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KSKV:Key-Strategy for Key-Value Data Collection with Local Differential Privacy

computer Modeling in engineering & sciences 2024年第6期139卷 3063-3083页

作者： Dan Zhao Yang You Chuanwen Luo Ting Chen Yang Liu Artificial Intelligence Development Research Center Institute of Scientific and Technical Information of ChinaBeijing100038China Industry Development Department NSFOCUS Inc.BeijingChina School of Information Science and Technology Beijing Forestry UniversityBeijing100083China School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu610054China Institute of Computing Technology China Academy of Railway Sciences Corporation LimitedBeijing10081China

In recent years,the research field of data collection under local differential privacy(LDP)has expanded its focus fromelementary data types to includemore complex structural data,such as set-value and graph ***,our comprehensive review of existing literature reveals that there needs to be more studies that engage with key-value data *** studies would simultaneously collect the frequencies of keys and the mean of values associated with each ***,the allocation of the privacy budget between the frequencies of keys and the means of values for each key does not yield an optimal utility *** the importance of obtaining accurate key frequencies and mean estimations for key-value data collection,this paper presents a novel framework:the Key-Strategy Framework forKey-ValueDataCollection under ***,theKey-StrategyUnary Encoding(KS-UE)strategy is proposed within non-interactive frameworks for the purpose of privacy budget allocation to achieve precise key frequencies;subsequently,the Key-Strategy Generalized Randomized Response(KS-GRR)strategy is introduced for interactive frameworks to enhance the efficiency of collecting frequent keys through group-anditeration *** strategies are adapted for scenarios in which users possess either a single or multiple key-value ***,we demonstrate that the variance of KS-UE is lower than that of existing *** claims are substantiated through extensive experimental evaluation on real-world datasets,confirming the effectiveness and efficiency of the KS-UE and KS-GRR strategies.

关键词： Key-value local differential privacy frequency estimation mean estimation data perturbation

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A Two-Stage Approach for Electric Vehicle Routing Problem with Time Windows and Heterogeneous Recharging Stations

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Tsinghua science and technology 2024年第5期29卷 1300-1322页

作者： Tianyu Luo Yong Heng Lining Xing Teng Ren Qi Li Hu Qin Yizhi Hou Kesheng Wang School of Electronic Engineering Xidian UniversityXi’an 71007China Beijing Institute of Electronic System Engineering Beijing 100854China School of Logistics and Transportation Central South University of Forestry and TechnologyChangsha 410004China School of Management Huazhong University of Science and TechnologyWuhan 430074China School of River and Ocean Engineering Chongqing Jiaotong UniversityChongqing 400074China Department of Mechanical and Industrial Engineering Norwegian University of Science and TechnologyTrondheim 7491Norway

An Electric Vehicle(EV)is an appropriate substitution for traditional transportation means for diminishing greenhouse gas ***,decision-makers are beset by the limited driving range caused by the low battery capacity and the long recharging *** resolve the former issue,several transportation companies increases the travel distance of the EV by establishing recharging stations in various *** proposed Electric Vehicle-Routing Problem with Time Windows(E-VRPTW)and recharging stations are constructed in this context;it augments the VRPTW by reinforcing battery capacity ***,super-recharging stations are gradually emerging in the *** can decrease the recharging time for an EV but consume more energy than regular *** this paper,we first extend the E-VRPRTW by adding the elements of super-recharging *** then apply a two-stage heuristic algorithm driven by a dynamic programming process to solve the new proposed problem to minimize the travel and total recharging ***,we compare the experimental results of this approach with other algorithms on several sets of benchmark ***,we analyze the impact of super-recharging stations on the total cost of the logistic plan.

关键词： Electric Vehicle(EV) vehicle routing Dynamic Programming(DP) two-stage algorithm

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Review of National Cybersecurity Policies: A Case Study on Asian Countries 1

Review of National Cybersecurity Policies: A Case Study on A...

