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A Real-Time Fall Detection System Based on MoveNet and LSTM 1

TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Liu, Shuxin Shi, Chengcheng School of Electrical Engineering Shanghai Dianji University Shanghai201306 China The Key Laboratory of Cognitive Computing and Intelligent Information Processing of Fujian Education Institutions Wuyi University Fujian354300 China

ISBN: (数字)9783031702358

ISBN: (纸本)9783031702341

Preventing injuries and deaths caused by the lack of timely assistance to the elderly after a fall is an important issue facing our society. Elderly people are prone to accidents such as falls due to the decline in their physical functions, and once they have fallen, if they do not receive timely assistance, it may lead to more serious consequences and even threaten their lives. Therefore, this study explores a deep learning-based method for fall detection. The objective is to minimize the consequences of such incidents. The study compares 2D pose estimation algorithms and proposes a fall detection algorithm based on MoveNet and Long short-term memory networks. This algorithm utilizes a camera to collect data and extracts skeletal information from videos or images. Long short-term memory is then used to analyze and detect the occurrence of a fall in elderly people. In addition, this study comparatively analyses four 2D pose estimation algorithms, namely OpenPose, BlazePose, PoseNet and MoveNet. The experimental results demonstrate that the MoveNet algorithm exhibits superior real-time performance and accuracy. Through experiments conducted on the UR Fall Detection Dataset, the algorithm achieved high performance. Additionally, the detection frame rate on the CPU reaches up to 33 fps, providing remarkable real-time performance in comparison to other algorithms. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Fall detection

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A Wideband Millimeter-wave Bidirectional OAM Antenna using sequential rotation feeding 4

A Wideband Millimeter-wave Bidirectional OAM Antenna using s...

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4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Wu, Jie Feng, Jian Huang, Zhixiang Wu, Xianliang Key Laboratory of Intelligent Computing Signal Processing Anhui University Ministry of Education Hefei China

ISBN: (纸本)9781733509619

A wideband bidirectional circularly polarized (CP) orbital angular momentum (OAM) antenna array is proposed for millimeter-wave frequency. The designed antenna array is composed of four bidirectional radiating dual-CP antenna units that rotate 90 degrees sequentially to each other in the clockwise direction. Results indicate that the left-hand circular polarization (LHCP) with a mode l-{OAM}=-1 in +z direction and right-hand circular polarization (RHCP) with a mode l-{OAM}=+1 in -z direction, over a wide impedance and 3-dB axial ratio (AR) relative bandwidth of 32.3% from 26 to 36 GHz. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Antenna arrays

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Polynomial stacked-attention network for nationality classification

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Frontiers of Computer Science 2022年第4期16卷 215-217页

作者： Kunyan Li Jie Zhang Shiguang Shan Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing100190China University of Chinese Academy of Sciences Beijing100049China

1Introduction In recent years,nationality and region inference has atracted more and_more *** anthropological researches indicate that human faces are influenced by genes,and other external factors,e.g-,geographical environment[1].This relevance provides possible solutions for geographical area inference by ***,it remains a challenging task due to the tiny differences on faces for various countries,which is even hard for human beings to tell.

关键词： Polynomial s. network

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ZTrans: A new Transformer for Speech Enhancement 4

ZTrans: A new Transformer for Speech Enhancement

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4th International Conference on Information Communication and signal processing, ICICSP 2021

作者： Guo, Yucheng Yu, Weiwei Zhou, Jian Key Laboratory of Intelligent Computing and Signal Processing Anhui University Anhui University HeFei China

ISBN: (纸本)9781665407571

At present, Transformer architectures based on the self-attention mechanism have attracted wide attention due to their excellent performance in many fields, such as natural language processing and computer vision. However, in the field of speech processing, the potential of Transformer architectures has not been fully utilized. The main reason is that the position embedding mechanism in the Transformer cannot effectively perform sequence modeling in speech tasks, and the Transformer itself is challenging to train and converge. Inspired by recent research, we propose a new speech enhancement in this paper. Specifically, a recurrent neural network is used to replace the position embedding in Transformer, and the fully connected layer in the Transformer feed forward layer is replaced with one-dimensional convolution. In addition, the model also introduces a weighted residual connection mechanism. Experiment results show that compared with baseline models, the new model performs better in speech quality and speech intelligibility. At the same time, the convergence and inference speed are also much improved. Compared with the baseline model, the processing speed of the proposed method is increased by 4.27 times. © 2021 IEEE.

