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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

Dynamical behaviors in discrete memristor-coupled small-world neuronal networks

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Chinese Physics B 2024年第4期33卷 729-734页

作者：鲁婕妤谢小华卢亚平吴亚联李春来马铭磷 school of Automation and Electronic Information Xiangtan UniversityXiangtan 411105China school of computer Science school of Cyberspace Science Xiangtan UniversityXiangtan 411105China

The brain is a complex network system in which a large number of neurons are widely connected to each other and transmit signals to each *** memory characteristic of memristors makes them suitable for simulating neuronal synapses with *** this paper,a memristor is used to simulate a synapse,a discrete small-world neuronal network is constructed based on Rulkov neurons and its dynamical behavior is *** explore the influence of system parameters on the dynamical behaviors of the discrete small-world network,and the system shows a variety of firing patterns such as spiking firing and triangular burst firing when the neuronal parameterαis *** results of a numerical simulation based on Matlab show that the network topology can affect the synchronous firing behavior of the neuronal network,and the higher the reconnection probability and number of the nearest neurons,the more significant the synchronization state of the *** addition,by increasing the coupling strength of memristor synapses,synchronization performance is *** results of this paper can boost research into complex neuronal networks coupled with memristor synapses and further promote the development of neuroscience.

关键词： small-world networks Rulkov neurons memristor synchronization

Applying an Improved Dung Beetle Optimizer Algorithm to Network Traffic Identification

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computers, Materials & Continua 2024年第3期78卷 4091-4107页

作者： Qinyue Wu Hui Xu Mengran Liu school of computer Science Hubei University of TechnologyWuhan430068China

Network traffic identification is critical for maintaining network security and further meeting various demands of network ***,network traffic data typically possesses high dimensionality and complexity,leading to practical problems in traffic identification data *** the original Dung Beetle Optimizer(DBO)algorithm,Grey Wolf Optimization(GWO)algorithm,Whale Optimization Algorithm(WOA),and Particle Swarm Optimization(PSO)algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution,an Improved Dung Beetle Optimizer(IDBO)algorithm is proposed for network traffic ***,the Sobol sequence is utilized to initialize the dung beetle population,laying the foundation for finding the global optimal ***,an integration of levy flight and golden sine strategy is suggested to give dung beetles a greater probability of exploring unvisited areas,escaping from the local optimal solution,and converging more effectively towards a global optimal ***,an adaptive weight factor is utilized to enhance the search capabilities of the original DBO algorithm and accelerate *** the improvements above,the proposed IDBO algorithm is then applied to traffic identification data analytics and feature selection,as so to find the optimal subset for K-Nearest Neighbor(KNN)*** simulation experiments use the CICIDS2017 dataset to verify the effectiveness of the proposed IDBO algorithm and compare it with the original DBO,GWO,WOA,and PSO *** experimental results show that,compared with other algorithms,the accuracy and recall are improved by 1.53%and 0.88%in binary classification,and the Distributed Denial of Service(DDoS)class identification is the most effective in multi-classification,with an improvement of 5.80%and 0.33%for accuracy and recall,***,the proposed IDBO algorithm is effective in increasing the efficiency of traffic identificati

关键词： Network security network traffic identification data analytics feature selection dung beetle optimizer

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

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computers, Materials & Continua 2024年第1期78卷 935-957页

作者： Li Zheng Gang Xu Wenbin Chen school of Mathematics and computer Sciences Nanchang UniversityNanchang330031China

Drone logistics is a novel method of distribution that will become *** advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption,resulting in cost savings for the company’s transportation *** firms must discern the ideal location for establishing a logistics hub,which is challenging due to the simplicity of existing models and the intricate delivery *** simulate the drone logistics environment,this study presents a new mathematical *** model not only retains the aspects of the current models,but also considers the degree of transportation difficulty from the logistics hub to the village,the capacity of drones for transportation,and the distribution of logistics hub ***,this paper proposes an improved particle swarm optimization(PSO)algorithm which is a diversity-based hybrid PSO(DHPSO)algorithm to solve this *** DHPSO,the Gaussian random walk can enhance global search in the model space,while the bubble-net attacking strategy can speed ***,Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the *** maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current *** DHPSO with other state-of-the-art intelligent algorithms,the efficiency of the scheme can be improved by 42.58%.This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO’s location *** the results show the location of the drone logistics hub is solved by DHPSO effectively.

