A pattern recognition based intelligent search method and?two?assignment problem case?studies

Numerous papers based on various search methods across a wide variety of applications have appeared in the literature over recent years. Most of these methods apply the following same approach to address the problems at hand: at each iteration of the search, they first apply their search methods to generate new solutions, then they calculate the objective values (or costs) by taking some constraints into account, and finally they use some strategies to determine the acceptance or rejection of these solutions based upon the calculated objective values. However, the premise of this paper is that calculating the exact objective value of every resulting solution is not a must, particularly for highly constrained problems where such a calculation is costly and the feasible regions are small and disconnected. Furthermore, we believe that for newly-generated solutions, evaluating the quality purely by their objective values is sometimes not the most efficient approach. In many combinatorial problems, there are poor-cost solutions where possibly just one component is misplaced and all others work well. Although these poor-cost solutions can be the intermediate states towards the search of a high quality solution, any cost-oriented criteria for solution acceptance would deem them as inferior and consequently probably suggest a rejection. To address the above issues, we propose a pattern recognition-based framework with the target of designing more intelligent and more flexible search systems. The role of pattern recognition is to classify the quality of resulting solutions, based on the solution structure rather than the solution cost. Hence, the general contributions of this work are in the line of “insights” and recommendations. Two real-world cases of the assignment problem, i.e. the hospital personnel scheduling and educational timetabling, are used as the case studies. For each case, we apply neural networks as the tool for pattern recognition. In addition, we present our theoretical and experimental results in terms of runtime speedup.     

A compact genetic algorithm for the network coding based resource minimization problem

In network coding based data transmission, intermediate nodes in the network are allowed to perform mathematical operations to recombine (code) data packets received from different incoming links. Such coding operations incur additional computational overhead and consume public resources such as buffering and computational resource within the network. Therefore, the amount of coding operations is expected to be minimized so that more public resources are left for other network applications.     

跨国建设投资项目协同管理的多元策略

随着上海经济的迅猛发展,建设工程项目市场全球化的趋势愈演愈烈,在沪投资的国际工程项目越来越多。这些外资投资项目在为我国建设企业引入新的管理理念和技术的同时,也与我国传统的建设项目管理模式发生着碰撞。为此,亟待根据我国建设企业项目管理现状,构建适应跨国投资项目良性运作的协同管理体系。     

“云安全”检测技术安全性分析

“云安全”检测已成为病毒查杀领域发展的新趋势,为对其在病毒检测过程中的安全性有进一步了解,研究了“云安全”检测体系结构以及主流“云安全”策略,针对某“云安全”检测软件的文件样本提取方式和网络传输数据的特点,分析了检测流程中存在的安全隐患,基于这些安全隐患设计并实现了“云安全”检测的规避方案,针对规避方案提出了防护建议.实验结果表明,“云安全”检测在实际应用过程中仍可能被恶意程序绕过.     

油液监测系统的多传感器信息融合处理技术研究

研究了基于多传感器信息融合技术的油液监测智能系统模型,分析了该模型各系统模块的功能,引入系统模型中信息融合的方法,提出信息融合技术在油液监测应用中的模型研究方法。以某工厂产品使用的柴油为实例,验证信息融合技术的有效性。实验结果表明:该信息融合处理技术对油液监测是有效的,具有较高的实用价值。     

Internal and contextual factors, knowledge processes and performance: From the Chinese provider’s perspective

This paper explores the influences of two internal factors, i.e. supplier team’s IT-based skills and communication with client’s team, and two contextual factors, i.e. supplier team’s understanding of client’s culture and collaboration with client’s team, on knowledge processes and performance in global sourcing of IT services from the Chinese provider’s perspective. Knowledge processes are characterized by knowledge sharing, knowledge-based coordination and expertise management, and performance is measured by product success and personal satisfaction. Data have been collected in 13 companies in Xi’an Software Park, with 26 in-depth, semi-structured interviews held with top and middle managers, and 200 structured questionnaires distributed to knowledge workers who are involved in global sourcing projects. The results indicate that supplier team’s IT-based skills, communication with client’s team, cultural understanding of client’s culture and collaboration with client’s team are positively associated with knowledge process and performance. Also, knowledge sharing, knowledge-based coordination and expertise management are found to be crucial for those influential factors to function positively and contribute to the performance. The findings of this study suggest that the effects of key factors on knowledge processes and performance in global sourcing of IT services appear to transcend the social and cultural differences; however, contextual factors seem to have more significant influences on knowledge processes and performance in global sourcing of IT services.     

基于仿真的物料平衡系统测评

为了更好地测评石化企业生产执行系统(MES)软件的物料平衡模块数据校正功能,提出了一种基于仿真的数据校正结果的测评方法。该方法通过搭建仿真模型产生全厂物流过程的真值,并应用动态数据驱动方法进行模型参数的修正,即通过向仿真真值添加测量误差生成误差可配置的测量值,模拟现场真实的测量网络;应用物料平衡系统及其内嵌数据协调算法对测量值进行数据校正得到校正值,将校正值分别与仿真真值、测量值进行对比,定量评估数据协调算法的性能。相对于仅比较校正值和测量值的原评定方法,该方法能更加精确、全面地测评数据校正算法的效果,并在某石化企业的案例中得到验证。     

一种基于社会网络的SIP垃圾即时消息的检测方法

根据SIP即时消息通信的行为特征,建立用户的社会网络关系图;提出一种IMNTA(IM network topology arithmetic)算法,将具有双向通信关系的用户归并为一类,建立SIP垃圾即时消息识别模型.通过提取待检测的即时消息的特征属性,判定是否SIP垃圾即时消息,并对SIP垃圾即时消息识别模型进行自动更新.实验结果表明,本方法只需要少量信息就可以快速、准确地对SIP垃圾即时消息进行检测.     

基于改进的BOCR和FANP模型的ERP系统选择方法*

ERP系统能够明显影响企业未来的竞争力和企业绩效。ERP系统的选择是一个典型的多因素决策问题。基于BOCR理论建立了ERP系统选择的评价指标体系,考虑了准则/指标之间的相互影响和反馈关系。由于评价过程中信息的不精确和模糊性,用三角模糊数表示专家或决策者的偏好意见,根据模糊优先规划方法计算三角模糊判断矩阵的局部权重。依据准则/指标之间的网络结构关系建立了未加权超矩阵,计算了收敛后的极限超矩阵,以得出各指标的综合权重。最后以案例说明如何应用提出的方法。