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Development of a Human Activity Recognition Algorithm Based on BiLSTM for Construction Workers

Development of a Human Activity Recognition Algorithm Based ...

引用

Advanced algorithms and Control Engineering (ICAACE), international conference on

作者： Wanzhou Li Xiao Sun Tianxiao He Taotao Jiang PowerChina Sinohydro Bureau 7 Co. Ltd. Chengdu Sichuan China Hohai University Nanjing Jiangsu China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

the safety management of a water conservancy construction site faces difficulties. To effectively supervise all workers' operational activity, this study develops a human activity recognition model using a modified BiLSTM algorithm with attention mechanism. the model has an accuracy of 91.65%, and a precision of 91.76%. the model was deployed to a cloud server and a mobile app was developed to transmit the collected action data. A validation test was performed in construction site, and the results show that the proposed model can accurately recognize the workers' activity.

关键词： Control engineering Safety management Water conservation Data models Mobile applications Human activity recognition Servers

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Efficient Bio-Robotic Estimation of Visual Dynamic complexity 7

Efficient Bio-Robotic Estimation of Visual Dynamic Complexit...

引用

7th IEEE international conference on Advanced Robotics and Mechatronics

作者： Fu, Qinbing Liu, Tian Sun, Xuelong Wang, Huatian Hu, Cheng Peng, Jigen Yue, Shigang Guangzhou Univ Sch Math & Informat Sci Machine Life & Intelligen Guangzhou Peoples R China Guangzhou Univ Sch Mech & Elect Engn Guangzhou Peoples R China Univ Lincoln Sch Comp Sci Computat Intelligence Lab Lincoln England Northwest Inst Mech & Elect Engn Xianyang Peoples R China

ISBN: (数字)9781665483063

ISBN: (纸本)9781665483063

Visual dynamic complexity is ubiquitous, hidden attribute of the visual world that every motion-sensitive vision system is faced with. However, it is implicit and intractable which has never been quantitatively described due to difficulty in defending temporal features correlated to spatial image complexity. Learning from biological visual processing, we propose a novel bio-robotic approach to estimate visual dynamic complexity, effectively and efficiently, which can be used as a new metric for assessing dynamic vision systems implemented in robots. Here we apply a bio-inspired neural network model to quantitatively estimate such complexity associated with spatial-temporal frequency of moving visual scene. the model is implemented in an autonomous micro-mobile robot navigating freely in an arena encompassed by visual walls displaying moving scenes. the response of the embedded visual module can make reasonable prediction on surrounding dynamic complexity since it can be mapped monotonically to varying moving frequencies of visual scene. the experiments demonstrate this "predictor" is effective against different visual scenarios that can be established as a new metric for assessing visual systems. To prove its viability, we utilise it to investigate the performance boundary of a collision detection visual system in changing environment with increasing dynamic complexity.

关键词： Measurement Visualization Machine vision Biological system modeling Dynamics Neural networks Visual systems

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7th international Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023

7th International Symposium on Cyber Security, Cryptology, a...

引用

7th international Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023

ISBN: (纸本)9783031346705

the proceedings contain 36 papers. the special focus in this conference is on Cyber Security, Cryptology, and Machine Learning. the topics include: Using Machine Learning Models for Earthquake Magnitude Prediction in California, Japan, and Israel;a Bag of Tokens Neural Network to Predict Webpage Age;correlations Between (Nonlinear) Combiners of Input and Output of Random Functions and Permutations;PPAuth: A Privacy-Preserving Framework for Authentication of Digital Image;Robust Group Testing-Based Multiple-Access Protocol for Massive MIMO;the Use of Performance-Countersto Perform Side-Channel Attacks;HAMLET: A Transformer Based Approach for Money Laundering Detection;hollow-Pass: A Dual-View Pattern Password Against Shoulder-Surfing Attacks;Practical Improvements on BKZ Algorithm;pseudo-random Walk on Ideals: Practical Speed-Up in Relation Collection for Class Group Computation;enhancing Ransomware Classification with Multi-stage Feature Selection and Data Imbalance Correction;a Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks;new Approach for Sine and Cosine in Secure Fixed-Point Arithmetic;How Hardened is Your Hardware? Guiding ChatGPT to Generate Secure Hardware Resistant to CWEs;evaluating the Robustness of Automotive Intrusion Detection Systems Against Evasion Attacks;On Adaptively Secure Prefix Encryption Under LWE;SigML: Supervised Log Anomaly with Fully Homomorphic Encryption;HBSS: (Simple) Hash-Based Stateless Signatures – Hash All the Way to the Rescue!: (Preliminary Version);improving Performance in Space-Hard algorithms;A Survey of Security Challenges in Automatic Identification System (AIS) Protocol;Efficient Extended GCD and Class Groups from Secure Integer Arithmetic;A New Interpretation for the GHASH Authenticator of AES-GCM;Fast ORAM with Server-Aided Preprocessing and Pragmatic Privacy-Efficiency Trade-Off;Improving Physical Layer Security of Ground Stations Against GEO Satellite Spoofing Attacks;midgame Attac

