Podcasting in education: Are students as ready and eager as we think they are?

Instructors in higher education are disseminating instructional content via podcasting, as many rally behind the technology’s potential benefits. Others have expressed concern about the risks of deleterious effects that might accompany the adoption of podcasting, such as lower class attendance. Yet, relatively few studies have investigated students’ perceptions of podcasting for educational purposes, especially in relation to different podcasting forms: repetitive and supplemental. The present study explored students’ readiness and attitudes towards these two forms of podcasting to provide fundamental information for future researchers and educators. The results indicated that students may not be as ready or eager to use podcasting for repetitive or supplemental educational purposes as much as we think they are, but they could be persuaded.     

Stability and synchronization for Markovian jump neural networks with partly unknown transition probabilities

This paper addresses the problems of stability and synchronization for a class of Markovian jump neural networks with partly unknown transition probabilities. We first study the stability analysis problem for a single neural network and present a sufficient condition guaranteeing the mean square asymptotic stability. Then based on the Lyapunov functional method and the Kronecker product technique, the chaos synchronization problem of an array of coupled networks is considered. Both the stability and the synchronization conditions are delay-dependent, which are expressed in terms of linear matrix inequalities. The effectiveness of the developed methods is shown by simulation examples.     

Exploring the relationship between Internet ethics in university students and the big five model of personality

The widespread use of the Internet and the convenient mechanism it provides, such as easy access, easy downloads, and easy copy and paste functions have made many types of unethical behaviors easier, particularly those involving students in academic settings. Among the issues in ethics within the academic environment that can be triggered by the Internet are fraudulence, plagiarism, falsification, delinquency, unauthorized help, and facility misuse. Given these issues, the study seeks to investigate the extent to which students at a public university in Malaysia engage in such unethical behavior and their relationship with the big five personality model. This study was conducted using a survey method of 252 students in three different academic faculties. The results of factor analyses confirm and refine the reliability of the scales for both big five personality variables and unethical Internet behaviors as conceptualized through Internet triggered academic dishonesty (ITADS). The findings indicate that personality traits such as (1) agreeableness, (2) conscientiousness and (3) emotional stability are significantly and negatively correlated with unethical Internet behavior in university students. Significant differences in facility misuse are also observed between the three academic faculties investigated. This research should provide significant contributions to educators in designing the computer ethics curriculum and in allowing for educational institutions as well as other organizations in developing relevant policies and guidelines on matters pertaining to academic conduct, utilization of computers and Internet, and recruitment exercises.     

基于蚁群优化的DBN转移网络结构学习算法

针对动态贝叶斯转移网络的特点,以I-ACO-B为基础,提出基于蚁群优化的分步构建转移网络的结构学习算法ACO-DBN-2S。算法将转移网络的结构学习分为时间片之间和时间片内2个步骤进行,通过改进隔代优化策略,减少无效优化次数。标准数据集下的大量实验结果证明,该算法能更有效地处理大规模数据,学习精度和速度有较大改进。     

基于改进基因表达式程序设计的股票指数预测

介绍基因表达式程序设计方法的基本原理,针对股票指数分析与预测问题,在经典的GEP算法基础上,提出一种基于动态变异算子的改进的GEP算法——IGEP算法,动态变异算子随着进化代数和染色体所含基因数目不同而变化,从而加快了GEP的收敛速度和精确度,对算法进行了复杂度和收敛性分析。设计一种基于IGEP的股票指数分析与预测算法,数值实验结果表明,该算法优于经典GEP算法,具有较广泛的通用性。     

基于动态默认转移的深度包检测算法

由于基于确定性有限自动机（DFA）的多模式匹配算法对内存的需求比较大,因此需要对DFA进行优化,以减少其对内存的需求量。算法通过用动态默认转移来替代DFA的failto转移,将DFA中大量的failto转移删掉,从而达到优化DFA的目的。实验结果证明,该算法能有效地优化DFA对内存的需求。     

#BIS-hardness for 2-spin systems on bipartite bounded degree graphs in the tree non-uniqueness region

Counting independent sets on bipartite graphs (#BIS) is considered a canonical counting problem of intermediate approximation complexity. It is conjectured that #BIS neither has an FPRAS nor is as hard as #Sat to approximate. We study #BIS in the general framework of two-state spin systems on bipartite graphs. We define two notions, nearly-independent phase-correlated spins and unary symmetry breaking. We prove that it is #BIS-hard to approximate the partition function of any 2-spin system on bipartite graphs supporting these two notions. Consequently, we classify the complexity of approximating the partition function of antiferromagnetic 2-spin systems on bounded-degree bipartite graphs.     

高职电子技术课程的兴趣教学法

高职院校学生学习基础相对较差,对于传统的课堂教育难以适应,提出在电子技术教学中实施兴趣教学法,提高学生主动学习的积极性,也有助于提高教学质量。电子技术课实践性强,几乎每堂课都会涉及到实验,这样可以长期在实验室上课或者在教室做演示实验,每次课前教师列一个清单让学生提前到实验室准备好实验器材,学生在准备器材的过程中就会带着疑问：这是做什么用的呢？学生有了疑问就会有学习的好奇心,进而也就激发了对该课程的学习兴趣。     

Suitability evaluation of urban construction land based on geo-environmental factors of Hangzhou, China

Suitability evaluation of urban construction land based on geo-environmental factors is the process of determining the fitness of a given tract of land for construction. This process involves a consideration of the geomorphology, geology, engineering geology, geological hazards, and other geological factors and is the basis of urban construction land planning and management. With the support of Geographic Information Systems (GIS), grid analysis, and geo-spatial analysis techniques, four factor groups comprising nine separate subfactors of geo-environmental attributes were selected to be used in the evaluation of the suitability level for construction land in Hangzhou. This was based on K-means clustering and back-propagation (BP) neural network methods due to their advantages in fast computing, unique adaptive capacity, and self-organization. Simultaneously, the evaluation results based on K-means clustering and BP neural network were compared and analyzed, and the accuracy evaluation was set. The results showed that the geo-environmental suitability evaluation results of construction land based on K-means clustering and BP neural network were similar in terms of the distribution and scale of construction land suitability level. At the same time, the results of the two evaluation methods were consistent with the variability in suitability level, engineering geology, and hydrogeology of Hangzhou. The results also showed that the real advantage of the methods proposed in this paper lies in their capacity to streamline the mapping process and to ensure that the results are consistent throughout. The suitability level of the urban construction land based on the geo-environment in Hangzhou was divided into four construction sites: land for building super high-rise and high-rise buildings, land for building multistorey buildings, land for low-rise buildings, and nonbuilding land. The results of the suitability evaluation for each category will provide a scientific basis for decision-making in urban development in Hangzhou.     

Mathematics for Architecture: Some European Experiences

Orietta Pedemonte studies how mathematics in taught in faculties or schools of architecture in Belgium, Portugal, France, Switzerland and Spain, comparing course organizations, subjects offered and entrance requirements. Which and how much mathematics for architecture? What kind of teaching? Is it better to have information on many aspects, or a deeper insight into only a few? Is it better to privilege a historical-philosophical overview, or to focus aspects of application that are current today? These are some of the questions that are raised by whoever deals with teaching mathematics in a faculty or school of architecture.