Evolutionary intelligence in asphalt pavement modeling and quality-of-information

Neves, José; Ribeiro, Jorge; Pereirâ, Paulo A. A.; Alves, Victor; Machado, José; Abelha, António; Nováis, Paulo; Analide, César; Santos, Manuel Filipe; Fernández-Delgado, Manuel

doi:10.1007/s13748-011-0003-5

Cited by 14 publications

(3 citation statements)

References 39 publications

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“…From information assembled from different environments, ML techniques may derive models of behaviour and interaction based on specialized backgrounds (e.g., users, environment, social interaction or consumption). ML and Data Mining (DM) techniques may also be used to obtain information about user's habits in AmI settings, from data gathered by sensors in the environment, namely using practices such as Sequence Discovery [3], Fuzzy Logic [6], Genetic Programming, Multi-Layer Perceptron, Evolutionary Intelligence [8] or combinations of these techniques [12].…”

Section: Previous Studymentioning

confidence: 99%

Sensorization and Intelligent Systems in Energetic Sustainable Environments

Silva

Cuevas

Analide

et al. 2013

Intelligent Distributed Computing VI

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Sustainability is an important topic of discussion in our world. However, measuring sustainability and assessing behaviors is not always easy. Indeed, and in order to fulfill this goal, in this work it will be proposed a multi-agent based architecture to measure and assess sustainable indicators taken from a given environment. These evaluations will be based on past and present behaviors of the users and the particularities of the setting, leading to the evaluation of workable indicators such as gas emissions, energetic consumption and the users fitting with respect to the milieu. Special attention is given to user interaction and user attributes to calculate sustainable indicators for each type of structure, i.e., the aim of this scheme is to promote sustainability awareness and sustainable actions through the use of sustainable markers calculated in terms of the information gathered from the environment.

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Section: Previous Studymentioning

confidence: 99%

Sensorization and Intelligent Systems in Energetic Sustainable Environments

Silva

Cuevas

Analide

et al. 2013

Intelligent Distributed Computing VI

Self Cite

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“…Before applying a clinical decision model that includes incomplete information, it is necessary to represent it in an appropriate way. Extensions to the Language of Logic Programming (ELP) [19,20] is one of the few techniques that enable this representation, using Mathematical Logic. ELP uses negation-byfailure and classic negation to represent explicit negative information.…”

Section: Clinical Decision Modelmentioning

confidence: 99%

A Web Platform and a Decision Model for Computer-Interpretable Guidelines

Oliveira

Nováis

Neves

2013

Advances in Intelligent Systems and Computing

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Situations of medical error and defensive medicine are common in healthcare environments and have repercussions in the quality of care under offer. The occurrence of adverse events and the increase of healthcare expenses are some of the consequences of medical malpractice. Indeed, these situations may be prevented by encouraging the compliance with Clinical Guidelines (CGs). However, the current format of CGs proved to be disadvantageous for real-time application, i.e., they may not provide recommendations to healthcare professionals when required, and on time. The introduction of Computer-Interpretable Guidelines (CIGs) may provide a solution to this problem, however they are not widely implemented and there are some issues that need to be contemplated. Indeed, in this paper it is presented the CompGuide project for guideline representation and sharing, combined with the handling of incomplete information in that context.

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“…With this paper we make a start on the development of an unusual or original diagnosis assistance system for schizophrenia. We will present a logic programming based approach in order to represent the knowledge and reasoning, with a focus on the Degree of Confidence (DoC) of the attributes set, that makes a function or a predicate [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

Cardoso

Marins

Magalhães

et al. 2015

The Scientific World Journal

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Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

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Evolutionary intelligence in asphalt pavement modeling and quality-of-information

Cited by 14 publications

References 39 publications

Sensorization and Intelligent Systems in Energetic Sustainable Environments

Sensorization and Intelligent Systems in Energetic Sustainable Environments

A Web Platform and a Decision Model for Computer-Interpretable Guidelines

Abstract Computation in Schizophrenia Detection through Artificial Neural Network Based Systems

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