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arXiv 2024年

作者： Liu, Shang Du, Hao Cao, Yang Yan, Bo Liu, Jinfei Yoshikawa, Masatoshi School of Computer Science and Technology China University of Mining and Technology Mine Digitization Engineering Research Center of the Ministry of Education Xuzhou China Hokkaido University Japan Institute of Science Tokyo Japan Beijing University of Posts and Telecommunications China Zhejiang University China Osaka Seikei University Japan

Differentially private graph analysis is a powerful tool for deriving insights from diverse graph data while protecting individual information. Designing private analytic algorithms for different graph queries often requires starting from scratch. In contrast, differentially private synthetic graph generation offers a general paradigm that supports one-time generation for multiple queries. Although various differentially private graph generation algorithms have been proposed, comparing them effectively remains challenging due to various factors, including differing privacy definitions, diverse graph datasets, varied privacy requirements, and multiple utility metrics. To this end, we propose PGB (Private Graph Benchmark), a comprehensive benchmark designed to enable researchers to compare differentially private graph generation algorithms fairly. We begin by identifying four essential elements of existing works as a 4-tuple: mechanisms, graph datasets, privacy requirements, and utility metrics. We discuss principles regarding these elements to ensure the comprehensiveness of a benchmark. Next, we present a benchmark instantiation that adheres to all principles, establishing a new method to evaluate existing and newly proposed graph generation algorithms. Through extensive theoretical and empirical analysis, we gain valuable insights into the strengths and weaknesses of prior algorithms. Our results indicate that there is no universal solution for all possible cases. Finally, we provide guidelines to help researchers select appropriate mechanisms for various scenarios. Copyright © 2024, The Authors. All rights reserved.

关键词： Differential privacy

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Light-controlled smart materials:Supramolecular regulation and applications

Smart Molecules

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Smart Molecules 2024年第4期2卷 1-24页

作者： Zi-Hao Liao Feng Wang Key Laboratory of Materials Chemistry for Energy Conversion and Storage(Huazhong University of Science and Technology)of Ministry of Education Hubei Key Laboratory of Material Chemistry and Service FailureHubei Engineering Research Center for Biomaterials and Medical Protective MaterialsSchool of Chemistry and Chemical EngineeringHuazhong University of Science and TechnologyWuhanChina Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization Guangdong HUST Industrial Technology Research InstituteDongguanChina

Smart materials serve as the fundamental cornerstone supporting humanity's transition into the intelligent *** materials possess the capability to perceive external stimuli and respond ***-controlled smart materials(LCSMs)are a significant category that can sense and respond to light ***,being a non-invasive,precisely regulated,and remotely controllable source of physical stimulation,makes LCSMs indispensable in certain application ***,the construction of LCSMs using supramolecular strategies has emerged as a significant research *** assembly,based on non-covalent bonding,offers dynamic,reversible,and biomimetic *** integrating supramolecular systems with photoresponsive molecular building blocks,these materials can achieve synergistic and rich intelligent stimulus *** review delves into the latest research advancements in LCSMs based on supramolecular *** are four sections in this *** first section defines LCSMs and outlines their *** second section discusses the design approaches of supramolecular *** third section highlights the latest advancements on supramolecular LCSMs over the past 3 *** fourth section summarizes the current research and provides insights into the future development of this field.

关键词： intelligent materials photochemistry photochromism photoresponsive materials supramolecular chemistry

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Correction to: Uncertainty-corrected fractional generalized Pareto motion for lithium-ion battery life prediction and value-at-risk-based maintenance framework (Nonlinear Dynamics, (2025), 10.1007/s11071-024-10815-4)

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Nonlinear Dynamics 2025年第12期113卷 14963-14963页

作者： Wang, Zhen Chen, Jianxue Gao, Yan Song, Wanqing Karimi, Hamid Reza Zhang, Yujin Qi, Deyu School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai201620 China Minnan University of Science and Technology Fujian Quanzhou362700 China Department of Mechanical Engineering Politecnico Di Milano Via La Masa 1 Milan20156 Italy Institute of Digitization Science and Technology South China Business College Guangdong University of Foreign Studies Guangzhou510545 China

The original article was published without its funding notes: This research was funded by the Major Project of science and technology of Quanzhou (Grant no. 2022GZ8), the technology Innovation Project of Minnan University of science and technology (Grant No. 23XTD113), Industry-University-Research Innovation Fund of the Chinese Ministry of Education (2021ZYB01003) and Education Department of Guangdong Province (2022GCZX013). The original article has been updated to include the note. The original article has been corrected. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

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通过局部结构异质性增强无铅Bifeo 3 -Batio 3陶瓷的原位压电性能和热稳定性

SSRN

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SSRN 2024年

作者： Wang, Xueting Yang, Xinyi Huang, Fenghao Yang, Huabin Guangxi Key Laboratory of Information Materials Guilin University of Electronic Technology Guangxi Guilin541004 China Guangdong HUST Industrial Technology Research Institute Guangdong Provincial Key Laboratory of Manufacturing Equipment Digitization Guangdong Dongguan523808 China School of Material Science and Engineering Guilin University of Electronic Technology Guangxi Guilin541004 China

