The most analyses of wire ropes are based on the well known classical treatise on elasticity by Love in 1944. A general theory of thin rods are included and investigated extensively. General equilibrium equations of a...
The most analyses of wire ropes are based on the well known classical treatise on elasticity by Love in 1944. A general theory of thin rods are included and investigated extensively. General equilibrium equations of a thin rod on arc length are derived and presented. The analytical and numerical solutions of wire ropes are based on the equilibrium equations as the starting point for the solutions in most of the papers. Helical rod model is first introduced by Phillips and Costello based on the equilibrium equations given by Love. General nonlinear equilibrium equation solution of the straight wire strand is given in this study and showed that it is harmonious with the results presented by Costello.
In software engineering domain, SPC is currently utilized only by organizations which have high maturity levels according to the process improvement models like ISO/IEC 15504 and CMMI. In this paper, we present a soft...
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(纸本)9788976416094
In software engineering domain, SPC is currently utilized only by organizations which have high maturity levels according to the process improvement models like ISO/IEC 15504 and CMMI. In this paper, we present a software tool that we developed to ease and enhance application of SPC especially for emergent organizations. Our tool has facilities to assess the suitability of software processes and metrics for SPC as well as to analyze a software process with respect to its qualifying metrics using SPC techniques like control charts, histograms, bar charts, and pareto charts. In this paper we explain the tool by means of a bug-fixing process of a system and software development organization.
We describe recruitment and selection procedures of the Computer Science, Engineering, and Mathematics Scholarship (CSEMS) program at the University of Wisconsin-Milwaukee that are designed to attract students who are...
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This paper presents a novel approach to the task of automatic music genre classification which is based on multiple feature vectors and ensemble of classifiers. Multiple feature vectors are extracted from a single mus...
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This paper presents a novel approach to the task of automatic music genre classification which is based on multiple feature vectors and ensemble of classifiers. Multiple feature vectors are extracted from a single music piece. First, three 30-second music segments, one from the beginning, one from the middle and one from end part of a music piece are selected and feature vectors are extracted from each segment. Individual classifiers are trained to account for each feature vector extracted from each music segment. At the classification, the outputs provided by each individual classifier are combined through simple combination rules such as majority vote, max, sum and product rules, with the aim of improving music genre classification accuracy. Experiments carried out on a large dataset containing more than 3,000 music samples from ten different Latin music genres have shown that for the task of automatic music genre classification, the features extracted from the middle part of the music provide better results than using the segments from the beginning or end part of the music. Furthermore, the proposed ensemble approach, which combines the multiple feature vectors, provides better accuracy than using single classifiers and any individual music segment.
Nucleic acid based analysis has an important role to play in many critical applications such as medical diagnostics,environmental monitoring and food safety *** the available analytical tools,real time polymerase chai...
Nucleic acid based analysis has an important role to play in many critical applications such as medical diagnostics,environmental monitoring and food safety *** the available analytical tools,real time polymerase chain reaction(PCR)has been widely adopted as a viable technique for rapid detection and quantification of trace nucleic acid analytes[1].One challenge to
The accumulation of genomic and proteomic data of many organisms presents an opportunity to analyze entire phylogenetic trees in a systematic, quantified manner. The universal tree of life, constructed by genomic data...
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Various clustering methods are applied to characterizing gene expression data from DNA microarrays. However, to elucidate functional dependencies of genes analysis of their associations is important. The REVerse Engin...
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Various clustering methods are applied to characterizing gene expression data from DNA microarrays. However, to elucidate functional dependencies of genes analysis of their associations is important. The REVerse Engineering ALgorithm (REVEAL) was developed for analyzing the functional dependencies. Although the algorithm has been tested using binary models of genetic networks, it remains unclear how the method or similar technology will operate with systems of continuous variables. In this study, first, the REVEAL was examined using noisy, continuous data and the results suggested that its application to such data required considerable refinement of the algorithm. Then a new implementation method of REVEAL was proposed. This implementation method was tested through numerical experiments. The results of the simulations demonstrated the potential of the proposed method for extracting gene associations.
Accurate base-assignment in repeat regions of a whole genome shotgun assembly is an unsolved problem. Since reads in repeat regions cannot be easily attributed to a unique location in the genome, current assemblers ma...
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There has been a steady increase in the use of mobile computing, especially with appliances such as sensors. The main challenge in this scenario is to increase network sensor lifetime. Cluster computing integration wi...
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There has been a steady increase in the use of mobile computing, especially with appliances such as sensors. The main challenge in this scenario is to increase network sensor lifetime. Cluster computing integration with wireless sensor networks can represent an interesting answer for high-performance computing to monitor several environments. Computational resources available from cluster configurations are cost effective components to improve several classes of applications in many organizations. Scientific, industrial and commercial applications are more relying on cluster performance. OSCAR is a useful open software approach to manage cluster of workstations. In this article, we present a middleware design and implementation that integrates an OSCAR cluster configuration with a wireless sensor network environment.
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