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Advances in Data and Information Sciences de Shailesh Tiwari

Advances in Data and Information Sciences: Lecture Notes in Networks and Systems, cartea 1193

Editat de Shailesh Tiwari, Munesh C. Trivedi, Mohan L. Kolhe, Brajesh Kumar Singh
en Limba Engleză Paperback – 27 apr 2025

Observăm că Advances in Data and Information Sciences se deschide cu o resursă valoroasă pentru cercetători: o colecție vastă de date și metodologii derivate din conferința ICDIS 2023, oferind soluții tehnice pentru provocări contemporane din securitatea informației și inteligența artificială. Ca și Anupam Yadav în Proceedings on International Conference on Data Analytics and Computing, editorii distilează experiență reală în principii acționabile, punând un accent deosebit pe validarea modelelor prin studii de caz concrete.

Structura volumului este riguros organizată, ghidând cititorul de la procesarea limbajului natural (NLP) — unde analizăm clasificarea emoțiilor în texte multilingve — până la aplicații medicale și financiare complexe. Apreciem progresia logică a capitolelor, care pornește de la algoritmi fundamentali de învățare automată pentru predicția riscurilor și avansează spre tehnologii de ultimă oră precum computer vision prin Mediapipe și sisteme de asistență pentru persoanele cu deficiențe de vedere folosind VGG16 și LSTM.

În contextul operei editorilor, acest titlu continuă direcția stabilită în Ambient Communications and Computer Systems și Advances in Computational Intelligence and Communication Technology, consolidând abordarea multidisciplinară a echipei coordonate de Shailesh Tiwari. Volumul nu se limitează la teorie, ci oferă o perspectivă tehnică asupra optimizării hiper-parametrilor în modelele de traducere neuronală și a utilizării algoritmilor de optimizare de tip „Whale Optimization” pentru predicția erorilor software. Cele 150 de ilustrații incluse sunt esențiale pentru înțelegerea arhitecturilor de rețele neurale și a fluxurilor de date prezentate.

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Specificații

ISBN-13: 9789819796182
ISBN-10: 9819796180
Pagini: 468
Dimensiuni: 155 x 235 x 24 mm
Greutate: 0.79 kg
Ediția:2025 edition
Editura: Springer
Colecția Lecture Notes in Networks and Systems
Seria Lecture Notes in Networks and Systems

De ce să citești această carte

Recomandăm acest volum profesioniștilor din industria IT și cercetătorilor care au nevoie de implementări practice în AI și Big Data. Cititorul câștigă acces la metodologii testate pentru securitatea tranzacțiilor cu carduri de credit și analiza antrenamentelor sportive prin computer vision. Este un instrument esențial pentru cei care doresc să aplice algoritmi de tip LSTM sau GRU în proiecte reale de procesare a datelor complexe.

Despre autor

Echipa editorială este formată din experți recunoscuți în domeniul științei datelor și comunicațiilor. Shailesh Tiwari și Munesh C. Trivedi au o experiență vastă în coordonarea publicațiilor academice de nivel înalt, fiind responsabili pentru multiple volume în seriile Springer dedicate rețelelor și sistemelor inteligente. Mohan L. Kolhe și Brajesh Kumar Singh completează această expertiză prin specializări în inginerie și tehnologii computaționale. Împreună, aceștia au transformat conferința ICDIS într-un punct de referință pentru comunitatea științifică internațională, facilitând schimbul de idei între mediul academic și cel industrial.

Cuprins

Emotion Classification of Mixed-Source Hindi Language Text Using Deep Learning.- Emotion Classification of Mixed-Source Hindi Language Text Using Deep Learning.- Heart Disease Prediction Using Machine Learning  Algorithms.- Cyber Security Threats Prediction for Credit Card transactions Using Machine Learning Algorithms.- Interpreting Personality Traits in Social Media Images through Visual Question Answering.- A Framework for Speech based Emotion Recognition using Neural Networks.- Real-Time Indoor Workout Analysis Using Computer Vision and Mediapipe.- Automated Image Caption Generator for Visually Impaired using VGG16 and LSTM.- WOAFS: Feature Selection using Whale Optimization Algorithm for Software Fault Prediction.- Time Series Forecasting for Stock Price Movement: Leveraging NLP for Stock Market Prediction.- Optimizing Hyper-Parameters for Sanskrit to English Neural Machine Translation with LSTM and GRU Models.- Advancements in Image-Guided Surgical Procedures: Enhancing X-Ray Images, Cross Marker Classification, and C-Arm Rotation Detection.- Deep Learning Based CNN Model for Classification and Prediction of Leaf Diseases.- Humidity Data Acquisition and Regulation for Optimal Environmental Condition.- AI assisted smart agriculture technique for predicting crop nutrients.- Traffic Sign Recognition and Classification with Convolution Neural Network (CNN) and OpenCV.- User Segmentation with RFM Analysis and K-Means Clustering for Play Store Database via Machine Learning.- Onion Price Prediction Assisted by Exploratory Data Analysis Employing ARIMA Technique for Varanasi.- Revolutionizing Indian Elections: Introducing Blockchain to Ballot Based Voting.- AI Mapping for Rapid Disaster Assessment.- AI Effect On Modern Healthcare System.- Predicting Chronic Kidney Disease Stages Through Ensemble Machine Learning Techniques.- Medical Image Classification: Binary Classification of X-ray Images to Classify Fractures in Bones.- Semantic Parsing of Data Practice Statements in Privacy Policies Using BERT Models.- Research on Security Tests Methods for IoT Devices.- Method of probabilistic identification of Images in solving problems of applied Photogrammetry.- Using Patterns for Autonomous Mobile Robot Control Tasks.

