Invited Speakers



Prof.Dr.John Wang

Dept. of Information Management & Business Analytics
School of Business Montclair State University, USA
E-mail:wangj@montclair.edu


John Wang, Ph.D, works in the Department of Information Management and Business Analytics at Montclair State University, USA. Having received a scholarship award, he came to the USA and completed his PhD in operations research from Temple University. Due to his extraordinary contributions, Prof. Wang has been honored with two special range adjustments in 2006 and 2009 respectively.  He has published over 100 refereed papers and more than ten books. He has also developed several computer software programs based on his research findings.
He is the Editor-in-Chief of Int. J. of Information Systems and Supply Chain Management (www.igi-global.com/ijisscm) and International Journal of Applied Management Science (www.inderscience.com/ijams). Also, he is the Editor of Encyclopedia of Business Analytics and Optimization (five-volume), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (six-volume) and the Editor of the Encyclopedia of Data Warehousing and Mining, 1st (two-volume) and 2nd (four-volume). His long-term research goal is on the synergy of operations research, data mining and cybernetics.


Prof.Dr. Kevin Deng is a distinguished professor and has served as Executive Director of Automotive Research Institute of Jilin University since 2010. Prior to that, he had worked for General Motors R&D Center in USA as a senior researcher since 1996.
He was a three-time recipient of the “Charles McCuen” Award, the highest research award in General Motors, and a twice-recipient of the `Boss' Kettering Award, the most prestigious award in GM for technical invention and innovation. He briefly served as an acting director of Hong Kong Automotive Parts & Accessories R&D Center in 2010. Currently he serves as the Editor in Chief of International Journal of Vehicle Autonomous Systems (http://www.inderscience.com/jhome.php?jcode=IJVAS) and Associate Editor of International Journal of Vehicle Design (http://www.inderscience.com/jhome.php?jcode=ijvd), and was the associate editor of IEEE Transaction on Vehicular Technology (http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=25). He was also the Chair of the Transportation Track of 2010-2016 IEEE Vehicular Technology Conferences respectively, and Technical Program Chair of FISITA on Chassis Systems and Integration Technology, etc.
He holds numerous patents and is the authors/co-authors of over 100 publications in international journals and conferences. He is also invited keynote speakers of numerous conferences and forums worldwide. His primary research interests are in electric and intelligent vehicles, dynamics and controls, and modeling and simulation technologies, etc.





Prof.Dr.Nilanjan Dey

Department of Information Technology,

Techno India College of Technology,

Kolkata, INDIA.

E-mail:  neelanjandey@gmail.com

 

Nilanjan Dey, PhD., is an Asst. Professor in the Department of Information Technology in Techno India College of Technology, Rajarhat, Kolkata, India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization Of- Sgientifig And Engineering Unions, BULGARIA, Associate Researcher of Laboratoire RIADI , University of Manouba, TUNISIA. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US , International Journal of Rough Sets and Data Analysis (IGI Global), US, Series Editor of Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, Regional Editor-Asia of International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience and Associated Editor of International Journal of Service Science, Management, Engineering, and Technology, IGI Global. His research interests include: Medical Imaging, Soft computing, Data mining, Machine learning, Rough set, Mathematical Modeling and Computer Simulation, Modeling of Biomedical Systems, Robotics and Systems, Information Hiding, Security, Computer Aided Diagnosis, Atherosclerosis. He has 8 books and 160 international conferences and journal papers. He is a life member of IE, UACEE, ISOC etc.

https://www.researchgate.net/profile/Nilanjan_Dey3

 

  Title: Bio-inspired Algorithms in Medical Information Hiding for Tele-monitoring


       Widespread use of wireless communication as well as telemedicine necessitates the demand for copyright protection of multimedia. Information required for detection of diseases is conveyed through medical images. Authentication is very significant in validating a medical content in the domain of telemedicine; however, there are many challenges. Any kind of misrepresentation can result in flawed diagnosis. However, for authenticity and security of data, a small amount of distortion can be ignored. Thus, accurate verification is paramount, and any misuse of personal information may have serious consequences. One of the effective techniques for secure information communication and transfer is watermarking. The watermarked image/signal of the individual is then transmitted through a communication channel.

         Hence, achieving a watermarking technique with an insignificant amount of distortion in bio-medical information is an exigent task. Watermarking requires embedding of diagnostic and health care information accurately without affecting the medical image or misuse of e-consultation. Medical information authentication is performed by embedding the ownership data within the content is more trustworthy than the classical method of transmitting the content individually without any ownership data.

There are numerous metrics to measure the effectiveness of the used watermarking algorithm. The most significant two requirements are watermark robustness and watermark imperceptibility. Though these two requirements are all very desirable, they conflict with each other and some tradeoff must be compromised. Additionally, depending upon the texture information and the image size, the watermarking embedding factors vary from one cover image/signal to another. To optimize the level of robustness and perceptibility of the watermarking technique, selection of an optimum set of embedding factors is very essential.

Thus, bio-inspired techniques can be employed for acquiring the optimized watermarking algorithm. In the fields of information hiding researches employed several types of bio-inspired computing, such as Ant Cuckoo Search (CS), Colony Optimization (ACO), Bee Algorithm (BA) and Firefly Algorithm (FFA). Consequently, it is required to design appropriate embedding factors for these optimization algorithms. With the properly designed selected embedding factors, bio-inspired computing can be helpful to the design of watermarking algorithm. The optimal scaling factors optimized by the used bio-inspired algorithm can be sent through some secret communication channel. Then, in the recipients end, the gray/binary hospital logo and the electronic patient report (EPR) are extracted from the watermarked image/signal.

In this talk, a comprehensively study the behavior of some well-established watermarking algorithms (transformation domain) for the preservation of diagnostic parameters in optimization framework is discussed. A secure and strong authentication system for an efficient and secure medical information watermarking using well-known bio-inspired algorithms, namely CS and FA are used to embed multiple medical data within a biomedical image in an optimized way are conducted. Additionally, watermarking based Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) performance is compared to the CS and FA based algorithms for watermarking. Furthermore, the talk will reported how the proposed optimized scale factors  can be utilized along with, two mathematical measures for the computation of the devalorization of diagnostic parameters caused as an effect of watermarking, namely the diagnostic devalorization (DDsystem) and diagnostic preservation (DPsystem) for effective watermarking. Moreover, two different sets of watermarking algorithms, namely: two correlation-based (binary logo hiding) and two singular value decomposition (SVD)-based (gray logo hiding) watermarking algorithms, as used for embedding ownership logo are conducted. The talk will clarify how the proposed optimized watermarking algorithm can have minimum effect on the diagnostic parameters.

The talk highlights a novel perception in understanding the watermarking based on bio-inspired optimization approach to alleviate scalability, communication and security for medical images transmission. Finally, the talk will discuss some of the future trends in watermarking using hybrid bio-inspired optimization algorithms.












Advances in Intelligent Systems and Computing(ISSN: 2194-5357)
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