A TQM-Based Approach to QoS Management

Total Quality Management (TQM) is one of the most interesting and effective concepts of management. Although, as of today, it has been extensively applied to manufacturing and industrial sectors, TQM principles have not received wide acceptance in the area of Telecommunications Network and Service Management. Application of those principles in Telecommunications can be facilitated by employing pertinent techniques and tools. This paper focuses on aspects of the performance management of Telecommunications Networks and Services. As basic quality control mechanisms, two versions of a Dynamic Scaling Service (DSS) are used to regulate the end-user perceived quality: a Crisp DSS and a Fuzzy Logic DSS. A quality-oriented user behavior model is built and a comparative study between the different quality control schemes is presented. Concluding, the paper delineates the scope of TQM with respect to QoS management in telecommunications.     

A new approach to water quality modelling and environmental decision support systems

The concepts and technology of environmental decision support systems (EDSS) have developed considerably over recent decades, although core concepts such as flexibility and adaptability within a changing decision environment remain paramount. Much recent EDSS theory has focussed on model integration and re-use in decision support system (DSS) tools and for design and construction of ‘DSS generators’. Many current specific DSS have architectures, tools, models and operational characteristics that are either fixed or difficult to change in the face of changing management needs. This paper reports on development and deployment of an EDSS that encompasses a new approach to DSS tools, generators and specific DSS applications. The system, named E2, is built upon a conceptualisation of terrestrial and aquatic environmental systems that has resulted in a robust and flexible system architecture. The architecture provides a set of base classes to represent fundamental concepts, and which can be instantiated and combined to form DSS generators of varying complexity. A DSS generator is described within which system users are able to select and link models, data, analysis tools and reporting tools to create specific DSS for particular problems, and for which new models and tools can be created and, through software reflection (introspection), discovered to provide expanded capability where required. This system offers a new approach within which environmental systems can be described in the form of specific DSS at a scale and level of complexity suited to the problems and needs of decision makers.     

A financial resource allocation model for regional water systems

The public water supply sector is facing significant external pressures for change from decreasing water resource availability, stricter water quality regulations, decreasing federal subsidies, increasing public scrutiny, decreasing financial health, and increasing infrastructure replacement costs. These forces necessitate greater accountability by community water systems (CWS) to their stakeholders. This paper presents a method for comparative efficiency analysis to improve the accountability of CWS to their stakeholders while maintaining the level of service. The method is achieved through three objectives, namely: (1) to construct standard efficiency metric parameters based on the techniques of data envelopment analysis; (2) to incorporate these uniform efficiency metric parameters into a transparent decision support system (DSS) based on the standard linear programming resource allocation problem; and (3) to utilize the DSS to determine the efficient allocation of limited budgetary resources among CWS operating as a regional water system (RWS). The paper is a significant departure, in three ways, from the current planning and management approach, which treats CWS as independent entities. First, it provides an open and transparent method for planning and management of CWS; second, it provides a uniform and consistent method for evaluating relative efficiencies across the CWS. Third, the DSS facilitates comparative efficiency analysis across the RWS, and guides financial allocation decisions among CWS operating as a RWS.     

TOTAL QUALITY MANAGEMENT: A GDSS APPROACH

Teams are a major factor in total quality management (TQM), so any technology that improves team performance facilitates the TQM process. This article describes how group decision support systems (GDSSs) can be used to increase team productivity and effectiveness within the TQM framework.     

Developing and assessing an intelligent forex rolling forecasting and trading decision support system for online e‐service

An effective foreign exchange (forex) trading decision is usually dependent on effective forex forecasting. In this study, an intelligent system framework integrating forex forecasting and trading decision is first proposed. Based on this framework, an advanced intelligent decision support system (DSS) incorporating a back‐propagation neural network (BPNN)‐based forex forecasting subsystem and Web‐based forex trading decision support subsystem is developed, which has been used to predict the directional change of daily forex rates and provide intelligent online decision support for financial institutions and individual investors. This article describes the forex forecasting and trading decision method, the system architecture, main functions, and operation of the developed DSS system. A comparative study is conducted between our developed system and others commonly used in order to assess the overall performance of the developed system. The assessment results show that our developed DSS outperforms some commonly used forex forecasting and trading decision systems and can provide intelligent e‐service for forex traders to make useful trading decisions in the forex market. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 475–499, 2007.     

