MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

&nbsp;

MIT World Peace University

School of Electronics & Communication Engineering

Electrocardiogram (ECG) is a non-stationary signal which constitutes a lineal recording that provides an insight into heart's electrical activity. Because Cardio Vascular diseases (CVD) are numbered one as reason of mortality globally, detection of abnormalities in ECG at an early stage is crucial for diagnosis and accordingly the treatment. A system can help the cardiologists in diagnosing the arrhythmia present in a patient. The proposed architecture uses Adaptive Neuro-Fuzzy Inference System (ANFIS) with the input preprocessed with subtractive clustering method to learn fuzzy logic. Five morphological and five statistical ECG features are utilized to determine if the patient's heartbeats are normal or irregular and classify them accordingly. During statistical feature extraction, Principal Component Analysis (PCA) on detail coefficients is implemented for optimization. For classification, four classes of ECG are considered, Left Bundle Branch Block (LBBB), normal, Atrial Premature Contraction (APC) and Paced Beats (PB). The proposed system gives an overall classification accuracy of 97.75%. The overall sensitivity, average specificity and average false prediction ratio obtained are 0.9775, 0.9925 and 0.0075 respectively. © 2017 IEEE.

World University root node

Engineering and Technology

2017 3rd International Conference on Advances in Computing, Communication &amp; Automation (ICACCA)(Fall)

Arrhythmia classification using neuro fuzzy approach

Biometric technologies are the automated procedures for validating and identifying the originality of an individual. The biometric systems for automatic authentication are fingerprint, iris, retina, voice, hand geometry recognition. Nowadays, the retina recognition has received an importance, as the unique characteristics of the retina. In the acquisition method, the retinal images might experience some deformations like a change in background intensity, rotation and scale etc. These troubles may disturb the feature extraction process, as a result of the identification process. The Optical Disc Ring (ODR) is used as a preprocessing method. Subsequently, the Speeded Up Robust Feature (SURF) is employed. It is fast as well as vigorous. Oriented FAST and Rotated and BRIEF (ORB) is also used as a feature extraction process. ORB is efficient, unaffected by noise and rotation invariant. The true acceptance rate for SURF and ORB is 98.148 percent. © 2017 IEEE.

2017 International conference on Microelectronic Devices, Circuits and Systems (ICMDCS)

Retina based biometric identification using SURF and ORB feature descriptors

In today's world, an enterprise user uses quite a number of applications or IT resources which have their own set of credentials. These credentials differ from system to system or applications to applications and needs to be remembered by the particular user. Also, user has to enter the different credentials too again and again whenever re-login to any application is needed. This consumes time and requires unnecessary efforts. This project made use of IBM Security Access Manager Enterprise Single Sign-On (ISAMESSO) and smartphone of the user to automate the above. ISAM ESSO securely manages each user's application credentials and automatically delivers these credentials to the logon screens of various applications when a user launches them. We have enhanced this by integrating the single sign on feature of ISAMESSO with Bluetooth proximity functionality. ISAM ESSO client is installed on laptop. Client's workstation and smartphone communicates via Bluetooth in such a way that, whenever the Bluetooth enabled phone of the user is within the laptop's Bluetooth range and unlock command is send via app, not only the OS get unlocked but using the single sign on feature of ISAMESSO, the different applications which the user was using also gets unlocked. Further, when the user moves out of the vicinity of the laptop/desktop it will get locked automatically together with all the applications. The locking/unlocking facility is made automatic as well as manual. © 2016 IEEE.

2016 IEEE Annual India Conference, INDICON 2016

Single sign on using Bluetooth device

This paper presents design of precision agriculture system infrastructure aiming at a multi-parameter monitoring system using wireless sensor network. Proposed infrastructure is based on low-power Intel’s Galileo Gen-2 platform for monitoring, controlling and decision-making support using Internet of Things (IoT). Collection of different farm field parameters is to be done using sensor nodes deployed in the farmland. Each node is connected wirelessly to the base station for the collection of data using wireless transreciever hardware platform. Data is then fed to the personal computer and displayed on screen, e.g. temperature, humidity, sprinkler water flow and soil moisture. From the collected data, decision-making and controlling action can be taken by the use of Internet of Things.

