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2023 International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2023

作者： Bahiru, Tadesse Kebede Manjula, V.S. Akele, Tadesse Birara Tesfaw, Engdaw Ayalew Belay, Tadesse Destaw Kombolcha Institute of Technology Wollo University College of Informatics Dept. of Information Technology Amhara Kombolcha Ethiopia Kombolcha Institute of Technology Wollo University College of Informatics Pg Dept of Computer Science Amhara Kombolcha Ethiopia Kombolcha Institute of Technology Wollo University College of Informatics Dept. of Information System Amhara Kombolcha Ethiopia Wachamo University School of Computing and Informatics College of Engineering and Technology Dept. of Information Technology SSNPR Hosaena Ethiopia

ISBN: (纸本)9781665474511

As World Health Organization reports show more than 1.3 million people die each year from traffic accidents and more than twenty to fifty million people are harmed by non-fatal accidents. Understanding and identifying the major factors of road traffic accidents can help the stakeholders to take appropriate measures to minimize the accidents. Support Vector Machine (SVM), J48, and Naïve Bayes (NB) classification techniques are implemented to build a model that predicts accident severities and to identify road traffic accident factors. As experimental findings showed weather conditions, number of lanes, road lighting conditions, and speed limit are the determinant factors that cause more accident severity. Finally, the classification and prediction performance of the models are compared using various performance evaluation techniques. J48 classifier has better classification performance than Support Vector Machine and Naïve Bayes classifiers. Naïve Bayes is the classifier that showed the lowest performance than others, but it has good performance in classifying fatal accident severities rather than serious and slight accident severities. © 2023 IEEE.

关键词： Support vector machines

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MATLAB GUI based Partial Discharge Localization in Power Transformers using UHF Acoustic Method 4

MATLAB GUI based Partial Discharge Localization in Power Tra...

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4th International Conference on Energy, Power, and Environment, ICEPE 2022

作者： Welankiwar, Avinash S. Sharma, R.B. G. H. Raisoni Institute of Engineering Technology Dept. of Electrical Engineering Nagpur440016 India Dept. of Electrical Engineering Government College of Engineering Amravati444604 India

ISBN: (纸本)9781665471244

Partial Discharge (PD) problem is getting more attention day by day due to its severity towards insulation deterioration and internal arcing problems. In this Paper, PD detection is illustrated with the help of a case study conducted on a Power Transformer by using Ultra High Frequency (UHF) injection and acoustic method combined with High frequency Current Transducer (HFCT) to get more accurate results. This method is getting more popular day by day due to its accuracy in PD detection. This paper represents the mathematical approach of UHF acoustic method for the Localization of PD in MATLAB GUI environment. Field testing is done on 100 MVA 400/220 kV Interconnecting Transformer at 400 kV receiving station and the obtained results are compared with the output of mathematical algorithm in MATLAB software. Results revels the effective visualization of the possible position of the PD in the transformer tank in terms of x, y and z coordinates. © 2022 IEEE.

关键词： Power transformers

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Multi-ID2R: An Intelligent Device Disaster Recovery Mechanism in Multipath Scenarios

Multi-ID2R: An Intelligent Device Disaster Recovery Mechanis...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Wang, Wenxiao Zhang, Yuyang Dong, Ping Du, Xiaojiang Yu, Chengxiao Zhang, Hongke Aitsaadi, Nadjib Beijing Jiaotong University School of Electronic and Information Engineering China Pengcheng Laboratory Dept. of New Networks Shenzhen China Stevens Institute of Technology Dept. of Electrical and Computer Engineering HobokenNJ United States Université Paris-Saclay Uvsq David Versailles France

ISBN: (纸本)9798350351255

At present, multipath transmission realized by multi-interface devices and bandwidth aggregation technology meets user demand for high-bandwidth communication in 6G wireless networks. However, multipath transmission systems face the threat of single-point failure by multi-interface servers themselves. Existing solutions for such failure are not suitable for multipath transmission scenarios, and this seriously limits the ability to bandwidth aggregation and reduces the reliability and invulnerability of the multipath transmission system in 6G wireless networks. In this paper, we propose a novel Intelligent Device Disaster Recovery (Multi-ID2R) mechanism to solve the single-point failure in multipath and aggregated environments for the first time. In particular, we establish the Multi-Dimensional Parameter Joint Analysis model (MDPJA) and propose an algorithm for judging the running state of multi-interface devices. The algorithm takes into account the different network parameters of the paths, including delay, packet loss rate, and throughput. Moreover, an intelligent switching mechanism based on service quality is designed. Multi-ID2R comprehensively considers the characteristics of the business and the current parameters of multipath networks to determine the moment of switching to flexibly adjust switching strategies. Finally, we deploy the mechanism on multi-interface servers in actual networks. Experiments demonstrate that, compared with Virtual Router Redundancy Protocol, Gateway Load Balancing Protocol, and Hot Standby Router Protocol, Multi-ID2R effectively improves the reliability and invulnerability of multi-interface server in 6G wireless networks. © 2024 IEEE.

