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 paper, details of testing wind turbine in a laboratory are given. For testing the wind generator in a laboratory, bicycle along with the gearbox is used. The bicycle is used as a prime mover. There is no need of wind flow to test the wind turbine. The need of motor as a prime mover is also eliminated in this method. With help of gear box, required speed of the generator may be obtained. There is no need to wait for sufficient wind speed to rotate the generator. The need of electricity to test the generator is eliminated. Various generators may be tested using this method. The mechanisms are very simple. Less skilled workers may work on the test set up to test the wind turbines. © 2017 IEEE.

World University root node

School of Electrical Engineering

2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017

Use of bicycle and gear box for testing of wind generator model

This Paper is related to the production of artificial turbulence in the test set up. I in this test set up the impact of turbulence intensity on the flicker initiated in the wind turbine output can be studied. In this test set up the blower fans are fitted on all sides of the test set up. The speed of each fan can be controlled with help of a speed regulator. The wind turbine model is kept in the test set up. The desired blower fans are started. The speed of the wind turbine is measured with help of the anemometer provided. The direction of the wind can be observed with help of the smoke gun provided. The output voltage waveform can be observed on the digital storage oscilloscope. The impact of turbulence on the flicker initiated in the turbine output voltage can be observed. Swiveling wheels are provided to the test set up. So the test set up is mobile and can be moves easily in the laboratory. © 2017 IEEE.

Wind turbine model testing using all side fans arrangement to create turbulence

Video error concealment is an error hiding Technique. Recently there is need of Error Concealment in video applications. Video applications are widely used in many domains such internet videos, entertainment media such as TV and DVD, video conferencing, video surveillance etc. In this paper, Video Error Concealment is achieved by Moment Invariance using MATLAB. Error is detected using moment invariance and corrected by using block matching algorithm. In Moment Invariance method, error frame is divided into macroblocks of size 16∗16 and that is compared with the macro block of previous frame. Moment invariance algorithm is carried out in three steps. The first step is designation of candidate motion vector set. The second step is to adaptively determine the error in the current and reference frame for feature extraction. The last step is to find the error function calculation using Moment Invariance. The quality of the video is analyzed using Structural Similarity Index (SSIM) and Peak Signal to Noise Ratio (PSNR). Result indicates that quality is improved for different error videos. © 2017 IEEE.

School of Electronics & Communication Engineering

2017 International Conference on Computing, Communication, Control and Automation, ICCUBEA 2017

Video Error Concealment using Moment Invariance

Many gazettes, toys, sensors, instruments, etc., devices are mushrooming in the electronics market these days which are running with different operating systems and application frameworks. In Mobile phones also many platforms are available with its own stack, right from hardware level to application level. So it is difficult to all the mobile phones or devices with same characteristics, performance, and features. The conclusive success of a platform entirely depends on its security to the user data ultimately, it constructs the global market. We present here a comparative study of four Mobile Operating Systems architecture and security perspectives of each. Moreover, experiments are carried out with Windows and android smartphone to study the cryptographic performance in these devices which plays as decisive parameters for future applications and system developers to implement secured devices and applications. We show that although algorithms characteristics are fixed, due to different architectures and dependencies in different devices with different operating systems, same efficiency, and performance is not guaranteed by cryptographic as well as other data structure algorithms. © 2018, Springer Nature Singapore Pte Ltd.

School of Computer Engineering & Technology

Intelligent Computing and Information and Communication

Issues of Cryptographic Performance in Resource-Constrained Devices: An Experimental Study

For recommending the best result to the user as per his requirement, User Profiling plays an important role. In user profiling, the profiles are created from the past data of same user. Maintaining the security and privacy of this data becomes a big challenge for researchers. Here, we are proposing the algorithm for privacy and security purpose of different profiles, with the integration of Information Dispersal Algorithm. The use of vast data of profiles by the user from any location at any time would be achieved by the use of the private cloud. As the profiles of different devices are maintained on the central cloud server, the recommendation for user for particular device can be executed easily. © Springer Nature Singapore Pte Ltd. 2018.

Information and communication technology for sustainable development

Proposed use of information dispersal algorithm in user profiling

The main objective of this paper was to propose cloud supporter framework to support cloud for processing multiple tasks. Because of multiple tasks on cloud server, it works slower and sometimes gets failed. In this situation distributing or scheduling of tasks on the distributed computing system is the only solution to reduce workload on server. Computing capability of smart phones CPU can compete with the CPU of the computers. Smart phones are energy-efficient and cost-effective alternative to running certain tasks of traditional servers. Distributing tasks for computations must utilize all the resources equally, no resource should be under or over utilize this problem leads to focus on the load balancing technique to support the cloud for processing tasks. Our approach is to form a load balancing frame work as cloud supporter for processing tasks on smart phones when they are plugged into the power sources.

2018 3rd International Conference for Convergence in Technology, I2CT 2018

A Load Balancing Framework in Cloud to Support Task Processing Using Smartphone with CWC

Texture image classification is very useful in many domains. It has been tried using statistical., spectral and structural approaches. A novel Pixel N-grams technique has emerged for image feature extraction recently. The aim of this paper is to analyse the efficacy of Pixel N-grams technique for texture image classification in comparison with the traditional techniques namely Intensity histogram., Haralick's features based on co-occurrence matrix and state-of-the-art Bag-of-Visual-Words (BoVW). The experiments were carried out on the benchmark UIUC texture dataset using SVM classifier. The classification performance was compared using Fscore., Recall and Precision. The classification results using Pixel N-gram were significantly better than that using Intensity histogram and Haralick features whereas., they were comparable with the BoVwapproach.

Comparison of Pixel N-Grams with Histogram, Haralick's features and Bag-of-Visual-Words for Texture Image Classification

The automatic detection and recognition of anomalous events in crowded and complex scenes on video are the research objectives of this paper. The main challenge in this system is to create models for detecting such events due to their changeability and the territory of the context of the scenes. Due to these challenges, this paper proposed a novel HOME FAST (Histogram of Orientation, Magnitude, and Entropy with Fast Accelerated Segment Test) spatiotemporal feature extraction approach based on optical flow information to capture anomalies. This descriptor performs the video analysis within the smart surveillance domain and detects anomalies. In deep learning, the training step learns all the normal patterns from the high-level and low-level information. The events are described in testing and, if they differ from the normal pattern, are considered as anomalous. The overall proposed system robustly identifies both local and global abnormal events from complex scenes and solves the problem of detection under various transformations with respect to the state-of-the-art approaches. The performance assessment of the simulation outcome validated that the projected model could handle different anomalous events in a crowded scene and automatically recognize anomalous events with success.