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2022 IEEE World Conference on Applied Intelligence and Computing, AIC 2022

作者： Gangurde, Pranav Japhet, Melita lobo, Clafacio Patil, Nilesh Patil, Prachi Fr. Conceicao Rodrigues College of Engineering Information Technology Mumbai India SVKM's D.J Sanghvi College of Engineering Computer Engineering Mumbai India Fr. Conceicao Rodrigues College of Engineering Computer Engineering Mumbai India

ISBN: (数字)9781665479882

ISBN: (纸本)9781509050017

Blockchain is the technology that has had the greatest influence on our lives in the last decade. It is a technique that makes it difficult to hack the system or alter the data it stores, keeping it safe and unchangeable at all times. Our research exploits this unique feature provided by blockchain to ensure the privacy of job applicants. We extract text from resumes in PdF format, encrypt it and store the hash value in a blockchain. Our implementation involves the usage of Ganache, Truffle and Metamask with a front end designed using ReactJS. The resumes can be accessed via the blockchain from the administrator side and viewed in its original format. The data integrity of the resumes can then be checked at any point by converting a resume to its unique hash and comparing it with the hash stored inside the blockchain. © 2022 IEEE.

关键词： Smart contract

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ApplediseaseNet-B7: A Robust Solution for Apple leaf disease Classification and Model Evaluation 4

AppleDiseaseNet-B7: A Robust Solution for Apple Leaf Disease...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Mathias, Ajisha Raj, J. Relin Francis Raja, S.R. Krishnan, R. Santhana Balamuralikrishnan, G. Soundiraraj, N. Vel Tech Rangarajan Dr Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Avadi Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Electronics and Communication Engineering Chennai India Hindustan Institute of Technology and Science Chennai India Scad College of Engineering and Technology Department of Electronics and Communication Engineering Cheranmahadevi India Velammal College of Engineering and Technology Department of Computer Science and Engineering Madurai India Psna College of Engineering and Technology Department of Electrical and Electronics Engineering Dindigul India

ISBN: (纸本)9798331540364

Apple leaf diseases, like cedar apple rust, black rot, and apple scab, pose severe obstacles to apple farming and impact crop productivity and quality. The sophisticated classification model ApplediseaseNet-B7, known for its efficiency and outstanding performance, was created using the EfficientNetB7 architecture and is presented in this paper. The model improves its feature extraction capabilities by utilizing pretrained weights from ImageNet, which makes it a good fit for differentiating between various apple leaf diseases. ApplediseaseNet-B7 incorporates numerous unique layers intended to increase classification precision. A Global Average Pooling layer streamlines feature maps, complicated patterns are captured by a dense layer with RelU activation, overfitting is reduced by a dropout layer, and class prediction is accomplished by a final dense layer with softmax activation. The model's resilience is further increased using thorough data preparation, and augmentation approaches from the PlantVillage and Kaggle Apple leaf disease datasets. A comprehensive comparison is made between ApplediseaseNet-B7's performance and other well-known models, including denseNet121, ResNet50, and AlexNet. The analysis shows that ApplediseaseNet-B7 regularly performs better than comparable models in terms of accuracy, precision, recall, and F1 score, among other criteria. This comparison demonstrates how well ApplediseaseNet-B7 performs in classifying apple leaf diseases, providing a reliable and effective method for managing and detecting agricultural diseases. The study emphasizes how crucial sophisticated model selection is to enhancing crop health monitoring and disease control. © 2024 IEEE.

关键词： Fruits

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Blockchain Based Voting System for Secure and Transparent Electoral Processes 10

Blockchain Based Voting System for Secure and Transparent El...

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

作者： Sumathy, S. Murugan, S. Karthick latha, J. Mageshwari, G. Andrews, Allen Joseph Gilbert Kumar, M. Hema Sir Theagaraya College-Shift Ii Pg Department of Computer Science Tamilnadu Chennai India R. M. D. Engineering College Department of Computer Science and Engineering Tamilnadu Thiruvallur India R. M. K. Engineering College Department of Computer Science and Engineering Tamilnadu Tiruvallur India R.M.K. College of Engineering and Technology Department of Artificial Intelligence and Data Science Tamilnadu Tiruvallur India Deloitte consulting Llp 200 Sterling road MechanicsburgPA United States Sona College of Technology Department of Ece Tamil Nadu Salem India

