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A robust deformed convolutional neural network(CNN)for image denoising

CAAI Transactions on Intelligence technology 2023年第2期8卷 331-342页

作者： Qi Zhang Jingyu Xiao Chunwei Tian Jerry Chun‐Wei Lin Shichao Zhang School of Economics and Management Harbin Institute of Technology at WeihaiWeihaiChina School of Computer Science Central South UniversityChangshaChina School of Software Northwestern Polytechnical UniversityXi'anShaanxiChina Research&Development Institute Northwestern Polytechnical UniversityShenzhenChina Yangtze River Delta Research Institute Northwestern Polytechnical UniversityTaicangChina Department of Computer Science Electrical Engineering and Mathematical SciencesWestern Norway University of Applied SciencesBergenNorway

Due to strong learning ability,convolutional neural networks(CNNs)have been developed in image ***,convolutional operations may change original distributions of noise in corrupted images,which may increase training difficulty in image *** relations of surrounding pixels can effectively resolve this *** by that,we propose a robust deformed denoising CNN(RDDCNN)in this *** proposed RDDCNN contains three blocks:a deformable block(DB),an enhanced block(EB)and a residual block(RB).The DB can extract more representative noise features via a deformable learnable kernel and stacked convolutional architecture,according to relations of surrounding *** EB can facilitate contextual interaction through a dilated convolution and a novel combination of convolutional layers,batch normalisation(BN)and ReLU,which can enhance the learning ability of the proposed *** address long-term dependency problem,the RB is used to enhance the memory ability of shallow layer on deep layers and construct a clean ***,we implement a blind denoising *** results demonstrate that our denoising model outperforms popular denoising methods in terms of qualitative and quantitative *** can be obtained at https://***/hellloxiaotian/RDDCNN.

关键词： blind denoising CNN deformed block enhanced block

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NLSP: A novel lattice-based secure primitive for privacy-preserving smart grid communications

NLSP: A novel lattice-based secure primitive for privacy-pre...

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作者： Bao, HaiYong Xu, Zheng Hong, HaiBo Kong, QingLei Qian, HaiFeng Software Engineering Institute East China Normal University Shanghai China School of Computer Science and Information Engineering Zhejiang Gongshang University Hangzhou China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China Institute of Space Science and Applied Technology Harbin Institute of Technology Shenzhen China

As the new generation of power scheme, smart grid is proposed to overcome the shortcomings of traditional systems, such as low efficiency and reliability. In this article, a novel lattice-based secure primitive for privacy-preserving smart grid communications is proposed, which has the remarkable characteristics, such as scalable multi-dimensional fine-grained power data structure and differential privacy security. First, combining with the lattice-based data encryption technology, while effectively resisting quantum attacks, the method of simultaneous processing of multi-dimensional data is innovated. Second, through combining the additive homomorphism of the lattice-based cryptosystem and the Chinese remainder theorem, the data aggregation mechanism that can directly perform homomorphic operations on compressed ciphertext is constructed. Thanks to the above innovative design ideas, the proposed scheme not only significantly improves the efficiency of data communication and processing, greatly reduces the computational cost of the intermediate entity, but also realizes the data confidentiality and information privacy. Finally, observing the decentralized topology of communication nodes in the typical cyber-physical system of smart grid, the localized differential privacy technology is leveraged to optimize and balance the utility, security, and efficiency of differential privacy. Extensive performance evaluations are conducted to illustrate that the proposed scheme outperforms the state-of-the-art similar schemes in terms of computation complexity and communication cost. © 2022 John Wiley & Sons, Ltd.

关键词： Smart power grids

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Multi-Scale Electromagnetic Simulation Through Parallel Adaptive Mesh Refinement FDTD Method with Symmetric Positive Semi-Definite Subgridding Scheme

Multi-Scale Electromagnetic Simulation Through Parallel Adap...

