On Cesari's property (Q)

In the present paper, we generalize, within the family of convex-valued multifunctions, a selection theorem of Cole (Ref. 1). This then leads us to prove some new results concerning Cesari's property (Q) and to the introduction of the Cesari limit of sets, which is then compared to the Kuratowski-Mosco limit.This work was done while the author was a visiting professor at the University of Pavia, Pavia, Italy. Financial support was provided by CNR and by NSF Grant No. 84-03135.     

The Möbius function of separable and decomposable permutations

We give a recursive formula for the Möbius function of an interval [σ,π] in the poset of permutations ordered by pattern containment in the case where π is a decomposable permutation, that is, consists of two blocks where the first one contains all the letters 1,2,…,k for some k. This leads to many special cases of more explicit formulas. It also gives rise to a computationally efficient formula for the Möbius function in the case where σ and π are separable permutations. A permutation is separable if it can be generated from the permutation 1 by successive sums and skew sums or, equivalently, if it avoids the patterns 2413 and 3142.We also show that the Möbius function in the poset of separable permutations admits a combinatorial interpretation in terms of normal embeddings among permutations. A consequence of this interpretation is that the Möbius function of an interval [σ,π] of separable permutations is bounded by the number of occurrences of σ as a pattern in π. Another consequence is that for any separable permutation π the Möbius function of (1,π) is either 0, 1 or −1.     

Product design and selection using fuzzy QFD and fuzzy MCDM approaches

Quality function deployment (QFD) is a useful analyzing tool in product design and development. To solve the uncertainty or imprecision in QFD, numerous researchers have applied the fuzzy set theory to QFD and developed various fuzzy QFD models. Three issues are investigated by examining their models. First, the extant studies focused on identifying important engineering characteristics and seldom explored the subsequent prototype product selection issue. Secondly, the previous studies usually use fuzzy number algebraic operations to calculate the fuzzy sets in QFD. This approach may cause a great deviation in the result from the correct value. Thirdly, few studies have paid attention to the competitive analysis in QFD. However, it can provide product developers with a large amount of valuable information. Aimed at these three issues, this study integrates fuzzy QFD and the prototype product selection model to develop a product design and selection (PDS) approach. In fuzzy QFD, the α-cut operation is adopted to calculate the fuzzy set of each component. Competitive analysis and the correlations among engineering characteristics are also considered. In prototype product selection, engineering characteristics and the factors involved in product development are considered. A fuzzy multi-criteria decision making (MCDM) approach is proposed to select the best prototype product. A case study is given to illustrate the research steps for the proposed PDS method. The proposed method provides product developers with more useful information and precise analysis results. Thus, the PDS method can serve as a helpful decision-aid tool in product design.     

基于可能性分布联合落影的红外图像融合算法选取

针对双模态红外图像实际融合需求中常涉及到异类差异特征协同优化融合,且现有差异特征属性无法针对性地调整融合算法进行有效驱动,导致融合效果差等问题,提出了基于可能性分布联合落影的双模态红外图像融合算法选取的方法。首先计算双模态红外图像差异特征幅值的融合有效度,利用K最近邻法得到差异特征幅值的概率密度分布,得到差异特征频次属性的分布;然后通过差异特征幅值属性与频次属性构造差异特征权重函数,建立异类差异特征权重函数与多融合算法间的可能性分布合成,得到异类差异特征权重函数多融合算法融合有效度的联合落影;最后构建融合性能指标动态选取最优融合算法。实验结果表明,本文方法所选出的最优融合算法在等级得分指标上明显优于其他算法,验证了本文将可能性分布联合落影运用于双模态红外图像最优融合算法选取中具有可行性。     

正交匹配追踪算法的近红外光谱定量分析

压缩感知(CS)是一种新兴的信号压缩和采样技术,正交匹配追踪(OMP)是一种贪婪追踪算法,广泛用于压缩感知领域中的稀疏信号重构.针对近红外光谱信号高维小样本以及信号稀疏先验的特点,为进一步提高小样本近红外光谱变量选择的灵活性和可靠性,基于压缩感知理论,提出了一种新颖的光谱变量选择方法正交匹配追踪变量选择(OM PBVS...     

An Isotonic Regression Problem for Infinite-Dimensional Parameters

We consider an infinite-dimensional isotonic regression problem which is an extension of the suitably revised classical isotonic regression problem. Given p-summable data, for p finite and at least one, there exists an optimal estimator to our problem. For p greater than one, this estimator is unique and is the limit in the p-norm of the sequence of unique estimators in canonical finite-dimensional truncations of our problem. However, for p equal to one, our problem, as well as the finite-dimensional truncations, admit multiple optimal estimators in general. In this case, the sequence of optimal estimator sets to the truncations converges to the optimal estimator set of the infinite problem in the sense of Kuratowski. Moreover, the selection of natural best optimal estimators to the truncations converges in the 1-norm to an optimal estimator of the infinite problem.     

On nonlinear coupled diffusions in competition systems

A class of reaction-diffusion systems modeling plant growth with spatial competition in saturated media is presented. We show, in this context, that standard diffusion can not lead to pattern formation (Diffusion Driven Instability of Turing). Degenerated nonlinear coupled diffusions inducing free boundaries and exclusive spatial diffusions are proposed. Local and global existence results are proved for smooth approximations of the degenerated nonlinear diffusions systems which give rise to long-time pattern formations. Numerical simulations of a competition model with degenerate/non degenerate nonlinear coupled diffusions are performed and we carry out the effect of the these diffusions on pattern formation and on the change of basins of attraction.     

Diffraction mode selection in planar Bragg resonators of optical and microwave wavelength ranges

Using the coupled waves approach complemented by the time-domain quasi-optical approximation, we solve a 2D diffraction problem which allows to evaluate the eigenfrequencies, quality factors and spatial structures of eigenmodes in planar Bragg resonators with a finite length and width of the corrugated area. We find the values of the Fresnel parameter determined by the geometrical dimensions of the system which allows for efficient transverse mode discrimination due to the larger diffraction losses of the modes with higher transverse numbers.     

Injection attack detection using machine learning for smart IoT applications

Smart cities are a rapidly growing IoT application. These smart cities mainly rely on wireless sensors to connect their different components (smart devices) together. Smart cities rely on the integration of IoT and 5G technologies, and this has created a demand for a massive IoT network of connected devices. The data traffic coming from indoor wireless networks (e.g., smart homes, smart hospitals, smart factories , or smart school buildings) contributes to over 80% of the total data traffic of the current IoT network. As smart cities and their applications grow, security and privacy challenges have become a major concern for billions of IoT smart devices. One reason for this could be the oversight of handling security issues of IoT devices by their manufacturers, which enables attackers to exploit the vulnerabilities in these devices by performing different types of attacks, e.g., DDoS and injection attacks. Intrusion detection is one way to detect and mitigate the risk of such attacks. In this paper, an intrusion detection method was proposed to detect injection attacks in IoT applications (e.g. smart cities). In this method, two types of feature selection techniques (constant removal and recursive feature elimination) were used and tested by a number of machine learning classifiers (i.e., SVM, Random Forest, and Decision Tree). The T-Test was conducted to evaluate the quality of this proposed feature selection method. Using the public dataset, AWID, the evaluation results showed that the decision tree classifier can be used to detect injection attacks with an accuracy of 99% using only 8 features, which were selected using the proposed feature selection method. Also, the comparison with the most related work showed the advantages of the proposed intrusion detection method.