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Soft Homotopy through Moore-Penrose Inverse 10

Soft Homotopy through Moore-Penrose Inverse

引用

10th IEEE international conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (IEEE CIVEMSA)

作者： Tausiesakul, Bamrung Srinakharinwirot Univ Dept Elect Engn Fac Engn 63 Mu 7Rangsit Nakhonnayok RdCanal 16 Nakhonnayok 26120 Thailand

ISBN: (数字)9781665434454

ISBN: (纸本)9781665434454

the acquisition of a discrete-time signal is an important part of a compressive sensing problem. A fine algorithm that could bring better signal recovery performance is often called for. In this work, two homotopy algorithms that involve a soft thresholding decision are proposed using the Moore-Penrose inverse. the additional complexity required in the two proposed methods is relatively minimal, since the necessary matrix inverse (AA(inverted perpendicular)) and the matrix multiplication A(inverted perpendicular) (AA(inverted perpendicular))(-1) can be done before the iteration starts, where. (inverted perpendicular) is the transpose. Numerical examples illustrate the improved error performance for different values of the shrinking parameter gamma. It is found that the greater the shrinking parameter, the less the signal recovery error one could obtain from the two new approaches.

关键词： Compressive sensing homotopy algorithm soft thresholding

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Methodologies Used in Safety-Critical Development

Methodologies Used in Safety-Critical Development

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international IEEE conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： György Schuster Obuda University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

Ever since we use computers to perform control technical tasks, our goal has been to ensure that their operational safety meets the desired standards, both from a hardware and software point of view. We can easily see that above a level that is difficult to define, the complexity of the software is so high that it is impossible to see trough and follow it and, as we wrote in several previous articles, to test it sufficiently. In this paper, after a brief historical summary, we will deal with the development methodologies used today, highlight their appropriate field of application and their main characteristics. We present examples of where and how each discussed methodology can be applied in aviation.

关键词： Computers Power engineering Software Hardware Safety complexity theory Standards

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Application of Multi-node Intelligent Monitoring System in Concrete Construction 7

Application of Multi-node Intelligent Monitoring System in C...

引用

7th IEEE Advanced Information Technology, Electronic and Automation Control conference, IAEAC 2024

作者： Peng, Chao Dongguan University of Technology International School of Microelectronics DongGuan China

ISBN: (纸本)9798350339161

this article first designs a new type of intelligent monitoring node, which is suitable for concrete construction applications in remote areas. Intelligent nodes have advantages such as battery power supply, low-power design, no need for external connections, and convenient networking. Intelligent nodes have advantages such as battery power supply, low power consumption design, no need for external connections, and convenient networking, as well as monitor the core temperature, external temperature, and internal strength information of concrete in real-time during construction and upload data wirelessly. Subsequently, a detailed discussion was conducted on the multi-node and multi-sensor information fusion algorithm based on Kalman filtering for the intelligent node. the algorithm first performs outlier removal on the collected data, then the algorithm considers the core temperature, external temperature, and intensity information as a whole and parallelly calculates the fusion information of multiple nodes and sensors. the experimental results show that under the information fusion of 10-100 sensors, the average measurement accuracy of core temperature is improved by 70.80%, the average measurement accuracy of external temperature is improved by 67.45%, and the average measurement accuracy of internal strength information is improved by 68.87%. Moreover, as the number of sensors increases, the measurement accuracy will further improve. the new intelligent monitoring node designed in the paper meets the needs of the vast majority of concrete construction scenarios. the sensor information fusion algorithm designed based on the intelligent node has low computational complexity, simple parameter adjustment, and significant improvement in measurement accuracy, whichs can not only accelerate construction progress, reduce construction costs, and ensure construction quality, but also provide strong support for intelligent analysis and judgment of subsequent multi node conc

关键词： Kalman filters

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Self-paced Learning for Pedestrian Trajectory Prediction 7

Self-paced Learning for Pedestrian Trajectory Prediction

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7th IEEE international conference on Advanced Robotics and Mechatronics

作者： Wu, Ya Li, Bin Zhang, Ruiqi Chen, Guang Li, Zhijun Liu, Zhengfa Tongji Univ Sch Automot Studies Shanghai 200092 Peoples R China Univ Sci & Technol China Dept Automat Hefei Peoples R China

ISBN: (数字)9781665483063

ISBN: (纸本)9781665483063

Pedestrian trajectory prediction is a task where a model predicts future trajectories of the target agent from historical clues and environment clues. However, earlier works do not distinguish between the level of difficulty in the samples, which considers all samples simultaneously. For the purpose of solving this problem, we propose a novel self-paced based learning paradigm for pedestrian trajectory prediction tasks that can simultaneously measure the easiness of samples and determine the order of samples. through experiments on public pedestrian trajectory forecasting benchmarks, our model-agnostic approach can easily be used in combination with other trajectory prediction baselines, and improve the performance for different baselines without increasing model complexity.

