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Towards informative tagging of code fragments to support the investigation of code clones

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arXiv 2021年

作者： Nishioka, Daisuke Kamiya, Toshihiro Department of Information Systems Design and Data Science Grad. Sch. of Natural Sci. & Tech. Shimane Univ. Matsue Japan Institute of Sci. & Eng. Shimane Univ Matsue Japan

Investigating the code fragments of code clones detected by code clone detection tools is a time-consuming task, especially when a large number of reference source files are available. This paper proposes (i) a method for clustering a clone class, which is detected by code clone detection tools using syntactic similarity, based on topic similarity by considering its code fragments as sequences of words and (ii) a method for assigning short tags to clusters of the clustering result. We also report an experiment of applying the proposed method to packages of an open source operating system. Copyright © 2021, The Authors. All rights reserved.

关键词： Cloning

Performance Analysis of SWIPT Networks over Composite Fading Channels

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Performance Analysis of SWIPT Networks over Composite Fading...

International Conference on Communications and Networking, ComNet

作者： Abubakar U. Makarfi Rupak Kharel Khaled M. Rabie Xingwang Li Osamah S. Badarneh Galymzhan Nauryzbayev Sultangali Arzykulov Omprakash Kaiwartya Manchester Metropolitan University Manchester UK Sch. of Physics and Electronic Information Engineering Henan Polytechnic University Jiaozuo China German-Jordanian University Amman Jordan Sch. of Engineering Nazarbayev University Astana Kazakhstan Sch. of Science and Tech. Nottingham Trent University Nottingham UK

ISBN: (数字)9781728153209

ISBN: (纸本)9781728153216

This paper studies the performance of dual-hop decode-and-forward (DF) simultaneous wireless information and power transfer (SWIPT) systems over Fisher-Snedecor F composite fading channels. We commence by deriving closed-form expressions of the cumulative distribution function (CDF) and the probability density function (PDF) of the product of two F random variables. These statistics are then used to derive closed-form expressions for the ergodic capacity and ergodic outage probability of the system under consideration. Three well-known energy harvesting (EH) relaying protocols are considered; namely time-switching relaying, power splitting relaying and ideal relaying receiver. The analysis provides insights into the effect of the key parameters on the overall network performance. Monte-Carlo simulations are provided throughout to validate the correctness of our analysis. The results show that the performance of the system in terms of ergodic capacity and outage probability improves as the fading and shadowing severity reduce for all EH protocols considered. The results further demonstrate the need to balance the relay distance with channel conditions of the links to minimise the system outage.

关键词： Fading channels Protocols Probability density function Power system reliability Relays Capacity planning Shadow mapping

On the distribution of GSVD

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arXiv 2019年

作者： Chen, Zhuo Ding, Zhiguo Key Lab of Wireless-Optical Commun. Chinese Acad. of Sciences Sch. Info Science & Tech. Univ. Science & Tech. China Hefei Anhui230027 Taiwan the School of Electrical and Electronic Engineering the University of Manchester Manchester United Kingdom

关键词： Singular value decomposition

Improving Clamping Accuracy of Thin-walled Workpiece in Turning Operation

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IOP Conference Series: Materials science and Engineering 2020年第1期751卷

作者： Ammar H. Elsheikh Jiajie Guo Kun Bai Kok-Meng Lee Production Engineering and Mechanical Design Department Tanta University Tanta 31527 Egypt. The State Key Laboratory of Digital Manufacturing and Equipment Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China. Woodruff Sch. of Mech. Eng. at Georgia Inst. of Tech. Atlanta GA 30332 USA.

This study presents theoretical and experimental error analysis and avoidance which results from the fixation of a thin-walled metal disk workpiece on a duplex turning machine. The distance between the rotating workpiece surface and a fixed datum point is measured using a laser displacement sensor (LDS). The measured data are analyzed numerically to get the error in the fixation system in terms of Euler angles. Then the workpiece clamping points are axially adjusted according to the calculated angles. Moreover, the problem formulation and the solution procedures are presented in details. Finally, a case study has been used to verify the proposed approach. The results indicate that the proposed tech.ique can be used to decrease the fixation error to a reasonable range.

