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

Image retrieval systems now a day's have more focus on searching desired image as a query. Search results are based on different contents of query image. Content based approach is more desirable as it neglects manual annotations of images. Systems aim at search and compare images based on similarity in color contents of query image. Comparison is performed by defining distance similarity measures between color histogram properties. Use of color features as important feature makes results more complete as search results and color contents are not affected by image resize and rotation operations. To extract color features of image we consider on color space, color reduction, color feature extraction process. Our image retrieval application aims at color feature comparison efficiency and accuracy. We aim at reduction in dimensions of local and global color feature which is possible through selection of proper quantization level. To define similarity in feature vector we applied Euclidean distance. Our experimental work shows that local hybrid color histogram produced more accurate image retrieval results than global color moments, color coherence vector and traditional color histogram.

World University root node

Engineering and Technology

Advances in Intelligent Systems and Computing

Local and Global Color Histogram Feature for Color Content-Based Image Retrieval System

Milk distribution and safety is of high concern as it involves the health of 90% of our society. Our project, milk distribution monitoring system targets the cold chain maintenance and milk spoilage avoidance. The system is based on Internet of Things and data mining. Traditionally milk is supplied in cans with minimum monitoring which may result in milk getting spoiled before its use specially during transportation at any point of time which causes vendors to know about milk spoilage only after the milk has been spoiled completely. To overcome these problems first data mining technique is employed to discover the routing plans so as to generate case-based routing plans for the drivers. Then the existing sensor based system will measure the pH value of milk and determine its quality. The system will direct to nearest milk booth with the highest proximity by using routing technique where data center serves as a cloud server to calculate the costs of a finding the nearest milk booth request, and these costs will be frequently updated by considering the location of van and the total number of milk booth in each areas whose data is accessible any time in the network. This routing algorithm will be used to offer a solution of finding an available milk booth if the PH value deviates from 6.7. This is implemented by a system prototype with wireless access in an open-source physical computing platform based on Ardiuno and using a smart phone that provides the communication and user interface for both the control system and the vehicles to verify the feasibility of the system. It will also give an alert SMS to vehicle driver so that collection of milk can be faster without more spoilage. This way it will maintain good quality and cost effective distribution of milk. © 2017 IEEE.

International Conference on Advances in Computing, Communication and Control 2017, ICAC3 2017

An Internet of Things (IOT) based monitoring system for efficient milk distribution

Due to increasing need of using distributed databases, high demand presents on sharing data to easily update and access the useful information without any interruption. The sharing of distributed databases causes a serious issue of securing information since the databases consist of sensitive personal information. To preserve the sensitive information and at the same time, releasing the useful information, a significant effort is made by the researchers under privacy preserving data publishing that have been receiving considerable attention in recent years. In this work, a new privacy measure, called c-mixture is introduced to maintain the privacy constraint without affecting utility of the database. In order to apply the proposed privacy measure to privacy preserving data publishing, a new algorithm called, CPGEN is developed using genetic algorithm and multi-objective constraints. The proposed multi-objective optimization considered the multiple privacy constraints along with the utility measurement to measure the importance. Also, the proposed CPGEN is adapted to handle the cold-start problem which commonly happened in distributed databases. The proposed algorithm is experimented with adult dataset and quantitative performance is analyzed using generalized information loss and average equivalence class size metric. From the experimentation, we proved that the proposed algorithm maintained the privacy and utility as compared with the existing algorithm.

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”C-mixture and multi-constraints based genetic algorithm forcollaborative data publishing

With the widespread technological development in the field of Wireless sensor network (WSN) and Internet of Things (IoT), provides various domain to take upon the challenges for new development of various applications. These technologies are utilized by layman without having awareness of, how they can use it for better results? FitnessMantra is the theme put forward in this paper, suggesting the collaborative architecture of Fitness Band, its inbound software, data analytics and Internet of Things. FitnessMantra is the solution set forth considering today's requirement of health monitoring. Paper looks after the issues of monitoring the walking activity (Gait Cycle Pattern) of patients under the process of rehabilitation after major/ critical leg surgeries. Architecture proposes collaborative working of Fitness band, data aggregation through related application, analysis of collected data and communication gateway for future updates. Typically used sensors for monitoring the walk is Accelerometer or pedometer. Further communication and analysis of data varies person by person. © 2017 IEEE.

