Computational Network Application Tools for Performance Management (eBook, PDF)

Redaktion: Pant, Millie; Banerjee, Chitresh; Basterrech, Sebastián; Sharma, Tarun K.

• Format: PDF

Produktbeschreibung

Discusses recent theoretical and practical issues in the field of computational networks

Highlights the latest advances using intelligent technology approaches

Addresses challenging issues like enhancing system efficiency, performance, and assurance management

Offers guidance and suggests best practices for addressing performance issues in computational network applications

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Produktdetails

• Verlag: Springer Nature Singapore
• Seitenzahl: 267
• Erscheinungstermin: 18. Oktober 2019
• Englisch
• ISBN-13: 9789813295858
• Artikelnr.: 57938656

Autorenporträt

Dr. Millie Pant is Associate Professor at the Department of Applied Science & Engineering., IIT Roorkee, India. She has published over 180 research papers and has edited a number of Springer Conference Proceedings volumes. She is Associate Editor, Guest Editor and Reviewer for various Springer and Inderscience journals and IEEE Transactions. She has served as General Chair, Program Chair, Session and Track Chair at numerous national & international conferences, and has delivered guest lectures at various leading national and international institutions. She has been involved in international collaboration with MIRS Lab, USA; Liverpool Hope University, UK; and Université Paris-EstCréteil Val-de-Marne, Paris, France. Dr. Tarun Kumar Sharma is an Associate Professor at Amity University Rajasthan, India. He holds a Ph.D. in Soft Computing from IIT, Roorkee, and has published over 90 research papers. He has served as General Chair, Program Chair, Track Chairin the SoCTA, SoCPros Conference Series. He has edited a number of Springer Conference Proceedings volumes. He is Associate Editor, Guest Editor and Reviewer for various Springer and Inderscience journals and IEEE Transactions. He has delivered guest lectures at various leading national and international institutions. He is member of IET, IANEG, CSTA, and MIRS Lab. Dr. Sebastian Basterrech is an Associate Professor at the Department of CS, Faculty of Electrical Engineering, Czech Technical University, Prague, He has 70+ research publications to his credit. He is Associate Editor, Guest Editor and Reviewer Springer and Inderscience journals and IEEE Transactions. He has acted as Program Chair and Technical Chair at numerous national & international conferences, and has made valuable contributions in areas related to quasi-Newton optimization, random neural networks, reservoir computing, neural computation & soft-computing techniques. Dr. Chitresh Banerjee is an Assistant Professor at Amity University, Rajasthan, India. He has published over 60 research papers and has also worked as Executive Officer on the Board of Studies at The Institute of Chartered Accountants of India (Set up by an Act of Parliament), New Delhi.  He is member of 15 international societies and associations. Under the Institute-Industry linkage program, he delivers expert lectures on various themes related to IT. He has authored several books, and has acted as Editor, Associate Editor, Guest Editor and Reviewer for numerous national and international journals and conference proceedings.

Inhaltsangabe

Performance Enhanced Hybrid Memetic Framework for Effective Coverage Based Test Case Optimization.- An Optimization Procedure for Quadratic Fractional Transportation Problem.- A Nature Inspired PID like Fuzzy Knowledge Based Fractional Order Controller for Optimization.- Neuro-Fuzzy-Rough Classification for Increasing Efficiency and Performance in Case-Based Reasoning Retrieval.- Better Performance of Human Action Recognition from Spatiotemporal Depth Information Features Classification.- Selecting Appropriate Multipath Routing In Wireless Sensor Networks for Improvisation of System's Efficiency and Performance.- A Classification of ECG Arrhythmic Analysis Based on Performance Factors using Machine Learning Approach.- A Time Efficient Semi Automatic Active Contour Model of Liver Tumor Segmentation from CT Images.- Denoising 1d Signal Using Wavelets for Signal Quality Enhancement.