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16th International Conference on Wireless Communications and Signal Processing, WCSP 2024

作者： Wang, Yanhu Guo, Shuaishuai Dong, Anming Zhao, Hui School of Control Science and Engineering Shandong University China School of Computer Science and Technology Qilu University of Technology China Eurecom Communication Systems Department France

ISBN: (纸本)9798350390643

Semantic communications offer promising prospects for enhancing data transmission efficiency. However, existing schemes have predominantly concentrated on point-to-point transmissions. In this paper, we aim to investigate the validity of this claim in interference scenarios compared to baseline approaches. Specifically, our focus is on general multiple-input multiple-output (MIMO) interference channels, where we propose an interference-robust semantic communication (IRSC) scheme. This scheme involves the development of transceivers based on neural networks (NNs), which integrate channel state information (CSI) either solely at the receiver or at both transmitter and receiver ends. Moreover, we establish a composite loss function for training IRSC transceivers, along with a dynamic mechanism for updating the weights of various components in the loss function to enhance system fairness among users. Experimental results demonstrate that the proposed IRSC scheme effectively learns to mitigate interference and outperforms baseline approaches, particularly in low signal-tonoise (SNR) regimes. © 2024 IEEE.

关键词： Radio transceivers

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Optimized shearing strategy for heavy plate based on contour recognition

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Journal of Iron and Steel Research International 2023年第9期30卷 1821-1833页

作者： Jian-zhao Cao Yu-xia Wang Shao-wen Huang Chang-tao Wang School of Computer Science and Engineering Shenyang Jianzhu UniversityShenyang 110168LiaoningChina Shandong Iron and Steel Co. Ltd.Jinan 271105ShandongChina School of Electrical and Control Engineering Shenyang Jianzhu UniversityShenyang 110168LiaoningChina

The shearing line is the key to improve the quality and efficiency of heavy plates.A model of contour recognition and intelligent shearing strategy for the heavy plate was ***,multi-array binocular vision linear cameras were used to complete the image ***,the total length of the steel plate after cooling was predicted by back propagation neural network algorithm according to the contour ***,using the scanning line and a new camber description method,the shearing strategy including head/tail irregular shape length and rough dividing strategy was *** practical application shows that the model and strategy can effectively solve the problems existing in the shearing process and can effectively improve the yield of steel *** maximum error of detection width,length,camber,and the length of the irregular deformation area at the head/tail of the plate are all less than 5 *** correlation coefficient of the length prediction model based on the back propagation neural network is very *** reverse ratio result of edge cutting failure using the proposed rough dividing strategy is 1/401=0.2%,which is 2%higher than that by human.

关键词： Heavy plate Contour detection Intelligent shearing strategy Length prediction Neural network model

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Anomalous metastable hcp Ni nanocatalyst induced by non-metal N doping enables promoted ammonia borane dehydrogenation

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Journal of Energy Chemistry 2023年第4期79卷 72-82页

作者： Ping Li Yuqi Huang Quhua Huang Ran Chen Jixin Li Shuanghong Tian School of Environmental Science and Engineering Sun Yat-sen UniversityGuangzhou 510275GuangdongChina Guangdong Provincial Key Laboratory of Environmental Pollution Control and Remediation Technology Guangzhou 510275GuangdongChina

Developing high-performing non-noble transition metal catalysts for H_(2) evolution from chemical hydrogen storage materials is of great significance for the hydrogen economy system, yet challenging. Herein,we present for the first time that anomalous metastable hexagonal close-packed Ni nanoparticles induced by heteroatom N doping encapsulated in carbon(N-hcp-Ni/C) can exhibit admirable catalytic performance for ammonia borane(AB) dehydrogenation, prominently outperforming conventional fcc Ni counterpart with similar morphology and favorably presenting the state-of-the-art *** experimental and theoretical studies unravel that unusual hcp phase engineering of Ni together with N doping could induce charge redistribution and modulate electronic structure, thereby facilitating H_(2)O adsorption and expediting H_(2)O dissociation(rate-determining step). As a result, AB dehydrogenation can be substantially boosted with the assistance of N-hcp-Ni/C. Our proposed strategy highlights that unconventional crystal phase engineering coupled with non-metal heteroatom doping is a promising avenue to construct advanced transition metal catalysts for future renewable energy technologies.

