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检索条件"主题词=Software Algorithms"

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Research on generation algorithm of SOA-oriented integration test order

Research on generation algorithm of SOA-oriented integration...

引用

IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Bingqing Zhang Gaolei Yi Yichen Wang Qi Fei BeiHang University Jiangsu Automation research institute

ISBN: (纸本)9781665478373

The generation of integration test order is an important issue in the research of software integration testing. A reasonable test order can improve the efficiency of integration testing and effectively reduce the cost of testing. The architectural complexity of the Service-Oriented Architecture and the complex coupling relationship between services make it difficult for traditional top-down and bottom-up integration test strategies to generate the best integration test order. Therefore, the paper proposes a test priority algorithm oriented to the TDG(test dependency graph) to represent the importance of integration testing between service software, and a genetic algorithm is designed to generate optimal integrated test order with the optimization goal of reducing test costs. Finally, through examples demonstrate the feasibility and validity of the method. The example results show that the method can generate integration test order that allows service software with a relatively high test priority to be integrated first and has a lower test cost.

关键词： Costs Heuristic algorithms software algorithms Sociology Computer architecture software Service-oriented architecture

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Dynamic Vehicle Routing for Battery Swapping in an Electric Bike-sharing System

Dynamic Vehicle Routing for Battery Swapping in an Electric ...

引用

IEEE International Conference on Industrial Engineering and Engineering Management

作者： Yi Yang Yaoming Zhou Tanmoy Kundu Suxiu Xu Shanghai Jiao Tong University Shanghai China The Logistics Institute - Asia Pacific National University of Singapore Singapore School of Management Jinan University Guangzhou China

ISBN: (纸本)9781665437721

In the daily operation of the emerging electric bike-sharing system, timely and efficient battery swapping is essential as there are no charging facilities at e-bike stations. This paper deals with the path planning of the trucks for battery swapping, considering dynamic battery demands at different stations. This problem is modeled as a vehicle routing problem with intermediate stops and soft time windows. A new solution method combining a dynamic planning strategy and a multiple neighborhood search algorithm is proposed to solve the problem. Numerical results on benchmark instances and a real-world case prove the effectiveness of our model and method.

关键词： Heuristic algorithms software algorithms Vehicle routing Transportation Search problems software Batteries

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Co-op Training: a Semi-supervised Learning Method for Data Streams

Co-op Training: a Semi-supervised Learning Method for Data S...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Paulo Martins Monteiro Elvys Soares Roberto Souto Maior de Barros Centro de Informática (CIn) Universidade Federal de Pernambuco (UFPE) Cidade Universitária Recife PE Brazil Instituto Federal de Educação Ciência e Tecnologia de Alagoas (IFAL) Maceió AL Brazil

ISBN: (纸本)9781665442084

Applying Machine learning algorithms to data streams is a challenging task because traditional strategies suppose datasets to be labeled, finite and stationary. In the context of data streams, where the data is generated in real-time and the labels may be missing due to the high cost of the labeling process, the proposal of semi-supervised learning (SSL) strategies to learn from labeled and unlabeled data at the same time seems to be a viable solution, despite also being challenging. In this paper, we present a novel approach to handle missing labels for classification learning in data streams, named co-op training, which is based on self-training incremental and co-training. In a controlled experiment, we execute the proposed algorithm, along with most well-known semi-supervised learning strategies, in 11 artificial and real-world datasets, and compare the results. We found our strategy to be more accurate than the other SSL algorithms in most datasets, also presenting better run-times when accuracies were similar. These methods are implemented in the Massive Online Analysis (MOA) open-source software as an internal benchmark component, to help researchers to run experimental comparisons on semi-supervised learning on data streams easily.

关键词： Training Costs Machine learning algorithms software algorithms Semisupervised learning Real-time systems Proposals

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Amplitude Recovery of Saturated Sinusoidal Signals

Amplitude Recovery of Saturated Sinusoidal Signals

引用

IEEE SENSORS

作者： R Abhishek Shankar Mohit Singh Bunghoo Jung School of Electrical and Computer Engineering Purdue University

A commonly encountered problem in sensing circuits is the saturation of sinusoidal signals. This arises due to limitations in the gain and operating voltage of analog circuits. A simple and novel method is presented here for recovering the amplitude of signals that have been clipped or saturated. The method is based on keeping track of the number of sample points that are not saturated and then relating it to the amplitude of the signal. The method shows high linearity up to 30 times the saturation voltage as found from simulation. The method can also be used to recover the amplitudes of non-sinusoidal but periodic signals.