ISBN: (纸本)9798350384369

This study describes an innovative approach to blockchain-based voting systems. The proposed method guarantees the integrity, security, and resistance to manipulation of elections conducted on a decentralized network through the utilization of smart contracts and cryptographic principles. Emphasizing participant confidentiality, vote integrity, and real-time auditability, the experimental outcomes demonstrate the system's scalability, dependability, and security. Within the domain of theoretical democratic discourse, presents a prospective scenario in which voting methods based on blockchain technology. The results indicate that the approach can be easily implemented on a large scale, representing a significant milestone in the struggle for democratic, secure, and transparent voting procedures. With highly efficient, boasting a transaction speed of 500 TPS, scalability to accommodate over a thousand users, and a block confirmation time of less than 10s. Encryption efficiency and digital signature dependability are indicators of the system's high level of security. Equipped with an accuracy rate that is 97.2%. © 2024 IEEE.

关键词： decentralized finance

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Energy-Efficient Communication Protocols for IoT devices 9

Energy-Efficient Communication Protocols for IoT Devices

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9th International Conference on Science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Rahamathunnisa, U. Vivekanand, Chettiyar Vani Chithras, T. Sreedevi, E. Kiran, Venneti Rajendiran, M. School of Computer Science Engineering And Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Rmk College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Thiruvallur India Veltech Rangarajan Dr.Sagunthala R&d Institute of Science And Technology Department of Electrical And Electronics Engineering Chennai Tamil Nadu Avadi600062 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram India Andhra Pradesh Surampalem India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350365092

The development and optimisation of energy-efficient communication protocols that are specifically adapted for Internet of Things (IoT) devices is the focus of this research. The proliferation of interoperable bias has given rise to the converse girding energy consumption, which has come a consummate concern in the contemporary period. The primary end of this bid is to probe innovative approaches and protocols with the capacity to reduce the energy consumption of Internet of Effects(IoT) connections. As a result, the bias will retain the capability to attain an extended functional lifetime while coincidently producing a lowered environmental footmark. The presented protocols aim to achieve a result that balances the utilisation of energy coffers with the conservation of dependable communication. A thorough examination of the presently employed protocols, coupled with the perpetration of sophisticated optimisation ways, will be the styles employed to achieve this thing. Theprovides a significant donation to the development and prosecution of communication protocols that effectively address the unique energy constraints encountered by Internet of effects(10T)- connected ecosystems. This contributes to the enhancement of effectiveness and sustainability in the world of networked bias, which is expanding at an accelerated rate. © 2024 IEEE.

关键词： Energy efficiency

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Advanced day lighting system using fiber optics

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Optical and Quantum Electronics 2023年第6期55卷 1-13页

作者： Kavitha, T. Pappa, C. Kanmani Shobana, R. Raj, A. Albert Ahilan, A. Veerasamy, B. Gnanamalar, A. Jasmine Department of Electronics and Communication Engineering Veltech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai 600054 India Department of Computer Science and Engineering S.A. Engineering College Chennai 600077 India Department of Electronics and Communication Engineering Sri Krishna College of Engineering and Technology Tamil Nadu Coimbatore 641008 India Department of Electronics and Communication Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli 627152 India Department of Electronics and Communication Engineering Hindusthan College of Engineering and Technology Tamil Nadu Coimbatore 641050 India Department of Electrical and Electronics Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli 627152 India

daylighting plays an important role in decreasing power usage in office buildings and enhancing indoor environments. Reducing the use of energy and producing energy from renewable sources will result in lower greenhouse gas emissions. daylighting is a method of providing light indoors through the use of windows, solar panels, optical fibers, parabolic mirrors and other forms of daylight technologies. The proposed fiber optic daylighting system will illuminate the light uniformly in interior space. Parabolic mirror and Frensnel lens are two different efficient approaches available for fiber-based day lighting system. Captured light is passed via concentrator, fiber and lenses. Uniform lighting at the capture point eliminates the heat problem when incorporating optical plastic fiber is critical in making the device cost-effective. Collimated light increases device performance helping to inject full light into the optical fibres. From simulation setup will verify that uniform intensity of light will be illuminated to different regions of buildings by the fiber optic bundle. Collimated lighting and reduction of shadows caused by mechanical parts and the convex reflector will enhances the system’s efficiency. Uniform illumination will be given at all time by using hybrid system. Using solar day lighting in homes and offices via optical fibre cables is a potential way to reduce the energy used for artificial lighting while also improving visual comfort and human health. Analysis and discussion have been conducted on the impact of optical fibre diameter on the brightness and homogeneity of light. This efficient technology can lower energy costs and also helps in climate change challenges. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, llC, part of Springer Nature.

