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Implementing a Robust Method for Detecting Human Actions in Health Monitoring by Employing Sensors on Mobile Internet of Things Devices and Utilizing a One-Dimensional Convolutional Neural Network

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Journal of Technology in Behavioral Science 2025年第1期10卷 79-91页

作者： Vignesh, T. Thyagharajan, K.K. Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Electronics and Communication Engineering R.M.D Engineering College Chennai India

This research is focused on developing a precise human action recognition system by utilizing accelerometer and gyroscope sensor data. The aim is to analyze various human actions like jogging, sitting, standing, walking, going upstairs, going downstairs, and falling, using multiple sensors found in modern smartphones. Previous studies have explored human action recognition using different sensors, cameras, and machine learning and deep learning techniques. However, some existing approaches, particularly those based on channel state information (CSI), have shown less satisfactory outcomes. In contrast, this paper employs deep learning techniques, specifically one-dimensional convolutional neural networks (1D-CNN), for more accurate human action analysis. One significant advantage of the proposed system is its potential as a wearable device. The paper will introduce a one-dimensional convolutional neural network tailored for human action recognition and an optimized approach for determining the magnitude of accelerometer's X, Y, and Z coordinates, as well as gyroscope sensor values. By utilizing these coordinates, the One-Dimensional Convolutional Neural Networks can effectively classify various human actions like jogging, sitting, standing, walking, going upstairs, going downstairs, and falling. To evaluate the performance of the 1D-CNN approach, a comparison is made with other methods, including SOM, SVM, and FCM. The results demonstrate that the proposed method (1D-CNN) outperforms other classification techniques with an impressive accuracy of 92.42 per cent. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Acceleration Gyroscope Human action recognition One-dimensional convolutional neural network Sensors

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Design and Analysis of 6 Degree of Freedom Robotic Whiteboard Cleaner 6th

Design and Analysis of 6 Degree of Freedom Robotic Whiteboar...

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6th International Conference on Mechanical engineering Research, ICMER 2021

作者： Estrera, Mark Ryan M. Genobiagon, Cresencio P. Mechanical Engineering Program College of Engineering Education University of Mindanao Matina Davao City Philippines

ISBN: (纸本)9789811915765

The design and analysis of a six DOF robotic white board cleaner is the focus of this project. A kinematic model for a six-degree-of-freedom (DOF) white board cleaner is presented in this study. Moreover, forward kinematics and inversed kinematics model is developed, and Denavit-Hartenberg (D-H) parameters are used to find solutions. The forward model is used to determine the position and orientation of the end-effector whereas inversed kinematics is used analyze its results associated with solidworks. The experiment is then repeated to confirm the simulation results. Results exhibit that the analytical data are consistent with the measured points and orientation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Robotics

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Artificial Neural Networks in Distribution Management Systems: Improving FLISR Efficiency 4

Artificial Neural Networks in Distribution Management System...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Praveen Kumar, C. Sudarshana Reddy, H.R. Shwetha, D. Sri Siddhartha Academy of Higher Education Department of Electrical and Electronics Engineering Tumakuru India Ubdt College of Engineering Department of Electrical and Electronics Engineering Davangere India University College of Science Tumakuru University Department of Electronics Tumakuru India

ISBN: (数字)9798331528348

ISBN: (纸本)9798350352931

Failures in electrical systems present significant obstacles to ensuring a dependable and continuous power supply, potentially leading to power outages, equipment damage, and interruptions to critical services. This emphasizes the significance of executing efficient fault detection, prevention, and restoration techniques. This study investigates the application of Artificial Neural Networks (ANNs) in 11kV Distribution Management Systems (DMS) to enhance the efficiency of Fault Location, Isolation, and Service Restoration (FLISR) processes. A comprehensive methodology is proposed, integrating power flow equations, FLISR technology, and a real-time database, implemented through MATLAB/Simulink and optimized using the Levenberg-Marquardt algorithm. An 11kV distribution network is modeled, and fault data are collected through simulations and real-world scenarios. A three-layer ANN architecture is designed and trained using the fault dataset to detect, classify, and locate faults. The network's performance is evaluated through regression analysis and validation curves, demonstrating a high correlation between predicted and actual values. The optimal validation performance is achieved at the 258th epoch, with a Mean Squared Error of 49.5591. The results indicate the model's efficacy in simulating various fault conditions and accurately predicting fault effects, with slight underestimation and good generalization to unseen data. The implementation of this ANN-based approach in real-world power distribution systems has the potential to significantly reduce downtime and improve overall system reliability by enabling rapid fault detection and localization. © 2024 IEEE.

