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

作者： saranya, v.s. Mangali, saikiran srinija, K. Medabalimi, Galeiah Devi, Meena venkata Ramana, N.R. Lakkshmanan, Ajanthaa School of Computing Srm Institute of Science and Technology Department of Computing Technologies Kattankulathur Campus Kattankulathur603203 India B V Raju Institute Of Technology Department of Csbs Narsapur Telangana Medak502313 India Mlrit Department: Data science Dundigal India Sagi Ramakrishnam Raju Engineering College Sagi Ramakrishnam Raju Marg Chinna Amiram Andhra Pradesh Bhimavaram India Kcg college of technology Department of electrical and electronics engineering Chennai600097 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering India

ISBN: (纸本)9798350377972

soil health is a critical component of agricultural productivity and sustainability. Traditional methods of assessing soil health, including physical sampling and laboratory testing, are labor-intensive, time-consuming, and costly. This paper proposes a novel image-based approach for soil health analysis using deep learning techniques. by utilizing aerial images captured by drones or satellites equipped with multispectral and thermal sensors, the system non-invasively assesses key soil health indicators such as moisture content, nutrient levels, organic matter, and erosion patterns. The proposed method integrates image processing techniques with machine learning models, particularly Convolutional Neural Networks (CNNs), to extract relevant soil features from the images. These CNNs are trained to predict soil health metrics, and the system's performance is evaluated through accuracy, mean squared error (MsE), and F1-score, showing significant improvements over traditional methods. This scalable solution offers a real-time tool for precision agriculture, aiding farmers and agronomists in making informed, data-driven decisions regarding soil health management. © 2024 IEEE.

关键词： Convolutional neural networks

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Emotion based Music Recommendation system for specially-Abled 6

Emotion Based Music Recommendation System for Specially-Able...

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6th International Conference on Recent Trends on Electronics, Information, Communication and Technology, RTEICT 2021

作者： shreya, L. Nagarathna, N. B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665435598

Human emotion is a psycho physiological state of mind that manifests as good or negative responses to external and internal stimuli. songs have long been a popular alternative for expressing human feelings as a medium of expression. Content-based recommendation engines are used by the majority of existing music recommendation systems. However, music selection is influenced not only by past tastes or musical substance, but also by the user's current mood. This research presents a framework for learning a user's emotion using data gathered from a wearable device that is combined with galvanic skin response (GsR), photo plethysmography (PPG), and electro encephalography (EEG) physiological sensor signals, as well as data taken via camera. This information is used as a supplement to the music recommendation engine. sensor data and face expression data can thus improve the effectiveness and accuracy of the recommendation engine. © 2021 IEEE.

关键词： Emotion Recognition

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An Analysis for the Prediction of Prefetched Content on social Media 6

An Analysis for the Prediction of Prefetched Content on Soci...

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6th International Conference on Recent Trends on Electronics, Information, Communication and Technology, RTEICT 2021

作者： saichandana, s. sooda, Kavitha B.M.S. College of Engineering Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9781665435598

In Recently, social media networks are popularly emerging through world. This has been a great platform for information sharing through network among people. being ubiquitous in nature, social media are accessible anywhere and at any point of time. To provide Quality of Experience support, a learning-based model for social media is been proposed. This is mainly used to improve user's usage satisfaction and to reduce access delay in Online social Networks (OsN). For this, an analysis of Twitter traces for over fourteen months is conducted. Over 2,800 users Twitter data is collected using Twitter API for the analysis of social media friendship. And a cluster-based analysis for these set of user friends is made for the prefetch prediction. A mechanism using XGboost algorithm and Decision Tree Regressor algorithm, the performance of this framework is been determined. The performance of this framework using trace-drive emulations on the social media network has been evaluated. Evaluation results could do superior performance with XG boost algorithm of around 85.1% accuracy of access delay reduction. © 2021 IEEE.

关键词： social networking (online)

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Research on the Application of Artificial Intelligence in Cybersecurity: Integrating Advanced Technologies to Improve Threat Detection and Response

Research on the Application of Artificial Intelligence in Cy...

