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arXiv 2023年

作者： Cheng, Huqiang Xie, Mengying Yang, Xiaowei Lü, Qingguo Li, Huaqing Key Laboratory of Dependable Services Computing in Cyber Physical Society-Ministry of Education College of Computer Science Chongqing University Chongqing401331 China School of Software Engineering South China University of Technology Guangzhou510006 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Southwest University Chongqing400715 China

In the intricate dance of multi-agent systems, achieving average consensus is not just vital–it is the backbone of their functionality. In conventional average consensus algorithms, all agents reach an agreement by individual calculations and sharing information with their respective neighbors. Nevertheless, the information interactions that occur in the communication network may make sensitive information be revealed. In this paper, we develop a new privacy-preserving average consensus method on unbalanced directed networks. Specifically, we ensure privacy preservation by carefully embedding randomness in mixing weights to confuse communications and introducing an extra auxiliary parameter to mask the state-updated rule in initial several iterations. In parallel, we exploit the intrinsic robustness of consensus dynamics to guarantee that the average consensus is precisely achieved. Theoretical results demonstrate that the designed algorithms can converge linearly to the exact average consensus value and can guarantee privacy preservation of agents against both honest-but-curious and eavesdropping attacks. © 2023, CC BY.

关键词： Consensus algorithm

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Emotion Recognition System via Facial Expressions and Speech Using Machine Learning and Deep Learning Techniques

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SN computer Science 2023年第4期4卷 1-10页

作者： Chaudhari, Aayushi Bhatt, Chintan Nguyen, Thanh Thi Patel, Nisarg Chavda, Kirtan Sarda, Kalind U & P U. Patel Department of Computer Engineering Chandubhai S. Patel Institute of Technology Charotar University of Science And Technology (CHARUSAT) Gujarat Changa 388421 India Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Knowledge Corridor Gujarat Gandhinagar 382007 India School of Information Technology Faculty of Science Engineering and Built Environment Deakin University Victoria 3216 Australia Bishop University 2600 College St Sherbrooke J1M 1Z7 QC Canada Crest Data Systems Private Limited Gandhinagar Highway Makarba Gujarat Ahmedabad 380051 India Programmer Analyst Meditab Software Pvt Ltd Kalasagar Mall Ghatlodiya Gujarat Ahmedabad 380061 India

Patients in hospitals frequently exhibit psychological issues such as sadness, pessimism, eccentricity, and anxiety. However, hospitals normally lack tools and facilities to continuously monitor the psychological health of patients. It is desirable to identify depression in patients so that it can be managed by instantly providing better therapy. This can be possible by advances in machine learning for image processing with notable applications in the domain of emotion recognition using facial expressions. In this paper, we have proposed two different methods, i.e. facial expression detection and voice analysis, to predict emotions. For facial expression recognition, we have used two approaches, one is the use of Gabor filters for feature extraction with support vector machine for classification and another is using convolutional neural network (CNN). For voice analysis, we extracted mel-frequency cepstral coefficients from speech data and, based on those features, predicted the emotions of the speech using a CNN model. Experimental results show that our proposed emotion recognition methods obtained high accuracy and thus could be potentially deployed to real-world applications. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： CNN Deep learning Expressions Facial emotion Machine learning Speech SVM

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Multi-Scale Exact and Opposition-Based Learning Sine Cosine Algorithm for Discounted {0-1} Knapsack Problems

SSRN

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SSRN 2022年

作者： Kang, Yan Wang, Haining Pu, Bin Huang, Xin Liu, Jiansong Yang, Xuekun National Pilot School of Software Yunnan university Yunnan Kunming650000 China College of Computer Science and Electronic Engineering Hunan University Hunan Changsha410082 China

The discounted {0-1} knapsack problem (DKP) is one of the NP-hard problems, which is more challenging to obtain optimal item combinations than the classical backpack *** and meta-heuristic algorithms have different merits in solving the DKP of different scales, and the existing methods still lack the balance of exact and fuzzy *** this paper, an exact hybrid algorithm efficiently solves the DKP by fusing greedy strategies, opposition-based learning (OBL), and the sine cosine algorithm (SCA) on a different ***, initial populations are generated by balancing randomness and exactness. Furthermore, a forward-inverse SCA search is proposed to jump out of the local optimum by utilizing the worst and best solutions alternating based on the OBL. A multi-strategy mutation operator and a dynamic adaptive strategy are proposed to efficiently balance exploration and exploitation and adjust the number of mutated items, ***, extensive experiments are conducted on 30 publicly available datasets compared with the greedy algorithm, 3 SCAs, and 5 competitive baseline methods. The experiment results demonstrate our method obtains state-of-the-art performance. © 2022, The Authors. All rights reserved.

