An axiom system for sequence-based specification

This paper establishes an axiomatic foundation and a representation theorem for the rigorous, constructive process, called sequence-based specification, of deriving precise specifications from ordinary (informal) statements of functional requirements. The representation theorem targets a special class of Mealy state machines, and algorithms are presented for converting from the set of sequences that define the specification to the equivalent Mealy machine, and vice versa. Since its inception, sequence-based specification has been effectively used in a variety of real applications, with gains reported in quality and productivity. This paper establishes the mathematical foundation independently of the process itself.     

WBMOAIS: A novel artificial immune system for multiobjective optimization

This study presents a novel weight-based multiobjective artificial immune system (WBMOAIS) based on opt-aiNET, the artificial immune system algorithm for multi-modal optimization. The proposed algorithm follows the elementary structure of opt-aiNET, but has the following distinct characteristics: (1) a randomly weighted sum of multiple objectives is used as a fitness function. The fitness assignment has a much lower computational complexity than that based on Pareto ranking, (2) the individuals of the population are chosen from the memory, which is a set of elite solutions, and a local search procedure is utilized to facilitate the exploitation of the search space, and (3) in addition to the clonal suppression algorithm similar to that used in opt-aiNET, a new truncation algorithm with similar individuals (TASI) is presented in order to eliminate similar individuals in memory and obtain a well-distributed spread of non-dominated solutions. The proposed algorithm, WBMOAIS, is compared with the vector immune algorithm (VIS) and the elitist non-dominated sorting genetic system (NSGA-II) that are representative of the state-of-the-art in multiobjective optimization metaheuristics. Simulation results on seven standard problems (ZDT6, SCH2, DEB, KUR, POL, FON, and VNT) show WBMOAIS outperforms VIS and NSGA-II and can become a valid alternative to standard algorithms for solving multiobjective optimization problems.     

ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION

Artificial immune systems (AIS) are computational systems inspired by the principles and processes of the vertebrate immune system. The AIS‐based algorithms typically exploit the immune system's characteristics of learning and adaptability to solve some complicated problems. Although, several AIS‐based algorithms have proposed to solve multi‐objective optimization problems (MOPs), little focus have been placed on the issues that adaptively use the online discovered solutions. Here, we proposed an adaptive selection scheme and an adaptive ranks clone scheme by the online discovered solutions in different ranks. Accordingly, the dynamic information of the online antibody population is efficiently exploited, which is beneficial to the search process. Furthermore, it has been widely approved that one‐off deletion could not obtain excellent diversity in the final population; therefore, a k‐nearest neighbor list (where k is the number of objectives) is established and maintained to eliminate the solutions in the archive population. The k‐nearest neighbors of each antibody are founded and stored in a list memory. Once an antibody with minimal product of k‐nearest neighbors is deleted, the neighborhood relations of the remaining antibodies in the list memory are updated. Finally, the proposed algorithm is tested on 10 well‐known and frequently used multi‐objective problems and two many‐objective problems with 4, 6, and 8 objectives. Compared with five other state‐of‐the‐art multi‐objective algorithms, namely NSGA‐II, SPEA2, IBEA, HYPE, and NNIA, our method achieves comparable results in terms of convergence, diversity metrics, and computational time.     

高层建筑结构力学模型仿真系统

该文介络了高层建筑结构力学模型仿真的理论基础、关键技术和实现途径,并简述了高层建筑结构多媒体仿真系统MSTB的设计特点。     

基于工作岗位的Linux课程教学体系构建与实践

Linux课程是高职计算机网络类专业的一门专业课程,具有较强的理论性和实践性。如何使学生既能掌握Linux的基本概念和基本技能,又能熟练的应用与实际工作,教学体系的构建至关重要。高职院校是培养应用型人才的基地,必须改革传统的教学体系,构建基于工作岗位的课程教学体系,培养高水平的Linux应用型人才。     

基于SSH架构的高职院校成绩管理系统的分析和设计

本文介绍了当前基于Struts2、Spring、Hibernate框架的高职院校成绩管理系统的分析和设计。     

基于DSP的矿井光纤直放系统的设计

根据煤矿井下巷道狭长、拐点多、分支多的特点,针对井下环境中移动通信系统通话质量差、可靠性低等问题,提出了一种基于DSP的矿井光纤直放系统的设计方案,详细介绍了系统基于DSP的自动监控单元和FIR数字滤波器的设计及语音激活技术在直放系统中的应用。该光纤直放系统解决了井下广域范围移动通信问题,采用DSP对系统实施自动监控,为系统稳定运行提供了可靠保障;数字滤波器的引入、话音激活技术的应用使井下通信系统性能更稳定、话音质量更好、抗干扰性更强,为矿井移动通信的最佳实现奠定基础。     

亲历加拿大高校任教有感

西门菲沙大学(SFU)是加拿大著名的综合类大学,学科门类齐全,办学理念先进。本文通过作者在SFU的教学和科研工作经历,对比了加拿大高校和我国高校在教学、科研、校园文化建设等方面的差别,以期对我国高校教育改革有所启示。