Analytical network process for software selection in product development: A case study

Application of software for manufacturing processes is one of the resolutions many enterprises have resorted to in the 21st century. This has been a result of increased complexity of products, globalization, rapid changes in technology and so on. The idea was that application of software especially for product development would increase the competitive advantage of industry nevertheless the irony has been that most of the investment in software has not achieved the expected results. We carry out a case study to introduce a methodology, the analytical network process as a multiattribute strategic decision making approach to help in the selection of appropriate software to suit the product development process of a particular product.     

Reliable Ad Hoc Routing Based on Mobility Prediction

Reliability is a very important issue in Mobile Ad hoc NETworks (MANETs). Shortest paths are usually used to route packets in MANETs. However, a shortest path may fail quickly, because some of the wireless links along a shortest path may be broken shortly after the path is established due to mobility of mobile nodes. Rediscovering routes may result in substantial data loss and message exchange overhead. In this paper, we study reliable ad hoc routing in the urban environment. Specifically, we formulate and study two optimization problems. In the minimum Cost Duration-bounded Path (CDP) routing problem, we seek a minimum cost source to destination path with duration no less than a given threshold. In the maximum Duration Cost-bounded Path (DCP) routing problem, we seek a maximum duration source to destination path with cost no greater than a given threshold. We use a waypoint graph to model the working area of a MANET and present an offline algorithm to compute a duration prediction table for the given waypoint graph. An entry in the duration prediction table contains the guaranteed worst-case duration of the corresponding wireless link. We then present an efficient algorithm which computes a minimum cost duration-bounded path, using the information provided in the duration prediction table. We also present a heuristic algorithm for the DCP routing problem. In addition, we show that the proposed prediction and routing schemes can be easily applied for designing reliable ad hoc routing protocols. Simulation results show that our mobility prediction based routing algorithms lead to higher network throughput and longer average path duration, compared with the shortest path routing. This research was supported in part by ARO grant W911NF-04-1-0385 and NSF grant CCF-0431167. The information reported here does not reflect the position or the policy of the federal government.     

产业集群、网络关系与企业竞争力的关系研究

本文以珠三角地区产业群聚内的企业为研究对象,采用随机抽样的调查方法获取所需的,可靠的研究数据,探讨产业集群内企业网络关系的类型、联结对象及网络地位对其竞争力的影响.研究表明:产业集群并不直接影响企业竞争力,而是一定程度上通过作用于企业的网络关系最终影响企业的竞争力.     

时间贝叶斯网络及其概率推理

针对贝叶斯网络应用中出现的循环和动态问题,研究贝叶斯网络的时间扩展.给出了时间贝叶斯网络的定义;探讨了时间贝叶斯网络中环的存在合理性判断问题;给出了时间贝叶斯网络的概率推理算法,应用示例说明了方法的可行性.     

基于时差分析的资源均衡问题探究

本文在已有时差概念分析的基础上,提出了三个新时差概念,给出了同一工序不同时差关系,提出了标值算法,算出了不同工序时差传递量。对资源均衡优化问题的初始方案进行研究,给出了随机时标网络图的绘制方式,使网络技术的应用更具灵活性和实用性。在时差传递性的基础上,进一步对有资源限制的资源均衡优化方案进行研究,提出了基于赋值算法的优化调整方式,最后通过算例对该调整方式进行了验证。     

网络舆情扰动下房地产投资者“追涨杀跌”行为扩散研究

一旦房地产投资者“追涨杀跌”行为发生大范围扩散,将诱发房地产市场的价格严重偏离甚至动荡。本文从传播学与行为金融学交叉视角,基于复杂网络理论构建了房地产投资者“追涨杀跌”行为的网络扩散模型,进而仿真分析了网络舆情与投资者行为偏好交互作用下房地产投资者“追涨杀跌”行为扩散的演化特征。研究表明：房地产投资者越偏向于随机建立关联,“追涨杀跌”行为越可能快速扩散;网络舆情因素在“追涨杀跌”行为扩散过程中发挥主导作用,同时对投资者行为偏好因素发挥较强的“强化效应”或“抑制效应”;当媒体权威性足够高或网民情绪足够乐观时,通过综合调节网络舆情和投资者行为偏好因素能够有效实现预防和限制“追涨杀跌”行为扩散的目的。     

粗集与神经网络相结合的股票价格预测模型

粗集和神经网络结合反映了人类智能的定性和定量、清晰和隐含、串行和并行相互交叉混合的常规思维机理。本文建立这样一种混合杂交模型用于股票价格波动趋势的预测,通过粗集对数据的二维约简预处理消除了样本中的噪声和冗余,在提高神经网络预测精度的同时降低了学习负担。为了获得最优的预测精度,本文还利用遗传算法进行属性离散化和网络学习。通过对上证综指的实证研究表明,这种混合杂交模型的性能明显优于BP和GA神经网络模型。     

伟大建党精神在引领时代新人中的价值探析

伟大建党精神充分体现了中国共产党的理想信念、初心使命、斗争精神和为民情怀,在中国革命、建设、改革和发展的不同历史时期形成了不同的精神品格。在建设社会主义现代化强国,实现中华民族伟大复兴的征程中,继承优良传统,赓续红色血脉,彰显中国共产党的精神品格和精神标识,培养立大志、明大德、成大才、担大任的时代新人不仅是党和中国特色社会主义事业后继有人、蓬勃发展的重要保证,也是培育有理想、敢担当、能吃苦、肯奋斗的新时代好青年的必然要求。     

新时代中国式现代化话语体系构建的三重逻辑

中国式现代化理论是中国特色社会主义理论的最新发展。建构中国式现代化话语体系是新时代发展中国式现代化理论的重要任务。从话语价值的维度来说,中国式现代化话语体系建构有利于驳斥西方社会对中国式现代化的话语诘难提供话语支持,为塑造中国式现代化的优良形象提供话语助力,为推进中华民族伟大复兴提供话语援助。中国式现代化话语价值强调了举旗定向功能。从话语历史的维度来说,中国式现代化话语经历了革命、建设、改革和新时代等不同历史阶段的语境,中国式现代化话语历史彰显了基因凝定功能。从话语实践的维度来说,中国式现代化话语体系构建凸显摸着石头过河的群众实践和顶层设计的政党实践的有效互动,中国式现代化话语实践体现了换羽新生功能。中国式现代化话语体系的三重维度构建有助于增强中国特色社会现代化建设的话语自信,进而推动社会主义现代化强国建设。     

Understanding the epidemiology of foreign body injuries in children using a data-driven Bayesian network

Bayesian networks (BNs) are probabilistic expert systems which have emerged over the last few decades as a powerful data mining technique. Also, BNs have become especially popular in biomedical applications where they have been used for diagnosing diseases and studying complex cellular networks, among many other applications. In this study, we built a BN in a fully automated way in order to analyse data regarding injuries due to the inhalation, ingestion and aspiration of foreign bodies (FBs) in children. Then, a sensitivity analysis was carried out to characterize the uncertainty associated with the model. While other studies focused on characteristics such as shape, consistency and dimensions of the FBs which caused injuries, we propose an integrated environment which makes the relationships among the factors underlying the problem clear. The advantage of this approach is that it gives a picture of the influence of critical factors on the injury severity and allows for the comparison of the effect of different FB characteristics (volume, FB type, shape and consistency) and children's features (age and gender) on the risk of experiencing a hospitalization. The rates it consents to calculate provide a more rational basis for promoting care-givers’ education of the most influential risk factors regarding the adverse outcomes.