关键词： Drone logistics location problem mathematical model diversity particle swarm optimization

YOLO-MFD:Remote Sensing Image Object Detection with Multi-Scale Fusion Dynamic Head

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computers, Materials & Continua 2024年第5期79卷 2547-2563页

作者： Zhongyuan Zhang Wenqiu Zhu school of computer Science Hunan University of TechnologyZhuzhou412007China

Remote sensing imagery,due to its high altitude,presents inherent challenges characterized by multiple scales,limited target areas,and intricate *** inherent traits often lead to increased miss and false detection rates when applying object recognition algorithms tailored for remote sensing ***,these complexities contribute to inaccuracies in target localization and hinder precise target *** paper addresses these challenges by proposing a solution:The YOLO-MFD model(YOLO-MFD:Remote Sensing Image Object Detection withMulti-scale Fusion Dynamic Head).Before presenting our method,we delve into the prevalent issues faced in remote sensing imagery ***,we emphasize the struggles of existing object recognition algorithms in comprehensively capturing critical image features amidst varying scales and complex *** resolve these issues,we introduce a novel ***,we propose the implementation of a lightweight multi-scale module called *** module significantly improves the model’s ability to comprehensively capture important image features by merging multi-scale feature *** effectively addresses the issues of missed detection and mistaken alarms that are common in remote sensing ***,an additional layer of small target detection heads is added,and a residual link is established with the higher-level feature extraction module in the backbone *** allows the model to incorporate shallower information,significantly improving the accuracy of target localization in remotely sensed ***,a dynamic head attentionmechanism is *** allows themodel to exhibit greater flexibility and accuracy in recognizing shapes and targets of different ***,the precision of object detection is significantly *** trial results show that the YOLO-MFD model shows improvements of 6.3%,3.5%,and 2.5%over the original YOLOv8 model in Precision,map@0.5 a

关键词： Object detection YOLOv8 multi-scale attention mechanism dynamic detection head

A Fair and Trusted Trading Scheme for Medical Data Based on Smart Contracts

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computers, Materials & Continua 2024年第2期78卷 1843-1859页

作者： Xiaohui Yang Kun Zhang school of Cyber Security and computer Hebei UniversityBaoding071000China

Data is regarded as a valuable asset,and sharing data is a prerequisite for fully exploiting the value of ***,the current medical data sharing scheme lacks a fair incentive mechanism,and the authenticity of data cannot be guaranteed,resulting in low enthusiasm of participants.A fair and trusted medical data trading scheme based on smart contracts is proposed,which aims to encourage participants to be honest and improve their enthusiasm for *** scheme uses zero-knowledge range proof for trusted verification,verifies the authenticity of the patient’s data and the specific attributes of the data before the transaction,and realizes privacy *** the same time,the game pricing strategy selects the best revenue strategy for all parties involved and realizes the fairness and incentive of the transaction *** smart contract is used to complete the verification and game bargaining process,and the blockchain is used as a distributed ledger to record the medical data transaction process to prevent data tampering and transaction ***,by deploying smart contracts on the Ethereum test network and conducting experiments and theoretical calculations,it is proved that the transaction scheme achieves trusted verification and fair bargaining while ensuring privacy protection in a decentralized *** experimental results show that the model improves the credibility and fairness of medical data transactions,maximizes social benefits,encourages more patients and medical institutions to participate in the circulation of medical data,and more fully taps the potential value of medical data.

