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

The Electrocardiogram (ECG) is most widely used techniques to detect cardiac diseases. In this paper we propose ECG signal analysis and classification method using wavelet energy histogram method and support vector machine (SVM). The classification of cardiac arrhythmia in the ECG signal consists of three stages including ECG signal preprocessing, feature extraction and heartbeats classification. The discrete wavelet transform is used as preprocessing tool for signal denoising and feature extraction such as R point location, QRS complex detection. Morphological features extracted from the QRS complex are employed as input to the classifier. Binary SVM is used as a classifier to classify the input ECG beat into four classes i.e. Normal, Left bundle branch block, Right bundle branch block and Premature ventricular contraction. MIT-BIH arrhythmia database is used for performance analysis. The proposed classifier performs well with an average sensitivity of 100%, specificity of 99.66%, positive prediction of 99%, false prediction of 0.0033, and average classification rate of 99.75%. © 2015 IEEE.

School of Electronics & Communication Engineering

World University root node

2015 Communication, Control and Intelligent Systems (CCIS)

QRS complex detection and arrhythmia classification using SVM

Computer-aided diagnosis (CAD) of mammograms assists the radiologists to detect the mammographic mass presence. Since the variability of shapes of such breast masses occurs very frequently, it is more difficult to classify them into benign and malignant stages. One efficient approach to classify them is the fractal analysis by deriving their shape features. Various methods have been proposed for the fractal dimension (FD) computation of region of interest (ROI) in biomedical images. Among those, two methods, namely power spectral analysis (PSA) and differential box counting method (DBCM), are used here for the FD computation of breast contour margins. Fractal analysis by PSA method is a frequency-domain approach which is applied to the one-dimensional (1D) signatures of the two-dimensional (2D) breast mass contours. However, the DBCM model assigns the smallest number of boxes that cover the whole image surface. Finally, a comparative analysis is performed between the above-said two methods which show the PSA method yields better accuracy than the DBCM. © Springer India 2015.

Advances in Intelligent Systems and Computing

Classification using fractal features of well-defined mammographic masses using power spectral analysis and differential box counting approaches

Ultra low permeability rocks such as shales exhibit complex fracture networks which must be discretely characterized in our reservoir models to evaluate stimulation designs and completion strategies properly. The pressure (Darcy’s law) and composition driven (Fick’s law) flow mechanisms when combined result in composition, pressure and saturationdependent slippage factor. The approach used in this study is to utilize pressure-dependent transmissibility multipliers to incorporate apparent gas-permeability changes resulting from multi-mechanism flows in commercial simulators. This work further expounds on the effectiveness of the theory by presenting a descriptive analysis between two commercially utilized numerical simulators. The applicability of dynamic slippage as an effective flow mechanism governing gas flow mechanisms within the computational environment of two different simulators is attempted in this analysis. Results indicate that slippage-governed flow in modelling shale reservoirs should not be ignored.

School of Petroleum Engineering

World Journal of Engineering

Impact of dynamic slippage on productivity of shale reservoirs

The Barnett Shale success in the 90's has led to a significant amount of focused work on fracturing and its related aspects. The work included understanding its nuances, to be able to design the treatments better, and pump them with enhanced efficiency. Production from these completed wells is highly dependent on both the characteristics of proppants being placed, as well as those of the reservoir being treated. Fracturing leads to an interaction between the minerals of the proppants, formation and the fluids. Incompatible chemical interactions between minerals of the proppants, formation and fracturing fluids lead to precipitations which reduce porosity. Under in-situ conditions, these interactions further facilitate the phenomenon of geo-chemical diagenesis as a result of which rapid loss of fracture conductivity is observed. The diagenesis process includes mechanisms such as diffusion, temperature induced dissolution, precipitation in the pore space, along with chemical reactions at the fracture surface. These mechanisms lead to a reduction in the width and hence, the permeability of the created fracture. Proppant pack permeability reduction is presented in this paper through a mathematical model, which simulates fluid-mineral reactions in the created hydraulic fracture. The model involves solving the diffusion and precipitation equations for each component to simulate the changing porosity and permeability over time. These coded partial differential equations are combined with the reactions occurring at the surface. Further, this work studies the impact of this reduction on the productivity of a well completed in shale reservoir, followed by a sensitivity study of critical parameters. This work will help in a better understanding of reactions occurring within the fractures and their effect on the loss of fracture conductivity. With India looking at developing its shale plays, this work also includes possible issues that could affect this development. © Copyright 2015, Society of Petroleum Engineers.

SPE Annual Technical Conference and Exhibition

Shale Gas Productivity: A Geo-chemical Diagenesis Perspective

Gas from shale reservoirs is difficult to produce, unless they are effectively stimulated. Production from wells completed in these quad-porosity reservoirs is dependent on the placement of hydraulic fractures and their degree of connectivity to the existing natural fractures. These propped fractures and their effectiveness is a direct function of the in situ stress in the formation. Furthermore, geochemical diagenesis in the created fractures significantly impacts fracture conductivity. This paper utilizes a fracture-completed horizontal well in different configurations of quad-porosity shale gas reservoir models to assess the effect of gas flow and storage in these systems on production parameters. Furthermore, sensitivity analysis is carried out on critical parameters to observe its impact on well performance. This work will help to provide a better understanding of hydraulic fracturing treatments and its effect on the forecast of a stimulated well with reasonable certainty.

