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21st IEEE International Symposium on Parallel and Distributed Processing with Applications, 13th IEEE International Conference on Big Data and Cloud Computing, 16th IEEE International Conference on Social Computing and Networking and 13th International Conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Zhang, Jingyu Yang, Jin Wu, Chenghao Luo, Lailong Changsha University of Science and Technology School of Computer and Communication Engineering Changsha China National University of Defense Technology Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering Changsha China

ISBN: (纸本)9798350329223

As an indispensable key network service in blockchain systems, digital wallet service is crucial for promoting the widespread application of blockchain technology and the development of the digital economy. However, with the increasing popularity of blockchain technology, the scale of the Unspent Transaction Output (UTXO) dataset continues to increase. A significant number of low-value UTXOs occupied the main dataset space, leading to blockchain dataset expansion. This has affected the performance of digital wallet service and the overall system performance. To address this issue, this paper proposes a Space-Efficient Digital Wallet (SEDW) service in blockchain systems. This strategy employs a Multidimensional Space Simulated Annealing (MSA) algorithm to obtain transaction input UTXOs. MSA can be combined with the UTXO dynamic adjustment mechanism, achieving the rapid consumption of low-value UTXOs without increasing the transaction fees. Experimental results demonstrate that the proposed SEDW strategy effectively optimized the selection of UTXOs in blockchain systems. It alleviated the expansion issue of the UTXO dataset, and controlled the generation of transaction fees, thereby achieving performance enhancement of digital wallet service. © 2023 IEEE.

关键词： Blockchain

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Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 932-945页

作者： Bin Yang Yaguo Lei Xiang Li Naipeng Li Asoke K.Nandi the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System the School of Mechanical EngineeringXi’an Jiaotong UniveristyXi’an 710049 the Hunan Provincial Key Labortory of Health Maintenance for Mechanical Equipment Hunan Univeristy of Science and TechnologyXiangtan 411201China the Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System Xi’an Jiaotong UniveristyXi’an 710049China the Department of Electronic and Electrical Engineering Brunel University LondonUxbridge UB83PHUK

The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source ***,in engineering scenarios,achieving such high-quality label annotation is difficult and *** incorrect label annotation produces two negative effects:1)the complex decision boundary of diagnosis models lowers the generalization performance on the target domain,and2)the distribution of target domain samples becomes misaligned with the false-labeled *** overcome these negative effects,this article proposes a solution called the label recovery and trajectory designable network(LRTDN).LRTDN consists of three ***,a residual network with dual classifiers is to learn features from cross-domain ***,an annotation check module is constructed to generate a label anomaly indicator that could modify the abnormal labels of false-labeled samples in the source *** the training of relabeled samples,the complexity of diagnosis model is reduced via semi-supervised ***,the adaptation trajectories are designed for sample distributions across *** ensures that the target domain samples are only adapted with the pure-labeled *** LRTDN is verified by two case studies,in which the diagnosis knowledge of bearings is transferred across different working conditions as well as different yet related *** results show that LRTDN offers a high diagnosis accuracy even in the presence of incorrect annotation.

关键词： Deep transfer learning domain adaptation incorrect label annotation intelligent fault diagnosis rotating machines

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Noise Generation Mechanisms of Marine Composite Pipelines Excited by the Internal and External Flows

Noise Generation Mechanisms of Marine Composite Pipelines Ex...

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2023 International Conference on Frontiers of Ocean science and technology, ICFOST 2023

作者： Lin, Yukun Feng, Baoming Kang, Rongjun Liu, Yongwei National Key Laboratory of Acoustic Science Technology Harbin Engineering University Harbin150001 China Key Laboratory of Marine Information Acquisition and Security Harbin Engineering University Ministry of Industry and Information Technology Harbin150001 China College of Underwater Acoustic Engineering Harbin Engineering University Harbin150001 China

The marine pipeline is an important energy transportation platform today. It can cause underwater noise pollution due to sound radiation caused by pipeline vibration during oil and gas transportation. This study focuses on the noise-generation mechanisms of marine composite pipelines under internal and external flow excitation. We investigated the impact of different materials, diameters, and wall thicknesses on the sound radiation characteristics of the pipeline under internal flow excitation. The relationship between radiated sound power and flow velocity was analysed. Additionally, we discussed the radiated sound field of marine composite pipelines under external flow excitation. Our results show that the radiated sound power under internal flow excitation is over 20 dB higher than that under external flow excitation in the 10 Hz to 2000 Hz frequency range. We conducted an experimental test near Zhoushan city, China, where the internal flow was driven by a pump and the external flow represented ocean currents. The results confirmed that the main noise-generating mechanism of marine composite pipelines is internal flow excitation. The numerical findings were validated by the experimental test. Overall, this paper provides a foundation for future investigations into the sound radiation of marine composite pipelines. © Published under licence by IOP Publishing Ltd.

