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

A graph theoretic approach is proposed to recognize interactions (e.g.; handshaking, punching, etc.) between two human performers in a video. Pose descriptors corresponding to each performer in the video are generated and clustered to form initial codebooks of human poses. Compact codebooks of dominating poses for each of the two performers are created by ranking the poses of the initial codebooks using two different methods. First, an average centrality measure of graph connectivity is introduced where poses are nodes in the graph. The dominating poses are graph nodes sharing a close semantic relationship with all other pose nodes and hence are expected to be at the central part of the graph. Second, a novel similarity measure is introduced for ranking dominating poses. The 'pose doublets', all possible combinations of dominating poses of the two performers, are ranked using an improved centrality measure of a bipartite graph. The set of 'dominating pose doublets' that best represents the corresponding interaction are selected using the perceptual analysis technique. The recognition results on standard interaction datasets show the efficacy of the proposed approach compared to the state-of-the-art. © 2013 Springer-Verlag Berlin Heidelberg.

(SoE) School of Engineering

World University root node

Machine Vision and Applications

Recognizing interactions between human performers by 'Dominating Pose Doublet'

International Journal of Engineering Research & Technology

<p>Key Issues in Machine Translation Evaluation of English-Indian Languages</p>

Given a set of points Q on a road network G = (V,E), an optimal meeting point (OMP) query offers a point on a road network with the smallest sum-of-distances (SoD) to all the points in Q. For example, a travel agency may issue OMP query to decide the location for a tourist bus to pick up the tourists thus minimizing the total travel cost for tourist. The OMP problem has been well studied in the Euclidean space. The currently available algorithms for solving this problem in the context of road networks are still not efficient for the practical applications and are in-memory algorithms which do not guarantee the scalability for the large road databases. Further, the most of the research work has been carried out around the single point OMP; however, the k-OMP problem on the road network setting is still unexplored. In this paper, we are proposing multiple variants of the scalable external-memory based algorithms for computing the optimal meeting point. There are mainly three variants of the proposed grid based algorithms i.e. Basic Grid based, Hierarchical Grid based and Greedy Centroid based OMP search. Later we used single point OMP as a start point to explore the k points OMP using breadth first search. The I/O optimized spatial grids are loaded from the secondary storage as and when required and hence the I/O complexity is reduced to O(N/B) as opposed to O(N) in the existing methods; where B is the average number of road vertices of the grid block. Extensive experiments are conducted on both real and synthetic datasets. © 2013 Springer-Verlag Berlin Heidelberg.

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

Scalable Method for k Optimal Meeting Points (k-OMP) Computation in the Road Network Databases

Mobile Agent (MA) based distributed computing paradigm offers numerous benefits over the existing and commonly used client/server computing paradigm in wireless sensor networks (WSN). MA performs the task of data processing and data aggregation at the node level rather than at the sink, thus, eliminating the redundancy network overhead. One of the most important issues in MA based paradigm is planning of an itinerary (route) for MA traversal. In this paper, we present a centralized MA itinerary planning approach using Grey Relational Analysis (GRA). The residual energy, migration cost and information gain are the factors considered for the next node selection of the itinerary, and GRA is used for finding out their importance level and determine their weighted values. Simulation results exhibit that the GRA based proposed approach performs better than the previously existing approaches. © 2013 IEEE.

2013 6th International Conference on Contemporary Computing, IC3 2013

Itinerary planning using grey relational analysis for mobile agent based wireless sensor networks

Huge information is intrinsically associated with certain places in the globe such as historical, geographical, cultural and architectural specialties. The next generation systems require access of the site specific information where the user is roaming at the moment. The on-the-spot learning (OTSL) is a system that allows the users to learn about the location, landmarks, regions where he/she is walking through. In this paper, we have proposed an OTSL model that includes the storage, retrieval and the landmark weighting heuristic. Apart from learning about the individual landmarks, we have proposed two ways of storing the spatial learning objects. First, use the administrative hierarchy of the region to fetch the information. This can be easily done by the reverse-geocoding operation without actually storing the physical hierarchy. Second, spatial chunking, creates the region based on the groups of landmarks in order to define a learning region. A hybrid solution has also been considered to achieve the advantages of both the region based methods. We use a weighting model to select the correct landmarks in the basic model. We extend the core model to include other factors such as speed, direction, side of the road etc. A prototype has been implemented to show the feasibility of the proposed model. © Springer International Publishing Switzerland 2013.