关键词： Bandwidth

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Advancements and Challenges in AI and ML-Based Applications for Diabetic Neuropathy: Current State and Future Directions 2

Advancements and Challenges in AI and ML-Based Applications ...

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2nd International Conference on Ambient Intelligence in Health Care, ICAIHC 2023

作者： Joshi, Sukumar Rout, Pravat Kumar Samanta, Indu Sekhar Swain, Kunjabihari Siksha 'O' Anusandhan University Department of Electrical and Electronics Engineering India NIST Institute of Science and Technology Dept. of Electrical and Electronics Engineering Berhampur India

ISBN: (纸本)9798350344882

Diabetic neuropathy, a common complication of diabetes mellitus, significantly impacts the quality of life for millions of individuals worldwide. It is characterized by nerve damage that can lead to pain, numbness, and impaired functionality in affected individuals. With the rise of artificial intelligence (AI) and machine learning (ML) technologies, there has been a growing interest in utilizing these techniques to enhance the diagnosis, prediction, and management of diabetic neuropathy. This research paper aims to explore the current state of AI and ML applications in diabetic neuropathy, highlighting advancements, challenges, and future directions. © 2023 IEEE.

关键词： Machine learning

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AN ATTEMPT TO UNIFY EVALUATION OF GROUND DEFORMATION MODULUS USED FOR COEFFICIENT OF HORIZONTAL SUBGRADE REACTION EVALUATION OF PILES

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AIJ Journal of technology and Design 2022年第69期28卷 621-626页

作者： Shimomura, Shuichi Suzuki, Yasutsugu Dept. of Architecture and Architectural Engineering College of Industrial Technology Nihon Univ. Japan Disaster Prevention and Wind Engineering Group Kajima Technical Research Institute Japan

In this paper, deformation modulus in an evaluation method of coefficient of subgrade reaction were evaluated. As a result, the variation of deformation modulus obtained from the pressuremeter tests can be suppressed its variation by considering the strain dependency of the ground rigidity. Furthermore, the relationships between the deformation modulus obtained from the pressuremeter test and the PS logging can be approximated proportionally, and the relationships between the deformation modulus and the SPT N-value are approximated by a power approximation formula with an intercept, which enable to unify evaluation of the deformation modulus. © 2022 Architectural Institute of Japan. All rights reserved.

关键词： Deformation

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A Characteristic Analysis of Power Quality on Railway Distribution Power Network Connection with Regenerative Inverter in DC Railway system

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Transactions of the Korean Institute of Electrical Engineers 2023年第9期72卷 1107-1112页

作者： Yun, Chi-Myeong Kim, Hyungchul Kim, Hansoo Kim, Malsoo Jung, Hosung Smart Electrical & Signaling Division Korea Railroad Research Institute Korea Republic of Dept. of Transportation Engineering Korea University of Science and Technology Korea Republic of System Management Dept Electric Team Incheon Transit Corporation Korea Republic of Renewable Energy Division G-philos Co. Ltd Korea Republic of

In this paper, the matters to be considered by the regenerative inverter according to the low or high-voltage connection plan of the railway were analyzed to utilize the regenerative energy generated by the urban railway DC traction system. Criteria for various considerations such as energy flow, voltage fluctuations, and power quality of regenerative energy were presented when connecting the railway traction system. Power analysis simulations were used to analyze whether criteria were satisfied. The power analysis program PSCAD/EMTDC confirmed that the criteria were satisfied below the international standard IEEE-519 according to the low-voltage and high-voltage connection method. Copyright © The Korean Institute of Electrical Engineers.

关键词： Power quality

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A Comprehensive Examination of Deep Learning Based Tea Leaf Disease Identification Methods 9

A Comprehensive Examination of Deep Learning Based Tea Leaf ...

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9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Narendra, M. Aditya, Bolla Krishna, B. Hari Suresh, K Naga Varma, C.M. Suvarna Vivek, Kolla Dept. of Cse Telangana Maisammaguda India Dept. of It CMR Technical Campus Telangana India Malla Reddy Engineering College Dept. of Cse Telangana Maisammaguda India Dept. of Cse Andhra Pradesh Ongole India Srk Institute of Technology Dept. of Cse Andhra Pradesh Vijayawada India Dept. of Cse Ongole523001 India

ISBN: (纸本)9798350377972

This research provides a comprehensive review of state-of-the-art deep learning (DL)-based approaches for disease detection and diagnosis in tea plants. The study reviews various DL methods, particularly Convolutional Neural Networks (CNNs), focusing on their implementations, datasets used, and performance metrics. While existing studies have shown promising results, the review highlights the challenges and limitations of current approaches. By identifying these challenges and proposing future research directions, this study aims to guide further research in this area and contribute to the development of more robust and effective DL-based solutions for disease detection and management in tea plants. © 2024 IEEE.

关键词： Adversarial machine learning

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Enhancing Siamese Neural Network Performance with Custom Local Binary Patterns for Face Matching 8

Enhancing Siamese Neural Network Performance with Custom Loc...

