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Advances in Remote Sensing Technologies for Ecological Monitoring and Applications in Carbon Stock Estimation 3

Advances in Remote Sensing Technologies for Ecological Monit...

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3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Sadhasivam, Shankaripriya Gayathri, G. Poongothai, P. Pavithra, S. Dept. of Computer Science and Engineering Chennai Institute of technology Chennai India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

This review explores recent advancements that are made in remote sensing, enabling detailed analysis of our ecosystem through high resolution and multispectral imaging. The recent advancements in remote sensing includes developments useful for generation of synthetic images using GAN such as StyleGAN3 and for estimation of carbon stocks in forest using OBIA. Ecotones like mangroves and saltmarsh are crucial for carbon sequestration but mapping them accurately was challenging due to spectral similarity and seasonal variations. Focusing on coastal protection by this review examines the mapping methodologies such as random forest classification, OBIA and FID for habitat distinction, canopy area assessment and analysis. Through these technologies data accuracy can be enhanced for better monitoring. This review concludes with a discussion of AI-powered image synthesis and classification. © 2025 IEEE.

关键词： Carbon sequestration

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Frequency Control of a Solar/Wind/Fuel Cell/Biogas/Biodiesel/Flywheel/Battery Storage based Microgrid under Dynamic Conditions 1

Frequency Control of a Solar/Wind/Fuel Cell/Biogas/Biodiesel...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Reddy, Galiveeti Hemakumar Bhattacharya, Devjani Bisht, Pushpanjali Singh Kulshreshtha, Akanksha Gunaga, Sruthi R Mathur, Neha Dpg Institute of Technology and Management Dept. of Electrical Engineering Gurugram India Dpg Institute of Technology and Management Dept. of Electronics and Communication and Engineering Gurugram India Dayananda Sagar College of Engineering Dept. of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798350360707

Renewable energy sources (RES) are the remedy for pollution free power generation. Availability of power from RES is uncertain in nature and this issue is mitigated with the help of energy storage system (ESS). The combination of RES and ESS leads to the formation of microgrids which can serve the loads by itself. The proposed microgrid in this paper consist of different energy sources and storage systems such as solar, wind, biogas, biodiesel, fuel cell, battery and flywheel energy storage system. It is very important to stabilize the frequency fluctuations due to changes in load, solar and wind output powers. In this work, frequency of the proposed microgrid is stabilized by using the PID controller. The unavailability of solar and wind output powers are also considered for the analysis. The proposed microgrid is modelled and validated using MATLAB/SIMULINK. © 2024 IEEE.

关键词： Biodiesel

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Automatic Recognition of Non-standard Number Plates using YOLOv8 18

Automatic Recognition of Non-standard Number Plates using YO...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Tupsounder, Asaavi Patwari, Renuka Ambati, Roja Chavarkar, Arya Shirsat, Kavita Vidyalankar Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9789380544519

A critical feature of vehicle movement applications is the detection and identification of a vehicle's License Plate (LP). Despite technological and algorithm developments, differences in LP properties by nation, such as number system, colors, character language, fonts, and size, necessitate more study to enhance detection and recognition. Despite substantial study, many systems function in well-defined contexts, necessitating the use of expensive equipment to capture photos from slow-moving vehicles or generate high-quality shots. This study describes a deep learning-based automated approach for LP detection and recognition, which is further separated into detection and character recognition. Yolov8 (You Only Look Once Version-8) was utilized for automatic pixel separation and gradient computation, making complicated model training easier. Using deep learning, Easy OCR (Optical Character Recognition) was utilized to retrieve text from number plates. Easy OCR (Optical Character Recognition) was utilized to extract text from license plates, with deep learning algorithms employed to effectively read text in difficult settings. For image and video processing, OpenCV (Open-Source computer Vision Library) was employed. The project titled 'Automatic Number Plate Using YOLOv8 Model' leverages the advanced capabilities of the YOLOv8 model to develop a robust system for automated number plate recognition, serving as the core component for real-time object detection and number plate localization within images and video streams. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： ANPR (Automatic Number Plate Recognition) Deep learning Image Recognition Non-Standard OpenCV YOLOv8

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A PID Control Algorithm for Path Tracking of a Nonholonomic Car-Like Robot 1

A PID Control Algorithm for Path Tracking of a Nonholonomic ...

