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检索条件"主题词=software algorithms"

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Scheduling algorithms for ultra-reliable execution of tasks under both hardware and software faults

Scheduling algorithms for ultra-reliable execution of tasks ...

引用

ACS/IEEE International Conference on Computer Systems and Applications

作者： O.A. Abulnaja S.H. Hosseini K. Vairavan King Abdulaziz University Jeddah Saudi Arabia University of Wisconsin Milwaukee Milwaukee WI USA

Summary form only given, as follows. We study the development of integrated fault-tolerant scheduling algorithms. The proposed algorithms ensure ultra-reliable execution of tasks where both hardware and software failures are considered, and system performance improvement. Also, the proposed algorithms have the capability for on-line system-level fault diagnosis.

关键词： software algorithms Scheduling algorithm Hardware Fault tolerance software performance System performance Fault diagnosis

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Hardware/software co-verification of cryptographic algorithms using Cryptol

Hardware/software co-verification of cryptographic algorithm...

引用

Formal Methods in Computer Aided Design (FMCAD)

作者： Levent Erkök Magnus Carlsson Adam Wick Galois Inc. Portland OR USA

Cryptol is a programming language designed for specifying cryptographic algorithms. Despite its high-level modeling nature, Cryptol programs are fully executable. Further, a large subset of Cryptol can be automatically synthesized to hardware. To meet the inherent high-assurance requirements of cryptographic systems, Cryptol comes with a suite of formal-methods based tools that enable users to perform various program verification tasks. In this paper, we provide an overview of Cryptol and its verification toolset, especially focusing on the co-verification of third-party VHDL implementations against highlevel Cryptol specifications. As a case study, we demonstrate the technique on two hand-written VHDL implementations of the Skein hash algorithm.

关键词： Cryptography Hardware software algorithms Safety Runtime Computer languages Algorithm design and analysis Availability Domain specific languages Arithmetic

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algorithms and software tools for LMI problems in control: an overview

Algorithms and software tools for LMI problems in control: a...

引用

IEEE International Symposium on Computer Aided Control System Design (CACSD)

作者： L. Vandenberghe V. Balakrishnan Information Systems Laboratory Electrical Engineering Department University of Stanford Stanford CA USA School of Electrical and Computer Engineering Purdue University West Lafayette IN USA

The purpose of this paper is to give an overview of recent developments in algorithms and software for linear matrix inequality (LMI) problems. We review the definition and some basic properties of the semidefinite programming (SDP) problem, and describe recent developments in interior point algorithms and available software. We conclude with some extensions of the SDP.

关键词： software algorithms software tools Linear matrix inequalities Linear programming Optimization methods Application software Matrix converters Control systems Information systems Laboratories

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Statistical algorithms and software for genomics

Statistical algorithms and software for genomics

引用

IEEE Annual International Computer software and Applications Conference (COMPSAC)

作者： T. Anantharaman B. Mishra Computer Science Department Courant Institute New York University NY USA

There are many large system problems that are hard to model exactly or in a computationally tractable fashion. Examples include the mapping of human DNA, speech recognition, and automated learning in computer chess. Traditional artificial intelligence solution techniques for such problems rely on a combination of custom encoding of expert knowledge and heuristic search. They take much time to hand craft and then often are unable to take advantage of faster computers as they become available. In this context, the authors explore the advantage of using statistical search techniques in which the knowledge is encoded in some form of statistical model whose parameters are automatically adjusted or trained with domain data. The benefits are faster development times, greater solution accuracy (compared to hand crafted solutions) and the ability to allow the problem size and desired solution accuracy to be scaled up with computational resources. They apply this approach to certain critical computational problems in mapping the human genome. They use a Bayesian model to provide the best solution accuracy as a function of the number of parameters. Heuristic search techniques derived from artificial intelligence are used to search the model space in an efficient manner in the average case.

关键词： software algorithms Genomics Bioinformatics Humans Artificial intelligence Speech recognition Learning DNA computing Encoding Context modeling

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Iterative decoding algorithms for real time software implementation in wireless communication systems

Iterative decoding algorithms for real time software impleme...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Y. Or G. Kutz A. Chass A. Gubeskys E. Pollak Motorola Semiconductor Israel Limited Herzliya Israel

Iterative decoding has emerged as one of the most promising techniques for improving receivers performance. This paper is focused on exploring the feasibility of software implementation of iterative decoding algorithms for the 2nd and 3rd generations of the cellular communications standards. Two examples for iterative decoding algorithms are described: turbo decoding for the 3G cellular standards and turbo equalization for a GSM receiver. The principles described can be used to efficiently construct and implement other iterative decoding algorithms.