关键词： Inverse problems

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Enhanced Small Object Detection Neural Network 2020

Enhanced Small Object Detection Neural Network

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2020 International Conference on Aviation Safety and Information Technology, ICASIT 2020

作者： Liu, Lin Fan, Jiahao Xu, Cong College of Software Engineering Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China Limited Company Jilin China

ISBN: (纸本)9781450375764

Faster-RCNN is an vital deep learning object detection algorithm. Nevertheless, the small object detection effect of Faster-RCNN, which does not use multi-layer feature map, is not good enough. In this paper, a new network architecture called enhanced small object detection neural network (ESOD) is proposed. Two advancements are proposed in ESOD. Firstly, a innovative multilayer combining network which integrating multi-layer feature map is designed to leverage multi-layer convolutional information. Thereupon, the ability of small object detection can be improved. Secondly, the scale-transfer layer (STL) is introduced in the fusion of features which are in high layer and features which are in low layer, which extends the size of the features by reducing the quantity of aisles. In this way, the semantic features of distinct size are acquired without additional parameters. Extensive experimental results on PASCAL VOC 2007 and 2012 datasets indicate that, compared with several commonly used algorithms, ESOD brings better small object detection ability than existing methods for object detection. © 2020 ACM.

关键词： Object detection

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A Topology Independent Fast Rerouting Scheme with Hop-by-Hop Forwarding Can Achieve a Full Protection

SSRN

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SSRN 2022年

作者： Geng, Haijun Meng, Zhuo Zhang, Han Shi, Xingang Wang, Zhiliang Yin, Xia Chen, Meng Guo, Yingya The School of Automation and Software Engineering Shanxi University School of Computer and Information Technology China The Institute for Network Sciences and Cyberspace Tsinghua University China The Department of Computer Science and Technology Tsinghua University China The School of Big Data and Software Engineering Chongqing University China The College of Computer and Data Science Fuzhou University China

To support critical applications or guarantee a high quality of service, Internet Service Providers (ISPs) generally deploy a technique called routing protection algorithm for local fast rerouting. Alternate next hops are stored alongside with the default next hops in a router’s forwarding table, and can be immediately activated to invoke a loop free repair path in face of link or node failures, or used for multipath transmission. However, the existing routing protection methods either cannot protect all possible single-failure scenarios in the network or needs the assistance of an auxiliary address. In response to the above problems, the present study proposes a single-failure routing protection algorithm based on hop by hop routing (SPA). The algorithm has the following three advantages: (1) supports hop-by-hop forwarding, (2) supports incremental deployment, and (3) can protect all possible singlefailure scenarios in the network as long as network keep connected. Extensive simulations show that, compared to the state-of-the-art schemes which are adopted by the industry, SPA not only can handle arbitrary single-failure situations in the network but also has a small path stretch. These advantages make SPA a good candidate for practical solution for IP fast reroute when network failure occurs. © 2022, The Authors. All rights reserved.

关键词： Internet service providers

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Intermodal interference based refractive index sensor employing elliptical core photonic crystal fiber

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Optoelectronics Letters 2021年第5期17卷 271-275页

作者： WU Xu-jie SONG Bin-bin WU Ji-xuan HUANG Wei The Key Laboratory of Computer Vision and System of Ministry of Education Tianjin Key Laboratory of Intelligence Computing and Novel Software TechnologyTianjin University of TechnologyTianjin 300384China Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems College of Electronic and Information EngineeringTiangong UniversityTianjin 300387China

A refractive index(RI)sensor based on elliptical core photonic crystal fiber(EC-PCF)has been *** asymmetric elliptical core introduces the polarization-dependent characteristics of the fiber core *** performances of intermodal interference between the intrinsic polarization fiber core modes are investigated by contrast in two interferometers based on the Mach-Zehnder(M-Z)and Sagnac interference *** addition,the RI sensing characteristics of the two interferometers are studied by successively filling the three layers air holes closest to the elliptical core in the *** results show that the M-Z interference between LP_(01)and LP_(11)mode in the same polarized direction is featured with the incremental RI sensing sensitivity as the decreasing interference length,and the infilled scope around the elliptical core has a weak correlation with the RI sensing *** to the high birefringence of LP11 mode,the Sagnac interferometer has better RI sensing performance,the maximum RI sensing sensitivity of 12000 nm/RIU is achieved under the innermost one layer air holes infilled with RI matching liquid of RI=1.39 at the pre-setting EC-PCF length of 12 cm,which is two orders of magnitude higher than the M-Z interferometer with the same fiber *** series of theoretical optimized analysis would provide guidance for the applications in the field of biochemical sensing.

