Computer tools to aid the learning and design steps for photovoltaic systems

This paper presents novel simulation tools to assist the lecturers about learning processes on renewable energy sources, considering photovoltaic (PV) systems. The PV behavior, functionality and its interaction with power electronic converters are investigated in the simulation tools. The main PV output characteristics, I (current) versus V (voltage) and P (power) versus V (voltage), were implemented in the tools, in order to aid the users for the design steps. In order to verify the effectiveness of the developed tools the simulation results were compared with Matlab. Finally, a prototype was implemented with the purpose to compare the experimental results with the results from the proposed tools, validating its operational feasibility. © 2011 IEEE.

Algebra

Incluye Bibliografía

Scheduler simulation using iSPD, an iconic-based computer grid simulator

Increased accessibility to high-performance computing resources has created a demand for user support through performance evaluation tools like the iSPD (iconic Simulator for Parallel and Distributed systems), a simulator based on iconic modelling for distributed environments such as computer grids. It was developed to make it easier for general users to create their grid models, including allocation and scheduling algorithms. This paper describes how schedulers are managed by iSPD and how users can easily adopt the scheduling policy that improves the system being simulated. A thorough description of iSPD is given, detailing its scheduler manager. Some comparisons between iSPD and Simgrid simulations, including runs of the simulated environment in a real cluster, are also presented. © 2012 IEEE.

Boosting optimum-path forest clustering through harmony Search and its applications for intrusion detection in computer networks

In this paper we propose a nature-inspired approach that can boost the Optimum-Path Forest (OPF) clustering algorithm by optimizing its parameters in a discrete lattice. The experiments in two public datasets have shown that the proposed algorithm can achieve similar parameters' values compared to the exhaustive search. Although, the proposed technique is faster than the traditional one, being interesting for intrusion detection in large scale traffic networks. © 2012 IEEE.

Intrusion detection in computer networks using optimum-path forest clustering

Nowadays, organizations face the problem of keeping their information protected, available and trustworthy. In this context, machine learning techniques have also been extensively applied to this task. Since manual labeling is very expensive, several works attempt to handle intrusion detection with traditional clustering algorithms. In this paper, we introduce a new pattern recognition technique called Optimum-Path Forest (OPF) clustering to this task. Experiments on three public datasets have showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, since it outperformed some state-of-the-art unsupervised techniques. © 2012 IEEE.

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

A computer vision approach to quantify leaf anatomical plasticity: A case study on gochnatia polymorpha (less.) cabrera

Inferences about leaf anatomical characteristics had largely been made by manually measuring diverse leaf regions, such as cuticle, epidermis and parenchyma to evaluate differences caused by environmental variables. Here we tested an approach for data acquisition and analysis in ecological quantitative leaf anatomy studies based on computer vision and pattern recognition methods. A case study was conducted on Gochnatia polymorpha (Less.) Cabrera (Asteraceae), a Neotropical savanna tree species that has high phenotypic plasticity. We obtained digital images of cross-sections of its leaves developed under different light conditions (sun vs. shade), different seasons (dry vs. wet) and in different soil types (oxysoil vs. hydromorphic soil), and analyzed several visual attributes, such as color, texture and tissues thickness in a perpendicular plane from microscopic images. The experimental results demonstrated that computational analysis is capable of distinguishing anatomical alterations in microscope images obtained from individuals growing in different environmental conditions. The methods presented here offer an alternative way to determine leaf anatomical differences. © 2013 Elsevier B.V.

Digital proficiency and digital inclusion: Comparison between students of computer science, public relations and engineering

New information and communication technologies may be useful for providing more in-depth knowledge to students in many ways, whether through online multimedia educational material, or through online debates with colleagues, teachers and other area professionals in a synchronous or asynchronous manner. This paper focuses on participation in online discussion in e-learning courses for promoting learning. Although an important theoretical aspect, an analysis of literature reveals there are few studies evaluating the personal and social aspects of online course users in a quantitative manner. This paper aims to introduce a method for diagnosing inclusion and digital proficiency and other personal aspects of the student through a case study comparing Information System, Public Relations and Engineering students at a public university in Brazil. Statistical analysis and analysis of variances (ANOVA) were used as the methodology for data analysis in order to understand existing relations between the components of the proposed method. The survey methodology was also used, in its online format, as a research instrument. The method is based on using online questionnaires that diagnose digital proficiency and time management, level of extroversion and social skills of the students. According to the sample studied, there is no strong correlation between digital proficiency and individual characteristics tied to the use of time, level of extroversion and social skills of students. The differences in course grades for some components are partly due to subject 'Introduction to Economics' being offered to freshmen in Public Relations, whereas subject 'Economics in Engineering' is offered in the final semesters of Engineering and Information Systems courses. Therefore, the difference could be more tied to the respondent's age than to the course. Information Systems students were observed to be older, with access to computers and Internet at the workplace, compared to the other students who access the Internet more often from home. This paper presents a pilot study aimed at conducting a diagnosis that permits proposing actions for information and communication technology to contribute towards student education. Three levels of digital inclusion are described as a scale to measure whether information technology increases personal performance and professional knowledge and skills. This study may be useful for other readers interested in themes related to education in engineering. © 2013 IEEE.

Algoritmos para geração de referências, inicialização e proteção de um condicionador unificado de qualidade de energia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A computer model of family building based on expected values; abstract of an article by Potter and Sakoda

Includes bibliography

Trabalhando conceitos matemáticos com tecnologias informáticas por meio da elaboração de projetos de construção civil

Pós-graduação em Educação Matemática - IGCE