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

School of Computer Engineering & Technology

World University root node

International Journal of Grid and Distributed Computing 14 (Vol. 14 No. 1 {\ldots}

A Survey Paper on Water Conservation Methodologies Using IOT and Sensors

This study has been undertaken to indicate the benefits of using flutter over other app development platforms. It consists of working of different platforms and their role in application development. In today's world ease of development is the thing all developers are looking for and flutter has come up with the required platform to support development of applications for both Android and iOS. Developers are enforced to either construct the same application numerous times for various OS (operating systems) or accept a low-quality similar solution that trades native speed and accuracy for portability. Flutter is an open-source SDK for developing high-performance and more reliable mobile applications for operating systems like iOS and Android.

International Journal of Creative Research Thoughts

Comparison of Flutter with Other Development Platforms

Lean-burn combustion using higher spark energy can enhance the combustion characteristics and emission performance. A laser is electrodeless with a high energy ignition source and can achieve multi-point ignition easily. This paper presents the computational fluid dynamics (CFD) modeling of combustion of methane-air and hydrogen-air mixture in a constant volume combustion chamber (CVCC) by using multi-point laser-induced spark ignition (LISI). The numerical simulation is carried out using ANSYS Fluent software and a standard turbulence model (k–$\epsilon$) is used. The pressure-time history and reaction progress was plotted for various equivalence ratios (ϕ). Numerical result shows that multi-point ignition can completely burn methane-air and hydrogen-air mixture in the range of 0.77 to 1.68 and 0.36 to 4.1, respectively. The maximum peak pressure (Pmax) and shortest combustion duration were observed at ϕ of 1.29 for the methane-air mixture and ϕ of 1.0 for the hydrogen-air mixture. The relative error between the numerical and the experimental results from the literature are within 10%. The faster reaction progress was observed for the hydrogen-air mixture compared to the methane-air mixture for all equivalence ratios. Finally, the validated numerical model was used to predict the CO, CO2 and NOx emission trends. For the methane-air mixture, CO emission increases as the equivalence ratio increases. However, the maximum CO2 emissions were observed at stoichiometric conditions. The highest NOx emissions were observed for the hydrogen-air mixture compared to the methane-air mixture at a stoichiometric equivalence ratio.

School of Mechanical Engineering

Energy Sources, Part A: Recovery, Utilization and Environmental Effects

Numerical simulation of combustion characteristics and emission predictions of methane-air and hydrogen-air mixtures in a constant volume combustion chamber using multi-point laser-induced spark ignition

Materials Today: Proceedings

Recent advances on the antibacterial coating on titanium implant by micro-Arc oxidation process

The grape cluster identification and its segmentation for the sake of total weight prediction task of wine yard shows the need of segmentation atomization with better accuracy. The challenge of grape cluster segmentation is considered to provide solutions using deep neural network models such as YOLO v3, Mask RCNN, U-net. This paper contributes in terms of the modified U-net model for the segmentation of grape clusters using training and testing strategy for the validation of the results. The results are obtained for the accuracy of the classification of pixels as part of grape cluster or outside of clusters and comparative results show improvement in segmentation using modified U-net. The accuracy, precision and recall analysis is performed and the comparatively proposed model shows better results

School of Electronics & Communication Engineering

INFORMATION TECHNOLOGY IN INDUSTRY

COMPARATIVE ANALYSIS OF DEEP LEARNING ARCHITECTURES FOR GRAPE CLUSTER INSTANCE SEGMENTATION

The hand sign language uses visual-manual modality to share a certain message. Specially abled people having hearing and speaking disabilities interact more naturally in hand sign language rather than verbal language. According to one of the Census study, 2.21% out of 121 crore population in India are 'disabled', out of which 19% are having a hearing disability and 7% are having speech disability. Since everyone cannot communicate in sign language as it is a lesser-known language, it often leads to communication gap. So, the automated Sign Language Interpreter (SLI) helps to meet this communication gap as a manual sign language translator is not a convenient option because of its privacy issues and lack of availability. This paper proposes an Indian Hand Sign Language Interpreter which operates upon a vision-based approach that uses Machine Learning and Deep Learning techniques to locate the hand gesture region accurately for extracting the features and finally interpreting the respective meaning. The experimentation for performance metrics such as accuracy and loss using various activation functions helped to analyzed the performance of the model. The system successfully identifies a number of hand spelled words and thus eases the communication among people. © 2021 IEEE.

2021 IEEE Pune Section International Conference, PuneCon 2021

Interpretation of Hand Spelled Banking Helpdesk Terms for Deaf and Dumb Using Deep Learning

At present, India has the largest population of below 14 years children in the Asia Pacific. With the increasing birth rate, critical Pneumonia cases have been referred to Neonatal Hospital for treatment. As the number of adults in India who have tested positive for COVID-19 has grown, so has the number of children who have contracted it. However, we haven't noticed a dramatic increase in the number of children infected with COVID-19 across the country. It's important to note that, unlike the previous wave, the second wave is more likely to infect whole homes. We must be vigilant and adhere to COVID-19's recommended practices. The current study says that the mortality rate of Pneumonia and Covid-19 infection in rural areas is high. Radiology plays a vital role to diagnose Pneumonia by the examination of X-Ray images. Over the years CNN Architectures have evolved and now produce appreciable accuracy (over 85%) for classification tasks. This has promoted the use of CNN Architectures in the field of medicine, especially for classification tasks such as disease detection from x-rays. This implementation evaluates the performance of four popular CNN Architectures viz. VGG16, ResNet50V2, InceptionV3 and MobileNetV2. The implementation will classify x-ray images into normal, covid, and pneumonia and then compare the performance of the aforementioned models over the accuracy, Area under the curve (AUC), precision, recall metrics. © 2021 IEEE.

