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检索条件"主题词=Software algorithms"

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Extraction of Prediction Rules of Code Smell using Decision Tree Algorithm

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

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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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The Correlation between Modern International Trade and Business English Based on Computer software Analysis System

The Correlation between Modern International Trade and Busin...

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Information Technology and Computer Application (ITCA), International Conference on

作者： Qin Ying School of Foreign Languages Wuzhou University Wuzhou China

The relevance of modern international trade and business English is studied based on computer software analysis system. Combined with the characteristics of computer software analysis system, a forgetting law model is proposed based on business English knowledge learning. Based on the characteristics of modern international trade development, BP neural network prediction model is established to analyze the export goods data to promote the wide application of business English. Finally, the algorithm is used to test the subject. The results show that the program can obviously overcome the forgetting of words and improve the vocabulary level of students. Modern international trade not only promotes the development of the national industrial economy, but also promotes the application of business English in modern international trade.

关键词： International trade Vocabulary Computational modeling software algorithms Education Globalization Predictive models

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The Repeater with Global Positioning System for Cellular Communication

The Repeater with Global Positioning System for Cellular Com...

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Systems of Signals Generating and Processing in the Field of on Board Communications

作者： M. S. Lokhvitskiy O. A. Shorin Moscow Technical University of Communications and Informatics Moscow Russia NIRIT Moscow Russia

In cellular communication systems, the distance from base station to subscriber equipment is limited. In cases where this distance cannot be reduced, it is suggested to introduce a repeater using a location detection method, such as GPS, to increase the range. The distance between the nearest base station and the repeater maybe calculated by determining the coordinates of the repeater and the base station. By increasing the power of both the repeater and the base station transmitters, and changing the time advance, the repeater may be connected to the base station. The connection between the subscriber terminal and the base station is facilitated through the repeater.

关键词： Base stations Transmitters Communication systems software algorithms Handover Repeaters software

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A real-time correlational combination algorithm to improve SNR for multi-channel neural recordings

A real-time correlational combination algorithm to improve S...

引用

IEEE Asia-Pacific Conference on Circuits and Systems

作者： Liyang Wang Sio-Hang Pun Peng Un Mak Achim Klug Bai-Jun Zhang Mang I Vai Tim C. Lei State Key Laboratory of Analog and Mixed-Signal VLSI Institute of Microelectronics University of Macau China University of Macau Macau China University of Colorado Aurora CO USA State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University Guangzhou China University of Colorado Denver CO USA

ISBN: (纸本)9781665439176

This paper presents a Correlational Combination (CC) algorithm and its hardware implementation to be used in future multi-channel real-time spike sorting systems. Preprocessing of neural spikes are required to eliminate duplication for neural spikes recorded from a neural probe with densely spaced recording channels. In this work, we proposed using Pearson's correlation to identify duplicated neural spikes and to combine them selectively to improve SNR for a representative spike prior to performing spike sorting. Other approaches (Single Selection and Average All) were also compared with simulated multi-channel neural spikes and CC has the highest SNR for both software and hardware implementations. A hardware implementation of the CC algorithm was realized with a Xilinx Zynq-UltraScale+ field programmable gate array (FPGA). A SNR improvement of 93% was achieved when compared to the other approaches. A processing latency of $1.58 \mu s$ for the CC hardware module was achieved when a 250MHz system clock was used to drive the FPGA.

关键词： Correlation software algorithms Hardware Real-time systems software Classification algorithms Probes

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Priority Based VM Allocation and Bandwidth Management in SDN and Fog Environment

Priority Based VM Allocation and Bandwidth Management in SDN...

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Mahmoud Al Ahmad Sudhansu Shekhar Patra Suman Bhattacharya Suchismita Rout Sachi Nandan Mohanty Subham Choudhury Rabindra K. Barik School of Computer Engineering KIIT Deemed to be University Bhubaneswar India School of Computer Applications KIIT Deemed to be University Bhubaneswar India KIIT Deemed to be University Bhubaneswar India Silicon Institute of Technology Bhubaneswar India College of Engineering Pune Pune India SRM Institute of Science and Technology Ramapuram India

Nowadays, fog assisted cloud is a dominant field of computing where data centers are engaged in providing services to various applications having distinct resource needs and priorities. Congestion in the network causes performance degradation in the applications. Some mission-critical applications need to data transfer even during the congestion period. In software Defined Networks (SDN) clouds, there is a possibility of reconfiguration of the network flows dynamically to avoid such congestions for critical applications. In this paper, a priority-based virtual machine (VM) placement algorithm is proposed which takes care of the hosts and the network configuration. It tries to place the VMs of high-priority applications closely connected to hosts for reducing the network congestion caused by the other applications. The needed bandwidth for the critical applications is also managed by implementing a priority queue on each network device taken care of by SDN controller. The experiment shows that in multi-tenant applications, the proposed combined approach solves the purpose of high priority applications by allocating sufficient resources and meeting the Quality of Service (QoS) requirements.

关键词： Degradation Cloud computing Heuristic algorithms software algorithms Mission critical systems Quality of service Bandwidth

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Design of a university English micro-course system based on mobile learning mode

Design of a university English micro-course system based on ...

引用

International Conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Ning Fang Shandong Institute of Commerce and Technology Jinan 250103

Mobile teaching is the current development trend of English teaching. The traditional English teaching system has low load capacity due to the design defects of hardware, and it cannot be targeted to teach and stimulate students' learning interest when it is actually applied. To address the above problems, we design a university English micro-course system based on mobile learning mode. After optimizing the resource calling instruction memory and system communication connection port in the hardware part of the system, the system software part integrates English micro-lesson resources and recommends teaching resources by using collaborative filtering algorithm to complete the system design. The comparison experimental results show that the carrying capacity of the system is improved by about 53%, and the actual use can effectively improve students' English learning ability.