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2023 International applied Computational Electromagnetics Society Symposium, ACES-China 2023

作者： Li, Hanyu Zhou, Haijing Bao, Xianfeng Chen, Xiaojie School of Physical Science and Technology Southwest Jiaotong University Chengdu China Institute of Applied Physics and Computational Mathematics Beijing China Software Center for High Performance Numerical Simulation Caep Beijing China

ISBN: (纸本)9781733509657

FDTD method is a common approach for electromagnetic propagation, scattering and coupling simulation. Conventional FDTD with universal mesh requires numerous computations to represent solve problems with multi-scale structures. In this paper, adaptive mesh refinement (AMR) strategy is performed to reduce the calculations along with symmetric positive semi-definite subgridding scheme to guarantee stability. Numerical example of a missile seeker coupling simulation shows that the computation time decrease down to 2% while preserving excellent precision. © 2023 applied Computational Electromagnetics Society (ACES).

关键词： Finite difference time domain method

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Multi-agent policy transfer via task relationship modeling

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science China(Information sciences) 2024年第8期67卷 102-114页

作者： Rongjun QIN Feng CHEN Tonghan WANG Lei YUAN Xiaoran WU Yipeng KANG Zongzhang ZHANG Chongjie ZHANG Yang YU National Key Laboratory for Novel Software Technology Nanjing University Polixir Technologies School of Engineering and Applied Sciences Harvard University Department of Computer Science and Technology Tsinghua University Institute for Interdisciplinary Information Sciences Tsinghua University

Team adaptation to new cooperative tasks is a hallmark of human intelligence, which has yet to be fully realized in learning agents. Previous studies on multi-agent transfer learning have accommodated teams of different sizes but heavily relied on the generalization ability of neural networks for adapting to unseen tasks. We posit that the relationship among tasks provides key information for policy *** utilize this relationship for efficient transfer by attempting to discover and exploit the knowledge among tasks from different teams, proposing to learn an effect-based task representation as a common latent space among tasks, and using it to build an alternatively fixed training scheme. Herein, we demonstrate that task representation can capture the relationship among teams and generalize to unseen tasks. Thus, the proposed method helps transfer the learned cooperation knowledge to new tasks after training on a few source ***, the learned transferred policies help solve tasks that are difficult to learn from scratch.

关键词： multi-agent reinforcement learning cooperative transfer learning task relationship modeling multi-agent policy reuse multi-agent multi-task learning

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Empowering Donors: How Blockchain technology Can Help Ensure Their Contributions Reach the Right Recipients 2

Empowering Donors: How Blockchain Technology Can Help Ensure...

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2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Ajmal, Sahar Muzammil, Muteeb Bin Shoaib, Muhammad Mehmood, Muhammad Hassaan National University of Computer and Emmerging Sciences Department of Software Engineering Faisalabad Pakistan Riphah International University College of Computing Faisalabad Pakistan University of Engineering and Technology Department of Computer Science Lahore Pakistan School of Computer Science NCBA&E Lahore Pakistan Applied School Research Center Applied Science Private University Amman11937 Jordan

ISBN: (纸本)9798350335644

Charity giving is a fundamental aspect of society, but there are concerns about the accountability and transparency of the donation process. Blockchain technology has emerged as a potential solution, offering a secure and auditable platform for managing charitable contributions. In this paper, we explore the concept of empowering donors through blockchain technology and examine how it can help ensure that contributions reach the right recipients. We review existing literature on the topic and identify key areas for future research, including the development of hybrid blockchain solutions along with the implementation of novel consensus mechanisms. Moreover, providing the idea of decentralized autonomous organizations, self-executing smart contracts, and integration of blockchain with artificial intelligence and Internet of things. By providing a comprehensive overview of the current state of the field and outlining a roadmap for future research, we hope to stimulate further exploration of the potential of blockchain technology to revolutionize charity giving, and create a more accountable and transparent system for managing charitable funds. Some research questions are designed for each novel idea. Our analysis suggests that blockchain has the potential to empower donors and ensure that their contributions make a positive impact in the world, but further research is needed to fully realize its potential. © 2023 IEEE.

