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

At the time of World War-II with advent of fighter planes Heads-Up display (HUD) were invented to assist pilot with their targets and navigation. Heads up display is a device which have a transparent display on which information is displayed, it is kept right in line of sight of driver or pilot. With advancement of technology the automobiles are equipped with features and machinery for making driving safe and comfortable example automatic windows, speedometer, milometer and displays for navigation etc. The equipment for driver navigation assistance are usually placed on dashboard of car. To see the information on display each time driver has to shift his focus from the road to the dashboard, which is if not fatal can be dangerous. To overcome the above mentioned problem Heads-Up display can be the solution. In this paper an economical prototype of HUD is presented which displays the symbols turn by turn with the other useful information for navigation on a transparent screen which is placed in line of sight of driver. Compared to existing complex, expensive HUD which are not in the reach of masses due their high cost, the innovative prototype of HUD is presented. The HUD proposed takes the advantage of mobile phones capability for building low cost system. The mobile application with the Arduino Uno, Bluetooth module and 2.8″ TFT are used to create this gadget. This paper also present the results of the experiment performed to check the effectiveness of system. © 2016 IEEE.

World University root node

Engineering and Technology

International Conference on Computing, Analytics and Security Trends, CAST 2016

A prototype of low cost heads up display for automobiles navigation system

People are delimited by abundance use of wireless computing and communication devices that are connected via wireless technology in an overlay network. Wireless sensor networks (WSNs) have gained much attention in both public and research communities as they are expected to bring the communication between humans, environment, and machines to a new paradigm. Wireless networks gradually need to self-organize and become accustomed to new conditions for ease in management and operation. In this article, we have considered an application of traffic management for smart city. The implementation of sensors for such an application needs long life of sensors. Clustering of sensor nodes can be used for energy conservation in WSN. We have proposed a framework of self-organized wireless sensor network (SOWSN) implemented the algorithm for clustering of nodes based on residual energy of nodes and node distance to minimize the average energy consumption. We will also study the effect of node distance on energy consumption. © Springer Science+Business Media Singapore 2017.

Advances in Intelligent Systems and Computing

Energy-efficient self-organization wireless sensor network for traffic management in smart cities

Liquid–liquid equilibrium data for the system consisting of toluene, n-heptane and Aliquat 336 ionic liquid was obtained at 303.15 K and atmospheric pressure. The values of distribution coefficient and selectivity were evaluated. Mathematical model relating distribution coefficient and dispersion, dipolar interaction and hydrogen bonding has been developed. Hansen’s solubility parameters were used to determine the parameters. The model was applied for various ionic liquids as solvents. The model predicted the trends similar to the trend reported in the literature. Thus model can predict better solvent for the given extraction application. This methodology has great potential to act as a knowledge-based framework to aid development of new tailor-made solvents. This will save cost and time in experimentation and analysis.

School of Chemical Engineering

Separation Science and Technology

Extraction of toluene and n- heptane mixture using ionic liquid Aliquat 336 and mathematical modeling for solvent selection

Currently Internet usage has increased a lot due to bandwidth availaility and technology advancements. Internet is widely used for knowledge sharing, online review of products etc. Many open forums, blogs are used for this purpose. Since many users are contributing their opinions towards any query submitted by information seeker, there is a possibility of confusion. Often opinions contradict with each other creating confusion in information seeker's mind. In these cases role of Opinion Leader(s) is very prominent. Opinion Leader is a person who has knowledge in the particular field, who's opinion makes difference and who can influence other's opinions. Identification of a person who has great experiences and/or knowledge, in a particular domain, is very helpful and useful in decision making, product marketing etc. This paper presents an approach for identification of Opinion Leader(s) using modified SPEAR (Spamming Resistant Expertise Analysis and Ranking) algorithm. The expertise of user is found out on different topics. Modified SPEAR algorithm effectively identifies Opinion Leader(s) by making use of additional influence measures in the form of credit score functions. It also analyses these measures and studies their effects while ranking the Opinion Leader(s) effectively. © 2016 IEEE.

Identification of topic-specific Opinion Leader using SPEAR algorithm in Online Knowledge communities

Hadoop MapReduce has been proved to be an efficient model for distributed data processing. This model is widely used by different service providers, which create a challenge of maintaining same efficiency and performance level in different systems. One of the most critical problems for this model is how to overcome heterogeneity and scalability in different systems. The decreases of performance in heterogeneous environment occur due to inefficient scheduling of Map and Reduce tasks. Another important problem is how to minimize master node overhead and network traffic created by scheduling algorithm. In this paper, we introduce a lightweight adaptive scheduler in which we provide the classifier with information about jobs requirement and node capabilities. The scheduler classifies jobs into executable and nonexecutable according to the nodes capabilities. Then the scheduler assigns the tasks to appropriate nodes in the cluster to get highest performance. © Springer Science+Business Media Singapore 2017.

