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

In this study, an aqueous solution containing amixture of heavy metal ion Cr(III) were treated by polymerenhanced Nanofiltration using polyethylene glycol as a bindingagent polymer. The performance of PEG in removing heavymetal ion Cr (III) was compared with PEG and without PEGaddition using polyamide Nano filtrationmembrane. Thepercentage rejection of heavy metal ions was studied under thedifferent value of pH, metal ion concentration and flow rate.AtpH 10,percentage rejection of heavy metal ion was highest ataround 99.2%,whereas,at 200ppm concentration and at3(l/hm2)flow rate percentage rejection of heavy metal ion withPEG was highest 99.5%,it was found that PEG gave higherpercentage rejection of Cr(III) ion than without the addition ofPEG.

School of Chemical Engineering

World University root node

International Journal of Recent Technology and Engineering

Enhancement of Separation Efficiency for Nano Filtration Membrane using Water-Soluble Polymer

Stochastic Computing (SC) is another substitute way to deal with digital information. With ongoing advances in Internet of Thigs (IOT) and wearable gadgets it is interesting to implement Artificial Neural Network (ANN), Image Processing applications on reconfigurable platform. However, several elements and very complicated connections are usually required, which leads to more hardware and power consumption. Stochastic Computing (SC) meet stringent requirement in embedded and mobile IOT devices. SC is an alternate approach to deterministic computing that treats binary data as probabilities. SC employs very low-complexity arithmetic units. SC is popular in immensely parallel systems and is exceptionally tolerant to soft errors. SC based hardware execution achieves low hardware foot print, low power and energy competent circuits while preserving high accuracy. This paper surveys SC's the low cost, low complexity, error tolerant, alternative to binary computing.

School of Electronics & Communication Engineering

2019 3rd International Conference on Recent Developments in Control, Automation and Power Engineering, RDCAPE 2019

Survey of Stochastic Computing for Hardware implementation

With increase in demand of construction industry, man has developed various techniques of construction. Post-installed connection is one of the techniques which allows to extend or strengthen the structure without affecting the existing structure. The technology of post-installed reinforcing bars is gaining importance since these bars are being frequently used in horizontal, vertical, and overhead applications in retrofit and rehabilitation of structures. Design of post-installed rebar connection is an issue as proper design guidelines are not yet provided in IS codes. Proper design of anchorage length is important parameter in post-installed connection. Post installed rebar connections, Eurocode approach to design, post-installed reinforcement approval and design method for static loads are discussed. The main aim of the study is to design post-installed rebar connections for existing structure. We have also carried out analytical investigation using finite element method to check the effect of post-installed connections by varying anchorage length as 10d, 15d, 20d and compared the effect with actual designed anchorage length for static loads. Behavior of structure after post-installed connection under static loading is studied. © 2019 IJSTR.

School of Civil Engineering

International Journal of Scientific and Technology Research

Effect of post-installed rebar connection on concrete structure

Coal mine in India is one of the biggest source of energy production. Coal is the major component used in thermal power plants which helps in consuming 71% of electricity generated by these thermal power plants in India. In opencast coal mining excavation of coal is done and huge area is abandoned after coal is being excavated. The OBD soil which is present at these mine sites is very poor in nutrients that it is usually unfavorable for any type of plantation to be carried out. Keeping this in mind another factor comes across is that thermal power plants are located nearby coal mines which gives fly ash as combustion product of coal and disposal of this fly ash is very crucial. Therefore, this fly ash can be used along with coal mine OBD soil which it has efficiency in improving soil fertility in many ways. Revegetation is one of the most accepted way of soil reclamation and reduction in soil erosion. The suitability of soil for growth of bamboo is checked by planting bamboo saplings in an area of 3 x 3 feet having depth 1 foot in a systematic manner by attempting field trial. © BEIESP.

International Journal of Innovative Technology and Exploring Engineering

Management of coal mine overburden and fly ash using bamboo cultivation

The construction boom in Pune is leading to generation of enormous of Construction & Demolition (CDW) waste and this trend is likely to further increase in recent decades. Pune is fast paced city and is known as IT and automobile hub of county with rapid growing population. A city with dynamic construction and real estate industry reinforced by some public infrastructure project of transportation and utilities. Rapid development has led to increase in construction activities in the city leading to increases in quantities of construction and demolition waste generated in the city. In this paper, content analysis approach was adopted to analyse the information collected from previous literature, government reports and information retrieved from relevant Construction & Demolition (CDW) waste management rules. This paper focuses on quantity & source of Construction & Demolition CDW waste; also reflects current scenario of disposal and its effects. It is anticipated that the collection plan could help in management of construction & demolition waste and in reduction of illegal dumping. © BEIESP.