Studies in Computational Intelligence

Modeling on-the-spot learning: Storage, landmarks weighting heuristic and annotation algorithm

The term Phylogentics is the study of evolutionary relationship between different species, organisms or genes. These relationships are depicted as branched, tree like diagrams that provide insight into the events that occurred during the evolution process. These trees may also have a root which is known as the common ancestor. Building the "Tree of Life" has been the prime objective of many researchers, until it was proved that the tree of life cannot be represented by a single? tree. Many evolutionary events cannot be represented with the help of a simple tree, hence phylogenetic networks came into picture. Phylogenetic networks can be classified into different categories. In this paper, an algorithm (ReTF) has been proposed which would improve the results of the current phylogenetic network reconstruction algorithms. The idea behind ReTF is rearranging the input sequences in a way that the new arrangement gives a better tree, since the order of input sequences affects the outcomes of phylogenetic network. © 2013 IEEE.

13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013

Reconstructing phylogenetic network with ReTF algorithm (rearranging transcriptional factor)

The Cell Broadband Engine (CBE) is a heterogeneous multicore architecture developed by IBM, Sony, and Toshiba. A CBE (Figure 10.1) consists of a Power PC (PPU) core, eight Synergistic Processing Elements or Units (SPEs or SPUs), and associated memory-transfer mechanisms [14]. The SPUs are connected in a ring topology, and each SPU has its own local store. However, SPUs have no local cache and no branch-prediction logic. Data may be moved between an SPU’s local store and central memory via a DMA transfer, which is handled by a Memory Flow Control (MFC). Since the MFC runs independent of the SPUs, data transfer can be done concurrently with computation. The absence of branch-prediction logic in an SPU and the availability of SIMD instructions that can operate on vectors that are comprised of four numbers poses a challenge when developing high-performance CBE algorithms. © 2014 by Taylor & Francis Group, LLC.

Multicore Computing: Algorithms, Architectures, and Applications

Sorting on the cell broadband engine

In this paper decision variables for the key-frame detection problem in a video are evaluated using statistical tools derived from the theory of design of experiments. The pixel-by-pixel intensity difference of consecutive video frames is used as the factor or decision variable for designing an experiment for key-frame detection. The determination of a key-frame is correlated with the different values of the factor. A novel concept of meaningfulness of a video key-frame is also introduced to select the representative key-frame from a set of possible key-frames. The use of the concepts of design of experiments and the meaningfulness property to summarize a video is tested using a number of videos taken from MUSCLE-VCD-2007 dataset. The performance of the proposed approach in detecting key-frames is found to be superior in comparison to the competing approaches like PME based method (Liu et al., IEEE Trans Circuits Syst Video Technol 13(10):1006-1013, 2003; Mukherjee et al., IEEE Trans Circuits Syst Video Technol 17(5):612-620, 2007; Panagiotakis et al., IEEE Trans Circuits Syst Video Technol 19(3):447-451, 2009). © Springer Science+Business Media, LLC 2011.

Multimedia Tools and Applications

A design-of-experiment based statistical technique for detection of key-frames

Scheduling a meeting is a difficult task for people who have overbooked calendars and many constraints. This activity becomes further complex when the meeting is to be scheduled between parties who are situated in geographically distant locations of a city and have varying traveling patterns. We extend the work of previous authors in this domain by incorporating some real life constraints (varying travel patterns, flexible meeting point and considering road network distance). We also generalize the problem by considering variable number of users. The previous work does not consider these dimensions. The search space for optimal meeting point is reduced by considering convex hull of the set of users locations. It can be further pruned by considering other factors, e.g., direction of movement of users. Experiments are performed on a real-world dataset and show that our method is effective in stated conditions. © 2013 IFIP International Federation for Information Processing.

Analyzing travel patterns for scheduling in a dynamic environment

Mobile Agent (MA) based computing paradigm offers many advantages over the existing and widely used client/server computing paradigm in wireless sensor networks (WSN). MA performs the task of data processing and data aggregation at the nodes rather than at the sink, thus, eliminating the redundancy in the sensory data. One of the most important issues in MA based paradigm is planning of an itinerary (route) for MA traversal. In this paper, we present a centralized MA itinerary planning approach using Analytic Hierarchy Process (AHP). The remaining energy of the node, migration cost and information gain are taken into consideration for the selection of subsequent node of the itinerary. AHP is used for determining the weights to each of the above parameter, thus, simplifying the task of decision making. Simulation results exhibit that the proposed approach lowers the task duration and energy consumption of the network. © 2013 IEEE.