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5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Optimizing All-to-All Collective Communication on Tianhe Supercomputer

Optimizing All-to-All Collective Communication on Tianhe Sup...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Jintao Peng Jie Liu Yi Dai Min Xie Chunye Gong National University of Defense Technology ChangSha China Science and Technology on Parallel and Distributed Processing Laboratory NUDT Changsha China Changsha and Laboratory of Software Engineering for Complex System NUDT Changsha China

All-to-all communication has a wide range of ap-plications in parallel applications like FFT. On most supercom-puters, there are multiple cores in a node. Message aggregation is an efficient method for smaller messages. Using multi-leader to aggregate message show significant improvement in intra-node overhead. However, compared to one-leader aggregation, existing multi-leader design incurs more message count and less aggregated message size. This paper proposes an Overlapped Multi-worker Multi-port all-to-all (OVALL) to scale the message size and parallelism of the aggregation algorithm. The algorithm exploits the all-to-all multi-core parallelism, concurrent commu-nication, and overlapping capabilities. Experiment results show that, compared to systems built-in MPI, OVALL'implementation achieves up to 5.9x or 18x speedup compared to MPI on different HPC systems. For the Fast Fourier Transform (FFT) application, OVALL is up to 2.7x (8192 cores, system A) or 5.6x (4800 cores, system B) faster compared to built-in MPI on peak performance.

关键词： Multicore processing Fast Fourier transforms Scalability Aggregates Supercomputers Libraries Pipeline processing

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DV-hop localization algorithm with cuckoo search

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Sensor Letters 2014年第2期12卷 444-447页

作者： Sun, Bin Cui, Zhihua Dai, Chaohua Chen, Weirong Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Shanxi China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu China School of Electric Engineering Southwest Jiaotong University Sichuan China

How to locate the nodes is an important problem for wireless sensor network. To solve it, many algorithms are proposed, and DV-Hop is one famous example. However, the location accuracy is not well for DV-Hop. Therefore, in this paper, cuckoo search (CS), a novel intelligent optimization algorithm, is incorporated into the methodology of DV-Hop to improve the performance. Simulation results show the proposed hybrid algorithm achieves better performance when compared with the standard DV-Hop. Copyright © 2014 American Scientific Publishers.

关键词： Sensor nodes

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Artificial plant optimization algorithm with dynamic local search for optimal coverage configuration

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Sensor Letters 2014年第1期12卷 118-122页

作者： Cui, Zhihua Liu, Wenjin Dai, Chaohua Chen, Weirong Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Shanxi 030024 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu 210093 China School of Electric Engineering Southwest Jiaotong University Sichuan 610031 China

Artificial plant optimization algorithm (APOA) is a novel stochastic population-based evolutionary algorithm by simulating the plant growing process. However, the exploitation capability of APOA is not enough. Therefore, in this paper, a new dynamic local search strategy is designed and incorporated into methodology of APOA. To illustrate the efficiency, this new variant is applied to solve the optimal coverage configuration problem in wireless sensor networks, simulation results show the validity of this variant. Copyright © 2014 American Scientific Publishers.

关键词： Stochastic systems

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An unsupervised deep learning framework for gene regulatory network inference from single-cell expression data

An unsupervised deep learning framework for gene regulatory ...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Guo Mao Jie Liu Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Laboratory of Software Engineering for Complex System National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China

Recent advances in single-cell RNA sequencing (scRNA-seq) technology provides unprecedented opportunities for reconstruction gene regulation networks (GRNs). At present, many different models have been proposed to infer GRN from a large number of RNA-seq data, but most deep learning models use a priori gene regulatory network to infer potential GRNs. It is a challenge to reconstruct GRNs from scRNA-seq data due to the noise and sparsity introduced by the dropout effect. Here, we propose GAALink, a novel unsupervised deep learning method. It first constructs the gene similarity matrix and then refines it by threshold value. It then learns feature representations of genes through a graphical attention autoencoder that propagates information across genes with different weights. Finally, we use gene feature expression for matrix completion such that the GRNs are reconstructed. Compared with seven existing GRNs reconstruction methods, GAALink achieves more accurate performance on seven scRNA-seq dataset with four ground truth networks. GAALink can provide a useful tool for inferring GRNs for scRNA-seq expression data.

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Multi-granularity dynamic analysis of complex software networks

Multi-granularity dynamic analysis of complex software netwo...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Bing Li Weifeng Pan Jinhu Lü State Key Laboratory Software Engineering and School Computer and Complex Network Research Center Wuhan University of China Wuhan China State Key Laboratory Software Engineering Wuhan University of China Wuhan China School Electrical Computer Engineering RMIT University Melbourne Australia Acad. Mathematics System Science Chinese Academy and Sciences Beijing China

software systems represent one of the most complex man-made systems. In this paper, we analyze the evolution of Object-Oriented (OO) software using complex network theory from a multi-granularity perspective. First, the software net works are constructed for a multi-version software system at different levels of granularity. Then, some parameters used in complex network theory are introduced to study the topological characteristics of these software networks. By investigating the parameters' values in consecutive software networks, we have a better understanding about software evolution. A case study on an open source OO project, Azureus, is conducted as an example to illustrate our approach. It uncovers some underlying dynamic characteristics of OO systems. These results provide a different dimension to our understanding of software system dynamics and also are very useful for the design and development of OO software systems.

