Developing green supply chain management taxonomy-based decision support system

The aim of this paper is to develop a comprehensive taxonomy of green supply chain management (GSCM) practices and develop a structural equation modelling-driven decision support system following GSCM taxonomy for managers to provide better understanding of the complex relationship between the external and internal factors and GSCM operational practices. Typology and/or taxonomy play a key role in the development of social science theories. The current taxonomies focus on a single or limited component of the supply chain. Furthermore, they have not been tested using different sample compositions and contexts, yet replication is a prerequisite for developing robust concepts and theories. In this paper, we empirically replicate one such taxonomy extending the original study by (a) developing broad (containing the key components of supply chain) taxonomy; (b) broadening the sample by including a wider range of sectors and organisational size; and (c) broadening the geographic scope of the previous studies. Moreover, we include both objective measures and subjective attitudinal measurements. We use a robust two-stage cluster analysis to develop our GSCM taxonomy. The main finding validates the taxonomy previously proposed and identifies size, attitude and level of environmental risk and impact as key mediators between internal drivers, external drivers and GSCM operational practices.

A web based decision support system for status assessment in advanced parkinson

The purpose of this work is to develop a web based decision support system, based onfuzzy logic, to assess the motor state of Parkinson patients on their performance in onscreenmotor tests in a test battery on a hand computer. A set of well defined rules, basedon an expert’s knowledge, were made to diagnose the current state of the patient. At theend of a period, an overall score is calculated which represents the overall state of thepatient during the period. Acceptability of the rules is based on the absolute differencebetween patient’s own assessment of his condition and the diagnosed state. Anyinconsistency can be tracked by highlighted as an alert in the system. Graphicalpresentation of data aims at enhanced analysis of patient’s state and performancemonitoring by the clinic staff. In general, the system is beneficial for the clinic staff,patients, project managers and researchers.

A fuzzy rule-based decision support system for Duodopa treatment in Parkinson

A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson’s disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson’s disease.

A scenario-driven decision support system for serious crime investigation

Consideration of a wide range of plausible crime scenarios during any crime investigation is important to seek convincing evidence and hence to minimize the likelihood of miscarriages of justice. It is equally important for crime investigators to be able to employ effective and efficient evidence-collection strategies that are likely to produce the most conclusive information under limited available resources. An intelligent decision support system that can assist human investigators by automatically constructing plausible scenarios, and reasoning with the likely best investigating actions will clearly be very helpful in addressing these challenging problems. This paper presents a system for creating scenario spaces from given evidence, based on an integrated application of techniques for compositional modelling and Bayesian network-based evidence evaluation. Methods of analysis are also provided by the use of entropy to exploit the synthesized scenario spaces in order to prioritize investigating actions and hypotheses. These theoretical developments are illustrated by realistic examples of serious crime investigation.

Hybrid visual-driven decision support system in video monitor manufacturing

An intelligent system that emulates human decision behaviour based on visual data acquisition is proposed. The approach is useful in applications where images are used to supply information to specialists who will choose suitable actions. An artificial neural classifier aids a fuzzy decision support system to deal with uncertainty and imprecision present in available information. Advantages of both techniques are exploited complementarily. As an example, this method was applied in automatic focus checking and adjustment in video monitor manufacturing. Copyright © 2005 IFAC.

A clinical decision support system for cancer diseases

The second main cause of death in Brazil is cancer, and according to statistics disclosed by National Cancer Institute from Brazil (INCA) 466,730 new cases of cancer are forecast for 2008. The analysis of tumour tissues of various types and patients' clinical data, genetic profiles, characteristics of diseases and epidemiological data may lead to more precise diagnoses, providing more effective treatments. In this work we present a clinical decision support system for cancer diseases, which manages a relational database containing information relating to the tumour tissue and their location in freezers, patients and medical forms. Furthermore, it is also discussed some problems encountered, as database integration and the adoption of a standard to describe topography and morphology. It is also discussed the dynamic report generation functionality, that shows data in table and graph format, according to the user's configuration. © ACM 2008.

Bases metodológicas y conceptuales para el desarrollo de un sistema de apoyo a la administración de la cooperación técnica: versión preliminar = Conceptual and methodological bases for the development of a support system for the management of technical co-operation

Incluye Bibliografía

Project ranking and logical design of an investment programming support system

Includes bibliography

Application of passive control to energy harvester efficiency using a nonideal portal frame structural support system

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A support system that delineates location-choice sets for firms seeking office space

Factors influencing the location decisions of offices include traffic, accessibility, employment conditions, economic prospects and land-use policies. Hence tools for supporting real-estate managers and urban planners in such multidimensional decisions may be useful. Accordingly, the objective of this study is to develop a GIS-based tool to support firms who seek office accommodation within a given regional or national study area. The tool relies on a matching approach, in which a firm's characteristics (demand) on the one hand, and environmental conditions and available office spaces (supply) on the other, are analyzed separately in a first step, after which a match is sought. That is, a suitability score is obtained for every firm and for every available office space by applying some value judgments (satisfaction, utility etc.). The latter are powered by a focus on location aspects and expert knowledge about the location decisions of firms/organizations with respect to office accommodation as acquired from a group of real-estate advisers; it is stored in decision tables, and they constitute the core of the model. Apart from the delineation of choice sets for any firm seeking a location, the tool supports two additional types of queries. Firstly, it supports the more generic problem of optimally allocating firms to a set of vacant locations. Secondly, the tool allows users to find firms which meet the characteristics of any given location. Moreover, as a GIS-based tool, its results can be visualized using GIS features which, in turn, facilitate several types of analyses.

Availability and Use of Audiovisual and Electronic Resources by Distance Learning Students in Nigerian Universities: a Case Study of National Open University of Nigeria (NOUN), Ibadan Study Centre

This study investigated the availability and use of audiovisual and electronic resources by distance learning students at the National Open University of Nigeria (NOUN). A questionnaire was administered tothe distance learning students selected across the various departments of the NOUN. The findings revealed that even though NOUN made provision for audiovisual and electronic resources for students' use, a majority of the audiovisual and electronic resources are available through personal provision by the students.The study also revealed regular use of audiovisual and electronic resources by the distance learning students. Constraints on use include poor power supply, poor infrastructure, lack of adequate skill, and high cost of access.

E-Health towards ecumenical framework for personalized medicine via Decision Support System

The purpose of the present manuscript is to present the advances performed in medicine using a Personalized Decision Support System (PDSS). The models used in Decision Support Systems (DSS) are examined in combination with Genome Information and Biomarkers to produce personalized result for each individual. The concept of personalize medicine is described in depth and application of PDSS for Cardiovascular Diseases (CVD) and Type-1 Diabetes Mellitus (T1DM) are analyzed. Parameters extracted from genes, biomarkers, nutrition habits, lifestyle and biological measurements feed DSSs, incorporating Artificial Intelligence Modules (AIM), to provide personalized advice, medication and treatment.