A decision support system for usability evaluation of web-based information systems

In this study, a decision support system (DSS) for usability assessment and design of web-based information systems (WIS) is proposed. It employs three machine learning methods (support vector machines, neural networks, and decision trees) and a statistical technique (multiple linear regression) to reveal the underlying relationships between the overall WIS usability and its determinative factors. A sensitivity analysis on the predictive models is performed and a new metric, criticality index, is devised to identify the importance ranking of the determinative factors. Checklist items with the highest and the lowest contribution to the usability performance of the WIS are specified by means of the criticality index. The most important usability problems for the WIS are determined with the help of a pseudo-Pareto analysis. A case study through a student information system at Fatih University is carried out to validate the proposed DSS. The proposed DSS can be used to decide which usability problems to focus on so as to improve the usability and quality of WIS.     

An economic design for optimum maintenance float policy

This paper introduces a cost model to solve for optimum maintenance float policy. The model is based on an iterative solution developed for closed queuing maintenance networks. The use of this approach makes it possible to solve and obtain closed form solutions to maintenance float problems when all the centers in the network are exponentially distributed. A computer program is developed for the cost model. The program searches through a three-dimensional cost surface for the optimum solution. On reaching the optimum, the optimum policy as well as the maintenance float performance measures are generated. The computer program offers a decision support mechanism for the maintenance manager by making maintenance float information readily available, providing a more expedient alternative to simulation.     

An intelligent decision support system for forecasting and optimization of complex personnel attributes in a large bank

Developing decision support system (DSS) can overcome the issues with personnel attributes and specifications. Personnel specifications have greatest impact on total efficiency. They can enhance total efficiency of critical personnel attributes. This study presents an intelligent integrated decision support system (DSS) for forecasting and optimization of complex personnel efficiency. DSS assesses the impact of personnel efficiency by data envelopment analysis (DEA), artificial neural network (ANN), rough set theory (RST), and K-Means clustering algorithm. DEA has two roles in this study. It provides data to ANN and finally it selects the best reduct through ANN results. Reduct is described as a minimum subset of features, completely discriminating all objects in a data set. The reduct selection is achieved by RST. ANN has two roles in the integrated algorithm. ANN results are basis for selecting the best reduct and it is used for forecasting total efficiency. Finally, K-Means algorithm is used to develop the DSS. A procedure is proposed to develop the DSS with stated tools and completed rule base. The DSS could help managers to forecast and optimize efficiencies by selected attributes and grouping inferred efficiency. Also, it is an ideal tool for careful forecasting and planning. The proposed DSS is applied to an actual banking system and its superiorities and advantages are discussed.     

Assessing the impacts of South-to-North Water Transfer Project with decision support systems

The South to North Water Transfer Project is one of the four largest trans-century projects in China, which is expected to be completed by 2008. The project seeks to promote Northern China's economic growth by relaxing water constraints in a region now facing severe water shortage. In this paper, a decision support system (DSS) for assessing the social–economic impact of China's South-to-North (S2N) Water Transfer project is presented. The DSS provides decision support through simulation with an embedded water computable general equilibrium model (WCGE). The system is able to perform qualitative analysis on regional water resource vulnerability with mathematical modeling. In addition, the system is also able to examine a region's water demand–supply balance dynamics through forecasting with the WCGE model on the basis of various scenarios for the time horizon up to the year 2020. The what-if analysis performed by the DSS shows that the incremental water supply from the project helps the recipient region to catch up with the development pace of the country as a whole.     