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1st IEEE Karachi Section Humanitarian technology Conference, Khi-HTC 2024

作者： Noor, Hera Seelro, Dodo Khan Ali, Syed Abbas NED University of Engineering & Technology Department of Computer Information System Engineering Karachi Pakistan Thar Institute of Engineering Science & Technology NED University of Engineering & Technology Karachi Pakistan

ISBN: (纸本)9798350373042

Accelerating the economic advantages of ICT is one of the finest methods for any nation to boost its economy. Due to the unique topography, governing laws, and cultural traditions of each nation, these colossal challenges must be confronted in each country. This comparative analysis aims to examine these aspects in further detail. To achieve the objectives of this study, research was conducted by collecting and analysing data from publicly accessible sources. This research compares Pakistan and other Asian countries' cybersecurity legislation, regulations, CERTs (national computer emergency response teams), CIIPs (computer intrusion prevention programs), and cyber security training and awareness. Among forty-eight Asian countries, the study focus on comparative analysis of major neighboring (developed or developing) countries of Pakistan such as Japan, China, Turkey, Iraq, Saudi Arabia, UAE, Nepal, Iran, Malaysia, Jordan, India, and Bangladesh. Cyber security has not been a major concern in Pakistan for a very long time, perhaps due to the way the government operates and how slowly it adapts to new technology. Many Asian countries have only ever released one version of their national cyber security plan, whilst Pakistan has never released anything;some other Asian countries are also added in this group. © 2024 IEEE.

关键词： Cybersecurity

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Study on Robot Grasping system of SSVEP-BCI Based on Augmented Reality Stimulus

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Tsinghua science and technology 2023年第2期28卷 322-329页

作者： Shangen Zhang Yuanfang Chen Lijian Zhang Xiaorong Gao Xiaogang Chen School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Beijing Institute of Mechanical Equipment Beijing 100854China Department of Biomedical Engineering School of MedicineTsinghua UniversityBeijing100084China Institute of Biomedical Engineering Chinese Academy of Medical Sciences and Peking Union Medical CollegeTianjin 300192China

Although notable progress has been made in the study of Steady-State Visual Evoked Potential(SSVEP)-based Brain-computer Interface(BCI),several factors that limit the practical applications of BCIs still *** of these factors is the importability of the *** this study,Augmented Reality(AR)technology was introduced to present the visual stimuli of SSVEP-BCI,while the robot grasping experiment was designed to verify the applicability of the AR-BCI *** offline experiment was designed to determine the best stimulus time,while the online experiment was used to complete the robot grasping *** offline experiment revealed that better information transfer rate performance could be achieved when the stimulation time is 2 *** of the online experiment indicate that all 12 subjects could control the robot to complete the robot grasping task,which indicates the applicability of the AR-SSVEP-humanoid robot(NAO)*** study verified the reliability of the AR-BCI system and indicated the applicability of the AR-SSVEP-NAO system in robot grasping tasks.

关键词： Steady-State Visual Evoked Potential(SSVEP) Brain-computer Interface(BCI) Augmented Reality(AR) robot grasping system

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Critical Relation Path Aggregation-Based Industrial Control Component Exploitable Vulnerability Reasoning

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computers, Materials & Continua 2023年第5期75卷 2957-2979页

作者： Zibo Wang Chaobin Huo Yaofang Zhang Shengtao Cheng Yilu Chen Xiaojie Wei Chao Li Bailing Wang School of Computer Science and Technology Harbin Institute of TechnologyWeihai264209China National Computer System Engineering Research Institute of China Beijing100083China School of Cyber Science and Technology Harbin Institute of TechnologyHarbin150001China Weihai Cyberguard Technologies Co.Ltd. Weihai264209China Faculty of Science Vrije Universiteit AmsterdamAmsterdam1081HVNetherlands

With the growing discovery of exposed vulnerabilities in the Industrial Control Components(ICCs),identification of the exploitable ones is urgent for Industrial Control system(ICS)administrators to proactively forecast potential ***,it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis *** address these challenges,we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph(KG)in which relation paths contain abundant potential evidence to support the *** reasoning task in this work refers to determining whether a specific relation is valid between an attacker entity and a possible exploitable vulnerability entity with the help of a collective of the critical *** proposed method consists of three primary building blocks:KG construction,relation path representation,and query relation reasoning.A security-oriented ontology combines exploit modeling,which provides a guideline for the integration of the scattered knowledge while constructing the *** emphasize the role of the aggregation of the attention mechanism in representation learning and ultimate *** order to acquire a high-quality representation,the entity and relation embeddings take advantage of their local structure and related *** critical paths are assigned corresponding attentive weights and then they are aggregated for the determination of the query relation *** particular,similarity calculation is introduced into a critical path selection algorithm,which improves search and reasoning ***,the proposed algorithm avoids redundant paths between the given pairs of *** results show that the proposed method outperforms the state-of-the-art ones in the aspects of embedding quality and query relation reasoning accuracy.

