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

Aphasia is a communication disability that falls under the category of neurological speech disorder. The main cause of the aphasia individual speech impairment damages certain portion of the cerebrum. The aphasic speech impairment ranges from mild level to the extreme level of severity in which the individual will not be able to communicate. The aphasia individuals face difficulties on the different communication categories like some individual have difficulty in formation of the clear and meaningful sentence, some have problem with understanding and some have trouble in the reading process. The aphasic speech impairment experience will be unique for each individual. It purely depends on the portion of the impairment in the cerebrum, position of the impairment in brain, degree of the severity and also individual age factor. This research work focuses on the assessment of speech impairment in the aphasia patients, basically in order to evaluate the communication aptitude of the aphasia individual. The assessment approach is based on the analysis of factors related to speech such as articulation, phonation, prosody and intelligibility. Through the assessment approach, degree of the severity level of patient will be identified through the automatic speech recognition (ASR) methodologies. This work helps the medical examiners namely neurologists and speech therapists to perform the effective speech analysis for the individuals with aphasia speech disorder. © 2020 IEEE.

Department of Computational Intelligence

School of Computer Science and Engineering

Vellore Campus

World University root node

Proceedings of the 3rd International Conference on Intelligent Sustainable Systems, ICISS 2020

A systematic review of machine learning based automatic speech assessment system to evaluate speech impairment

IoT (Internet of Things) become essential role of our day-to-day life, so the number of connected devices with internet is unpredictable rate. These IoT generated data are moved to cloud for computation. Today‘s cloud computing is not suitable for velocity volume and variety of data produced by the IoT devices. Fog computing has emerged to provide the attractive solution to the distributed application of IoT. Overhead traffic is increased as all the requests are sent to the server causing delays that cannot be accepted in many applications. While fog computing reduces data transfer latency, load balancing between fog servers still needs to be addressed for better timing performance. The challenges include a great number of tasks, customer mobility and fog server heterogeneity. To overcome this problem, consolidate fog computing resources so that requests are handled by foglets, and only essential requests for processing are sent to the cloud. Servers are locally installed in each city to manage nearby requests to make efficient use of resources along with load balancing among all servers, resulting in reduced latency and traffic cover head with improved service quality. This paper gives a comprehensive survey of fog computing with comparing other computing paradigms, issues and challenges. © 2019 ETA-Florence Renewable Energies.

Journal of Advanced Research in Dynamical and Control Systems

Survey on fog computing: Issues and challenges

Smart Vehicular Systems prevail at improving the efficiency of vehicular systems; however, the aftereffects of an efficient system are often negated. This chapter focuses on developing a system that identifies a vehicle based on its unique ID using RFID readers. It makes an attempt to integrate the big hub technologies Blockchain and the Internet of Things to develop a viable Smart Vehicular System. The Internet of Things concept is used to maintain a log of the vehicles identified in various parking lots along with the time duration in the corresponding parking space. Blockchain is used to make automatic and secure payments towards parking based on the unique IDs of the vehicle and that of the parking area. The aim of a Smart Contract is to achieve a common parking fee irrespective of places, such as malls, theaters, hospitals, etc., and to reduce waiting time for parking and payment during peak hours. The Smart Vehicular System becomes a part of the Digital India Movement by reducing usage of physical currency notes and promotes the ecosystem by issuing e-receipts. Blockchain and manual transactions based on estimated data provided by the Ministry of Road and Transport were analyzed, and the transaction timing graph was plotted.

Department of Information Security

Department of Analytics

EAI/Springer Innovations in Communication and Computing

Smart vehicular management system using blockchain for internet of connected vehicles

Aphasia is a communication disorder that hinders the ability to express and communicate with society. Aphasia individual can face difficulties in sentence formation, opinions and trouble with pronunciation. In this survey paper, various techniques have been reviewed based on previous researches including diagnosis and treatment. Automatic diagnosis can evaluate the severity level of aphasia disorder. The important feature of this disorder is that it will not affect their intelligence. This motivated to come up with a speech assessment system which will evaluate speech based on acoustic features. Further, speech will classify into Aphasia quotient score (0 - 100). This system will analyse aphasic speech and provides feedback to the patients. This will help them to improve their speaking and reading skills. © 2020 IEEE.

