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

Engineering and Technology

Manufacturing compound weirs for exact discharge measurement has been a challenge, according to studies so far. The length of the weir crest (L), weir height, and weir width all affect the efficacy of compound broad crested weirs as flow monitoring devices. As a result, the flow characteristics of a given flume are determined by changes in weir geometry, particularly the discharge coefficient (Cd), which varies proportionally with the h/L ratio. For varying h/L levels, many researchers have maintained an average range of Cd. The experimental and Computational Fluid Dynamics simulations for measuring discharge by compound broad crested weir are presented in this work. Validation in the results is achieved using CFD FLOW 3D software. For enhanced accuracy in free surface simulations, the model uses the renormalized group (RNG) approach with the volume of fluid (VOF) method. Laboratory models were employed in an attempt to analyse and validate the CFD model. The model is fabricated using PVC material first and later resorted to additive manufacturing for targeting accurate discharges. The shape of the compound broad crested weir was modified to achieve constant Cd by comparing three-dimensional computational fluid dynamics models to experimental measurements. The performance of the CBC weir for precise measurement of a wide range of discharges is confirmed by numerical simulations and experimental measurements, with a reasonably constant design input value of discharge coefficient of 0.6. When compared to empirical methods, CFD-based weir geometry optimization produces more exact model predictions. Moreover, manufacturing this optimized model with 3D printing technology using Poly Lactic Acid plastic material has validated the weir performance with accurate estimates between theoretical, experimental and CFD outputs. © 2021 All rights reserved, Legal Deposit.

School of Civil Engineering

World University root node

Larhyss Journal

Performance enhancement in discharge measurement by compound broad crested weir with additive manufacturing

Cognitive computing is an intelligent system that converses with and mimics the human being in a natural form by learning at scale, reasoning with purpose. Cognitive computing is the third era of computing and now cognitive computing has attracted considerable attention in both academia and industry. Machines and humans’ intelligence gets combined to solve the most complex problems of the world. Complicated problems can be solved by computing framework without intervention of humans. Natural language processing with emotion analysis, artificial intelligence (AI), machine learning, neural networks are building blocks of cognitive computing process to tackle problems as the way human beings do. Nowadays, advance technologies adapt cognitive computing in many areas to assist human experts in smart decision making for the betterment of businesses. Current technology expectations are to make human life better and to help them work in better ways. Nowadays, there is explosive data growth, business conditions are also changing rapidly so intelligent, hassle-free, and enhanced interactions amongst human beings and technology can be effectively addressed by cognitive systems. AI is in use in many apps like the Alexa: Amazon voice assistant, Netflix and Amazon algorithms which recommend the next to watch or buy. Some examples of personal assistants that uses cognitive computing are Alexa, Siri, Google assistant, and Cortana. Advancement of technology and its adoption in the public and private sectors will greatly affect the future of cognitive computing due to technology evolutionary paths and trends. Cognitive systems must be adaptive, interactive, iterative, and stateful and contextual in commercial and widespread applications. Some of the applications that can use cognitive computing to gain benefits from this type of technology are cognitive computing for changing business values, Financial and Investment firms, Healthcare and veterinary medicine, Travel and Tourism, Health and wellness, Education and learning, Agriculture, Communication and network technology. © 2021 Elsevier Inc. All rights reserved.

School of Computer Engineering & Technology

Cognitive Computing for Human-Robot Interaction: Principles and Practices

Introduction to cognitive computing and its various applications

Engineering design is an iterative process that requires to be dealt with all feasible design solutions in order to arrive at a desired objective. Gear drives are considered as the critical components in a mechanical power transmission system. It is possible that gears will predominate as the most effective means of transmitting power in future machines due to their high degree of reliability and compactness. With the advancing technology in recent years, the machines are demanding varying speed and load. Over the years, research has been done predominantly on gears to minimize or to reduce the failures and for optimal design. The main aim of this work is to design and analyse the hybrid composite gears for two stage constant mesh helical gearbox and to compare the stress and deformation results with and without the inclusion of Carbon Fibre Reinforced (CFR) material. The objective of this research work is to reduce weight and rotational inertia of the entire assembly by using Hybrid Helical Gears. Carbon Fibre Standard UT Prepreg was selected for this study because of its high strength to weight ratio. By comparing the weights of EN36 Steel Gear and Hybrid Gear, a 25.3% reduction in weight was observed. This research work illuminates the replacement of EN36 alloy steel gear in terms of stresses and deformation with an added advantage of reduced weight and rotational inertia of the helical gear by using EN36/Carbon Fibre Composite material while considering the safety of the component in the application of two-stage constant mesh gearbox. © 2021 Elsevier Ltd. All rights reserved.

