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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1613-1623页

作者： Manna, Siladittya Bhattacharya, Saumik Pal, Umapada Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata700108 India Indian Institute of Technology Kharagpur Department of Electronics and Electrical Communication Engineering Kharagpur721302 India

In medical image analysis, the cost of acquiring high-quality data and annotation by experts is a barrier in many medical applications. Most of the techniques used are based on a supervised learning framework and require a large amount of annotated data to achieve satisfactory performance. As an alternative, in this article, we propose a self-supervised learning approach for learning the spatial anatomical representations from the frames of magnetic resonance (MR) video clips for the diagnosis of knee medical conditions. The pretext model learns meaningful context-invariant spatial representations. The downstream task in our article is a class-imbalanced multilabel classification. Different experiments show that the features learned by the pretext model provide competitive performance in the downstream task. Moreover, the efficiency and reliability of the proposed pretext model in learning representations of minority classes without applying any strategy toward imbalance in the dataset can be seen from the results. To the best of our knowledge, this work is the first of its kind in showing the effectiveness and reliability of self-supervised learning algorithms in imbalanced multilabel classification tasks on MR scans. © 2020 IEEE.

关键词： Supervised learning

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Multilayer Neural Network Based Speech Emotion Recognition for Smart Assistance

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computers, Materials & Continua 2023年第1期74卷 1523-1540页

作者： Sandeep Kumar MohdAnul Haq Arpit Jain C.Andy Jason Nageswara Rao Moparthi Nitin Mittal Zamil S.Alzamil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAP522502India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Computer Science and Engineering Teerthanker Mahaveer UniversityMoradabadUttar Pradesh244001India Department of Electronics and Communication Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia

Day by day,biometric-based systems play a vital role in our daily *** paper proposed an intelligent assistant intended to identify emotions via voice message.A biometric system has been developed to detect human emotions based on voice recognition and control a few electronic peripherals for alert *** proposed smart assistant aims to provide a support to the people through buzzer and light emitting diodes(LED)alert signals and it also keep track of the places like households,hospitals and remote areas,*** proposed approach is able to detect seven emotions:worry,surprise,neutral,sadness,happiness,hate and *** key elements for the implementation of speech emotion recognition are voice processing,and once the emotion is recognized,the machine interface automatically detects the actions by buzzer and *** proposed system is trained and tested on various benchmark datasets,i.e.,Ryerson Audio-Visual Database of Emotional Speech and Song(RAVDESS)database,Acoustic-Phonetic Continuous Speech Corpus(TIMIT)database,Emotional Speech database(Emo-DB)database and evaluated based on various parameters,i.e.,accuracy,error rate,and *** comparing with existing technologies,the proposed algorithm gave a better error rate and less *** rate and time is decreased by 19.79%,5.13 *** the RAVDEES dataset,15.77%,0.01 s for the Emo-DB dataset and 14.88%,3.62 for the TIMIT *** proposed model shows better accuracy of 81.02%for the RAVDEES dataset,84.23%for the TIMIT dataset and 85.12%for the Emo-DB dataset compared to Gaussian Mixture Modeling(GMM)and Support Vector Machine(SVM)Model.

关键词： Speech emotion recognition classifier implementation feature extraction and selection smart assistance

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Implementation of Instantaneous P-Q Theory to Improve Power Quality by Shunt Active Power Filter for Non-Linear Loads 3

Implementation of Instantaneous P-Q Theory to Improve Power ...

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3rd IEEE International Conference on Electrical Power and Energy Systems, ICEPES 2024

作者： Kumar, S. Sampath Arya, K. Chandrakala, K. R. M. Vijaya Nadar, Kannan Pauliah Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Electrical and Electronics Engineering Coimbatore India Institute of Technology Jigjiga University Department of Electrical and Computer Engineering Ethiopia