关键词： Freshnel lens Optical fibre Parabolic reflector Solar concentrator Uniform illumination

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detection of Breast Cancer using Curvelet Transform and Adaptive Particle Swarm Optimization Technique 12

Detection of Breast Cancer using Curvelet Transform and Adap...

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12th IEEE International Conference on Advanced Computing, ICoAC 2023

作者： Meena, l.C. Joe Prathap, P.M. Sankara Narayanan, S. R.M.D. Engineering College Department of Computer Science and Engineering Tiruvallur India Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur India

ISBN: (纸本)9798350318210

The breast cancer is the most prevalent malignancy. Better chance of curing breast cancer is early detection, which can also lower mortality rates. The best technique for early breast disease detection is the mammography. In the suggested approach, curvelet transform is utilized to extract features, and adaptive particle swarm optimization helps to choose the eminent features. Adaptive Particle Swarm optimization has been devised to speed up and simplify the process of feature selection and Support Vector Machine (SVM) aids in breast cancer classification. We present an Adaptive Particle Swarm optimization (APSO) that outperforms Particle Swarm optimization (PSO) regarding search efficiency. The suggested model is examined using a collection of 332 images from the Mammographic Image Analysis Society (MIAS) database. The executed findings are compared with the old transforms, and the results demonstrate that the suggested model has higher detection accuracy rates than the earlier approaches. © 2023 IEEE.

关键词： Mammography

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lyapunov stability analysis and FIl implementation for boundary-based hybrid controller in boost converter

Advanced Control for Applications: Engineering and Industria...

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Advanced Control for Applications: engineering and Industrial Systems 2024年第3期6卷

作者： Patel, Hardik Shah, Ankit Instrumentation and Control Engineering Department Government Engineering College Rajkot India Instrumentation and Control Engineering Department L. D. College of Engineering Ahmedabad India

This paper presents a comprehensive stability analysis of the boundary-based hybrid control (BBHC) algorithm designed for boost converter. The stability assessment is carried out utilizing multiple lyapunov functions, addressing both continuous conduction mode (CCM) and discontinuous conduction mode (dCM) operation. The boost converter is modeled as a hybrid automaton to capture its dynamic behavior accurately. Through rigorous lyapunov stability analysis, this study demonstrates the effectiveness of the BBHC algorithm in ensuring stable operation of the boost converter across various operating modes. Additionally, the proposed control algorithm's validation is conducted using the FPGA-in-the-loop (FIl) technique, highlighting its efficiency and robustness in real-world applications. This research contributes valuable insights into the design and implementation of stable control strategies for boost converter, emphasizing the practical utility of the BBHC algorithm with FIl for enhanced performance and reliability in power electronics systems. © 2024 John Wiley & Sons ltd.

关键词： Field programmable gate arrays (FPGA)

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data Fusion and Analysis Techniques for Enhanced decision-Making in IoT Environments 7

Data Fusion and Analysis Techniques for Enhanced Decision-Ma...

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7th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2023

作者： deepa, S. Radhika, M. diwakar, Meenakshi Rufina, Princy Nithya, A. Mohanapriya, M. Panimalar Engineering College Department of Electronics and Communication Engineering Tamilnadu Chennai India R.M.D. Engineering College Department of Information Technology Tamilnadu Chennai India S.A Engineering College Department of AI & DS Tamilnadu Chennai India Prince Shri Venkateswara Padmavathy Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India R.M.K.College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Jeppiar Institute of Technology Department of AI & DS Tamilnadu Chennai India

ISBN: (纸本)9798350340600

The proliferation of Internet of Things (IoT) devices has resulted in an inundation of diverse data sets that have the potential to considerably improve decision-making across many domains. This research work investigates the potential for modern data integration and analysis techniques to improve the decision-making abilities of IoT networks. Using regulated data acquisition, data integration, and cutting-edge analytic methods, the proposed work develops a solution to improve the accuracy of judgments. Using examples from smart manufacturing and healthcare monitoring, the proposed work demonstrates how the new methodology increases productivity and yields actionable data. Comparative analyses indicate that new methodologies markedly outperform those of the competition. This study identifies areas for future research on how integrating disparate IoT data with advanced analytics could lead to improved decision-making in a variety of contexts. © 2023 IEEE.

