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8th International conference on Civil engineering, ICOCE 2024

8th International Conference on Civil Engineering, ICOCE 202...

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8th International conference on Civil engineering, ICOCE 2024

ISBN: (纸本)9789819759095

the proceedings contain 36 papers. the special focus in this conference is on Civil engineering. the topics include: Inspection, Appraisal, and Rehabilitation Plan for the Main Shaft Tower at a Gold Mine;evaluation Equations of Global Stability for Single-Layer Cylindrical Grid Shells Based on Parametric analysis and Regression analysis;flexural Behavior of Indonesian Berua Timber: Experimental Test and Numerical analysis;experimental and Numerical Study of Full-Size Reinforced Geopolymer Concrete Beams;structural Behavior of Reinforced Concrete Spliced Beams Subjected to Repeated Loads: An Experimental Study;theoretical Study on the Influence of Plate Position Parameters on the Compressive Bearing Capacity of Concrete Expanded Plate Double Pile;Detecting Debonding in FRP Retrofitted Concrete Beams Using Nonlinear Ultrasonic Waves;CFRP Strengthening of Corroded Short thin-Walled Steel Tubular Columns Filled with Concrete Under Direct Loading;selection of Highway Underpass Accessibility Solution for Flooded Area Using Analytical Hierarchy Process Method;local Scour Studies on Spur Dyke with Grouped Piles;analysis of Karst Water System and Upper Reservoir Leakage of the Pumped-Storage Power Station in Jiangyou, China;indicators to Check Global Optimality of design Solution of Looped Water Distribution Networks;urban Flood Resilience: A Comparative Exploration of Rain Garden Infiltration with Diverse Vegetation;generative Urban design Methods Based on Interactive Web Application;research on the Availability of Outdoor Space Under the Background of Aging;mitigation Measures to Protect the Quality of Life in an Expansion of thailand’s Mega Port;preparation of Porous Concrete Suitable for Vegetation Growth: An Approach Toward Green Infrastructure.

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8th International conference on Microelectronics Electromagnetics and Telecommunications, ICMEET 2023

8th International Conference on Microelectronics Electromagn...

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8th International conference on Microelectronics Electromagnetics and Telecommunications, ICMEET 2023

ISBN: (纸本)9789819784219

the proceedings contain 40 papers. the special focus in this conference is on Microelectronics, Electromagnetics and Telecommunication. the topics include: Enhanced Two-Way Cooperative DCSK System via Grouping Subcarrier-Permutation Index Modulation;modelling of Fractional-Order System in Complex Domain Using Direct Approach: A Comparative Study;Securing Cellular-V2X at Physical Layer: A Two-Stage User Authentication for Massive MIMO systems;ASER analysis of a DF Relay-Assisted Transmission System Influenced by Fisher-Snedecor F Fading Channels Applying Non-coherent Modulation Schemes;design of Compact Patch Antenna for TPMS Applications;key Components of Optically Transparent Antennas and their Specifications;Performance analysis of Diverse Mobility Speeds on MANET Routing Protocols;Qualitative analysis of WOC Channel-Based Optical Communication System;Analyzing the Role of DCF in Symmetrical Compensated Network Using Dispersion Compensation Technique;improved design of Microstrip Low Pass Filter by Using Numerous Metamaterial Patterns;design of a Low-Power Varactor-Based DCO Using NMOS Switching Network as a Digital Control Technique;comparison of Four Approaches of Image Compression for Wireless Communication;Numerical Study of Laguerre–Gaussian Beams and analysis of OAM Based OOK Communication System;specific Absorption Rate Evaluation in Layered Human Head Models Using Transparent Conducting Film;a Novel Four-Channel Optical De-multiplexer Using Photonic Crystal Ring Resonator;design of L-Shaped Microstrip Patch Antenna;wideband High-Gain Franklin Antenna Array for 5G Millimeter-Wave Applications;change Detection Mechanism Over Multi-spectral Images Using Machine-Learning Techniques;a Comprehensive Machine-Learning-Based Approach for Aspect-Based Sentiment analysis Over Food Consumables;a Deep Learning-Based Face Recognition Model for Comprehensive Student Logging Mechanism Using Tkinter;attention Deficit Hyperactivity Disorder Using Machine Learning.

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design and analysis of Compact Millimeter-Wave Vivaldi Antenna for Wearable WBAN Application 8

Design and Analysis of Compact Millimeter-Wave Vivaldi Anten...

