SANTHOSH KUMAR C
@pmctech.org
Assistant Professor CSE
Er.Perumal Manimekalai College of Engineering
C.Santhosh kumar is currently a Researcher , at PMC Tech , is having 10 years of Experience in Teaching. He graduated B.E. from SRM Easwari Engineering College , Chennai , PG Degree from Anna University Regional centre , Coimbatore .Presently he is pursuing his Ph.D. at Anna University, Chennai. His area of interest includes Soft Computing, Machine learning, Semantic web. He published a book"Problem solving and python programming" at Anuradha Publications and "Theory of Computation" at Bonfring publications . He is passionate in learning Soft Computing Techniques . He presented and published 17 research papers in International and National conferences. He is a Professional member of Association of Computing Machinery, Soft Computing Research Society and CSI. He is one of the Computer Science related Tamil Online Tutor under the youtube channel name santhosh kumar Study circle . His channel has 670 subscribers and 1,67,400 views.
EDUCATION
2017-2024 Doctor of Philosophy (I&C),Pursuing Ph.D. at Anna University, Chennai .
2010-2012 Master of Engineering ,M.E.(CSE), Anna University Regional Centre Coimbatore, Anna University Chennai , 2012;First Class.
2006-2010 Bachelor of Engineering ,B.E.(CSE), Easwari Engineering College Chennai, Anna University Chennai , 2010;First Class.
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence
Scopus Publications
Scholar Citations
Scholar h-index
Scopus Publications
M. Ramkumar, S. Syed Jamaesha, M. S. Gowtham, and C. Santhosh Kumar
Springer Science and Business Media LLC
P. Arangarajan, C. Santhosh Kumar, N. Shunmugakarpagam, R. Vijayabhasker, and C. Gayathri
IEEE
S. Vanakovarayan, C. Santhosh Kumar, A. Raj Ganesh, P. Yogananth, T. Ragupathi, and N. Palanivel
IEEE
The Internet of Things plays a prominent role in the development of health applications. Smart gadgets and wireless sensor networks are used to track patients' various health markers in real time. Every day, the number of heart diseases increases at a rapid rate, which makes it very imperative to predict any such diseases in advance. In order to accurately diagnose heart diseases, researchers are utilizing machine learning algorithms, backed up by electronic health data, to develop smart systems. Based on a variety of medical attributes, we employ Machine Learning algorithms to identify potential heart disease in people. This paper presents an IoT- based prediction system for heart disease diagnosis using Logistic Regression (LR) Random Forest (RF)and Support Vector Machines (SVM) to predict and classify patients with heart disease. Ultimately, the aim of our project is to develop a set of modules for tele-monitoring that doctors can employ to diagnose their patients more accurately. This system uses UCI repository datasets for training and testing. Based on comparisons with existing classifiers, the proposed
N. Palanivel, K. Madhan, C. Santhosh Kumar, R. SarathKumar, T. Ragupathi, and Deivanai S
IEEE
Cybersecurity is the large subject matter that connects everything, processes, units and technologies. Network safety is a set of policies and settings. They are the integrity, accessibility and availability of facts and networks. Confidentiality of Software and Hardware Use. Today's community threats are continuously evolving and the surroundings is an increasing number of complex. Similarly, the clever domestic has emerge as a low-security threat. That's why it is so vital to remain secure online. Due to the vulnerability of the clever domestic network, there are purposes in many areas, such as users, locations, data, etc. Some clever units may additionally be lacking from your clever home. The machine has been hardened so that passwords can be scrambled. Unencrypted passwords can be searched on the machine or in the software. The safety of the clever domestic community is pretty high. Prioritize linked gadgets to forestall hackers from gaining access to them. Access to touchy or private data. Failure to do so should put your complete clever domestic community at risk. This learn about builds a mannequin to analyze specific protection problems in clever domestic conversation networks. This lookup wants to use qualitative methods, such as anecdotes. A lookup evaluation was once fundamental to raise out this study. and Other applicable records on the secondary facts series techniques used. Several research have been carried out on the protection threats associated to clever domestic networks and the use of applied sciences derived from block chain technology. Reduce protection troubles and defend your intelligence. Secure your domestic network.
V. Mathavan, P. Sumathi, C. Gayathri, C. Santhosh Kumar, T. Ragupathi, and N. Palanivel
IEEE
Smart Parking and Parking Guidance finding parking methods are in demand in modern megacities. This will reduce traffic, air pollution, driver strain and wasted parking time. This paper presents the design and implementation of an improved version of a CNN based on a parking dataset for finding free parking spaces in parking images. The purpose of this paper is to produce a reliable version with fast generalization that can get information about parking, but it is intended for use with technical cameras that display the number of new parking spaces. This paper provides 94% application accuracy when advertising multiple parking lots. This version also achieved an overall accuracy of 94% while receiving single parking and testicle parking information with a digital camera at an alternative parking lot. Previous reasoning suggests that these pictures should have strong generalizability. These generalizations allow the expert version to be deployed in real parking management structures. It can also serve as the basis for a study to gather new information about parking volumes or add more layers to refine and improve versions.
Santhosh Kumar C. and R. Vijayabhasker
The Electrochemical Society
Web services are used all around the world for commercial purposes. It works majorly by Universal Resource Locators, which are stored in the repository UDDI. The different web service has to be composed for creating new business services. It is time dependent for composing more web services, which is massive. A semantically described WSDL description solves automatic composition of web services. Also with ontological models and languages, such as RDF, OWL, and SWRL, the better automatic discovery, selecting, integration, and composition of services have been done. Service requirements, such as connectivity, quality-of-service properties, correctness, and scalability, need to be satisfied. For achieving these, many evolutionary algorithms will be used for improving quality of service parameters. This paper describes many optimizations algorithms which will be used efficiently in optimizing composition techniques in semantic web.