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检索条件"任意字段=7th International Conference on Computing in Engineering and Technology, ICCET 2022"

共 10978 条记录，以下是41-50 订阅

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A Time Series Prediction Method for Debris Flow Hazards Based on Improved LSTM 14th

A Time Series Prediction Method for Debris Flow Hazards Base...

引用

14th international conference on Frontier computing, FC 2024

作者： Zhang, Hongtao Zhou, Qinguo School of Information Science and Engineering Lanzhou University Lanzhou China

ISBN: (纸本)9789819623945

Debris flow disaster are sudden and can cause significant property damage and casualties. In response to the problem of delayed prediction of debris flow disasters, this paper proposes a debris flow disaster time series prediction model based on an improved LSTM algorithm. Firstly, we obtained the dataset through on-site investigation and cleaning. then, based on the PCA algorithm, the influencing factors of debris flow disasters were orthogonalized and dimensionally reduced, and 8 key factors affecting debris flow disasters were identified;Next, we established a time series prediction model for debris flow disasters using the LSTM network, trained, tested, and validated it with a dataset, and then conducted comparative experiments with traditional prediction models. the experimental results showed that the training error of the model was less than 0.06, the testing error was less than 0.12, and the validation set prediction error was less than 0.19. Compared with traditional prediction models, the model has high prediction accuracy and strong generalization ***, the method studied in this article has strong predictive ability and can provide certain decision-making support for relevant departments. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

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Improving Data Transmission Efficiency in UAV Networks through Adaptive Coding

Improving Data Transmission Efficiency in UAV Networks Throu...

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international Youth conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Majd M. Safadi Vladislav B. Amoursky Mathematical and Software of Computing Systems Complexes and Computer Networks Faculty of Information Science and Control Systems Bauman Moscow State Technical University Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

In recent years, unmanned aerial vehicles (UAV) have become widely used in civil and military applications such as surveillance, data collection, and cargo delivery. With the increasing use of this technology, there is a need for improved communication systems to ensure reliable and efficient data transmission. UAV networks face unique challenges due to dynamic motion, environmental interference, and energy and bandwidth limitations. the objective of this study is to propose an adaptive coding scheme using Rate-Compatible Punctured Coding (RCPC) technology, which assigns different coding rates to different data depending on their importance and channel conditions. the proposed scheme includes a mechanism to dynamically adjust the coding rates based on the change in link quality. this study demonstrates that adaptive coding can improve resource efficiency, reduce latency, and enhance communication reliability.

关键词： Surveillance Interference Autonomous aerial vehicles Encoding Reliability Data communication Time factors Vehicle dynamics Adaptive coding Signal to noise ratio

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Research on Distribution Network Load Classification and Identification technology Based on Edge computing 24

Research on Distribution Network Load Classification and Ide...

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Proceedings of the 7th international conference on Information Technologies and Electrical engineering

作者： Yuankun Jiang Wei Zhang Yuan Liu Liguo Liu Xuehua Li Chenjie Yang State Grid Information & Telecommunication Co. Ltd. Beijing Branch Beijng China SGIT-UNI (QINGDAO) CLOUD DATA TECHNOLOGY CO. LTD. Beijng China

ISBN: (纸本)9798400707087

In response to the needs of distribution network load classification and identification, this study proposes an efficient classification method based on edge computing, aiming to solve the problem of high real-time and accuracy requirements in the power system. through in-depth analysis of the application potential of edge computing in power systems, a lightweight neural network model was designed and optimized through the momentum gradient descent method, which significantly improved the model's convergence speed and computational efficiency. In the experimental verification, through field testing in multiple scenarios, the results showed that the method performed well in terms of classification accuracy, latency and resource utilization, especially in the classification of residential, commercial and industrial loads, showing high accuracy and Lower processing latency. In addition, through in-depth analysis of actual application cases, this study further proves the wide applicability and application value of edge computing in power load classification. the results of this research provide a new technical path for the optimization and management of power systems, and lay a theoretical and practical foundation for the development of future smart grids.

关键词： Distribution Network

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SIET 2022 - Proceedings of 7th international conference on Sustainable Information engineering and technology 2022

SIET 2022 - Proceedings of 7th International Conference on S...

