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Redundant Data Detection and Deletion to Meet Privacy Protection Requirements in Blockchain-Based Edge Computing Environment

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China Communications 2024年第3期21卷 149-159页

作者： Zhang Lejun Peng Minghui Su Shen Wang Weizheng Jin Zilong Su Yansen Chen Huiling Guo Ran Sergey Gataullin Cyberspace institute Advanced Technology Guangzhou UniversityGuangzhou 510006China College of Information Engineering Yangzhou UniversityYangzhou 225127China School Math&computer science Quanzhou Normal UniversityQuanzhou 362000China computer science Department City University of Hong KongHong Kong 999077China School of computer and Software Nanjing University of Information Science and TechnologyNanjing 21004China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei 230601China Department of computer science and Artificial Intelligence Wenzhou UniversityWenzhou 325035China Guangzhou University Library Guangzhou UniversityGuangzhou 510006China Central economic and Mathematics institute Russian Academy of Sciences MIREA-Russian Technological University Moscow RegionRussia

With the rapid development of information technology,IoT devices play a huge role in physiological health data *** exponential growth of medical data requires us to reasonably allocate storage space for cloud servers and edge *** storage capacity of edge nodes close to users is *** should store hotspot data in edge nodes as much as possible,so as to ensure response timeliness and access hit rate;However,the current scheme cannot guarantee that every sub-message in a complete data stored by the edge node meets the requirements of hot data;How to complete the detection and deletion of redundant data in edge nodes under the premise of protecting user privacy and data dynamic integrity has become a challenging *** paper proposes a redundant data detection method that meets the privacy protection *** scanning the cipher text,it is determined whether each sub-message of the data in the edge node meets the requirements of the hot *** has the same effect as zero-knowledge proof,and it will not reveal the privacy of *** addition,for redundant sub-data that does not meet the requirements of hot data,our paper proposes a redundant data deletion scheme that meets the dynamic integrity of the *** use Content Extraction Signature(CES)to generate the remaining hot data signature after the redundant data is *** feasibility of the scheme is proved through safety analysis and efficiency analysis.

关键词： blockchain data integrity edge computing privacy protection redundant data

Bayesian and Non-Bayesian Analysis for the Sine Generalized Linear Exponential Model under Progressively Censored Data

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computer Modeling in Engineering & sciences 2024年第9期140卷 2795-2823页

作者： Naif Alotaibi A.S.Al-Moisheer Ibrahim Elbatal Mohammed Elgarhy Ehab M.Almetwally Department of Mathematics and Statistics Faculty of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Mathematics College of ScienceJouf UniversityP.O.Box 848Sakaka72351Saudi Arabia Mathematics and computer science Department Faculty of ScienceBeni-Suef UniversityBeni-Suef62521Egypt Department of Basic sciences Higher Institute of Administrative SciencesBelbeisEgypt Faculty of Business Administration Delta University for Science and TechnologyGamasa11152Egypt

This article introduces a novel variant of the generalized linear exponential(GLE)distribution,known as the sine generalized linear exponential(SGLE)*** SGLE distribution utilizes the sine transformation to enhance its *** updated distribution is very adaptable and may be efficiently used in the modeling of survival data and dependability *** suggested model incorporates a hazard rate function(HRF)that may display a rising,J-shaped,or bathtub form,depending on its unique *** model includes many well-known lifespan distributions as separate *** suggested model is accompanied with a range of statistical *** model parameters are examined using the techniques of maximum likelihood and Bayesian estimation using progressively censored *** order to evaluate the effectiveness of these techniques,we provide a set of simulated data for testing *** relevance of the newly presented model is shown via two real-world dataset applications,highlighting its superiority over other respected similar models.

关键词： Sine G family generalized linear failure rate progressively censored data moments maximum likelihood estimation Bayesian estimation simulation

Abnormal Traffic Detection for Internet of Things Based on an Improved Residual Network

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computers, Materials & Continua 2024年第6期79卷 4433-4448页

作者： Tingting Su Jia Wang Wei Hu Gaoqiang Dong Jeon Gwanggil School of computer science and Technology Xinjiang UniversityUrumqi830046China School of Cyber science and Engineering Jinling Institute of Technology CityNanjing210000China College of Information Technology Incheon National UniversityIncheon22012Korea

Along with the progression of Internet of Things(IoT)technology,network terminals are becoming continuously more *** has been widely applied in various scenarios,including urban infrastructure,transportation,industry,personal life,and other socio-economic *** introduction of deep learning has brought new security challenges,like an increment in abnormal traffic,which threatens network *** feature extraction leads to less accurate classification *** abnormal traffic detection,the data of network traffic is high-dimensional and *** data not only increases the computational burden of model training but also makes information extraction more *** address these issues,this paper proposes an MD-MRD-ResNeXt model for abnormal network traffic *** fully utilize the multi-scale information in network traffic,a Multi-scale Dilated feature extraction(MD)block is *** module can effectively understand and process information at various scales and uses dilated convolution technology to significantly broaden the model’s receptive *** proposed Max-feature-map Residual with Dual-channel pooling(MRD)block integrates the maximum feature map with the residual *** module ensures the model focuses on key information,thereby optimizing computational efficiency and reducing unnecessary information *** results show that compared to the latest methods,the proposed abnormal traffic detection model improves accuracy by about 2%.

