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

Rice husk consists of a huge amount of silica when it is burned properly, and cement can be partially replaced by rice husk ash (RHA) to make concrete. In the present experimental research, flexural strength (FS), workability, compressive strength (CS), and indirect split tensile strength (STS) of M30 grade concrete are investigated by partially replacing cement with RHA with an increment of 5%. The influence of the various percentages of RHA as a cement substitution material on the workability, CS, STS, and FS is compared with that of normal M30 grade concrete. The water-cement ratio is 0.55, which is maintained constant. The test results also concluded that the CS, STS, and FS of concrete decreased with an increase in RHA above 15%. The findings of the experimental research show that the optimum percentage of RHA was 15%, at which point the CS, STS, and FS were at their maximum, and any additional RHA addition beyond 15% causes a significant decrease in the CS, STS, and FS, and that it is recommended to replace cement with RHA in the range of 5–15% to achieve an effective and high strength of concrete.1 © 2022

World University root node

School of Civil Engineering

Materials Today: Proceedings

An experimental study on rice husk ash concrete

School of Computer Engineering & Technology

2022 IEEE Pune Section International Conference, PuneCon 2022

Personality Prediction with Natural Language Processing using Questionnaire Responses

School of Electronics & Communication Engineering

Innovations in Electrical and Electronic Engineering: Proceedings of ICEEE …

Dual-Band Antenna Design at Sub-6 GHz and Millimeter Wave Band for 5G Application

School of Mechanical Engineering

Lecture Notes in Mechanical Engineering

Mechanical Behavior of Nylon Load Bearing Structures Fabricated by Fused Deposition Modeling

Construction of steel buildings is increasing very rapidly due to its strength, flexibility, recyclable nature, longer span, no limitation in size of components and more seismic resistance capacity as compared to concrete buildings. A Pre-Engineered Building (PEB) refers to a building which is engineered at a factory as per the specifications, codes and the loads that will be acting on the structure before production of the building components and then finally assembled at site thereby reducing the completion time. The concept of PEB involves predesigning and prefabrication process. The material usage in PEB is optimized by matching the frame geometry with the bending moment diagram's shape, which reduces the overall weight of the structure. In the present study, a review on the analysis and design of PEB structure is presented. The study discusses the various components of the PEB system and provides a detailed step to model PEB structures. From the past studies, it has been found that PEB structures are up to 50% lighter due to the usage of tapered I-sections and cold formed “Z” &amp; “C” sections, approximately 35% cheaper as compared to the conventional steel structures and show reduced lateral and vertical displacements when subjected to the seismic loading and can be constructed in half the time taken for conventional steel buildings (CSB). PEB gives a better output from the architectural point of view with large clear spans &amp; flexibility in future expansion. It has also been found that construction of PEB is more sustainable, environment friendly and economical than CSB.1 © 2022

A state of art review on analysis and design of pre-engineered buildings

With constant research in the last decade, Object Detection has become one of the rapidly evolving sub-fields of Deep Learning. As a result, the complexity and applications of Object Detection models have grown, necessitating larger datasets and multi-format labelled annotations for training and testing. To aid with the annotation work, a variety of tools based on various technologies, techniques, and features have been developed. However, some of the tools only cater to specific standards, requirements and problem domain. Researchers have observed that a drop in the quality of labelled annotations can have unintended consequences for model performance. This study provides an overview of various annotation tools with the goal of assisting researchers in determining the appropriate tool for their needs. The work will also serve as a reference for developers as they work on subsequent features to improve or create new tools. © 2022 IEEE.

Proceedings - International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

A Review of Image Annotation Tools for Object Detection

Synthetic fibers were used as reinforcements for a long period of time due to their excellent properties and compatibility with natural rubbers. Tensile properties and manufacturability of natural fabrics- Jute and Bamboo are studied. Layer by layer type of composite was manufactured by compression moulding and the crosslinking of matrix and reinforcement was done by using chemlok 250 as adhesive. Properties obtained from the tests are given in this paper. Production was carried out in two stages, 1st stage was by using adhesive and the results were compared and based on these results 2nd stage of manufacturing was carried out without using adhesive and specimens of ASTM D412 standard die type A was obtained by water jet cutting. Tensile test was carried out on the basis of ASTM D412 standard. Results show that the strength of bamboo fabric as reinforcement increases the strength of material and can be used in many applications. Short fibers are always used as reinforcement in polymers for increasing their mechanical properties; one can also use the fabrics as reinforcement in different fields to increase the mechanical properties of the composites. © 2022 Elsevier Ltd. All rights reserved.

