A web-based intelligent tutoring system on teaching and learning electrical project

The Information and Communication Technology (ICT) provide new strategies for disseminating information and new communication models in order to change attitudes and human behaviour concerning to education. Nowadays the internet is crucial as a means of communication and information sharing. To education or tutorship will be required to use ICT, supported on the internet, to establish the communication of teacher-student and student-student, disseminating the content of the subjects, and as a way of teaching and learning process. This paper presents an intelligent tutor that aims to be a tool to support teaching and learning in the field of the electrical engineering project.

Occupational exposure to poultry dust and effects on the respiratory system in workers

Farmers are occupationally exposed to many respiratory hazards at work and display higher rates of asthma and respiratory symptoms than other workers. Dust is one of the components present in poultry production that increases risk of adverse respiratory disease occurrence. Dust originates from poultry residues, molds, and feathers and is biologically active as it contains microorganisms. Exposure to dust is known to produce a variety of clinical responses, including asthma, chronic bronchitis, chronic airways obstructive disease (COPD), allergic alveolitis, and organic dust toxic syndrome (ODTS). A study was developed to determine particle contamination in seven poultry farms and correlate this with prevalence rate of respiratory defects and record by means of a questionnaire the presence of clinical symptoms associated with asthma and other allergy diseases by European Community Respiratory Health Survey. Poultry farm dust contamination was found to contain higher concentrations of particulate matter (PM) PM5 and PM10. Prevalence rate of obstructive pulmonary disorders was higher in individuals with longer exposure regardless of smoking status. In addition, a high prevalence for asthmatic (42.5%) and nasal (51.1%) symptoms was noted in poultry workers. Data thus show that poultry farm workers are more prone to suffer from respiratory ailments and this may be attributed to higher concentrations of PM found in the dust. Intervention programs aimed at reducing exposure to dust will ameliorate occupational working conditions and enhance the health of workers.

Learning objects recommendation in an adaptive educational hypermedia system

The aim of this paper is presenting the modules of the Adaptive Educational Hypermedia System PCMAT, responsible for the recommendation of learning objects. PCMAT is an online collaborative learning platform with a constructivist approach, which assesses the user’s knowledge and presents contents and activities adapted to the characteristics and learning style of students of mathematics in basic schools. The recommendation module and search and retrieval module choose the most adequate learning object, based on the user's characteristics and performance, and in this way contribute to the system’s adaptability.

Ant colony system based approach to single machine scheduling problems: weighted tardiness scheduling problem

The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.

Multi-apprentice learning for meta-heuristics parameter tuning in a multi agent scheduling system

The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance.

Case-based reasoning for meta-heuristics self-parameterization in a multi-agent scheduling system

A novel agent-based approach to Meta-Heuristics self-configuration is proposed in this work. Meta-heuristics are examples of algorithms where parameters need to be set up as efficient as possible in order to unsure its performance. This paper presents a learning module for self-parameterization of Meta-heuristics (MHs) in a Multi-Agent System (MAS) for resolution of scheduling problems. The learning is based on Case-based Reasoning (CBR) and two different integration approaches are proposed. A computational study is made for comparing the two CBR integration perspectives. In the end, some conclusions are reached and future work outlined.

Negotiation mechanism for self-organized scheduling system

This paper presents a negotiation mechanism for Dynamic Scheduling based on Swarm Intelligence (SI). Under the new negotiation mechanism, agents must compete to obtain a global schedule. SI is the general term for several computational techniques which use ideas and get inspiration from the social behaviors of insects and other animals. This work is concerned with negotiation, the process through which multiple selfinterested agents can reach agreement over the exchange of operations on competitive resources.

Cooperative intelligent system for manufacturing scheduling

Hybridization of intelligent systems is a promising research field of computational intelligence focusing on combinations of multiple approaches to develop the next generation of intelligent systems. In this paper we will model a Manufacturing System by means of Multi-Agent Systems and Meta-Heuristics technologies, where each agent may represent a processing entity (machine). The objective of the system is to deal with the complex problem of Dynamic Scheduling in Manufacturing Systems.

Validação da eficácia dos procedimentos de limpeza, no equipamento de fabrico e embalagem, na indústria farmacêutica

Na indústria farmacêutica, a limpeza dos equipamentos e superfícies é muito importante no processo de fabrico/embalagem dos produtos farmacêuticos. Possíveis resíduos contaminantes devem ser removidos dos equipamentos e das superfícies envolvidas no processo. De acordo com as Boas Práticas de Fabrico (GMP), os procedimentos de limpeza e os métodos analíticos usados para determinar as quantidades de resíduos devem ser validados. O método analítico combinado com o método de amostragem utilizado na colheita de amostras deve ser sujeito a um ensaio de “recovery”. Neste trabalho apresenta-se uma estratégia inovadora para a validação de limpeza de formas farmacêuticas semi-sólidas. Propõe-se o uso de um método de amostragem que consiste na colheita direta de amostra após o seu fabrico, sendo a análise de resíduos feita directamente nesta amostra. Os produtos escolhidos para a avaliação da estratégia foram dois medicamentos dermatológicos, apresentados na forma de pomada e produzidos numa unidade de fabrico de vários produtos, pela Schering Plough Farma/ Merck Sharp & Dohme (Cacém, Portugal). Como métodos analíticos para a quantificação dos resíduos, utilizaram-se métodos validados por via espectrofotométrica (HPLC), usados na análise do produto acabado. A validação de limpeza foi avaliada através da análise de uma quantidade conhecida de pomada (produto B (*)), usando o método de análise da pomada fabricada anteriormente (produto A (*)), de modo a verificar-se a existência ou não de agente de limpeza e substâncias ativas deixadas após a limpeza do produto A, e vice-versa. As concentrações residuais das substâncias ativas e do agente de limpeza encontradas após a limpeza foram nulas, ou seja, inferiores ao limite de deteção (LOD), sendo que o critério de aceitação da limpeza utilizado foi de 6,4 x 10-4 mg/g para a substância ativa 1 (*); 1,0 x 10-2 mg/g para a substância ativa 2 (*); 1,0 x 10-3 mg/g para a substância ativa 3 (*) e de 10 ppm para o agente de limpeza. No ensaio de “recovery”, obtiveram-se resultados acima de 70% para todas as substâncias ativas e para o agente de limpeza nas duas pomadas. Antes de se proceder a este ensaio de “recovery”, houve a necessidade de ajustar as condições cromatográficas dos métodos analíticos de ambos os produtos e do agente de limpeza, por forma a obter-se valores da conformidade do sistema (fator de tailling e de resolução) de acordo com as especificações. A precisão dos resultados, reportada como desvio padrão relativo (RSD), deu abaixo de 2,0%, excepto nos ensaios que envolvem a substância ativa 3, cuja especificação é inferior a 10,0%. Os resultados obtidos demonstraram que os procedimentos de limpeza usados na unidade de fabrico em causa são eficazes, eliminando assim a existência de contaminação cruzada.

