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 thermal conductivity (k), heat transfer coefficient (HTC) and viscosity of the ethylene glycol/water dispersed with graphite nanoparticles was studied under heating and cooling conditions for temperatures ranging from 0 °C to 75 °C using tubular heat exchanger system built in house. Flow rate was varied from 5 l/h to 25 l/h giving Reynolds number (Re) ranging from 50 to 750. The HTC increased with the increase of Re as well as temperature. The thermal conductivity of the nanofluid was determined at constant low Re (200) for all concentrations and temperatures used in the experiment. The concentration dependence of thermal conductivity was found to be much different than that predicted by models suggested in literature. The viscosity was measured for different concentrations of nanoparticles (0 to 0.8%) as well as temperatures 275 K to 340 K. The temperature dependence of viscosity was found to follow Arrhenius type equation η = ηoexp(E/kbT) with very little change in the activation energy from that of the base fluid. On the other hand the pre-exponential constant increased six folds with the increase in nanoparticle concentration. An empirical relation derived from Brownian motion was found between the product of viscosity and thermal conductivity (Ω = kr · ηr) with respect to concentration of the nanoparticles which was found to be true for whole range of temperature and compositions studied.

School of Mechanical Engineering

School of Polymer Engineering

World University root node

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Journal of Nanofluids (USA)

Investigations on Thermal Conductivity, Heat Transfer Coefficient and Viscosity of Graphite Nanoparticle Dispersed Nanofluid

Self-Organized Wireless Sensor Network (SOWSN) is a system of sensor nodes that takes global decisions through local interactions without involvement of any central entity. Wireless sensor nodes have constrained processing capability and energy. The key characteristic used to evaluate performance of Wireless Sensor Network (WSN) is its lifetime which depends on residual energy of nodes; hence the major challenge in WSN is the efficient use of available energy. Node clustering saves energy and also shows self-organization because global decision like Cluster Head (CH) selection is taken through mutual communication between nodes. In this paper, a new clustering method based on self-organization is implemented to boost lifetime of WSN. Sensor network is divided into regions. Cluster formation relies on Residual Energy (RE) and nearest Distance (D) from CH. Node with highest residual energy becomes CH. Rest nodes join the nearest CH. Clusters are broken when residual energy of CH falls below threshold energy; causing the sensor network to get self-organized into new clusters. RED also focuses to solve the energy hole problem caused due to higher energy consumption by CHs near Sink Node or Base Station (BS). © 2018, Springer International Publishing AG.

School of Computer Engineering & Technology

International Conference on Information and Communication Technology for Intelligent Systems

RED: Residual energy and distance based clustering to avoid energy hole problem in self-organized wireless sensor networks

Recently, stereoscopic image/video conversion has been most demanding as it has a great stereo video experience. This paper presents the development of the methodology for generation of the depth map used for stereoscopic view. Normally, Stereoscopic conversion involves two steps: generation of depth map and generation of two left and right view using estimated depth. This paper focus for the generation of the depth map as a second step is well known. The estimation of the depth map is a difficult task. This paper uses a fusion of monocular cues as motion, Aerial Perspective cue(AP), Linear Perspective cue(LP), and Defocus cue to estimate the depth. The experimental results show that generation of the depth map is very close to the real depth map. Thus, the algorithm can apply for 2D-to-3D conversion in 3D displays. This algorithm tested in different conditions such as the sequence of camera motion and multiple objects, static cameras, and background as stationary, a highly dynamic foreground and with less motion as background, and motion is in behind the foreground. © 2017 ACM.

School of Electronics & Communication Engineering

Proceedings of the 9th International Conference on Machine Learning and Computing

Development of Semi-Automatic Methodology for Extraction of Depth for 2D-to-3D Conversion

Data mining also sometimes called data or knowledge discovery is the process of analyzing data from different perspectives and summarizing it into useful information. Image processing is related to Computer vision, which is a high-level image processing out of which a machine/computer/software intends to decipher the physical contents of an image or a sequence of images. One of the ways to do this is by comparing selected facial features from the image and a facial database. Recognizing emotion from images has become one of the active research themes in image processing and in applications based on human-computer interaction. This research conducts an experimental study on recognizing facial emotions. The flow of our emotion recognition system include the basic process in FER system. These include image acquisition, preprocessing of an image, face detection, feature extraction, classification and then when the emotions are classified the system assigns the user particular music according to his emotion. Our system focuses on live images taken from the webcam. The aim of this research is to develop automatic facial emotion recognition system for stressed individuals thus assigning them music therapy so as to relief stress. The emotions considered for the experiments include happiness, Sadness, Surprise, Fear, Disgust, and Anger that are universally accepted. © 2017 IEEE.

Proceedings of the 2017 International Conference on Intelligent Computing and Control Systems, ICICCS 2017

Facial emotion recognition system through machine learning approach

Real time business search largely has the involvement of Internet of Things which has now become a huge set of objects with large magnitude of intercommunication links and services. This scalability issue can be resolved by bringing in (SIoT) Social IoT i.e. an object looking for its social partners who will have similar set of rules to positively influence the performance of the service. In this work, we are putting forward the analysis of the impact of deep web on real time search. We also propose a novel approach by analyzing the shortcomings of the existing techniques. The novel idea is the distribution of web search engine to take care of sub parts of entity and sensor pages by distributing the search engine itself along with the index over multiple nodes. Deep websites are needed to be brought in for accurate results. This work offers better accuracy and a significant speed up for multiple query execution in distributed environment. © 2017 IEEE.

