Department of Computer Science & Engineering

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

In this paper, we have proposed proactive approach for fast-handoff using Access Point (AP) in Vehicular Ad-hoc Network (VANET). The existing schemes are based on context transfer for fast hand-off, but needs to reduce the latency of hand-off for VANETs. Fast hand-off in vehicle scans only the selected AP at any instance of time depending upon the association pattern. The Fast Hand-off Algorithm using AP Graph with Multiple Vehicles for VANET improves the re-association latency and context transfer process must be separated from reassociation process. From experimental and simulation results, we find that the use of AP graphs reduces the handoff latency due to re-association process and that the effectiveness of the approach improves dramatically as user mobility increases. The context transfer process for proactive fashion is used for fast handoff and reducing the context transfer latency of handoffs. The Inter-Access Point Protocol (IAPP) protocol is called the context transfer protocol. © 2013 IEEE.

World University root node

2013 Annual IEEE India Conference, INDICON 2013

Proactive approach based fast handoff algorithm for VANETs

Sensor networks deployed for the border area monitoring requires a high degree of reliability for the data gathering in spite of any arbitrary node or sink failures. This paper proposes RelBAS, a robust data gathering scheme specially designed for the border area network to provide a guaranteed delivery of sensory data. The proposed protocol aims to find out multiple node-disjoint paths to multiple sinks so that the disconnectivity in one path due to a node failure does not disrupt the delivery of data to the sink. The forwarding path selection at every node in RelBAS is based on the combination of three parameters-the hop-count, the residual energy and the number of children for for parent of the corresponding tree. This helps in adapting the protocol to the application requirement depending on the delay, energy efficiency and data aggregation. Moreover, RelBAS is capable of detecting an affected zone due to multiple node failures. The effectiveness of the proposed scheme has been analyzed using the simulation results. © 2013 IEEE.

Proceedings - International Symposium on Computers and Communications

RelBAS: Reliable data gathering from border area sensors

In this paper, the security of two recent RFID mutual authentication protocols are investigated. The first protocol is a scheme proposed by Huang et al. [7] and the second one by Huang, Lin and Li [6]. We show that these two protocols have several weaknesses. In Huang et al.’s scheme, an adversary can determine the 32-bit secret Access password with a probability of 2−2, and in Huang-Lin-Li scheme, a passive adversary can recognize a target tag with a success probability of 1−2−4 and an active adversary can determine all 32 bits of Access password with success probability of 2−4. The computational complexity of these attacks is negligible. © Springer-Verlag Berlin Heidelberg 2013.

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

On the security of two RFID mutual authentication protocols

Automatically generating meaningful descriptions for images has recently emerged as an important area of research. In this direction, a nearest-neighbour based generative phrase prediction model (PPM) proposed by (Gupta et al. 2012) was shown to achieve state-of-the-art results on PASCAL sentence dataset, thanks to the simultaneous use of three different sources of information (i.e. visual clues, corpus statistics and available descriptions). However, they do not utilize semantic similarities among the phrases that might be helpful in relating semantically similar phrases during phrase relevance prediction. In this paper, we extend their model by considering inter-phrase semantic similarities. To compute similarity between two phrases, we consider similarities among their constituent words determined using WordNet. We also re-formulate their objective function for parameter learning by penalizing each pair of phrases unevenly, in a manner similar to that in structured predictions. Various automatic and human evaluations are performed to demonstrate the advantage of our 'semantic phrase prediction model' (SPPM) over PPM. © 2013 IEEE.

IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops

Generating image descriptions using semantic similarities in the output space

The Z-number is a new fuzzy-theoretic concept, proposed by Zadeh in 2011. It extends the basic philosophy of Computing With Words (CWW) to include the perception of uncertainty of the information conveyed by a natural language statement. The Z-number thus, serves as a model of linguistic summarization of natural language statements, a technique to merge human-affective perspectives with CWW, and consequently can be envisaged to play a radical role in the domain of CWW-based system design and Natural Language Processing (NLP). This article presents a comprehensive investigation of the Z-number approach to CWW. We present here: a) an outline of our understanding of the generic architecture, algorithm and challenges underlying CWW in general; b) a detailed study of the Z-number methodology - where we propose an algorithm for CWW using Z-numbers, define a Z-number based operator for the evaluation of the level of requirement satisfaction, and describe simulation experiments of CWW utilizing Z-numbers; and c) analyse the strengths and the challenges of the Z-numbers, and suggest possible solution strategies. We believe that this article would inspire research on the need for inclusion of human-behavioural aspects into CWW, as well as the integration of CWW and NLP.

