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Publications

2012

Combining meta-learning and search techniques to select parameters for support vector machines

Authors
Gomes, TAF; Prudencio, RBC; Soares, C; Rossi, ALD; Carvalho, A;

Publication
NEUROCOMPUTING

Abstract
Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

2012

Effects of a Process-Oriented Goal Setting Model on Swimmer's Performance

Authors
Simoes, P; Vasconcelos Raposo, J; Silva, A; Fernandes, HM;

Publication
JOURNAL OF HUMAN KINETICS

Abstract
The aim of this work was to study the impact of the implementation of a mental training program on swimmers' chronometric performance, with national and international Portuguese swimmers, based on the goal setting model proposed by Vasconcelos-Raposo (2001). This longitudinal study comprised a sample of nine swimmers (four male and five female) aged between fourteen and twenty, with five to eleven years of competitive experience. All swimmers were submitted to an evaluation system during two years. The first season involved the implementation of the goal setting model, and the second season was only evaluation, totaling seven assessments over the two years. The main results showed a significant improvement in chronometric performance during psychological intervention, followed by a reduction in swimmers' performance in the second season, when there was no interference from the investigators (follow-up).

2012

ADOPTING ELECTRONIC HEALTH RECORDS IN HEALTH CARE PRACTICES: A MULTIPLE CASE STUDY OF THE PORTUGUESE HEALTHCARE SYSTEM

Authors
Oliveira, M; Brito, AC; Patricio, L;

Publication
PROCEEDINGS OF THE IADIS INTERNATIONAL CONFERENCE E-HEALTH 2012

Abstract
Recently, we are witnessing the effort of healthcare providers to move from paper-based records to electronic records, in order to reduce data access times and also to share clinical information. However, many of these electronic records projects have failed, as they are not well fitted to the healthcare professionals' practices. This paper presents a study on the impact of Information Technology in the daily routine of healthcare providers, to support the development of Electronic Health Records that are well adapted to these organizations' operational processes and are successfully adopted.

2012

Integrated pulp and paper mill planning and scheduling

Authors
Santos, MO; Almada Lobo, B;

Publication
COMPUTERS & INDUSTRIAL ENGINEERING

Abstract
This article describes a real-world production planning and scheduling problem occurring at an integrated pulp and paper mill (P&P) which manufactures paper for cardboard out of produced pulp. During the cooking of wood chips in the digester, two by-products are produced: the pulp itself (virgin fibers) and the waste stream known as black liquor. The former is then mixed with recycled fibers and processed in a paper machine. Here, due to significant sequence-dependent setups in paper type changeovers, sizing and sequencing of lots have to be made simultaneously in order to efficiently use capacity. The latter is converted into electrical energy using a set of evaporators, recovery boilers and counter-pressure turbines. The planning challenge is then to synchronize the material flow as it moves through the pulp and paper mills, and energy plant, maximizing customer demand (as backlogging is allowed), and minimizing operation costs. Due to the intensive capital feature of P&P, the output of the digester must be maximized. As the production bottleneck is not fixed, to tackle this problem we propose a new model that integrates the critical production units associated to the pulp and paper mills, and energy plant for the first time. Simple stochastic mixed integer programming based local search heuristics are developed to obtain good feasible solutions for the problem. The benefits of integrating the three stages are discussed. The proposed approaches are tested on real-world data. Our work may help P&P companies to increase their competitiveness and reactiveness in dealing with demand pattern oscillations.

2012

Integrating data mining and optimization techniques on surgery scheduling

Authors
Gomes, C; Almada Lobo, B; Borges, J; Soares, C;

Publication
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract
This paper presents a combination of optimization and data mining techniques to address the surgery scheduling problem. In this approach, we first develop a model to predict the duration of the surgeries using a data mining algorithm. The prediction model outcomes are then used by a mathematical optimization model to schedule surgeries in an optimal way. In this paper, we present the results of using three different data mining algorithms to predict the duration of surgeries and compare them with the estimates made by surgeons. The results obtained by the data mining models show an improvement in estimation accuracy of 36%.We also compare the schedules generated by the optimization model based on the estimates made by the prediction models against reality. Our approach enables an increase in the number of surgeries performed in the operating theater, thus allowing a reduction on the average waiting time for surgery and a reduction in the overtime and undertime per surgery performed. These results indicate that the proposed approach can help the hospital improve significantly the efficiency of resource usage and increase the service levels. © Springer-Verlag 2012.

2012

Synthesis of Nonuniform TEM-Mode Directional Couplers with Arbitrary Coupling Response

Authors
Pereira, MR; Salgado, HM; Pereira, JR;

Publication
2012 INTERNATIONAL CONFERENCE ON ELECTROMAGNETICS IN ADVANCED APPLICATIONS (ICEAA)

Abstract
We propose the use of inverse scattering on the design of ultra wide band nonuniform coupled line directional couplers with a specified coupling response. The inverse scattering is performed using the layer peeling algorithm which is simple and of easy implementation as a computer routine. To validate the method a wide band directional coupler is designed and implemented. © 2012 IEEE.

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