2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017

Analyzing the impact of deep web on real-time business search

Nano-powders are composed of particles in size range from about 1 to 100 nano-metres (nm). The growing demand for nano-powders arises from the change in physical, chemical and electrical properties exhibited by such particles when their size falls below 100 nm. Along with the increasing production and use of Nano scale particles, there has been a growing concern over the impact of this new technology on health, safety and environment. This has almost exclusively concentrated on the potential health hazards of nano-powders. One potential hazard that appears to have received little attention to date is their explosivity. Explosive dust clouds can be generated from most organic materials, many metals and even some non-metallic inorganic materials. Dust explosions involving particle sizes ranging from a few microns to hundreds of microns, there is a need for these particles to be extensively studied. This work involves computationally modelling the explosion, and investigation of critical parameters that can enhance the severity of the explosion. These parameters include but are not limited to effect of particle size, dust concentration and composition, ignition strength, degree of dust dispersion, explosion characteristics of nano-particles, operating conditions. Further, the work involved in this paper looks at the impact onto the environment by explosion of such nano-powders. The possibility of dust generation accumulation and explosion in various areas of the facility are investigated. A checklist for adequacy of existing safety measures is prepared, and requirement for additional safeguards is studied, in order to avoid catastrophic effects. © 2017, Society of Petroleum Engineers

School of Petroleum Engineering

SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition

Assessment of Explosion Hazards Associated With Nano-Powders

The test suite minimization approach is a major research topic that it requires huge attention from the researchers as the traditional methods used for performing the test suite minimization is concentrated on the cost of regression testing but the requirements were not satisfied. To solve the problem of satisfying requirements, researchers proposed greedy algorithms, optimization algorithms, and so on. In this paper, a novel optimization algorithm is proposed termed as the Diversity Dragonfly Algorithm (DDF) algorithm that concentrates on the cost and quality of the test suite. The diversification included in the standard Dragonfly algorithm forms the DDF that uses three bitwise operators for diversification. The DDF algorithm determines the best suite based on the hunting mechanism of the dragonfly using a minimum objective function such that the selected test suite satisfies all the requirements. The experiment is carried out using five subject programs and the performance analysis of the proposed DDF is carried out and compared with the existing methods. It is found that the reduction capability of the DDF is better than existing methods and the cost of the proposed DDF is low ensuring a quality test suite reduction. © 2017 IEEE.

DDF: Diversity Dragonfly Algorithm for cost-aware test suite minimization approach for software testing

For wells drilled in shale gas reservoirs to be economic, hydraulic fracturing has become a common completion practice. Production from these completed wells is highly dependent on the characteristics of proppants placed in the created fractures. Fracturing leads to an interaction between the minerals of the proppants, formation and the fluids; this results in the phenomenon of proppants diagenesis. It involves mechanisms such as diffusion, dissolution, precipitation along with chemical reactions that take place at the fracture surface. Over time, this combined process results in a loss of proppant pack permeability thereby leading to a decline in well productivity. This occurs due to changes in compositional differences between proppants, fracturing fluid and the formation. A mathematical model, representing this phenomenon is developed in this paper. It inculcates the phenomenon of mass transfer along the length of the fracture coupled with associated surface chemical reactions, and mass conservation equations are solved for individual components. Further, the impact of finite difference techniques on the results is studied. This is supplemented with studies involving changes in fracture aperture as well as velocity profile of the flowing fluid. Impact of results from the developed mathematical model on typical shale gas well productivity is evaluated. [Received: April 1, 2015; Accepted: September 8, 2015]

International Journal of Oil, Gas and Coal Technology

Impact of proppant diagenesis on shale gas productivity

The compressor is the most important and expensive component in Refrigeration system. Moreover, linear compressor is an immerging technology in cryogenics and refrigeration field. Hence, it is necessary to improve the reliability of the linear compressor. Failure modes effects and criticality analysis (FMECA) is a step-by-step approach for identifying all possible causes of failures and its effects in designing, manufacturing and assembly process of a product. In this paper, an attempt has been made to perform FMECA of linear compressor. Major failure modes such as valve failure, continuity in coil former, breakage of flexure bearing and leakage are identified. The effect of these identified failure modes is studied. Depending on impact of failure modes on the system components are classified into different levels. In this work, 7 failure modes of linear compressor are prioritized by probability of occurrence, detect ability and severity of the failure, accordingly Risk Priority Number (RPN) is calculated. The results of this analysis can be used to improve the design and optimize the performance of the linear compressor. © 2017 Elsevier Ltd.

Materials Today: Proceedings

Failure modes effects and criticality analysis of the linear compressor

The Cuckoo Search algorithm is a recently developed meta-heuristic optimization algorithm, which is used for solving optimization problems. This is a nature-inspired metaheuristic algorithm, which is based on the brood parasitism of some cuckoo species, along with Levy flights random walks. Normally, the parameters of the cuckoo search are kept constant for certain duration, this results into decrease the efficiency of the algorithm. To make a deal with this issue, a proper strategy for tuning the cuckoo search parameters is to be defined. Cuckoos are fascinating birds, not only because of the beautiful sounds they can make but also because of their aggressive reproduction strategy. Some species such as the Ani and Guira cuckoos lay their eggs in host bird nest, and they may remove others eggs to increase the hatching probability of their own. In this paper, cuckoos behaviour & their egg laying strategy in the nests of other host birds is explained.