关键词： Hcp Ni Non-metal doping Phase engineering Electronic regulation Ammonia borane dehydrogenation

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Numerical study of the influence of the atmospheric pressure on the thermal environment in the passenger cabin

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Building Simulation 2024年第2期17卷 253-265页

作者： Xin Su Yu Guo Zhengwei Long Yi Cao Tianjin Key Lab.of Indoor Air Environmental Quality Control School of Environmental Science and EngineeringTianjin UniversityTianjin300072China Shanghai Aircraft Design and Research Institute Jinke RoadPudong DistrictShanghai201210China

The cabin air pressure remains lower than the horizontal atmospheric pressure when the airplane is in *** pressure is one of the parameters that must be taken into consideration while studying the thermal environment of an airplane *** are still no reference values for aircraft cabins despite the fact that numerous studies on low pressure heat transfer have demonstrated the connection between convective heat transfer coefficient(CHTC)and air *** this paper,a correction method for CHTC under low pressure conditions was established by using the dummy heat dissipation in the low-pressure cabin *** this basis,a thermal environment simulation model was developed,then was applied to the simulation of a seven-row aircraft cabin containing 42 passengers,and the CHTC and heat loss of dummy surface in the cabin were ***,the results of PMV calculated by using heat dissipation and air parameters at sampling points were *** results show that the modified CHTC can accurately reflect the cabin thermal environment under low pressure conditions,and the correction of CHTC can be realized by adjusting the turbulent Prandtl number,which is nonlinear correlated with the *** simulation results of the thermal environment in the seven-row cabin show that the CHTC changes by about 42%before and after *** air pressure decreases during take-off,which reduces the average CHTC of the crew surface from 5.09 W/(m^(2)·K)to 4.56 W/(m^(2)·K),but the air temperature rises by about 0.2°C as a *** deviation of PMV results calculated by using simulated heat loss data and using air parameters of measuring points in space is up to 0.5,but the latter is representative for calculating the thermal comfort level of the whole cabin.

关键词： low pressure aircraft cabin simulation heat dissipation convective heat transfer coefficient

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Research on the natural circulation characteristic of deep borehole heat exchanger and the influences on the water circulation resistance

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Building Simulation 2024年第12期17卷 2213-2232页

作者： Jiewen Deng Yanhui Wang Yangyang Su Yuanguo Wang Yin Chen Minghui Ma Chenwei Peng Wanlong Cai Ji Li Qingpeng Wei Hubei Key Laboratory of Multi-media Pollution Cooperative Control in Yangtze Basin School of Environmental Science&EngineeringHuazhong University of Science and TechnologyWuhanHubei 430074China Department of Building Science Tsinghua UniversityBeijing 100084China School of Human Settlements and Civil engineering Xi'an Jiaotong UniversityXi'anShaanxi 710049China China Academy of Building Research Bejing 100101China

As deep borehole heat exchangers(DBHEs)extract heat from geothermal energy with depth of 2–3 kilometers,the circulation water pressure drop is larger than that of shallow-depth borehole heat exchangers,influenced by the water flow *** paper conducted field tests and simulation analysis to study the heat transfer performance and water circulation resistance of DBHE in coupled,where the natural circulation characteristic has been discovered and analyzed *** show that the water temperature and density variation along DBHE forms the driving force of natural *** mechanical flow rate of 6.0 kg/s and inlet water temperature of 20.0℃,the natural circulation flow rate reaches about 2.2 kg/s with transient heat extraction power of 78.5 kW,without energy consumption of water *** the larger inlet water temperature,smaller mechanical water flow rate,higher inner tube thermal conductivity coefficient and larger depth of DBHE all contribute to the larger natural circulation water flow *** addition,the natural circulation could effectively decrease the comprehensive water pressure drops of DBHE,which is about 47.3%smaller than the calculated value of traditional *** the natural circulation characteristic has significant influence on the heat transfer performance of DBHE,and also on the energy performance of whole heat pump systems.

