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- 저자 : Paulo Novais (검색결과 3 건)
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A General Template to Configure Multi-Criteria Problems in Ubiquitous GDSS
João Carneiro,Diogo Martinho,Goreti Marreiros,Paulo Novais 보안공학연구지원센터 2015 International Journal of Software Engineering and Vol.9 No.11
The study of multi-criteria problems adapted to the context of Ubiquitous Group Deci-sion Support Systems (UbiGDSS) is covered in the literature through very different per-spectives and interests. There are scientific studies related to the multi-criteria problems that lie across argumentation-based negotiation, multi-agent systems, dialogues, etc. However, to perform most of these studies, a high amount of information is required. The usage of so much data or information that is difficult to collect or configure can bring good results in theoretical scenarios but can be impossible to use in the real world. In order to overcome these issues, we present in this paper a general template to configure multi-criteria problems adapted for the contexts of UbiGDSS that intends to be easy and fast to configure, appellative, intuitive, permits to collect a lot of data and helps the deci-sion-maker transmitting his beliefs and opinions to the system. Our proposal includes three sections: Problem Data, Personal Configuration and Problem Configuration. We have developed a prototype with our template with the purpose to simulate the configura-tion of a multi-criteria problem. We invited real decision-makers to use our prototype in a simulated scenario and asked to them to fulfil a survey in the end in order to study our hypotheses. Our general template achieved good results and proved to be very percepti-ble and fast to configure.
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UbiGDSS : A Theoretical Model to Predict Decision-Makers’ Sat-isfaction
João Carneiro,Ricardo Santos,Goreti Marreiros,Paulo Novais 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.7
The market globalization and the firms’ internationalization hinder the matching of the top managers’ agenda, making it difficult to meet in the same space or time. On the one hand, the appearance of Ubiquitous Group Decision Support Systems (UbiGDSS) ena-bled individuals to gather and make decisions in different spaces at different times, but on the other hand, originated problems related to the lack of human interaction. To under-stand how the arguments used can influence each of the decision-makers, what is their satisfaction regarding the decision made, and other affective issues such as emotions and mood, are some examples of that lack. In order to try to overcome this lack, we propose a theoretical model that is specially designed for agents, helping to understand the interac-tions impact on each agent and their satisfaction with the decision made.
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Characterize a Step Using Machine Learning
Ricardo Anacleto,Lino Figueiredo,Ana Almeida,Paulo Novais,António Meireles 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.11
Most of pedestrian inertial navigation system estimates displacement based on the integration of inertial sensors measurements. However, due to low-cost sensors and pedestrian dead reckoning inherent characteristics these systems provide huge location estimation errors. To suppress some of these limitations we propose a pedestrian inertial navigation system based on low-cost sensors and on information fusion and learning techniques. The proposed system introduces a step characterization module that characterizes the step according to the activity that the pedestrian is performing. This module performs three characterizations: terrain, direction and length. Thus, in this work are presented and evaluated several machine learning approaches that perform the terrain characterization. The inclusion of this machine learning module led to a significantly better performance of the pedestrian inertial navigation system.
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