Notă biografică

Prof. Shailesh Tiwari, Ph.D., currently works as a director and professor in Computer Science and Engineering Department, Krishna Engineering College, Ghaziabad, India. He is also taking care of the responsibility of additional director, KIET Group of Institutions, Ghaziabad, India. He is an alumnus of Motilal Nehru National Institute of Technology Allahabad, India. His primary areas of research are software testing, implementation of optimization algorithms and machine learning techniques in various engineering problems. He has published more than 100 publications in international journals and in proceedings of international conferences of repute. He has edited special issues of several Scopus, SCI and E-SCI-indexed journals. He has also edited several books published by Springer. He has published 6 Indian patents as IPRs. He has organized several international conferences under the banner of IEEE, ACM and Springer.
Dr. Munesh Chandra Trivedi having more than 18 years of teaching experience (out of which 12 years post Ph.D.) is currently working with National Institute of Technology, Agartala, Tripura, India, previously. He has successfully filed 60 patents (51 National and 09 International Patents) in Germany, South Africa and Australia. He has also published 12 text books and 148 research papers in different international journals and proceedings of repute. He has also edited 38 books of the Springer Nature. He has also received numerous awards including Young Scientist Visiting Fellowship, Albert Einstein Research Scientist Award, and Best Senior Faculty Award, Outstanding Scientist, Dronacharya Award, Author of Year and Vigyan Ratan Award from different national as well international forum. He has also organized more than 32 international conferences technically sponsored by IEEE, ACM and Springer.
Prof. Dr. Mohan Lal Kolhe is a full professor in smart grid and renewable energy at the Faculty of Engineering and Science of the University of Agder(Norway). He is a leading renewable energy technologist with three decades of academic experience at the international level and previously held academic positions at the world's prestigious universities, e.g., University College London (UK / Australia), University of Dundee (UK); University of Jyvaskyla (Finland); Hydrogen Research Institute, QC (Canada); etc. In addition, he was a member of the Government of South Australia’s first Renewable Energy Board (2009–2011) and worked on developing renewable energy policies. His research works in energy systems have been recognized within the top 2% of scientists globally by Stanford University’s 2020, 2021 matrices. He is an internationally recognized pioneer in his field, whose top 10 published works have an average of over 175 citations each.
Prof. Brajesh Kumar Singh is presently working as a professor and head in Department of Computer Science and Engineering, R.B.S. Engineering Technical Campus, Agra, India, with more than 20 years of teaching experience. He completed his doctorate degree in Computer Science and Engineering from Motilal Nehru National Institute of Technology, Allahabad (UP). His key areas of research are software engineering, software project management, data mining, soft computing and machine learning. He has supervised 02 Ph. D. candidates. Prof. Singh has delivered several invited talks/ key note addresses and chaired sessions in national and international conferences of high repute in India and abroad. He is having collaborative training programs/workshops with IIT Bombay.

Textul de pe ultima copertă

This book gathers a collection of high-quality peer-reviewed research papers presented at the 6th International Conference on Data and Information Sciences (ICDIS 2024), held at Raja Balwant Singh Engineering Technical Campus, Agra, India, on May 24–25, 2024. The book covers all aspects of computational sciences and information security, including central topics like artificial intelligence, cloud computing, and big data. Highlighting the latest developments and technical solutions, it shows readers from the computer industry how to capitalize on key advances in next-generation computer and communication technology.

Caracteristici

Presents research works in the field of data and information sciences Gather the outcomes of the ICDIS 2023, held in Agra, India Offers a reference guide for researchers and practitioners in academia and industry