A decision support system for a waste collection vehicle routing problem

The selective collection of municipal solid waste for recycling is a very complex and expensive process, where a major issue is to perform cost-efficient waste collection routes. Despite the abundance of commercially available software for fleet management, they often lack the capability to deal properly with sequencing problems and dynamic revision of plans and schedules during process execution. Our approach to achieve better solutions for the waste collection process is to model it as a vehicle routing problem, more specifically as a team orienteering problem where capacity constraints on the vehicles are considered, as well as time windows for the waste collection points and for the vehicles. The final model is called capacitated team orienteering problem with double time windows (CTOPdTW).We developed a genetic algorithm to solve routing problems in waste collection modelled as a CTOPdTW. The results achieved suggest possible reductions of logistic costs in selective waste collection.

Decision methods applied to solve a safety problem on a waste treatment facility

To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

Safety classification using GIS in decision-making process to define priority road interventions

Given the current economic situation of the Portuguese municipalities, it is necessary to identify the priority investments in order to achieve a more efficient financial management. The classification of the road network of the municipality according to the occurrence of traffic accidents is fundamental to set priorities for road interventions. This paper presents a model for road network classification based on traffic accidents integrated in a geographic information system. Its practical application was developed through a case study in the municipality of Barcelos. An equation was defined to obtain a road safety index through the combination of the following indicators: severity, property damage only and accident costs. In addition to the road network classification, the application of the model allows to analyze the spatial coverage of accidents in order to determine the centrality and dispersion of the locations with the highest incidence of road accidents. This analysis can be further refined according to the nature of the accidents namely in collision, runoff and pedestrian crashes.

A proactive intelligent decision support system for predicting the popularity of online news

"Lecture notes in computer science series, ISSN 0302-9743, vol. 9273"

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

Step towards multiplatform framework for supporting pediatric and neonatology care unit decision process

Children are an especially vulnerable population, particularly in respect to drug administration. It is estimated that neonatal and pediatric patients are at least three times more vulnerable to damage due to adverse events and medication errors than adults are. With the development of this framework, it is intended the provision of a Clinical Decision Support System based on a prototype already tested in a real environment. The framework will include features such as preparation of Total Parenteral Nutrition prescriptions, table pediatric and neonatal emergency drugs, medical scales of morbidity and mortality, anthropometry percentiles (weight, length/height, head circumference and BMI), utilities for supporting medical decision on the treatment of neonatal jaundice and anemia and support for technical procedures and other calculators and widespread use tools. The solution in development means an extension of INTCare project. The main goal is to provide an approach to get the functionality at all times of clinical practice and outside the hospital environment for dissemination, education and simulation of hypothetical situations. The aim is also to develop an area for the study and analysis of information and extraction of knowledge from the data collected by the use of the system. This paper presents the architecture, their requirements and functionalities and a SWOT analysis of the solution proposed.

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

BeSmart2: A multicriteria decision aid application

This paper presents an improved version of an application whose goal is to provide a simple and intuitive way to use multicriteria decision methods in day-to-day decision problems. The application allows comparisons between several alternatives with several criteria, always keeping a permanent backup of both model and results, and provides a framework to incorporate new methods in the future. Developed in C#, the application implements the AHP, SMART and Value Functions methods.

Análise de dados e aplicação de modelos estatísticos para apoio à decisão de contratação na Petróleo Brasileiro

Dissertação de mestrado em Engenharia Industrial

Escala de atitudes frente ao HIV/AIDS: análise de fatores

OBJETIVO: Este trabalho apresenta resultados acerca das propriedades psicométricas da "Escala de atitudes frente ao HIV/AIDS". Os dados, provenientes de uma amostra de 549 alunos entre universitários, ensinos médio e ensino fundamental. MÉTODOS: Os dados foram tratados pelo método dos componentes principais da análise fatorial. A análise final, postulado um eigenvalue mínimo de 2, resultou cinco fatores. Foram eliminados itens que apresentaram carga fatorial menor que 0,30. Neste estudo, o menor alfa observado foi de 0,79. Portanto, é provável que todos os 47 itens do instrumento final elaborado meçam o mesmo construto: atitude frente ao HIV/AIDS. RESULTADOS: Escores inferiores a 96 foram considerados "fraco grau de conhecimento sobre HIV/AIDS"; entre 96 e 192 "moderado grau de conhecimento" e acima de 192 "alto grau de conhecimento sobre HIV/AIDS". Foram estabelecidos os fatores: 1, 2 e 3, sendo "fator geral de percepção da informação técnico-científica"; "fator de percepção da informação técnico-científica versus sexualidade e preconceito"; "fator de percepção da informação técnico-científica no uso de drogas", respectivamente. CONCLUSÕES: O alfa de Cronbach encontrado para a escala como um todo foi de 0,859, sugerindo fortemente a existência da fidedignidade do instrumento que se mostrou útil para avaliar o grau de conhecimento acerca do HIV/AIDS e o risco decorrente do desconhecimento, entre estudantes.