关键词： Abnormal network traffic deep learning residual network multi-scale feature extraction max-feature-map

Utilizing engineered extracellular vesicles as delivery vectors in the management of ischemic stroke:a special outlook on mitochondrial delivery

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Neural Regeneration Research 2025年第8期20卷 2181-2198页

作者： Jiali Chen Yiyang Li Xingping Quan Jinfen Chen Yan Han Li Yang Manfei Zhou Greta Seng Peng Mok Ruibing Wang Yonghua Zhao institute of Chinese Medical sciences State Key Laboratory of Quality Research in Chinese MedicineUniversity of MacaoTaipaMacao Special Administrative RegionChina Department of Pharmacy Hunan Provincial People’s Hospitalthe First Affiliated Hospital of Hunan Normal UniversityChangshaHunan ProvinceChina Department of Electrical and computer Engineering University of MacaoTaipaMacao Special Administrative RegionChina Department of Pharmaceutical sciences Faculty of Health SciencesUniversity of MacaoTaipaMacao Special Administrative RegionChina

Ischemic stroke is a secondary cause of mortality worldwide,imposing considerable medical and economic burdens on *** vesicles,serving as natural nanocarriers for drug delivery,exhibit excellent biocompatibility in vivo and have significant advantages in the management of ischemic ***,the uncertain distribution and rapid clearance of extracellular vesicles impede their delivery *** utilizing membrane decoration or by encapsulating therapeutic cargo within extracellular vesicles,their delivery efficacy may be greatly ***,previous studies have indicated that microvesicles,a subset of large-sized extracellular vesicles,can transport mitochondria to neighboring cells,thereby aiding in the restoration of mitochondrial function post-ischemic *** extracellular vesicles have also demonstrated the capability to transfer mitochondrial components,such as proteins or deoxyribonucleic acid,or their sub-components,for extracellular vesicle-based ischemic stroke *** this review,we undertake a comparative analysis of the isolation techniques employed for extracellular vesicles and present an overview of the current dominant extracellular vesicle modification *** the complex facets of treating ischemic stroke,we also delineate various extracellular vesicle modification approaches which are suited to different facets of the treatment ***,given the burgeoning interest in mitochondrial delivery,we delved into the feasibility and existing research findings on the transportation of mitochondrial fractions or intact mitochondria through small extracellular vesicles and microvesicles to offer a fresh perspective on ischemic stroke therapy.

关键词： delivery engineering extracellular vesicles identification ischemic stroke isolation mitochondria targeting strategy therapeutic effects

Urban Electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

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computers, Materials & Continua 2024年第7期80卷 1163-1177页

作者： Amel Ali Alhussan Doaa Sami Khafaga El-Sayed M.El-kenawy Marwa M.Eid Abdelhameed Ibrahim Department of computer sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric *** demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of *** establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this ***,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of *** the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging *** is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic *** vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering ***,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature ***,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic *** on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is *** results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algori

关键词： Electric vehicle graylag goose optimization metaheuristics optimization machine learning

The Lambert-G Family:Properties,Inference,and Applications

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computer Modeling in Engineering & sciences 2024年第7期140卷 513-536页

作者： Jamal N.Al Abbasi Ahmed Z.Afify Badr Alnssyan Mustafa S.Shama Accounting Department Ashur UniversityBaghdad10011Iraq Department of Statistics Mathematics and InsuranceBenha UniversityBenha13511Egypt Department of Management Information Systems and Production Management College of Business and EconomicsQassim UniversityBuraydah51452Saudi Arabia Department of Basic sciences Common First Year(CFY)King Saud UniversityRiyadh11362Saudi Arabia Department of Mathematics and Statistics Osim Higher Institute of Administrative ScienceOsim12961Egypt

This study proposes a new flexible family of distributions called the Lambert-G *** Lambert family is very flexible and exhibits desirable *** three-parameter special sub-models provide all significantmonotonic and non-monotonic failure rates.A special sub-model of the Lambert family called the Lambert-Lomax(LL)distribution is *** expressions for the LL statistical properties are *** of the LL distribution are addressed mathematically based on its hazard *** estimation of the LL parameters is discussed using six estimation *** performance of this estimation method is explored through simulation *** usefulness and flexibility of the LL distribution are demonstrated empirically using two real-life data *** LL model better fits the exponentiated Lomax,inverse power Lomax,Lomax-Rayleigh,power Lomax,and Lomax distributions.

