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Electromagnetic three-dimensional vibration energy harvester based on an oblique cross-spring vibrator structure

science China(Technological sciences) 2025年第1期68卷 185-202页

作者： Yaohui AN Yimin FAN Kefan XU Yuhao CHEN Yewei ZHANG Liqun CHEN School of Science Harbin Institute of TechnologyShenzhen 518055China College of Aerospace Engineering Shenyang Aerospace UniversityShenyang 110136China

This paper presents an electromagnetic three-dimensional vibration energy harvesting device that uses an oblique cross-spring vibrator structure to collect low-frequency vibration *** oblique cross-spring structure allowed the center vibrator to vibrate in any *** with six-directional coils,this configuration senses and harvests environmental vibrations across all directions and ***,the dynamics of the oblique cross-spring vibrator structure were analyzed and a finite element simulation was performed for the magnet arrangement and mode shape of the structure.A prototype is designed,fabricated,and experimentally *** results showed that the efficiency of the three-dimensional energy output was higher under the same excitation,which was 2.7 times higher than that of the unidirectional *** unidirectional output power with load is 0.94 mW at 11 Hz under 0.3 g base *** highest total output power of the prototype was 50 mW when it was fixed to the leg at a running speed of 8 km/***,the energy harvesting scheme proposed in this study has a considerable low-frequency output effect,which provides a novel means of improving the electrical performance of energy harvesting systems for self-powered IoT and sensor devices.

关键词： energy harvesting electromagnetic three-dimensional oblique cross-spring human motion

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A review of the research on electro-hydraulic load simulator and characteristics with improvement methods

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Recent Patents on engineering 2024年第3期18卷 45-56页

作者： Li, Jianying Li, Weidong Liang, Heng Kong, Lingbing Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin China College of Mechanical and Power Engineering Harbin University of Science and Technology Harbin China

The electro-hydraulic load simulator is a semi-physical simulation system. It is used to simulate different loads on the bearing capacity object (steering gear system) under working conditions and further test the dynamic and static characteristics of the bearing capacity object. Therefore, it is widely used in important applications such as the simulation of various loads and the development of high-performance steering gear systems. By analyzing and discussing the electro-hydraulic load simulator equipment and its improvement methods, some useful conclusions have been drawn to predict the development of the electro-hydraulic load simulator and its key technologies. The current status of research on electro-hydraulic load simulator prototypes is discussed in depth. The electro-hydraulic load simulators are classified according to the loading system applying force (torque). The improvement methods of the electro-hydraulic load simulator, including the method of suppressing the extraneous force, the compensation method of nonlinear factors, and the method of establishing the mathematical model, are analyzed and summarized. By summarizing the literature and patents on electro-hydraulic load simulation technology, the principle, and characteristics of different equipment and improvement methods are analyzed and compared, and future development of electro-hydraulic load simulation equipment and technology is discussed. The research on the characteristics of the prototype, the hardware means and control strategy to suppress the extraneous force, the compensation of nonlinear factors, and the methods of establishing the mathematical model are beneficial to improve the loading accuracy of the electro-hydraulic load simulator. © 2023 The Author(s).

关键词： Loads (forces)

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Designing new low alloyed Mg-RE alloys with high strength and ductility via high-speed extrusion

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International Journal of Minerals,Metallurgy and Materials 2023年第1期30卷 82-91页