关键词： Transparency

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SMRI: A New Method for siRNA Design for COVID-19 Therapy

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Journal of Computer science & technology 2022年第4期37卷 991-1002页

作者： Meng-Xin Chen Xiao-Dong Zhu Hao Zhang Zhen Liu Yuan-Ning Liu College of Software Jilin UniversityChangchun 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Jilin UniversityChangchun 130012China College of Computer Science and Technology Jilin UniversityChangchun 130012China Graduate School of Engineering Nagasaki Institute of Applied ScienceNagasaki 851-0193Japan

First discovered in Wuhan, China, SARS-CoV-2 is a highly pathogenic novel coronavirus, which rapidly spreads globally and becomes a pandemic with no vaccine and limited distinctive clinical drugs available till March 13th, 2020. Ribonucleic Acid interference (RNAi) technology, a gene-silencing technology that targets mRNA, can cause damage to RNA viruses effectively. Here, we report a new efficient small interfering RNA (siRNA) design method named Simple Multiple Rules Intelligent Method (SMRI) to propose a new solution of the treatment of COVID-19. To be specific, this study proposes a new model named Base Preference and Thermodynamic Characteristic model (BPTC model) indicating the siRNA silencing efficiency and a new index named siRNA Extended Rules index (SER index) based on the BPTC model to screen high-efficiency siRNAs and filter out the siRNAs that are difficult to take effect or synthesize as a part of the SMRI method, which is more robust and efficient than the traditional statistical indicators under the same circumstances. Besides, to silence the spike protein of SARS-CoV-2 to invade cells, this study further puts forward the SMRI method to search candidate high-efficiency siRNAs on SARS-CoV-2's S gene. This study is one of the early studies applying RNAi therapy to the COVID-19 treatment. According to the analysis, the average value of predicted interference efficiency of the candidate siRNAs designed by the SMRI method is comparable to that of the mainstream siRNA design algorithms. Moreover, the SMRI method ensures that the designed siRNAs have more than three base mismatches with human genes, thus avoiding silencing normal human genes. This is not considered by other mainstream methods, thereby the five candidate high-efficiency siRNAs which are easy to take effect or synthesize and much safer for human body are obtained by our SMRI method, which provide a new safer, small dosage and long efficacy solution for the treatment of COVID-19.

关键词： COVID-19 SARS-CoV-2 RibonucleicAcid interference

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PathLAD+: An Improved Exact Algorithm for Subgraph Isomorphism Problem 32

PathLAD+: An Improved Exact Algorithm for Subgraph Isomorphi...

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32nd International Joint Conference on Artificial Intelligence, IJCAI 2023

作者： Wang, Yiyuan Jin, Chenghou Cai, Shaowei Lin, Qingwei School of Computer Science and Information Technology Northeast Normal University China Key Laboratory of Applied Statistics of MOE Northeast Normal University Changchun China Computer School Beijing Information Science and Technology University Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences China Microsoft Research China

ISBN: (纸本)9781956792034

The subgraph isomorphism problem (SIP) is a challenging problem with wide practical applications. In the last decade, despite being a theoretical hard problem, researchers designed various algorithms for solving SIP. In this work, we propose three main heuristics and develop an improved exact algorithm for SIP. First, we design a probing search procedure to try whether the search procedure can successfully obtain a solution at first sight. Second, we design a novel matching ordering as a value-ordering heuristic, which uses some useful information obtained from the probing search procedure to preferentially select some promising target vertices. Third, we discuss the characteristics of different propagation methods in the context of SIP and present an adaptive propagation method to make a good balance between these methods. Experimental results on a broad range of real-world benchmarks show that our proposed algorithm performs better than state-of-the-art algorithms for the SIP. © 2023 International Joint Conferences on Artificial Intelligence. All rights reserved.

关键词： Set theory

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Evaluating Time Series Database Management Systems for Insurance Company 13

Evaluating Time Series Database Management Systems for Insur...

