各向异性椭圆方程障碍问题弱解的拟最小化性质

拟最小化性质是研究椭圆方程弱解的重要工具。该文研究了各向异性的A-调和方程-divA(x,Du)=0障碍问题的弱解,使用了Hlder不等式,Young不等式以及一些基本不等式,完成了各向异性情形下弱解的积分估计,得到了各向异性障碍问题弱解的拟最小化性质。     

Bounded memory protocols

It is well-known that the Dolev–Yao adversary is a powerful adversary. Besides acting as the network, intercepting, decomposing, composing and sending messages, he can remember as much information as he needs. That is, his memory is unbounded. We recently proposed a weaker Dolev–Yao like adversary, which also acts as the network, but whose memory is bounded. We showed that this Bounded Memory Dolev–Yao adversary, when given enough memory, can carry out many existing protocol anomalies. In particular, the known anomalies arise for bounded memory protocols, where although the total number of sessions is unbounded, there are only a bounded number of concurrent sessions and the honest participants of the protocol cannot remember an unbounded number of facts or an unbounded number of nonces at a time. This led us to the question of whether it is possible to infer an upper-bound on the memory required by the Dolev–Yao adversary to carry out an anomaly from the memory restrictions of the bounded protocol. This paper answers this question negatively (Theorem 8).     

当前建筑施工安全管理工作中存在的问题

对于建筑企业而言，能否实现安全生产直接影响着企业的可持续健康发展。建筑施工业属于事故多发行业，随着建筑施工规模及难度的加大，建筑施工安全生产方面的事故发生率也在不断上升。因此，加强建筑施工安全管理意义重大。     

A cluster-DEE-based strategy to empower protein design

The Medical and Pharmaceutical industries have shown high interest in the precise engineering of protein hormones and enzymes that perform existing functions under a wide range of conditions. Proteins are responsible for the execution of different functions in the cell: catalysis in chemical reactions, transport and storage, regulation and recognition control. Computational Protein Design (CPD) investigates the relationship between 3-D structures of proteins and amino acid sequences and looks for all sequences that will fold into such 3-D structure. Many computational methods and algorithms have been proposed over the last years, but the problem still remains a challenge for Mathematicians, Computer Scientists, Bioinformaticians and Structural Biologists. In this article we present a new method for the protein design problem. Clustering techniques and a Dead-End-Elimination algorithm are combined with a SAT problem representation of the CPD problem in order to design the amino acid sequences. The obtained results illustrate the accuracy of the proposed method, suggesting that integrated Artificial Intelligence techniques are useful tools to solve such an intricate problem.     

Effects of problem characteristics on the online helping behavior of shy individuals

The present research examined how problem characteristics might influence the online helping behavior of shy individuals. Three hundred undergraduates were recruited and assessed using the College Students’ Shyness Scale. According to the scores, 68 high-shy students and 68 low-shy students were selected to participate in simulated experiments designed to determine the influence of the shyness level, the presence of a foreseeable reward, the complexity of the problem, and the urgency of the problem influence online helping behavior. The results showed that (a) High-shy individuals tended to exhibit online helping behavior more for low-complexity problems and high-urgency problems than for high-complexity problems and low-urgency problems. (b) Low-shy individuals always exhibited online helping behavior less for high-complexity problems and when no reward was offered than they did for low-complexity problems and when a reward was offered. (c) High-shy individuals showed online helping behavior more than low-shy individuals did for no-reward, high-complexity problems and high-urgency problems. (d) Participants online had higher shyness scores for showing helping behavior than those offline.     

求解旅行商问题的多样化搜索帝国竞争算法

帝国竞争算法是一种局部搜索能力较强的群智能优化算法，但过度的局部搜索会导致多样性丢失并陷入局部最优。针对这一问题提出基于多样化搜索的帝国竞争算法（MSSICA）。将国家定义为一条可行解，将王国定义成四种特性不同的组合人造解方式。在搜索时使用区块机制保留各自的优势解片段，并对不同的帝国使用差异化的组合人造解方式以搜索不同解空间的有效可行解信息。在陷入局部最优时，使用多样化搜索策略注入均匀分布的可行解替换较无优势的解以提升多样性。实验结果显示，多样化搜索策略可以有效地改善帝国算法的求解多样性，并提升求解质量与稳定性。     

Optimal Location of Unified Power Quality Conditioner in Distribution System for Power Quality Improvement

The increased use of nonlinear loads in distribution system is increasing the distortion in the voltage and current waveforms. Moreover, the distribution systems are inherently unbalanced. This paper presents Cuckoo Optimization Algorithm (COA) based Unified Power Quality Conditioner (UPQC) allocation in three phase unbalanced distribution network. The performance of UPQC is studied in terms of minimization of load disturbance during fault condition in the test systems, % reduction of total harmonic distortion and individual harmonics, minimization of real power loss, decrease in voltage unbalance and increase in cost savings during normal operating condition. The performance of COA is compared with other soft computing techniques to get the better results, i.e., better voltage profile, the optimal location and optimal number of UPQCs.     

Investigating driver injury severity patterns in rollover crashes using support vector machine models

Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is important to investigate the factors that affect rollover crashes and their influence on driver injury severity outcomes. This study employs support vector machine (SVM) models to investigate driver injury severity patterns in rollover crashes based on two-year crash data gathered in New Mexico. The impacts of various explanatory variables are examined in terms of crash and environmental information, vehicle features, and driver demographics and behavior characteristics. A classification and regression tree (CART) model is utilized to identify significant variables and SVM models with polynomial and Gaussian radius basis function (RBF) kernels are used for model performance evaluation. It is shown that the SVM models produce reasonable prediction performance and the polynomial kernel outperforms the Gaussian RBF kernel. Variable impact analysis reveals that factors including comfortable driving environment conditions, driver alcohol or drug involvement, seatbelt use, number of travel lanes, driver demographic features, maximum vehicle damages in crashes, crash time, and crash location are significantly associated with driver incapacitating injuries and fatalities. These findings provide insights for better understanding rollover crash causes and the impacts of various explanatory factors on driver injury severity patterns.     

Tractability frontiers of the partner units configuration problem

The partner units problem (PUP) is an acknowledged hard benchmark problem for the Logic Programming community with various industrial application fields like surveillance, electrical engineering, computer networks or railway safety systems. Although it is already known for a while that the PUP is NP-complete in its general form, complexity for subproblems reflecting the real problems in industrial fields remained widely unclear so far. In this article we provide all missing complexity results. For the subclass of the PUP that belongs to the complexity class P we present a polynomial-time algorithm and give in-depth algorithmic complexity results.