关键词： Recurrent neural networks

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Impact of Crosstalk and Loss on the Training Process of Integrated Photonic Neural Networks 6

Impact of Crosstalk and Loss on the Training Process of Inte...

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6th International Conference on Electronic Engineering and Informatics, EEI 2024

作者： Pang, Jing Su, Ye Xie, Yiyuan College of Electronic and Information Engineering Southwest University Chongqing400715 China Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing Chongqing400715 China Key Laboratory of Networks and Cloud Computing Security of Universities in Chongqing Chongqing400715 China

ISBN: (纸本)9798350353594

Integrated photonic neural networks (IPNNs), with their ability to process large-scale data and parallelize multiple computational tasks, have shown impressive promise for applications in the field of artificial intelligence. However, due to some hard-to-ignore non-ideal characteristics of the underlying silicon photonic MZI devices constituting the IPNN, these non-ideal characteristics can cause the input signal to be affected by crosstalk noise and optical loss during transmission, thus affecting the training and inference accuracy of the IPNN. In order to solve these problems, this paper establishes an analytical model of IPNN affected by crosstalk noise and loss during the training process, covering component level, layer level and system level. Simulations using this model show that the inference accuracy of IPNN decreases by about 65% when the crosstalk noise in the training phase of IPNN reaches -20 dB, while the inference accuracy of IPNN decreases by about 55% when the optical loss reaches -0.5 dB. © 2024 IEEE.

关键词： Crosstalk

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Research on Alignment and Evaluation Methods for Large Language Models 24

Research on Alignment and Evaluation Methods for Large Langu...

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2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence, DEAI 2024

作者： Li, Yingjie Yan, Qidong Ma, Ning Wan, Fucheng Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China Key Laboratory of China's Ethnic Languages and Intelligent Processing of Gansu Province Northwest Minzu University Gansu Lanzhou730000 China

ISBN: (纸本)9798400717147

Large language models trained on large-scale text corpora have become the primary solution for various natural language processing tasks. The alignment work to make the output content of large models consistent with human values and true intentions has become a significant research topic. This paper investigates the alignment of large models and related evaluation work by specifying the alignment goals at three levels: human instructions, human preferences, and human values. And then introducing the alignment paradigms and methods such as In-context Learning, Supervised Fine-tuning, and Reinforcement Learning, along with evaluation work derived from the alignment task, and presenting the existing evaluation paradigms and benchmarks. Finally, by synthesizing and refining existing research findings, the paper provides insights into the future development of alignment tasks for large language models. © 2024 ACM.

关键词： Alignment

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A U-shape Compensation Structure for Differential-to-Common Mode Conversion Noise Suppression in 90°-Bended differential Line 13

A U-shape Compensation Structure for Differential-to-Common ...

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13th Asia-Pacific International Symposium on Electromagnetic Compatibility and Technical Exhibition, APEMC 2022

作者： He, Zhikang Zhu, Haoran Anhui Province Anhui University Information Materials and Intelligent Sensing Laboratory Hefei230039 China Anhui University Ministry of Education Key Lab of Intelligent Computing and Signal Processing Hefei230039 China

ISBN: (数字)9781665416719

ISBN: (纸本)9781665416719

a U-shaped structure, based on the equivalent lumped circuit of differential transmission line, is proposed to suppress the noise of differential-common-mode conversion. With the equivalent lumped circuit, the cause of mode conversion noise is analyzed. The U-shaped structure has reached the suppression level of 24.31 dB from DC to 10 GHz according to the simulated result. © 2022 IEEE.