关键词： Path-based reasoning representation learning attention mechanism vulnerability knowledge graph industrial control component

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Prediction of futile recanalisation after endovascular treatment in acute ischaemic stroke:development and validation of a hybrid machine learning model

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Stroke & Vascular Neurology 2024年第6期9卷 631-639页

作者： Ximing Nie Jinxu Yang Xinxin Li Tianming Zhan Dongdong Liu Hongyi Yan Yufei Wei Xiran Liu Jiaping Chen Guoyang Gong Zhenzhou Wu Zhonghua Yang Miao Wen Weibin Gu Yuesong Pan Yong Jiang Xia Meng Tao Liu Jian Cheng Zixiao Li Zhongrong Miao Liping Liu Department of Neurology Capital Medical UniversityBeijingChina China National Clinical Research Center for Neurological Diseases Beijing Tiantan HospitalBeijingChina School of Computer and Communication Engineering University of Science and TechnologyBeijingChina Department of Radiology Beijing Tiantan HospitalBeijingChina Key Laboratory of Biomechanics and Mechanobiology Ministry of EducationSchool of Biological Science and Medical Engineering International Research Institute for Multidisciplinary ScienceBeihang UniversityBeijingChina Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Computer Science and EngineeringBeihang UniversityBeijingChina Department of Interventional Neuroradiology Beijing Tiantan HospitalCapital Medical UniversityBeijingChina

Background Identification of futile recanalisation following endovascular therapy(EVT)in patients with acute ischaemic stroke is both crucial and ***,we present a novel risk stratification system based on hybrid machine learning method for predicting futile *** Hybrid machine learning models were developed to address six clinical scenarios within the EVT and perioperative management *** models were trained on a prospective database using hybrid feature selection technique to predict futile recanalisation following *** optimal model was validated and compared with existing models and scoring systems in a multicentre prospective cohort to develop a hybrid machine learning-based risk stratification system for futile recanalisation *** Using a hybrid feature selection approach,we trained and tested multiple classifiers on two independent patient cohorts(n=1122)to develop a hybrid machine learning-based prediction *** model demonstrated superior discriminative ability compared with other models and scoring systems(area under the curve=0.80,95%CI 0.73 to 0.87)and was transformed into a web application(RESCUE-FR Index)that provides a risk stratification system for individual prediction(accessible online atfr-index.biomind.cn/RESCUE-FR/).Conclusions The proposed hybrid machine learning approach could be used as an individualised risk prediction model to facilitate adherence to clinical practice guidelines and shared decision-making for optimal candidate selection and prognosis assessment in patients undergoing EVT.

关键词： database prediction optimal

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Bald Eagle Search Algorithm with Hierarchical Deep Learning for Internet of Things Assisted Sleep Quality Recognition

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SN computer science 2024年第5期5卷 564页

作者： Duhayyim, Mesfer Al Sharif, Mahir Mohammed Munjal, Muskaan Hilal, Anwer A. Department of Computer Science College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz University Al-Kharj 16273 Saudi Arabia Department of Computer Science Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan Computer Engineering Thapar Institute of Engineering and Technology Punjab Patiala India Department of Information System Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan

Sleep quality prediction in Internet of Things (IoT) involves leveraging a system of interrelated devices to gather as well as analyse related data. Smart devices like wearable devices or smart mattresses endlessly monitor many parameters such as body movement, heart rate, and environmental situations in bedroom. Real-time recommendations and feedback transported to consumers, allowing them to create informed lifestyle changes for superior sleep hygiene. As IoT ecosystem continues to develop, a combination of various data streams as well as classy analytics holds assurance for further refining sleep quality forecasts and improving overall well-being. The article designs a Bald Eagle Search Algorithm with Hierarchical Deep Learning for Internet of Things Assisted Sleep Quality Recognition (BESHDL-SQP) technique. The purpose of the BESHDL-SQP technique is to recognize and classify the quality of the sleep level in the IoT environment. In the presented BESHDL-SQP technique, the preliminary stage of data pre-processing using min–max normalization involved to normalize the input data. For predicting sleep quality, hierarchical long short-term memory (LSTM) technique exploited. Lastly, BES model utilized for optimal hyperparameter selection of LSTM method which helps in attaining enhanced results. To validate better performance of BESHDL-SQP technique, a huge range of simulation analysis is carried out. The extensive results stated that the BESHDL-SQP technique exhibits supreme performance over other models. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Bald eagle search Internet of things LSTM Sleep quality recognition Smart devices

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Dynamic Modeling of Key Operating Parameters for Supercritical Circulating Fluidized Bed Units based on Data-Knowledge-Driven Method

