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

Medium of music has evolved specifically for the expression of emotions, and it is natural for us to organize music in terms of its emotional associations. Much of the difficulty in developing emotion-based features is the ambiguity of the ground-truth. Emotion recognition is an advanced trend in research field. Indian Classical music is an ancient tradition and also has very effective mathematical structure. In the field of emotion recognition, most of the work has been done on western music but very less on Indian Classical Music. In this paper, we are proposing a system which will help to recognize an emotion for Indian Classical Music. © 2017 IEEE.

World University root node

Engineering and Technology

Proceedings of the 2017 International Conference on Intelligent Computing and Control Systems, ICICCS 2017

A framework for emotion identification in music: Deep learning approach

Smart City concept is being adopted by many governments to implement sustainable solutions and improve the quality of life of the citizens. This paper presents a data oriented view of a smart city by studying the characteristics of data generated by various sources in the city. This data would be used to build smart city components related to transport, healthcare, energy and environment. Datafication of smart city reveals that the data to be managed is Big Data. Hence, we further review how big data can be used for smart city solutions, and provide a process flow and mapping for some of the smart city components. © 2017 IEEE.

2017 International Conference on Emerging Trends and Innovation in ICT, ICEI 2017

Data oriented view of a smart city: A big data approach

In real life scenario, facial expressions and emotions are nothing but responses to the external and internal events of human being. In human computer interaction, recognition of end user's expressions and emotions from the video streaming plays very important role. In such systems it is required to track the dynamic changes in human face movements quickly in order to deliver the required response system. The one real time application is physical fatigue detection based on facial detection and expressions such as driver fatigue detection in order to prevent the accidents on road. Face expression based physical fatigue analysis or detection is out of scope of this paper, but this paper reveal study on different methods those are presented recently for facial expression and/or emotions recognition using video. This paper presenting the methodologies in terms of feature extraction and classification used in facial expression and/or emotion recognition methods with their comparative study. The comparative study is done based on accuracy, implementation tool, advantages and disadvantages. The outcome of this paper is the current research gap and research challenges those are still open to solve for video based facial detection and recognition systems. The survey on recent methods is appropriately presented throughout this paper by considering future research works. © 2017 IEEE.

Proceedings of the International Conference on IoT in Social, Mobile, Analytics and Cloud, I-SMAC 2017

Study of video based facial expression and emotions recognition methods

There are several approaches to reduce the energy consumption. Among them, one approach which allows for reducing the transmission energy consumption is Delay Tolerant Networks (DTNs). Several techniques are adopted to optimize the energy efficiency. Adjusting the resource allocation and decreasing the equipment usages are the basic two categories, which are used to reduce the energy consumption. With the increasing data transmission rate the energy consumption increases, which result in the diminishing of its efficiency. So, it is a necessity to manage the trade-off between energy and performance in Delay Tolerant Networks. The DTN nodes commonly operate on low-power battery resource; hence, there is need of improving the energy efficiency by using appropriate technique to increase the lifetime of the node and also to increase the probability of delivering the bundle. For that purpose, this paper describes the various techniques to achieve energy efficiency in Delay Tolerant Networks. © Springer Nature Singapore Pte Ltd. 2017.

Lecture Notes in Networks and Systems

A Survey on Energy-Efficient Techniques to Reduce Energy Consumption in Delay Tolerant Networks

Self-Organized Wireless Sensor Network (SOWSN) is a system of sensor nodes that takes global decisions through local interactions without involvement of any central entity. Wireless sensor nodes have constrained processing capability and energy. The key characteristic used to evaluate performance of Wireless Sensor Network (WSN) is its lifetime which depends on residual energy of nodes; hence the major challenge in WSN is the efficient use of available energy. Node clustering saves energy and also shows self-organization because global decision like Cluster Head (CH) selection is taken through mutual communication between nodes. In this paper, a new clustering method based on self-organization is implemented to boost lifetime of WSN. Sensor network is divided into regions. Cluster formation relies on Residual Energy (RE) and nearest Distance (D) from CH. Node with highest residual energy becomes CH. Rest nodes join the nearest CH. Clusters are broken when residual energy of CH falls below threshold energy; causing the sensor network to get self-organized into new clusters. RED also focuses to solve the energy hole problem caused due to higher energy consumption by CHs near Sink Node or Base Station (BS). © 2018, Springer International Publishing AG.