Management of construction &amp; demolition waste in Pune city

Now-a-days demand forecasting is used in many countries for military applications such as spare parts of aircraft and for improving budget efficiency. In supply chain management demand forecasting is a major issue. Currently, time series technique is used to demand forecast but this technique resulted in lack of accuracy and improvement in accuracy is needed. So this paper focused on comparing the features which leads to improvement in the accuracy and propose a system for demand forecasting of spare parts of anti-aircraft missiles, which are based on machine learning and neural networks such that equipment's are properly utilized and alongwith that budget is also maintained. We have compared the existing features with the new features added and applied algorithms and looked upon at the accuracy. Experimental results proves that the new features added gave higher accuracy. Here, we also present an end-to-end boosting system called XGBoost and Multi-layer Perceptron. These new techniques were compared with traditional Machine Learning techniques. This experiment is conducted on the Vietnam War dataset. © 2019 IEEE.

School of Computer Engineering & Technology

Proceedings of the 4th International Conference on Communication and Electronics Systems, ICCES 2019

Analysis on Machine Learning Algorithms and Neural Networks for Demand Forecasting of Anti-Aircraft Missile Spare Parts

A farmer uses different agriculture practices to improve the crop yield generating the greenhouse gases (GHGs). The soil management practices are very important in the greenhouse gas emission from agriculture sector. In this paper we tried to find the greenhouse gas CH4 and CO2 emission from agriculture using soil attributes i.e. soil moisture, soil temperature, humidity, pH values, and N-P-K values. We used different machine learning algorithm such as Decision table, SOM regression, ZeroR, Randomforest, Multilayer Perception and Multiple Linear regression for comparison purpose. We collected soil sample using different sensors from the farm. We have used Mean absolute error(MAE) and Root mean squared error (RMSE) as a coefficient of correlation with 10 fold cross validation. The result shows that for CH4 eq and CO2 eq the SOMregressor performs better than other classifiers with perfect positive correlation whereas the ZeroR classifier gives negative correlation for CO2 eq and CH4 eq emission. Also the OLS statistics of multiple linear regression result shows that R squared value 0.786 means 78% predicted values are similar to actual reading of CH4 eq emission. © 2019 IEEE.

2019 IEEE Pune Section International Conference, PuneCon 2019

Effect of Soil Attribute on Greenhouse Gas Emission from Agriculture using IoT

Human interaction and carrier of feelings among humans are accomplished mainly through five senses, such as touch, smell, taste, audio, and Visual. Considering Visual sense, images and videos are important gradients in day-to-day life. It can elevate/depress mood of a person. Video Aesthetics improves user satisfaction. In this study of mood detection, we are demonstrating an approach which is automatically assessed the aesthetics of videos, with emphasis on detecting the mood of videos. With the rising popularity of DSLR camera, Mobile dual camera, the amount of Visual data available on the internet is expanding exponentially. Some of the videos and pictures are aesthetically pleasing and beautiful to human eyes. But there are some videos as well as photos which are uninteresting and of low-quality. This paper demonstrates a simple but powerful method to classify videos into pleasing and non-pleasing categories. Further, our aesthetic quality assessment will find the mood of aesthetically pleasing video (i.e. video representing a happy video or sad or fear, etc), that reflect on a person's mood. © 2019 IEEE.

2019 Global Conference for Advancement in Technology, GCAT 2019

Detecting Mood of Aesthetically Pleasing Videos Using Deep Learning

In recent times, the advancements in Brain-Computer Interface has not only been instrumental in achieving its fundamental purpose of aiding disabled people, but also in creating novel applications like playing games without physical controls or operating home appliances merely by the power of your brain. The electrical activity generated in the brain is measured by an EEG device after which the collected raw data undergoes through various steps, namely: Signal acquisition, Data Preprocessing, Feature Extraction, and Classification. This paper helps the reader in understanding the different algorithms and methods used in each of these processes. A detailed survey of various applications of BCI using different feature extraction and classification techniques is done. Finally, we have compiled all the current issues which hinder the efficiency of BCI systems. © 2019 IEEE.

ICCIDS 2019 - 2nd International Conference on Computational Intelligence in Data Science, Proceedings

A review of recent trends in EEG based Brain-Computer Interface

Composites are modern materials which are currently used in almost all areas of technology. Because of the versatile behaviour of composites, analysis of composites is required to be done. In this work a unidirectional epoxy-carbon fiber reinforced composite was subjected to tensile load. While loading, the electrical resistance measurement is done using Kelvin’s four-wire method. Electrical contacts were made by epoxy-silver adhesive on the specimen. Connecting wires were attached with the epoxy-silver adhesive. The results obtained during tensile test were analysed to study the mechanical and electrical behaviour of the composite and their correlation which could be helpful in predicting the performance of composite materials. © 2019, International Journal of Scientific and Technology Research. All rights reserved.