed nature of this function enhances its applicability in image edge extraction. Secondly, the definitions of (I, PSO)-fuzzy rough sets are provided, using (I, PSO)-fuzzy rough sets, a pair of new fuzzy mathematical morphological operators (IPSOFMM operators) is proposed. Finally, by combining the fuzzy C-means algorithm and IPSOFMM operators, a novel image edge extraction algorithm (FCM-IPSO algorithm) is proposed and implemented. Compared to existing algorithms, the FCM-IPSO algorithm exhibits more image edges and a 73.81% decrease in the noise introduction rate. The outstanding performance of (I, PSO)-fuzzy rough sets in image edge extraction demonstrates their practical application value.

Generating Type 2 Trapezoidal Fuzzy Membership Function Using Genetic Tuning

Fuzzy inference system(FIS)is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs.The system starts with identifying input from data,applying the fuzziness to input using membership functions(MF),generating fuzzy rules for the fuzzy sets and obtaining the output.There are several types of input MFs which can be introduced in FIS,commonly chosen based on the type of real data,sensitivity of certain rule implied and computational limits.This paper focuses on the construction of interval type 2(IT2)trapezoidal shape MF from fuzzy C Means(FCM)that is used for fuzzification process of mamdani FIS.In the process,upper MF(UMF)and lower MF(LMF)of the MF need to be identified to get the range of the footprint of uncertainty(FOU).This paper proposes Genetic tuning process,which is a part of genetic algorithm(GA),to adjust parameters in order to improve the behavior of existing system,especially to enhance the accuracy of the system model.This novel process is a hybrid approach which produces Genetic Fuzzy System(GFS)that helps to enhance fuzzy classification problems and performance.The approach provides a new method for the construction and tuning process of the IT2 MF,based on the FCM outcomes.The result is compared to Gaussian shape IT2 MF and trapezoid IT2 MF generated by the classic GA method.It is shown that the proposed approach is able to outperform the mentioned benchmarked approaches.The work implies a wider range of IT2 MF types,constructed based on FCM outcomes,and an optimum generation of the FOU so that it can be implemented in practical applications such as prediction,analytics and rule-based solutions.

Sub-Differential Characterizations of Non-Smooth Lower Semi-Continuous Pseudo-Convex Functions on Real Banach Spaces

In this paper, we characterize lower semi-continuous pseudo-convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the pseudo-monotonicity of its Clarke-Rockafellar Sub-differential. We extend the results on the characterizations of non-smooth convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the monotonicity of its sub-differentials to the lower semi-continuous pseudo-convex functions on real Banach spaces.

Fuzzy Semi-continuity of fuzzy number-valued function

In this paper we discuss the conecept and property of fuzzy semi continuous function.

Functionalization of Semi-terminated Silica Nanotubes

The semi-terminated silica nanotubes with 80-100 nm porous diameter were prepared with AI/Al2O3 （AAO） template by the sol-gel method, and then were functionalized by 3-aminopropyltriethoxysilane （APTES）. The functionalized silica nanotubes were characterized by transmission electron microscope （TEM）, fourier transform infrared spectroscopy （FT-IR）, nuclear magnetic resonance （1H-NMR and 29Si-NMR）. The results indicated that APTES was successfully functionalized onto the internal surface and the mouth of the silica nanotubes. It would provide the material base for silica nanotubes corking and delivery drug.

SEMI-WEIGHT FUNCTION METHOD ON COMPUTATION OF STRESS INTENSITY FACTORS IN DISSIMILAR MATERIALS

Semi_weight function method is developed to solve the plane problem of two bonded dissimilar materials containing a crack along the bond. From equilibrium equation, stress and strain relationship, conditions of continuity across interface and free crack surface, the stress and displacement fields were obtained. The eigenvalue of these fields is lambda. Semi_weight functions were obtained as virtual displacement and stress fields with eigenvalue?_lambda. Integral expression of fracture parameters, K Ⅰ and K Ⅱ, were obtained from reciprocal work theorem with semi_weight functions and approximate displacement and stress values on any integral path around crack tip. The calculation results of applications show that the semi_weight function method is a simple, convenient and high precision calculation method.

Filtering Function Method for the Cauchy Problem of a Semi-Linear Elliptic Equation

A Cauchy problem for the semi-linear elliptic equation is investigated. We use a filtering function method to define a regularization solution for this ill-posed problem. The existence, uniqueness and stability of the regularization solution are proven;a convergence estimate of H?lder type for the regularization method is obtained under the a-priori bound assumption for the exact solution. An iterative scheme is proposed to calculate the regularization solution;some numerical results show that this method works well.

