Atjaunināt sīkdatņu piekrišanu

E-grāmata: Proceedings of International Conference on Data Science and Applications: ICDSA 2021, Volume 2

Edited by , Edited by , Edited by , Edited by
  • Formāts - EPUB+DRM
  • Cena: 237,34 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2021), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from April 10 to 11, 2021. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

Chapter
1. Feature Selection using Multiple Ranks with Majority Vote
Based Relative Aggregate Scoring Model for Parkinson Dataset.
Chapter
2.
Performance Enhancement of Fractional PI^ D^ Controllers using Modified
Grey Wolf Optimization.
Chapter
3. Evaluation of Intent Classification
Models on Frequently Asked Railway Queries.
Chapter
4. On Cost Analysis of
New Crossbar Interconnection Network.
Chapter
5. A Review on Pattern
Recognition based Retinal blood vessels extraction technique to detect
Diabetic Retinopathy (DR).
Chapter
6. Multiband Reconfigurable Antenna
Design with Frequency, Polarization and Pattern diversities.
Chapter
7.
Issues and Framework of Rules for Resolving Anaphora in Marathi Text.-
Chapter
8. Investigation on Customer Churn Prediction using Machine Learning
Techniques.
Chapter
9. Key object classification for Activity Recognition in
tennis using cognitive approach in Mask RCNN.
Chapter
10. BioGamal Privacy
Preserving Public Auditing for Cloud Computing.- Chapter
11. Analysis of
Intelligent Fuzzy Logic MPPT for Hybrid PV-Wind Energy System.
Chapter
12.
Fusion Based Feature Extraction Approach for Recognition of Handwritten
Devnagari Numerals.
Chapter
13. Analysis of independence and Clustering
pattern of students in adopting MOOCs.
Chapter
14. Enhancing Monitoring in
Online Exams using Artificial Intelligence.
Chapter
15. Emergent use of AI
and Social Media for Disaster Management.
Dr. Mukesh Saraswat is Associate Professor at Jaypee Institute of Information Technology, Noida, India. Dr. Saraswat has obtained his Ph.D. in Computer Science and Engineering from ABV-IIITM Gwalior, India. He has more than 18 years of teaching and research experience. He has guided 02 Ph.D. students and more than 50 M.Tech. and B.Tech. dissertations and is presently guiding 05 Ph.D. students. He has published more than 40 journal and conference papers in the area of image processing, pattern recognition, data mining, and soft computing. He was the part of successfully completed DRDE-funded project on image analysis and is currently running two projects funded by SERB-DST (New Delhi) on Histopathological Image Analysis and Collaborative Research Scheme (CRS), under TEQIP III (RTU-ATU) on Smile. He has been an active member of many organizing committees of various conferences and workshops. He was also Guest Editor of the journal of Swarm Intelligence. He is Active Member of IEEE, ACM, CSI Professional Bodies. His research areas include image processing, pattern recognition, mining, and soft computing. 





Sarbani Roy is Professor in the Department of Computer Science and Engineering, Jadavpur University, Kolkata, India. She received her Ph.D. degree in Engineering from Jadavpur University in 2008. She was awarded Fulbright-Nehru Senior Research Fellowship in 20132014, and she joined the research program at University of North Carolina, Charlotte, USA.  Her research interests include cloud computing, wireless sensor networks, IoT, social network analysis, and data science. She has published around 130 research papers in international journals, conference proceedings, and book chapters. She has served on the technical program committees of various international conferences and has organized many international conferences and workshops. She is Senior Member of IEEE. 





Chandreyee Chowdhury is Associate Professor in the Department of Computer Science and Engineering at Jadavpur University, India. She has received M.E. in Computer Science and Engineering in 2005 and Ph.D. in 2013 from Jadavpur University. Her research interests include IoT in health care, indoor localization, and human activity recognition. She was awarded Post Doctoral Fellowship by Erusmus Mundus in 2014 to carry out research work at Northumbria University, UK. She has served as the technical program committee members of many international conferences. She has published around 90 papers in reputed journals, book chapters, and international peer-reviewed conferences. She is Member of IEEE and IEEE Computer Society. 





Amir H. Gandomi is Professor of Data Science and ARC Discovery Early Career Research Award (DECRA) Fellow at the Faculty of Engineering and Information Technology, University of Technology Sydney. Prior to joining UTS, Prof. Gandomi was Assistant Professor at the School of Business, Stevens Institute of Technology, USA, and distinguished Research Fellow in BEACON center, Michigan State University, USA. Prof. Gandomi has published over two hundred journal papers and seven books which collectively have been cited more than 17,000 times (H-index = 60). He has been named as one of the most influential scientific mind and highly cited researcher (top 0.1%) for four consecutive years, 2017 to 2020. He also ranked 18th in GP bibliography among more than 12,000 researchers. He has served as an associate editor, editor and guest editor in several prestigious journals such as AE of SWEVO, IEEE TBD, and IEEE IoTJ. Prof Gandomi is active in delivering keynotes and invited talks. His research interests are global optimization and (big) data analytics using machine learning and evolutionary computations in particular.