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1st IEEE International Symposium on Consumer technology, ISCT 2024

作者： Siradjuddin, Indrazno Prayoga, Dimas Adi Wibowo, Sapto Syaifudin, Yan Watequlis Wicaksono, Rendi Pambudi Achmadiah, Mas Nurul State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State Polytechnic of Madiun Dept. of Computer Control Engineering Madiun Indonesia

ISBN: (纸本)9798350365191

A car-like robot with an Ackermann steering system is a type of nonholonomic which is characterised by a set of first-order differential constraints on its configuration variables, which are not integrable. This distinctive characteristic gives rise to complex issues in the construction of feedback controllers. This research proposes reactive control using a feedback controller using PID algorithm for a car-like robot navigation. The proposed method controls the steering angle of the car-like robot to follow the prescribed path with a constant longitudinal robot velocity. The open-loop car-like dynamical system has been formulated in the form of state-space model. Two PID controllers in parallel computed the lateral position error and the yaw angle error. The summation of the two outputs from the PID controllers was inputted into the state-space model. The PID controller parameters were selected based on trial and error. The simulation results confirm the effectiveness of the proposed control algorithm. © 2024 IEEE.

关键词： Three term control systems

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Analysis of Acceptance of The National Industrial Information System Using The Unified Theory of Acceptance And Use of technology (UTAUT) Method 25

Analysis of Acceptance of The National Industrial Informatio...

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25th International Seminar on Intelligent technology and Its Applications, ISITIA 2024

作者： Nuraini, Fasha Amellia Wibawa, Adhi Dharma Mukti, Prasetiyono Hari Institut Teknologi Sepuluh Nopember Dept. of Electrical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Dept. of Electrical Engineering Dept. of Medical Technology Surabaya Indonesia

ISBN: (纸本)9798350378573

The National Industrial Information System (SIINas) is an integrated information system that contains data and information about the industry in Indonesia. Information technology services encounter the challenge of grasping the factors that drive customers to utilize systems and the attitudes that impact the adoption and acceptance of technology. To unravel these recurring problems, it is necessary to analyze and evaluate the performance of SIINas comprehensively to map the current conditions. This study employs an explanatory research design utilizing a quantitative approach. The participants in this research comprised 100 industrial companies registered in SIINas. The sampling method of this research is simple random sampling Slovin formula. The questionnaire data gathered for the study was analyzed following the approach of the Unified Theory of Acceptance and Use of technology (UTAUT) model. The specific aims of this study were to investigate the impact of Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions on users' Behavioral Intention. Data was analyzed using the Structural Equation Modeling Partial Least Squares (SEM-PLS) method, which checks validity, and reliability and tests the model between variables (Path Analysis). We found that two of the four investigated hypotheses showed significant influence on Behavioral Intention, particularly the variables Performance Expectancy and Facilitating Conditions. This indicates that the more the Performance Expectancy and Facilitating Conditions are provided, the more Indonesian industrial companies intend to use SIINas. © 2024 IEEE.

关键词： Information services

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eDermaCare: Enhancing Skin Disease Classification with ResNet50 18

eDermaCare: Enhancing Skin Disease Classification with ResNe...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Karambele, Aakanksha Tamhane, Mrunal Jayanty, Pranati Patil, Rutuja Shirsat, Kavita Vidyalankar Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9789380544519

In today's world, skin diseases are caused by various factors and affect a person's mental and physical wellbeing. Particularly in private areas, there is considerable reluctance to disclose skin diseases, especially among female patients, which further intensifies the challenge of early detection and treatment. To tackle this issue, the study proposes the implementation of eDermaCare, a novel approach leveraging the advanced Residual Network-50 (ResNet-50) convolutional neural network architecture. Several convolutional neural network (CNN) architectures were explored, but unsatisfactory results were obtained. ResNet-50 has the ability to capture complex features from skin images. The goal is to improve skin disease classification using ResNet-50's deep learning capabilities. This model uses the rest of the course to explain training and retention issues. Block balances allow training deep networks without suffering from degradation in performance. As a result, the model achieves a classification accuracy of 76.07%. The proposed system wm help improve early detection and treatment of skin diseases, address societal challenges, and support effective healthcare. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： classification CNN Deep Learning Resnet50 Skin disease

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Intelligent Fall Detection and Alert System for the Elderly Using Yolov8 and Cloud-Based Analytics 5

Intelligent Fall Detection and Alert System for the Elderly ...