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8th International conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2025

作者： Lakshmi, M Bhagya Srinivas, K.Kalyana Devi, Dhara Jahnavi Bhargavi, Madipelly Moses, M.J. VNRVJIET ECE Bachupally India

ISBN: (纸本)9798331520762

A novel low-profile antenna, designed for operation in the millimeter-wave frequencies in WBANs at 32.5 GHz, is presented. Optimized to be compact in a form factor of approximately 7 × 10 mm with height 0.79mm for body-worn devices, which is a crucial area with vast space constraints, it has an efficiency for short-distance optical interactions in wearables that do not allow rough wireless performances. this is the small size of the antenna that allows it to support high-speed and low-latency communication;hence, it can be used for real-time data transfer in WBANs. this design contributes to wearable technology advancement by achieving a balance between performance, energy efficiency, and compactness for a wide range of applications, including health, fitness, and smart wearable devices. © 2025 IEEE.

关键词： Antenna on-body antenna Vivaldi wire-less body area network (WBAN)

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Machine Learning Techniques for Structural Health Monitoring 8th

Machine Learning Techniques for Structural Health Monitoring

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8th World conference on Smart Trends in systems Security and Sustainability, WorldS4 2024

作者： Casillo, Mario Cecere, Liliana Colace, Francesco Lorusso, Angelo Santaniello, Domenico Tucker, Allan 1DiSPaC University of Salerno SA Fisciano84084 Italy DIIn University of Salerno SA Fisciano84084 Italy College of Engineering Design and Physical Sciences Brunel University London Uxbridge United Kingdom

ISBN: (纸本)9789819795581

Deploying structural control devices based on machine learning is a significant advancement for infrastructure management. Such systems, capable of combining IoT and artificial intelligence, make it possible to detect and deal with various structural incidents on time. Machine learning plays an important role, as it analyzes data from sensors placed on the structure, such as vibration, acceleration, and temperature. Its ability to continuously learn over time from the data allows the device to identify faults increasingly effectively. this enables effective predictive maintenance, which reduces costs and increases safety. Several data analysis tools exploit various machine learning techniques. Starting with data from accelerometers, the study compares different unsupervised methods and their effectiveness. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive maintenance

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SysML static model conversion based on QVT-O 24

SysML static model conversion based on QVT-O

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8th International conference on Electronic Information Technology and Computer engineering, EITCE 2024

作者： Ni, Yongkang Deng, Yuandan Mao, Yanling Chen, Weiqin School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China Sichuan Provincial Key Laboratory of Intelligent Terminal jointly built by Hall and City Sichuan Yibin China University of Electronic Science and Technology of China Yibin Park Sichuan Yibin China

ISBN: (纸本)9798400710094

For the conversion from SysML (System Modeling Language) static model to dynamic model, the mapping between the two models is not direct or automated. A method to implement SysML static model conversion based on QVT-O (Query/Views/Transformation - Operational) is proposed. Extract necessary information from the BDD (Block Definition Diagram) of the SysML static model, and generate a sequence diagram corresponding to the dynamic model based on predefined rules and mapping between models. the effectiveness of this method is verified through a simple system. this automated conversion not only improves modeling efficiency, but also enhances the consistency and accuracy of the model, which has important practical value for system engineers in system design and analysis. © 2024 Copyright held by the owner/author(s).

关键词： Mapping

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Research on Large-scale Ocean Date analysis based on Machine Learning 24

Research on Large-scale Ocean Date Analysis based on Machine...

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8th International conference on Electronic Information Technology and Computer engineering, EITCE 2024

作者： Zhou, Tong Meng, Wenzheng Yu, Dingfeng Wuhan Second Ship Design and Research Institute Hubei Wuhan China School of Energy and Power Engineering Huazhong University of Science and Technology Hubei Wuhan China

ISBN: (纸本)9798400710094

the rapid development of electronic information and communication technology has led to the widespread use of a variety of marine monitoring technologies, including aerospace remote sensors, automatic buoys, multi-beam echo-sounders, and underwater detection equipment. this has resulted in a significant increase in the volume of marine big data. this work puts forth an innovative model that is based on the most recent machine learning techniques. In consideration of the distinctive attributes of high-dimensional, nonlinear, and strongly spatiotemporally correlated marine data, the model employs an enhanced deep neural network architecture. Initially, the Variational Autoencoder (VAE) was employed for the purpose of reducing the dimensionality of the data set and extracting the most pertinent features, thus enabling the effective handling of the noise and redundant information inherent to marine data. Subsequently, the spatiotemporal dependencies in the data were mined using a spatiotemporal convolutional neural network (ST-CNN) with a self-attention mechanism, enabling high-precision prediction and classification of ocean parameters. the model has been optimised to account for the distinctive characteristics of marine data, thereby enhancing its capacity to adapt to complex marine environments. © 2024 Copyright held by the owner/author(s).

关键词： Convolutional neural networks

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Development of an RFID-based Children’s Disaster and Emergency PreparednessDevice 24

Development of an RFID-based Children’s Disaster and Emerge...