Proceedings of the IEEE International Conference Image Information Processing

Comparison and Evaluation of CNN Architectures for Classification of Covid-19 and Pneumonia

In today's era of communication, sharing of information is unavoidable. Analysis of security and reliability while communicating is essential. Information may get altered, copied and copyright can be infringed. Previously, digital watermarking and different encryption techniques like AES, DES, HASH and MAC were used as a primary security technique for information hiding. But, in all these methods, there are some vulnerabilities, because of which information may be hacked or changed while transmission. In addition to the security of the information, there should also be an error-free transmission of data. This review paper discusses various image encryption techniques which are using joint error correction and encryption methods. Based on the literature review, a novel method for joint encryption and encoding is suggested. Low-Density Parity-Check (LDPC) code, a highly recommended technique in 5G, is used for reliability. Chaotic sequence based on a logistic map is used for security. Proposed technique also uses the S-Box of AES algorithm for enhancing the security obtained by combining LDPC and Chaotic sequence. This paper aims to provide a general overview of image encryption techniques. Based on the study, a new system for joint encryption and encoding using LDPC, Chaotic map and AES S-Box is suggested. © 2021 IEEE.

Proceedings of IEEE International Conference on Signal Processing,Computing and Control

Review of Joint Encoding and Encryption for Image Transmission using Chaotic Map, LDPC and AES Encryption

The objective of this paper is to ease the designing of mechanical spring, reduce calculation time, and improve accuracy and optimization in design using a Knowledge-based Engineering approach. The Application programming interface (API) was programmed using Java on the NetBeans IDE, which provides a variety of tools to build applications. Several standard reference books, research papers, and links were studied to finalize the formulae and factors like materials of the springs. The design for a user-friendly Graphic User Interface (GUI) was made considering the input and output values. To examine the API, we tested it with some numerical problem statements for each spring. From the results obtained, it was observed to have 0 to 3% of the error, when compared with manual calculations. The objectives of the calculator were achieved as the time of calculations was reduced by 95%. Other aims of accuracy and efficiency desired were fulfilled too. As a result of all this, the overall cost, errors, and complexities of mechanical components design are also reduced. The findings prove that this API can be a quick and efficient method to choose the spring of desired requirements for spring manufacturers and designers as it enhances design assistance. The API aids Design Automation and CAD Customization. The API calculator displays if the designed spring is safe and if a guide is required. The user can choose materials and can customize the calculator as required. © 2021 Author(s).

AIP Conference Proceedings

Optimization in spring design using knowledge based engineering approach

Human beings when born are adorned with a presence that helps them to differentiate among other individuals around ie. 'Face'. Alongside speech and fingerprints, A face is significantly used in biometrics as no two individuals have the same face. Myths though say that in this world you may resemble with some facial characteristics to 7 different individuals then these facial detection and recognition algorithms help us to identify between them. Facial expressions detection, face detection, and recognition have been impactful in the research domain especially in fields of image processing. Although it might sound like a cakewalk though undoubtedly it has proven to be a complex task for a computer to detect and pose all the features of the image passed since various other variables impair the accuracy/confidence of the algorithms mainly illumination variation, the background noise of the image, low resolution, occlusion, blurriness of the image, pixel scale of the image and many more components.Considering these myths, this research is based upon face recognition algorithms and a model to identify if there is a face in an image passed, identify the number of faces, and justify with confidence value obtained which algorithm should be suggested, is most optimum for face detection and recognition among (Haar classifiers, default face recognizer, Local Binary Pattern Histogram (LBPH) face recognizers, {Adaboost algorithm, Eigenface methods, etc.). This research particularly focuses on the use of Haar cascades and the LBPH Face recognizer algorithm as a hybrid combination for the smart voting system as an authentication approach. © 2021 IEEE.}, author_keywords={Face detection; Face Recognition; Haar cascade Classifier; Image processing; LBPH Face Recognizer; Smart Voting system}, keywords={Adaptive boosting; Image classification; Voting machines, Face detection and recognition; Face recognition systems; Faces detection; Haar cascade classifiers; Haar classifiers; Images processing; Local binary pattern histogram face recognizer; Local binary patterns; Smart voting system; Voting systems, Face recognition}, publisher={Institute of Electrical and Electronics Engineers Inc.}, isbn={9781665425032}, language={English}, abbrev_source_title={Int. Conf. Smart Gener. Comput., Commun. Netw., SMART GENCON}, document_type={Conference Paper}, source={Scopus},