Heritage Institute of Technology

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

Stiffened Hypar Shell with Cutout

Abstract: Free vibration characteristics of stiffened composite hypar shell (hyperbolic paraboloidal shells bounded by straight edges) in the presence of cutout are considered following a generalized finite element formulation using eight-noded curved quadratic isoparametric element for shell with a three-noded beam element for stiffener. The size of the cutouts and their positions with respect to the shell centre for different edge constraints are varied to obtain the results in the form of figures and tables. The results are analysed to achieve guidelines for the selection of optimum size and position of the cutout with respect to shell centre considering different practical constraints.

Handwritten signature hiding and extraction using alternate bit-replacement of bi-color images

Abstract: In this paper, we propose hiding and extraction algorithms for Handwritten Signature. Handwritten Signature Image can be transmitted from source to target securely over untrusted network by using this proposed Data Hiding Algorithm. In this algorithm, size of the carrier image must be double or more the size of source image. If necessary then additional bytes or noise needed to be injected into carrier image to attain the required size. To do this, the header is updated by the new value (sum of original size of file and amount of noise). There are numerous Data Hiding and Extraction algorithms are already proposed. In this paper, we propose a novel and new alternative. Entire work divides into - a. security on transmission; and b. Extraction. This proposed scheme could be applied for ownership protection, copy control, annotation and authentication of digital media. This work is focused on hiding Handwritten Signature during transmission over untrusted network.

Selection of Pathway Markers for Cancer Using Collaborative Binary Multi-Swarm Optimization

Abstract: Pathway information for cancer detection helps to find co-regulated gene groups whose collective expression is strongly associated with cancer development. In this paper, a collaborative multi-swarm binary particle swarm optimization (MS-BPSO) based gene selection technique is proposed that outperforms to identify the pathway marker genes. We have compared our proposed method with various statistical and pathway based gene selection techniques for different popular cancer datasets as well as a detailed comparative study is illustrated using different meta-heuristic algorithms like binary coded particle swarm optimization (BPSO), binary coded differential evolution (BDE), binary coded artificial bee colony (BABC) and genetic algorithm (GA). Experimental results show that the proposed MS-BPSO based method performs significantly better and the improved multi swarm concept generates a good subset of pathway markers which provides more effective insight to the gene-disease association with high accuracy and reliability.

Reducing the Negative Effect of Malicious Nodes in Opportunistic Networks Using Reputation Based Trust Management

Abstract: One of the major security issues common in any trust and reputation management mechanism is Bad mouthing in which malicious participants victimize nodes with high reputations by giving lower or negative feedbacks in order to undermine them. Opportunistic Networks are more vulnerable to this type of attacks as there is no pre defined path between the source and the destination. Hence it is important to ensure the trustworthiness or reliability of the next-hop nodes as the nodes communicates by forwarding the message to the next hop using opportunistic connectivity due to node proximity. Otherwise there is the risk of malicious nodes interrupting secure transmission, thus affecting the performance of the network. To deal with this issue of Bad mouthing due to the presence of malicious nodes in the network, we have proposed and implemented a Reputation based Trust Management Model using Friendship vector (RTMF). We have compared the performance of our algorithm with an existing Trust management system based on Ontology and it has been observed that RTMF has successfully reduced the negative effect of the presence of malicious nodes and improved the performance of the network.

Correction to "Compact Differentially Fed Inverted Microstrip Circular Patch With an Integrated Coupler" [2010 627-630]

Abstract: In the above titled paper (ibid., vol. 9, pp. 627-630, 2010), the y-axis nomenclature of Fig. 3 is incorrect. The corrected figure is presented here.