Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach

The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.

Multi-relational algorithm for mining association rules in large databases

Multi-relational data mining enables pattern mining from multiple tables. The existing multi-relational mining association rules algorithms are not able to process large volumes of data, because the amount of memory required exceeds the amount available. The proposed algorithm MRRadix presents a framework that promotes the optimization of memory usage. It also uses the concept of partitioning to handle large volumes of data. The original contribution of this proposal is enable a superior performance when compared to other related algorithms and moreover successfully concludes the task of mining association rules in large databases, bypass the problem of available memory. One of the tests showed that the MR-Radix presents fourteen times less memory usage than the GFP-growth. © 2011 IEEE.

Optimization of algorithm to identification of duplicate tuples through similarity phonetic based on multithreading

Aiming to ensure greater reliability and consistency of data stored in the database, the data cleaning stage is set early in the process of Knowledge Discovery in Databases (KDD) and is responsible for eliminating problems and adjust the data for the later stages, especially for the stage of data mining. Such problems occur in the instance level and schema, namely, missing values, null values, duplicate tuples, values outside the domain, among others. Several algorithms were developed to perform the cleaning step in databases, some of them were developed specifically to work with the phonetics of words, since a word can be written in different ways. Within this perspective, this work presents as original contribution an optimization of algorithm for the detection of duplicate tuples in databases through phonetic based on multithreading without the need for trained data, as well as an independent environment of language to be supported for this. © 2011 IEEE.

Optimization of query results in peer-to-peer database supported by semantics

The development of new technologies that use peer-to-peer networks grows every day, with the object to supply the need of sharing information, resources and services of databases around the world. Among them are the peer-to-peer databases that take advantage of peer-to-peer networks to manage distributed knowledge bases, allowing the sharing of information semantically related but syntactically heterogeneous. However, it is a challenge to ensure the efficient search for information without compromising the autonomy of each node and network flexibility, given the structural characteristics of these networks. On the other hand, some studies propose the use of ontology semantics by assigning standardized categorization of information. The main original contribution of this work is the approach of this problem with a proposal for optimization of queries supported by the Ant Colony algorithm and classification though ontologies. The results show that this strategy enables the semantic support to the searches in peer-to-peer databases, aiming to expand the results without compromising network performance. © 2011 IEEE.

A logical approach to the management of object identifiers in non-conventional database management systems

Non-conventional database management systems are used to achieve a better performance when dealing with complex data. One fundamental concept of these systems is object identity (OID), because each object in the database has a unique identifier that is used to access and reference it in relationships to other objects. Two approaches can be used for the implementation of OIDs: physical or logical OIDs. In order to manage complex data, was proposed the Multimedia Data Manager Kernel (NuGeM) that uses a logical technique, named Indirect Mapping. This paper proposes an improvement to the technique used by NuGeM, whose original contribution is management of OIDs with a fewer number of disc accesses and less processing, thus reducing management time from the pages and eliminating the problem with exhaustion of OIDs. Also, the technique presented here can be applied to others OODBMSs. © 2011 IEEE.

Spatial clustering applied to health area

The significant volume of work accidents in the cities causes an expressive loss to society. The development of Spatial Data Mining technologies presents a new perspective for the extraction of knowledge from the correlation between conventional and spatial attributes. One of the most important techniques of the Spatial Data Mining is the Spatial Clustering, which clusters similar spatial objects to find a distribution of patterns, taking into account the geographical position of the objects. Applying this technique to the health area, will provide information that can contribute towards the planning of more adequate strategies for the prevention of work accidents. The original contribution of this work is to present an application of tools developed for Spatial Clustering which supply a set of graphic resources that have helped to discover knowledge and support for management in the work accidents area. © 2011 IEEE.

Anfis applied to the prediction of surface roughness in grinding of advanced ceramics

This paper introduces a methodology for predicting the surface roughness of advanced ceramics using Adaptive Neuro-Fuzzy Inference System (ANFIS). To this end, a grinding machine was used, equipped with an acoustic emission sensor and a power transducer connected to the electric motor rotating the diamond grinding wheel. The alumina workpieces used in this work were pressed and sintered into rectangular bars. Acoustic emission and cutting power signals were collected during the tests and digitally processed to calculate the mean, standard deviation, and two other statistical data. These statistics, as well the root mean square of the acoustic emission and cutting power signals were used as input data for ANFIS. The output values of surface roughness (measured during the tests) were implemented for training and validation of the model. The results indicated that an ANFIS network is an excellent tool when applied to predict the surface roughness of ceramic workpieces in the grinding process.

Managing object identity with less I/O operations

Non-conventional database management systems are used to achieve a better performance when dealing with complex data. One fundamental concept of these systems is object identity (OID). Two techniques can be used for the implementation of OIDs: physical or logical. A logical implementation of OIDs, based on an Indirection Table, is used by NuGeM, a multimedia data manager kernel which is described in this paper. NuGeM Indirection Table allows the relocation of all pages in a database. The proposed strategy modifies the workings of this table so that it is possible to reduce considerably the number of I/O operations during the request and release of pages containing objects and their OIDs. Tests show a reduction of 84% in reading operations and a 67% reduction in writing operations when pages are requested. Although no changes were observed in writing operations during the release of pages, a 100% of reduction in reading operations was obtained. © 2012 IEEE.

Indicadores fisiológicos de estresse e expressão do gene hsp70 em juvenis do Pacu (Piaractus mesopotamicus) após implante de cortisol

Pós-graduação em Aquicultura - FCAV

Aprendizagem Baseada em Problemas (PBL – Problem-Based Learning): estratégia para o ensino e aprendizagem de algoritmos e conteúdos computacionais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Proposta para aumento da escalabilidade do sistema WSE-OS por meio do escalonamento de conexões e gerenciamento da replicação de dados dos servidores

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Help-me-Here: sistema para atendimento a chamada de emergência rápida e inteligente

This final paper is a reflection on mobile service of urgency by raising the main difficulties encountered by organizations, and seeking innovative solutions through new technological features like smartphones, tablets application and cloud computing to develop a scalable system and globalized, based on geolocation that is able to overcome this difficulty being accessible to the whole population

Análise do efeito de entropia em computação quântica: simulações em ambiente paralelo

Pós-graduação em Ciência da Computação - IBILCE

Ocorrências e distribuição de bactérias resistentes a metais pesados em sedimentos da Baía do Araça, São Sebastião (SP)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Teoria quântica da computação

This undergraduate thesis aims formally define aspects of Quantum Turing Machine using as a basis quantum finite automata. We introduce the basic concepts of quantum mechanics and quantum computing through principles such as superposition, entanglement of quantum states, quantum bits and algorithms. We demonstrate the Bell's teleportation theorem, enunciated in the form of Deutsch-Jozsa definition for quantum algorithms. The way as the overall text were written omits formal aspects of quantum mechanics, encouraging computer scientists to understand the framework of quantum computation. We conclude our thesis by listing the Quantum Turing Machine's main limitations regarding the well-known Classical Turing Machines