A web based DSS for the management of floods and wildfires (FLIRE) in urban and periurban areas

The FLIRE DSS is a web-based Decision Support System for the combined forest and flood risk management and planning. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of web based DSS with no need of local complex infrastructure and maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in that way to plan its efficient elimination. Also, they can implement “what-if” scenarios for areas prone to fire and thus develop plans for forest fire management. Flood services include flood maps and flood-related warnings; these become available to relevant authorities for visualization and further analysis on a daily basis. Real time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real time and a high resolution weather forecast grid support flood modeling and “what-if” scenarios for the fire modeling. The innovations of the FLIRE DSS are the use of common Earth Observation (EO) data as the backbone of the system to produce data for the support of fire and flood models, the common use of weather related information, the distributed architecture of the system and the web-based access of it with no need for installation of dedicated software. All these can be accessed by all means of computer sources like PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility.     

一个新的支持多学科模型集成的流域决策支持系统框架研究

传统流域决策支持系统往往使用一两个模型来解决某些特定目标,限于系统结构而不能综合考虑多领域问题。提出了一种新的支持多学科模型集成的流域决策支持系统原型,在一个系统中实现多种学科模型的跨时空尺度集成,为流域综合管理提供全面科学支持。系统采用开放式多学科模型管理方法,其脚本扩展机制使得系统可以容纳几乎所有模型,模型因子方法使得形式多样的科学模型模拟结果可以应用到决策方法中,使系统在多学科模型支持下提供科学合理的决策方案。情景驱动的决策流程、向导式交互界面及GIS等图形化工具支持使得系统用户界面友好\,易用性强。     

Clinical decision support system in medical knowledge literature review

The current study involved methodology and content analyses of abstracts of 30 clinical decision support system (CDSS) related studies with high impact factors. The main aim of the current work was to identify the performance and efficiency of CDSS, and enhance the understanding of CDSS for a better health management among the physicians and the patients. To add structure to the current study, major research areas were categorized based on a multidimensional unfolding analysis. In this regard, eight studies were conducted based on theoretical research, ten studies were related to the system and performance of CDSS, and 12 studies verified the efficacy through analysis and evaluation of CDSS. The results indicated that the above-mentioned studies on improvement in systematic performance. Then, based on the improvement, effectively used evaluations were conducted comparably. Moreover, 14 studies analyzed patients’ data and assessed decision support system (DSS). The related findings denoted that DSS has been mainly used for patient management and a large number of studies have verified its effectiveness, using several data to ensure its accuracy and reliability. In addition, the analyzed results of the abstracts and the titles were compared to find whether the titles of the literature articles reveal their content. Using these methodological studies, the academic outlook of medical informatics could be forecasted and the academic quality could be improved by resolving the problems, arising out of system development and realization processes. Such problems can be solved through analyses and interpretation of multilateral parameters, such as the trend in academic development, research direction, topics and methods.     

Model management system for IRT-based test construction decision support system

Decision support system (DSS) has become widespread for some specific domains in recent years. However, DSS for IRT-based (item response theory) test construction has not yet been developed. This domain basically imposes a semi-structured or unstructured decision and, therefore, involves a very complex modeling process. This study develops a model management system (MMS) architecture to assist a non-expert user in manipulating test construction process efficiently and effectively. This architecture consists of four components: problem analysis, model type selection, model formulation and solver. The model type selection subsystem is further organized into three levels of hierarchy, i.e., environment, structure and parameter. A prototype is presented to demonstrate the feasibility of this architecture. The results indicate that this approach can be applied for providing an integrated, flexible and user-friendly DSS environment for producing better quality of results in less solution time.     

An effective database formation for decision support systems

Managers' tasks have two aspects: to monitor (control) business activities and to plan the future based upon the monitored results. Thus a decision Support System (DSS) must have two kinds of databases appropriate for its needs.A management database, i.e., one for monitoring activities, is constructed mainly from the existing operational databases. A data cube should be employed for the logical data structure of the management database so that managers can share it and access it in multiple ways.Planning databases, i.e., those for planning activities, are constructed mostly from the management database. A table form should be employed for its logical data structure so that managers will find it easy to use.The management and planning databases should be connected through DSS's system architecture [1]. This makes the operational data (indicating business activities) directly and immediately available for management decision making.We have previously presented the DSS architecture. This paper discusses the management and planning databases from the viewpoint of it.     