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Global Conference for Advancement in Technology (GCAT)

作者： T.s.balaji R.Nadanasabai Rajesh Jagadeesan Ravikumar s.sharanyaa R.Meenal Nandigam Poornima Deepthi Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Chennai Department of MBA St.Josephs College of Engineering Chennai Software Engineering Senior Advisor Evernorth Health Services Chattanooga TN Department of Information Technology Panimalar Engineering College Chennai Tamil Nadu India Department of Electrical and Electronics Engineering V.S.B Engineering College India Department of ECE MLR Institute of Technology Hyderabad

ISBN: (数字)9798350376685

ISBN: (纸本)9798350376692

In the current age of digital change, the field of cybersecurity is faced with progressively advanced and enduring dangers. Conventional security measures are finding it difficult to keep up with the fast-changing nature of cyber threats. Artificial intelligence (AI) offers a significant chance to enhance threat detection and response systems by leveraging its sophisticated data processing and pattern recognition abilities. This study explores the incorporation of artificial intelligence (AI) technology in the field of cybersecurity, specifically aiming to improve the effectiveness of systems that identify and respond to threats. The paper commences by examining the present difficulties encountered by cybersecurity experts, which encompass the large number and diverse range of potential threat vectors, the covert and flexible nature of contemporary malware, and the limitations imposed by resource constraints on the efficacy of human-driven analysis. The text explores the current cutting-edge AI strategies used to tackle these difficulties, including anomaly identification through machine learning algorithms, predictive analysis using deep learning models, and threat intelligence collecting through natural language processing. The research also examines the distinct factors of AI in the cybersecurity field, such as the requirement for immediate decision-making, the significance of comprehending the model, and the possibility of hostile attacks on AI systems. This study seeks to analyse current literature and emerging trends to gain a deep understanding of how artificial intelligence (AI) can enhance cybersecurity. Additionally, it aims to identify the obstacles and deficiencies that must be overcome to effectively incorporate AI technologies into this crucial domain. To summarise, the research highlights the considerable capacity of AI to transform cybersecurity practices, providing a way to develop more robust and flexible defence methods against the numerous danger

关键词： Deep learning Ethics Machine learning algorithms Transforms semisupervised learning Threat assessment vectors safety Artificial intelligence computer security

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Review of recent designs, performance, and configurations for the pyramid solar still

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International Journal of Energy and Water Resources 2025年第2期9卷 1145-1176页

作者： Hussein, A. Kadhim Rashid, F. Lafta Abed, A.M. sultan, H.s. Togun, H. Attia, M. El Hadi Manokar, A. Muthu Hamida, M. bechir ben Ali, b. Younis, O. Khutar, N. Murad Mechanical Engineering Department College of Engineering University of Babylon Babylon City Hilla Iraq Petroleum Engineering Department College of Engineering University of Kerbala Karbala Iraq Air Conditioning and Refrigeration Techniques Engineering Department Al-Mustaqbal University College Babylon 51001 Iraq College of Engineering University of Warith Al-Anbiyaa Karbalaa 56001 Iraq Biomedical Engineering Department University of Thi-Qar Nassiriya 64001 Iraq Physics Department Faculty of Exact Sciences University of El Oued El Oued 3900 Algeria Department of Mechanical Engineering B.S. Abdur Rahman Crescent Institute of Science and Technology Tamil Nadu Chennai 600048 India Department of Chemical Engineering College of Engineering Imam Mohammad Ibn Saud Islamic University (IMSIU) Riyadh Saudi Arabia Research Laboratory of Ionized Backgrounds and Reagents Studies (EMIR) Preparatory Institute for Engineering Studies of Monastir (IPEIM) University of Monastir Monastir City Tunisia Higher School of Sciences and Technology of Hammam Sousse Department of Physics University of Sousse Sousse Tunisia School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen 518055 China Department of Mechanical Engineering College of Engineering in Wadi Addwasir Prince Sattam Bin Abdulaziz University Al-Kharj 11942 Saudi Arabia Department of Mechanical Engineering Faculty of Engineering University of Khartoum Khartoum Sudan Department of Computer Technical Engineering Technical Engineering College Al-Ayen University Thi-Qar Iraq

Fresh water is essential for day-to-day survival. The primary issue facing undeveloped nations is the continuous scarcity of clean water, and drinking contaminated water to survive may harm one’s health. Due to population expansion, there is less fresh water available. boring wells, rainwater, and water from rivers or lakes are among the potential water sources. For isolated, arid, and semiarid regions, solar distillation is appropriate. Where there is a severe drinking water deficit and intense solar radiation. With free energy, straightforward, affordable technology, and a clean atmosphere, solar still (ss) partly meets man’s demand for drinking water, especially in distant locations. This review focuses on pyramid solar stills (Pss), highlighting their potential to meet drinking water demands with free, clean energy and simple technology. This paper comprehensively reviews numerical, experimental, and combined (numerical and experimental), discussing various setups, parameters, and results. Key advancements, performance improvements, and future research directions are outlined, emphasizing the importance of innovative designs and optimization for enhanced efficiency and freshwater production. © The Author(s), under exclusive licence to Iranian society of Environmentalists (IRsEN) and science and Research branch, Islamic Azad University 2024.