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Asymptotic performance analysis of GSVD-NOMA systems with a large-scale antenna array

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arXiv 2018年

作者： Chen, Zhuo Ding, Zhiguo Dai, Xuchu sch.ber, Robert Key Lab of Wireless-Optical Commun. Chinese Acad. of Sciences Sch. Info Science & Tech. Univ. Science & Tech. China Hefei Anhui230027 China School of Computer and Communications Lancaster University LA1 4YW United Kingdom Institute for Digital Communications University Erlangen-Nürnberg Cauerstrasse 7 ErlangenD-91058 Germany

This paper considers a multiple-input multiple-output (MIMO) downlink communication scenario with one base station and two users, where each user is equipped with m antennas and the base station is equipped with n antennas. To efficiently exploit the spectrum resources, we propose a transmission protocol which combines generalized singular value decomposition (GSVD) and non-orthogonal multiple access (NOMA). The average data rates achieved by the two users are adopted as performance metrics for evaluation of the proposed GSVD-NOMA sch.me. In particular, we first characterize the limiting distribution of the squared generalized singular values of the two users' channel matrices for the asymptotic case where the numbers of transmit and receive antennas approach infinity. Then, we calculate the normalized average individual rates of the users in the considered asymptotic regime. Furthermore, we extend the proposed GSVD-NOMA sch.me to the MIMO downlink communication scenario with more than two users by using a hybrid multiple access (MA) approach, where the base station first divides the users into different groups, then the proposed GSVD-NOMA sch.me is implemented within each group, and different groups are allocated with orthogonal bandwidth resources. Finally, numerical results are provided to validate the effectiveness of the proposed GSVD-NOMA protocol, and the accuracy of the developed analytical results. Copyright © 2018, The Authors. All rights reserved.

关键词： Singular value decomposition

Dart: Domain-adversarial residual-transfer networks for unsupervised cross-domain image classification

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arXiv 2018年

作者： Fang, Xianghong Bai, Haoli Guo, Ziyi Shen, Bin Hoi, Steven Xu, Zenglin SMILE Lab Univ. of Electronic Sci and Tech.of China Chengdu Sichuan611731 China Dept Computer Science and Engineering Chinese University of Hong Kong Shatin N. T. Hong Kong SMILE Lab Sch. of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu Sichuan611731 China Google Inc. Singapore Management University

The accuracy of deep learning (e.g., convolutional neural networks) for an image classification task critically relies on the amount of labeled training data. Aiming to solve an image classification task on a new domain that lacks labeled data but gains access to cheaply available unlabeled data, unsupervised domain adaptation is a promising tech.ique to boost the performance without incurring extra labeling cost, by assuming images from different domains share some invariant characteristics. In this paper, we propose a new unsupervised domain adaptation method named Domain-Adversarial Residual-Transfer (DART) learning of Deep Neural Networks to tackle cross-domain image classification tasks. In contrast to the existing unsupervised domain adaption approaches, the proposed DART not only learns domain-invariant features via adversarial training, but also achieves robust domainadaptive classification via a residual-transfer strategy, all in an end-to-end training framework. We evaluate the performance of the proposed method for cross-domain image classification tasks on several well-known benchmark data sets, in which our method clearly outperforms the state-of-the-art approaches. Copyright © 2018, The Authors. All rights reserved.

关键词： Image classification

Functional Enhancer Elements Drive Subclass-Selective Expression from Mouse to Primate Neocortex

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SSRN

SSRN 2020年

作者： Mich, John K. Graybuck, Lucas T. Hess, Erik E. Mahoney, Joseph T. Kojima, Yoshiko Ding, Yi Somasundaram, Saroja Miller, Jeremy A. Weed, Natalie Omstead, Victoria Bishaw, Yemeserach Shapovalova, Nadiya V. Martinez, Refugio A. Fong, Olivia Yao, Shenqin Mortrud, Marty Chong, Peter Loftus, Luke Bertagnolli, Darren Goldy, Jeff Casper, Tamara Dee, Nick Opitz-Araya, Ximena Cetin, Ali Smith, Kimberly A. Gwinn, Ryder P. Cobbs, Charles Ko, Andrew L. Ojemann, Jeffrey G. Keene, C. Dirk Silbergeld, Daniel L. Sunkin, Susan M. Gradinaru, Viviana Horwitz, Gregory D. Zeng, Hongkui Tasic, Bosiljka Lein, Ed S. Ting, Jonathan T. Levi, Boaz P. Allen Institute for Brain Science SeattleWA United States Washington National Primate Research Center University of Washington. SeattleWA United States Depts. of Biol. and Appl. Phys. Stanford Univ. StanfordCA United States Dept. of Neurological Surgery Univ. of Wash. Sch. of Med. Regional Epilepsy Ctr Harborview Med. Ctr Seattle WA SeattleWA United States Dept. of Neurological Surgery Univ. of Wash. SeattleWA United States Dept. of Pathology Univ. of Wash. SeattleWA United States Dept. of Neurological Surgery Alvord Brain Tumor Center Univ. of Wash. SeattleWA United States Div. of Biol. and Biol. Engineering California Inst. of Tech. PasadenaCA United States Dept. of Physiology & Biophysics Univ. of Wash. SeattleWA United States Department of Pathology Department of Epilepsy Surgery and Functional Neurosurgery The Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment

Viral genetic tools to target specific brain cell types in humans and nongenetic model organisms will transform basic neuroscience and targeted gene therapy. Here we used comparative epigenetics to identify thousands of human neuronal subclass-specific putative enhancers to regulate viral tools, and 34% of these were conserved in mouse. We established an AAV platform to evaluate cellular specificity of functional enhancers by multiplexed fluorescent in situ hybridization (FISH) and single cell RNA sequencing. Initial testing in mouse neocortex yields a functional enhancer discovery success rate of over 30%. We identify enhancers with specificity for excitatory and inhibitory classes and subclasses including PVALB, LAMP5, and VIP/LAMP5 cells, some of which maintain specificity in vivo or ex vivo in monkey and human neocortex. Finally, functional enhancers can be proximal or distal to cellular marker genes, conserved or divergent across species, and could yield brain-wide specificity greater than the most selective marker genes. © 2020, The Authors. All rights reserved.

关键词： RNA

Towards Parallel Model Generation for Random Performance Testing of Model-Oriented Operations

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Towards Parallel Model Generation for Random Performance Tes...

Theoretical Aspects of Software Engineering (TASE)

作者： Xiao He Wenfeng Li Tian Zhang Yi Liu Sch. of Comput. & Commun. Eng. University of Science and Technology Beijing Beijing Beijing CN State Key Lab. for Novel Software Technol. Nanjing University Nanjing Jiangsu CN Coordination Center of China Nat. Comput. Network Emergency Response Tech. Team China

ISBN: (纸本)9781509017652

Model-oriented operations, such as model transformation, model query, and model comparison, are the core of Model-Driven Engineering. Their scalability becomes an important issue when they are to be applied in industry. Large-scale models, however, are not widely available, making it hard to test the performance and coverage of those operations without any bias. To do so, one must be able to generate large models, which are syntactically correct, as test inputs efficiently and randomly. This paper proposes a parallel approach to generating large random model, which improves on our previous sequential algorithm. First, the paper identifies the dependencies existing in the process of model generation, which hinders parallelization. Then, the paper proposes a partitioning strategy that is able to turn a sequential generation task into a series of parallelizable subtasks. Experimental results of performance are also presented, which show that the parallel approach proposed can reduce 50% time costs compared to the sequential one in most cases, while the correctness and the randomness of the models generated by this approach are kept.

关键词： Unified modeling language Object oriented modeling Syntactics Partitioning algorithms Testing Heuristic algorithms Computational modeling

Adaptive Flexible Antenna Array System for Deformable Wing Surfaces

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Adaptive Flexible Antenna Array System for Deformable Wing S...

IEEE Aerospace Conference

作者： Dimitris Anagnostou Mina Iskander Electrical & Computer Engineering South Dakota Sch. of Mines & Tech. Rapid City SD

A 4×1 coplanar and flexible antenna array for deformable surfaces is studied under different bending angles. It is assumed that the array is bent from one edge on top of an insulating cylinder (single-edge cylindrical bending). Due to flexing, the array radiates a tilted main beam. The beam can be redirected back toward its original direction by applying the correct phase difference between the elements. This compensation phase vector is calculated using a closed-form equation. Simulated results are presented, showing successful recovery of the intended radiation direction. The autonomous array can be used in unmanned aerial vehicles with wings that bend or flex on demand, morphing wings, adaptive wings, as well as on other surfaces where it is required to focus an antenna pattern toward a specific location with respect to the mounting surface.

关键词： Arrays Antenna radiation patterns Mathematical model Microcontrollers Adaptive arrays Strain