关键词： Electric lines

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Adaptive Multi-Updating Strategy Based Particle Swarm Optimization

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intelligent Automation & Soft computing 2023年第9期37卷 2783-2807页

作者： Dongping Tian Bingchun Li Jing Liu Chen Liu Ling Yuan Zhongzhi Shi School of Computer Science and Technology Kashi UniversityKashi844006China Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of SciencesBeijing100190China

Particle swarm optimization(PSO)is a stochastic computation tech-nique that has become an increasingly important branch of swarm intelligence ***,like other evolutionary algorithms,PSO also suffers from premature convergence and entrapment into local optima in dealing with complex multimodal *** this paper puts forward an adaptive multi-updating strategy based particle swarm optimization(abbreviated as AMS-PSO).To start with,the chaotic sequence is employed to generate high-quality initial particles to accelerate the convergence rate of the ***,according to the current iteration,different update schemes are used to regulate the particle search process at different evolution *** be specific,two different sets of velocity update strategies are utilized to enhance the exploration ability in the early evolution stage while the other two sets of velocity update schemes are applied to improve the exploitation capability in the later evolution *** by the unequal weightage of acceleration coefficients is used to guide the search for the global worst particle to enhance the swarm *** addition,an auxiliary update strategy is exclusively leveraged to the global best particle for the purpose of ensuring the convergence of the PSO ***,extensive experiments on two sets of well-known benchmark functions bear out that AMS-PSO outperforms several state-of-the-art PSOs in terms of solution accuracy and convergence rate.

关键词： Particle swarm optimization local optima acceleration coefficients swarm diversity premature convergence

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A Miniaturized Microwave Limiter by Using T-Type LC Network Topology with GaAs Technology 13

A Miniaturized Microwave Limiter by Using T-Type LC Network ...

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13th Asia-Pacific International Symposium on Electromagnetic Compatibility and Technical Exhibition, APEMC 2022

作者： Wang, Jun Zhu, Haoran Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province Hefei230039 China Anhui University Ministry of Education Key Lab of Intelligent Computing & Signal Processing Hefei230039 China

ISBN: (数字)9781665416719

ISBN: (纸本)9781665416719

A miniaturized ultra-wideband microwave limiter with low insertion loss is presented in this paper. This limiter adopts a three-stage antiparallel diode structure. A T-type LC network topology consisting of two spiral inductors and a parallel grounded metal-insulator-metal (MIM) capacitor is utilized to replace the traditional λ/4 transmission line in series between the limiting circuits. Compared with the traditional topology, the proposed limiter has the advantages of miniaturization and ultra-wideband. The area of the presented microwave limiter chip is only 1.25×0.75mm2. The simulation results show that the limiter can work in 0.05-18GHz. Insertion loss is less than 0.65dB at 18GHz. The output power can be maintained below 15dBm with a maximum power input of 40dBm continuous wave. © 2022 IEEE.

关键词： Network topology

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Robust H Sliding Mode Controller Design of a Class of Time-Delayed Discrete Conic-Type Nonlinear Systems

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2021年第2期51卷 885-892页

作者： He, Shuping Lyu, Weizhi Liu, Fei Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Key Laboratory of Advanced Process Control for Light Industry Ministry of Education Jiangnan University Wuxi China

This paper studies the {H}_{ {\infty }} sliding mode control (SMC) problem for a class of discrete-time conic-type nonlinear systems with time-delays and uncertainties. The nonlinear terms satisfy the conic-type constraint condition that lies in a know hyper-sphere with an uncertain center. By choosing a proper Lyapunov candidate, sufficient conditions are derived to ensure the asymptotic stability of the sliding mode dynamics while achieving a prescribed {H}_{ {\infty }} disturbance attenuation level and finally converted into a minimization problem. The controller is constructed to guarantee the discrete-time reach condition and maintain the states on the prespecified sliding surface. A simulation result and a practical example related to the Chua's circuit are given at last to show the validity of our SMC strategy. © 2013 IEEE.

关键词： Time delay

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