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7th international conference on Sustainable Information engineering and technology, SIET 2022

ISBN: (纸本)9781450397117

the proceedings contain 54 papers. the topics discussed include: a comparative study of YOLOv5 models on American sign language dataset;a generative-based chatbot for daily conversation: a preliminary study;android-based chatbot application using back propagation neural network to help the first treatment of children’s diseases;classification comparison of activity distraction detection in car driving;classification of mobile usage car driving activities using convolutional neural network;explainable ai prediction of cooking oil prices over time;improving stress detection using weighted score-level fusion of multiple sensor;heart and lung sound monitoring system based embedded system;multi-tier topology design of wireless sensor networks using multi-objective particle swarm optimization;parameter fault estimation in distributed heating/cooling systems;and an in-depth analysis of cooperative multi-robot hierarchical reinforcement learning.

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An Inference Spatiotemporal Machinery Prognostics Approach Based on Graph Learning

An Inference Spatiotemporal Machinery Prognostics Approach B...

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international Youth conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Ahmed Ayman Omneya Attallah Ahmed Onsy Hadley Brooks Iman Morsi School of Engineering and Computing University of Central Lancashire Preston UK Department of Electronics and Communications Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Machinery prognostics facilitates predictive maintenance, minimizing downtime and operational expenses. Nonetheless, challenges persist due to low signal-to-noise ratio and non-stationary signals. Spatiotemporal feature extraction through recurrent and convolutional neural networks has shown promise in addressing these challenges. Nevertheless, the traditional convolutional learning algorithm, which is based on Euclidean distances between the learned features, can increase the model uncertainty. Moreover, traditional feature fusion techniques can weaken the model's performance. this study proposes a novel inferential spatiotemporal approach. Two independent networks based on long short-term memory and a graph convolutional network are designed to extract the influential spatiotemporal features. then an adaptive neurofuzzy inferential network is introduced to calculate the remaining useful life based on the extracted spatiotemporal features. Experimental validation using a benchmark bearing dataset under various operational conditions demonstrates that the proposed approach outperforms existing state-of-the-art methods by 59.34 %.

关键词： Deep learning Adaptation models Graph convolutional networks Benchmark testing Feature extraction Spatiotemporal phenomena Machinery Long short term memory Signal to noise ratio Predictive maintenance

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Polariton Spectrum and Optical Features of Porous All-Metal One-Dimensional Plasmonic Photonic Crystal

Polariton Spectrum and Optical Features of Porous All-Metal ...

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international Youth conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Sofia A. Chebakova Daria A. Gavrilovets Maria A. Kulagina Veronika V. Volkova Vladimir V. Filatov Bauman Moscow State Technical University Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Photonic crystal is an artificial metamaterial with a periodic superlattice resulting in photonic bandgaps in the visible spectrum. this allows the photonic crystal to act as an optical semiconductor and to create optical chips based on a photonic crystal technology. When a photonic crystal contains metallic inclusions, it becomes not only photonic, but also plasmonic and “works” both in optics and in electronics. this paper analyzes optical features of such a crystal made from a single metal, whose superlattice is formed during anodization under controllable etching (this leads to regularly alternating layers of different porosity in the same material). the analyses reveal the presence of a (very narrow) photonic bandgap and a (rather wide) plasmonic one in the polariton spectrum of the porously-structured metal. In the allowed spectral ranges, both quasi-linear normal and anomalous dispersion are observed, and in the anomalous region, the refraction of light is negative.

关键词： Photonic band gap Metals Optical computing Plasmons Optical superlattices Optical refraction Optical sensors Nonlinear optics Dispersion Photonics

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Hydraulic and Civil engineering technology VII - Proceedings of the 7th international Technical conference on Frontiers of HCET 2022

Hydraulic and Civil Engineering Technology VII - Proceedings...

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7th international Technical conference on Frontiers of Hydraulic and Civil engineering technology, HCET 2022

ISBN: (纸本)9781643683546

the proceedings contain 163 papers. the topics discussed include: experimental simulation of hydraulic jump for the study of sequent depth using an obstruction;determination of water-saturated tailings compaction characteristics during geotechnical massif formation;analytical model for assessment of deflections of corrosion-damaged reinforced concrete beams;experimental study of discharge variability on impact coefficient of jet for sustainable development;filtration in porous medium with particle release;technical characteristics and development trend of Russian high-rise buildings;study on simplified calculation method of horizontal displacement of wharf pile foundation under horizontal cyclic load;design strategy of building components based on passive ventilation technology;research on the application of intelligent curing system of cement concrete precast beam;and research on dredging method of slagging shaft blockage by inverted shaft construction in tunnel.