作者： Jinshu Xie Zhi Zhang Shujuan Liu Jinghuai Zhang Jun Wang Yuying He Liwei Lu Yunlei Jiao Ruizhi Wu Key Laboratory of Superlight Material and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China Ningbo Branch Ordnance Science Institute of ChinaNingbo 315103China School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Two new low-alloyed Mg-2RE-0.8Mn-0.6Ca-0.5Zn(wt%,RE=Sm or Y)alloys are developed,which can be produced on an in-dustrial scale via relatively high-speed *** two alloys are not only comparable to commercial AZ31 alloy in extrudability,but also have superior mechanical properties,especially in terms of yield strength(YS).The excellent extrudability is related to less coarse second-phase particles and high initial melting point of the two as-cast *** high strength-ductility mainly comes from the formation of fine grains,nano-spaced submicron/nano precipitates,and weak ***,it is worth noting that the YS of the two alloys can maintain above 160 MPa at elevated temperature of 250°C,significantly higher than that of AZ31 alloy(YS:45 MPa).The Zn/Ca solute segregation at grain boundaries,the improved heat resistance of matrix due to addition of RE,and the high melting points of strengthening particles(Mn,MgZn_(2),and Mg-Zn-RE/Mg-Zn-RE-Ca)are mainly responsible for the excellent high-temperature strength.

关键词： magnesium alloys high-speed extrusion high strength high ductility solute segregation

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TRE-DSP:A traceable and revocable CP-ABE based data sharing scheme for IoV with partially hidden policy

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Digital Communications and Networks 2025年第2期11卷 455-464页

作者： Yousheng Zhou Rundong Peng Yuanni Liu Pandi Vijayakumar Brij Gupta College of Computer Science and Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China College of Cyber Security and Information Law Chongqing University of Posts and TelecommunicationsChongqing 400065China Department of Computer Science and Engineering University College of EngineeringTindivanamMelpakkamTamil nadu 604001India Department of Computer Engineering National Institute of Technology KurukshetraIndia

With the popularity of the Internet of Vehicles(IoV),a large amount of data is being generated every *** to securely share data between the IoV operator and various value-added service providers becomes one of the critical *** to its flexible and efficient fine-grained access control feature,Ciphertext-Policy Attribute-Based Encryption(CP-ABE)is suitable for data sharing in ***,there are many flaws in most existing CP-ABE schemes,such as attribute privacy leakage and key *** paper proposes a Traceable and Revocable CP-ABE-based Data Sharing with Partially hidden policy for IoV(TRE-DSP).A partially hidden access structure is adopted to hide sensitive user attribute values,and attribute categories are sent along with the ciphertext to effectively avoid privacy *** addition,key tracking and malicious user revocation are introduced with broadcast encryption to prevent key *** the main computation task is outsourced to the cloud,the burden of the user side is relatively *** of security and performance demonstrates that TRE-DSP is more secure and practical for data sharing in IoV.

关键词： Privacy-preserving Attribute-based encryption Partially hidden policy Traceability User revocation Internet of vehicles

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Application and Effectiveness Evaluation of BP Neural Network Model Based on Rafflesia Optimization Algorithm Optimization in Daily Average Temperature Prediction 15th

Application and Effectiveness Evaluation of BP Neural Netw...

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15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Zhang, Zhen Chu, Shu-Chuan Pan, Jeng-Shyang Li, Wei Yang, Hongmei College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China College of Computer Science and Technology Harbin Engineering University Harbin China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

ISBN: (纸本)9789819700677

With economic and social development, the impact of climate change on human social life is constantly deepening. The ability to accurately predict trends in meteorological data has become an important area of research at present. The main focus of this research is to explore the application and evaluation of the effectiveness of a BP neural network model based on the optimization of the Rafflesia Optimization Algorithm(ROA) for daily average temperature prediction. The data for this study uses a large amount of historical meteorological data as the training set, including date, time and the corresponding daily mean temperature. The prediction model was constructed using a BP neural network-based temperature prediction model, and the ROA was used to optimise the weights and biases of the BP neural network to improve the accuracy and reliability of the prediction model. The experimental results show that the optimized BP neural network model has higher accuracy and stability in predicting the daily average temperature compared with the traditional BP neural network model. The optimised model is also able to better capture the non-linear relationships and time-series features in the meteorological data, thus improving the accuracy and reliability of the prediction. This research can provide a reliable tool for meteorological prediction and climate research, which helps to accurately predict future climate change trends and provide scientific basis and decision support for future economic and social development and human life progress. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Climate change