School of Mechanical Engineering

Materials Today: Proceedings

Design of helical gear with carbon reinforced EN36 steel for two stage constant mesh gearbox weight reduction

Topology optimization is a technique which has proven to be a very crucial and effective tool in modification of the geometry of various mechanical or load bearing components. This technique has been used in aerospace, mechanical and civil applications to save material and reduce the overall mass of the component. There are various existing topology optimization algorithms which produce remarkable results, each algorithm is unique, and the results obtained are different. Implant dentistry has become a new area where topology optimization has found a good scope. The goal of modifying a dental implant is to improve the osseointegration and enhance its stability, hence when a topological optimization study is being performed on a dental implant these additional factors are necessary to be considered. The literature pertaining to the topology optimization employed in dental implants is limited and this study focuses on the available literature and other important aspects like selection of the optimization algorithm, bone density and manufacturing method which influence the topology optimization procedure when employed in the modification of dental implants.

AIP Conference Proceedings

A review on techniques employed for topology optimization in implant dentistry

Thermoplastic PVC matrix was reinforced with waste fiber portion of Citrus Maxima (CM) fruit for making composites. The CM fibers were separated, dried at 50-60 °C for 24 h, coarse ground and sieved. PVC/CM fiber composite film with different fiber loading (10-70 wt%) were cast using solvent casting method. Sheets were cast in large petri dish using tetrahydrofuran (THF) as solvent and dried in an oven thoroughly at 50-60 °C. The evaluation of mechanical properties was done as per ASTM D882; stereo image of the fractured specimen and FTIR was used for the study of morphology and microstructure of the composite. Incorporation of fibers into PVC made the material stiff, leading to significant increase in Tensile Modulus, Breaking Strength and Yield Stress at higher filler loadings. Uniform distribution of the fibers in the microstructure of PVC matrix led to the formation of cross-ply structure and improved the mechanical properties. These results indicate that the fiber portion from CM can be effectively used as an eco-friendly reinforcing additive to form PVC composites.

School of Chemical Engineering

School of Polymer Engineering

Studies on effective utilization of Citrus Maxima fibers based PVC composites

The use of composite adsorbent with nano particle additives having high surface area can lead to enhanced heat transfer, higher adsorption capacity and faster rate leading to better adsorber performance. The objectives of the present study were to investigate the effectiveness of nanofluid as a cooling fluid of a composite adsorber by carrying out nanofluid characterization and to investigate adsorption-desorption characteristics of a composite adsorbent for ammonia as an adsorbate. An experimental set up with tube-in-tube type configuration was constructed to monitor the thermal characteristics (heat transfer from and to the adsorber) and ammonia adsorption/desorption rates. The composite of calcium chloride with activated carbon and expanded graphite nanoparticles was made having different concentrations of CaCl2 ranging from 40 % to 80 % in the composite and expanded natural graphite (ENG) content ranging from 0-3 % by weight. The desorption characteristics were studied at different temperatures from 70° C to 110° C. The cooling fluid with and without graphite nanofibers (GNF) was circulated in the inner tube at different flow rates from 5 LPH to 25 LPH. From the experimentation on adsorption-desorption characteristics, it was found that the total amount of ammonia adsorbed increased from 133 g for 50:50 composition of CaCl2:AC to 156 g for CaCl2:AC composition of 50:50 with the addition of 3 % ENG nanoparticles. Also the adsorption process time reduced from 22 minutes to 18 minutes. For 50 % CaCl2 in the composite the temperature at which the maximum desorption occurred was 70°C. So, desorption could occur at lower temperature, which is advantageous as it increases the number of options for heat sources to be used. When nanofluid was used as a cooling fluid of the composite adsorber, the total amount of ammonia adsorbed increased from 79.411 g for basefluid to 90.206 g for 0.4 % graphite nanofiber nanofluid for flow rate of 25 LPH. With the use of composite adsorbent of CaCl2:AC of 50:50 composition and addition of expanded natural graphite (ENG) by 3% and when 0.4 % graphite nanofiber nanofluid was used as a cooling fluid, the maximum ammonia was adsorbed up to the bed length of 600 mm only out of the total bed length of 1 m indicating the possibility of reduction in the size of an adsorber. © 2021 Author(s).