CURRENTS CARRIED BY THE SUBGRADIENT GRAPHS OF SEMI-CONVEX FUNCTIONS AND APPLICATIONS TO HESSIAN MEASURES

In this paper we study integer multiplicity rectifiable currents carried by the subgradient （subdifferential） graphs of semi-convex functions on an n-dimensional convex domain, and show a weak continuity theorem with respect to pointwise convergence for such currents. As an application, the structure theorem of the Lagrangian currents for semi-convex functions is given and the k-Hessian measures are calculated by a different method in terms of currents.

Green's function for T-stress of semi-infinite plane crack

Green’s function for the T-stress near a crack tip is addressed with an analytic function method for a semi-infinite crack lying in an elastical, isotropic, and infinite plate. The cracked plate is loaded by a single inclined concentrated force at an interior point. The complex potentials are obtained based on a superposition principle, which provide the solutions to the plane problems of elasticity. The regular parts of the potentials are extracted in an asymptotic analysis. Based on the regular parts, Green’s function for the T-stress is obtained in a straightforward manner. Furthermore, Green’s functions are derived for a pair of symmetrically and anti-symmetrically concentrated forces by the superimposing method. Then, Green’s function is used to predict the domain-switch-induced T-stress in a ferroelectric double cantilever beam （DCB） test. The T-stress induced by the electromechanical loading is used to judge the stable and unstable crack growth behaviors observed in the test. The prediction results generally agree with the experimental data.

Cascaded Construction of Semi-Bent and Bent Functions

Based on the theory of quadratic forms over finite fields, a new construction of semi-bent and bent functions is presented. The proposed construction has a cascaded characteristic. Some previously known constructions of semi-bent and bent functions are special cases of the new construction.

Radar emitter signal recognition method based on improved collaborative semi-supervised learning

Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.

ENHANCING GROUND RESOLUTION OF TM6 BASED ON MULTI-VARIATE REGRESSION MODEL AND SEMI-VARIOGRAM FUNCTION

It is well known that Landsat TM images are the most widely used remote sensing data in various fields.Usually,it has 7 different electromagnetic spectrum bands,among which the sixth one has much lower ground resolution compared with the other six bands.Nevertheless,it is useful in the study of rock spectrum reflection,geothermal resources exploration,etc.To improve the ground resolution of TM6 to the level as that of the other six bands is a problem .This paper presents an algorithm based on the combination of multivariate regression model with semivariogram function which can improve the ground resolution of TM6 by "fusing" the data of other six bands.It includes the following main steps: （1） testing the correlation between TM6 and one of TM15,7.If the correlation coefficient between TM6 and another one is greater than a given threshold value,then select the band to the regression analysis as an argument.（2） calculating the size of the template window within which some parameters needed by the regression model will be calculated; （3） replacing the original pixel values of TM6 by those obtained by regression analysis; （4） using image entropy as a measurement to evaluate the quality of the fused image of TM6.The basic mechanism of the algorithm is discussed and the V C ++ program for implementing this algorithm is also presented.A simple application example is given in the last part of this paper,showing the effectiveness of the algorithm.

Features on N/P ratio of plants with different functional groups between two types of steppe in semi-arid area

The differences in nitrogen/phosphorus(N/P)ratios of different functional groups in ecology are more helpful in explaining species competition and community dynamics.Based on the functional groups of plant growth type,carbon metabolism pathway,root type and phylogenetic type,we analyzed characteristics of leaf N/P ratios of 77 species in Sanggendalai(typical grassland zone)of Zhenglan Banner,Inner Mongolia,China and 91 species in the Habahu National Nature Reserve(desertified grassland zone)in Yanchi County of Ningxia,China.The results show that the N/P ratio(16.91)of C3 plants in the desertified steppe was significantly larger than that(12.72)in the typical steppe,but there was no significant difference between the N/P ratios of C4 plants in the two zones.There was no significant difference in N/P ratios between C3 plants and C4 plants in the same zone.Similarly,the N/P ratio(16.60)of dicotyledons in desertified steppe were significantly higher than that(12.98)in typical steppe,while differences in N/P ratios between monocotyledonous plants of the two zones was not significant,and there existed no significant difference in N/P ratios between dicotyledonous and monocotyledonous plants in the same zone.The N/P ratio had significant difference between gramineous and non-gramineous plants in the typical steppe but not in the desertified steppe,but there existed no significant difference in N/P ratios among different root types of perennial herbaceous plants in the same type of steppe or between two types of steppe.Thus,different features on the N/P ratios of C3 plants and dicotyledonous plants between typical steppe and desertified steppe may lead to different growth status of plants,and the N/P ratio stoichiometric of the same plant functional group may be a foundation of the changes of a plant community.

