面向工业平稳/非平稳复杂系统的在线故障监测技术

针对复杂系统中关键性能指标（KPI）相关故障检测方法检测精度低的问题,提出基于双层改进潜结构投影（DL-IPLS）的KPI相关故障检测方法. 利用协整分析和主元分析建立底层模型,对非平稳和平稳变量进行特征提取. 将提取的信息进行融合,建立改进潜结构投影的上层模型,根据融合信息对KPI的贡献进行空间分解. 在2个正交子空间中设计统计量,实现KPI相关故障的在线监测. 田纳西-伊斯曼过程和青霉素发酵过程的仿真结果表明,在面向工业平稳和非平稳复杂工业系统检测时,所提方法有效提高了KPI相关故障的检测率,降低了KPI无关故障的误报率.     

IS风险评估方法分类研究*

尝试分别从信息技术演化过程和驱动因素两个方面对信息系统风险评估方法(ISRAM)进行分类.首先选择信息技术和ISRAM发展的时间主线划分ISRAM,然后提取ISRAM设计实现过程中考虑的驱动因素划分ISRAM,并分别给出两种分类方法的半形式化描述;最后,分析目前ISRAM面临的挑战和未来发展趋势.     

A framework for variable content document generation with multiple actors

ContextAdvances in customization have highlighted the need for tools supporting variable content document management and generation in many domains. Current tools allow the generation of highly customized documents that are variable in both content and layout. However, most frameworks are technology-oriented, and their use requires advanced skills in implementation-related tools, which means their use by end users (i.e. document designers) is severely limited.ObjectiveStarting from past and current trends for customized document authoring, our goal is to provide a document generation alternative in which variants are specified at a high level of abstraction and content reuse can be maximized in high variability scenarios.MethodBased on our experience in Document Engineering, we identified areas in the variable content document management and generation field open to further improvement. We first classified the primary sources of variability in document composition processes and then developed a methodology, which we called DPL – based on Software Product Lines principles – to support document generation in high variability scenarios.ResultsIn order to validate the applicability of our methodology we implemented a tool – DPLfw – to carry out DPL processes. After using this in different scenarios, we compared our proposal with other state-of-the-art tools for variable content document management and generation.ConclusionThe DPLfw showed a good capacity for the automatic generation of variable content documents equal to or in some cases surpassing other currently available approaches. To the best of our knowledge, DPLfw is the only framework that combines variable content and document workflow facilities, easing the generation of variable content documents in which multiple actors play different roles.     

Data-driven hair segmentation with isomorphic manifold inference

Hair segmentation is challenging due to the diverse appearance, irregular region boundary and the influence of complex background. To deal with this problem, we propose a novel data-driven method, named Isomorphic Manifold Inference (IMI). The IMI method assumes the coarse probability map and the binary segmentation map as a couple of isomorphic manifolds and tries to learn hair specific priors from manually labeled training images. For an input image, firstly, the method calculates a coarse probability map. Then it exploits regression techniques to obtain the relationship between the coarse probability map of the test image and those of training images. Finally, this relationship, i.e., a coefficient set, is transferred to the binary segmentation maps and a soft segmentation of the test image will be achieved by a linear combination of those binary maps. Further, we employ this soft segmentation as a shape cue and integrate it with color and texture cues into a unified segmentation framework. A better segmentation is achieved by the Graph Cuts optimization. Extensive experiments are conducted to validate effectiveness of the IMI method, compare contributions of different cues and investigate the generalization of IMI method. The results strongly encourage our method.     

基于损益云模型的制造车间重调度决策方法

针对制造车间重调度触发机制问题,建立了制造车间重调度损益函数,揭示了生产车间重调度过程损失及增益的变化规律.引入云理论测度重调度损益的不确定性,使用逆向云算法计算重调度增益云和损失云的数字特征,根据云形态预测重调度损益变化趋势.提出一种基于损益云模型的重调度决策方法以判断是否需要重调度,并利用最佳损益比甄选预调度方案以兼顾生产系统的稳定性和有效性.最后,通过实例验证了该方法的合理性和实用性.     

Incremental inconsistency detection with low memory overhead

Ensuring models’ consistency is a key concern when using a model‐based development approach. Therefore, model inconsistency detection has received significant attention over the last years. To be useful, inconsistency detection has to be sound, efficient, and scalable. Incremental detection is one way to achieve efficiency in the presence of large models. In most of the existing approaches, incrementalization is carried out at the expense of the memory consumption that becomes proportional to the model size and the number of consistency rules. In this paper, we propose a new incremental inconsistency detection approach that only consumes a small and model size‐independent amount of memory. It will therefore scale better to projects using large models and many consistency rules. Copyright © 2012 John Wiley & Sons, Ltd.     

A model driven architecture for the development of smart card software

Smart cards are portable integrated devices that store and process data. Speed, security and portability properties enable smart cards to have a widespread usage in various fields including telecommunication, transportation and the credit card industry. However, the development of smart card applications is a difficult task due to hardware and software constraints. The necessity of the knowledge of both a very low-level communication protocol and a specific hardware causes smart card software development to be a big challenge for the developers. Written codes tend to be error-prone and hard to debug because of the limited memory resources. Hence, in this study, we introduce a model driven architecture which aims to facilitate smart card software development by both providing an easy design of smart card systems and automatic generation of the required smart card software from the system models. Differentiating from the previous work, the study in here contributes to the field by both providing various smart card metamodels in different abstraction layers and defines model-to-model transformations between the instances of these metamodels in order to support the realization of the same system on different smart card platforms. Applicability of the proposed methodology is shown for rapid and efficient application development in two major smart card frameworks: Java Card and ZeitControl Basic Card. Lessons learned during the industrial usage of the architecture are also reported in the paper. Finally, we discuss how the components of the architecture can be integrated in order to provide a domain-specific language for smart card software.     

Java课程教学改革与实践

针对Java课程教学特点及传统教学中存在的问题,对课程教学内容的整合、课堂教学和实践教学的组织、教学方法的综合运用、课程实训方法的选择与实施,以及考核方案的设定等环节进行了教学改革。实践表明,这些改革对提高学生的实践能力和就业竞争能力有一定的帮助。     

“网络营销”课程改革实施方案

"网络营销"课程知识体系须随着互联网应用的出现和普及而逐渐得到完善,为此提出了该课程的教学改革实施方案。网络营销课程的教学始终要以实践应用为主导,在教学过程中采用案例教学、任务驱动、结合竞赛、学科互动、团队合作等方法。考核应采用灵活分配学分比例的办法。最终使得学生能够将课堂上的知识灵活地运用到工作当中。     

Windows Server操作系统课程教学模式改革探索

从Windows Server操作系统课程的教学现状出发,提出了在Windows Server操作系统课程的教学中引入项目驱动教学模式及设计原则,并阐述了此模式下具体的教学环节设计,为Windows Server操作系统课程的教学在计算机网络技术专业技能训练与职业能力培养方面提供了新的视角,具有一定的实用和推广意义。