Fundamenta Informaticae

An insight into the Z-number approach to CWW

Cyber physical space is potentially hosting innumerable spatio-temporal data streams due to increasing use of social networking platforms as real-time information dissemination system and world-wide deployment of sensors for continuous monitoring of physical phenomena. In this paper we address the problem of how cyber physical space can be used for sensing and responding to global calamities such as earthquake. The paper proposes a novel approach of generating online adaptive response in assisting search-and-rescue operations using situation awareness built from realtime heterogeneous spatio-temporal data streams. Online adaptive response is achieved by using agent-based cooperative task sharing and modeling agent decision making as self-organized emergent behavior based on concepts of complex adaptive system. An implemented simulation platform use concepts of situation modeling, domain task network, contract net protocol based negotiation and complex adaptive system to generate adaptive plans. Preliminary simulation results are promising as we have been able to demonstrate a repertoire of self-organized emergent behaviors. © 2013 IEEE.

Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013

Towards adaptive multi-agent planning in cyber physical space

Digitization of newspaper article is important for registering historical events. Layout analysis of Indian newspaper is a challenging task due to the presence of different font size, font styles and random placement of text and non-text regions. In this paper we propose a novel framework for learning optimal parameters for text graphic separation in the presence of complex layouts. The learning problem has been formulated as an optimization problem using EM algorithm to learn optimal parameters depending on the nature of the document content. © 2013 ACM.

ACM International Conference Proceeding Series

Text graphic separation in Indian newspapers

This paper proposes an optimized learning method for large feature-sets using AdaBoost to produce hardware-efficient boosted decision stumps. The paper also proposes a method for training decision stumps to construct the ensemble. AdaBoost sequentially searches for the best weak classifier in the pool and adds it to the ensemble, using weighted training samples. In the proposed method, Particle Swarm Optimization quickens the selection of decision stumps. It is shown experimentally that the optimized method is more than 60% faster than the exhaustive search method. © Springer-Verlag 2013.

Incorporation of particle swarm optimization in adaptive boosting

In today's competitive market, mobile service providers are very keen on improving the customer satisfaction by providing personalized services. Recommending recharge packs to the subscribers that suits their personal profile is an important such personalized service. But a solution to this problem is not that simple as it requires careful analysis of the subscribers' usage behavior and involves very large volume of data generated by the subscribers' frequent interaction with the telecom network. Also, this solution needs to ensure a fine balance between customer satisfaction and profitability of service providers. This paper discusses about an adaptive recommendation model which overcomes various deficiencies associated with existing solutions. The model recommends suitable recharge packs to subscribers based on their usage history and affordability. Further, it accommodates a configurable fairness parameter that ensures a balance between the profitability factor, conversion probability and relevance of the recommendations. Due to the sheer volume of the data involved, the model is implemented using a distributed framework. The validity of the model is evaluated on the basis of statistical properties and conversion factor. © 2013 IEEE.

2013 National Conference on Communications, NCC 2013

Best-fit mobile recharge pack recommendation

Widespread acceptability and use of biometrics for person authentication has instigated several techniques for evading identification. One such technique is altering facial appearance using surgical procedures that has raised a challenge for face recognition algorithms. Increasing popularity of plastic surgery and its effect on automatic face recognition has attracted attention from the research community. However, the nonlinear variations introduced by plastic surgery remain difficult to be modeled by existing face recognition systems. In this research, a multiobjective evolutionary granular algorithm is proposed to match face images before and after plastic surgery. The algorithm first generates non-disjoint face granules at multiple levels of granularity. The granular information is assimilated using a multiobjective genetic approach that simultaneously optimizes the selection of feature extractor for each face granule along with the weights of individual granules. On the plastic surgery face database, the proposed algorithm yields high identification accuracy as compared to existing algorithms and a commercial face recognition system. © 2005-2012 IEEE.