关键词： Flow velocity

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UAV-Aided Localization and Communication: Joint Frame Structure, Beamwidth, and Power Allocation

IEEE Journal of Selected Areas in Sensors

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IEEE Journal of Selected Areas in Sensors 2024年 1卷 154-165页

作者： Liang, Tianhao Zhang, Tingting Zhou, Sheng Liu, Wentao Li, Dong Zhang, Qinyu School of Electronics and Information Engineering Shenzhen518055 China Guangdong Provincial Key Laboratory of Space-Aerial Networking and Intelligent Sensing 518055 China Pengcheng Laboratory Shenzhen150001 China Tsinghua University Department of Electronic Engineering Beijing100084 China Macau University of Science and Technology School of Computer Science and Engineering 999078 China

In wireless sensors networks, integrating localization and communication technique is crucial for efficient spectrum and hardware utilizations. In this article, we present a novel framework of the unmanned aerial vehicle (UAV)-aided localization and communication for ground node (GN), where the average spectral efficiency (SE) is used to reveal the intricate relationship among the frame structure, channel estimation error, and localization accuracy. In particular, we first derive the lower bounds for channel estimation error and the 3-D location prediction error, respectively. Leveraging these comprehensive analysis, we formulate a problem to maximize the average SE in the UAV-GN communication, where the frame structure, beamwidth, and power allocation can be jointly optimized. Subsequently, we propose an efficient iterative algorithm to address this nonconvex problem with closed-form expressions for beamwidth design and power allocation. Numerical results demonstrate that the performance of our proposed method can approach the upper bound with low complexity, and achieve over 70% performance gain compared with communication-only benchmarks. In addition, the analysis highlights the dominated impacts of the Doppler effect on the average SE. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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High Precision Temperature Sensor Based on p-PhaseShifted FBG and OFDR system

High Precision Temperature Sensor Based on p-PhaseShifted FB...

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CLEO: Applications and technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Sun, Zhengqi Lv, Yuejuan Zou, Meng Sun, Qizhen Yan, Zhijun School of Optical and Electronic Information Wuhan National Laboratory for Optoelectronics National Engineering Research Center of Next Generation Internet Access-system Huazhong University of Science and Technology Wuhan430074 China Wuxi Research Institute Huazhong University of Science and Technology Jiangsu Wuxi214174 China

We proposed a high precision temperature sensing system which is based on phase-shifted fiber grating interrogated by an OFDR system. The temperature sensing system showed 0.1°C temperature precision with ±0... 详细信息

关键词： Fiber Bragg gratings

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Remote sensing of liquid cloud profiles based on an analytical cloud profiling model

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science China Earth sciences 2025年第4期68卷 998-1012页

作者： Huazhe SHANG Husi LETU Lesi WEI Run MA Yutong WANG Zhaoxin CAI Shuai YIN Chong SHI State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing100101China University of Chinese Academy of Sciences Beijing100049China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science&EngineeringYibin644005China Meteorological Disasters Defense Technology Center Meteorological Bureau of Shanxi ProvinceTaiyuan030032China

The characteristics of microphysical profiles of liquid clouds(i.e.,the cloud effective radius(ER)and liquid water content(LWC))are important factors in understanding the aerosol-cloud-precipitation process and improving the evaluation of cloud radiative effects on a global ***,the profiling of clouds is limited to measurements such as radars or lidars,and retrievals from active sensors are influenced by the attenuation of signals and surface *** when vast amounts of cloud property retrievals that express column or cloud-top/base characteristics from passive sensors are generated,these two-dimensional cloud products are scarcely ever used to further produce three-dimensional cloud profiles because of the lack of a reasonable analytical model to bridge the ***,this study developed a cloud profile reconstruction model(CPRM)based on our previous analytical cloud profile model and evaluated the sensitivities of visible-to-infrared bands of passive cloud observation sensors to each parameter of the *** results indicated that the optical thickness,cloud-top ER,and geometrical thickness can be derived from multiwavelength measurements,whereas the slope of the cloud droplet number concentration(CDNC)and the cloud-base ER could hardly be directly ***,the analytical model was utilized to rebuild cloud profiles seen by CloudSat and *** analytical model could capture the shape and the vertical variations of the cloud ER and LWC.

关键词： Analytical cloud profiling model Cloud effective radius Cloud liquid water content CloudSat Airborne mea-surements

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Real-Time Myanmar Hand Gestures Recognition Using Deep Learning Models 8th

Real-Time Myanmar Hand Gestures Recognition Using Deep Learn...