关键词： Iterative decoding software algorithms Iterative algorithms Real time systems Communication system software Wireless communication GSM Detectors Application software Table lookup

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Applying Genetic algorithms for Optimizing Program Increment Planning in software Development Teams

Applying Genetic Algorithms for Optimizing Program Increment...

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International IEEE Conference on Intelligent Systems, IS

作者： Dimitar Lyubchev Angel Marchev Department of Management University of National and World Economy Sofia Bulgaria

ISBN: (数字)9798350350982

ISBN: (纸本)9798350350999

Effective and efficient Program Increment (PI) planning plays a pivotal role in enhancing collaboration and productivity within software development teams following the Agile way of working. This paper investigates the integration of Genetic algorithms (GAs) into the PI planning process to address the challenge of optimizing resource allocation. PI planning can be a complex and time-consuming process, requiring teams to balance numerous interdependent factors such as resource constraints, task urgency and importance, as well as team member availability. Genetic algorithms, inspired by the principles of natural selection, provide an alternative optimization technique that can explore a vast solution space and propose a number of possible and more efficient PI plans. By modeling the PI planning problem as a genetic algorithm, teams can leverage the algorithm's ability to rapidly converge on near-optimal solutions, leading to improved resource utilization, reduced planning time, and enhanced team alignment.

关键词： Decision making software algorithms Collaboration Manuals Planning Resource management Stakeholders Security Genetic algorithms software development management

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Development and evaluation of processor farm algorithms/software for robot sensing applications

Development and evaluation of processor farm algorithms/soft...

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IEEE Instrumentation and Measurement Technology Conference

作者： I. Dancea Dkpartement d'informatique Universite du Quebec a Hull Hull QUE Canada

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Comparison of Graph Clustering algorithms for Recovering software Architecture Module Views

Comparison of Graph Clustering Algorithms for Recovering Sof...

引用

(CSMR) European Conference on software Maintenance and Reengineering

作者： Roberto Almeida Bittencourt Dalton Dario Serey Guerrero Formal Methods Group-Department of Systems and Computing UFCG Federal University of Campina Grande Campina Grande Paraiba Brazil UEFS-State University of Feira de Santana Feira de Santana Bahia Brazil

In the domain of software architecture recovery, classical clustering algorithms have been used to recover module views, while new ones have been proposed to tackle specific software architecture issues. Nonetheless, little information concerning their empirical evaluation in this context is presently available. This paper presents an empirical study that evaluates four clustering algorithms according to three previously proposed criteria: extremity of cluster distribution, authoritativeness, and stability, which were measured against consecutive releases of four different systems. Our results suggest that the k-means algorithm performs best in terms of authoritativeness and extremity and that the modularization quality algorithm produces more stable clusters. They also point out that fully automated clustering techniques alone cannot recover module views in a sensible way, but may provide a reasonable first step to speed up an expert-assisted architecture recovery process.

关键词： Clustering algorithms software algorithms software architecture Partitioning algorithms Extremities Stability criteria Algorithm design and analysis software maintenance Data mining Computer architecture

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LVQPAK: A software package for the correct application of Learning Vector Quantization algorithms

LVQPAK: A software package for the correct application of Le...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： T. Kohonen J. Kangas J. Laaksonen K. Torkkola Laboratory of Computer and Information Science Helsinki University of Technology Espoo Finland

An overview of the software package LVQPAK, which has been developed for convenient and effective application of learning vector quantization algorithms, is presented. Two new features are included: fast conflict-free... 详细信息

关键词： software packages Application software Vector quantization software algorithms Packaging Laboratories Information science Pattern recognition Stochastic processes Personal communication networks

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Analyzing software change in open source projects using Artificial Immune System algorithms

Analyzing software change in open source projects using Arti...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Ruchika Malhotra Megha Khanna Department of Software Engineering Delhi Technological University Delhi India Delhi Technological University Delhi India Acharya Narendra Dev College University of Delhi Delhi India

Development of software change prediction models, based on the change histories of a software, are valuable for early identification of change prone classes. Classification of these change prone classes is vital to yield competent use of limited resources in an organization. This paper validates Artificial Immune System (AIS) algorithms for development of change prediction models using six open source data sets. It also compares the performance of AIS algorithms with other machine learning and statistical algorithms. The results of the study indicate, that the models developed, are effective means of predicting change prone classes in the future versions of the software. However, AIS algorithms do not perform better that machine learning and other statistical algorithms. The study provides conclusive results about the capabilities of AIS algorithms and reports whether there are any significant differences in the performance of different algorithms using a statistical test.

关键词： Prediction algorithms Measurement Accuracy software software algorithms Machine learning algorithms Algorithm design and analysis

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