Computer Science and Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

In this study, a novel substitution method for finding potential protein–protein interactions (PPIs) has been discussed. This newly designed method for analyzing PPI also aids in the comparison of evolutionary distances. The method deals with various data sets, and additionally performs measurable assessment to determine PPIs is introduced. PPIs are biologically relevant and aid in better conceptual framework of phylogenetic profiling. The newly designed framework gives vision to relate the topological properties of the system with evolutionary behavior of datasets. Firstly, this study found that the most conserved protein motifs exist at the roots of the system, whereas newer motifs with mutations have a tendency to dwell on the branches. In-depth functional analysis revealed that the most conserved motifs have high specificity for improved structural procedures and pathway engagements, which may help identify their formative parts in cells. In conclusion, this study demonstrates several important aspects for future studies focusing to enhance phylogenetic profiling systems. This study can also be used effectively to utilize such strategies to develop new biological insights which will further lead to understanding of disease mechanisms. © The Institution of Engineering and Technology 2017.

World University root node

(SoE) School of Engineering

IET Nanobiotechnology

Reconstructing phylogenetic tree using a protein–protein interaction technique

Centrality is an important measure to identify the most important actors in a network. This paper discusses the various Centrality Measures used in Social Network Analysis. These measures are tested on complex real-world social network data sets such as Video Sharing Networks, Social Interaction Network and Co-Authorship Networks to examine their effects on them. We carry out the correlation analysis of these centralities and plot the results to recommend when to use those centrality measures. Additionally, we introduce a new centrality measure - Cohesion Centrality based on the cohesiveness of a graph, develop its sequential algorithm and further devise a parallel algorithm to implement it. © 2016 IEEE.

2016 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2016

Correlating centralities of social networks

Vehicle Indoor Air Quality (VIAQ) is a very important parameter that we often tend to ignore in our daily driving. VIAQ can worsen due to build-up of carbon dioxide (CO2), carbon monoxide (CO) and other harmful gases emitted by vehicles. Poor VIAQ can lead to short term health conditions like drowsiness, breathlessness, discomfort and headache. Drowsiness while driving is a predominant health condition that leads to large number of accidents and deaths all over the world. Standard equipment of air intake and recirculation in both low end and high end cars do not completely support pervasive maintenance of VIAQ. Due to unavailability of miniaturized sensors, a general purpose solution to this problem was rarely studied and addressed. In this work, we propose a novel mobile sensing system to monitor and understand change in VIAQ. Our mobile sensing system is general purpose, built by using an Android Smartphone and a mobile sensor, is independent of car age and model, and monitors VIAQ at all times. © 2016 IEEE.

2016 IEEE Annual India Conference, INDICON 2016

Real time in-vehicle air quality monitoring using mobile sensing

Widespread usage of Location based services (LBS) has eventually raised the concern for user’s privacy. Various privacy preserving techniques are based on the idea of forwarding cloaking area to service provider who might be untrusted party, instead of actual location of query issuer/client. For such scenarios, in which cloaking area is exploited for privacy, results of the query request are generally based on nearest distance between client and service requested. Such techniques do not include real time context which is important in determining security, accessibility, etc. of the service and enhancing service quality. In this work, a novel method, based on crowd-sourcing concept has been proposed which takes into account the real time context for determining results of query. A system consisting of real time context-aware component is coined. Real time context has been obtained through crowd-resources available in cloaking area of client. A fuzzy inference system (FIS) has been proposed which takes nearest distance and real time context parameters as input. Based on these parameters FIS generates a new rank for the service requested. This rank is the new position on the answer list for the service requested. A prototype of the proposed system is implemented. Evaluation of prototype has been done by taking feedback of 112 users about their satisfaction in the range (0–10). User feedback for the prototype is compared with feedback of other similar systems using Kruskal Wallis test for significant differences. It has been discovered that user satisfaction for proposed system stochastically dominates other prevalent systems. © Springer International Publishing AG 2017.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Quality enhancement of location based services through real time context aware obfuscation using crowd sourcing

Analysing and mining trajectories pose new challenges for trajectory privacy. We are addressing privacy issue for offline (historical) trajectories which are generally published for research. A fundamental research question in trajectory privacy domain is of trajectory anonymisation. k-anonymity is used as a standard for privacy which ensures that every entity in the dataset is indistinguishable from (k - 1) other entities. The proposed work aims at anonymising trajectories based on graph split method. We have used technique of constructing trajectory graph to simulate spatial and temporal relations of trajectories, based on which trajectory k-anonymity sets are found through graph split. For the purpose, we have proposed a novel method that uses earth mover's distance as a metric to find trajectory k-anonymity sets in contrast to Euclidean distance. It is discovered through a series of experiments that the proposed method is outperforming in terms of low information loss and computation time. Copyright © 2017 Inderscience Enterprises Ltd.

