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IET Cyber-Systems and Robotics 2024年第1期6卷 24-37页

作者： Xin Peng Gaofeng su Raja Sengupta Department of Civil and Environmental Engineering University of CaliforniaBerkeleyBerkeleyCaliforniaUSA

Catastrophic natural disasters like earthquakes can cause infrastructure ***-gency response agencies need to assess damage precisely while repeating this process for infrastructures with different shapes and *** authors aim for an autonomous Unmanned Aerial Vehicle(UAV)platform equipped with a 3D LiDAR sensor to comprehensively and accurately scan the infrastructure and map it with a predefined resolution *** the inspection,the UAV needs to decide on the Next Best View(NBV)position to maximize the gathered information while avoiding collision at high *** authors propose solving this problem by implementing a hierarchical closed‐loop control system consisting of a global planner and a local *** global NBV planner decides the general UAV direction based on a history of measurements from the LiDAR sensor,and the local planner considers the UAV dynamics and enables the UAV to fly at high speed with the latest LiDAR *** proposed system is vali-dated through the Regional Scale Autonomous Swarm Damage Assessment simulator,which is built by the *** extensive testing in three unique and highly constrained infrastructure environments,the autonomous UAV inspection system suc-cessfully explored and mapped the infrastructures,demonstrating its versatility and applicability across various shapes of infrastructure.

关键词： autonomy hierarchical control structural health inspection Unmanned Aerial Vehicle

Numerical Simulation of Droplet Generation in Coaxial Microchannels

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Fluid Dynamics & Materials Processing 2024年第3期20卷 487-504页

作者： Zongjun Yin Rong su Hui Xu School of Mechanical Engineering Anhui Institute of Information TechnologyWuhu241100China

In this study,numerical simulations of the pinching-off phenomena displayed by the dispersed phase in a continuous phase have been conducted using COMSOL Multiphysics(level-set method).Four flow patterns,namely“drop flow”,“jet flow”,“squeeze flow”,and“co-flow”,have been obtained for different flow velocity ratios,channel diameter ratios,density ratios,viscosity ratios,and surface *** flow pattern map of two-phase flow in coaxial microchannels has been obtained accordingly,and the associated droplet generation process has been critically discussed considering the related frequency,diameter,and pinch-off *** particular,it is shown that the larger the flow velocity ratio,the smaller the diameter of generated droplets and the shorter the pinch-off *** pinch-off length of a droplet is influenced by the channel diameter ratio and density *** changes in viscosity ratio have a negligible influence on the droplet generation pinching *** an increase in surface tension,the frequency of generation and pinch-off length of droplets decrease,but for small surface tension the generation diameter of droplet increases.

关键词： Droplet generation characteristics coaxial microchannels flow patterns pinch-off length

Public Opinions on ChatGPT:An Analysis of Reddit Discussions by Using Sentiment Analysis,Topic Modeling,and SWOT Analysis

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Data Intelligence 2024年第2期6卷 344-374页

作者： Shwe Zin su Naing Piyachat Udomwong International College of Digital Innovation and Financial Technology 239 Nimmanhaemin Road SuthepMuangChiang Mai 50200Thailand

The sudden arrival of AI(Artificial Intelligence) into people's daily lives all around the world was marked by the introduction of ChatGPT, which was officially released on November 30, 2022. This AI invasion in our lives drew the attention of not only tech enthusiasts but also scholars from diverse fields, as its capacity extends across various fields. Consequently, numerous articles and journals have been discussing ChatGPT, making it a headline for several topics. However, it does not reflect most public opinion about the product. Therefore, this paper investigated the public's opinions on ChatGPT through topic modelling, Vader-based sentiment analysis and SWOT analysis. To gather data for this study, 202905 comments from the Reddit platform were collected between December 2022 and December 2023. The findings reveal that the Reddit community engaged in discussions related to ChatGPT, covering a range of topics including comparisons with traditional search engines, the impacts on software development, job market, and education industry, exploring ChatGPT's responses on entertainment and politics, the responses from Dan, the alter ego of ChatGPT, the ethical usage of user data as well as queries related to the AI-generated images. The sentiment analysis indicates that most people hold positive views towards this innovative technology across these several aspects. However, concerns also arise regarding the potential negative impacts associated with this product. The SWOT analysis of these results highlights both the strengths and pain points, market opportunities and threats associated with ChatGPT. This analysis also serves as a foundation for providing recommendations aimed at the product development and policy implementation in this paper.

