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;

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MIT World Peace University

Engineering and Technology

With advances in sequencing technologies, large amounts of biological data is easily accessible for research. Advanced techniques to extract biologically relevant knowledge from this data have gained importance. In this paper, we discuss the computation based disease associations that infer human diseases. The biological knowledge of diseases dictates associations between diseases and biological molecules like genes, miRNAs and proteins as well as the associations between diseases and pathways and phenotypes. It is essential to model and represent this knowledge in a computational form with minimal loss of biological context. Based on biological assumptions and statistical analysis, samples of (disease) affected and normal individuals are compared to generate a hypothesis about the disease as depicted by disease associations. We survey computation based disease associations supported by internal interactions i.e interactions between various biological molecules as well as external interactions i.e interactions between the biological molecules and external factors like environment and drugs.

School of Computer Engineering & Technology

World University root node

Proceedings Iwbbio 2014: International Work-Conference on Bioinformatics and Biomedical Engineering, Vols 1 and 2

Computation Based Disease Associations in Disease Inference

International Journal of Computer Applications

Feature-based Comparison of iSCSI Target Implementations

The automobile sector requires continuous progress in the development of 'Starter Motor' by innovative approaches, although significant progresses were made in the past. Development of Starter Motor has made it possible to start the engine by electrical means instead of doing it manually. The outstanding features of this motor are they can produce the maximum starting torque to crank the engine. In this case, we use electrical energy and convert it to mechanical energy in order to start the engine in motor vehicles. As the starter motor is mounted near the engine; vibrational disturbances produced due to either uneven road conditions or engine vibrations or both hampering the performance of starter motor which may result in breaking of component of motors. Vehicle will experience vibrations whose values are un-predictable at certain point of time, causing random excitation and random vibrations. Aim of the paper is to perform analytical formulation for the Power Spectral Density function of Starter Motor by treating it as a cantilever beam and to find its response to random vibrations by using Finite Element Analysis (FEA). © (2014) Trans Tech Publications, Switzerland.

School of Mechanical Engineering

Applied Mechanics and Materials

Response of starter motor of an engine subjected to random vibrations

Invisible Data Hiding on Compressed \&amp; Encrypted JPEG2000 Images

IJITEE ISSN-2278-3075

Study of Hadoop Features for Large Scale Data

RESOURCE SCHEDULING USING RESOURCE POOL IN OPENSTACK

With the advent and common usage of high resolution tree gauges, downhole permanent pressure/temperature gauges, and continuous flow measurement, many of the common petroleum engineering calculations and analysis tools for production systems can and have been automated. These include: a) Well Test Analysis, b) Well Productivity, c) Static and Flowing Material Balances and Energy Balances. In addition, the use of rigorous wellbore thermal and phase behavior models allows the two gauges (wellhead and downhole) to be used as a giant differential pressure meter - making it possible to calculate gas rates and water cuts independently of the flow measurements, as well as mid-completion bottomhole pressure (BHP). The purpose of this paper is to present the basic physics involved in these calculations/analyses, as well as to discuss the implications that these processes will have on instrumentation selection and on engineering work flows. The crux of the argument for these types of automated systems is that it is much easier for an engineer to check the results than to spend his/her entire day just looking for useful information in the database, then analyzing it (or getting someone else to analyze it). Furthermore, being able to see the "big picture" - seeing what skin, perm, productivity and apparent hydrocarbon reservoir volumes are now and how they have changed with time, allows engineers to make quicker, more accurate decisions. The use of automated analysis also reduces bias - the computer doesn't care what the answer is. This paper will also include several case studies for both oil and gas wells. Copyright 2014, Society of Petroleum Engineers.

School of Petroleum Engineering

Society of Petroleum Engineers - SPE Asia Pacific Oil and Gas Conference and Exhibition, APOGCE 2014 - Changing the Game: Opportunities, Challenges and Solutions

Using the results from automated petroleum engineering calculations to accelerate decision workflows

Radiologist analyzes thousands of mammograms daily and this causes fatigue and eye strain. Out of thousands of cases, not more than 10 have breast cancer tissues and thus an abnormality might not be detected. To assist radiologists in order to detect mammographic abnormalities, computer-aided detection (CAD) algorithms are developed. This work proposes a CAD system which makes use of principal and independent component analysis (PCA and ICA). Classifiers used in this work are support vector machines (SVMs), classifier and artificial neural network (ANN) classifier. SVM or ANN identifies the suspicious regions and classifies them into the labels assigned. PCA which is a necessary pre-processing step for ICA reduces the dimensionality of the input images. ICA extracts the maximum independent features from the reduced data set and then SVM or ANN classifies the test image into normal or malignant. A comparative analysis of the classification accuracy by using ANN and SVM as classifier is done. For both these classifiers, different numbers of principal components are experimented. © 2014 WIT Press.

School of Electronics & Communication Engineering

WIT Transactions on Information and Communication Technologies

Comparison of SVM and ANN classifier for mammogram classification using ICA features

Shale gas is one of the most widely discussed unconventional gas resource with vast potential. With the United States having benefitted immensely from it, other countries are also venturing into it. Drilling horizontal wells and hydraulically fracturing them are two major components of developing a shale gas reservoir economically. With many countries in Europe looking at the possibility of producing gas from shale reservoirs, the practice of hydraulic fracturing (HF) is going to gain even more prominence. However, operationally the procedure to hydraulically fracture a well is very complex, and has many possible situations which can lead to an accident. Some of these accidents may lead to catastrophic consequences, leading to loss of lives. In the industry, there are multiple methods used to classify and quantify risk, based on certain parameters. This paper performs a comprehensive risk assessment for the entire hydraulic fracturing job, from an operational perspective. This is done using industry available techniques. The result of this work is to assess the risk factor achieved from each technique, and check whether each of the methods converges onto a single sub-operation, classifying it as the most risky, with the highest risk ranking. Based on the results, this paper recommends steps to counter the minor but risky situations that may arise due to negligence. The results are compared with an actual fracturing operation on the field. Hydraulic Fracturing Most of the reservoirs being explored today have good porosity but poor permeability. Poor permeability reservoirs do not allow oil and gas to reach the wellbore in sufficient volumes. To increase the flow of oil and gas from the reservoir rock to wellbore in poor permeable reservoirs, fracturing of the wells is deemed necessary. Fracturing may also be used in case of depleted reservoirs, where additional energy and surface area is required for fluids to flow to the wellbore. Fracturing is a complex operation, involving multiple equipments, as shown in Figure 1. Fracturing involves the pumping of fracturing fluid and proppant into a formation at a calculated, pre-defined rate and pressure. These defined conditions result in initiation and development of fractures in the rock formation. In shale gas reservoirs, the low permeability of the reservoir impedes the capacity of gas to flow freely within the formation. Poorer the reservoir, the more advanced the technology and. Copyright © 2014, Society of Petroleum Engineers.

SPE Middle East Health Safety Environment &amp; Sustainable Development Conference and Exhibition

A Comparative Assessment of Quantitative Risk as Applied to Hydraulic Fracturing Operations

The detection of moving object is fundamental to automated video surveillance, object analysis and recognition. It involves the trajectory of an object over time by locating its position in every frame of the video. In this paper we implement a moving object detection method on FPGA. Detection of moving object is a challenging task. In our implementation of the design we used the background subtraction based method. Background subtraction is a method which detects moving objects from reference background image. Experiment is carried out in MATLAB and on FPGA board. © 2014 IEEE.