Experimental and Numerical Study on Behavior of Externally Bonded RC T-Beams using GFRP Composites
Fiber-reinforced polymer (FRP) application is a very effective way to repair and strengthen structures that have become structurally weak over their lifespan. FRP repair systems provide an economically viable alternative to traditional repair systems and materials. In this study experimental investigation on the flexural behavior of RC T-beams strengthened using glass fiber reinforced polymer (GFRP) sheets are carried out. Reinforced concrete T beams externally bonded with GFRP sheets were tested to failure using a symmetrical two-point static loading system. Seven RC T-beams were cast for this experimental test. All of them were weak in flexure and were having same reinforcement detailing. One beam was used as a control beam and six beams were strengthened using different configurations of glass fiber reinforced polymer (GFRP) sheets. Experimental data on load, deflection and failure modes of each of the beams were obtained. The effect of different amount and configuration of GFRP on ultimate load carrying capacity and failure mode of the beams were investigated. The experimental results show that externally bonded GFRP can increase the flexural capacity of the beam significantly. In addition, the results indicated that the most effective configuration was the U-wrap GFRP. A series of comparative studies on deflection between the present experimental data and results from finite element method and IS code method were made. A future area of research is being outlined.
Published by: T. Kavitha, N. Swathi , Sk. Jain Saheb
Author: T. Kavitha
Paper ID: V3I6-1356
Paper Status: published
Published: December 5, 2017
Proficient Mining and Suggestions In Online By Means Of User Behavior
The Web makes magnificent open doors for organizations to give customized online administrations to their clients. Recommender frameworks plan to naturally create customized proposals of items/administrations to clients (business or person). In spite of the fact that recommender frameworks have been very much examined, there are as yet two difficulties in the advancement of a recommender framework, especially in genuine B2B e-administrations. In Proposed a suggestion system using the quick dissemination and data sharing capacity of a substantial client arrange. This framework executed a GRS in light of sentiment elements that consider these connections utilizing a brilliant weights lattice to drive the process. In GRSs, a suggestion is generally figured by a straightforward total strategy for individual information the proposed technique [described as the client-driven recommender framework (CRS)] takes after the synergistic sifting (CF) standard, however, performs dispersed and nearby looks for comparative neighbors over a client organize with a specific end goal to produce a suggestion list.
Published by: R. Kavi Priya, P. Shanthi
Author: R. Kavi Priya
Paper ID: V3I6-1337
Paper Status: published
Published: December 5, 2017
KNN- A Machine Learning Approach to Recognize a Musical Instrument
In this paper, the methodology used to recognize the musical instrument is summarized. To recognize musical instruments, there are two ways. They are training phase & testing phase. The details regarding the same is mentioned. Music Information Retrieval toolbox is used to extract features of the input signals. There are no. of ways classifiers available out of which we have used KNN- a machine learning approach.
Published by: Sushen R. Gulhane, Dr. Suresh D. Shirbahadurkar, Sanjay Badhe
Author: Sushen R. Gulhane
Paper ID: V3I6-1335
Paper Status: published
Published: December 5, 2017
A Comparative Study on E–Banking Services at Bangalore City
Technology in Indian banking has evolved substantially from the days of back office automation to today's online, centralized and integrated solutions. Banking is now no longer confined to the branches where one has to approach the branch in person, to withdraw cash or deposit a cheque or request a statement of accounts. With the expansion of internet usage, e-banking has become one of the most revolutionized components of today’s economic growth. E-banking is powerful value added tool to attract new customers and retain the existing ones. With the proliferation of the internet and computer usage, the electronic delivery of e-banking service has become ideal for banks to meet customer expectations.
Published by: Ranjini M. L, Dr. Mahesh Kumar K. R
Author: Ranjini M. L
Paper ID: V3I6-1277
Paper Status: published
Published: December 2, 2017
Roles and Responsibilities of Managers in Corporates – An Insight
Management is “getting things done in right way in right time by right persons with the right amount of resources and with effective use of resources”. Some refer it to a process of getting things done, effectively and efficiently, through and with other people in changing the environment. Managers Talent is something personal related to an individual and represents a native gift from nature about that something inside that talented persons. All persons cannot be artists. Usually, artists are born with the gift of art, but despite their talent, they continue to develop their talent to improve their skills. When we talk about managerial skills, we talk about Innovative skills of a manager to maintain high efficiency in the way how his or her employees complete their everyday working tasks. Because of that, all Level of managers will need skills that will help them to manage people and technology to ensure an effective and efficient realization of their working tasks.
Published by: Shivali Khare, Dr. Abhay Varma
Author: Shivali Khare
Paper ID: V3I6-1343
Paper Status: published
Published: December 2, 2017
Multivariate Feature Descriptor based CBIR Model to Query Large Image Databases
The content-based image retrieval (CBIR) applications have grown their popularity in the past decade with the exponential growth in the image data volumes. The social networks have aggravated the size of image data on the internet. Social network enables everyone to upload the images of one’s choice, which becomes the reason behind aggregation of millions of images on the cyber space. It’s not possible to query these large image databases with the ordinary methods. Hence there was a strong requirement of a smart and intelligent method to discover the similar images, which has been accomplished by using the machine learning methods. In this paper, the multivariate feature descriptor method has been presented to extract the required and relevant information from the large image databases. The proposed multivariate method involves the image color and texture for the purpose of image matching to the query image (also known as a reference image). The most matching entities are returned as the final results by the image extraction method. There are four methods, which involves three singular feature and one multivariate feature-based models, have been implemented. The multivariate model has been found much stable and returned the maximum accuracy under this model.
Published by: Harkamal Kaur, Er. Manit Kapoor, Dr. Naveen Dhillon
Author: Harkamal Kaur
Paper ID: V3I6-1322
Paper Status: published
Published: December 2, 2017