2017 International Conference on Big Data, IoT and Data Science, BID 2017

Fitness mantra: Theme for health analysis in rehabilitation process

Mantra meditation is easy to practice. “OM” Mantra is the highest sacred symbol in Hinduism. The present study investigated the temporal dynamics of oscillatory changes after OM mantra meditation. Twenty-three naive meditators were asked to perform loud OM chanting for 30 min and the EEG were subsequently recorded with closed eyes before and after it. To obtain new insights into the nature of the EEG after OM chanting, EEG signals were analyzed using spectral domain analysis. Statistical analysis was performed using repeated measures of analysis of variance. It did not reveal any specific band involvement into OM mantra meditation. But significantly increase in theta power was found after meditation when averaged across all brain regions. This is the main effect of OM mantra meditation. However, the theta power showed higher theta amplitude after condition at all regions in comparison to the before condition of meditation. Finding was similar to other studies documenting reduction in cortical arousal during a state of relaxation. The study argues for the potential role of loud ‘OM’ chanting in offering relaxation. It provides a new perspective of meditation to the naive meditators. This information may help to demystify meditation and encourage those considering this as beneficial practice.

Applied psychophysiology and biofeedback

EEG spectral analysis on OM mantra meditation: A pilot study

The retail market is wide and has a lot of prospects to offer, may it be in terms of revenue or meeting the customer demands. Albeit the pros it is losing its daily or regular clientele because of the unnecessary overhead of going through the various aisles and racks to find the necessary product and then proceed to a lengthy procedure to checkout. This paper addresses one such major issue in a way that the customers benefit from and the retailers can easily increase and analyse the sales. The solution is achieved using a low energy Bluetooth Beacon that communicates with other Bluetooth devices that are within the range and hence acts as a locator. In this paper we also discuss the various use cases which can be applied in retail store to address the problems faced by the customer. Our focus is on minimal power/ resource consumption in all of the scenarios. We also discuss various algorithms and communication protocols to satisfy all the aspects of the problem statement.

2018 International Conference On Advances in Communication and Computing Technology, ICACCT 2018

Bluetooth Beacon Applications in Retail Market

Use of computer science in the field of medical gives the major importance to the world. Hence in the medical field we use the technology in order to help the doctor to diagnose the disease. In this paper we make use of the segmentation technique on the MRI (Magnetic Resonance Images) data to diagnose the osteoarthritis. Osteoarthritis is a knee joint disease and in this paper we are mainly focused on the cartilage degradation i.e., degrading the femur and tibia cartilage. Image Segmentation provides the analysis of the image and extracts the data in order to perform the operation on it. This paper lists out various image segmentation techniques, to perform the segmentation of the knee cartilage from magnetic resonance images (MRI). The segmentation technique by the rough fuzzy c means classifier which provides the degrade in cartilage region and the SVM (support vector Machine) technique is used to classify the degradation cartilage. © 2018 IEEE.

Proceedings - 2018 4th International Conference on Computing, Communication Control and Automation, ICCUBEA 2018

Image Segmentation for Detection of Knee Cartilage

All humans operating vehicles with several in-puts(steering wheel, pedals, gears etc.) do so in a unique way. We attempt to identify drivers based on this characteristic driving profile. Users were made to playa realistic 3D driving simulation, StuntRally. Their keypress events were logged. These logs were used to train and test different classifiers such as Support Vector Machine(SVM), K Nearest Neighbour(KNN) and Naive Bayes(NB). The SVM performed best with an average testing accuracy of 80 %. © 2018 IEEE.

2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT)

Driver Profiling Using Realistic Racing Games

Drowsiness is one of the most prevalent causes of car accidents, especially after drunk driving. There have been many studies to detect drowsiness while driving using different approaches. We propose a system which would efficiently detect drowsiness by integrating the real-Time EEG method of detection and our concept of individual-level Hypothesized Variable Speed Limit (HVSL). By studying the power spectral density obtained from the driver's EEG and the overall duration of the persistence of the alpha waves, it can be determined whether the driver is going into a state of drowsiness or not. In response to elongated time periods of persisting alpha waves, an alarm will be put off to alert the driver. The HVSL module would recommend an appropriate speed depending on environmental conditions as well as drowsy level, thus monitoring the vehicle speed. Hence, drowsiness detection can be combined with HVSL system to mitigate the chances of potential accidents. © 2018 IEEE.

2018 IEEE Punecon

Proposed System Based on EEG and VSL to Detect Drowsiness and Curb Accidents

This chapter emphasizes on retrieving user emotions from keyboard and mouse using different parameters. These parameters can be user keyboard typing style, mouse movements, and some physiological sensors are used. This field of retrieving emotions from machines comes under the field of affective computing. © 2018, Springer Nature Singapore Pte Ltd.