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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Koschel, Arne Astrova, Irina Alsleben, Stephan-Tobias Bellok, Jannis Meyer, Niklas Meyer, Sebastian University of Applied Sciences and Arts Hannover Faculty Iv Department of Computer Science Hannover Germany Tallinn University of Technology School of It Department of Software Science Tallinn Estonia

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

This paper provides the criteria and sources of information that an insurance company should consider when evaluating time series databases for its needs. The company wanted to select either QuestDB or Graphite in order to replace InfluxDB. Selecting a new database is an important process. Like any other successful database management system, the database selected today begins to define the legacy of the company's future. There are many different parameters that can be used by the company to evaluate the time series database alternatives, and there is no single most correct process for conducting this evaluation. Not only are there many possible pertinent evaluation criteria, but there also is typically a degree of uncertainty about the requirements and characteristics of the target application environment. This paper focuses on evaluation criteria, with emphasis on horizontal scalability and performance. © 2022 IEEE.

关键词： Database systems

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Engine Fault Diagnosis Method Based on Convolution Neural Network and BiLSTM

Engine Fault Diagnosis Method Based on Convolution Neural Ne...

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2023 Asia-Pacific Conference on Image Processing, Electronics and Computers, IPEC 2023

作者： Feng, Donghua Li, Yahong Wu, Sa Software and Communication School Tianjin Sino-German University of Applied Sciences Tianjin China School of Information Engineering Tianjin College Beijing University of Science and Technology Tianjin China University of Newcastle Upon Tyne Faculty of Science Agricultuer and Engineering Newcastle upon Tyne United Kingdom

ISBN: (纸本)9781665457033

Aiming at the complex characteristics of engine fault and fuzzy boundary of fault area, a method of engine fault diagnosis based on convolution neural network and bidirectional LSTM is proposed. To explore the causes of common engine faults, a convolutional neural network feature extraction model is established, the modified linear unit is used to improve the over fitting problem of the model, and the SoftMax classifier is used to lock the fault area, and the long short-term is established Memory rural network model, the introduction of remaining life tag, using min max method to complete data preprocessing, adding a dropout layer in the bidirectional LSTM layer and full connection layer, removing the output value of hidden layer, obtaining the final fault diagnosis results, and using root mean square error and asymmetric score function to evaluate the reliability of the method. The simulation results show that the fault diagnosis has fast convergence rate, high diagnosis accuracy and strong applicability, which provides valuable technical reference for engine maintenance and maintenance. © 2023 IEEE.

关键词： Feature extraction

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Model for Recognition of Sign Language and Hand Gesture by Hard Hearing People

Model for Recognition of Sign Language and Hand Gesture by H...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Manjula, R. Jagadeesan, S. Ramalingam, Venkadeshan Vetriselvi, T. Johnpeter, T. Srm Institute of Science and Technology College of Engineering and Technology Department of Computing Technologies Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Tamilnadu Vellore India Information Technology Department University of Technology and Applied Sciences-Shinas Branch Sultanate of Oman Oman Vellore Institute of Technology School of Computer Science and Engineering Department of Iot Tamilnadu Vellore India K.Ramakrishnan College of Engineering Department of Computer Science and Engineering Trichy India

ISBN: (纸本)9798350313987

Hard hearing and deaf people are communicating with other people using the sign language. This is the only way of communication of such people to convey Since this is the only means by which these individuals can communicate, it is imperative that others be able to understand their language. Sign language recognition by computer begins with the acquisition of sign gestures and ends with recognition and conversion to text or voice. Static and dynamic are the two ways of sign gestures used. This study aims at focusing on the dynamic gesture recognition and the steps for recognizing sign language are discussed. The collected data are preprocessed and feature are extracted for classification. Finally the results are all investigated and developed for single user. © 2023 IEEE.

关键词： Gesture analysis Hand gesture recognition Hand tracking Sign language

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