在钙钛矿结构铋基压电陶瓷中，实际工作温度的升高通常伴随着压电常数（d 33）的急剧恶化，这是一个尚未解决的悖论，严重限制了其实际应用。本文提出了采用协同策略设计的0.67BF-0.33BT-0.02BZT- x BA无铅压电陶瓷。高T dr和大d 33相... 详细信息

在钙钛矿结构铋基压电陶瓷中，实际工作温度的升高通常伴随着压电常数（d 33）的急剧恶化，这是一个尚未解决的悖论，严重限制了其实际应用。本文提出了采用协同策略设计的0.67BF-0.33BT-0.02BZT- x BA无铅压电陶瓷。高T dr和大d 33相容性是通过调节多相共存中极性相的比例、晶粒尺寸和域结构来实现的。X =0.01 陶瓷的原位 d 33范围高达 801pC/N，T dr=361°C，并且T c =432°C。该研究结果为高性能BF-BT基无铅压电陶瓷的制备提供了一种新颖的设计思路。 © 2024, The Authors. All rights reserved.

关键词： Barium titanate

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Enhanced In-Situ Piezoelectric Properties and Thermal Stability of Lead-Free Bifeo3-Batio3 Ceramics by Local Structural Heterogeneity

SSRN

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SSRN 2024年

In perovskite-structure Bi-based piezoelectric ceramics, an increase in the actual operating temperature is usually accompanied by a sharp deterioration of the piezoelectric constant (d33), an unresolved paradox that severely limits their practical applications. In this paper, 0.67BF-0.33BT-0.02BZT-xBA lead-free piezoelectric ceramics designed using a synergistic strategy are presented. High Tdr and large d33 compatibility is achieved by regulating the ratio of polar phases in multiphase coexistence, grain size and domain structure. X=0.01 ceramics have an in-situ d33 ranging up to 801pC/N, Tdr=361°C, and Tc=432°C. The results of this study provide a novel design idea for the preparation of high-performance BF-BT-based lead-free piezoelectric ceramics. © 2024, The Authors. All rights reserved.

关键词： Piezoelectricity

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Big Data Theory of Industrial Supply Chain Based on Complex Information Integration

Engineering Intelligent Systems

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Engineering Intelligent Systems 2024年第5期32卷 421-433页

作者： Dai, Weihuang Zhu, Zijiang Qi, Deyu South China Business College of Guangdong University of Foreign Studies Guangdong Guangzhou510545 China Institute of Digitization Science and Technology South China Business College of Guangdong University of Foreign Studies Guangdong Guangzhou510545 China School of Computer Science South China Business College of Guangdong University of Foreign Studies Guangdong Guangzhou510545 China

The development of big data provides a more adequate foundation for the management and construction of traditional industrial supply chain finance. This article discusses the research on big data theory in industrial supply chains based on complex information integration. This paper proposes and designs a big data system for the common industry supply chain. The whole system architecture is comprised of: platform support layer, data resource layer, data processing layer, internal business layer and public service layer. The platform support layer provides public services for financial big data, and addresses all problems related to infrastructure, hardware resources, and software environment. The data resource layer is used for the management of the list of rights and responsibilities and the list of events. The data processing layer can transform the information into understandable knowledge. The internal business layer is logically isolated from the Internet to ensure information security. The operation module of the supply chain industry standardizes the interface between logistics, the supply chain management system and related collaborative supervision system. Based on this, the research on complex information integration of industrial supply chain is carried out to improve the parallel processing efficiency of big data. Through complex information integration, the parallel processing efficiency of big data in industrial supply chain has increased by 76%, the execution time is short, and the alignment performance is better. The results show that the system designed in this paper can reasonably develop the data resources in the online supply chain and improve the parallel processing efficiency of big data in the industrial supply chain. © 2024 CRL Publishing Ltd.

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Data Driven based Malicious URL Detection using Explainable AI

Data Driven based Malicious URL Detection using Explainable ...

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IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Saranda Poddar Deepraj Chowdhury Ashutosh Dhar Dwivedi Raghava Rao Mukkamala Department of Computer Science RCC Institute of Information Technology Kolkata India Department of Electronics and Communication International Institute of Information Technology Naya Raipur India Department of Digitization Centre for Business Data Analytics Copenhagen Business School Frederiksberg Denmark

With the ever-increasing reach of the internet, and its increasing access through various types of devices, the spread of malware, phishing attempts, etc. have steadily been increasing, along with their level of sophistication. Thus it becomes very important to conduct research on different methods to prevent such harmful attacks on systems and users. Using a malicious URL is the common way for hackers to attack a system, thus, to accommodate the variety attack vectors of malicious websites, 21 features were extracted from 651,191 URLs to train the proposed model. A two-stage stacked ensemble learning model, based on gradient boosting methods and random forest, has been trained and tested in the 70:30 ratio of the 651,191 URLs, and an accuracy of 97% has been achieved. Then Explainable AI (XAI) has been used to clearly explain the working of the model, and study the impact of each of the 21 features on the 4 class predictions (benign, defacement, phishing and malware).