Springer Singapore Advances in Intelligent Systems and Computing bookseries

Precision agriculture system design using wireless sensor network

Many machine learning softwares are available which help the researchers to accomplish various tasks. These software packages have various conventional algorithms which perform well if the training and test data are independent and identically distributed. However, this might not be the case in the real world. The training data may not be available at one time. In the case of neural networks, the architecture has to be retrained with new data that are made available subsequently. In this paper, we present a novel training algorithm which can avoid complete retraining of any neural network architecture meant for visual pattern recognition. To show the utility of the algorithm, we have investigated the performance of convolutional neural network (CNN) architecture for a face recognition task under transfer learning. The proposed training algorithm may be used for enhancing the utility of machine learning software by providing researchers with an approach that can reduce the training time under transfer learning.

Fulltext

Complex and Intelligent Systems , Springer

A Novel Training Algorithm for Convolutional Neural Network

The aim of this paper is to design a wearable air pollution mapping system for an individual. For this itincludes interfacing some pollution related sensors (CO2, CO and dust sensor) to the user’s body which will constantlymonitor the surrounding air pollution levels and calculate the exact amount of toxic gases inhaled by the userdepending upon the breathing rate of the user. Depending upon these values, the user will be alerted in real time byshowing warnings where pollution level has surpassed the permissible limits. The data will be preserved and lateranalyzed using graphs and diagrams prepared in Excel using Visual Basic. The data analysis will provide the user withhealth prediction i.e. probability of immediate or long term health effects of various poisonous gases or pollutants.

International Journal of Advanced Research in Computer and Communication Engineering

Personal Pollution Exposure Estimates using Pollution Sensors and Health Prediction

Ultrasound Video Quality Enhancement for Analysis of Region of Interest

International Journal of Engineering Science Invention Research & Development

Medical information composed of clinical data, images, videos & other physiological signals, has become an essential part of patients care during screening, diagnostic and treatment phases. Today, a wide range of different image modalities can be found in medical imaging like Ultrasound (US), Computed Tomography (CT), Magnetic Resonance (MRI) and Positron Emission Tomography (PET). Amongst all Ultrasound is a widely used technique as it is non-invasive, non-ionizing, portable, free of radiation risk, gives real time acquisition of internal structure such as heart, kidney, liver, uterus and spleen and relatively inexpensive when compared with other imaging modalities such as MRI and CT

International Journal of Engineering Science Invention Research & Development (IMPACT FACTOR - 2.215) IJESI 2016-06-07ISSN - 2349 6185

Ultrasound Video Quality Enhancement for Analysis of Region of Interest”,

This paper presents texture image segmentation based on the combination of phase correlation and region growing algorithm. Image segmentation is an integral part of image analysis. In image processing different processes are done on images to enhance it at different parameters. These processes are not directly applied on images but before that it needs to be segmented or divided in smaller parts called pixels or small blocks of pixels. So segmentation becomes an integral and basic part in image analysis and error at this stage can influence other processing techniques. As in this paper three algorithm are developed on two different dimensions for two class images. Phase correlation is used to find similarities in the windows of pixels which are of size 16x16. Similar and different pixel or pixel blocks are decided by the threshold value of the phase correlation result to find out which pixel falls into the same segments and which is not.

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering

Segmentation of Textured Images Using Region Growing and Phase Correlation Algorithm

Smart helmet safety system is the idea that has been developed for the social responsibil-ity towards the society. Recently the number of bike riders has increased so there is over-all increase in the number of motor bike acci-dents. The system assists in reducing major number of accidents. It consists of microcon-troller along with IR and PIR sensors for hel-met authentication followed by alcohol detec-tion with the help of MQ3 sensor. As soon as the bike rider try to start the bike it shall rst authenticate if the person is wearing the hel-met through IR and PIR sensors. Secondly, MQ3 sensor detects the presence of alcohol, if detected the bike wont start. It also detects fall detection through accelerometer. The project focuses on bike rider safety and reduction of accidents which are fatal.