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Iron-nitrogen-doped porous carbon absorbers constructed from hypercrosslinked ferrocene polymers for efficient electromagnetic wave absorption

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International Journal of Minerals,Metallurgy and Materials 2025年第3期32卷 578-590页

作者： Yi Hu Yijia Zhou Lijia Liu Qiang Wang Chunhong Zhang Hao Wei Yudan Wang Key Laboratory of Superlight Materials&Surface Technology of Ministry of Education College of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China Yantai Research Institute of Harbin Engineering University Yantai 264006China Qingdao Innovation and Development Base of Harbin Engineering University Qingdao 266404China

Herein,an external crosslinker facilitated the hypercrosslinking of ferrocene and a nitrogen heterocyclic compound(either melamine or imidazole)through a direct Friedel-Crafts reaction,which led to the formation of nitrogen-containing hypercrosslinked fer-rocene polymer precursors(HCP-FCs).Subsequent carbonization of these precursors results in the production of iron-nitrogen-doped por-ous carbon absorbers(Fe-NPCs).The Fe-NPCs demonstrate a porous structure comprising aggregated nanotubes and *** porosity of this structure can be modulated by adjusting the iron and nitrogen contents to optimize impedance *** uniform dis-tribution of Fe-N_(x)C,N dipoles,andα-Fe within the carbon matrix can be ensured by using hypercrosslinked ferrocenes in constructing porous carbon,providing the absorber with numerous polarization sites and a conductive *** electromagnetic wave absorption performance of the specially designed Fe-NPC-M_(2)absorbers is satisfactory,revealing a minimum reflection loss of-55.3 dB at 2.5 mm and an effective absorption bandwidth of 6.00 GHz at 2.0 *** utilizing hypercrosslinked polymers(HCPs)as precursors,a novel method for developing highly efficient carbon-based absorbing agents is introduced in this research.

关键词： hypercrosslinked polymers porous carbon iron-nitrogen doping annealing

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Optimizing Image Retrieval in Cloud Servers with TN-AGW: A Secure and Efficient Approach

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Journal of The Institution of Engineers (India): Series B 2025年第2期106卷 459-473页

作者： Ponnuviji, N.P. Nirmala, G. Kokila, M. L. Sworna Priyadharshini, S. Indra Department of Computer Science and Engineering RMK College of Engineering and Technology Puduvoyal Thiruvallur India Department of Computer Science and Engineering RMD Engineering College Chennai India Department of Computing Technologies School of Computing Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nādu Kattankulathur Chennai India School of Computer Science and Engineering Vellore Institute of Technology Chennai India

The increasing use of cloud-based image storage and retrieval systems has made ensuring security and efficiency crucial. The security enhancement of image retrieval and image archival in cloud computing has received considerable attention in transmitting data and ensuring data confidentiality among cloud servers and users. Various traditional image retrieval techniques regarding security have developed in recent years but they do not apply to large-scale environments. This paper introduces a new approach called Triple network-based adaptive grey wolf (TN-AGW) to address these challenges. The TN-AGW framework combines the adaptability of the Grey Wolf Optimization (GWO) algorithm with the resilience of Triple Network (TN) to enhance image retrieval in cloud servers while maintaining robust security measures. By using adaptive mechanisms, TN-AGW dynamically adjusts its parameters to improve the efficiency of image retrieval processes, reducing latency and utilization of resources. However, the image retrieval process is efficiently performed by a triple network and the parameters employed in the network are optimized by Adaptive Grey Wolf (AGW) optimization. Imputation of missing values, Min–Max normalization, and Z-score standardization processes are used to preprocess the images. The image extraction process is undertaken by a modified convolutional neural network (MCNN) approach. Moreover, input images are taken from datasets such as the Landsat 8 dataset and the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset is employed for image retrieval. Further, the performance such as accuracy, precision, recall, specificity, F1-score, and false alarm rate (FAR) is evaluated, the value of accuracy reaches 98.1%, the precision of 97.2%, recall of 96.1%, and specificity of 917.2% respectively. Also, the convergence speed is enhanced in this TN-AGW approach. Therefore, the proposed TN-AGW approach achieves greater efficiency in image retrieving than other existing