Proceedings of the 4th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2020

AI based Speech Language Therapy using Speech Quality Parameters for Aphasia Person: A Comprehensive Review

A recommender system is an information model that ideally, serves context-aware personalized suggestions and recommendation for an entity that the user might want to use or purchase (e.g., music, movies, and books). This addresses the need to filter and prioritize data into germane information for the user. Traditionally, recommender models follow the two most widely used techniques of Content-Based recommendations and Collaborative filtering. A recommender system should be intuitive and understand contextual references. The model should also exhibit serendipity. Which are too accurate fail in practice since our aim is to generate inclusive and non-intrusive recommendations. This paper presents a roundup of the various recommender models and their prediction techniques, aimed at serving as a basic guideline to the people new to the realm of recommender system and to hopefully empower further research and practice in this field. © 2019 American Scientific Publishers

VIT Unitversity

Journal of Computational and Theoretical Nanoscience

Qualitative Analysis of Models and Issues in Recommender Systems

With the outstanding development in high-speed net technologies, the conception of virtualization and cloud computing has become an additional standard. The cloud framework provides advantageous and on demand access to computing resources over the web. Individual and enterprises can get access to the product resources and equipment, for example, arrange, capacity, server and applications which are found remotely effectively with the assistance of Cloud Service. The tasks/jobs that are submitted to this cloud environment need to be serviced on time exploiting the resources available in order to achieve proper resource utilization, efficiency and lesser makespan. The proposed work surveys a series of currently existing task scheduling algorithms with respect to their characteristics and come up with a new method of real time task scheduling algorithm based on equal resource split. © BEIESP.

Department of Software Systems

International Journal of Innovative Technology and Exploring Engineering

Certain investigations on opulence split algorithm and particle swarm optimization algorithm for task scheduling in a virtualized cloud environment

Aphasia is a neurological speech disorder which impairs the person's ability to understand or express and also reading and writing capability of an Individual will be affected. Aphasia is caused due to stroke, brain trauma, tumor in cerebrum, brain surgery, infection in cerebrum, some neurological diseases. It also affects the language skills of an aphasia individual due to harmness in the section of cerebrum. Individuals with Aphasia face difficulties in sentence framing, analyzing meaning of words, finding correct words to express their ideas, feelings, thoughts and also problem with pronunciation and stammering, all these difficulties greatly affect their personal and professional life. This paper focus on bridging a gap between the individual with Aphasia and the receiver. This motivated us to come up with the Speech Intelligence System which act as an interface for the communication between the individual with Aphasia and the society. Based on the severity of Aphasia, our knowledge-based system will analyze the unstructured words pronounced by the speech disorder person and transformed it to the meaningful prediction Our Speech Intelligence System will interpret speech disorder person's spoken words into text form by matching with the datasets. © 2019 IEEE.

Proceedings of 2019 International Conference on Computational Intelligence and Knowledge Economy, ICCIKE 2019

Speech Intelligence Using Machine Learning for Aphasia Individual

Frequent load fluctuation and set point variations are the major issues in grid connected heavy duty gas turbine power plants. It may affect the stability of the plant and may lead to inevitable shutdown. Dynamic stability analysis of higher order heavy duty gas turbine in real-time environment would be tedious and expensive. Various model order reduction techniques namely clustering technique-Pade approximation (CT-PA), modified clustering technique-Pade approximation (MCT-PA), and Mihailov criterion-Pade approximation (MC-PA) are proposed for identifying the reduced order model of 18.2 MW industrial heavy duty gas turbine with field test parameter. The step response of gas turbine plant against the load disturbance and set point variations is obtained using the reduced order models and compared with that of higher order system. The time domain specifications and error criteria have witnessed that the MC-PA-based reduced order model retains the original characteristics and yields an improved transient and steady-state responses. Therefore, MC-PA-based reduced order model is identified as an effective reduced order model for the higher order gas turbine plant. The proposed reduced order model would be useful for analysing the behaviour of latest derivative speedtronic controlled gas turbine plant. © 2018 John Wiley & Sons, Ltd.

