Aswani Kumar Cherukuri
Dr. Ch. Aswani Kumar is Professor of School of Information Technology and Engineering, Vellore Institute of Technology, Vellore, India. Dr. Ch. Aswani Kumar holds a PhD degree in Computer Science from VIT University, India. He also possesses Bachelor's and Master's Degrees in Computer Science from Nagarjuna University, India. His current research interests are Data Mining, Formal Concept Analysis, Information Security, and Machine Intelligence. Dr. Aswani Kumar has published 60 refereed research papers so far in various national, international journals and conferences. He received Young Scientist Fellowship from Tamilnadu State Council for Science and Technology for his research at Tata Institute of Fundamental Research (TIFR), Bombay during the year 2004. He received The New Indian Express (India's leading English daily newspaper) award for inspiring young teachers 40 under forty. (www.edexlive.com/live-story/2017/may/25/computing-his-teaching-path-515.html).Dr. Aswani Kumar was principal investigator to major research projects sponsored by the Department of Science and Technology, Govt. of India, during 2006 - 2008 and National Board of Higher Mathematics, Dept of Atomic Energy, Govt. of India during 2011-13
Address: Dr. Ch. Aswani Kumar
Professor
Network & Information Security Division,
School of Information Technology & Engineering,
VIT University, Vellore - 632014.
India.
Address: Dr. Ch. Aswani Kumar
Professor
Network & Information Security Division,
School of Information Technology & Engineering,
VIT University, Vellore - 632014.
India.
less
InterestsView All (29)
Uploads
Research Papers by Aswani Kumar Cherukuri
market share and sales. This can result in lower marketing costs in the long-term. India contributes 0.8% of a $600 billion global cross-border e-commerce market. Thus, this is an enormous target segment that exporters can focus to expand their international business. There are numerous advantages of cross-border e-commerce, which will be discussed in detail in this chapter. This chapter discusses the meaning of GDPR, the subjects of GDPR, and the effects of GDPR on individuals and organizations. This chapter also states the impact of GDPR on different fields and technologies. In addition, the major cross-border e-commerce security issues are analyzed, and optimal solutions are discussed.
representing knowledge in cognitive systems. In this
paper, we have adapted conceptual space framework for
prosthetic arm considering its cognitive abilities such as
receiving signals, recognizing and decoding the signal
and responding with the corresponding action in order
to develop a conceptual space of the prosthetic arm.
Cognitive functionalities such as learning, memorizing
and distinguishing configurations of prosthetic arm are
achieved via its conceptual space. To our knowledge,
this work is the first attempt to adapt the conceptual
spaces to model cognitive functionalities of prosthetic
arm. Adding to this, we have made use of different
notion of concept that reflects the topological structure
in concepts. To model the actions of the prosthetic arm
functionalities, we have made use of force patterns to
represent action. Similarly, to model the distinguishing
ability, we make use of the relationship between the
attributes conveyed by adapted different notion of
concept.
problem involves finding the shortest path between the delivery points while simultaneously avoiding stationary obstacles
(for example high raised buildings) and moving obstacles like
other drones. The path needs to be continuously changed based
on the telemetry from other drones or based on the addition of
new way-points. This is major issue in planning problems. Any
algorithm will have to make complex choices like abandoning
shortest paths to avoid collisions. In this paper we propose a
tangent algorithm which chooses paths based on many performance measures like number of obstacles in current path and
the future path and the distance to the next obstacle. The path
has very few sharp turns and the locations of these turns are calculated during the path planning. This solves one of the major
problems for fast-moving fixed wing systems.
The performance evaluation on different environments demonstrates that the algorithm will be particularly faster in case of
sparse obstacles since it always starts first by drawing a straight
line between way-points and if there are no obstacles in the way
then it can exit in a single step.
The performance evaluation on different environments demonstrates that the algorithm will be particularly faster in case of both sparse and dense obstacles.
market share and sales. This can result in lower marketing costs in the long-term. India contributes 0.8% of a $600 billion global cross-border e-commerce market. Thus, this is an enormous target segment that exporters can focus to expand their international business. There are numerous advantages of cross-border e-commerce, which will be discussed in detail in this chapter. This chapter discusses the meaning of GDPR, the subjects of GDPR, and the effects of GDPR on individuals and organizations. This chapter also states the impact of GDPR on different fields and technologies. In addition, the major cross-border e-commerce security issues are analyzed, and optimal solutions are discussed.
representing knowledge in cognitive systems. In this
paper, we have adapted conceptual space framework for
prosthetic arm considering its cognitive abilities such as
receiving signals, recognizing and decoding the signal
and responding with the corresponding action in order
to develop a conceptual space of the prosthetic arm.
