Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Steganography & Support vector machine. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

A Utility Driven Post Disaster Emergency Resource Allocation System Using DTN

Abstract: Two of the most dominant challenges in post disaster emergency resource allocation are: 1) understanding the exact utility, i.e., exigency, of emergency resources and 2) collecting and transmitting the need for these resources to the control station from where resources are allocated. Measuring the utility of resources with precision becomes tricky in a dynamic post disaster scenario, where demands are constantly evolving and supplies trickle in at an uncertain rate. Moreover, collection and transmission of resource needs of far-flung areas are easier said than done owing to the post disaster disruption of communication infrastructure. These result in the ad-hoc allocation of emergency resources to the shelters. In this paper, we first derive a utility function for dynamically enumerating the shelter specific utility of each emergency resource. Subsequently, we propose an opportunistic knowledge sharing scheme for gathering and disseminating resource needs to the control station using a smartphone-based delay tolerant network. Finally, based on these opportunistically transmitted needs, we formulate a utility driven optimal resource allocation model which minimizes overall resource deficit and total resource deployment time. The proposed system optimally assigns constrained emergency resources to different shelters, so that high-utility resources are deployed fast. The effectiveness of the proposed system is evaluated using ONE simulator and LINGO optimization modeling tool. Exhaustive simulation is done to evaluate the comparative performance of our system with a number of competing schemes. Results show that our system outperforms all these schemes in a fully connected scenario. It is also observed that even in an intermittently connected environment, the performance of our system is almost at par with the competing schemes.

Finding Influential Nodes in Social Networks Using Minimum k-Hop Dominating Set

Abstract: Challenges in social interaction networks are often modelled as graph theoretic problems. One such problem is to find a group of influential individuals of minimum size or the initial seed set in a social network, so that all the nodes in the network can be reached with only one hop from the seeds. This problem is equivalent to finding a minimum dominating set for the network. In this paper, we address a problem which is similar to finding minimum dominating set but differs in terms of number of hops needed to reach all the nodes. We have generalized the problem as k-hop dominating set problem, where a maximum of k hops will be allowed to spread the information among all the nodes of the graph. We show that the decision version of the k-hop dominating set problem is NP-complete. Results show that, in order to reach the same percentage of nodes in the network, if one extra hop is allowed then the cardinality of the seed set i.e. the number of influential nodes needed, is considerably reduced. Also, the experimental results show that the influential nodes can be characterized by their high betweenness values.

Uniformly dispersed nanocrystalline silver reduces the residual stress within diamond-like carbon hard coatings

Abstract: Composite films containing silver (Ag) nanoparticles embedded in amorphous diamond-like carbon (Ag–DLC) matrix have been deposited on glass and Si (100) substrates using r.f. capacitatively coupled plasma chemical vapour deposition (rf-CVD). Ag content in the DLC films varies with the relative amount of argon in the methane and argon gas mixture during the plasma growth. The film thickness ranges from 50 nm to 105 nm. The sp2/sp3 ratio in the DLC films decreases with the incorporation of nanocrystalline silver. A considerable amount, of about 99% residual stress reduction in Ag–DLC films has been demonstrated through theoretical calculation with the help of experimental optical absorption spectra. The results are verified by experimental nano-mechanical property evolution using nano-indentation. The related residual compressive stress reduction in the Ag–DLC composite films is attributed to the addition of uniformly dispersed nanocrystalline silver nanoparticles in the DLC matrix and the corresponding relative sp2/sp3 ratio variation.

Fast detection of community structures using graph traversal in social networks

Abstract: Finding community structures in social networks is considered to be a challenging task as many of the proposed algorithms are computationally expensive and does not scale well for large graphs. Most of the community detection algorithms proposed till date are unsuitable for applications that would require detection of communities in real time, especially for massive networks. The Louvain method, which uses modularity maximization to detect clusters, is usually considered to be one of the fastest community detection algorithms even without any provable bound on its running time. We propose a novel graph traversal-based community detection framework, which not only runs faster than the Louvain method but also generates clusters of better quality for most of the benchmark datasets. We show that our algorithms run in $$O(|V| + |E|)$$ time to create an initial cover before using modularity maximization to get the final cover.