Effect of Weight Function in Nonlinear Part on Global Solvability of Cauchy Problem for Semi-Linear Hyperbolic Equations

In this paper, we investigate the effect of weight function in the nonlinear part on global solvability of the Cauchy problem for a class of semi-linear hyperbolic equations with damping.

Electromagnetic response function for the semi-annual variations estimated by the single-station method using the night-time values of the geomagnetic fields

The geomagnetic night-time values were used to estimate the electromagnetic response function Q1 for half-year period. If the spatial structure of the source field can be described by the approximation, one can estimate the Q1 value using the single-station Z/H method. This technique enables us to carry out regional deep gcomagnetic sounding by the method. The data used for analyses are geomagnetic night-time values for about, typically, 26 years from 5 good-quality stations and for several years from 34 stations distributed over the globe. The results indicate that the night-time values yield more reliable response estimates for half-year period compared to the usual estimates obtained from daily means. It implies that the approximation for the night-time fields holds good for the half-year period, but the daily means are not suitable for estimating the response function of the semi-annual variations by using the single-station method. Source field analyses for daily means data and night-time means data have also been carried out in this paper.

Weight Function Method for Stress Intensity Factor of Internal Surface Semi-elliptical Crack in Elliptical Holes

The hatches for inspecting are usually designed with elliptical holes in airplane structures, so computation of the stress intensity factor of three dimensional crack at elliptical holes is pivotal for damage tolerance analysis of these structures. In this paper, weight function is derived for a two dimensional through cracks at elliptical holes by applying a compounding method. Stress intensity factor formulas for an internal surface semi-elliptical crack in elliptical holes are obtained wing the three dimensional weight function method. Stress intensity factors for an internal surface semi-elliptical crack in elliptical holes under remote tension are computed. At the same time, research on how radius of curvature for elliptical holes affect stress intensity factors was conducted. Stress intensity factors decrease when radius of curvature increases. Some results and conclusions which are of practical value are given.

基于模糊评判的无线传感器网络簇间数据转发算法

由于无线传感器网络在簇间数据转发过程中消耗能量较大、转发效率低,导致数据在转发过程中容易失效。为此,提出基于模糊评判的无线传感器网络簇间数据转发算法。建立无线传感器网络模型和通信模型,明确节点的运行方式和转发数据所消耗的能量,构建模糊综合评判模型,选取梯形隶属度函数计算传感器节点的相似度和活跃度,找出最佳转发节点,完成数据转发任务。仿真结果表明,所提算法的第一个节点死亡轮数和网络失效轮数最高为167和178,在仿真轮数达到1000轮时,该算法剩余的网络能量和节点平均能量分别为4 J和0.01 J,证明所提算法在数据转发过程中可消耗最少的能量,高效率地完成数据转发任务。

非均质气藏井间地层压力计算方法及应用

中国陆相沉积气藏储层普遍存在非均质性,常规地层压力计算方法具有很大局限性,难以准确评价井间地层压力。本文以均质地层中的点源解为基础,采用边界元思想,建立了一种可用于非均质气藏井间地层压力计算的半解析方法。基本思想是将非均质储层进行分块处理,分别建立单个均质区域的压力方程,通过各区交界面处的压力和流量连续条件,将各区压力方程耦合求解,并将求解结果回代至单个区域的压力方程,从而计算地层中任意一点的压力。建立了理论模型,对所提出的井间地层压力计算方法进行了数值验证,并将其应用于长庆靖边气田某区块。结果表明,本文所建立的非均质气藏井间地层压力半解析计算方法与数值模拟计算结果相吻合,仅在早期和井筒附近存在微小差异;半解析方法能很好地预测实际气藏中单井及井间的地层压力变化,与实测数据趋势一致。

基于显著性区域检测的多尺度图像盲复原算法

针对大多数基于先验的盲图像去模糊算法耗时较长和显著边缘结构提取不理想的问题,提出一种基于显著性区域检测的多尺度图像盲复原算法。为了复原出更加清晰的图像,采用由粗略到精细的多尺度交替迭代框架构建图像金字塔。在图像单一尺度方面,首先提取出图像中具有强边缘结构的显著性区域,并对其施加l_(0)范数约束,提出显著映射先验;将显著性映射先验和最大后验概率相结合并引入传统图像去模糊模型中,构造出点扩散函数估算模型,利用半二次分裂算法解决模型的非凸问题;对点扩散函数进行复原时,利用点扩散函数相似度的变化量限制每个尺度中的过渡迭代;对模糊图像和最终估计的点扩散函数进行非盲解卷积,获得复原图像。实验结果表明:与现有的主流去模糊算法相比,新算法在合成数据集和真实数据集中都可以有效抑制振铃和伪影现象,得到了很好的视觉体验,且评价指标均优于对比算法,同时大大缩减了复原时间。