关键词： Blockchain data transactions zero-knowledge proof game pricing

Facial Expression Recognition with High Response-Based Local Directional Pattern (HR-LDP) Network

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computers, Materials & Continua 2024年第2期78卷 2067-2086页

作者： Sherly Alphonse Harshit Verma school of computer Science and engineering Vellore Institute of TechnologyChennaiIndia

Although lots of research has been done in recognizing facial expressions,there is still a need to increase the accuracy of facial expression recognition,particularly under uncontrolled *** use of Local Directional Patterns(LDP),which has good characteristics for emotion detection has yielded encouraging *** innova-tive end-to-end learnable High Response-based Local Directional Pattern(HR-LDP)network for facial emotion recognition is implemented by employing fixed convolutional filters in the proposed *** combining learnable convolutional layers with fixed-parameter HR-LDP layers made up of eight Kirsch filters and derivable simulated gate functions,this network considerably minimizes the number of network *** cost of the parameters in our fully linked layers is up to 64 times lesser than those in currently used deep learning-based detection *** seven well-known databases,including JAFFE,CK+,MMI,SFEW,OULU-CASIA and MUG,the recognition rates for seven-class facial expression recognition are 99.36%,99.2%,97.8%,60.4%,91.1%and 90.1%,*** results demonstrate the advantage of the proposed work over cutting-edge techniques.

关键词： Emotion classification CNN network HR-LDP

A Lightweight, Searchable, and Controllable EMR Sharing Scheme

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computers, Materials & Continua 2024年第4期79卷 1521-1538页

作者： Xiaohui Yang Peiyin Zhao school of Cyber Security and computer Hebei UniversityBaoding071000China

Electronic medical records (EMR) facilitate the sharing of medical data, but existing sharing schemes suffer fromprivacy leakage and inefficiency. This article proposes a lightweight, searchable, and controllable EMR sharingscheme, which employs a large attribute domain and a linear secret sharing structure (LSSS), the computationaloverhead of encryption and decryption reaches a lightweight constant level, and supports keyword search andpolicy hiding, which improves the high efficiency of medical data sharing. The dynamic accumulator technologyis utilized to enable data owners to flexibly authorize or revoke the access rights of data visitors to the datato achieve controllability of the data. Meanwhile, the data is re-encrypted by Intel Software Guard Extensions(SGX) technology to realize resistance to offline dictionary guessing attacks. In addition, blockchain technology isutilized to achieve credible accountability for abnormal behaviors in the sharing process. The experiments reflectthe obvious advantages of the scheme in terms of encryption and decryption computation overhead and storageoverhead, and theoretically prove the security and controllability in the sharing process, providing a feasible solutionfor the safe and efficient sharing of EMR.

关键词： Lightweight keyword search large attribute domain controllability blockchain

Endogenous Security Formal Definition,Innovation Mechanisms,and Experiment Research in Industrial Internet

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Tsinghua Science and Technology 2024年第2期29卷 492-505页

作者： Hongsong Chen Xintong Han Yiying Zhang school of computer and communication engineering University of Science and Technology BeijingBeijing 100083China

With the rapid development of information technologies,industrial Internet has become more open,and security issues have become more *** endogenous security mechanism can achieve the autonomous immune mechanism without prior ***,endogenous security lacks a scientific and formal definition in industrial ***,firstly we give a formal definition of endogenous security in industrial Internet and propose a new industrial Internet endogenous security architecture with cost ***,the endogenous security innovation mechanism is clearly ***,an improved clone selection algorithm based on federated learning is ***,we analyze the threat model of the industrial Internet identity authentication scenario,and propose cross-domain authentication mechanism based on endogenous key and zero-knowledge *** conduct identity authentication experiments based on two types of blockchains and compare their experimental *** on the experimental analysis,Ethereum alliance blockchain can be used to provide the identity resolution services on the industrial *** of Things Application(IOTA)public blockchain can be used for data aggregation analysis of Internet of Things(IoT)edge ***,we propose three core challenges and solutions of endogenous security in industrial Internet and give future development directions.

关键词： industrial Internet endogenous security architecture federated learning blockchain