关键词： Comprehensive review Pyramid solar still Remote regions Water desalination

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Optimizing Heart Disease Detection: A Novel Approach Combining LIGX Hybrid Models and Advanced Data Handling 8

Optimizing Heart Disease Detection: A Novel Approach Combini...

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8th International Conference on I-sMAC (IoT in social, Mobile, Analytics and Cloud), I-sMAC 2024

作者： Ram Pavan Kumar, M.v.T. Pratyusha, K. Neethika, Alluri Kumar, v. s. Pavan Kaliappan, s. Thota, Krishna Kishore Kakaraparti Bhavanarayana College Department of Computer Science Vijayawada India B V Raju Institute of Technology Narsapur Medak India S.R.K.R Engineering College Department of Information Technology Bhimavaram India Mlr Institute of Technology Department of CSE-AIML Hyderabad India Lovely Professional University Division of Research and Development Punjab Jalandhar India Vaddeswaram India

ISBN: (纸本)9798350376425

This study improves the accuracy of heart disease prediction through the inclusion of data preprocessing strategies together with a mixture of model systems. Data cleaning was performed on the dataset with great attention, then balanced the class using synthetic Minority Oversampling Technique (sMOTE) and also using the IQR method to remove outliers. Feature selection was done to make further improvements in performance, the AL2C (ANOvA-L2 Combination) model was used for this purpose. To overcome the limitations of both LightGbM (LGbM) and XGboost, a new model named LIGX which is a combination of both the models was designed. This model's accuracy turned out to be quite impressive and reached of 97.78%, as compared to the earlier studies and showed better precision, recall, and relatively more ruggedness. The findings suggest that the accuracy is boosted by ensemble method, learning and advanced preprocessing techniques. The results of the area support practical use of these techniques in clinical practice which means potential for enhancement of the diagnosis and treatment of heart diseases. subsequent studies will strive to continue rectifying these techniques and focus on including real-time data feed in order to maintain and improve the forecasting accuracy. © 2024 IEEE.

关键词： Diseases

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A Hybrid-sFLA-based Hyper-Parameter Tuning Algorithm in svR for Exchange Rate Prediction

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sN computer science 2024年第3期5卷 285页

作者： Halder, Tanmoy Ganguly, souvik Mukhopadhyay, somnath Chaudhuri, Tamal Dutta Computer Application Dr. B. C. Roy Engineering College Jemua Road West Bengal Durgapur 713212 India Computer Science Sikkim University Samdur Sikkim Gangtok 700047 India Bengal Economic Association Raja S. C. Mallick Road West Bengal Kolkata 700047 India

This paper proposes a hybrid machine learning-based approach to forecast the exchange rate between the Indian Rupee and the Us dollar. The prediction of the exchange rate is carried out by support vector regression (svR) and a hybrid-shuffled frog leaping algorithm (HsFLA). svR predicts the exchange rate, whereas the hybrid-sFLA is used to tune the hyper-parameters. Hybrid-sFLA is an improvement over sFLA where random movement of particles is carried out using levy flight distribution. The proposed work has been compared with state-of-the-art hybrid prediction models that have applied different meta-heuristic algorithms. To measure predictive efficiency, root mean square error, mean absolute percentage error, Theil’s U, and average relative variance have been used, and the proposed HsFLA outperformed the other methods. © The Author(s), under exclusive licence to springer Nature singapore Pte Ltd 2024.

关键词： Exchange rate Hybrid-shuffled frog leaping algorithm (HsFLA) Memetic algorithm svR

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Applying Machine Learning to Enhance COvID-19 Prediction and Diagnosis of COvID-19 Treatment Using Convalescent Plasma

Applying Machine Learning to Enhance COVID-19 Prediction and...