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Journal of Thermal science 2024年第3期33卷 1216-1230页

作者： YU Haoyang GAO Mingming ZHANG Hongfu CHEN Jiyu LIU Jizhen YUE Guangxi The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer EngineeringNorth China Electric Power UniversityBeijing102206China CHN Energy New Energy Technology Research Institute Co. Ltd.Beijing102209China Department of Energy and Power Engineering Tsinghua UniversityBeijing100084China

To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidized bed(SCFB)***,data-knowledge-driven dynamic model of bed temperature,load,and main steam pressure of the SCFB unit has been ***,a knowledge-driven method is employed to develop a dynamic model for key operating parameters of SCFB *** model parameters are determined based on the operating data of the unit and continuously optimized in real ***,Bidirectional Long Short-Term Memory combined with Convolutional Neural Network and Attention Mechanism is utilized to build the dynamic model of bed temperature,load,and main steam ***,a collaboration and integration method based on the critic weight method and the variation coefficient method is proposed to establish data-knowledge-driven model of key operating parameters for SCFB *** model displays great accuracy and fitting ability compared with other methods and effectively captures the dynamic characteristics,which can provide a research basis for the design of intelligent flexible control mode of SCFB unit.

关键词： circulating fluidized bed dynamic model data-knowledge-driven method deep learning power plant

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On the Convergence of Finite Element Domain Decomposition Methods for Discontinuous Subdomain Interfaces

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IEEE Transactions on Antennas and Propagation 2025年第6期73卷 4122-4127页

作者： Xin, Xi-Min Gao, Hong-Wei Wang, Shu Jian Lim, Qi Peng, Zhen Beijing Institute of Technology School of Integrated Circuits and Electronics Beijing100081 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China The University of New Mexico Applied Electromagnetics Group Department of Electrical and Computer Engineering AlbuquerqueNM87131 United States NVIDIA Corporation Santa ClaraCA95050 United States University of Illinois at Urbana–Champaign Department of Electrical and Computer Engineering UrbanaIL61801 United States

In this communication, we propose a finite element domain decomposition method (FE-DDM) with Robin-type transmission conditions (TCs) at discontinuous subdomain interfaces. By definition, these discontinuous interfaces refer to impedance surfaces where electromagnetic (EM) fields exhibit discontinuities, which are common in applications of metamaterials/metasurfaces, frequency-selective surfaces, or thin dielectric layer approximation. Through a detailed convergence study, we propose an optimized set of parameters in the TC. The proposed TC provides convergence for both propagating and evanescent EM waves across subdomain interfaces and is valid for all resistivity values. Numerical experiments are supplied to validate our theoretical analysis, demonstrating the convergence and accuracy of our proposed work. © 1963-2012 IEEE.

关键词： Electromagnetic wave transmission

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Collaborative Service Provisioning for UAV-Assisted Mobile Edge Computing

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Chinese Journal of Electronics 2024年第6期33卷 1504-1514页

作者： Yuben QU Zhenhua WEI Zhen QIN Tao WU Jinghao MA Haipeng DAI Chao DONG The Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space Ministry of Industry and Information Technology Colllege of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Xi'an Research Institute of High Technology Department of Information and Communication Noncommissioned Officer Academy of PAP National University of Defense Technology Department of Computer Science and Technology Nanjing University

Unmanned aerial vehicle(UAV)-assisted mobile edge computing(MEC), as a way of coping with delaysensitive and computing-intensive tasks, is considered to be a key technology to solving the challenges of terrestrial MEC networks. In this work, we study the problem of collaborative service provisioning(CSP) for UAV-assisted MEC. Specifically, taking into account the task latency and other resource constraints, this paper investigates how to minimize the total energy consumption of all terrestrial user equipments, by jointly optimizing computing resource allocation, task offloading, UAV trajectory, and service placement. The CSP problem is a non-convex mixed integer nonlinear programming problem, owing to the complex coupling of mixed integral variables and non-convexity of CSP. To address the CSP problem, this paper proposes an alternating optimization-based solution with the convergence guarantee as follows. We iteratively deal with the joint service placement and task offloading subproblem, and UAV movement trajectory subproblem, by branch and bound and successive convex approximation, respectively,while the closed form of the optimal computation resource allocation can be efficiently obtained. Extensive simulations validate the effectiveness of the proposed algorithm compared to three baselines.

关键词： Energy consumption Multi-access edge computing Collaboration Programming Autonomous aerial vehicles Minimization Trajectory Resource management Optimization Convergence

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