Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system. © Published under licence by IOP Publishing Ltd.

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Department of Information Technology

School of Information Technology and Engineering

Vellore Campus

School of Computer Science and Engineering

VIT Unitversity

Fulltext

IOP Conference Series: Materials Science and Engineering

Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

Now a days, every part of country try to take care of the health status of its public. There comes a process called health examination, which will predict health condition of the people. In this process the overall health records is merged into a single document and according to the data the prediction of risk will be calculated. Here we are using two types of data called real and synthetic, the real data comes under the data which we directly get through the hospital records and synthetic means the data which we have collect by ourselves. For the synthetic data we have to examine personally patient’s health records. We may call the synthetic data as unlabeled because we don’t have the exact records. The most important trial here is to predict the unlabeled one. This type of data-set is unique as it describes the person’s health that is fluctuating i.e. good health to worst. In this paper we try to show the prediction of risk for the patient, whether the patient is good in health or they require some precaution. For this application we used an algorithm which is designed to detect the situation in process. Semi supervised is the main method for the entire application. © 2017 Published by Oriental Scientific Publishing Company.

Department of Software and Systems Engineering

Biomedical and Pharmacology Journal

Risk prediction to examine health status with real and synthetic datasets

The expanding of information and data in this period builds the age of information science instruments. The majority of the business needs a suggestion framework which have been utilized by a great many clients. Step by step, the measure of clients, items and data has developed quickly, yielding the enormous information investigation issue for benefit recommender frameworks. Thus, general recommender frameworks regularly have a few detriments like versatility and productivity when handling or investigation of this information on a substantial scale. To keep away from these, another suggestions framework utilizing Hadoop condition is actualized in Apache Hadoop utilizing MapReduce worldview for Bigdata. Apache Hadoop is an open structure for distributed preparing frameworks can process substantial volumes of information. It can be utilized for disconnected handling and can be reasonable for extensive databases. Import information onto the cutting-edge databases like HBase and upgrade its execution. Proposed Framework have awesome change in execution contrasted with general devices. In this paper, we have a tendency to propose a totally one of a kind suggestion strategy which incorporates information on regular writer relations between articles (i.e., 2 articles with steady author(s)). © IAEME Publication.

Department of General Management

VIT Business School

International Journal of Mechanical Engineering and Technology

A case study on coactive subject modelling for acclaiming technical articles

The objective of ensuring anytime and anywhere networking services for collaborative and group-oriented applications can be realised with the concept of Mobile Ad Hoc Networks (MANETs) due to its certain inherent characteristics such as self-organizing, infrastructure-less setup, and little or no requirement of planning and ease of deployment. On the other hand, some other inherent characteristics of MANETs such as dynamic topology, limited resource constraints, open wireless medium for communication, lack of central administration, multi hop communication, etc. demands some emphasis about security for group communication. Also internal as well as external security attacks are possible. To tackle this issue significant research has been carried out in recent years but most of the schemes use the cryptographic keying material. So the key management takes place a vital starring role. An efficient scalable and secure group key management framework for MANETs is an ongoing hot research area. The purpose of this paper is to give the survey about group key management goals, state of the art frameworks, discuss their pros and cons, and also future challenges for young research community in the context of MANETs. © 2016, International Journal of Pharmacy and Technology. All rights reserved.

International Journal of Pharmacy and Technology

A survey on group key management frameworks for secure group communication in mobile Ad Hoc networks

Spontaneous group communication can be attained by deploying Mobile Ad Hoc Networks (or MANETs). The limitations thrown by these networks, motivate the necessity of a group key management framework to secure data traffic. In this context, significant research work done in the last decade and proved that the trust based frameworks deliver better performance than others. Trust value can be evaluated based on direct and indirect interactions with other nodes in the network. The threshold trust value does binary classification about a node is genuine or fake (misbehavior) and further communication includes or excludes. However, in many automated systems, the result for a given input cannot be just categorized as binary output. Instead of a binary, it is more spontaneous and natural to use a fuzzy set based classification which gives the degree of genuineness. To realize this concept, we propose a reliable group key management framework by adding fuzzy logic rules in this paper. The clustering scheme with Fuzzy classifier aids, to eliminate the pretended nodes over a span of time in order to evade internal attacks. Moreover, it saves the energy of each node due to lightweight framework and less key management overhead. Our simulation outcomes prove that our method is more reliable compared to existing frameworks.

International Journal of Intelligent Engineering and Systems

A Reliable Group Key Management Framework Using Fuzzy Logic for MANETs

This study was aimed to develop the QR code based U learning materials tool. The tool is used by teachers to provide the class materials to the students and this material will encourage the students for their studies. The materials provided are like context aware materials. The students learn the whole content deeply and easily understandable way by providing the videos images for the concept so that they can understand very well. This tool which gives interest to the teachers to upload the materials and also Interest to the students to learn. The materials provided by the teachers using the tool is available offline also to the students. © 2016,International Journal of Pharmacy and Technology. All rights reserved.

Creating trusted learning by using QR based U learning system

Instant collaborative group communication can be achieved by deploying Mobile Ad Hoc Networks (or MANETs) without any pre-plan and pre-existing infrastructure setup. However, the curbs thrown by these networks, motivate the necessity of a group key management framework to secure data traffic. In this context, significant research work done in the last decade and proved that the trust based frameworks deliver better performance than others. In MANETs, trust quantified as the belief held by a node about another node. It is evaluated based on the assessing node direct experiences with assessed node itself, if they are neighbors and recommendations from remote nodes in the network with which assessed node has a direct experience, if they are remote. However, the framework based on recommendations by other nodes in the network might ultimately lead to system failure due to the menace of unfair recommendations by selfish and malicious nodes. Lying and on-off attacks on the system are such type of attacks. This motivates us to work on a framework which is immune to aforesaid attacks and should be lightweight due to node's has limited computing resources. We propose a framework which scrutinizes dishonest recommendations based on the trust threshold value of remote nodes, distance from mean of trust recommendations and by maintaining a history of recommendations. Our simulation outcomes prove that proposed framework can deliver better network performance and resistance to lying and on-off attacks.

Mitigate Lying and On-Off Attacks on Trust Based Group Key Management Frameworks in MANETs

Bio-data analysis deals with the most vital discovering problem of similarity search and finding relationship among bio sequences and structures. In this paper, we are trading the problem of discovering the most recurrently occurring patterns in a given DNA or protein sequence. Several on hand tools need the user to spell out gap constraints in advance in turn to find specific patterns. Practically it is not possible for the user to provide the gap constraints. So the need arises of budding an algorithm to obtain the patterns easily on its own without the need of user intervention in the form of mentioning of gap constraints. We have got two analytical methods to find out the recurrent subsequences and guesstimate the maximum support for data with complexity O(|T|.Sup) where |T| stands for text sequence length and Sup represents the number of occurrences of the pattern. We are proposing an altered version of the previously proposed algorithm with complexity O(|T|). © 2016, International Journal of Pharmacy and Technology. All rights reserved.