School of Polymer Engineering

Uniaxial tensile properties for bamboo and jute fabric reinforced natural rubber

In the field of remote sensing satellite imagery, malfunctions in the available raw data are prominent. Especially in Short-Wave Infrared (SWIR) detectors used in satellite imaging cameras, which suffer from dropouts in pixel and line direction in raw data. With the recent development in generative adversarial networks and its vast application in inpainting the missing data, the possibility to predict and fill in the missing data accurately with contextual attention has become prevalent. This paper presents SN-GANs (SN-generative adversarial networks) which is two-staged architecture, and it is based on the concept of feed forward neural networks with contextual attention layers. While reconstructing the corrupted part of the images, the model takes surrounding pixels into consideration. Moreover, this architecture is adept enough to fill in the multiple lines and pixel dropouts efficiently even in super-resolution satellite images. The available traditional methods fail to address the loss of data that incurs, while inpainting a 16-bit raw image because they are effective enough for 8-bit RGB images. SN-GANs have effectively resolved this issue with a lossless image inpainting method for 16-bit satellite images as it retains the features of non-corrupted data. The performance of the model is evaluated using similarity metrics like structural similarity index measure (SSIM), peak signal-to-noise ratio (PSNR) and mean-squared error (MSE). © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Lecture Notes in Networks and Systems

Reconstruction of Missing Data in Satellite Imagery Using SN-GANs

A huge population of India is dependent on agriculture as their primary source of livelihood. The financial growth of India depends on the GDP (gross domestic product) rate of the agricultural commodities. Since dragon fruit is in high demand both domestically and globally, dragon fruit plantations are economical for small scale to large scale growers and businesses. There is a heavy focus on each stage of the fruit’s development because prolonged or premature harvesting of the fruit can result in food decay and can also impact the India’s economic growth. Farmers are still making use of manual methods of grading fruit maturity and identifying disease ridden crops, which can result in poor grading due to weariness and misjudgment. The article proposes the use of region-based convolutional neural network, a deep learning algorithm for detection and classification of common dragon fruit diseases and detection of dragon fruit maturity. There are three key steps to this process of detection and classification. The first step includes identification of several regions of interest, which are the bounding box candidates using selective search. A broad convolutional neural network extracts features from each region in the second step. The last step performs grouping of support vector machine (SVM) that tries to classify the regions for the classification of different dragon fruit diseases and detecting its maturity. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Detection and Classification of Diseases and Maturity of Dragon Fruits

Agro-industrial waste material such as non-edible deoiled Castor bean cake (CBC) is one of the most abundant sources for bioethanol demonstrating the feasibility of utilizing bioethanol as commercial biofuel. This is an alternative to mitigate fossil fuel dependence and carbon dioxide accumulation in the atmosphere. The CBC was pretreated with the help of thionyl chloride at a temperature of 35 °C for residence time 25 min. Subsequently, CBC substrate obtained from pretreatment was subjected to enzymatic hydrolysis with T. viride concentration varying from 0.5 to 5 g L−1 at 35 °C, pH 6 for 48 h. Under optimized conditions the process integrating pretreatment followed by enzymatic hydrolysis for 48 h at 35 °C with pH 7 resulted in 76 g L−1 of reducing sugars from 100 g CBC. The obtained sugar was further fermented at 30 °C for 72 h with saccharomyces cerevisiae as a fermenting media which yields 37.5 g L−1 of bioethanol. A study of different particle sizes of CBC with BSS-5, BSS-10, BSS-20 was done for efficient enzymatic hydrolysis and fermentation into bioethanol. On a pilot-scale 375 g L−1 of bioethanol was obtained from 1 kg of CBC with the same reaction conditions. The present study demonstrates optimized solid: liquid ratio 1:2 for hydrolysis, fermentation process, and the production cost for bioethanol per L. Figure S1 represents graphical abstract for the production of bioethanol from CBC in supplementary information. © 2022 The Author(s)