International Journal of Computational Science and Engineering

Trajectory anonymisation based on graph split using EMD

Machine Translation, sometimes referred by the acronym MT, is one of the important fields of study of computational linguistics that investigates the use of computer software to translate text or speech from one natural language to another. At its basic level, MT performs simple substitution of atomic words in one natural language for words in another language. Around the world, numerous systems are available in the market for the assessment of the translation being done by the various translation systems. Even within India, a large number of such evaluation systems are available and a lot of research is still going on to develop a better evaluation system which can beat the results produced by Human Evaluators. Even the main challenge before Indian Researchers is that the evaluation systems which are giving unbeatable results for the translation of Foreign languages (such as German, French, Chinese, etc.) are not even giving considerable results for the translation of Indian Languages (Hindi, Tamil, Telugu, Punjabi, etc.). So at par these evaluation systems cannot be applied as it is to evaluate Machine Translations of Indian Languages. Indian languages require a novel approach because of the relatively unrestricted order of words within a word group. In this paper, we are presenting an algorithm (by incorporating different modules of language models like synonym replacement, root word extraction and shallow parsing) which when applied upon the translation of English to Hindi text gives better evaluation results as compared to those algorithms which do not incorporate all these modules. Moreover, our study is limited to English to Hindi language pair and the testing is being with the corpora of agriculture domain. © 2017 IEEE.

Proceeding - IEEE International Conference on Computing, Communication and Automation, ICCCA 2017

An algorithm for the better assessment of machine translation

This paper proposes an approach for event recognition in Egocentric videos using dense trajectories over Gradient Flow - Space Time Interest Point (GF-STIP) feature. We focus on recognizing events of diverse categories (including indoor and outdoor activities, sports and social activities and adventures) in egocentric videos. We introduce a dataset with diverse egocentric events, as all the existing egocentric activity recognition datasets consist of indoor videos only. The dataset introduced in this paper contains 102 videos with 9 different events (containing indoor and outdoor videos with varying lighting conditions). We extract Space Time Interest Points (STIP) from each frame of the video. The interest points are taken as the lead pixels and Gradient-Weighted Optical Flow (GWOF) features are calculated on the lead pixels by multiplying the optical ow measure and the magnitude of gradient at the pixel, to obtain the GF-STIP feature. We construct pose descriptors with the GF-STIP feature. We use the GF-STIP descriptors for recognizing events in egocentric videos with three different approaches: following a Bag of Words (BoW) model, implementing Fisher Vectors and obtaining dense trajectories for the videos. We show that the dense trajectory features based on the proposed GF-STIP descriptors enhance the efficacy of the event recognition system in egocentric videos. © 2016 ACM.

ACM International Conference Proceeding Series

Event recognition in egocentric videos using a novel trajectory based feature

Acquiring the knowledge about the relationship among friendship network properties and check-in behavior of users (connected in the friendship network) has several benefits such as planning advertising strategies and recommending the friends or places. This paper aims to find the impact of structural patterns hidden in the nodes of a friendship network and external environment changes in the check-in patterns of the users. First, we categorize each spatial check-in event based on its cause into either self reinforcing behavior or social influence or external effect. Then, we explore how network and spatial properties and external factors affect the number of check-ins and influences. Using check-ins data from four major cities/states and its users' friendship graph, we show how network and spatial properties like centrality, network neighborhood overlap, spatial check-ins overlap, strong ties effects the check-ins and influential behavior of individuals. © 2016 IEEE.

IEEE International Conference on Data Mining Workshops, ICDMW

Correlating Social Interconnections of Users with Spatio-Temporal Check-Ins Behavior

Hierarchical generative modeling and Monte-Carlo EM in Riemannian shape space for hypothesis testing

Different compilers offer different kind and different level of optimization techniques. These days, scale of applications is increasing rapidly. This increase in scale demands more complex applications to be developed. This results in imbalance of resource capability and application demand. To take maximum of existing resources, compiler optimization techniques are used. There are existing compiler optimization techniques for single core processors. But use of these optimization techniques requires expert level knowledge. Optimization of Compiler means minimization or maximization or various objectives. These objectives may be latency, size, power requirement etc. Importance of these objectives may vary from one application to other. This paper illustrates analysis of existing optimization techniques, which are available for single core processor systems. The speed-up analysis of different applications is performed and architecture level features are extracted. Analysis graphs are generated at the end to show effect of various program features on applicability of optimization techniques. © 2015 IEEE.