关键词： Training Productivity Mechatronics Predictive models Benchmark testing Trajectory complexity theory

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Efficient Algorithm for Scalable High Efficiency Video Coding Intra Prediction process

Efficient Algorithm for Scalable High Efficiency Video Codin...

引用

international conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Amina Kessentini Ibtissem Wali Taheni Damak Nouri Masmoudi National School of Engineers of Sfax Laboratory of Electronics and Information Technologies University of Sfax Sfax Tunisia National School of Engineers of Sfax University of Sfax Laboratory of Electronics and Information Technologies Sfax Tunisia ENET’COM New Technologies and Telecommunication SystemsResearch Unit University of Sfax Sfax Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

the Scalable High Efficiency Video Coding (SHVC) standard is a state-of-the-art technology for scalable video coding that uses an exhaustive prediction mode decision algorithm within a recursive quad-tree structure coding unit to enhance coding efficiency. However, this improvement comes at the cost of increased computational complexity during encoding, which poses a challenge. To address this challenge, a novel approach has been proposed to accelerate the SHVC encoder. the proposed technique leverages the inherent spatial correlation between the selected Prediction Unit (PU) within the enhancement layer (EL) and its corresponding PU in the base layer (BL). this strategic exploitation yields impressive results, as evidenced by significant reductions in encoding time. It is worth noting that this efficiency boost is achieved with a manageable compromise in video quality and an acceptable uptick in bit rate, which remains well within the bounds of mainstream media requirements. In practice, the proposed methodology showcases its prowess by consistently achieving an average time-saving of 81.77% and 81.59%, thereby underscoring its effectiveness in practical scenarios.

关键词： Correlation Image coding Scalability Prediction algorithms Encoding Computational complexity Optimization

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Augmented reality training, command and control framework for first responders 7

Augmented reality training, command and control framework fo...

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7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media conference, SEEDA-CECNSM 2022

作者： Peretti, Oceane Spyridis, Yannis Sesis, Achilleas Efstathopoulos, Georgios Lytos, Anastasios Lagkas, thomas Sarigiannidis, Panagiotis 0 Infinity Limited London United Kingdom Sidroco Holdings Ltd Nicosia Cyprus International Hellenic University Department of Computer Science Kavala Greece University of Western Macedonia Department of Electrical and Computer Engineering Kozani Greece

ISBN: (数字)9798350398588

ISBN: (纸本)9798350398588

this paper presents an augmented reality (AR) training, command and control framework targeting the preparation of first responders for emergency situations. Utilising novel AR and virtual reality (VR) technologies, the framework aims to offer efficient training sessions, while minimising the cost and complexity associated with real-world exercises. An assortment of training examples and task execution sequences are available, while particular focus is given in the ability to personalise each training session according to specific emergencies or first responder needs. the control aspect of the framework offers insight about the deployment of each first responder on the field, allowing real-time visualisation based on their current location, while displaying useful information regarding health status and mission data. © 2022 IEEE.

关键词： Augmented reality

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SAR Aircraft Target Detection Based on Improved YOLOv8

SAR Aircraft Target Detection Based on Improved YOLOv8

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Pattern Recognition and Artificial Intelligence (PRAI), international conference on

作者： Jinghan Zheng Jie Guo Ming Hao Signal and information processing Department Nanjing Research Institute of Electronics Technology Nanjing China

ISBN: (数字)9798350350890

ISBN: (纸本)9798350350906

Aiming at the problems of weak generalization ability and poor detection effect caused by strong background interference and small size of aircraft target in SAR (Synthetic Aperture Radar) images, this paper proposes an aircraft target detection algorithm for SAR images based on improved YOLOv8. In view of the shortcomings of YOLOv8 network in small target detection, the Simplified-YOLOv8 network is proposed. Combined with the advantages of DCN (Deformable Convolutional Networks), a C2f_DCNv3 module is proposed to improve the feature extraction ability and anti-interference ability of the model. EMA (Efficient Multi-Scale Attention) is introduced into the neck network, so that the algorithm can retain more feature information in the stage of feature fusion. Inner-CIoU Loss is used as the loss function to improve the convergence speed and regression accuracy. the experimental results on the SAR-AIRcraft-1.0 dataset show that the proposed algorithm achieves a 69.4% reduction in parameter quantity and a 25.9% reduction in computation. the precision rate, recall rate and mAP reach 86.3%, 90.8% and 95.2% respectively. the proposed algorithm greatly reduces the model complexity while ensuring high detection effect. Compared with other popular algorithms, the proposed algorithm is more suitable for aircraft target detection in SAR images.

关键词： Atmospheric modeling Object detection Interference Feature extraction Radar polarimetry complexity theory Neck Aircraft Synthetic aperture radar Convergence

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