关键词： Internet of things

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Cardiovascular Abnormalities Identification by Machine learning Classifiers and its Comparision

Cardiovascular Abnormalities Identification by Machine Learn...

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2023 Intelligent Computing and Control for engineering and Business Systems, ICCEBS 2023

作者： Surendran, S. Reddy, B.Malakonda Krishnammal, P.Muthu Venkataramanaiah, B. Murugesan, S. Joany, R.M. Tagore Engineering College Department of Computer Science and Engineering Chennai India Narayana Engineering College Andhra Pradesh Gudur India School of Electronics Engineering VIT-AP University Andhra Pradesh Amaravati India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Electronics and Communication Engineering Chennai India R.M.D Engineering College Department of Computer Science and Engineering Chennai India Sathyabama Institute of Science and Technology Department of Ece Chennai India

ISBN: (纸本)9798350394580

Heart diseases related to the heart increasing everywhere. Human beings are suffering from most dangerous cardiovascular disorders (CVd). Features are main parameters to identify diseases. The feature extraction is done from the signals and make ready for the analysis. Where machine learning (Ml) is a technique that tells the potential emergence of cardiac disease. Information science uses machine learning to address a variety of difficulties. The basic use of machine learning is the forecasting of a result based on data that is already available. The machine applies the designs from the current dataset to a hidden dataset in order to predict the disorders. There are several arranging calculations to be completed with sufficient accuracy. We have used various machine learning classifiers for identifying CVds. Random forest (RF) classifier producing highest accuracy compared to other classifiers. © 2023 IEEE.

关键词： decision Tree KNN logistic Regression Ml RF Support Vector Machine

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A Chic Giza reformed deep attention model (GizRAM) for opinion mining on Twitter with text and emojis

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Iran Journal of computer Science 2025年 1-17页

作者： Kothandan, Prema Pushpavalli, Rajaram Thirumalaikumari, T. Selvanathan, Pournima Sunitha, Pamarthi Nimmagadda, Padmaja Subburayalu, Gopalakrishnan Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Tamil Nadu Chennai 624622 India PG & Research Department of Computer Science Sri Sarada College for Women (A) Salem Fairlands Tamil Nadu Salem 636016 India Department of Computer Science Saveetha College of Liberal Arts and Sciences SIMATS Deemed to Be University Tamil Nadu Chennai India Department of Computer Science and Engineering Sona College of Technology (Autonomous) Salem 636 005 India Department of Electronics and Communication Engineering Aditya University Andhra Pradesh Surampalem 533437 India Department of Electronics and Communication Engineering Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College) Andhra Pradesh Tirupati 517102 India Department of Information Technology Hindustan Institute of Technology and Science Tamil Nadu Chennai 603103 India

Today more than ever, social media like Twitter is significant. However, it has transformed into a public bulletin board where regular people, businesses, and even well-known figures like celebrities regularly post their opinions and take part in discussions. Also, Twitter persists as a useful tool for friends to stay in touch. despite the widespread adoption of Twitter globally, it is more important than ever to be able to do trustworthy analyses of opinions to assess public opinion and perceptions on a variety of topics. Emojis are often used to convey emotions or thoughts that are challenging to put into words concisely. This paper establishes a new way of analyzing opinions by merging deep learning-based sentiment analysis approaches and integrating them with emojis. In this line of action, we propose the Giza reformed deep attention model for both textual as well as emoji-based feature extraction to classify user sentiments. To construct an enhanced opinion mining, a feature extraction and data preparation process based on multi-sets is carried out, followed by the application of the Giza pyramid construction optimizer to feature selection. It significantly reduces the dimensions to lead toward improved accuracy in predictions. This paper proposes the reformed temporal attention-based gated convoluted network (RefTAC) for effective sentiment classification based on the selected features. We validate the effectiveness of our proposed approach on popular Twitter datasets, and the results show impressive performance: 99.1% accuracy on the Airlines dataset, 99% accuracy on the Crowd Flower dataset, and 99% accuracy on the Apple dataset. Our method is better in terms of accuracy and efficiency than the state-of-the-art methods, which shows that adding emojis to sentiment analysis works well. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： And Giza reformed deep attention model (GizRAM) deep learning Emojis text Opinion mining Sentiment analysis Social data Twitter

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