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5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Papan, Vishal Maheswari, S. Vellore Institute of Technology Dept. of Computer Engineering Chennai India

ISBN: (纸本)9798350379945

As people age, the frequency and impact of falls among the elderly continue to escalate, presenting significant health and mobility risks. Efficient detection and immediate response are crucial in reducing the severity of injuries and potentially life-threatening complications associated with such falls. This research study introduces a real-time alert system for the elderly by utlilizing the cutting-edge capabilities of YOLO v8, the latest iteration in the You Only Look Once series of models known for its high speed and accuracy in object detection tasks. The system is designed to operate with inputs from a variety of sources, including direct video feeds, RTSP streams from existing CCTV infrastructure, static images, and data from wearable sensors. This multi-source approach ensures that the system is adaptable for use in a wide range of environments, from personal residences to care facilities, providing continuous monitoring with enhanced accuracy. Upon the detection of a fall, the system immediately activates an alert protocol via Amazon Web Services (AWS) Simple Notification Service (SNS), ensuring that caregivers or family members are promptly notified to respond swiftly to the incident. This data-driven approach not only enhances the accuracy and responsiveness of the system over time but also aids caregivers and healthcare providers in understanding fall patterns and potential risk factors associated with specific environments or individuals, effectively addressing the critical challenges in elderly fall prevention and care. © 2024 IEEE.

关键词： Web services

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Gallium Nitride-based 48V-to-1V Point-of-Load (PoL) Converter for Aerospace Telecommunications and Computing Applications 39

Gallium Nitride-based 48V-to-1V Point-of-Load (PoL) Converte...

引用

39th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2024

作者： Ellis, Nathan M. Zhu, Yicheng Pilawa-Podgurski, Robert C.N. University of California Dept. of Electrical Engineering and Computer Sciences Berkeley United States

ISBN: (纸本)9798350316643

This paper presents a regulating Hybrid Switched Capacitor Converter (HSCC) topology suitable for high conversion ratio Point-of-Load (PoL) applications, specifically targeting 48 V to 1 V power delivery in space-based high-performance computing systems, where size and weight are important considerations, along with device de-rating for radiation tolerance. The proposed topology merges an initial 2:1 switched capacitor conversion stage with a recently developed symmetric dual inductor hybrid (SDIH) conversion stage, reaping benefits of both. The SDIH stage offers reduced component count and an excellent switch stress figure of merit, while the initial 2:1 voltage reduction stage significantly reduces the volume of flying capacitors, enabling compact size and low weight. A high density gate drive solution is also presented, using a minimal number of driver ICs without compromising on driving capability. A preliminary hardware prototype demonstrates this topology's feasibility while employing de-rated gallium nitride (GaN) switches to safeguard against radiation total ionizing dose (TID) and single event effects (SEE). This prototype achieves a very high measured power density of 2,020 W/inch3 (123.3 kW/liter) while performing 48 V to 1 V conversion and switching at 1 MHz. © 2024 IEEE.

关键词： Gallium nitride

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Voice Analysis for Detecting Artificial Speech and Predicting Gender

Voice Analysis for Detecting Artificial Speech and Predictin...

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2024 OPJU International technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Bharadwaj, Rakhi Dugad, Raj Gile, Akshata Patil, Gyaneshwari Hatyalikar, Shrinivas Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350373783

This research paper presents a comprehensive voice analysis system capable of detecting artificial speech and accurately predicting the gender and age of the speaker. Leveraging machine learning, acoustic features, and spectral analysis, the system distinguishes between natural human speech and artificial synthesis with high accuracy. It also excels in predicting the gender and age of the speaker, offering versatile applications in marketing, human-computer interaction, and demographic analysis. The study not only introduces an innovative solution to these challenges but also emphasizes its practical applicability across various domains, underscoring the relevance of voice analysis in today's technology landscape. © 2024 IEEE.

关键词： Prediction models

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Revolutionizing Mango Crop Health: A Deep Learning Approach for Precise Identification of Leaf Diseases 10

Revolutionizing Mango Crop Health: A Deep Learning Approach ...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Navadharani, N. Mouthami, K. Devipriya, R. Anandamurugan, S. Kpr Institute of Engineering and Technology Dept. of Computer Science Engineering Coimbatore India Kongu Engineering College Dept. of Information Technology Erode India

ISBN: (纸本)9798350384369

Plant diseases pose significant challenges to the agricultural sector, leading to decreased crop production and financial losses. Mango, being a popular fruit worldwide, is susceptible to various leaf diseases. Traditional diagnosis of these disorders requires labor-intensive and time-consuming manual picture interpretation. To address this issue, deep learning models have been utilized to enhance the precision and effectiveness of identifying leaf illness in mango crops. In this study, ResNet50, ResNext50, Convnet, and Conventv2 deep learning models were compared to find the most successful approach. The results demonstrated that the Conventv2 model achieved the highest accuracy of 98.21%. The major aim of the research work is improvising sustainable agricultural practices by leveraging advanced technology for accurate plant disease classification. The findings have implications for improving mango crop management and ensuring a more sustainable and efficient agricultural industry. © 2024 IEEE.

关键词： Fruits

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