International Conference on Information and Communication Technology for Intelligent Systems

RED: Residual energy and distance based clustering to avoid energy hole problem in self-organized wireless sensor networks

Data mining also sometimes called data or knowledge discovery is the process of analyzing data from different perspectives and summarizing it into useful information. Image processing is related to Computer vision, which is a high-level image processing out of which a machine/computer/software intends to decipher the physical contents of an image or a sequence of images. One of the ways to do this is by comparing selected facial features from the image and a facial database. Recognizing emotion from images has become one of the active research themes in image processing and in applications based on human-computer interaction. This research conducts an experimental study on recognizing facial emotions. The flow of our emotion recognition system include the basic process in FER system. These include image acquisition, preprocessing of an image, face detection, feature extraction, classification and then when the emotions are classified the system assigns the user particular music according to his emotion. Our system focuses on live images taken from the webcam. The aim of this research is to develop automatic facial emotion recognition system for stressed individuals thus assigning them music therapy so as to relief stress. The emotions considered for the experiments include happiness, Sadness, Surprise, Fear, Disgust, and Anger that are universally accepted. © 2017 IEEE.

Facial emotion recognition system through machine learning approach

Real time business search largely has the involvement of Internet of Things which has now become a huge set of objects with large magnitude of intercommunication links and services. This scalability issue can be resolved by bringing in (SIoT) Social IoT i.e. an object looking for its social partners who will have similar set of rules to positively influence the performance of the service. In this work, we are putting forward the analysis of the impact of deep web on real time search. We also propose a novel approach by analyzing the shortcomings of the existing techniques. The novel idea is the distribution of web search engine to take care of sub parts of entity and sensor pages by distributing the search engine itself along with the index over multiple nodes. Deep websites are needed to be brought in for accurate results. This work offers better accuracy and a significant speed up for multiple query execution in distributed environment. © 2017 IEEE.

2017 4th International Conference on Advanced Computing and Communication Systems, ICACCS 2017

Analyzing the impact of deep web on real-time business search

The test suite minimization approach is a major research topic that it requires huge attention from the researchers as the traditional methods used for performing the test suite minimization is concentrated on the cost of regression testing but the requirements were not satisfied. To solve the problem of satisfying requirements, researchers proposed greedy algorithms, optimization algorithms, and so on. In this paper, a novel optimization algorithm is proposed termed as the Diversity Dragonfly Algorithm (DDF) algorithm that concentrates on the cost and quality of the test suite. The diversification included in the standard Dragonfly algorithm forms the DDF that uses three bitwise operators for diversification. The DDF algorithm determines the best suite based on the hunting mechanism of the dragonfly using a minimum objective function such that the selected test suite satisfies all the requirements. The experiment is carried out using five subject programs and the performance analysis of the proposed DDF is carried out and compared with the existing methods. It is found that the reduction capability of the DDF is better than existing methods and the cost of the proposed DDF is low ensuring a quality test suite reduction. © 2017 IEEE.

DDF: Diversity Dragonfly Algorithm for cost-aware test suite minimization approach for software testing

Understanding human emotions is a complex problem. Various tools and techniques have been employed by researchers across various domains to understand and infer human emotions. With the advent of smart machines, the problem took a different angle to try and machines themselves make to understand the emotions of its user (s). Human emotions had to be labeled and then were organized with inverse emotions being placed opposite to each other. Various continuous as well as discrete emotion-mapping models were proposed to identify and quantify human emotions. This paper is the result of studying around fifteen such models and comparing them with each other to come to a more concrete viewpoint towards understand human emotions. © 2017 ACM.

Proceedings of the 9th International Conference on Computer and Automation Engineering

Circle of Emotions in Life: Emotion Mapping in 2Dimensions

Phishing is a criminal scheme to steal the user's personal data and other credential information. It is a fraud that acquires victim's confidential information such as password, bank account detail, credit card number, financial username and password etc. and later it can be misuse by attacker. We aim to use fundamental visual features of a web page's appearance as the basis of detecting page similarities. We propose a novel solution, to efficiently detect phishing web pages. Note that page layouts and contents are fundamental feature of web pages' appearance. Since the standard way to specify page layouts is through the style sheet (CSS), we develop an algorithm to detect similarities in key elements related to CSS. In this paper, we proposed a system that uses SVM technique along with map-reduce paradigm to achieve a higher accuracy in detection of the spam email. By using the map-reduce technique we also try to overcome the two hurdles of the SVM. © 2017 IEEE.