The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times s...
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ISBN:
(纸本)9781467363822
The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times specifically for embedded optimization problems with computational limitations. For reducing execution times we propose a hardware parallel architecture of the FA algorithm that facilitates the implementation in Field programmable Gate Arrays (FPGAs). In addition, this work proposes the application of the opposition-based learning (OBL) approach to the FA algorithm. The respective hardware implementation (HPOFA) was mapped into a Virtex5 FPGA device and numerical experiments using four well-known benchmark problems demonstrate that the opposition-based approach allows the FA algorithm to improve its functionality, preserving the swarm diversity and avoiding the premature convergence problem. Synthesis results point out that the HPOFA architecture is effectively mapped in hardware and is suitable for embedded applications.
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 1...
To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.
Rating and recommendation systems have become a popular application area for applying a suite of machine learning techniques. Current approaches rely primarily on probabilistic interpretations and extensions of matrix...
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ISBN:
(纸本)9781479931446
Rating and recommendation systems have become a popular application area for applying a suite of machine learning techniques. Current approaches rely primarily on probabilistic interpretations and extensions of matrix factorization, which factorizes a user-item ratings matrix into latent user and item vectors. Most of these methods fail to model significant variations in item ratings from otherwise similar users, a phenomenon known as the "Napoleon Dynamite'' effect. Recent efforts have addressed this problem by adding a contextual bias term to the rating, which captures the mood under which a user rates an item or the context in which an item is rated by a user. In this work, we extend this model in a nonparametric sense by learning the optimal number of moods or contexts from the data, and derive Gibbs sampling inference procedures for our model. We evaluate our approach on the Movie Lens 1M dataset, and show significant improvements over the optimal parametric baseline, more than twice the improvements previously encountered for this task. We also extract and evaluate a DBLP dataset, wherein we predict the number of papers co-authored by two authors, and present improvements over the parametric baseline on this alternative domain as well.
Information about several papers discussed at the 11th German Conference on Chemoinformatics (GCC) held November 8-10, 2015 sponsored by the Chemistry-Information-computer (CIC) division of the German Chemical Society...
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Information about several papers discussed at the 11th German Conference on Chemoinformatics (GCC) held November 8-10, 2015 sponsored by the Chemistry-Information-computer (CIC) division of the German Chemical Society is presented. Topics include accurate description of protein-ligand binding and its functional activity, combination of chemoinformatics and bioinformatics using three dimensional structure of amino acids, and Human Genome Project leading to advancement in drug discovery.
A step-based tutoring system for linear circuit analysis is being developed with the capabilities to automatically generate circuit problems with specified characteristics, including randomly generated topologies and ...
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A step-based tutoring system for linear circuit analysis is being developed with the capabilities to automatically generate circuit problems with specified characteristics, including randomly generated topologies and element values. The system further generates fully-worked, error-free solutions using the methods typically taught in such classes, and accepts a rich variety of student input such as equations, matrix equations, numerical and multiple-choice answers, re-drawn circuit diagrams, and sketches of waveforms. A randomized, controlled study was conducted using paid student volunteers to compare the effectiveness of two of our tutorials in comparison to working conventional textbook-based problems. The average learning gain was only 3/100 points for the textbook users, but 29/100 points, about 10 times higher, for the tutorial users. The effect size on the post-test scores was 1.21 pooled standard deviations (Cohen d-value) and was statistically significant. A motivational survey administered to these students yielded a 0.53 point higher rating for the software than for the textbook (on a 1-5 scale). The system is being used in Spring 2013 by over 340 students in EEE 202 at Arizona State and two community colleges. About 99% of these students rated the system as “very helpful” or “somewhat helpful”.
The context-awareness is a central aspect in the design of pervasive systems, characterizing their ability to adapt its structure and behavior. The context-aware exception handling (CAEH) is an existing approach emplo...
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Business processes are dynamic and constantly evolving. Contextual elements that had not yet been identified and represented can arise and influence the execution of each process instance in diverse manners. In this s...
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Software product lines, usually described using feature models, have proven to be a feasible solution to develop mobile and context-aware applications. These applications use con- text information to provide services ...
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ISBN:
(纸本)9781450313094
Software product lines, usually described using feature models, have proven to be a feasible solution to develop mobile and context-aware applications. These applications use con- text information to provide services and data for their users from anywhere and at any time. However, building feature models for mobile and context-aware software product lines demands advanced skills of software engineers, since it comprises system and context information. Moreover, to guarantee a correct application execution, these models must be thoroughly specified, composed and verified to check whether some composition and adaptation rules are violated. Although this is an important task, there is a lack of formalization of such rules, which makes it difficult to use those rules for feature models verification. In this paper, we propose an approach to prevent defects in context-aware feature models and in their product reconfiguration based on formal methods. To validate our work, we developed a prototype to check the correctness of context-aware feature models. Copyright 2012 ACM.
BPMN 2.0 is a widely used notation to model business process that has associated tools and techniques to facilitate process management, execution and monitoring. As a result using BPMN to model Software Development Pr...
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