Cognitive functionalities such as learning, memorizing
and distinguishing configurations of prosthetic arm are
achieved via its conceptual space. To our knowledge,
this work is the first attempt to adapt the conceptual
spaces to model cognitive functionalities of prosthetic
arm. Adding to this, we have made use of different
notion of concept that reflects the topological structure
in concepts. To model the actions of the prosthetic arm
functionalities, we have made use of force patterns to
represent action. Similarly, to model the distinguishing
ability, we make use of the relationship between the
attributes conveyed by adapted different notion of
concept.
problem involves finding the shortest path between the delivery points while simultaneously avoiding stationary obstacles
(for example high raised buildings) and moving obstacles like
other drones. The path needs to be continuously changed based
on the telemetry from other drones or based on the addition of
new way-points. This is major issue in planning problems. Any
algorithm will have to make complex choices like abandoning
shortest paths to avoid collisions. In this paper we propose a
tangent algorithm which chooses paths based on many performance measures like number of obstacles in current path and
the future path and the distance to the next obstacle. The path
has very few sharp turns and the locations of these turns are calculated during the path planning. This solves one of the major
problems for fast-moving fixed wing systems.
The performance evaluation on different environments demonstrates that the algorithm will be particularly faster in case of
sparse obstacles since it always starts first by drawing a straight
line between way-points and if there are no obstacles in the way
then it can exit in a single step.
The performance evaluation on different environments demonstrates that the algorithm will be particularly faster in case of both sparse and dense obstacles.
Basics of Formal Concept Analysis
Mathematics behind FCA
Knowledge representation using FCA
Formal concepts & concept generation
Attribute implications
Applications
This talk will discuss the potential cyber security related risks and challenges in the smart grid environment.
Greetings.
We are inviting the Chapters for the proposed IET Handbooks on Big Data Analytics jointly edited Dr. Ravi Vadlamani, IDRBT, Hyderabad & Dr. Aswani Kumar, Vellore Institute of Technology, Vellore. This edited 2-volume handbook will present a large spectrum of contributions from methodologies of Big data analytics to applications.
These two volumes will be indexed in Scopus, ISI/Web of Science, INSPEC and Google Scholar.
We solicit chapters from you & your research team.
Also, we request you to publicize this CFC amongst your colleagues, friends, and students. For further details, please see the attached CFC.
Important Dates
1. Submission of the Chapter Proposals: July 31st, 2019.
2. Notification of Acceptance of the Chapter Proposal: August 15th, 2019.
3. Submission of the Full Chapter: October 31st, 2019.
4. Reviews to the authors: December 15th, 2019.
5. Revised Chapter Submissions: February 28th, 2020.
6. Notification of Final Acceptance: March 31st, 2020.
For the proposed chapter, please provide the title and a brief synopsis. For further details and submissions, please contact: iethandbook@gmail.com
i. Theories and developments within FCA
ii. Applications of FCA and
iii. Integrating FCA to other related fields.
During the last three decades, solid mathematical foundations of FCA have attracted scientists to utilize FCA for transforming data into information and finally actionable knowledge. In spite of the research findings available in this field, there are still several underlying issues that are worthy of further investigations. Considering the potential of FCA, this book is intended to serve as a reference collection on the issues, trends and applications of FCA for knowledge representation and reasoning. Whilst providing the in-depth treatment of current research issues and directions, this book will also explain the fundamental aspects of FCA trends such as FCA in fuzzy settings etc. Thus this innovative collection can serve as a basis for learners and a reference for researchers.
Objectives of the book:
· Provides an in-depth analysis on current research, issues and applications of FCA.
· Presents self-contained discussions and rigorous reviews on different flavors of FCA.
· Provides the future research directions and opportunities in FCA.
The International Conference on Computational Aspects of Social Networks (CASoN 2016) brings together an interdisciplinary venue for social scientists, mathematicians, computer scientists, engineers, computer users, and students to exchange and share their experiences, new ideas, and research results about all aspects (theory, applications and tools) of intelligent methods applied to Social Networks, and to discuss the practical challenges encountered and the solutions adopted.
Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. These social network systems are usually characterized by the complex network structures and rich accompanying contextual information. Recent trends also indicate the usage of complex network as a key feature for next generation usage and exploitation of the Web. This international conference on Computational Aspect of Networks is focused on the foundations of social networks as well as case studies, empirical, and other methodological works related to the computational tools for the automatic discovery of Web-based social networks. This conference provides an opportunity to compare and contrast the ethological approach to social behavior in animals (including the study of animal tracks and learning by members of the same species) with web-based evidence of social interaction, perceptual learning, information granulation, the behavior of humans and affinities between web-based social networks. The main topics cover the design and use of various computational intelligence tools and software, simulations of social networks, representation and analysis of social networks, use of semantic networks in the design and community-based research issues such as knowledge discovery, privacy and protection, and visualization.
We solicit original research and technical papers not published elsewhere. The papers can be theoretical, practical and application, and cover a broad set of intelligent methods, with particular emphasis on Social Network computing.
Computational methods such as (but not restricted to):
Neural Networks and Connectionist Models
Evolutionary Algorithms
Fuzzy Logic
Knowledge Management
Multi-valued Logic
Semantic Networks
Rough Sets
Intelligent Agents
Ontologies
Reinforcement Learning
Applications on Social Networks:
Network evolution
Network evolution and growth mechanisms.
Online communities and computer networks.
Information diffusion in social networks.
Detection of communities by document analysis.
Topology of real networks.
Recommendation
Information diffusion in social networks.
Recommendations for product purchase, information acquisition and establishment of social relations.
Impact of recommendation models on the evolution of the social network.
Classification models and their application in social recommender systems.
Advertisement models
Economical impact of social network discovery.
Social advertising.
Use of social networks for marketing.
Search in network
Web page ranking informed by social media.
Search algorithms on social networks.
Collaborative Filtering.
Security
Anomaly detection in social network evolution.
Data protection inside communities.
Crime data mining and network analysis.
Modeling trust and reputation in social networks.
Misbehavior detection in communities.
Network geography
Geographical clusters, networks, and innovation.
Social geography.
International Collaborations in e-Social network.
Web
Automatic discovery and analysis of Web based social networks.
Link Topology and Site Hierarchy.
Web mining algorithms.
Web communities.
Web-Based Cooperative Work.
Evaluation
Test collection.
Benchmark creation.
Measures and methodologies.
Paper submission
Submitted papers should be original and contain contributions of theoretical, experimental or application nature, or be unique experience reports.
Proceedings are expected to be published by:
Advances in Intelligent and Soft Computing, which is now indexed by ISI Proceedings, DBLP. Ulrich's, EI-Compendex, SCOPUS, Zentralblatt Math, MetaPress, Springerlink
Papers maximum length is 10 pages.
- Papers must be formatted according to Springer format (Latex/word) available at: http://www.springer.com/series/4240
Submit your paper at the submission site.
Topics
Soft Computing and Applications (but not limited to):
Evolutionary computing
Swarm intelligence
Artificial immune systems
Fuzzy Sets
Uncertainty analysis
Fractals
Rough Sets
Support vector machines
Artificial neural networks
Case Based Reasoning
Wavelets
Hybrid intelligent systems
Nature inspired computing techniques
Machine learning
Ambient intelligence
Hardware implementations
Pattern Recognition and Applications (but not limited to):
Information retrieval
Data Mining
Web Mining
Image Processing
Computer Vision
Bio-informatics
Information security
Network security
Steganography
Biometry
Remote sensing
Medical Informatics
E-commerce
Signal Processing
Control systems
Proceedings:
All accepted papers fulfilling requirements on quality will be published in the Springer proceedings. It is mandatory that at least one author registers for every paper that is included in the conference proceedings. Proceedings are expected to be published by: Advances in Intelligent and Soft Computing, which is now indexed by ISI Proceedings, DBLP. Ulrich's, EI-Compendex, SCOPUS, Zentralblatt Math, MetaPress, Springerlink. Papers maximum length is 10 pages.
- Papers must be formatted according to Springer format (Latex/word) available at: http://www.springer.com/series/11156
Please follow the link for electronic submission: https://easychair.org/conferences/?conf=socpar2016
Special Issues:
Organizers have successfully negotiated with several International Journals to accommodate special issues on various topics. Expanded versions of SoCPaR 2016 selected papers will be published in Special Issues and Edited Volumes.