关键词： Uniform resource locators Phishing Forestry Predictive models Feature extraction Malware Security

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On-Orbit Identification of Unstable Micro-Propulsion System Parameters Using Drag-Free Control

On-Orbit Identification of Unstable Micro-Propulsion System ...

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Data Driven Control and Learning Systems (DDCLS)

作者： Nuo Xu Xiwang Xia Zhaoxiong Li Xiongfeng He Ning Guo Pengcheng Wang Yonghe Zhang Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai P. R. China University of Chinese Academy of Sciences Beijing P. R.China Chinese Academy of Sciences Key Laboratory for Satellite Digitization Technology Shanghai P. R.China Science and Technology on Vacuum Technology and Physics Lab Lanzhou Institute of Physics Lanzhou P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

Space gravitational wave detection spacecraft is equipped with a drag-free control and micro-propulsion system, and adopts thrust closed-loop feedback control structure. An on-orbit high accuracy estimation algorithm of micro-thruster parameters based on drag-free control model is proposed in this paper in order to deal with the problem of unsteady nominal thrust caused by thruster failure or aging and and extend thrusters lifespan. In this method, the recursive gain and covariance are designed to estimate the parameter matrix of system. Adaptive forgetting factors are added to the covariance matrix for designing a fading memory window to determine the influence of prior data on the results. At the same time, the thruster state is deconstructed into three parts: thrust gain, thrust direction and lever arm to facilitate the redistribution of control force and torque. Simulations show that the on-orbit thrust identification errors of the proposed method in different micro-propulsion states are all at sub-micro-newton level, and the noise is less than $0.1\mu N/\sqrt{Hz}$ which has capability to meet the requirements corresponding to drag-free control system.

关键词： Space vehicles Fading channels Accuracy Torque Attitude control Heuristic algorithms Simulation

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Resource Demand Analysis of IoT Terminal Chips Based on Atomic Service Modeling

Resource Demand Analysis of IoT Terminal Chips Based on Atom...

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IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia)

作者： Yigong Zhang Yongjie Nie Siyang Liu Jian Li Yuxing Mao Tianyan Jiang Xianping Zhao Tiejun Cao School of Electrical Engineering Chongqing University Chongqing China Electric Power Science Research Institute of Yunnan Power Grid Co. Ltd. Kunming China Department of Technology Innovation and Digitization Yunnan Power Grid Co. Ltd. Kunming China

The diversity of smart city scenarios makes it difficult for Internet of Things terminals (IoTT) to accurately match their differential demands for computing, storage, and communication resources with general-purpose MCU chips, leading to resource redundancy and cost increases. Due to the lack of resource demand analysis for IoT application scenarios, traditional customized chip design methods cannot be directly used for the design of IoTT chips. To address this issue, we propose building a decoupled atomic service set to analyze the resource demands of practical IoT application scenarios. Specifically, we use timed automata to model the atomic services of IoTT, characterize the event attributes and time constraints of atomic services, and use UPPAAL to verify the reachability of the timed automata model of the proposed atomic services. Finally, these atomic services are mapped to the resource call situation of RISC-V instructions to guide the architecture design of specialized chips for IoTT.

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AUTODEEPSLICE: A Data Driven Network Slicing Technique of 5G network using Automatic Deep Learning

AUTODEEPSLICE: A Data Driven Network Slicing Technique of 5G...

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IEEE Globecom Workshops

作者： Deepraj Chowdhury Rupanjan Das Risav Rana Ashutosh Dhar Dwivedi Pushpita Chatterjee Raghava Rao Mukkamala Department of Electronics and Communication International Institute of Information Technology Naya Raipur India Department of Digitization Centre for Business Data Analytics Copenhagen Business School Frederiksberg Denmark Department of Computer Science Tennessee State University Nashville USA

ISBN: (纸本)9781665459761

With the advancement of mobile networks, and the revolution of mobile communication from 1G to 5G, human dependency has increased, so it has become the most priority to provide an efficient and highly reliable network. The 5G networks need high capacity and high-speed data transfer, with the least latency and increased security. 5G service providers are trying to find a programmable solution that can handle a huge number of independent service users on the same physical infrastructure. Network slicing is used to provide end-to-end network resource allocation. To accelerate the 5G network performance, Artificial Intelligence (AI) powered data-driven based decisions will be used for future communication. In this proposed work, Automatic deep learning has been implemented, where the hyperparameter will automatically select the algorithm and tune the hyperparameter. The proposed model AUTODEEPSLICE efficiently makes intelligent decisions and will choose the best network slice at the time of network breakdown.

关键词： Deep learning Wireless communication 5G mobile communication Network slicing Load management Security Resource management

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