关键词： Restoration

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The advanced development of innovative photocatalytic coupling strategies for hydrogen production

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Chinese Chemical Letters 2025年第1期36卷 80-91页

作者： Yuehai Zhi Chen Gu Huachao Ji Kang Chen Wenqi Gao Jianmei Chen Dafeng Yan College of Electronic and Optical Engineering&College of Flexible Electronics(Future Technology) Nanjing 210023China Hubei Key Laboratory for Precision Synthesis of Small Molecule Pharmaceuticals&Ministry of Education Key Laboratory for the Synthesis and Application of Organic Functional Molecules&College of Chemistry and Chemical Engineering Hubei UniversityWuhan 430062China

Photocatalytic technology harnesses solar energy to facilitate chemical transformations,presenting significant potential in energy generation and environmental ***,the conventional O_(2)evolution process is hindered by high reaction barriers and inefficiencies,which limit its widespread ***,exploring novel photocatalytic coupling strategies to replace water oxidation has become a key route to enhance the efficiency of H_(2)*** this review,organic pollutants removal and the valorization of organics as substitutes for water oxidation coupling strategies for photocatalytic H_(2)production are comprehensively *** strategies not only circumvent the high reaction barriers associated with O_(2)evolution to enhance the H_(2)production but also aid in the removing of organic pollutants or synthesis of value-added *** also present future research directions and underscore the significance of advanced catalyst design,in-depth analysis of reaction mechanisms,and systematic optimization strategies in realizing an efficient and sustainable photocatalytic *** guidance is anticipated to provide theoretical and practical new insights for the future development of photocatalytic coupling reactions,fostering further explorations in the realm of renewable energy and environmental governance.

关键词： Photocatalysis Pollutants removal Valorization of organics Catalyst design

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Temperature Profile of Mixed Mode Solar Cabinet Coconut Dryer 6th

Temperature Profile of Mixed Mode Solar Cabinet Coconut Drye...

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6th International Conference on Mechanical engineering Research, ICMER 2021

作者： Diez, Keith Yvonne B. Yap, Jao Philip A. Genobiagon Jr, Cresencio P. Mechanical Engineering Program College of Engineering Education University of Mindanao Matina Davao City Philippines

ISBN: (纸本)9789811915765

A low-cost mixed-mode natural convection dryer was designed to dry coconut kernels. The dryer was made of low-cost materials readily available in local areas. The dryer consists of two major parts, the heat collector and the chamber. The study aim to compare the performance of solar dryer with sun drying. The experiment was conducted in the open field at the University of Mindanao, Davao City, Davao del Sur, Philippines. Coconut cups were placed in the drying chamber and dried until the ideal moisture content is achieved. The temperature, and moisture content were observed during the experiment, as well as the weight of coconut. The drying chamber has a maximum temperature of 78.4 °C and a minimum temperature of 64.6 °C under a clear sky sunny weather. The dryer has reduced the initial moisture content of 54.86 to 6.82% in 21 h of drying. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Natural convection

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Pedestrian Lane Control System with Alert System 6th

Pedestrian Lane Control System with Alert System

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6th International Conference on Mechanical engineering Research, ICMER 2021

作者： Galang, Emmanuel V. Portillo, Noel R. Adtoon, Jetron J. Computer Engineering Program College of Engineering Education University of Mindanao Davao City8000 Philippines

ISBN: (纸本)9789811915765

Pedestrian accidents are inevitable despite the inclusion of pedestrian lanes. Vehicle users tend to neglect pedestrian lanes unless law enforcers are watching. On the other hand, pedestrian users also have lapses in the use of the lanes. This innovative study aims to secure the people and vehicles who are crossing the road. With image processing, a new pedestrian lane system can distinguish pedestrians and cars as inputs for the system to work. The algorithm of the system could process the matching scenarios provided in the fuzzy logic decision table. A prototype design of the project was fabricated along with traffic lights and cameras. The accuracy of the whole system yielded a result of 96.67% for the entire system, with 30 samples covering six scenarios simulated randomly. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fuzzy logic

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Enhanced Fault Identification and Classification of Wind Turbine Blades using Machine Learning 7

Enhanced Fault Identification and Classification of Wind Tur...

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7th International Conference on Signal Processing and Information Security, ICSPIS 2024

作者： Bharathi, M. Amsaveni, A. Sowmiya, K. Kumaraguru College of Technology Department of Electronics and Communication Engineering Coimbatore India Karpagam Academy of Higher Education Department of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350368673

Wind energy is rapidly growing across the world. Wind Turbine generate energy without emitting greenhouse gases. Faults in the wind turbine blades can considerably impact the efficiency, reliability and safety of wind turbine operations. Traditional methods of fault detection often rely on human inspection or basic monitoring systems which is time consuming and prone to human errors. In this paper we use an enhanced fault detection and classification method for the blades in wind turbines with the help of different machine learning algorithms using the images captured by Unmanned Arial Vehicles (UAVs). By leveraging advanced ML algorithms, our approach aims to accurately detect early-stage faults and classify them based on their types, which helps more precise and timely maintenance operations. The proposed method is trained using a comprehensive dataset which includes various blade conditions, including those affected by environmental factors, material fatigue, and operational stress. Through extensive testing and validation, this work demonstrates significant improvement in detection accuracy and classification performance. This enhanced fault detection framework not only reduces downtime and maintenance cost but also contributes to the operational efficiency of the wind turbines, Supporting the sustainable growth of wind energy. © 2024 IEEE.

