D-side: A facility and workforce planning group multi-criteria decision support system for Johnson Space Center

“To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers” is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility's alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility's replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach.     

An expert decision support system for network routing: a case study

The paper presents a case study of the development of an expert decision support system which uses simple heuristic methods for fast determination of routes for simultaneous signals in a transmission network of limited capacity. It illustrates how heuristic solutions can be embodied in a model-based DSS and how the standard decision support literature, although intuitively appealing, provides little practical assistance in system construction or classification     

Bayesian inference in disputed authorship: A case study of cognitive errors and a new system for decision support

Bayesian inference provides a formal framework for assessing the odds of hypotheses in light of evidence. This makes Bayesian inference applicable to a wide range of diagnostic challenges in the field of chance discovery, including the problem of disputed authorship that arises in electronic commerce, counter-terrorism and other forensic applications. For example, when two documents are so similar that one is likely to be a hoax written from the other, the question is: Which document is most likely the source and which document is most likely the hoax? Here I review a Bayesian study of disputed authorship performed by a biblical scholar, and I show that the scholar makes critical errors with respect to several issues, namely: Causal Basis, Likelihood Judgment and Conditional Dependency. The scholar’s errors are important because they have a large effect on his conclusions and because similar errors often occur when people, both experts and novices, are faced with the challenges of Bayesian inference. As a practical solution, I introduce a graphical system designed to help prevent the observed errors. I discuss how this decision support system applies more generally to any problem of Bayesian inference, and how it differs from the graphical models of Bayesian Networks.     

东津水电站引水隧洞进口不良地质段施工

东津水电站引水隧洞进口段工程地质条件恶劣，施工干扰大，渡汛工期紧。采用喷锚支护洞脸边坡，洞口明挖３ｍ浇筑钢筋混凝土明拱和Ｌ形护坡墙；洞身段采用新奥法施工，先打通上导洞；进口４０ｍ分段开挖，分段衬砌；进水塔压板混凝土模板采用门字框架钢支撑；排除了施工干扰，防止了洞口滑塌，进口段塌方的恶性事故发生，保证了引水隧洞工程的顺利施工。     

军事地理信息系统的现状与发展

在信息作战条件下，军事地理信息系统（MGIS）作为作战指挥自动化、数字化战场和现代武器系统的战场地理环境平台备受世界各国的重视。美国投入了大量人力、物力和财力先后研制并使用了地形分析系统等一系列应用系统，目前正着手研制地理影像情报综合管理系统（TPED）和地理影像与地理空间信息系统。我国的MGIS起步较晚，但发展很快，已成功地研制出了第一个具有自主版权的MGIS工具软件。该软件采用层次化体系结构和面向对象的设计方法，具有功能齐全、结构紧密、安全性好等特点。文章在分析国内外MGIS的基础上，着重介绍了军事地理信息系统软件的研制特点，并对军事地理信息系统进一步发展要解决的若干问题进行了探讨。     

Negotiation support systems: roots, progress and needs

Abstract. This paper identifies game theories and social behavior science as important roots for negotiation support systems (NSS) research. As these are not typically cited in the NSS literature, summary reviews of them are provided with indications of their relevance to NSS study. On the other hand, neither offers a sufficiently general-purpose formal model of negotiation that could serve as a backbone for NSS research. A survey of that research is provided, indicating that prugress to date has been somewhat eclectic and devoid of such a model. Our central contention is that a theoretical foundation for NSS study is much needed. Desirable characteristics of a suitable negotiation model are identified as guidance for future research that will aim to devise (and subsequently apply and test) such a model.     

Tree-based partitioning of date for association rule mining

The most computationally demanding aspect of Association Rule Mining is the identification and counting of support of the frequent sets of items that occur together sufficiently often to be the basis of potentially interesting rules. The task increases in difficulty with the scale of the data and also with its density. The greatest challenge is posed by data that is too large to be contained in primary memory, especially when high data density and/or low support thresholds give rise to very large numbers of candidates that must be counted. In this paper, we consider strategies for partitioning the data to deal effectively with such cases. We describe a partitioning approach which organises the data into tree structures that can be processed independently. We present experimental results that show the method scales well for increasing dimensions of data and performs significantly better than alternatives, especially when dealing with dense data and low support thresholds. Shakil Ahmed received a first class BSc (Hons) degree from Dhaka University, Bangladesh, in 1990; and an MSc (first class), also Dhaka University, in 1992. He received his PhD from The University of Liverpool, UK, in 2005. From 2000 onwards he is a member of the Data Mining Group at the Department of Computer Science of the University of Liverpool, UK. His research interests include data mining, Association Rule Mining and pattern recognition. Frans Coenen has been working in the field of Data Mining for many years and has written widely on the subject. He received his PhD from Liverpool Polytechnic in 1989, after which he took up a post as a RA within the Department of Computer Science at the University of Liverpool. In 1997, he took up a lecturing post within the same department. His current Data Mining research interests include Association rule Mining, Classification algorithms and text mining. He is on the programme committee for ICDM'05 and was the chair for the UK KDD symposium (UKKDD'05). Paul Leng is professor of e-Learning at the University of Liverpool and director of the e-Learning Unit, which is responsible for overseeing the University's online degree programmes, leading to degrees of MSc in IT and MBA. Along with e-Learning, his main research interests are in Data Mining, especially in methods of discovering Association Rules. In collaboration with Frans Coenen, he has developed efficient new algorithms for finding frequent sets and is exploring applications in text mining and classification.     

基于MPC850 VxWorks系统的BSP设计

首先介绍嵌入式系统VxWorks及其启动过程;分析了基于MPC 850最小系统的硬件和BSP的执行流程;重点研究了MPC850BSP的设计与应用程序加载,包括其硬件驱动程序的设计、应用程序加载、建立调试环境和target server的配置等;基于MPC850系统的Vxworks BSP调试平台的实现,对Vxworks上层应用软件和底层硬件驱动的并行开发有着很重要的意义。     

最小支持度在教学质量评价系统中的数据挖掘应用

以当前的高职高专院校教育教学为平台,研究分析最小支持度关联规则挖掘技术与教学质量评价相结合的问题,针对教学质量评价结果中的盲目性、不易把握等问题,提出利用最小支持度来分析质量评价体系,获取以影响因素为条件,以评价分析为结论的关联规则来解决目前教学质量评价中的不合理性,使教学质量评价公平、公正、合理、高效,并给教学管理人员提供决策分析资料。     

Transformation of semantic knowledge into simulation-based decision support

Simulation is capable to cope with the uncertain and dynamic nature of industrial value chains. However, in-depth system expertise is inevitable for mapping objects and constraints from the real world to a virtual model. This knowledge-intensity leads to long development times of respective projects, which contradicts the need for timely decision support. Since more and more companies use industrial knowledge graphs and ontologies to foster their knowledge management, this paper proposes a framework on how to efficiently derive a simulation model from such semantic knowledge bases. As part of the approach, a novel Simulation Ontology provides a standardized meta-model for hybrid simulations. Its instantiation enables the user to come up with a fully parameterized formal simulation model. Newly developed Mapping Rules facilitate this process by providing guidance on how to turn knowledge from existing ontologies, which describe the system to be simulated, into instances of the Simulation Ontology. The framework is completed by a parsing procedure for an automated transformation of this conceptual model into an executable one. This novel modeling approach makes model development more efficient by reducing its complexity. It is validated in a use case implementation from semiconductor manufacturing, where cross-domain knowledge was required in order to model and simulate the impacts of the COVID-19 pandemic on a global supply chain network.