ISBN: (纸本)9798350390728

Non-linear loads insert harmonics into the electrical power system. Harmonic frequencies in an electrical network are a foremost cause for introducing issues in the quality of power. Most of the power quality troubles are non-stationary in nature and mostly occur when a non-linear load is connected to the source. The Total Harmonic Distortion (THD) itself will be very high and becomes a sizable challenge to maintain the quality of power as desired. In this work, a three-phase supply feeding to a three-phase non-linear load as a diode bridge rectifier (DBR) with resistive load is considered. In this context, the source side will be injected with harmonics because of the non-linear load which is not advisable. Therefore, various techniques are implemented to filter the harmonics across the source side. Orthodox systems are based on a filtering technique and from distorted source current, the fundamental current component is separated. Shunt Active Power Filter (SAPF) is the most collective device to reduce the source current harmonics. The pulses generated for SAPF are through the Instantaneous p-q theory technique. The SAPF model is connected among source and non-linear load which is analyzed by MATLAB/Simulink® and validated the operation experimentally by DS1104 card of dSPACE system integrated into MATLAB. A power quality analyzer (fluke meter) is used to evaluate the source current harmonics in the hardware setup. © 2024 IEEE.

关键词： Harmonic analysis

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Navigating Bengali Linguistics: Insights from Machine and Deep Learning Perspectives for Categorization of Sentences 26

Navigating Bengali Linguistics: Insights from Machine and De...

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26th International Conference on computer and Information technology, ICCIT 2023

作者： Islam, Md Minhazul Jubaer, Tanbeer Srizon, Azmain Yakin Rakib Hossain, Md. Mahedy Hasan, S.M. Farukuzzaman Faruk, Md. Minhazur Rahman, A.F.M. Rajshahi University of Engineering and Technology Department of Computer Science & Engineering Rajshahi Bangladesh Rajshahi University of Engineering and Technology Department of Electronics and Telecommunication Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350359015

The paper presents an innovative exploration into the classification of Bengali sentences, an essential aspect of advancing natural language processing (NLP) for languages characterized by rich linguistic diversity. In this comprehensive study, various machine learning and deep learning methodologies were meticulously applied to navigate the intricate linguistic landscape of the Bengali language. The research draws upon and synthesizes insights from previous studies that have focused on aspects such as sentence attributes, simplification algorithms, context-free grammar applications, and grammar-rule based transformations. The core of this study is anchored in the deployment of three distinct vectorization approaches - BERT-based, Glove-based, and TF-IDF-based - for the nuanced classification of Bengali sentences into simple, complex, and compound categories. A series of classifiers were applied, with the BERT-based vectorization demonstrating exemplary proficiency, registering an impressive 98.07% overall test accuracy. This finding underscores the model's robustness and versatility, illuminating its potential applicability beyond the designated dataset to encompass bespoke, real-life datasets. The research is set against the backdrop of a recently published large-scale Bengali sentence dataset titled Bangla Transformation of Sentence Dataset (BTSD) consisting of 3793 samples, which has filled a significant void in the existing literature, enabling a more intricate and detailed analysis. The findings of this study not only contribute to the enriched understanding of Bengali sentence structures but also hold implications for the broader field of computational linguistics and NLP. © 2023 IEEE.

关键词： Bengali Text Processing BERT Deep Learning Natural Language Processing Sentence Classification

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Optimizing Antenna Design for 6G Applications Using Machine Learning Techniques

Optimizing Antenna Design for 6G Applications Using Machine ...

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2024 International Conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Sharma, Praveen Kumar Yadav, Vivek Prakash Mukesh, Aashiwal Nirmal Jawale, Sourabh Kumar, Ankit Research Center for Electrical and Information Technology Seoul National University of Science and Technology Seoul01811 Korea Republic of FEAL: Flexible Electronics and Antenna Lab Department of Electronics and Communication Engineering Pilani India FEAL: Flexible Electronics and Antenna Lab Department of Electronics and Communication Engineering Mumbai India Medicaps University Department of Computer Science and Engineering Indore India Seoul National University of Science and Technology Department of Computer Science and Engineering Seoul01811 Korea Republic of

ISBN: (纸本)9798350379716

The emergence of 6G networks requires innovative antenna designs that operate at extremely high frequencies. The proposed paper explores the application of advanced machine learning techniques to optimize the design of antennas for 6G applications at 15 GHz. Traditional design methods are often time-consuming and depend on expert knowledge, whereas machine learning can automate and expedite this process. We developed a dataset incorporating critical antenna design parameters such as geometric dimensions and applied algorithms to predict key performance metrics like return loss, gain, and bandwidth. Our results demonstrate that neural networks, in particular, offer superior predictive accuracy, significantly reducing design iteration times. This integration of machine learning into antenna design not only improves performance but also facilitates the development of adaptive antenna systems, meeting the stringent demands of 6G networks. This research highlights the potential of machine learning to revolutionize antenna design, enabling rapid and efficient development of next-generation communication systems. © 2024 IEEE.

