scispace - formally typeset
Search or ask a question
Institution

Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, a new hybrid Engineered Cementitious Composite (ECC) based on the steel short random fiber reinforcement has been developed to improve the tensile strength of cementitious material and enhance better flexural performance.
Abstract: Abstract This study focuses to develop a new hybrid Engineered Cementitious Composite (ECC) and assesses the performance of a new hybrid ECC based on the steel short random fiber reinforcement. This hybrid ECC aims to improve the tensile strength of cementitious material and enhance better flexural performance in an RC beam. In this study, four different mixes have been investigated. ECC with Poly Vinyl Alcohol (PVA) fiber and PolyPropylene (PP) fiber of 2.0% volume fraction are the two Mono fiber mixes; ECC mix with PVA fiber of 0.65% volume fraction hybridized with steel fiber of 1.35% volume fraction, PP fiber of 0.65% volume fraction hybridized with steel of 1.35% volume fraction are the two additional different hybrid mixes. The material properties of mono fiber ECC with 2.0 % of PVA is kept as the reference mix in this study. The hybridization with fibers has a notable achievement on the uniaxial tensile strength, compressive strength, Young’s modulus, and flexural behavior in ECC layered RC beams. From the results, it has been observed that the mix with PVA fiber of 0.65% volume fraction hybrid with steel fiber of 1.35% volume fraction exhibit improvements in tensile strength, flexural strength, and energy absorption. The PP fiber of 0.65% volume fraction hybridized with steel of 1.35% volume fraction mix has reasonable flexural performance and notable achievement in displacement ductility over the reference mix.

14 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a green cloud based queuing management system for 5G networks that helps in addressing the issues related to latency and energy consumption in mobile edge computing.
Abstract: The mobile users have acquired the benefits of cloud computing with the help of Mobile Edge Computing (MEC) technology in order to satisfy the increasing data demands. The efficiency of the system is highly limited by the bandwidth limitations and limitations associated with the mobile devices despite the rapid development of MEC as well as the cloud computing technology. Our aim is to provide an optimal method to optimize the energy consumption in the mobile edge computing. In this regard, the research paper proposed a Green Cloud based Queue Management system for 5G networks that helps in addressing the issues related to latency and energy consumption. While serving the users, the proposed methodology results in less amount of energy being wasted and hence the reduced latency. By means of alleviating the congestion and implementing the virtual list, this issue can be resolved greatly. Simulation is done with the help of NS2 green cloud simulator and the results are obtained by comparing the proposed model to conventional cloud model and cloudlet based on throughput, latency, energy consumption and normalized overhead as these are the evaluation measures. The results show that there has been considerable enhancement in the energy consumption. As the throughput increases, the quality of the service also increases.

13 citations

Journal ArticleDOI
01 Feb 2021
TL;DR: The finding showed that DL techniques outperformed all other image processing techniques but DL performs mainly depends on the dataset used.
Abstract: Deep learning establishes an ongoing, modern technique for image processing with large potential and promising results. After proving its efficiency in various applications DL has also entered into the domain of agriculture. Here, we surveyed 38 research works that applied deep learning techniques to various research problems in tomato plant. We examine the areas of tomato plant research where deep learning is applied, data preprocessing techniques applied, transfer learning and augmentation techniques used. Studied dataset information like data sources used, number of images, classes and train test validation ratio applied. In addition, we study comparisons done on various deep learning architectures and discussed the outcome. The finding showed that DL techniques outperformed all other image processing techniques but DL performs mainly depends on the dataset used.

13 citations

Proceedings ArticleDOI
22 Jul 2009
TL;DR: This work proposes a model of QoS-based Web services discovery that combines an augmented UDDI registry to publish the QoS information and designs a new framework that enhances retrieval algorithms by combining syntactic and semantic matching of services.
Abstract: Web service technology is playing a major role in today's distributed system computing. The wide adoption of web services raises the challenging problem of service discovery. With an increasing number of Web services providing similar functionalities, Quality of Service (QoS) is becoming an important criterion for selecting of the best available service. We aim to refine the discovery process through designing a new framework that enhances retrieval algorithms by combining syntactic and semantic matching of services. We propose a model of QoS-based Web services discovery that combines an augmented UDDI registry to publish the QoS information.

13 citations

Journal ArticleDOI
TL;DR: Improved Location aided Cluster based Routing Protocol (ILCRP) for GPS enabled MANETs has been evaluated for performance metrics such as end to end delay, control overhead, and packet delivery ratio and illustrates that ILCRP performs better compared to other protocols.
Abstract: Routing has been the main challenge for ad hoc networks due to dynamic topology as well as resource constraints. Completely GPS(Global Positioning System) free as well as GPS scarce positioning systems for wireless, mobile, ad-hoc networks has been proposed recently by many authors. High computational overhead and high mobility of the nodes typically require completely GPS enabled MANETs for higher performance. In this article, Improved Location aided Cluster based Routing Protocol (ILCRP) for GPS enabled MANETs has been evaluated for performance metrics such as end to end delay, control overhead, and packet delivery ratio. Use of cluster based routing as well as exact location information of the nodes in ILCRP reduces the control overhead resulting in higher packet delivery ratio. GPS utility in nodes reduces the end to end delay even during its high mobility. Simulations are performed using NS2 by varying the mobility (speed) of nodes as well as number of the nodes. The results illustrate that ILCRP performs better compared to other protocols.

13 citations


Authors
Network Information
Related Institutions (5)
Anna University
19.9K papers, 312.6K citations

89% related

VIT University
24.4K papers, 261.8K citations

89% related

National Institute of Technology, Rourkela
10.7K papers, 150.1K citations

88% related

SRM University
11.7K papers, 103.7K citations

88% related

Thapar University
8.5K papers, 130.3K citations

87% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202221
2021572
2020234
2019121
2018143
2017136