An adaptive Mapreduce scheduler for scalable heterogeneous systems

Recently, many online attacks have increased due to the growing use of the Internet, Among these the most well-known attack is phishing. Phishing is a demonstration of getting delicate data by persuading the users to uncover their own data by pretending as a trusty source in the web transaction. Most phishing attacks work by sending a forged email that contains a URL which leads you to the fake website by clicking on it. In most of the cases, phisher chooses http URLs for the attack. Along these lines, we are proposing a novel algorithm which will detect whether a given http URL is of phishing site or not. Our algorithm performs Google's updated blacklist check, utilizes Google search engine results, Alexa Ranking and no of URL-based features, for detecting phishing URLs. It displays alert message if the URL found as possible phishing, otherwise it displays safe message. This algorithm enhances the performance when dealing with known/old phishing URLs. © 2016 IEEE.

International Conference on Automatic Control and Dynamic Optimization Techniques, ICACDOT 2016

A novel algorithm to detect phishing URLs

In this era, the web usage mining plays one of the important role in analyzing and improving performance of web applications. Initially in this paper, the concept of web usage mining has been introduced along with Improved AprioriAll algorithm which is the base algorithm for the proposed tool along with its limitation. The improved approach is discussed which integrates sequential pattern mining with graph theory. In the next part, design of web usage mining tool with improved approach is discussed. Implementation details of the tool are discussed along with the results. The last part covers how the raw result from the proposed tool can be further visualized and analyzed using new technologies like D3.js and Neo4j. The future scope of the proposed tool is mentioned at the end of the paper. © 2017 IEEE.

Proceedings - 1st International Conference on Intelligent Systems and Information Management, ICISIM 2017

Web usage mining tool by integrating sequential pattern mining with graph theory

Over the last decade social media platforms such as Facebook and Twitter have gained huge popularity. Usage of social media sites has increased leaps and bounds. An organization or institute can make use of the data obtained from various such social networking sites to their benefit. Digital Identity created by any person/customer on such sites can be targeted by the organization or institute for promoting their services as well as to target some new customers, thus providing them new business opportunities. Thus it can be a win-win situation for both the parties-the organization gets opportunity to increase their business footprint and the customers may be more than happy with the personalized offers from the organization. In this paper, we propose a method to understand customer's likings using public APIs made available by the social network sites such as Twitter and Facebook. As there is huge concern regarding privacy of data on social media, we have used only the data made available publicly by these platforms without using any unethical tools or methods. © 2016 IEEE.

Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2016

Digital identity based recommendation system using social media

Cloud computing nowadays are gaining high importance from government services, private users and public sectors. The rise in cloud computing is due to the provided facilities such as flexibility, disaster recovery, security, etc. Moving data into cloud servers provide great convenience to users because they just have to upload their data and not care about the hardware management and security. But, the sensitive or privacy relevant data has some major implications. The techniques used so far for storage security are the cryptographic methods and some compression techniques such as compression sensing, JPEG compression technique, etc. to make more space for future data. In this paper we propose a system so that the cloud storage can be made more secure. To increase the efficiency, we are using DCT algorithm for compression and AES for encryption. The main concept of the proposed system is to increase the security so we are splitting the image in chunks. This Image splitting method, lowers the risk of image being retrieved by attacker as we upload the chunks instead of image. © 2017 IEEE.

2017 International Conference on Computer Communication and Informatics, ICCCI 2017

Image stack management and data access control for multi-authority cloud storage

Emotions are fundamental to human lives and their decision-making. Understanding an expression of emotional feeling between people forms an intricate web. There are systems, been developed that attempt to recognize aspects of emotion related behaviors and to respond to these, for example systems designed to improve the user experience or to change user behavior. The emotion recognition through facial images in recent times have proved to be an interesting topic for the researchers. Since two decades, a big research has been addressed to enhance Human Computer Interaction (HCI). There are a lot of applications and API-accessible software online that parallels the human ability to discern emotional behavior. The visual detection market is expanding enormously that can be seen noted from various system developed and described in this paper. This paper discuss various attributes, methods and emotional labels that are considered by various emotion API system. This paper also gives an overview of the databases available for inferring emotion through human facial features. The paper. © 2017 IEEE.