关键词： deep borehole heat exchangers water circulation resistance natural circulation field tests simulation analysis

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4th International Conference on Computer science, Electronic Information engineering and Intelligent control Technology, CEI 2024

作者： Zhou, Xulang Wen, Yongdiao Hu, Wenhui Li, Gang Li, Tie Xidian University School of Electric Engineering Xi'an China Science and Technology on Electromechanical Dynamic Control Laboratory Xi'an China

ISBN: (纸本)9798350378542

To address the challenge of effectively evaluating ISAR image similarity under multi-precision fusion processing, this paper proposes a Fine-Grained Weighted Entropy (FGWE)-based image similarity evaluation method. This approach fully considers the subtle structural features in radar images by assigning different entropy weights to various regions, thereby emphasizing the differences of the important structural information and then reflecting accurately the similarity between images. Experimental results demonstrate that, compared with traditional methods, when FGWE was used to evaluate radar images, it showed a greater sensitivity to structural feature differences, and more accurately trapped the image information loss which derived from multi-precision processing. The mentioned FGWE reveals great potential in the field of radar image precision evaluation. © 2024 IEEE.

关键词： Radar imaging

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An adaptive large neighborhood search for the multi-point dynamic aggregation problem

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control Theory and Technology 2024年第3期22卷 360-378页

作者： Shengyu Lu Bin Xin Jie Chen Miao Guo School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Lab of Autonomous Intelligent Unmanned Systems Beijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

The multi-point dynamic aggregation(MPDA)problem is a challenging real-world *** the MPDA problem,the demands of tasks keep changing with their inherent incremental rates,while a heterogeneous robot fleet is required to travel between these tasks to change the time-varying state of each *** robots are allowed to collaborate on the same task or work separately until all tasks are *** is challenging to generate an effective task execution plan due to the tight coupling between robots abilities and tasks'incremental rates,and the complexity of robot *** effectiveness consideration,we use the variable length encoding to avoid redundancy in the solution *** creatively use the adaptive large neighborhood search(ALNS)framework to solve the MPDA *** the proposed algorithm,high-quality initial solutions are generated through multiple problem-specific solution construction *** heuristics are also used to fix the broken solution in the novel integrated decoding-construction repair process of the ALNS *** results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed ALNS can obtain better task execution plans than some state-of-the-art algorithms in most MPDA instances.

关键词： Adaptive large neighborhood search(ALNS) Multi-point dynamic aggregation(MPDA) Heuristic solution construction Multi-robot collaboration

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Multi-path Heart Sound Detection Based on Wavelet Scattering and Attention Mechanism 16

Multi-path Heart Sound Detection Based on Wavelet Scattering...

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16th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2023

作者： Han, Baokun Chen, Meng Li, Yongjian Liu, Lei Wei, Shoushui Jiang, Xinge School of Control Science and Engineering Shandong University Jinan China School of Information Science and Electrical Engineering Shandong Jiaotong University Jinan China

ISBN: (纸本)9798350330755

Changes in heart sounds can often be the earliest signs of organic heart disease, and algorithms for the automatic classification of normal and abnormal heart sounds are essential for early diagnosis of cardiovascular disease. This work proposes a multi-path heart sound detection network based on wavelet scattering and attention mechanism algorithms. The wavelet scattering transform, long-short term memory (WST-LSTM) is used to extract the wavelet scattering features of the heart sound signal;the spatial attention network (SAN) is used to extract the spatial domain features of the time-frequency map of the heart sound signal;and the temporal attention network (TAN) is used to extract the time domain features of the time-frequency map. Sixteen features are extracted from each of the three paths, and after combining the features extracted from multiple path networks, a total of 48 fusion features are obtained, the final classification is performed using a support vector machine (SVM). The method proposed in this work has been well validated on the 2016 PhysioNet/CinC Challenge database, with accuracy (Acc), sensitivity (Se), specificity (Sp), and mean accuracy (Macc) of 96.94%, 97.42%, 96.82%, and 97.12%, respectively. This work also investigates the advantages of multi-path learning, discusses the effectiveness of different features and visualises them. The results show that the proposed method can effectively classify both normal and abnormal heart sound samples with good generalisation ability © 2023 IEEE.

