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Explainable-AI-based two-stage solution for WSN object localization using zero-touch mobile transceivers

Science China(Information Sciences) 2024年第7期67卷 27-45页

作者： Kai FANG Junxin CHEN Han ZHU Thippa Reddy GADEKALLU Xiaoping WU Wei WANG School of Mathematics and Computer Science Zhejiang A&F University School of Software Dalian University of Technology Faculty of Applied Sciences Macao Polytechnic University Department of Electrical and Computer Engineering Lebanese American University School of Information Engineering Huzhou University Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University

Artificial intelligence technology is widely used in the field of wireless sensor networks(WSN).Due to its inexplicability, the interference factors in the process of WSN object localization cannot be effectively eliminated. In this paper, an explainable-AI-based two-stage solution is proposed for WSN object localization. In this solution, mobile transceivers are used to enlarge the positioning range and eliminate the blind area for object localization. The motion parameters of transceivers are considered to be unavailable,and the localization problem is highly nonlinear with respect to the unknown parameters. To address this,an explainable AI model is proposed to solve the localization problem. Since the relationship among the variables is difficult to fully include in the first-stage traditional model, we develop a two-stage explainable AI solution for this localization problem. The two-stage solution is actually a comprehensive consideration of the relationship between variables. The solution can continue to use the constraints unused in the firststage during the second-stage, thereby improving the performance of the solution. Therefore, the two-stage solution has stronger robustness compared to the closed-form solution. Experimental results show that the performance of both the two-stage solution and the traditional solution will be affected by numerical changes in unknown parameters. However, the two-stage solution performs better than the traditional solution, especially with a small number of mobile transceivers and sensors or in the presence of high noise. Furthermore,we have also verified the feasibility of the proposed explainable-AI-based two-stage solution.

关键词： explainable AI object localization semidefinite relaxation mobile transceiver two-stage solution closed-form solution

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Solving the subset sum problem by the quantum Ising model with variational quantum optimization based on conditional values at risk

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Science China(Physics,Mechanics & Astronomy) 2024年第8期67卷 43-55页

作者： Qilin Zheng Miaomiao Yu Pingyu Zhu Yan Wang Weihong Luo Ping Xu institute for Quantum Information and State Key Laboratory of High Performance computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China Hefei National Laboratory Hefei 230088China

The subset sum problem is a combinatorial optimization problem,and its complexity belongs to the nondeterministic polynomial time complete(NP-Complete)*** problem is widely used in encryption,planning or scheduling,and integer *** accurate search algorithm with polynomial time complexity has not been found,which makes it challenging to be solved on classical *** effectively solve this problem,we translate it into the quantum Ising model and solve it with a variational quantum optimization method based on conditional values at *** proposed model needs only n qubits to encode 2ndimensional search space,which can effectively save the encoding quantum *** model inherits the advantages of variational quantum algorithms and can obtain good performance at shallow circuit depths while being robust to noise,and it is convenient to be deployed in the Noisy Intermediate Scale Quantum *** investigate the effects of the scalability,the variational ansatz type,the variational depth,and noise on the ***,we also discuss the performance of the model under different conditional values at *** computer simulation,the scale can reach more than nine *** selecting the noise type,we construct simulators with different QVs and study the performance of the model with *** addition,we deploy the model on a superconducting quantum computer of the Origin Quantum Technology Company and successfully solve the subset sum *** model provides a new perspective for solving the subset sum problem.

关键词： subset sum problem quantum Ising model conditional values at risk variational quantum optimization

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Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad Ali Zeb Hani Alshahrani Mohammed Hamdi Mohammad Alsulami Asadullah Shaikh institute of computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic *** review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their ***,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by *** paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic *** has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation *** recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM *** paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM ***,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

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A Transfer Function Design for Medical Volume Data Using a Knowledge Database Based on Deep Image and Primitive Intensity Profile Features Retrieval

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Journal of Computer Science & Technology 2024年第2期39卷 320-335页

