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

School of Computer Engineering & Technology

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Engineering and Technology

INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH \& TECHNOLOGY (IJERT)

Study on Cyber Warfare During 2001-2019

Comparative Study of PC and Gaming Console for Video Games

Nanotechnology in Wearable Electronics

Virtual Personal Assistants

Intelligent Content-Based Hybrid Cryptography Architecture for Securing File Storage Over Cloud

International Journal of Wireless Network Security

Advanced AQM Blue Algorithm in Wireless Network

Cryptography at its very core is nothing but math - pure, simple, undiluted math. Math created algorithms that are basics for various encryption algorithm. Encryption is a method in which user’s confidential data or private data is encoded to cipher text and this text can be read only if it is decrypted by authorized user using the right key. Cipher text can be decoded back to plain text, only by the authorized users using a right key. Various encryption algorithm are used to encrypt the plain text to cipher text and the cipher text is decrypted back to plain text by authorized user using right key. The symmetric key algorithm uses the same key to encrypt the plain text and decrypt the cipher text. In this paper we have proposed new symmetric algorithm using ASCII value. The plain text using key and ASCII values is converted to cipher text. Encryption algorithm sends cipher text and minimum value to the authorized receiver. Receiver decrypts the cipher text to plain text using same key and minimum value. In this algorithm sequence of five pseudo random number is generated and sum of this five pseudo random number is added to the obtained decimal value. Seed to generate common sequence of pseudo random number is kept secret between sender and receiver. Proposed algorithm support variable key length and plain text size. This algorithms performs faster when text is small message, but the execution time increases as the plain text size increases. This algorithm can be used to send small messages in a secured way. .

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International Journal of Recent Technology and Engineering (IJRTE)

Symmetric Encryption Algorithm using ASCII Values

Obesity is becoming one of the prevalent lifestyle diseases across the globe; need to be deal with behavioral intervention through self-management and motivation in line with rigorous physical exercise. When it is a matter to handle obesity to regain the health, parameters like: self-motivation, self-control, guided treatment, counseling, monitored exercise, and medical assistance are essential in consideration list. Paper proposes the model encompassing three-dimensional care including nutritional intake, counseling, and gait monitoring during exercise. Considering the effect of obesity on biomechanics of foot, gait pattern analysis of obese person provides greater information regarding variations in spatio-temporal parameters. Ever-increasing contribution of behavioral intervention will maintain the line of action in the perfect direction. A selection of accelerometer, gyroscope, and electromyography sensors is appropriate for the cause to derive basic hardware. MSP430 processor and ZigBee module are used for processing information and establishing communication. Within close proximity and placement of nodes at a different level, nodes are able to achieve 90–94% packet delivery ratio in actual environment compare to the 100% packet delivery in simulation environment. Result suggests that with the adaption of accurate classification process, system could be useful for controlled exercise monitoring or for daily activity monitoring, which is working at low-power level with affordable wearable technology in achieving wellness. © Springer Nature Singapore Pte Ltd 2020.

Advances in Intelligent Systems and Computing

Achieving Wellness by Monitoring the Gait Pattern with Behavioral Intervention for Lifestyle Diseases

Facial based human age estimation has become popular now a days due to tremendous increase in real time applications. Age estimation process comes with various challenges such as variation in lighting conditions, poses and facial expression. Performance of age estimation is evaluated with the help of measure 'Mean Absolute Error' (MAE). Main purpose of this work is improving facial based age estimation accuracy by building a Neural Network (NN). Beauty of NN is it learns nonlinear features of input data efficiently. For building NN model input images undergoes preprocessing, feature extraction, training and testing phases. NN model is built by providing training using various training algorithms. For prediction of age estimation neural network have shown superior performance for trainlm algorithm as compared to trainscg and traingdm algorithm. Experimentation are performed on partitioned training images and evaluated on testing images. We achieved low mean absolute error of 4.53 for 70 percent training images dataset.

Indian journal of computer science & Engineering

Gabor Feature Extraction driven facial age estimation using multilayer perceptron neural network

Synthesizing three-dimensional objects from single or multiple two-dimensional views has been a challenging task. To combat this, several techniques involving Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs), and Recurrent Neural Network (RNN) have been proposed. Since its advent in 2014, there has been a tremendous amount of research done in the area of Generative Adversarial Networks (GANs). Among the various applications of GANs, image synthesis has shown great potential due to the power of two deep neural networks—generator and discriminator, trained in a competitive way, which are able to produce reasonably realistic images. Formulation of 3D-GANs—which are able to generate three-dimensional objects from multiple two-dimensional views with impressive accuracy—has emerged as a promising solution to the aforementioned issue. This paper provides a comprehensive analysis of deep learning methods used in generating three-dimensional objects, reviews the different models and frameworks for three-dimensional object generation, and discusses some evaluation metrics and future research direction in using GANs as an alternative for simultaneous localization and environment mapping as well as leveraging the power of GANs to revolutionize the field of education and medicine. © 2020, Springer Nature Singapore Pte Ltd.

Generative Adversarial Networks as an Advancement in 2D to 3D Reconstruction Techniques