关键词： Support vector machines

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Exploiting Machine Learning and LSTM for Human Activity Recognition: Using Physiological and Biological Sensor Data from Actigraph 25

Exploiting Machine Learning and LSTM for Human Activity Reco...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Oyeleye, Matthew Chen, Tianhua Su, Pan Antoniou, Grigoris School Of Computing And Engineering University Of Huddersfield Department Of Computer Science United Kingdom School Of Control And Computer Engineering North China Electric Power University China

ISBN: (纸本)9798350340266

Human activity recognition involves identifying the daily living activities of an individual through the utilization of sensor attributes and intelligent learning algorithms. The identification of intricate human activities proves to be a labo-rious task, given the inherent difficulty of capturing long-term dependencies and extracting efficient features from unprocessed sensor data. For this purpose, this study aims at recognizing and classifying human activities using physiological and biological sensor data generated by Actigraph, as they can accurately measure moderate-to-vigorous intensity physical which is mostly affected by body composition and also better suited for self-monitoring. We examined the effectiveness of these features by applying prevalent machine learning classifiers and long short-term memory (LSTM) networks on recently publicly available data, which includes accelerometer and heart rate recordings. The results from our experiments showed that LSTM models performed better than conventional ML classifiers with the best result achieving an accuracy of 86.5%. The findings also confirms the significance of the heart rate in accurately classifying and identification of human activity more. © 2024 IEEE.

关键词： Long short-term memory

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Compression Format and Systolic Array Structure Co-design for Accelerating Sparse Matrix Multiplication in DNNs 24th

Compression Format and Systolic Array Structure Co-design f...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Cao, Yongxiang Jiang, Jixiang Zhao, Guocheng Wang, Wei Jiang, Hongxu Song, Yanfei School of Computer Science and Engineering Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9789819615445

The systolic array (SA) architecture is widely used in accelerator/AI chip design due to its excellent matrix multiplication acceleration effect. However, the mismatch between the traditional sparse matrix compression format and the SA architecture results in poor SA performance in computing sparse matrices. To solve the problem, we propose a method for co-designing the sparse compression format and SA architecture. This work proposes the Vector Group Compressed Coordinate (VGCC) data stream compression format and designs a sparse SA architecture based on hardware encoding and decoding. VGCC can handle data streams of any size without increasing the index bit width. The VGCC compression size is significantly smaller than general sparse compression formats such as COO/CSR. In a sparse matrix with a sparsity of 90%, it saves 67.13% of storage space compared to the state-of-the-art ECOO data stream compression format and achieves an average acceleration of 1.54 times. We also propose a VGCC-friendly SA architecture. Our SA architecture engine reduces logic consumption by 51.6% compared to Sparse TPU while achieving a 3.23x speedup. To mitigate the issue of high no-load rates in systolic arrays, we introduce a Data Transmission Priority (DTP) data matching algorithm. With sparsity levels ranging from 50% to 90%, the algorithm’s calculation speed is enhanced by 1.124x to 1.991x. We implemented a sparse DNN accelerator on an FPGA Zynq UltraScale+MPSoC ZCU102, utilizing the VGCC compression format proposed in this study for compressing input data. When compared to the S2 Engine, the accelerator achieved a 3.37x speed improvement in matrix multiplication with 75% sparsity, significantly enhancing the speed of sparse matrix multiplication. The accelerator achieved an average throughput of 1079.33GOP/s when inferencing DNNs. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Systolic arrays

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