Determinants of vaccination after the Colombian health system reform

OBJECTIVE: To assess the effects of individual, household and healthcare system factors on poor children's use of vaccination after the reform of the Colombian health system. METHODS: A household survey was carried out in a random sample of insured poor population in Bogota, in 1999. The conceptual and analytical framework was based on the Andersen's Behavioral Model of Health Services Utilization. It considers two units of analysis for studying vaccination use and its determinants: the insured poor population, including the children and their families characteristics; and the health care system. Statistical analysis were carried out by chi-square test with 95% confidence intervals, multivariate regression models and Cronbach's alpha coefficient. RESULTS: The logistic regression analysis showed that vaccination use was related not only to population characteristics such as family size (OR=4.3), living area (OR=1.7), child's age (OR=0.7) and head-of-household's years of schooling (OR=0.5), but also strongly related to health care system features, such as having a regular health provider (OR=6.0) and information on providers' schedules and requirements for obtaining care services (OR=2.1). CONCLUSIONS: The low vaccination use and the relevant relationships to health care delivery systems characteristics show that there are barriers in the healthcare system, which should be assessed and eliminated. Non-availability of regular healthcare and deficient information to the population are factors that can limit service utilization.

Content adaptation for an adaptive hypermedia system

The aim of this paper is presenting the recommendation module of the Mathematics Collaborative Learning Platform (PCMAT). PCMAT is an Adaptive Educational Hypermedia System (AEHS), with a constructivist approach, which presents contents and activities adapted to the characteristics and learning style of students of mathematics in basic schools. The recommendation module is responsible for choosing different learning resources for the platform, based on the user's characteristics and performance. Since the main purpose of an adaptive system is to provide the user with content and interface adaptation, the recommendation module is integral to PCMAT’s adaptation model.

Cooperation mechanism for team-work based multi-agent system in dynamic scheduling through meta-heuristics

This paper describes a Multi-agent Scheduling System that assumes the existence of several Machines Agents (which are decision-making entities) distributed inside the Manufacturing System that interact and cooperate with other agents in order to obtain optimal or near-optimal global performances. Agents have to manage their internal behaviors and their relationships with other agents via cooperative negotiation in accordance with business policies defined by the user manager. Some Multi Agent Systems (MAS) organizational aspects are considered. An original Cooperation Mechanism for a Team-work based Architecture is proposed to address dynamic scheduling using Meta-Heuristics.

ABS4GD: a multi-agent system that simulates group decision processes considering emotional and argumentative aspects

Emotion although being an important factor in our every day life it is many times forgotten in the development of systems to be used by persons. In this work we present an architecture for a ubiquitous group decision support system able to support persons in group decision processes. The system considers the emotional factors of the intervenient participants, as well as the argumentation between them. Particular attention will be taken to one of components of this system: the multi-agent simulator, modeling the human participants, considering emotional characteristics, and allowing the exchanges of hypothetic arguments among the participants.

Ambient intelligence in emotion based ubiquitous decision making

As the time goes on, it is a question of common sense to involve in the process of decision making people scattered around the globe. Groups are created in a formal or informal way, exchange ideas or engage in a process of argumentation and counterargumentation, negotiate, cooperate, collaborate or even discuss techniques and/or methodologies for problem solving. In this work it is proposed an agent-based architecture to support a ubiquitous group decision support system, i.e. based on the concept of agent, which is able to exhibit intelligent, and emotional-aware behaviour, and support argumentation, through interaction with individual persons or groups. It is enforced the paradigm of Mixed Initiative Systems, so the initiative is to be pushed by human users and/or intelligent agents.

ISEM: a multi-agent system that simulates competitive electronic marketplaces

With the increasing importance of large commerce across the Internet it is becoming increasingly evident that in a few years the Iternet will host a large number of interacting software agents. a vast number of them will be economically motivated, and will negociate a variety of goods and services. It is therefore important to consider the economic incentives and behaviours of economic software agents, and to use all available means to anticipate their collective interactions. This papers addresses this concern by presenting a multi-agent market simulator designed for analysing agent market strategies based on a complete understanding of buyer and seller behaviours, preference models and pricing algorithms, consideting risk preferences. The system includes agents that are capable of increasing their performance with their own experience, by adapting to the market conditions. The results of the negotiations between agents are analysed by data minig algorithms in order to extract rules that give agents feedback to imprive their strategies.