关键词： Smart antennas

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Deep Learning Models for Acoustic Monitoring of the Himalayan Monal and Other Elusive Bird 4

Deep Learning Models for Acoustic Monitoring of the Himalaya...

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4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Nikshya, J. Ebens Raj, J. Relin Francis Krishnan, R. Santhana Rajkumar, G.Vinoth Settu, Imran Javeed Kavitha, S. Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India J. P. College of Engineering Department of Electronics and Communication Engineering Tenkasi India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India

ISBN: (纸本)9798331523923

Acoustic monitoring of rare and elusive bird species presents significant challenges due to the complexity of environmental noise and the variability in bird vocalizations. This study proposes a novel deep learning framework, BioAudio VisionNet (BAVNet), specifically designed for the acoustic identification and monitoring of the Himalayan Monal and other rare bird species. The performance of the proposed algorithm was evaluated against three established algorithms: Support Vector Machines with Acoustic Features (SVM-AF), Audio Spectrogram Transformer (ASF), and Deep Belief Networks (DBN). Simulation experiments were conducted using metrics such as accuracy versus the number of epochs, processing time versus accuracy, and spectrogram classification accuracy versus spectrogram resolution. The results demonstrated that BAVNet achieved a notable improvement in classification accuracy, computational efficiency, and adaptability to varying spectrogram resolutions when compared to existing methods. These findings highlight the potential of BAVNet for real-time biodiversity monitoring in challenging environments. Future work can explore the integration of additional contextual data, such as environmental factors, to further enhance system performance. © 2025 IEEE.

关键词： Birds

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Convolutional Neural Networks for Automated Detection and Classification of Plasmodium Species in Thin Blood Smear Images 1

Convolutional Neural Networks for Automated Detection and Cl...

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1st International Conference on Software, Systems and Information technology, SSITCON 2024

作者： Mahesh Kumar, A.S. Maindola, Meenakshi Salis, Vimuktha E Mitra, Abhijit Janumala, Tabitha Vijayan, Alpha Maharaja Institute of Technology Department of Electronics and Communication Engineering Belawadi India Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Global Academy of Technology Department of Information Science and Engineering Bengaluru India Pune India R v College of Engineering Department of Electronics and Instrumentation Engineering Bengaluru India Christ University Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350352931

There has been a continued transmission of malaria throughout the world due to protozoan parasites from the Plasmodium species. As for treatment and control, it is very important to make correct and more efficient diagnostic. In order to observe the efficiency of the proposed approach, This Research built a Convolutional Neural Network (CNN) model for Automated detection and classification on thin blood smear images of Plasmodium species. This model was built on a corpus of 27558 images, included five Plasmodium species. Our CNN model got an overall accuracy of 96% for the cheating detection with an F 1score of 0.94. In the detection of the presence of malaria parasites the test accuracy conducted was as follows: 8%. Species-specific classification accuracies were: P. falciparum (95.7%), P. vivax (94.9%), P. ovale (93.2%), P. malaria (92.8%) and P. Knowles (91, 5%). As for the model SL was found to have sensitivity of 97.3% And the specificity in this case is 9 6. 1 %. The proposed CNN-based approach provides a sound and fully automated solution for malarial parasite detection and species determination, which could lead to better diagnostic performances in day-to-day practices. © 2024 IEEE.

关键词： Convolutional neural networks

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A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar for Human Pose Estimation 12

A Study on 1D-Point Cloud Using Through-Wall mm Wave Radar f...