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8th International conference on E-Society, E-Education and E-Technology, ESET 2024

作者： Broas, Pauline Ingrid Derama, Lovely Mae Rosales, Rosban Bacus, John Computer Engineering Program College of Engineering Education University of Mindanao Davao City Philippines

ISBN: (纸本)9798400707094

RFID Technology has grown increasingly popular over recent years due to its efficiency. this study examines the development, implementation, and impact of an RFID-based cognitive learning system focusing on child preparedness in disasters and emergencies. this study aims to design a stand-alone interactive device, fabricate an RFID-based touchscreen interactive device for children, conduct functionality testing on the accuracy of the eLearnCards and responsiveness of the LCD Touchscreen, and evaluate system accuracy and performance on children using a paired T-test. A quantitative research approach is adopted, encompassing the collection and analysis of pre-test and post-test scores from a stratified random sample of 60 children from New Matina Elementary School with an age range of 7-12 years old. the results of this study signify that the RFID-based cognitive learning system substantially contributes to enhancing students’ disaster preparedness knowledge. this study concludes that it underscores the considerable potential of RFID-based educational technology in reinforcing disaster preparedness among children. © 2024 Copyright held by the owner/author(s).

关键词： Disasters

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Research on Novel Intelligent Patient Call System Based on Surface Electromyography Recognition 24

Research on Novel Intelligent Patient Call System Based on S...

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8th International conference on Electronic Information Technology and Computer engineering, EITCE 2024

作者： Xiao, Dongya Zhou, Zhenang Mei, Chudong Shu, Xinyan School of Electrical Engineering and Information Technology Changchun Institute of Technology Jilin Changchun China

ISBN: (纸本)9798400710094

A novel intelligent patient call system based on surface electromyography recognition is proposed to improve the performance of existing call systems which have the issues of fixed location, inconvenient calling and lack of real-time monitoring. the system uses the STM32 as the main control chip. Firstly, the overall scheme of the call system is designed. Secondly, the hardware of the call system is designed, consisting of the surface electromyography recognition module, basic vital signs detection module, and ZigBee wireless information transmission module. then, the software process of the call system is designed. Finally, the experiment tests of the call system are carried out. the experiment results show that when using the point-to-point working mode, the data transmission success rate reaches 100% from the slave to the host, and when using the broadcast communication mode, the data transmission success rate is 95%, both of which meet the design specification requirements. the novel intelligent call system designed in this paper features straightforward calling operations. It can monitor the physical condition of the patients in real-time, and can transmit data to the control center wirelessly for analysis and processing, which can facilitate medical staff to grasp the condition of the patients in real-time. © 2024 Copyright held by the owner/author(s).

关键词： Zigbee

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analysis and Detection of Defamatory Posts against Athletes on Social Media 24

Analysis and Detection of Defamatory Posts against Athletes ...

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8th International conference on Natural Language Processing and Information Retrieval, NLPIR 2024

作者： Nishitani, Senchiyo Ando, Kazuaki Graduate School of Science for Creative Emergence Kagawa University Takamatsu Japan Faculty of Engineering and Design Kagawa University Takamatsu Japan

ISBN: (纸本)9798400717383

Defamation against athletes on social media has become a significant issue. Athletes who are subjected to defamation may not be able to perform at their best in the upcoming event. therefore, it is necessary to develop a method to automatically detect defamation against athletes on social media at an early stage. In this paper, we analyze Japanese defamatory posts against athletes on Twitter (currently X) and propose methods to detect defamatory posts using feature-based models and pre-trained language models. Moreover, we investigate the effectiveness of using the source post of defamatory posts in defamation detection task. From the experimental results, we found that the method based on BERT achieved the best F1-score of 0.838 among all the methods. We also confirmed that the use of both source and reply posts was effective in detecting defamatory tweets. © 2024 Copyright held by the owner/author(s).

关键词： Tweets

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Comparison of the Efficiency of Lamella Modules with Various designs Based on Numerical Modeling 8th

Comparison of the Efficiency of Lamella Modules with Various...

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8th International conference on Construction, Architecture and Technosphere Safety, ICCATS 2024

作者： Yu, Shuaixian Fedorov, S.V. Saint Petersburg State University of Architecture and Civil Engineering 4 2Nd Krasnoarmeiskaya Str St Petersburg190005 Russia

ISBN: (纸本)9783031804816

Lamella modules are the principal components of sedimentation tanks applied to water purification systems. the design of lamella modules determines the efficacy of the sedimentation process. this paper examines the efficacy of sedimentation tanks in the removal of solids suspended in wastewater within the pulp and paper industry. A comprehensive three-dimensional computational fluid dynamics (CFD) analysis was conducted to examine the influence of design parameters on the flow field and settleability of suspended particles in four distinct lamella module designs. the calculations were performed using the discrete phase model, which was supported by Ansys Fluent. therefore, it can be concluded that the high sedimentation efficiency of the Lamella module, which is designed with two layers, makes it a suitable treatment for the wastewater produced by the pulp and paper industry in particular, at high flow rates and with small particles. Based on these results, there are significant practical implications for the advancement of wastewater treatment technologies. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Wastewater treatment

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