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Research Paper

Decentralized file sharing application in a global approach

Use of semantic technologies has been prevalent in sharing files and media over the internet. This project proposes a new cooperative file sharing and storage system that allows users to store, share and find files over a robust and scalable network. This system is based on peer-to-peer technologies and provides a self-managed, decentralized, efficient and distributed way to store and retrieve files on peer nodes. Each node donates storage space to the system. The system also provides its users with a global hierarchical directory structure to browse for files like a file-system maintaining RDF Graphs forming Ontology in individual systems with the implementation of peer to peer communication in global scenario overcoming the drawbacks of Network Address Translation using TCP Hole Punching technique.

Published by: K. Mohan Krishna, M. Kranthi Kiran, P. Kiran Kumar, M. Tejasmika, K. Ravi Teja Reddy, K. Sandeep

Author: K. Mohan Krishna

Paper ID: V5I2-1287

Paper Status: published

Published: March 19, 2019

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Research Paper

Neuromarketing: Understanding why we buy what we buy

In recent times, there has been an emerging field of study called neuromarketing, it has taken the marketing world by storm.it makes use of neuroscience research in a marketing context. The purpose of this paper is to understand how neuromarketing is carried out and to evaluate the influence of neuromarketing tools on traditional marketing inputs in order to give a deeper understanding of consumer behavior. The job of any marketer has less to do with designing attractive ads and more to do with understanding consumer behavior. It is said that people buy with emotions and justify it with logic, but this has proven to be true by neuromarketing research. Neuromarketing seeks to replace the traditional type of market research. Every year, nearly 450 billion dollars is invested in various advertising campaigns. still, traditional ways for testing and predicting the success and efficiency of those advertising campaigns have usually failed because they depend on customers’ willingness and capacity to describe how they react or feel when they are exposed to an advertisement.

Published by: Yogesh Maniyar, Atif Ahmed, Yash Tyagi

Author: Yogesh Maniyar

Paper ID: V5I2-1346

Paper Status: published

Published: March 19, 2019

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Research Paper

Image enhancement by averaging histogram equalization

Image Processing is defined as the process of converting an image into digital form and perform operations on it, in order to get an enhanced image or to extract some useful information from it. Image Processing has various categories in which Image Enhancement is one of them. Image enhancement is defined as the process of adjusting digital images such that the results are more suitable for display or further image analysis. The fundamental requirements for any vision based application are contrast enhancement and brightness preservation. The existing systems don’t satisfy both the requirements simultaneously. In this paper, a system is proposed which consists of step by step processes like color stretching, histogram averaging and re-mapping. The proposed system employs a search process to find optimal algorithmic parameters, such that the mean brightness difference between the input and output images is minimized. The proposed system is tested against different images to test the working of the system.

Published by: Anurag Cherukuri, B. Ravi Kiran, Buela Rani Badugu, Ravali Sujatha Alamuri, Yashwanth Aytha

Author: Anurag Cherukuri

Paper ID: V5I2-1359

Paper Status: published

Published: March 19, 2019

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Research Paper

Partial replacement of PPC with glass powder

Disposal problem of waste material is becoming critical day by day. A million tone of waste glass powder generated every year in the world. In this topic, an attempt has been made to utilize glass powder, which is a waste of glass industry. The research work is a determination of the effect of the use of Glass powder as a replacement of cement to assess the pozzolanic nature of fine glass powder when mixed in concrete and compare the difference in performance with other pozzolanic materials are mixed in concrete like silica fume and fly ash. The concrete in place of cement to some extent i.e., 10%, 20%, 30% and mechanical properties of M40 (Design Mix) are investigated. Cube specimen of 36 numbers were cast, cured and tested for 3, 7, and 28 days strength. Compression was conducted and the results were compared. The finding revealed an increase in compressive strength with the increase in the replacement of cement by Glass powder. To reduce the demand for cement, glass powder decreases the unit weight as well as the porosity as indicated by a decrease in water absorption. It reduces the quantity of cement to be used in concrete. Also, glass powder is proved to be economical and is considered an environmentally friendly construction material.

Published by: Shubham G. Keshattiwar, Vipul Rathod, Dhiraj Wankhede, Saurabh Kurrewar, Aishwarya H. Meshram

Author: Shubham G. Keshattiwar

Paper ID: V5I2-1366

Paper Status: published

Published: March 18, 2019

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Research Paper

An IoT based smart traffic control system

An automated Pi based traffic control system using webcams and sensors that help in reducing traffic density in busy traffic junctions. The design of this traffic infrastructure can help to avoid traffic congestions. This paper describes a system where webcams are integrated with the Raspberry Pi to operate the lanes of traffic junction based on the count of traffic and RFID Sensors for emergency vehicles to be prioritized for the safety of passengers. As a result, the improvement in the traffic system can be exponentially improved, which can lead to progressive in the overall traffic system.

Published by: Bevara Atchyuth, Irugatla Sarat Kumar, Swarna Datla, Ganta Ajay Rahul

Author: Bevara Atchyuth

Paper ID: V5I2-1294

Paper Status: published

Published: March 18, 2019

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Research Paper

Semantic text analysis using machine learning

As the amount of information on the World Wide Web grows, it becomes increasingly burdensome to and just what we want. While general-purpose search engines such as Ask.com and Bing high coverage, they often provide only low precision compared to others, even for detailed and relative queries. When we know that we want information about a certain type, or on a certain topic, a domain-specific search engine can be a powerful tool. Like www.campsearch.com allows complex queries over summer camps by age-group, size, location, and cost. Domain-specific search engines are becoming increasingly popular because they increase accuracy not possible with general, Web-wide search engines. Unfortunately, they are also burdensome and time-consuming to maintain. In this paper, we use machine learning techniques to greatly automate the creation and maintenance of domain-specific search. It describes new research in semi-supervised learning, text classification, and information extraction. We have built a demonstration system using these technics like Web Scrapping, Fuzzy C-Means and Hierarchy Clustering for a search engine which gives accurate results which is a more advantage when compared to other Search engines. Searching with a traditional, general purpose search engine would be extremely tedious or impossible to perform search operations. For this basis, domain-specific search engines are becoming popular. This article mainly concentrated on Project an effort to automate many aspects of creating and maintaining domain-specific search engines by using machine learning techniques. These techniques permit search engines to be created quickly with less effort and are suited for re-use across many domains.

Published by: Bhargavi Joga, Sarath Sattiraju, Venkatesh Kandula, Narayana Murthy Kallempudi, Mandava Kranthi Kiran

Author: Bhargavi Joga

Paper ID: V5I2-1312

Paper Status: published

Published: March 18, 2019

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