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International Conference on Data Analytics, Intelligent Computing, and Cyber security, ICDIC 2020

作者： Kongala, Lavanya shilpa, Thoutireddy Reddy Madhavi, K. Ghantasala, Pradeep Kallam, suresh Department of Computer Science Vignan Nirula Institute of Technology and Science for Women Andhra Pradesh Guntur India Department of CSE B V Raju Institute of Technology Telangana Narsapur Medak India Department of CSE Sree Vidyanikethan Engineering College Tirupati India Chitkara University Institute of Engineering and Technology Punjab Chandigarh India

ISBN: (纸本)9789811941610

The Coronavirus 2 relentless discriminating Respiratory syndrome, the source of coronavirus syndrome (COvID-19), has sparked a universal fitness catastrophe. so far, there is no such thing as approved prophylaxis solutions for the ones who were revealed to neither sARs-Cov-2 nor therapies for individuals who have acquired COvID-19. Impervious, i.e., "convalescent" plasma relates toward plasma obtained as of persons, subsequent infection decree, and antibody production. Flaccid supervision of antibodies throughout Convalescent plasma transfusion can happen to provide Just for the short term policy on behalf of giving instantaneous resistance headed for liable Participants. In COvID-19 convalescent plasma was also used epidemic;It is limited in China records advise scientific detriment, together with radiological motion, viral load diminution, and enhanced endurance. Internationally, blood centers have a robust infrastructure for storing and building a catalog of convalescent plasma to congregate increasing stipulate. © 2023, The Author(s), under exclusive license to springer Nature singapore Pte Ltd.

关键词： COvID-19

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An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier

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International Journal of Cognitive Computing in engineering 2021年 2卷 40-46页

作者： Kumari, saloni Kumar, Deepika Mittal, Mamta Department of Electronics and Communication Engineering Bharati Vidyapeeth's College of Engineering New Delhi India Department of Computer Science & Engineering Bharati Vidyapeeth's College of Engineering New Delhi India Department of Computer Science & Engineering G B Pant Govt. College of Engineering New Delhi 110020 India

Diabetes is a dreadful disease identified by escalated levels of glucose in the blood. Machine learning algorithms help in identification and prediction of diabetes at an early stage. The main objective of this study is to predict diabetes mellitus with better accuracy using an ensemble of machine learning algorithms. The Pima Indians Diabetes dataset has been considered for experimentation, which gathers details of patients with and without having diabetes. The proposed ensemble soft voting classifier giv.s.binary classification and uses the ensemble of three machine learning algorithms viz. random forest, logistic regression, and Naive bayes for the classification. Empirical evaluation of the proposed methodology has been conducted with state-of-the-art methodologies and base classifiers such as Adaboost, Logistic Regression,support vector machine, Random forest, Naïve bayes, bagging, Gradientboost, XGboost, Catboost. by taking accuracy, precision, recall, F1-score as the evaluation criteria. The proposed ensemble approach gives the highest accuracy, precision, recall, and F1_score value with 79.04%, 73.48%, 71.45% and 80.6% respectively on the PIMA diabetes dataset. Further, the efficiency of the proposed methodology has also been compared and analysed with breast cancer dataset. The proposed ensemble soft voting classifier has given 97.02% accuracy on the breast cancer dataset. © 2021

关键词： classification Diabetes ensemble Machine Learning soft voting

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Handwritten Text Recognition Using Deep Learning Techniques

Handwritten Text Recognition Using Deep Learning Techniques

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IEEE International Conference on engineering Education: Innovative Practices and Future Trends (AICERA)

作者： L. Navya MD.Farhan Ali K.Pavan sai K. shyam Alabazar Ramesh Computer Science and Engineering B V Raju Institute of Technology Narsapur Medak(D) Telangana(S)

“HANDWRITING RECOGNITION” has generated a lot of attention in the realms of pattern recognition and machine learning due to its applicability in a variety of disciplines. both optical character recognition (OCR) and hand-written character recognition (HCR) have a defined operation sphere. In the near future, character recognition technology may be essential for exercising and digitising paper documents in order to create a paperless environment. This action categorises each handwritten word in order to convert handwritten notes into digital form. Input text or photos are directly identified by handwriting; many automated process systems also look at these materials. Numerous sorts of handwritten characters, such as integers, figures, cursive notation, symbols, and scripts in various languages have emerged as a result of the development of handwriting. In multitudinous situations where it's necessary to exercise large amounts of handwritten data, analogous as the identification of addresses and postcodes on envelopes, the interpretation of amounts on bank checks, document analysis, and hand verification, automatic recognition of handwritten text can be truly helpful. therefore, a computer is demanded in order for document processing to be as simple as possible.

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