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8th IEEE International Conference on Information and Communication technology, CICT 2024

作者： Koranga, Pawan Singh Indian Institute of Technology Kharagpur Dept. of Computer Science and Engineering Kharagpur India School of Computer Sciences Upes Dehradun248001 India

ISBN: (纸本)9798331531539

In this study, we investigate the efficacy of incorporating custom local binary patterns (LBP) as a preprocessing technique to enhance the performance of Siamese neural networks for face matching tasks. Our research focuses on training Siamese models using the DC Face dataset and comparing their performance when trained with and without LBP integration. The custom LBP function is designed to capture fine-grained texture details from facial images, providing robust feature representations that are invariant to variations in lighting conditions and facial expressions. Through rigorous experimentation and evaluation, we analyze the impact of LBP on the threshold point for image differentiation and compare the matching accuracy of Siamese models trained with and without LBP. Our findings reveal significant improvements in matching accuracy and robustness when utilizing the texture features extracted by the custom LBP function. By encoding local pixel structures and capturing subtle facial characteristics, LBP-enhanced Siamese models demonstrate enhanced performance in accurately matching faces across different images. Further-more, our study highlights the importance of using domain-specific preprocessing techniques, such as LBP, to optimize the capabilities of Siamese neural networks for face matching tasks. The results underscore the effectiveness of customizing feature extraction methods to suit the characteristics of the dataset, leading to improved matching accuracy and robustness. Overall, our research contributes valuable insights into the role of LBP in enhancing the performance of Siamese neural networks for image-based similarity tasks, with implications for various real-world applications in face recognition and biometric authentication. © 2024 IEEE.

关键词： Local binary pattern

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Convolutional Neural Network Based Approach for Automatic Detection of Diseases from Pomegranate Plants 8

Convolutional Neural Network Based Approach for Automatic De...

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8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Rana, Harsh Singh Manjunatha, N. Pokhare, Somnath S. Marathe, Rajiv A. Rajan, Jeny National Institute of Technology Karnataka Dept. of Computer Science and Engineering Surathkal India ICAR National Research Centre on Pomegranate Solapur India

ISBN: (纸本)9798350350593

Recent advancements in Artificial Intelligence, particularly Convolutional Neural Networks (CNNs), have significantly enhanced computer vision tasks, including plant disease detection. India is a global leader in pomegranate cultivation and production. Pomegranate is a vital horticultural commodity with significant export potential but is highly susceptible to various diseases, leading to substantial economic losses. Existing research on automatic pomegranate disease detection has limitations, as it typically analyzes either fruits or leaves in isolation and uses datasets with plain backgrounds that do not reflect real-world complexities such as lighting variations and overlapping foliage. This study proposes a novel hybrid deep learning approach that addresses these limitations. We utilized a hybrid CNN model specifically developed using the pomegranate dataset provided by the ICAR-National Research Centre on Pomegranate. This comprehensive collection includes 1,632 high-resolution images captured from orchards across India, categorized into three classes: healthy, bacterial diseases, and fungal diseases. Our model achieves an impressive accuracy rate of 98.46%, demonstrating its potential for real-world application in pomegranate disease detection and improved agricultural outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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Crowd Estimation Using Sensors for Public Transport (BUSES)

Crowd Estimation Using Sensors for Public Transport (BUSES)

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2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023

作者： Sumathi, S. Soms, Nisha Gowtham, S. Pagalavan, M. Hariharan, S. Sri Eshwar College of Engineering Dept. of Artificial Intelligence and Data Science Coimbatore641 202 India Kpr Institute of Engineering and Technology Coimbatore India

ISBN: (纸本)9798350317060

The Population in Indian metropolitan metropolises have been growing at an intimidating rate. In these metropolises, motorcars are generally the most preferred last afar trip, due to their cheap rates and expansive routes. Crowd estimation ways using cameras inside the motorcars aren't suitable. Hence, we've enforced a result using Internet of effects. Crowd operation system is necessary in those circumstances to prevent crowd problems. Therefore, in order to preserve lives, it is very necessary for a frame to be in charge of these masses. In terms of crowd timing and used sweating, this frame shall be clever and efficient. The suggested framework is based on IoT, facilitates relationships between electronic devices, and presents information through smart operations with a tidy, straightforward interface for flexible and simple operation by individuals from all eras. The goal is to support directors' control in an explosive way and distribute to callers over the designated area. The detector, operation, and affiliate layers make up the three layers that make up the frame. The detector subcaste is in charge of gathering crowd data. As a mediator between detectors and affiliate layers, the operation subcaste. It consists of online or other services that are in charge of gathering and analyzing data flowing from the detectors. Additionally, it alerts managers of busy places so they can act appropriately. Later, the appropriate choice will be made and communicated to the interface subcaste. The proposed crowded the machine is and how far is it from their position for which They're staying. To reduce the vexation in the operation of Public Transport system(motorcars) through Integration of tackle and software technologies that provides stoner interface with 1. Live position of the machine (through GPS). 2. Crowd position in the machine (through Detectors). © 2023 IEEE.

关键词： Internet of things

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