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A parallel approach of COFFEE objective function to multiple sequence alignment
(2015-09-21)
The computational tools to assist genomic analyzes show even more necessary due to fast increasing of data amount available. With high computational costs of deterministic algorithms for sequence alignments, many works ...
Performance improvement of genetic algorithm for multiple sequence alignment
(2016-07-02)
The multiple sequence alignment (MSA) is considered one of the most important tasks in Bioinformatics. Nevertheless, with the growth in the amount of genomic data available, it is essential the results with biological ...
Performance Improvement of Genetic Algorithm for Multiple Sequence Alignment
(Ieee, 2016-01-01)
The multiple sequence alignment (MSA) is considered one of the most important tasks in Bioinformatics. Nevertheless, with the growth in the amount of genomic data available, it is essential the results with biological ...
Comparative study of algorithms for mining association rules: Traditional approach versus multi-relational approach
(2011-12-01)
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 ...
Operating system support to an online hardware-software co-design scheduler for heterogeneous multicore architectures
(Chongqing UniversityIEEE Computer SocietySeção TaipeiChongqing, 2014-08-20)
This paper aims at designing and implementing a
scheduler model for heterogeneous multiprocessor architectures
based on software and hardware. As a proof of concept, the
scheduler model was applied to the Linux operating ...
Modular mathematical model for a low-speed maneuvering simulator
(ASMESan Francisco, 2014-06-08)
This paper presents the mathematical model of the real-time ship simulator for low-speed maneuvering developed by the University of São Paulo, Transpetro and Petrobras, with the technical collaboration of Brazilian Pilots ...
Combined active and semi-supervised learning using particle walking temporal dynamics
(Ieee, 2013-01-01)
Both Semi-Supervised Leaning and Active Learning are techniques used when unlabeled data is abundant, but the process of labeling them is expensive and/or time consuming. In this paper, those two machine learning techniques ...