关键词： ChatGPT Sentiment analysis Topic modeling SWOT analysis Public opinion Reddit

ON THE CAUCHY PROBLEM FOR THE GENERALIZED BOUSSINESQ EQUATION WITH A DAMPED TERM

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Acta Mathematica Scientia 2024年第5期44卷 1766-1786页

作者： Xiao su Shubin WANG College of Science Henan University of TechnologyZhengzhou450001China School of Mathematics and Statistics Zhengzhou UniversityZhengzhou450001China

This paper is devoted to the Cauchy problem for the generalized damped Boussinesq equation with a nonlinear source term in the natural energy *** the help of linear time-space estimates,we establish the local existence and uniqueness of solutions by means of the contraction mapping *** global existence and blow-up of the solutions at both subcritical and critical initial energy levels are ***,we construct the sufficient conditions of finite time blow-up of the solutions with arbitrary positive initial energy.

关键词： damped Boussinesq equation Cauchy problem global solutions blow-up

Cross-Domain Bilateral Access Control on Blockchain-Cloud Based Data Trading System

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 671-688页

作者： Youngho Park su Jin Shin Sang Uk Shin Electronics and Information Communications Research Center Pukyong National UniversityBusan48513Republic of Korea Department of Information Security Graduate SchoolPukyong National UniversityBusan48513Republic of Korea Division of Computer Engineering Pukyong National UniversityBusan48513Republic of Korea

Data trading enables data owners and data requesters to sell and purchase *** the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of ***,to reduce the on-chain storage cost,a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading ***,the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data *** the data marketplace,it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple *** this paper,we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading *** consider a system model that consists of domain authorities,data senders,data receivers,a blockchain layer,and a cloud *** proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic *** the proposed protocol,the outsourced data of the sender is encrypted under the target receiver’s identity,and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature ***,data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each *** demonstrate efficiency,we evaluate the performance of the proposed protocol and compare it with existing studies.

关键词： Bilateral access control blockchain data sharing policy-match

Sources, enrichment mechanisms, and resource effects of rare metal elements-enriched geothermal springs in Xizang, China

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Science China Earth Sciences 2024年第11期67卷 3476-3499页

作者： Fei XUE Hongbing TAN Xiying ZHANG Jinbao su School of Earth Sciences and Engineering Hohai University Qinghai Provincial Key Laboratory of Geology and Environment of Salt Lakes Qinghai Institute of Salt Lakes Chinese Academy of Sciences School of Oceanology Hohai University

Rare metals such as lithium(Li), rubidium(Rb), and cesium(Cs) are strategically crucial mineral resources for the development of emerging industries in China. Ensuring a stable long-term supply of these resources is essential. The geothermal systems in Xizang, China are well-developed, with a wide distribution of various types. Most high-temperature geothermal systems in Xizang are exceptionally enriched in rare metal elements(RMEs) and have the potential to become a new source of rare metals to secure China's strategic mineral resource supply in the future. A close relationship also exists between the geothermal system and the special salt lake resources on the Tibetan Plateau. Geothermal springs thus play a key role in the migration and enrichment of RMEs from deep to shallow parts of the crust, in the transition between endogenous and exogenous mineralization, and source-to-sink processes. However, the mechanisms of element enrichment and evolution in these springs have not been systematically discussed, and many theoretical issues remain to be investigated. Based on summarizing and analyzing previous research, this study employs hydrochemical and isotopic geochemistry methods to investigate typical geothermal springs across Xizang and explore the anomalous enrichment mechanism of RMEs, and the resource effects of geothermal springs. Comprehensive analysis shows that the total dissolved solids(TDS) and hydrochemical types of geothermal springs are similar to those of major geothermal fields worldwide, but the Tibetan springs are abnormally rich in Li(averaging5.48 mg/L), Rb(averaging 0.75 mg/L), and Cs(averaging 3.58 mg/L), which are hundreds to thousands of times more concentrated than natural waters. The distribution of these enriched geothermal springs is controlled by the Yarlung Zangbo suture zone and the extended N-S trending rifts, especially in the intersection zone of the two, where the geothermal springs are the most enriched. Based on the spatial distr

