872 resultados para Multi-criteria Decision Support (MCDS)


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This research is concerned with identifying prequalification criteria that both clients and contractors believe are good indicators of future construction performance. Criteria used in the past have been developed by clients in a largely idiosyncratic manner with little or no consultation with the contractors affected. The methodology chosen for the research was a survey which probed stakeholder attitudes to commonly used prequalification criteria. This was carried out via a postal questionnaire involving contactors and clients across Australia. The data was analysed using Discriminant Analysis, which is a multivariate statistical approach that determines the differences between groups. The research is structured around 39 criteria that were developed as part of a whole-of–government task force into best practice in procurement. The findings identified the most important criteria from both a client’s perspective, and a contractor’s perspective. The purpose was to discover if those differences reduce the effectiveness of the procurement process. This paper contributes to a more clarified understanding of the impact or contrasting views between the stakeholders involved in the prequalification process. This work is innovative because it is one of a few pieces of research that showed that clients and contractors do actually have divergent opinions on the importance of some criteria currently relied upon in the decision making process. The most important prequalification criteria are identified and possible reasons for these differences are discussed.

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This paper proposes an intelligent decision-support system for managing manufacturing technology investments. The intelligent system is a hybrid integration of two information processing modules: case-based reasoning and fuzzy ARTMAP – a supervised adaptive resonance theory (ART) neural network with a multi-dimensional map. The developed system captures a company's strategic information, provides facilities to quantify qualitative attributes and analyses them alongside the quantitative attributes in an evaluation framework. Through the system, similar cases can be retrieved to enable managers to make effective use of their knowledge and experience of previously delivered technologies and projects as an input to the prioritization of future projects. Other salient features of the system include its ability to adapt and absorb new knowledge and responses pertaining to significant events in the business environment, as well as to extract and elucidate information from the knowledge database for explaining and justifying its analysis. The applicability of the developed system is evaluated using a real case study in collaboration with a pharmaceutical manufacturing firm.

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Stakeholder involvement in the management of estuaries is a necessary element of good environmental governance. In Victoria, Australia, a key challenge for estuary managers is whether or not estuaries should be artificially opened since many river mouths close ‘naturally’ from time to time. Estuary closure resulting in raised estuarine water levels leads to economic and social impacts on local communities. In the past these effects have been addressed by artificial river mouth openings, often without reference to associated environmental impacts. This article discusses the development and features of an Estuary Entrance Management Support System and considers its performance against principles of effective environmental management. It concludes that, in bringing together technical information with stakeholder input through a structured process, such a system makes a useful contribution to improving estuary entrance management.

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This article describes the implementation of machine learning techniques that assist cycling experts in the crucial decision-making processes for athlete selection and strategic planning in the track cycling omnium. The omnium is a multi-event competition that was included in the Olympic Games for the first time in 2012. Presently, selectors and cycling coaches make decisions based on experience and opinion. They rarely have access to knowledge that helps predict athletic performances. The omnium presents a unique and complex decision-making challenge as it is not clear what type of athlete is best suited to the omnium (e.g., sprint or endurance specialist) and tactical decisions made by the coach and athlete during the event will have significant effects on the overall performance of the athlete. In the present work, a variety of machine learning techniques were used to analyze omnium competition data from the World Championships since 2007. The analysis indicates that sprint events have slightly more influence in determining the medalists, than endurance-based events. Using a probabilistic analysis, we created a model of performance prediction that provides an unprecedented level of supporting information that assists coaches with strategic and tactical decisions during the omnium.

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Background: Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics.Objective: This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new contentMethods: A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper.Results: The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective content management.Conclusions: The prevalence of large numbers of online health resources is a key obstacle for domain experts involved in content management of health information portals and websites. The proposed technique has proven successful at search and identification of resources and the measurement of their relevance. It can be used to support the domain expert in content management and thereby ensure the health portal is up-to-date and current.

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Shared decision making enables a clinician and patient to participate jointly in making a health decision, having discussed the options and their benefits and harms, and having considered the patient's values, preferences and circumstances. It is not a single step to be added into a consultation, but a process that can be used to guide decisions about screening, investigations and treatments. The benefits of shared decision making include enabling evidence and patients' preferences to be incorporated into a consultation; improving patient knowledge, risk perception accuracy and patient-clinician communication; and reducing decisional conflict, feeling uninformed and inappropriate use of tests and treatments. Various approaches can be used to guide clinicians through the process. We elaborate on five simple questions that can be used: What will happen if the patient waits and watches? What are the test or treatment options? What are the benefits and harms of each option? How do the benefits and harms weigh up for the patient? Does the patient have enough information to make a choice? Although shared decision making can occur without tools, various types of decision support tools now exist to facilitate it. Misconceptions about shared decision making are hampering its implementation. We address the barriers, as perceived by clinicians. Despite numerous international initiatives to advance shared decision making, very little has occurred in Australia. Consequently, we are lagging behind many other countries and should act urgently.