关键词： Turbomachine blades

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Minimum Component Switched Capacitor Inverter With Modified Pwm Control 2

Minimum Component Switched Capacitor Inverter With Modified ...

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2nd IEEE International Conference on Emerging Research in Computational Science, ICERCS 2024

作者： Sathish Kumar, D. Arun, V. Vijayakumar, M. Elango, S. Muthuvel, K. Raja, A. Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India Mohan Babu University Department of Electrical and Electronics Engineering Tirupati India K.S.R. College of Engineering Department of Electrical and Electronics Engineering Tiruchengode India Nandha Engineering College Department of Biomedical Engineering Perundurai India Shree Sathyam College of Engineering and Technology Department of EEE Sangagiri India SSM College of Engineering Department of Electrical and Electronics Engineering Namakkal India

ISBN: (数字)9798331534967

ISBN: (纸本)9798331534950

The study presents a minimal component switched capacitor inverter (MCSCI). The proposed Minimum Component Switched Capacitor Inverter (MCSCI) tackles significant concerns with the use of an increased number of semiconductor switches, DC sources, and capacitors. The proposed inverter generates a nine-level resultant voltage using a DC supply, eight switches, and three capacitors. The suggested inverter has the capability to amplify the output voltage with a gain of two. The proposed MCSCI used a variable frequency APOD pulse width modulation technique to augment the resulting voltage and improve the quality of the output voltage. The efficacy and practicality of the proposed MCSCI are evaluated using various modulation indices utilizing MATLABSIMULINK. © 2024 IEEE.

关键词： Capacitor bank

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Individuation and Interaction Enhancement of Landscape Design Based on Computer-Aided Design and Reinforcement Learning

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Computer-Aided Design and Applications 2024年第S23期21卷 224-238页

作者： Feng, Zhen Wu, Jianghong Bai, Jiabao Department of Art and Design Shaanxi Fashion Engineering University Shaanxi Xi'an712046 China Preschool Education Program of the Art Education College Xi'an Academy of Fine Arts Shaanxi Xi'an712046 China

The traditional approach to landscape design primarily hinges on the designer's expertise and gut feeling, greatly constraining the design's adaptability to diverse and personalized user needs. Current research, therefore, focuses on integrating cutting-edge technology into landscape design to enhance its individuality and user engagement. This article aims to pioneer innovative methods that enhance the uniqueness and interactivity of landscape designs, thus catering to the escalating demands of users. To this end, we introduce a novel approach that seamlessly merges Computer-Aided Design (CAD) with Reinforcement Learning (RL) algorithms. This approach allows us to capture users' preferences in real-time and leverages RL technology to continuously refine the design proposal, fostering a profound interaction between users and the design process. Rigorous experimental validations and user evaluations reveal that this approach significantly outperforms traditional design methodologies in terms of user satisfaction, design efficacy, and an overall superior score. The findings underscore that this method not only elevates the individuality and interactivity of designs but also propels the automation and intelligence of the design process. © 2024 U-turn Press LLC.

关键词： Computer aided design

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AGWO-CNN Classification for Computer-Assisted Diagnosis of Brain Tumors

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Computers, Materials & Continua 2022年第4期71卷 171-182页

作者： T.Jeslin J.Arul Linsely Department of Electronics and Communication Engineering Universal College of Engineering and TechnologyVallioor627117India Department of Electrical and Electronics Engineering Noorul Islam Centre for Higher EducationKumarakovil629180India

Brain cancer is the premier reason for cancer deaths all over the *** diagnosis of brain cancer at an initial stage is mediocre,as the radiologist is *** experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are ***,the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary *** key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain *** the beginning stage,an anisotropic diffusion filters(ADF)method with un-sharp intensification masking is utilized to eliminate the noise discernment in *** the following stage,within the improved nodule image sequence,a Superpixel Segmentation Based Iterative Clustering(SSBIC)algorithm is proposed for irregular brain tissue ***,the brain nodule samples are captured using deep learning methods:Advanced Grey Wolf Optimization(AGWO)with ONN(AGWO-ONN)and Advanced GWO with CNN-based(AGWOCNN).The proposed technique indicates that the sensitivity is increased and the calculation time is ***,the proposed methodology manifests that the advanced Computer-Assisted Diagnosis(CAD)system has outstanding potential for automatic brain tumor *** average segmentation time of the nodule slice order is 1.06s,and 97%of AGWO-ONN and 97.6%of AGWO-CNN achieve the best classification reliability.

关键词： Advanced GWO with ONN(AGWO-ONN) Advanced GWO with CNN(AGWO-CNN) brain cancer superpixel segmentation based iterative clustering(SSBIC)algorithm

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