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Multi-Layer Perceptron Regression Model for Material Characterization in the Microwave Frequency Range with Cross-Dataset Validation

Multi-Layer Perceptron Regression Model for Material Charact...

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international Youth conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Hanima Kannan C H Deepa Gupta Parul Mathur Dhanesh G Kurup Tilesh Sanjay Chaudhari Priyanka Mathur Department of Electronics and Communication Engineering RF and Wireless Systems Laboratory Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Department of Chemical Engineering Creative and Advanced Research Based on Nanomaterials Laboratory Indian Institute of Technology Hyderabad School of Engineering and Applied Science Bennett University Greater Noida U.P. India

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

this paper presents a Multi-Layer Perceptron (MLP) based regression model for characterizing materials at micrwave frequency range. A mathematical model and experimental setup of the Open-Ended Coaxial Probe (OECP) sensor interacting with the material under test (MUT) generate a cross-dataset to validate the MLP regression model, utilizing the frequency-dependent complex dielectric constant for material characterization. this paper utilizes the frequency-dependent response of the OECP sensor (scattering parameters) as input features for the MLP model, while the complex dielectric constant of the MUT serves as the output feature. the optimized MLP model has an $R^th$ of 99.991% and MSE of $6.65 \times 10^{-5}$ , with predictions closely aligning with literature values for standard loads such as distilled water, acetone, and ethanol, obtained using a commercially available dielectric assessment software kit. this cost-effective model enables precise dielectric property estimation, with future work extending to unknown materials, mixtures, and electrolyte solutions.

关键词： Power engineering Dielectric constant Predictive models Mathematical models Software Scattering parameters Probes Permittivity Standards Load modeling

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A Flexible IMU-Based Unit for Validation Studies: A Step Counting Application 18th

A Flexible IMU-Based Unit for Validation Studies: A Step Cou...

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18th EAI international conference on Pervasive computing Technologies for Healthcare, PervasiveHealth 2024

作者： Angelucci, Alessandra Barbieri, Lorenzo Caramaschi, Sara Sarmiento, Clarysse A. Sekules, Virginia Aliverti, Andrea Dipartimento di Elettronica Informazione e Bioingegneria Politecnico di Milano P.zza Leonardo da Vinci 32 Milan20133 Italy Internet of Things and People Research Center Department of Computer Science and Media Technology Malmö University Nordenskiöldsgatan 1 Malmö211 19 Sweden

ISBN: (纸本)9783031855740

Wearable step counting devices, such as smartwatches and activity trackers, have become ubiquitous, embedding sensors like Inertial Measurement Units (IMUs), barometers, and GPS systems to monitor physical activity. Despite their widespread use, these devices often restrict access to raw data, limiting their utility in research. this study introduces a customizable IMU-based unit, designed for flexible data acquisition and integration into a body sensor network (BSN), which can serve as a reference system for validating commercial smartwatches. the IMU-based unit transmits data via the ANT protocol and stores backups on an SD card to mitigate transmission data loss. Five volunteers participated in a protocol involving various conditions, such as resting, walking on a treadmill, walking outdoors, and climbing stairs. Preliminary results indicate that the IMU-based unit detects steps correctly accordingly to the typical waveforms reported in the literature the flexibility of the IMU-based unit allows for extensive post-processing and analysis, making it a valuable tool for validating commercial wearable devices and advancing research in physical activity monitoring. Future improvements include integrating multiple units and adopting Bluetooth Low Energy for enhanced data transmission and compatibility. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Personal computing

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Design and Implementation of a High-speed Data Acquisition and Analysis System for Robot Grinding and Polishing Force Position 24

Design and Implementation of a High-speed Data Acquisition a...

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Proceedings of the 7th international conference on Information Technologies and Electrical engineering

作者： Changyi Deng Zhentao Ma Hongliang Wang Mingshi Li Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang Liaoning China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400707087

In the process of grinding the surface of complex curved parts, simply controlling the position of the robot cannot ensure the consistency of the grinding removal amount, which is easy to lead to the phenomenon of over-grinding and under-grinding. Aiming at the above problems, this paper designed a high-speed data acquisition and analysis system for robot grinding and polishing force position based on ARM+FPGA, including hardware circuit design and software system implementation. the system could control the contact force in real time and monitor the distance between the grinding tool and the surface of the part. the experiments show that the system can effectively improve the precision and quality of surface grinding of complex curved parts. Its functions and performance in high-speed acquisition and data interaction can meet the consistent requirements of surface grinding removal of curved parts.

关键词： Complex surface grinding

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