Analysis of composite adsorber with graphite nanofiber based nanofluid as coolant

The main aim of the this work is to design and develop a suitable mechanism to finish the hard surfaces and improve the performance of finishing processes based on MR fluid using external magnetic field. This work is carried out by considering the significant process parameters like the concentration ratio of CIPs to aluminum oxide (Al2O3) as an abrasives, magnetizing current, the rotating speed of the tool, feed rate of workpiece, working gap and hardness of work pieces to know the response as a percentage change in surface roughness Ra. SEM technique is employed to know the surface integrity and understand the performance of MR fluid based finishing process over the surface of die steel materials. While, performing the experimental work, a full factorial design is applied and the results are characterized using regression and ANOVA technique. It is revealed from the results that the foremost contribution of the factors in the highest order are working gap, magnetizing current and the hardness of the work piece followed by the ratio of CIP to Al2O3 abrasives, feed rate and rotating speed of the tool in improving the surface roughness Ra. The regression model confirms the linear relationship between observed Ra and the predicted Ra and its correlation coefficient is + 0.85. The average percentage deviation is 3.56 within 5% error band. Thus, this method is capable to obtain the Nano finishing over the surface of hardened materials

Experimental investigation of parameters and surface integrity of die steel based on MR fluid finishing process

In this research novel approach to the selection of the best suitable composition of nanocomposite from the various alternatives of nano-Al2O3/Al6061 using multi-criteria decision-making, techniques are presented. Low strength and hardness limit the use of Al6061 in moderate to high-stress applications such as in aerospace and automobiles. To overcome this deficiency, multi-characteristics <a href="https://www.sciencedirect.com/topics/materials-science/al2o3">Al2O3</a> nanoparticles are successfully reinforced in various wt. % to Al6061 matrix to fabricate novel Al2O3/Al6061 nanocomposites on aluminum stir casting furnace. That results in an improvement in mechanical properties at a different order of importance and various material cost. Hence it is essential to determine the best suitable alternative of nanocomposite and corresponding optimum quantity satisfying application requirements. Therefore, to tackle the difficulty of best suitable composition selection at required order of importance, multicriteria decision-making techniques such as TOPSIS and EXPROM2, was implemented and rankings are obtained. Weight criteria are determined using the AHP model. Comparative study of all MCDM is carried out by spearmen’s rank correlation. The best material found is 4A (4% Al2O3 reinforcement). MCDM analysis was found satisfactory for material selection problems.

TOPSIS &amp; EXPROM2 multicriteria decision methods for Al2O3/Al 6061 nanocomposite selection

Image Captioning is one of the emerging topics of research in the field of AI. It uses a combination of Computer Vision (CV) and Natural Language Processing (NLP) to derive features from the image, use this information to identify objects, actions, their relationships, and generate a description for the image. It is most important concept in artificial intelligence applied in the fields like aid to the blind, self-driving cars, and many more. This paper we demonstrates a concise state of art image captioning and its method for caption generation using deep learning concepts. We also determine the approach for image caption generation using Convolutional Neural Network (CNN) and Generative Adversarial Network (GAN) model in deep learning framework. Using this approach system intelligent enough to create sentences for images. It uses the encoder-decoder architecture, where CNN is used for image vector generation and LSTM is used for the generation of a logical sentence using the NLP concepts. Finally, we evaluate the proposed system experimental analysis with numerous existing systems and show the effeteness of system. © 2021 IEEE.

2021 International Conference on Emerging Smart Computing and Informatics, ESCI 2021

Image captioning methods and metrics

Social media has been an unavoidable part of our life over the years. As it is getting popular, the number of social media bots are also increasing. Social media bots are the artificial agents who imitate as a human on social media. They are intended to like, retweet the posts which eventually can tamper with the genuineness of the trend. They can also be a menace to democracy as they can falsely influence people. Social media bots can be used for cyberbullying, terrorist activities, gaining fame, spreading wrong information, restricting freedom of speech, spamming. To detect social media bots on Twitter, we utilized metadata of Twitter profiles and applied a unique feature selection method, and also explored the power of ensemble learning to make a robust classifier. © 2021 IEEE.