Associação entre uso de álcool em indivíduos com AIDS e adesão ao tratamento antirretroviral: uma revisão da literatura

OBJETIVO: O objetivo deste trabalho foi fazer uma revisão sistemática da literatura, utilizando a base de dados MedLine, sobre o tema: uso/abuso/dependência de álcool como um fator de risco à redução da adesão, à redução na supressão da carga viral ou ao pior desfecho clínico em pacientes com AIDS em uso de highly active antiretroviral therapy (HAART). MÉTODO: Foi realizada uma pesquisa sistemática na base de dados MedLine utilizando como unitermos "HAART", "adherence" e "alcohol", na busca de artigos que versassem sobre a temática: avaliação ou associação de uso/abuso/dependência de álcool e adesão/supressão da carga viral/ desfecho clínico nos pacientes em uso de terapia antirretroviral. RESULTADOS: A busca resultou em 65 artigos. Contudo, apenas 21 deles contemplaram os critérios de inclusão e foram selecionados. Foi encontrada associação positiva entre uso/abuso/dependência de álcool e baixa adesão/baixa supressão da carga viral/pior desfecho clínico em 18 (85,7%) artigos. CONCLUSÃO: O uso/abuso/dependência de álcool é um fator de risco para baixa adesão/baixa supressão da carga viral/pior desfecho clínico nos indivíduos em uso de HAART.

Estudo do autorrelato de adesão e uso problemático de álcool em uma população de indivíduos com AIDS em uso de HAART

OBJETIVO: O objetivo deste estudo foi analisar a força de associação entre as variáveis autorrelato de adesão à medicação e uso problemático de álcool em uma população de indivíduos com AIDS que fazem uso de HAART. MÉTODO: Foram entrevistados 103 pacientes com AIDS, em uso de HAART há pelo menos seis meses, que frequentavam o ambulatório do Instituto de Doenças Tropicais Natan Portela (IDTNP), localizado na cidade de Teresina, PI. A variável independente estudada foi o uso problemático de álcool, além de variáveis sociodemográficas. O questionário utilizado para avaliar o uso problemático de álcool foi o AUDIT (Alcohol Use Disorders Identification Test). A variável dependente avaliada neste estudo foi o autorrelato de adesão ao tratamento para o HIV. Para sua mensuração, optou-se por utilizar o QSAM (Questionário Simplificado de Adesão à Medicação), por tratar-se de um questionário bastante simples e de fácil aplicação. RESULTADOS: A frequência de AUDIT > 08 foi de 33%; já o autorrelato de adesão, avaliado pelo QSAM, foi positivo em 45% da amostra. Testada a associação entre a frequência de QSAM positivo e o AUDIT positivo, encontrou-se forte associação entre essas variáveis (p = 0,004). CONCLUSÃO: Conclui-se deste estudo que o autorrelato de falha na adesão ao HAART aferido por meio do QSAM é um fator de risco para a presença de uso problemático de álcool.

Psychosocial factors associated with adherence to treatment and quality of life in people living with HIV/AIDS in Brazil

Objective: The objective of this article was to investigate the biopsychosocial factors that influence adherence to treatment and the quality of life of individuals who have been successfully following the HIV/AIDS treatment. Methods: It is a cross-sectional study carried out with 120 HIV positive participants in the south of Brazil. Among the variables studied, of note are: perceived stress, social support, symptoms of anxiety and depression and quality of life. Results: The results show that a moderate to high adherence to the treatment paired with a strong sense of social support indicate a higher quality of life. Conclusion: The combination of social support and antiretroviral treatment have an impact on physical conditions, improving immune response and quality of life.

Normal aging and decision-making: a systematic review of the literature of the last 10 years

Objective Conduct a systematic review to investigate whether healthy elderly have deficits in the decision-making process when compared to the young. Methods We performed a systematic search on SciELO, Lilacs, PsycINFO, Scopus and PubMed database with keywords decision making and aging (according to the description of Mesh terms) at least 10 years. Results We found nine studies from different countries, who investigated 441 young and 377 elderly. All studies used the IOWA Gambling Task as a way of benchmarking the process of decision making. The analysis showed that 78% of the articles did not have significant differences between groups. However, 100% of the studies that assessed learning did find relevant differences. Furthermore, studies that observed the behavior of individuals in the face of losses and gains, 60% of articles showed that the elderly has more disadvantageous choices throughout the task. Conclusion: The consulted literature showed no consensus on the existence of differences in performance of the decision-making process between old and young, but it is observed that the elderly has deficits in learning and a tendency to fewer advantageous choices.

Pervasive decision support to predict football corners and goals by means of data mining

Football is considered nowadays one of the most popular sports. In the betting world, it has acquired an outstanding position, which moves millions of euros during the period of a single football match. The lack of profitability of football betting users has been stressed as a problem. This lack gave origin to this research proposal, which it is going to analyse the possibility of existing a way to support the users to increase their profits on their bets. Data mining models were induced with the purpose of supporting the gamblers to increase their profits in the medium/long term. Being conscience that the models can fail, the results achieved by four of the seven targets in the models are encouraging and suggest that the system can help to increase the profits. All defined targets have two possible classes to predict, for example, if there are more or less than 7.5 corners in a single game. The data mining models of the targets, more or less than 7.5 corners, 8.5 corners, 1.5 goals and 3.5 goals achieved the pre-defined thresholds. The models were implemented in a prototype, which it is a pervasive decision support system. This system was developed with the purpose to be an interface for any user, both for an expert user as to a user who has no knowledge in football games.