关键词： Analytical models Microcontrollers Filtering software algorithms Linearity Voltage Dynamic range

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Mass-ratio-variance based Outlier Factor

Mass-ratio-variance based Outlier Factor

引用

International Joint Conference on Computer Science and software Engineering (JCSSE)

作者： Phichapop Changsakul Somjai Boonsiri Krung Sinapiromsaran Faculty of Science Chulalongkorn University Bangkok Thailand

An outlier of a finite dataset in statistics is defined as a data point that differs significantly from others. It is normally surrounded by a few data points while normal ones are engulfed by others. This behavior leads to the proposed outlier factor called Mass-ratio-variance Outlier Factor (MOF). A score is assigned to a data point from the variance of the mass-ratio distribution from the rest of data points. Within a sphere of an outlier, there will be few data points compared with a normal one. So, the mass-ratio of an outlier will be different from that of a normal data point. The algorithm to generate MOF requires no parameter and embraces the density concept. Experimental results show that top-10 highest scores from MOF could identify all outliers from synthesized datasets similar to those scores from the state-of-the-art outlier scoring methods such as LOF and FastABOD. Moreover, it could retrieve more outliers from three real World datasets.

关键词： Computer science software algorithms Clustering algorithms Ionosphere software engineering

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Parameter Identification of DC Motor Drive Systems using Particle Swarm Optimization

Parameter Identification of DC Motor Drive Systems using Par...

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International Conference on Engineering and Emerging Technologies (ICEET)

作者： Ishaq Hafez Rached Dhaouadi Mechatronics Engineering Graduate Program College of Engineering American University of Sharjah Sharjah United Arab Emirates College of Engineering American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781665427159

Accurate parameter estimation is of increasing importance in system modeling and control of highperformance motor drive systems. The inaccurate calculation or assumption of the system modal parameters may cause instability and/or bias control performance. This work presents the mathematical modeling, simulation, and experimental study to estimate the mechanical parameters of a two-mass-model system in DC motor drives using Artificial Swarm Intelligence. The electrical parameters such as resistance and inductance are usually provided by the DC motor manufacturer. However, the mechanical parameters such as the moment of inertia, and viscous friction will vary when the motor is connected to a mechanical load for a given application. Computer modeling and parameter estimation of the system were carried out using MATLAB/Simulink software. The parameters estimation of the mechanical side of a DC Motor drive system will be converted into an optimization problem using an objective function. The standard PSO algorithm is compared to the proposed modified PSO algorithms in the literature.

关键词： Chaos Motor drives Parameter estimation Heuristic algorithms software algorithms DC motors Search problems

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Effect of Optimal Energy Management Strategy on Parallel Hybrid Electric Vehicle Performances

Effect of Optimal Energy Management Strategy on Parallel Hyb...

引用

IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Marwa Ben Ali Ghada Boukettaya University of Gabes National School of Engineering Gabes Tunisia University of Sfax Natinal School of Enginnerenig Sfax Tunisia

Currently, electric vehicles (EV) has become an adequate alternative to the conventional vehicle (CV) for many consumers in the world. However, in Tunisia, it is not yet time for plug-in electric vehicles (PEV) depending on the lack of charge station parks and intelligent infrastructure. Hybrid electric vehicles (HEV) are an adequate answer for this situation. HEV is not pure clean vehicles, and various efforts are taken to develop optimal energy management of electric and thermal torques for a parallel HEV. Therefore, this paper presents a comparison study between HEV, EV, and CV performances, their limited and perspective propagation generally in the world and mainly in Tunisia. As an application of an optimal energy management study, we opt for the adaptive particle swarm optimization (APSO) algorithm to investigate the maximum fuel consumption economy and lower CO2 emission for a known drive cycle. Here, the presented algorithms were used to find out the optimum energy flow between two power sources. Thus, a detailed economic analysis that involves components of electric charge and fuel consumption costs were also presented. The economic formulation problem will be, then, implemented using MATLAB/SIMULINK software, and the simulation results were discussed.