关键词： Lambert function Lomax distribution maximum likelihood hazard function statistical model simulation

A Lambda Layer-Based Convolutional Sequence Embedding Model for Click-Through Rate Prediction

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Wuhan University Journal of Natural sciences 2024年第3期29卷 198-208页

作者： ZHOU Liliang YUAN Shili FENG Zijian DAI Guilan ZHOU Guofu Tenth Research institute China Electronics Technology Group CorporationChengdu 610000SichuanChina Department of computer science Nanjing University of Posts and TelecommunicationsNanjing 210023JiangsuChina Research Institution of Information Technology Tsinghua UniversityBeijing 100084China School of computer science Wuhan UniversityWuhan 430072HubeiChina

In the era of intelligent economy, the click-through rate(CTR) prediction system can evaluate massive service information based on user historical information, and screen out the products that are most likely to be favored by users, thus realizing customized push of information and achieve the ultimate goal of improving economic benefits. Sequence modeling is one of the main research directions of CTR prediction models based on deep learning. The user's general interest hidden in the entire click history and the short-term interest hidden in the recent click behaviors have different influences on the CTR prediction results, which are highly important. In terms of capturing the user's general interest, existing models paid more attention to the relationships between item embedding vectors(point-level), while ignoring the relationships between elements in item embedding vectors(union-level). The Lambda layer-based Convolutional Sequence Embedding(LCSE) model proposed in this paper uses the Lambda layer to capture features from click history through weight distribution, and uses horizontal and vertical filters on this basis to learn the user's general preferences from union-level and point-level. In addition, we also incorporate the user's short-term preferences captured by the embedding-based convolutional model to further improve the prediction results. The AUC(Area Under Curve) values of the LCSE model on the datasets Electronic, Movie & TV and MovieLens are 0.870 7, 0.903 6 and 0.946 7, improving 0.45%, 0.36% and 0.07% over the Caser model, proving the effectiveness of our proposed model.

关键词： click-through rate prediction deep learning attention mechanism convolutional neural network

Coupon-based Demand Response for Consumers Facing Flat-rate Retail Pricing

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 1887-1900页

作者： Hongxun Hui Yi Ding Kaining Luan Tao Chen Yonghua Song Saifur Rahman State Key Laboratory of Internet of Things for Smart City and the Department of Electrical and computer Engineering University of MacaoMacao 999078China. College of Electrical Engineering Zhejiang UniversityHangzhou 310027China State Grid Jiangsu Electric Power Co. LTD.Nanjing 210000China School of Electrical Engineering Southeast UniversityNanjing 210096China Advanced Research institute and Department of Electrical and computer Engineering Virginia Polytechnic Institute and State UniversityVA 22203USA

Even though smart meters have been widely used in power systems around the world,many consumers are still finding it hard to participate in demand response(DR)due to flat-rate retail pricing *** address this issue,this paper proposes a coupon-based demand response(CDR)scheme to achieve equivalent dynamic retail prices to inspire consumers’inherent ***,a security-constrained unit commitment optimization model is developed in the day-ahead market to obtain coupon rewards,which are then broadcast to consumers to motivate them to reschedule their power consumption *** evaluate the adjustment value of consumers’power consumption,a collective utility function is proposed to formulate the relationship between power quantity and coupon *** this basis,the security-constrained economic dispatch model is developed in the intra-day market to reschedule generating units’output power according to real-time load demands and fluctuating renewable *** the operation interval,a settlement method is developed to quantify consumers’electricity fees and coupon benefits on a monthly *** proposed CDR scheme avoids real-time iterative bidding process and effectively decreases the difficulty of massive,small consumers participating in *** proposed CDR is implemented in a realistic DR project in China to verify consumers’energy cost and renewables’curtailment can both be decreased.

关键词： Coupons demand response flat-rate retail pricing renewable energies small consumers

Financial inclusion and carbon emissions in Asia:Implications for environmental sustainability

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economic and Political Studies 2024年第1期12卷 88-104页

作者： Shahzad Hussain Tanveer Ahmad Sabeeh Ullah Ajid Ur Rehmand Syed Jawad Hussain Shahzad Department of Business Administration Rawalpindi Women UniversityRawalpindiPakistan institute of Business Studies Kohat University of Science and TechnologyKohatPakistan institute of Business and Management sciences Faculty of Management and Computer SciencesThe University of AgriculturePeshawarPakistan NUST Business School National University of Sciences and TechnologyIslamabadPakistan Finance Control and Law DepartmentMontpellier Business SchoolMontpellierFrance

This study explores how carbon emissions are affected by financial *** a balanced panel data set of 26 Asian countries,we compute a composite index,through the principal component analysis(PCA)technique,of financial inclusion based on a set of attributes related to financial *** main analysis also delineates the subsamples of developed and developing Asian *** results reveal a long(short)-run positive(negative)impact of financial inclusion on carbon emissions across the Asian *** finding is also true for the developed country subsample,implying nonlinearity in shortand long-run *** the developing countries,a more pronounced long-run positive impact compared to developed countries is ***,the pairwise causality test results indicate the existence of bi-directional causality between financial inclusion and carbon *** findings have important policy implications,especially in the context of the strategic integration of financial inclusion and climate change strategies.

关键词： Financial inclusion CO2 emissions climate change sustainable development Asian countries