关键词： Extraction

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Microstructure Recrystallization and Mechanical Properties of a Cold-Rolled TiNbZrTaHf Refractory High-Entropy Alloy

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Acta Metallurgica Sinica(English Letters) 2024年第4期37卷 633-647页

作者： Chuan Rong Jieren Yang Xiaoliang Zhao Ke Huang Ying Liu Xiaohong Wang Dongdong Zhu Ruirun Chen College of Materials Science and Engineering Sichuan UniversityChengdu610065China Key Laboratory of Air-Driven Equipment Technology of Zhejiang Province Quzhou UniversityQuzhou324000China School of Materials Science and Engineering Harbin Institute of TechnologyHarbin150001China

The equiatomic TiNbZrTaHf alloy was successfully rolled at room temperature with the reduction of ~ 85%. The microstructure and tensile properties were investigated after cold working and annealing. It was determined that the recrystallization temperature of the TiNbZrTaHf alloy between 850 and 900 ℃. Complete recrystallization and normal grain growth occurred, the high stability of single phase was maintained after annealing at 1000, 1200, and 1400 ℃. But the precipitated phase appeared after long term annealing, as seen after 500 h at 1000 ℃. After cold working, the tensile strength and the elongation of TiNbZrTaHf were 1137 MPa and 25.1%, respectively. The annealed alloy has a high tensile strength (σ_(b )= 863 MPa) and ductility (ε_(e )= 28.5%). Moreover, the oxidation of TiNbZrTaHf alloy at elevated temperatures has a significant impact on its mechanical properties. The poor oxidation resistance of TiNbZrTaHf can accelerate tensile failure by inducing fractures at grain boundaries.

关键词： Refractory high entropy alloy Cold rolling Recrystallization Oxidation resistance Mechanical properties

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Knowledge-Aware Multimodal Explainable Fake News Detection 5

Knowledge-Aware Multimodal Explainable Fake News Detection

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5th International Conference on computer, Big Data and Artificial Intelligence, ICCBD+AI 2024

作者： Liu, Xin Dai, Lican Cao, Kaichen Song, Dan Lu, Liangyu Wang, Shengze Liu, Haibo The Southwest Institute of Electronic Technology Chengdu China Harbin Engineering University College of Computer Science and Technology Harbin China

ISBN: (纸本)9798331533991

This paper addresses the limited interpretability of current deep learning-based fake news identification methods, which often fail to incorporate background knowledge embedded in the news. It leverages commonsense knowledge extracted from the Baidu Baike commonsense knowledge graph as evidence to clarify the detection process. To effectively utilize the external knowledge implicit in the news, relevant commonsense is extracted from the ConceptNet knowledge graph, providing essential background knowledge for detection. We introduce the Commonsense-based Multimodal Fake News Detection Network (CMFNDN), designed to integrate evidence, commonsense, text, and image information for effective fake news detection. © 2024 IEEE.

关键词： Knowledge graph

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NeurDB: an AI-powered autonomous data system

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science China(Information sciences) 2024年第10期67卷 129-150页

作者： Beng Chin OOI Shaofeng CAI Gang CHEN Yanyan SHEN Kian-Lee TAN Yuncheng WU Xiaokui XIAO Naili XING Cong YUE Lingze ZENG Meihui ZHANG Zhanhao ZHAO School of Computing National University of Singapore College of Computer Science and Technology Zhejiang University Department of Computer Science and Engineering Shanghai Jiao Tong University School of Information Renmin University of China School of Computer Science and Technology Beijing Institute of Technology

In the wake of rapid advancements in artificial intelligence(AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB(AI×DB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, and selfdriving capabilities for improved system performance. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.

关键词： AI$\times$DB in-database AI intelligent data system

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