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8th International Conference on Intelligent Technologies, ICIT 2023

作者： Kyaw, Nwe Ni Mitra, Pabitra Sinha, G.R. Department of Computer Science and Engineering Indian Institute of Technology Kharagpur West Bengal721302 India Indian Knowledge System Lab International Institute of Information Technology Bangalore Karnataka Bengaluru560100 India

ISBN: (纸本)9789819738588

The proposed system for recognizing Myanmar sign language between individuals who are deaf. The aim of this study is to develop deep learning models for the purpose of accurately identifying dynamic hand gesture images depicting 14 classes of Myanmar words and numbers. The present system utilizes a new dataset comprising 7834 images for 14 classes obtained through Webcam. The objective of this study is to enhance the robustness of the new model. Next, we proceed to evaluate the proposed model by comparing them to those of existing convolutional neural network models. These models are generally recognized as effective deep-learning approaches for recognition tasks. The proposed model exhibits a performance level of 96% for both validation and testing accuracies. Furthermore, the experimental finding demonstrates that the model, convolutional layers, achieved an accuracy of 100% in recognizing Myanmar Sign Language (MSL). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Convolutional neural networks

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Stock Monitoring and Localization systems for FIFO Method Using RFID Based Pressure Sensing Tag and AI

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2024年第9期144卷 894-900页

作者： Hadi, Danang Kumara Song, Zequn Rahmadya, Budi Sun, Ran Takeda, Shigeki Graduate School of Science and Engineering Ibaraki University 4-12-1 Nakanarusawa Ibaraki Hitachi316-8511 Japan Department of Agroindustrial Technology Universitas Muhammadiyah Jember Jember68124 Indonesia Computer System Department Faculty of Information Technology Andalas University Padang25175 Indonesia

This research introduces real-time monitoring and localizing product stock using the First-In-First-Out (FIFO) method with radio frequency identification (RFID) pressure sensing tags. The proposed FIFO system has RFID pressure sensing tags that detect pressure changes, generate sensor codes, and estimate a stock location. Integrating artificial intelligence (AI) improves location estimation accuracy of up-to-date stock visibility. The ability of RFID pressure sensing tags and AI to detect stock from sensor code data enables more effective asset management, optimizes stock management, reduces product waste, and contributes to better efficiency in product inventory management. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Inventory control

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An efficient data aggregation scheme with local differential privacy in smart grid

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Digital Communications and Networks 2022年第3期8卷 333-342页

作者： Na Gai Kaiping Xue Bin Zhu Jiayu Yang Jianqing Liu Debiao He School of Cyber Science and Technology University of Science and Technology of ChinaHefeiAnhui230027China Department of Electronic Engineering and Information Science University of Science and Technology of ChinaHefeiAnhui230027China Department of Electrical and Computer Engineering University of Alabama in HuntsvilleHuntsvilleAL35899USA Key Laboratory of Aerospace Information Security and Trusted Computing of Ministry of Education School of Cyber Science and EngineeringWuhan UniversityWuhanBeihu430072China

By integrating the traditional power grid with information and communication technology, smart grid achieves dependable, efficient, and flexible grid data processing. The smart meters deployed on the user side of the smart grid collect the users' power usage data on a regular basis and upload it to the control center to complete the smart grid data acquisition. The control center can evaluate the supply and demand of the power grid through aggregated data from users and then dynamically adjust the power supply and price, etc. However, since the grid data collected from users may disclose the user's electricity usage habits and daily activities, privacy concern has become a critical issue in smart grid data aggregation. Most of the existing privacy-preserving data collection schemes for smart grid adopt homomorphic encryption or randomization techniques which are either impractical because of the high computation overhead or unrealistic for requiring a trusted third party.

关键词： Local differential privacy Data aggregation Smart grid Privacy preserving

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Adaptive Virtual Synchronous Machine Control Strategy for MMC Interconnect Converter Based on Distributed Measurement 9

Adaptive Virtual Synchronous Machine Control Strategy for MM...

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9th Asia Conference on Power and Electrical engineering, ACPEE 2024

作者： Lu, Shaoqun Xiang, Zhengrong Zhong, Kunyan Meng, Jinxue Dang, Yinning Guangxi Science&Technology Normal University School of Mechanical and Electrical Engineering Laibin China Hunan Vocational Institute of Technology Hunan Engineering Laboratory for Photovolatic System Control and Optimization Xiangtan China

ISBN: (纸本)9798350309638

Aiming at the problem of poor stability and response of traditional voltage source control, an adaptive virtual synchronous machine control strategy for Modular Multilevel Converter (MMC) interconnect converter based on distributed measurement is proposed. Through the introduction of virtual synchronous machine control, the interconnect converter can actively participate in grid stabilisation, and its adaptive strategy is adopted to enhance control system suppression capability on frequency oscillation, and the distributed measurement-based MCC control method can solve the insufficient flexibility and scalability of the traditional MMC centralised control strategy. The experimental results show that a large inertia in the DC bus dynamic process helps to enhance the voltage stability of the DC microgrid system. The AC microgrid bus frequency also has a large inertia, which contributes to the AC microgrid frequency stability. The transmitted power has greater inertia during load variations, especially when the load variations are greater. In addition, the distributed measurement-based MMC interconnect converter excels in steady-state control performance, balancing the capacitive voltages of the sub-modules and maintaining stable operation of the system through steady-state distributed control. © 2024 IEEE.

关键词： Balancing

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