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12th International Electrical engineering Congress, iEECON 2024

作者： Phaisiri, Kritthee Kittiyanpunya, Chainarong Shutimarrungson, Nattakarn Boonpoonga, Akkarat Akkaraekthalin, Prayoot Kaemarungsi, Kamol King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand Rajamangala University Of Technology Rattanakosin Faculty Of Engineering Department Of Mechatronics Engineering Nakhon Pathom Thailand Mahasarakham Business School Mahasarakham University Department Of Business Computer Maha Sarakham Thailand Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand National Electronics And Computer Technology Center National Science And Technology Development Agency Pathum Thani Thailand

ISBN: (纸本)9798350383591

This paper presents human pose estimation using millimeter-wave (mmWave) radar technology capable of penetrating obstacles. Operating within the frequency modulated continuous wave (FMCW) at 60 - 64 GHz, our radar system generates signals conducive to accurate human pose representation. Our data processing framework focuses on producing point cloud data, effectively capturing each human movement. Results are visualized through a 2D graph, with the z-axis representing time. Experimental data, collected from various activities conducted behind different walls, underwent thorough analysis, comparing point cloud positions with actual human postures. The outcomes affirm the effectiveness of mmWave radar systems, positioned behind obstacles, in accurately extracting human postures. © 2024 IEEE.

关键词： Frequency modulation

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AI based Compact Controller for Wind farms Economical Operation, Control and Monitoring 2

AI based Compact Controller for Wind farms Economical Operat...

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2nd International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2024

作者： Sasikala, C. Palpandian, P. Muthuram, G. Kumar, S. Siva Karthik, S. Sam Raj, C. Mohan Arjun College of Technology Department of Electronics and Communication Engineering Coimbatore642 120 India Karpagam College of Engineering Department of Electrical and Electronics Engineering Coimbatore641 032 India Hindusthan College of Engineering and Technology Department of Electrical and Electronics Engineering Coimbatore India Nehru Institute of Engineering and Technology Department of Computer Science and Engineering Coimbatore641 105 India Dhanalakshmi Srinivasan College of Engineering Department of Electrical and Electronics Engineering Coimbatore641 105 India Sri Eshwar College of Engineering Department of Electrical and Electronics Engineering Coimbatore641 202 India

ISBN: (纸本)9798350368413

In India, 42.6 GW power is generated by wind turbine generators for supplying electricity to the load. Permanent Magnet DC generator, Synchronous generator and Induction generator are the most commonly used generators in the wind mill. Though the generators are designed for producing the power with maximum efficiency, monitoring, operation and control of wind mill plays an important role. The instantaneous faults like open circuit fault and least resistance fault can be easily detected and removed by the protection scheme. But the inter turn fault, core saturation condition, loss of dielectric due to ageing of machines cannot be detected until the fault occurs. The economic operation of the wind mill is based on the fault detection and prediction, uninterrupted operation of the wind mill, monitoring of parameters from the remote location. The AI based compact controller R04CPU with remote I/O module is used to monitor, control the windmill and ensures the economic operation/fault detection. © 2024 IEEE.

关键词： Windmill

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Ergonomical Investigation of Musculoskeletal Distress during Water-Barrel Lifting using sEMG Sensors and MATLAB 7

Ergonomical Investigation of Musculoskeletal Distress during...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Ravisankar, B. Shankar, S. Abbas, G. Gopalakrishnan, M. Gugapriyan, S. Nadin, L. Kongu Engineering College Department of Electrical And Electronics Engineering Erode India Kongu Engineering College Department of Mechatronics Engineering Erode India Kongu Engineering College Department of Computer Technology Erode India

ISBN: (数字)9798350359299

ISBN: (纸本)9798350359299

In developing countries like India, several parts of works are carried out manually with the help of hand tools which may lead to health issues. Therefore, proper design is important for avoiding musculoskeletal disorder like arm vibration syndrome, tendonitis, carpal tunnel syndrome etc. This kind of health concerns can be reduced significantly by using hand tools designed from ergonomic concepts. The feeling of discomfort in the form of fatigue, experiencing pain during work can be caused due to prolonged usage of improperly designed hand tools. By introducing ergonomics issues in design of product, the customer's well-being and effectiveness of manual operations can be improved by reducing the musculoskeletal disorders. The aim of the proposed study is to analyze the effects of ergonomically designed holder used to uplift the water canes. Two holders which have been designed ergonomically with various holding position are used. Nearly six male participants are subjected to uplift the water canes using two different modified holders and standard holder. © 2024 IEEE.

关键词： Developing countries

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