作者： Younhyun Jung Jim Kong 盛斌 Jinman Kim School of computing Gachon UniversitySeongnam 13120Korea School of Computer Science The University of SydneySydney 2006Australia Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Direct volume rendering(DVR)is a technique that emphasizes structures of interest(SOIs)within a volume visually,while simultaneously depicting adjacent regional information,e.g.,the spatial location of a structure concerning its *** DVR,transfer function(TF)plays a key role by enabling accurate identification of SOIs interactively as well as ensuring appropriate visibility of *** generation typically involves non-intuitive trial-and-error optimization of rendering parameters,which is time-consuming and *** at mitigating this manual process have led to approaches that make use of a knowledge database consisting of pre-designed TFs by domain *** these approaches,a user navigates the knowledge database to find the most suitable pre-designed TF for their input volume to visualize the *** these approaches potentially reduce the workload to generate the TFs,they,however,require manual TF navigation of the knowledge database,as well as the likely fine tuning of the selected TF to suit the *** this work,we propose a TF design approach,CBR-TF,where we introduce a new content-based retrieval(CBR)method to automatically navigate the knowledge *** of pre-designed TFs,our knowledge database contains volumes with SOI *** an input volume,our CBR-TF approach retrieves relevant volumes(with SOI labels)from the knowledge database;the retrieved labels are then used to generate and optimize TFs of the *** approach largely reduces manual TF navigation and fine *** our CBR-TF approach,we introduce a novel volumetric image feature which includes both a local primitive intensity profile along the SOIs and regional spatial semantics available from the co-planar images to the *** the regional spatial semantics,we adopt a convolutional neural network to obtain high-level image feature *** the intensity profile,we extend the dynamic time warping technique to address subtle alignment

关键词： data retrieval direct volume rendering ray analysis transfer function

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An anonymous authentication and secure data transmission scheme for the Internet of Things based on blockchain

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Frontiers of Computer Science 2024年第3期18卷 183-197页

作者： Xingxing CHEN Qingfeng CHENG Weidong YANG Xiangyang LUO State Key Laboratory of Mathematical Engineering and Advanced computing Zhengzhou Institute of Information Science and TechnologyZhengzhou 450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of TechnologyZhengzhou 450001China Henan Province Key Laboratory of Cyberspace Situation Awareness Zhengzhou Institute of Information Science and TechnologyZhengzhou 450001China

With the widespread use of network infrastructures such as 5G and low-power wide-area networks,a large number of the Internet of Things(IoT)device nodes are connected to the network,generating massive amounts of ***,it is a great challenge to achieve anonymous authentication of IoT nodes and secure data *** present,blockchain technology is widely used in authentication and s data storage due to its decentralization and ***,Fan et *** a secure and efficient blockchain-based IoT authentication and data sharing *** studied it as one of the state-of-the-art protocols and found that this scheme does not consider the resistance to ephemeral secret compromise attacks and the anonymity of IoT *** overcome these security flaws,this paper proposes an enhanced authentication and data transmission scheme,which is verified by formal security proofs and informal security ***,Scyther is applied to prove the security of the proposed ***,it is demonstrated that the proposed scheme achieves better performance in terms of communication and computational cost compared to other related schemes.

关键词： Internet of Things blockchain authentication data transmission

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Local search yields a PTAS for fixed-dimensional k-means problem with penalties

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Journal of the Operations Research Society of China 2024年第2期12卷 351-362页

作者： Fan Yuan Da-Chuan Xu Dong-Lei Du Dong-Mei Zhang Beijing institute for Scientific and Engineering computing Beijing University of TechnologyBeijing 100124China Faculty of Management University of New BrunswickFrederictonNB E3B 9Y2Canada School of Computer Science and Technology Shandong Jianzhu UniversityJinan 250101ShandongChina

We study a problem called the k-means problem with penalties(k-MPWP),which is a natural generalization of the typical k-means *** this problem,we have a set D of client points in R^(d),a set F of possible centers in R^(d),and a penalty cost Pj>O for each point j∈*** are also given an integer k which is the size of the center point *** want to find a center point set S■F with size k,choose a penalized subset of clients P■D,and assign every client in D\P to its open *** goal is to minimize the sum of the squared distances between every point in D\P to its assigned centre point and the sum of the penalty costs for all clients in *** using the multi-swap local search technique and under the fixed-dimensional Euclidean space setting,we present a polynomial-time approximation scheme(PTAS)for the k-MPWP.