关键词： Geothermal springs Rare metal elements Enrichment mechanisms Salt lakes Tibetan Plateau

Cascade failure modeling and resilience analysis of mine cyber physical systems under deliberate attacks

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JOURNAL OF SAFETY SCIENCE AND RESILIENCE 2024年第3期5卷 266-280页

作者： Wang, Xinping Zhu, Jialin su, Chang Zhen, Xinyue Xian Univ Sci & Technol Sch Management Xian 710054 Peoples R China Xian Univ Sci & Technol Sch Safety Sci & Engn Xian 710054 Peoples R China

Guided by the intelligent construction of coal mines and integrating the concept of the Cyber-Physical System (CPS), a novel approach to a coal mine information-physical fusion system is proposed. This concept emerges from the advancement of intelligent mines and the growing need for enhanced safety in coal mine operations. From a system safety perspective, this approach aims to effectively evaluate security issues by better integrating the informational and physical layers of intelligent mines. Currently, research in areas such as power grids and water networks has widely adopted concepts of cascade failures and robustness. It is suggested that the CPS framework be adapted to the mining sector. Considering the critical role of coal mines in China's energy security and their vulnerability to cyber attacks, a mine-specific CPS system is designed. This system incorporates a model of mine information-physical fusion, including networks for mine operations, management, and control, tailored to the unique conditions of mine shafts and underground settings. Utilizing Markov process theory, the paper delves into the theoretical study of the cascade failure process under deliberate attack strategies. This analysis is essential to effectively assess the safety issues within the information-physical system, providing vital support for fault prediction and safety analysis. The model of cascading failures in the mine information-physical system is developed, and based on an analysis of resilience and robustness, the study identifies key factors influencing the security of mine information-physical systems. Critical factors affecting the reliability of these systems include the number of system nodes, node coupling, edge count, and the interconnection methods of the dual-layer dependency network. The paper concludes by discussing the challenges in analyzing the security of information-physical systems and suggesting directions for future research.

关键词： Mine cyber physical system Cascading failure Resilience Robustness INTERDEPENDENT NETWORK RELIABILITY ASSESSMENT COMPLEX NETWORKS ROBUSTNESS SECURE

Sparse Adversarial Learning for FDIA Attack Sample Generation in Distributed Smart

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2095-2115页

作者： Fengyong Li Weicheng Shen Zhongqin Bi Xiangjing su College of Computer Science and Technology Shanghai University of Electric PowerShanghai201306China College of Electrical Engineering Shanghai University of Electric PowerShanghai201306China

False data injection attack(FDIA)is an attack that affects the stability of grid cyber-physical system(GCPS)by evading the detecting mechanism of bad *** FDIA detection methods usually employ complex neural networkmodels to detect FDIA ***,they overlook the fact that FDIA attack samples at public-private network edges are extremely sparse,making it difficult for neural network models to obtain sufficient samples to construct a robust detection *** address this problem,this paper designs an efficient sample generative adversarial model of FDIA attack in public-private network edge,which can effectively bypass the detectionmodel to threaten the power grid system.A generative adversarial network(GAN)framework is first constructed by combining residual networks(ResNet)with fully connected networks(FCN).Then,a sparse adversarial learning model is built by integrating the time-aligned data and normal data,which is used to learn the distribution characteristics between normal data and attack data through iterative ***,we introduce a Gaussian hybrid distributionmatrix by aggregating the network structure of attack data characteristics and normal data characteristics,which can connect and calculate FDIA data with normal ***,efficient FDIA attack samples can be sequentially generated through interactive adversarial *** simulation experiments are conducted with IEEE 14-bus and IEEE 118-bus system data,and the results demonstrate that the generated attack samples of the proposed model can present superior performance compared to state-of-the-art models in terms of attack strength,robustness,and covert capability.