关键词： Sagnac PCF Intermodal interference based refractive index sensor employing elliptical core photonic crystal fiber

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Improved Differential Evolution Algorithm for 4PL Supply Chain Network Design Considering the Customer Behavior

IJLAI Transactions on Science and Engineering

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IJLAI Transactions on Science and engineering 2025年第1期3卷 8-21页

作者： Liwei Dong Chao Deng Xiaoying Gao Weijing Yin College of Software Shenyang Normal University 110034 ShenyangLiaoningChina College of Computer and Information Engineering 210097 Nanjing JiangsuChina

Fourth party logistics(4PL)supply chain network design problem considering the behavior of customer service satisfaction becomes more important in supply chain network design *** is NP-hard *** differential evolution(IDE)algorithm is applied to solve this problem in this *** order to handle the infeasible solution efficiently,a two-stage algorithm,the minimum cost flow incorporated with macro-micro adjustment embedded improved differential evolution(MMAMFC-IDE),is *** results of numerical experiments show that MMAMFC-IDE can get relatively better results compared with the minimum cost flow embedded improved differential evolution(MFC-IDE).

关键词： Fourth party logistics Supply Chain Network Design service satisfaction MMAMFC-IDE

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Evolutionary-based image encryption with dna coding and chaotic systems 1

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17th International Conference on Web Information Systems and Applications, WISA 2020

作者： Qin, Shiyue Tan, Zhenhua Zhang, Bin Zhou, Fucai School of Computer Science and Engineering Northeastern University Shenyang China Software College Northeastern University Shenyang China

ISBN: (数字)9783030600297

ISBN: (纸本)9783030600280

In order to obtain encrypted image with optimal correlation coefficient, we propose a new evolutionary-based image encryption scheme in this paper, based on DNA coding, chaotic systems, and a genetic algorithm (GA). Firstly, the DNA encoding operation is performed over the original plain image. Then logistic mapping and hyper-chaotic systems are used to create the number of encrypted images over the DNA matrices. We fix these encrypted images as the initial population for the GA, and the GA is applied to them to determine the best one based on the fitness function. The correlation coefficient is used to define the fitness function in this paper. Finally, after the evolution, the encrypted image with the lowest correlation coefficient will be obtained as the final result. The novelty of this research is in using the logistic map over the DNA matrix of the original image directly, which will make the initial group of encrypted images more secure and with lower initial fitness for the GA. Therefore, the scheme will achieve high fitness in fewer iterations and retain the efficiency of the encryption. Experimental results confirm that the proposed scheme not only has a good encryption effect, but also has the ability of resisting statistical analysis attacks, brute force attacks, and differential attacks. © Springer Nature Switzerland AG 2020.

关键词： Genetic algorithms

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A Bayesian k-vector estimation method for electromagnetic waves in magnetized cold plasma

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URSI Radio Science Bulletin 2023年第378期2021卷 77-82页

作者： Yuji Tanaka Mamoru Ota Shoya Matsuda Yoshiya Kasahara Division of Electrical Engineering Graduate School of Engineering Kyoto University Kyotodaigaku-Katsura Nishikyo-ku Kyoto Kyoto Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College 13 Hongo-machi Toyama Toyama Japan Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kakuma Kanazawa Ishikawa Japan

Using the plasma wave characteristics and remote sensing technology, the k-vector direction of plasma waves can provide important information for understanding the global features of space plasma. In this study, we proposed a Bayesian k-vector estimation method in magnetized cold plasma based on the wave distribution function method. The proposed method can be applied to various types of sensors with easy visualization and calculation of the estimation accuracy. We verified the effectiveness of the proposed method through simulations.

关键词： Estimation Plasmas Electromagnetics Mathematical models Magnetic sensors Bayes methods Plasma waves

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GPUSCAN++: Efficient Structural Graph Clustering on GPUs

arXiv

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arXiv 2023年

作者： Yuan, Long Zhou, Zeyu Lin, Xuemin Chen, Zi Zhao, Xiang Zhang, Fan The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China The School of Computer Science and Engineering The University of New South Wales Sydney Australia The Software Engineering Institute East China Normal University Shanghai China The College of Systems Engineering National University of Defense Technology Changsha China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China

Structural clustering is one of the most popular graph clustering methods, which has achieved great performance improvement by utilizing GPUs. Even though, the state-of-the-art GPU-based structural clustering algorithm, GPUSCAN, still suffers from efficiency issues since lots of extra costs are introduced for parallelization. Moreover, GPUSCAN assumes that the graph is resident in the GPU memory. However, the GPU memory capacity is limited currently while many real-world graphs are big and cannot fit in the GPU memory, which makes GPUSCAN unable to handle large graphs. Motivated by this, we present a new GPU-based structural clustering algorithm, GPUSCAN++, in this paper. To address the efficiency issue, we propose a new progressive clustering method tailored for GPUs that not only avoid high parallelization costs but also fully exploits the computing resources of GPUs. To address the GPU memory limitation issue, we propose a partition-based algorithm for structural clustering that can process large graphs with limited GPU memory. We conduct experiments on real graphs, and the experimental results demonstrate that our algorithm can achieve up to 168 times speedup compared with the state-of-the-art GPU-based algorithm when the graph can be resident in the GPU memory. Moreover, our algorithm is scalable to handle large graphs. As an example, our algorithm can finish the structural clustering on a graph with 1.8 billion edges using less than 2 GB GPU memory. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphics processing unit

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