关键词： Approximation algorithm k-means Local search Penalty

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A Method for Detecting and Recognizing Yi Character Based on Deep Learning

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Computers, Materials & Continua 2024年第2期78卷 2721-2739页

作者： Haipeng Sun Xueyan Ding Jian Sun HuaYu Jianxin Zhang School of Computer Science and Engineering Dalian Minzu UniversityDalian116600China institute of Machine Intelligence and Bio-computing Dalian Minzu UniversityDalian116600China 3Yi Language Research RoomChina Ethnic Languages Translation Centre Beijing100080China

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and *** the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character ***,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different ***,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original *** maps are then subjected to a differentiable binarization process,resulting in an approximate binarization *** map helps to identify the boundaries of the text ***,the text detection box is generated after the post-processing *** the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters ***,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text *** experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,*** also,we have compared the detection and re

关键词： Yi characters text detection text recognition attention mechanism deep neural network

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Finding Ordered State in a Disordered Jungle

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Chinese Physics Letters 2024年第4期41卷 124-125页

作者：周晓东沈健 State Key Laboratory of Surface Physics and institute for Nanoelectronic Devices and Quantum computing Fudan UniversityShanghai 200433China Zhangjiang Fudan International Innovation Center Fudan UniversityShanghai 201210China Shanghai Research Center for Quantum Sciences Shanghai 201315China

A rich portfolio of emergent phenomena has been discovered in twisted two-dimensional(2D)moirésystems,including strongly correlated insulators,[1]superconductivity,[2]integer and fractional Chern insulators(ChIs),[3-... 详细信息

关键词： integer twisted ferroelectric

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A Bitcoin Address Multi-Classification Mechanism Based on Bipartite Graph-Based Maximization Consensus

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 783-800页

作者： Lejun Zhang Junjie Zhang Kentaroh Toyoda Yuan Liu Jing Qiu Zhihong Tian Ran Guo College of Information Engineering Yangzhou UniversityYangzhou225127China Cyberspace institute Advanced Technology Guangzhou UniversityGuangzhou510006China Research and Development Center for E-Learning Ministry of EducationBeijing100039China institute of High Performance computing(IHPC) Agency for ScienceTechnology and Research(A∗STAR)Singapore138632Singapore School of Physics and Materials Science Guangzhou UniversityGuangzhou510006China

Bitcoin is widely used as the most classic electronic currency for various electronic services such as exchanges,gambling,marketplaces,and also scams such as high-yield investment *** the services operated by a Bitcoin address can help determine the risk level of that address and build an alert model *** engineering can also be used to flesh out labeled addresses and to analyze the current state of Bitcoin in a small *** this paper,we address the problem of identifying multiple classes of Bitcoin services,and for the poor classification of individual addresses that do not have significant features,we propose a Bitcoin address identification scheme based on joint multi-model prediction using the mapping relationship between addresses and *** innovation of the method is to(1)Extract as many valuable features as possible when an address is given to facilitate the multi-class service identification task.(2)Unlike the general supervised model approach,this paper proposes a joint prediction scheme for multiple learners based on address-entity mapping ***,after obtaining the overall features,the address classification and entity clustering tasks are performed separately,and the results are subjected to graph-basedmaximization *** final result ismade to baseline the individual address classification results while satisfying the constraint of having similarly behaving entities as far as *** testing and evaluating over 26,000 Bitcoin addresses,our feature extraction method captures more useful *** addition,the combined multi-learner model obtained results that exceeded the baseline classifier reaching an accuracy of 77.4%.

关键词： Bitcoin multi-service classification graph maximization consensus data security

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The First Verification Test of Space-Ground Collaborative Intelligence via Cloud-Native Satellites

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China Communications 2024年第4期21卷 208-217页

作者： Wang Shangguang Zhang Qiyang Xing Ruolin Qi Fei Xu Mengwei State Key Laboratory of Networking and Switching Beijing University of Posts and TelecommunicationsBeijing 100876China Star Network and Intelligent computing Laboratory Beiyou Shenzhen InstituteShenzhen 518000China Huawei Technologies Co. LtdShenzhen 518129China

Recent advancements in satellite technologies and the declining cost of access to space have led to the emergence of large satellite constellations in Low Earth Orbit(LEO).However,these constellations often rely on bent-pipe architecture,resulting in high communication *** onboard inference architectures suffer from limitations in terms of low accuracy and inflexibility in the deployment and management of in-orbit *** address these challenges,we propose a cloud-native-based satellite design specifically tailored for Earth Observation tasks,enabling diverse computing *** this work,we present a case study of a satellite-ground collaborative inference system deployed in the Tiansuan constellation,demonstrating a remarkable 50%accuracy improvement and a substantial 90%data *** work sheds light on in-orbit energy,where in-orbit computing accounts for 17%of the total onboard energy *** approach represents a significant advancement of cloud-native satellite,aiming to enhance the accuracy of in-orbit computing while simultaneously reducing communication cost.

关键词： cloud-native satellite orbital edge computing satellite inference verification test

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