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The vision of a smart grid is to provide a modern, resilient, and secure electric power grid as it boasts up with a highly reliable and efficient environment through effective use of its information and communication technology (ICT). Generally, the control and operation of a smart grid which integrate the distributed energy resources (DERs) such as, wind power, solar power, energy storage, etc., largely depends on a complex network of computers, softwares, and communication infrastructure superimposed on its physical grid architecture facilitated with the deployment of intelligent decision support system applications. In recent years, multi-agent system (MAS) has been well investigated for wide area power system applications and specially gained a significant attention in smart grid protection and security due to its distributed characteristics. In this chapter, a MAS framework for smart grid protection relay coordination is proposed, which consists of a number of intelligent autonomous agents each of which are embedded with the protection relays. Each agent has its own thread of control that provides it with a capability to operate the circuit breakers (CBs) using the critical clearing time (CCT) information as well as communicate with each other through high speed communication network. Besides physical failure, since smart grid highly depends on communication infrastructure, it is vulnerable to several cyber threats on its information and communication channel. An attacker who has knowledge about a certain smart grid communication framework can easily compromise its appliances and components by corrupting the information which may destabilize a system results a widespread blackout. To mitigate such risk of cyber attacks, a few innovative counter measuring techniques are discussed in this chapter.

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Leilões são instituições seculares utilizadas nas relações comerciais entre indivíduos e organizações. Provêem maior flexibilidade aos processos de determinação de preços e alocação de bens, aumentando o espaço para negociações entre compradores e vendedores. Na Internet, têm sido empregados, de maneira crescente, em atividades de comércio eletrônico B2B e G2B, em sua maioria, através da modalidade de leilão reverso. No entanto, seu aspecto unidimensional reduz as negociações à variável preço, produzindo, muitas vezes, resultados aquém do desejado. No caso brasileiro, o Governo Federal instituiu o Portal Comprasnet, através do qual, as organizações públicas adquirem bens e serviços de fornecedores cadastrados. Dentre as modalidades de licitação disponíveis, destaca-se o Pregão Eletrônico, um mecanismo de leilão eletrônico reverso baseado no atributo preço, através do qual, fornecedores submetem lances decrescentes, na disputa por contratos do setor público. No presente trabalho, o autor propõe uma abordagem de decisão multicritério, baseada na Teoria da Utilidade Multiatributo, como uma alternativa para a adoção de leilões reversos baseados em múltiplos atributos e, consequentemente, para uma maior agregação de valor pelas organizações compradoras do setor público brasileiro.

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The discussions wherein develop proposals for university reform in Brazil include, among other things, the conception of the university titled "New University", whose structural origin comes from the bill of higher education reform and unification of the foundations of education European upper (Bologna process). At its core, the Bologna process has imposed a series of transformations, among which, the promotion of mobility, as a stimulus to interinstitutional cooperation to enable an better and bigger qualification of the students. Nevertheless, what we see is that this point is one of the main points made flawed by Brazilian institutions that have adopted this model of higher education. An example is the Bachelor of Science and Technology - BC&T, Federal University of Rio Grande do Norte - UFRN, where there are problems of the internal order, represented by the problem of the reusing of the disciplines, such also of external order, in cases of transfers interinstitutional. Because of this, and knowing that this is a typical problem in which multiple criteria are involved, the aim of this study is to propose a multicriteria model for selection of interciclo of the BC&T of the UFRN which addresses the issue of mobility. For this, this study was of exploratory and study case nature, use as tools of data collection, the bibliographic and documentary research, as well as semi-structured interviews. For the elaboration of the model, were used the five phases most commonly used in the modeling of problems in operational research in a sample of 91 students of BC&T. As a result, we obtained a model that addresses the issue of internal and external mobility of the school and that, moreover, was also more robust and fair than the current model of BC&T and also what is used in other courses of the UFRN, taking into consideration the expected results by the decision makers

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The industrial automation is directly linked to the development of information tecnology. Better hardware solutions, as well as improvements in software development methodologies make possible the rapid growth of the productive process control. In this thesis, we propose an architecture that will allow the joining of two technologies in hardware (industrial network) and software field (multiagent systems). The objective of this proposal is to join those technologies in a multiagent architecture to allow control strategies implementations in to field devices. With this, we intend develop an agents architecture to detect and solve problems which may occur in the industrial network environment. Our work ally machine learning with industrial context, become proposed multiagent architecture adaptable to unfamiliar or unexpected production environment. We used neural networks and presented an allocation strategies of these networks in industrial network field devices. With this we intend to improve decision support at plant level and allow operations human intervention independent

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The communication between user and software is a basic stage in any Interaction System project. In interactive systems, this communication is established by the means of a graphical interface, whose objective is to supply a visual representation of the main entities and functions present in the Virtual Environment. New ways of interacting in computational systems have been minimizing the gap in the relationship between man and computer, and therefore enhancing its usability. The objective of this paper, therefore, is to present a proposal for a non-conventional user interface library called ARISupport, which supplies ARToolKit applications developers with an opportunity to create simple GUI interfaces, and provides some of the functionality used in Augmented Reality systems. © Springer-Verlag Berlin Heidelberg 2005.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)