Industrial and Engineering Chemistry Research

Simulation and Mathematical Modeling of Stimulated Shale Gas Reservoirs

Background/Objectives: Leg Length Discrepancy (LLD) after THA is the most common cause of patient’s dissatisfaction. Hence, this paper aims at determining magnitude of LLD which is bearable by any person. Methods/Statistical analysis: It includes simulation and analysis of human musculoskeletal models in Open Sim software for various hip muscles as these muscles are more affected after THA. Firstly, muscle force results from Open Sim are cross-checked and validated with an established muscle model. Then, models of different LLDs are obtained in Open Sim and results of muscle force are plotted on graphs for various hip movements like flexion/extension, adduction/abduction, etc. Findings: LLD bearing capacity for different body weights of the person is found in the range of 2.0-2.5 cm. It is found that more is the body weight of the person; smaller is the range of his/her LLD bearing capacity and vice-versa. Through literature survey, it is found that person can bear LLD from 10-50 mm to avoid major problems like lower back pain, muscle or ligament injury, nerve palsy, etc. Different researchers found different values of LLD to avoid same problem. So, this range is quite large to define LLD bearing capacity of a person. From this study, a concise range of LLD bearing capacity was found. Application/ Improvements: Surgeon can plan his/her preoperative planning and prosthesis design in such a way that LLD will not exceed a given range after THA.

School of Mechanical Engineering

Fulltext

Indian Journal of Science and Technology

Simulation and analysis of leg length discrepancy and its effect on muscles

Mixing of two or more materials (i.e. heavy density metal powder in the fluid or fluid in another jelly fluid) is very difficult. In conventional method of mixing the metal powder and fluid mixing is carried out on unidirectional stirring machine. This paper investigates the limitations of the conventional mixer. This paper also discussed about the Schatz geometry shaker-mixer is used for a homogeneous mixing of powdery substances with differing specific weights and particle sizes. The product is mixed in its own closed container. The mixing container is set into a three-dimensional movement that use of rotation, translation and inversion according to the Schatz geometric theory. The results fulfil the highest requirements and are achieved in a minimum of time.

Materials Today: Proceedings

Schatz Mechanism with 3D-Motion Mixer-A Review

Solution-blended hybrid composites with carbon black (CB) as the second conducting filler in polyethersulfone (PES)-graphite have been prepared by first dissolving PES in dichloro methane. Addition of 1 wt% CB to solution-blended PES-7 wt% graphite results in decrease in the direct current electrical resistivity by four orders compared to the addition of 0 wt% CB. The particle size of graphite is reduced from few micron to nano level as evidenced by transmission electron microscopy analysis resulting in better dispersion. Without the addition of CB, the binary composite namely PES-7 wt% graphite exhibits finite conductivity due to increase in the contact between graphite particles as a result of reduction in the particle size. Comparison of electrical conductivity of PES-7 wt% graphite-2 wt% CB composites prepared by both solution-blending and powder-mixing routes proves the above-mentioned point. The alternating current behaviour, both conductance and effective dielectric constant studies shows that solution-blended composites exhibit higher value of conductance and effective dielectric constant at 0.01 Hz. This can only be attributed to better graphite dispersion in solution-blended composites. The enhancement is due to only particle size reduction of graphite that decreases the interparticular distance as the solution-blended binary composites with CB act as insulators up to 10 wt%. The charge transport at low concentrations of CB in solution-blended hybrid composites is dominated by the interfacial barriers and capacitance effects, while at higher concentrations it is mainly of hopping type at room temperature. The interfacial capacitance increases from 37.6 pF with 0 wt% CB addition to 96 pF with 2 wt% CB addition in PES-7 wt% graphite. Differential scanning calorimetry result suggests that more than 10°C enhancement in the glass transition temperature of PES is obtained for PES-7 wt% graphite-1 wt% CB.

School of Polymer Engineering

Journal of thermoplastic Composite Materials

Solution-blended polyethersulfone-graphite hybrid composites: Formation of nanographite and electrical characterization

Early pest detection and identification in agriculture is necessary for good quality and quantity of crop production. This will help to reduce the effect of pest and the use of pesticides. Detection of pest is necessary to get the information and location of the pest and this can be achieved only if temperature is controlled in the room like in the greenhouse. There are various conventional techniques which are used to detect the pest, but the proposed method is very fast, easy and convenient. This project proposes pest detection and movement by using the video processing. Video processing involves capturing the video and processing on it to find the presence and location of pest. © 2015 IEEE.

2015 International Conference on Information Processing (ICIP)

Agriculture pest detection using video processing technique

Our planet is blessed with various species of fauna and flora. It’s well known that plants play a crucial role in preserving the earth’s ecology and environment by maintaining a healthy atmosphere and providing sustenance and shelter to innumerable insect and animal species. Plants are also important for their medicinal properties and as alternative energy sources like bio-fuel. Today as many types of plants are at the brink of extinction. In our day to day life herbal plays vital role on human physic maintenance. Plant classification has a broad application perspective in agriculture medicine and is especially significant to the biology diversity research. In recent time’s computer vision have been successfully applied towards automated systems of plant cataloguing. The proposed system tries to bring atomization in the process of plant leaf classification such that without any precious knowledge of the leaf species, we are trying to detect the leaf. This wi ll help the botanists in their study and speed up the process of identifying the species of plant. India is enriching source of plant species which is the base of ‘Ayurveda’ so the classification and identification of various plant species is one of the important phase. Our idea is to develop an automated tool which would detect and classify the plant leaf species after comparing with the trained sets. These trained sets are used by Artificial Neural Network (ANN) after image processing. The Neural Network would be trained for detection of edge and vein analysis. Earlier atomization was difficult, but now due to drastic development in technological field it is possible in just few steps. This paper proposes the automated tool for plant leaf recognition of leaf its digital image. Manual identification requires prior knowledge of species and is a lengthy process, thus the atomization technique helps t