Rogério Eduardo Garcia

A methodological approach to use technological support on teaching and learning data structures

The Data Structure discipline consists on studying data organization in computer memory, primary and secondary ones. Data structures are organized using conceptual and behavioral issues that require high degree of abstract representation. It has been observed significant difficulty, by students, to understand the abstract concepts related, which is observed during practical tasks. In fact, practical tasks are essential to consolidate knowledge about data structures, but the students need support to understand the concepts before practical tasks. There are several works in literature showing tools to support conceptual and behavior comprehension, each one with specific features. However, the tools by themselves are not enough, dealing with specific data structure, with severe constraint. In literature, some tools are presented using case studies specific to the data structures supported. And we observed that the tools are presented focusing on their functionalities (the case studies are designed to explore such functionalities). Also, we observed the lack of a methodological approach to incorporate tools in a learning process effectively. In this scenario, we address the use of technological support to teaching-learning process. We propose a methodology based on constructionism, in which students, tasks (home works) and tools are coordinated by a teacher in favor of knowledge construction. In order to present our methodology, we use a learning tool, named CADILAG, developed using visual resources to support students understand data structures concepts. We applied the methodology proposed for two years. The positive results are observed in students grades and their evaluation. Also, according to the teacher, the students have shown interest and motivation.

Simulation and analysis applied on virtualization to build Hadoop clusters

The data growth enhances the need of a method and paradigms responsible to deal with high scalability, reliability and fault tolerance in large amounts of data. Big Data is a framework capable of dealing with this need. This research makes usage of Apache Hadoop, and a Virtual Private Server (VPS) to analyze the performance through benchmark tests executed on locally, geographically distributed, and centralized Hadoop computational layout. The result from the simulations metrics, and performance analyses are compared to real servers and introduce an alternative model implemented with a tunnel protocol that enhance the processing power of the cluster.

Scalable information system using event oriented programming and NoSQL

One of many challenges in a web information systems is the capability of staying stable and available as the number of users and requests increase rapidly, what we call scalability. This paper provides a model based on development of events-oriented applications, non-blocking in the environment Node.JS with the non-relational database model (MongoDB), preparing to establish scalability and a comparison with a traditional model (relational database (MySQL), HTTP Apache server and PHP language). The results obtained reveal that the proposed model is more efficient (response time of six to eight faster) than the comparative model, can be used in production environments with development quality, performance improvement and scalability.

Teaching-learning methodology for formal languages and automata theory

Formal languages and automata (FLA) theory have fundamental relevance to the base of knowledge in the computer science area, especially focusing on scientific education. Usually presented by a discipline, the teaching-learning process of FLA is characterized by the high level of abstraction, and it is considered difficult due to the complexity of language formalisms. As support for the learning process, tools have been used to simulate language formalisms. However, the simulation is not enough to reinforce the construction of an abstract concept. In this paper, we present an FLA teaching-learning methodology based on the development of simulators as an approach to clarify the formalism for the students. Through developing their simulators, students are exposed to the data structure and algorithms to handle the formalism. Consequently, students have the opportunity to make the concept concrete.

Coordinated Multiple Views to Support Image Retrieval

The number of images available has grown over the years, as well as the number of techniques to aid to organizing and retrieving from image collections. Techniques and systems have been proposed to recover images based on query, in which an image (or words) is used as input parameter and a list of similar images (or images with related text content) is recovered. However, understanding how the retrieved images are related to each other remains as a problem. This paper proposes an approach based on multidimensional visualization and coordination techniques to show the relationship from retrieved images. In this approach, coordination techniques are employed to perform image retrieval methods and highlight the results in visual representations, showing how retrieved images are relate. To evaluate our proposal image collections with and without textual annotations related to each image were used, and also image retrieval mechanisms based on distance, topic and semantic to retrieve images from distinct and multimodal datasets.