International Transactions on Electrical Energy Systems

Model order reduction of heavy duty gas turbine power plants with field test parameters

The quick development of the Internet surpasses all desires. The investigation and mining of immense sums of web information is confronting a bottleneck in computational power and storage room. Using cloud computing innovation, we can encourage the system access to capable thinking power, stockpiling limit and foundation. Cloud computing can viably take care of the issues by giving an information handling stockpiling focus of high dependability and versatility, which will enhance the capacity to process web information and decrease the necessities of the terminal gadgets. This paper thinks about web mining calculations in a cloud computing platform. The web information mining calculation and the MapReduce programming model are consolidated. We concentrate on the web mining methods, particularly the W-Miner clustering calculation, investigate the mix of web mining calculations and cloud computing innovation and enhance the information mining calculations to adjust to the examination and preparing of mass web information based on cloud computing stages. Our review develops a circulated cloud condition utilizing a Hadoop structure. In the exploratory condition, we dissect the effect on computational execution by setting distinctive piece measure parameters of Prediction accuracy with the number of clusters. Here, the cluster size decides the number that the pending information record is part, and the comparing scale with the measure of Hierarchical Clusters. © 2019 American Scientific Publishers

A Novel Approach for Web Usage Prediction and Recommendation Using Web Session Clustering

Now -a-days health problems has been a major concern and monitoring the patients has become a significant part of various healthcare services. If the vital signals such as blood pressure, ECG, pulse and blood oxygenation of patients are disseminated to the physicians or doctors in real time then the likelihood of saving the patient’s life considerably increases. Thus in this paper VANET technology has been exploited to collect data from the patients and transmit it to the final destination. Here, a hop scheduled data dissemination algorithm has been proposed to disseminate huge amount of medical data to hospitals. Prior to transmission, the medical data are encoded with transmission frequency using polynomial function to allow efficient transmission. Simulations are carried out to analyze the effectiveness of the proposed approach. © 2015, Journal of Pure and Applied Microbiology. All rights reserved.

Journal of Pure and Applied Microbiology

An effective approach for bio-medical data transmission using hop scheduled data dissemination through VANET

Optimization and quality-of-service (QoS) protocols are very important for safety, emergency, and multimedia applications in vehicular ad hoc network (VANET). VANET requires real-time message propagation that is able to deliver data in a timely and accurate manner. For example, considering the case of safety applications, any delay in the message delivery may entrain risky and fatal accidents. Similarly, sending multimedia files and video streams requires a high level of QoS. This paper gives the brief review of various optimization techniques and QoS protocols in VANETs which will help in better understanding of these protocols in VANETs and pave their way to develop a new protocol to overcome the drawbacks of existing protocols. © Springer India 2015.

Advances in Intelligent Systems and Computing

Optimization and quality-of-service protocols in VANETs: A review

This research work gives the potential implementation of Advanced Novel Compact Assistant Sensor Systems with Fuzzy logic, which reduces the road accidents and it also improves the journey of the travellers on road. Road accidents takes thousands of lives every day in India and it becomes a major concern for the government and other regulatory agencies. Vehicular Ad-hoc Network in Intelligent transportation systems (ITS) are advanced applications which, mean to give imaginative services identifying with distinctive modes of transport and traffic management and empower different users to be better informed and make more secure, more coordinated, and "smarter" utilization of transport networks.The impact of intelligent transport system results in decreasing the road accidents. It can be analysed by using theClaim Prediction model in Vehicular Adhoc Networks provides the efficient way in decreasing the road accidents and thereby results in improving the transportation planning and traffic safety programme. © Research India Publications.