关键词： Economics software packages Simulation software algorithms Propulsion Thermal management Hybrid electric vehicles

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CloudPin: A Root Cause Localization Framework of Shared Bandwidth Package Traffic Anomalies in Public Cloud Networks

CloudPin: A Root Cause Localization Framework of Shared Band...

引用

International Symposium on software Reliability Engineering (ISSRE)

作者： Shize Zhang Yunfeng Zhao Jianyuan Lu Biao Lyu Shunmin Zhu Zhiliang Wang Jiahai Yang Lin He Jianping Wu Tsinghua University China Alibaba Group China Peng Cheng Laboratory China

ISBN: (纸本)9781665425889

Due to the sharing nature of public cloud, most of the cloud services use a sharing bandwidth package (sBwp) model to conduct inbound/outbound communication. The sBwp model allows users to purchase a sharing bandwidth for plenty of virtual machines instead of purchasing bandwidth for each virtual machine separately. The advantage of sBwp is that it can provide users with convenient configuration and lower economic cost. However, the sBwp model brings new challenges for operators to localize the root cause of traffic anomalies of a sharing bandwidth, especially for a globally distributed large-scale public cloud with millions of users. In this paper, we first formalize the sBwp problem on the cloud and propose CloudPin, a root cause localization framework for this problem. Our framework solves all the challenges by employing a multi-dimensional algorithm with three sub-models of prediction deviation, anomaly ampli-tude, and shape similarity, and an overall ranking algorithm. Evaluations on real-world data, from one of the world-renowned public cloud vendors, show that our algorithm precision reaches 97.8% for the top 1 of the ranking list, outperforming multiple baseline algorithms.

关键词： Location awareness Cloud computing Costs Shape software algorithms Bandwidth Prediction algorithms

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Analysis of an Efficiency of Parallelization of algorithms Running on Computing Cluster Based on Single-Board Diskless Computers Raspberry PI 3 Model B

Analysis of an Efficiency of Parallelization of Algorithms R...

引用

IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Aleksandr B. Vavrenyuk Darya V. Matveeva Nikita M. Lukyantsev Victor V. Makarov National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) Moscow Russia

ISBN: (数字)9781665404761

ISBN: (纸本)9781665446426

This article is devoted to the analysis of parallelization efficiency of algorithms for solving linear systems of equations. The article presents an assessment of the quality of optimization of two algorithms for distributing the computational load between cluster nodes. The hardware is a computing cluster based on single-board computers with Linux Debian 8 as an operation system. Hydra Process Manager with an Slurm resource manager that implements a queue for multi-user access to the system is used to run and debug parallel tasks. The resulting system is planned to be used in the future in the educational process of MEPhI (Moscow Engineering Physics Institute) for a laboratory workshop on parallel computing.

关键词： Computers Conferences software algorithms Clustering algorithms Parallel processing Task analysis Testing

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Extraction of Prediction Rules of Code Smell using Decision Tree Algorithm

Extraction of Prediction Rules of Code Smell using Decision ...

引用

Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON)

作者： Pravin Singh Yadav Seema Dewangan Rajwant Singh Rao Guru Ghasidas Vishwavidyalaya Bilaspur India

ISBN: (纸本)9781665426879

Code Smell is a set of information of a source code that indicates any serious problem in the software. To detect the code smell prediction rule, we have applied a Decision tree algorithm. For this objective, we have taken two code smell datasets namely Blob-class and Data-class from Fontana et al. These datasets were prepared from 74 open-source systems. To calculate the performance measurement of the decision tree model on each dataset, we applied 5-fold cross-validation that divides datasets into training set and testing set and further splitting the training set into two part, one part is used for training and second part is used for validation. We have applied grid search for hyper-parameter tuning followed by extraction of decision rules to detect code smell instances. We have achieved the highest accuracy of 97.62% in both class predictions.

关键词： Training Codes software algorithms Microwave communication Prediction algorithms Microwave theory and techniques Decision trees

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