Using Otsu's Threshold Selection Method for Eliminating Terms in Vector Space Model Computation

Visualization techniques have proved to be valuable tools to support textual data exploration. Dimensionality reduction techniques have been widely used to produce visual representation of document collections. Focusing on multidimensional projection techniques, good visual results are produced depending on how representative terms to discriminate the documents are chosen to compose the vector space model (VSM). To define a good VSM it is necessary to apply filters during the preprocessing in order to eliminate terms using their frequency. For that, the user must evaluate the term frequency histogram based on his/her expertise in the text subject and decide the threshold value for frequency cut. Usually it is a trial and error approach that requires the user to verify the quality of visual representation after each trial. In this paper, we propose an automatic approach that applies the Otsus Threshold Selection Method for computing a threshold using a term frequency histogram. We conducted experiments that have shown our approach generates visual representations as good as those generated with a threshold obtained by trial and error approach. The contribution of our approach is that users with non expertise are able to generate good visual representations and the time to get a good threshold is decreased.

Teaching and learning software project management: A hands-on approach

Project management is an essential activity across several areas, including Software Engineering. Through good management it is possible to achieve deadlines, budgets goals and mainly delivering a product that meets customer expectations. Project management activity encompasses: measurement and metrics; estimation; risk analysis; schedules; tracking and control. Considering the importance of managing projects, it is necessary that courses related to Information Technology and Computer Science present to students concepts, techniques and methodology necessary to cover all project management activities. Software project management courses aim at preparing students to apply management techniques required to plan, organize, monitor and control software projects. In a nutshell, software project management focuses on process, problem and people. In this paper we proposed an approach to teaching and learning of software project management using practical activities. The intention of this work is to provide the experience of applying theoretical concepts in practical activities. The teaching and learning approach, applied since 2006 in a Computer Science course, is based on teamwork. Each team is divided into groups assuming different roles of software process development. We have set four groups, each one assuming a different role (manager; software quality assurance; analyst and designer; programmer). The team must be conducted across the software process by its manager. We use four projects, each group is in charge of managing a different project. In this paper we present the proposed approach (based on hands on activities for project management); we summarize the lessons learned by applying the approach since 2006; we present a qualitative analysis from data collect along the application.

Supportive environment for teaching and learning digital image processing

Digital Image Processing (DIP) consists of a set of techniques to acquire, represent and transform digital images. Through these techniques, it is possible to extract and identify information of images and improve the visual quality by facilitating human perception and interpretation by computer systems. However, the Digital Image Processing teaching is hindered by the complexity of implementation of many techniques, on several occasions is not possible that student visualize the results of DIP techniques when are discussed during the course. This paper presents an experiment over a web platform to support the teaching of digital image processing. The goal of this platform is not replace coding techniques, but allow rapid visualization and experimentation of studied methods, without be necessary to install software or previous knowledge of a specific programming language.

Simplified Stress and Simplified Silhouette Coefficient to a Faster Quality Evaluation of Multidimensional Projection Techniques and Feature Spaces

Several multidimensional projection techniques have been proposed in literature over the last years. The quality of those techniques can be evaluated based on the dimensionality reduction or the clusters quality. The first evaluation aim to verify if the similarities from multidimensional space are preserved in projected space. While the second evaluation aim to verify if instances from a same class are placed in a same cluster in projected space. Respectively, Stress and Silhouette Coefficient are the main measures to quality evaluations. In this paper we present two new approaches -- named Simplified Stress and Simplified Silhouette Coefficient -- to speed up the computation of measures, enabling a faster evaluation of multidimensional projection techniques and feature spaces. We present experiments showing the high correlation between results obtained using original approaches and results obtained with those proposed in this paper. In addition, we show how to use Simplified Silhouette Coefficient to perform a fast feature space evaluation and selection.

Computational support for the process of software requirement specification

The software industry has become more and more concerned with the appropriate application of activities that composes requirement engineering as a way to improve the quality of its products. In order to support these activities, several computational tools have been available in the market, although it is still possible to find a lack of resources related to some activities. In this context, this paper proposes the inclusion of a module to aid in the requirements specification to a tool called Requirements Elicitation Support Tool. This module allows to specify requirements in accordance with IEEE 830 standard, thus contributing to the documentation of the requirements established for a software system, besides supporting the learning of concepts related to the requirements specification, which improves the skills of users of the tool.