关键词： Distributed smart grid FDIA adversarial learning power public-private network edge

Automated Machine Learning Algorithm Using Recurrent Neural Network to Perform Long-Term Time Series Forecasting

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Computers, Materials & Continua 2024年第3期78卷 3529-3549页

作者： Ying su Morgan C.Wang Shuai Liu Department of Statistics and Data Science University of Central FloridaOrlandoFL32816-2370USA School of Mathematics and Statistics Beijing Technology and Business UniversityBeijing100048China

Long-term time series forecasting stands as a crucial research domain within the realm of automated machine learning(AutoML).At present,forecasting,whether rooted in machine learning or statistical learning,typically relies on expert input and necessitates substantial manual *** manual effort spans model development,feature engineering,hyper-parameter tuning,and the intricate construction of time series *** complexity of these tasks renders complete automation unfeasible,as they inherently demand human intervention at multiple *** surmount these challenges,this article proposes leveraging Long Short-Term Memory,which is the variant of Recurrent Neural Networks,harnessing memory cells and gating mechanisms to facilitate long-term time series ***,forecasting accuracy by particular neural network and traditional models can degrade significantly,when addressing long-term time-series ***,our research demonstrates that this innovative approach outperforms the traditional Autoregressive Integrated Moving Average(ARIMA)method in forecasting long-term univariate time *** is a high-quality and competitive model in time series prediction,and yet it requires significant preprocessing *** multiple accuracy metrics,we have evaluated both ARIMA and proposed method on the simulated time-series data and real data in both short and long ***,our findings indicate its superiority over alternative network architectures,including Fully Connected Neural Networks,Convolutional Neural Networks,and Nonpooling Convolutional Neural *** AutoML approach enables non-professional to attain highly accurate and effective time series forecasting,and can be widely applied to various domains,particularly in business and finance.

关键词： Automated machine learning autoregressive integrated moving average neural networks time series analysis

An automatic Q-factor matching method for eliminating 77%of the ZRO of a MEMS vibratory gyroscope in rate mode

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Microsystems & Nanoengineering 2024年第3期10卷 35-48页

作者： Jingbo Ren Tong Zhou Yi Zhou Yixuan Li Yan su School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210000China

Mismatching quality factors(Q-factors)is one of the main factors causing zero-rate output(ZRO)in degenerate(DE)Micro-Electro-Mechanical Systems(MEMS)vibratory *** eliminate the ZRO of the DE MEMS gyroscope,this study introduces a method for real-time identification and automatic matching of Q-factors in rate *** leveraging the vibration characteristics of the DE MEMS vibratory gyroscope in rate mode,dedicated online test methods are designed to determine the Q-factors for both the drive and sense modes,enabling online identification of the Q-factor ***,an automatic Q-factor matching system is designed utilizing the mechanical-thermal dissipation mechanism of the resistive *** effectiveness of this proposed method is validated through simulations and experiments conducted on a MEMS disk resonator gyroscope(DRG).The results show a measurement error within 4%for Q-factor identification,and automatic Q-factor matching effectively reduces the ZRO by 77%.Employing this automatic Q-factor matching method successfully reduces the ZRO that is caused by the mismatching of Q-factors in the MEMS DRG from 0.11°/s to 0.025°/s and improves the bias instability(BI)from 0.40°/s to 0.19°/s.

关键词： matching mode method