关键词： Ports (computers) Mechatronics Filtering Collaborative filtering Education software algorithms Market research

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Analysis and Simulation of Maximum Power Point Tracking Based on Gradient Ascent Method

Analysis and Simulation of Maximum Power Point Tracking Base...

引用

Renewable Engineering Conference (IREC), International

作者： Hani Muhsen Ihab Tanninah German Jordanian University Amman Jordan

ISBN: (纸本)9781665447010

This paper aims to implement the gradient ascent algorithm for maximum power point tracking (MPPT) in a photovoltaic (PV) system. The proposed MPPT algorithm will ensure the PV module's operation at the maximum power point by finding the optimal duty cycle that corresponds to each time step. The gradient ascent algorithm is an iterative method, and it is one of the most popular machine learning optimization algorithms. The gradient ascent is used for the first-order optimization, which means it only takes the first derivative into account when doing the parameter updates. On each iteration, the parameters have been changed in the opposite direction of the objective function gradient. Steps proportional to the positive gradient have been applied to find a local maximum of the function. This function has been implemented in a PV model to investigate the gradient ascent algorithm's applicability as an MPPT algorithm under various conditions.

关键词： Maximum power point trackers Photovoltaic systems Machine learning algorithms software packages software algorithms Machine learning Minimization

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On the Optimality of Backward Regression: Sparse Recovery and Subset Selection

On the Optimality of Backward Regression: Sparse Recovery an...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Sebastian Ament Carla Gomes Cornell University Ithaca NY

Sparse recovery and subset selection are fundamental problems in varied communities, including signal processing, statistics and machine learning. Herein, we focus on an important greedy algorithm for these problems: Backward Stepwise Regression. We present novel guarantees for the algorithm, propose an efficient, numerically stable implementation, and put forth Stepwise Regression with Replacement (SRR), a new family of two-stage algorithms that employs both forward and backward steps for compressed sensing problems. Prior work on the backward algorithm has proven its optimality for the subset selection problem, provided the residual associated with the optimal solution is small enough. However, the existing bounds on the residual magnitude are NP-hard to compute. In contrast, our main theoretical result includes a bound that can be computed in polynomial time, depends chiefly on the smallest singular value of the matrix, and also extends to the method of magnitude pruning. In addition, we report numerical experiments highlighting crucial differences between forward and backward greedy algorithms and compare SRR against popular two-stage algorithms for compressed sensing. Remarkably, SRR algorithms generally maintain good sparse recovery performance on coherent dictionaries. Further, a particular SRR algorithm has an edge over Subspace Pursuit.

关键词： Greedy algorithms Machine learning algorithms Dictionaries software algorithms Signal processing algorithms Signal processing Sparse matrices

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A Learning-to-Rank Based Approach for Improving Regression Test Case Prioritization

A Learning-to-Rank Based Approach for Improving Regression T...

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Asia-Pacific Conference on software Engineering

作者： Chu-Ti Lin Sheng-Hsiang Yuan Jutarporn Intasara National Chiayi University Chiayi Taiwan Faculty of Science and Technology Suratthani Rajabhat University Surat Thani Thailand

ISBN: (纸本)9781665437851

Many prior studies with attempt to improve regression testing adopt test case prioritization (TCP). TCP generally arranges the execution of regression test cases according to specific rules with the goal of revealing faults as early as possible. It is noted that different TCP algorithms adopt different metrics to evaluate test cases' priority so that they may be effect at revealing faults early in different faulty programs. Adopting a single metric may not generally work well. In this decade, learning-to-rank (LTR) strategies have been adopted to address some software engineering problems. This study also uses a pairwise LTR strategy XGBoost to combine several existing metrics so as to improve TCP effectiveness. More specifically, we regard the metrics adopted by TCP techniques to evaluate test cases' priority as the features of the training data and adopt XGBoost to learn the weights of the combined metrics. Additionally, in order to avoid overfitting, we use a fuzzy inference system to generate additional features for data augmentation. The experimental results show that our approach achieves more excellent effectiveness than the existing TCP techniques with respect to the selected subject programs.

关键词： Measurement Fuzzy logic software algorithms Training data software engineering Testing

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A Point-of-Care Device for Sensitive Protein Quantification

A Point-of-Care Device for Sensitive Protein Quantification

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IEEE International Symposium on Circuits and Systems

作者： Francesca Romana Cavallo Khalid B. Mirza Sara de Mateo Jesus Rodriguez Manzano Konstantin Nikolic Christofer Toumazou Centre for Bio-Inspired Technology Imperial College London United Kingdom Department of Infectious Disease Imperial College London UK Dept. of Biotechnology and Medical Engineering National Institute of Technology Rourkela India Imperial College London London UK School of Computing and Engineering University of West London London UK

In this paper we present the design of a new point-of-care device for protein quantification. The proposed design is based on a novel aptamer-mediated methodology and real time polymerase chain reaction (RT-PCR), a robust and ultrasensitive method for DNA amplification, which we employ for very sensitive quantification of proteins. In addition, we have also developed an algorithm for the processing of raw fluorescence data from the portable RT-PCR device. The algorithm leads to better linearity than a proprietary software from a commercially available RT-PCR machine. The modular nature of the system allows for easy assembly and adjustment towards a variety of biomarkers for applications in disease diagnosis and personalised medicine.

关键词： Proteins software algorithms Point of care Fluorescence Biomarkers software Medical diagnosis

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