Development of a decision support system for machining center selection

The machining centers are key resources for manufacturing companies in their dealing with their fierce competitive market environments. However, although selecting the most appropriate machining center is a very important decision for manufacturing companies, the availability of wide-range of types and models makes the selection process a complex and difficult task. In this study, a decision support system (DSS), namely MACSEL, is developed to help the decision makers in their machining center selection decisions. Several issues and applicability of the MACSEL is illustrated with case problems in the paper.Within the developed DSS, to select the feasible set of machining centers fifteen questions are placed in the elimination (pre-selection) module. The developed DSS uses fuzzy analytical hierarchy process (FAHP) or fuzzy technique for order preference by similarity to ideal solution (FTOPSIS), which are extended versions of multi-criteria decision making approaches, to rank the feasible machining centers. In the DSS, FAHP is used if a detailed pair-wise weighting of the hierarchically structured criteria is wanted. On the other hand, when a simpler separate weighting of each criterion is be considered as enough, FTOPSIS is used.     

基于数据仓库的后勤保障决策支持系统的实现

本文在分析了数据仓库技术、联机事件分析处理技术、数据挖掘技术后,提出了综合利用三种技术来解决将管理信息系统（MIS）提高为决策支持系统（DSS）的实现方案并给出了我们的一个实现实例。     

基于Web的决策支持系统的设计与实现

实现了一个基于Web的原型决策支持系统。该系统依据以往天气条件的记录,递归地构建一个决策树,用其预测未来网球比赛能否举行。详细展示了一个原型决策支持系统开发周期,包括从分析、设计到实现,如何使用面向对象技术来开发系统。     

模型库管理系统的设计和实现*

模型库管理系统是决策支持系统的核心，其基本功能包括模型的定义、组合、存储和调用.该文介绍一个支持客户/服务器模式的模型库管理系统的设计和实现，在这个系统中，模型被视为程序模块，通过运用面向对象的方法进行组织以及对模型的远程和动态的透明调用提供支持，使实现的系统具有良好的动态可扩充性.同时,通过提供模型定义语言和模型库管理，便于决策支持系统客户软件的开发.     

Development of a web-based decision support system for supporting integrated water resources management in Daegu city,South Korea

Demands on fresh water by human beings have been continuously increasing due to population growth, living standard improvement, and economic development. At the same time, many regions are suffering greatly from floods and droughts. Those are the results of ineffective management of water resources due to the associated complexities. In this study, a decision support system (DSS) was developed for supporting integrated water resources management in Daegu city, Republic of Korea. The developed DSS contained four subsystems including database, modelbase, and knowledgebase, as well as general user interface (GUI). It was then connected with the National Water Management Information System (WAMIS). A flow prediction could be conducted through the incorporated HEC-HMS Version 3.0.1. Also, an urban water demand forecasting model was developed using an artificial neural network (ANN) based model. At the same time, a water resources management model based on genetic algorithm (GA) was developed in the DSS, facilitating efficient allocation of water resources among different regions within a city. The result indicated that the developed DSS is very useful to deal with complex water resources management problems and could be further applied to similar cities in South Korea.     

基于数据仓库OLAP在决策支持系统中的应用研究

在21世纪的今天,以信息爆炸为特征的互联网时代,越来越多的企业决策需要根据企业以往的业务数据做参考,因此,需要建立一个可靠的决策支持系统(DSS)。决策支持系统(DSS)中一种通用的决策分析方式是建立在数据仓库的基础的,通过在线联机分析处理(OLAP)技术来实现的。文章主要讲述决策支持系统(DSS)中的数据组织方式、以及数据仓库(DW)的基本知识、联机分析处理(OLAP)的基础体系结构、及其决策分析的实现过程等方面的研究。并结合实际应用中的某大商场的销售分析决策系统为实例,分析企业如何把业务经营同市场需求联系起来,并在此基础上建立数据仓库系统,为企业做出科学、正确的决策。从而更加全面深入的分析整个企业的业务数据,从不同的角度来评估销售情况,这样方能给企业管理层人员提供更真实、客观的、全面的参考数据,提高整个企业的销售水平。