关键词： Logic gates Communities US Department of Defense

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Portrait image segmentation based on improved grabcut algorithm 6th

Portrait image segmentation based on improved grabcut algori...

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6th International Conference on Swarm Intelligence, ICSI 2015 held in conjunction with the 2nd BRICS Congress on Computational Intelligence, CCI 2015

作者： Li, Shuai Zheng, Xiaohui Chen, Xianjun Zhan, Yongsong Key Laboratory of Cloud Computing and Complex System Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Experiment Center of Information Science Guilin University of Electronic Technology Guilin Guangxi541004 China Key Laboratory of Intelligent Processing of Computer Image and Graphics Guilin University of Electronic Technology Guilin Guangxi541004 China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin Guangxi541004 China Information Engineering School Haikou College of Economics Haikou Hainan571127

ISBN: (纸本)9783319204680

Traditional computer portrait caricature system mainly take the method that exaggerate and deform real images directly, that lead the facial image background also been deformed when exaggerate facial image. If in pretreatment stage, we segmented the characters and background of the input image, and then do the subsequent processing, the problem may be solved. But for better portrait caricature effects, we need an excellent segmentation algorithm. So, we propose an improved Grabcut image segmentation algorithm and use it to extract the prospect character image for exaggeration and deformation. In practical application, we separate deform and exaggerate the foreground characters image with TPS method, then fuse it with the original or new background picture, get the final image. Application proves, the method solves the background deformation problem well, and improves the quality and rate of image segmentation, caricature synthesis effect reality and natural. © Springer International Publishing Switzerland 2015.

关键词： Image segmentation

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A Model Based Heterogeneous Data Collaboration Method

A Model Based Heterogeneous Data Collaboration Method

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IEEE International Conference on Electronics and Communication engineering (ICECE)

作者： Junjie Xue Junhua Zhou Guoqiang Shi Yanhong Jiang Bowen Wei Hongyan Quan Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Simulation Center Science and Technology on Space System Simulation Laboratory Beijing China School of Software Engineering East China Normal University Shanghai China School of Computer Science and Technology East China Normal University Shanghai China

ISBN: (数字)9781728192581

ISBN: (纸本)9781728192598

Model based heterogeneous data collaboration is important in the integrated design and manufacturing technology. In this work, we propose a systematic method of collaborative design method for heterogeneous data sources. In our method, we use the Open Model Based engineering Environment (OpenMBEE) to study. In our work, we setup environment and construct the integrated multi-tools achieving consistency design, and then we successfully design and implement a reasonable scheme to parameterize the model in requirement analysis and store the extracted parameters in Model Management system (MMS) for transporting to the visualization tool for further simulation. We integrate the mathematical analysis tools of MATLAB, and successfully design the interface in the tool integration, and realize the model consistency in the problem of integrating multiple tools in the design based on model center. The effectiveness of the proposed integration strategies is verified by some practical instances. That is verified that our provided study can an effective design idea for complex production.

关键词： Analytical models Collaboration Production Tools Data models Mathematical model Matlab

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End-to-End AI-Based Point-of-Care Diagnosis system for Classifying Respiratory Illnesses and Early Detection of COVID-19

arXiv

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arXiv 2020年

作者： Belkacem, Abdelkader Nasreddine Ouhbi, Sofia Lakas, Abderrahmane Benkhelifa, Elhadj Chen, Chao Department of Computer and Network Engineering CIT UAEU UAE Department of Computer Science and Software Engineering CIT UAEU UAE Cloud Computing and Applications Reseach Lab Staffordshire University United Kingdom Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms, including coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases such as the recent COVID-19 pandemic. One of the factors that contributed to the spread of the pandemic, was the late diagnosis or confusing it with regular flu-like symptoms. Science has proved that one of the possible differentiators of the underlying causes of these different respiratory diseases is coughing, which comes in different types and forms. Therefore, a reliable lab-free tool for early and more accurate diagnosis that can differentiate between different respiratory diseases is very much needed. This paper proposes an end-to-end portable system that can record data from patients with symptom, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly solution can play an important part in the early diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

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RNA secondary structure prediction with guided binary-coded cuckoo search

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Journal of Bionanoscience 2014年第5期8卷 391-394页

作者： Sun, Bin Zhu, Zhuanghua Cui, Zhihua Dai, Chaohua Chen, Weirong Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology Shanxi030024 China Economic Information Department Shanxi Finance and Taxation College Shanxi030024 China State Key Laboratory for Novel Software Technology Nanjing University Jiangsu210093 China School of Electric Engineering Southwest Jiaotong University Sichuan610031 China

Cuckoo search algorithm (CS) is a new intelligent optimization algorithm inspired by the brood parasitism phenomenon. Due to the simple concepts and easy implementation, it has been applied to many applications. In this paper, a new variant, guided binary-coded cuckoo search with binarycoded manner, is designed by incorporating one guided search direction to enhance the local search capability. To investigate the performance, we apply it to predict the RNA secondary structure problem. Ten famous sequences are selected and compared with Mfold, simulation results show the validity. Copyright © 2014 American Scientific Publishers.

关键词： RNA

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