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Research Paper

Document clustering using K-Means clustering in Hadoop using Map Reduce

The high dimensional information concerns expansive volume, mind-boggling, mounting informational indexes with various, self-governing sources. As the Data expanding radically every day, it is a noteworthy concern to oversee and compose the information productively. This developed the need for machine learning systems. With the Fast advancement of Networking, information stockpiling and the information gathering limit, Machine learning bunch calculations are presently quickly growing in all science and building spaces, for example, Pattern acknowledgment, information mining, bioinformatics, and proposal frameworks. In order to help the adaptable machine learning system with Map Reduce and Hadoop bolster, we are utilizing YARN Yet Another Resource Negotiator to deal with the High Voluminous information. Different Cluster issues, for example, Cluster propensity, partition, Cluster legitimacy, and Cluster recital canister be effectively overwhelmed by YARN bunching calculations. Mahout oversees information in four stages i.e., bringing information, content mining, bunching, arrangement, and community-oriented separating. In the proposed approach, different information writes, for example, Numbers, Raw Data and 3D-Images however, datasets are arranged in the few classifications i.e., Collaborative Filtering, Clustering, Classification or Frequent Itemset Mining.

Published by: Utkarsh Jaiswal, Kunal Gupta

Author: Utkarsh Jaiswal

Paper ID: V4I4-1526

Paper Status: published

Published: August 29, 2018

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Dissertations

Performance based design of RCC structure

The prediction of inelastic seismic responses and the evaluation of seismic performance of a building structure are very important subjects in performance-based seismic design. The seismic performances of reinforced-concrete buildings evaluated by nonlinear static analysis (pushover analysis) and nonlinear time history analysis are compared in this research. A finite element model that can accurately simulate the nonlinear behavior of building is formulated by considering several important effects such as p-delta can be considered rigid zones with joint failure due to the poor detailing of joints. Both global responses such as system ductility demand and local response such as inter-story drift are investigated in this research. A numerical example is performed on a 20-story reinforced concrete building in ZONE V. Finally, the global and local responses obtained from the pushover analysis are compared with those obtained from the nonlinear dynamic analysis of MDOF system. The results show that the PA is accurate enough for practical applications in seismic performance evaluation when compared with the nonlinear dynamic analysis of MDOF system.

Published by: Md. Rehan, Faiyaz Azam

Author: Md. Rehan

Paper ID: V4I4-1548

Paper Status: published

Published: August 29, 2018

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Thesis

Clinicopathological Profile of Gastrointestinal Stromal Tumors

Gastrointestinal stromal tumors (GISTs) are rare tumors of gastrointestinal tract arising from interstitial cells of Cajal. They present with varied clinical features most of which are non- specific. This study was done to identify the clinical features of GISTS and immunohistochemistry. It was a retrospective and prospective study. The total number of studied patients was 50. Out of 50 patients- 26 were females (52%). Mean Age of involvement was 59 years. Gastrointestinal bleeding and Pain abdomen were the most common symptoms. Stomach was involved in 64%, small gut in28% and colon in 4% of the patients. The average size of the tumor was 5.2cm. 96% were CD117 positive. GISTS are rare tumors arising in late middle age. They affect males and females equally. They present non- specific signs and symptoms. Most of them are CD117 positive.

Published by: Rayees A Khanday, Ajaz Malik, Munir Wani, Zubaida Rasool

Author: Rayees A Khanday

Paper ID: V4I4-1541

Paper Status: published

Published: August 29, 2018

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Research Paper

Pochhammer symbol of ultra gamma function and its applications to hypergeometric functions

The aim of this paper is to investigate an extension of generalized hypergeometric function rFs with r numerator and s denominator parameters with help of ultra gamma function. Some Recurrence relation of the Pochhammer symbol of Ultra Gamma Function is investigated. Certain particular cases of the derived results are considered and indicated to further reduce to some known results. Finally, we present a systematic study of the various fundamental properties of the class of hypergeometric functions introduced here.

Published by: Anita, K. S. Gehlot, Chena Ram

Author: Anita

Paper ID: V4I4-1553

Paper Status: published

Published: August 29, 2018

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Research Paper

Experimentally the performance and exhaust emission characteristics by adding additive as ethanol in methyl ester of rice bran oil in CI engine

One of the methods to reduce the use of fossil fuel is blending ethanol with fossil diesel. However, an emulsifier or a co-solvent is needed to homogenize the diesel-ethanol blends. This project is aimed to investigate experimentally the performance and exhaust emission characteristics by adding additive as ethanol in methyl ester of rice bran oil in CI engine. The experimental results showed that the highest brake thermal efficiency was observed with 5% ethanol in the diesel-biodiesel-ethanol blend was lower than that of diesel fuel. The hydrocarbons and smoke were lower than that of diesel fuel, the rice bran oil biodiesel can be used as an additive to mix higher percentage of ethanol in diesel-ethanol blends to improve the performance and reduce the emissions of a diesel engine.

Published by: Paramjeet Singh, Amit Kumar, Amit Kumar Tiwari

Author: Paramjeet Singh

Paper ID: V4I4-1544

Paper Status: published

Published: August 29, 2018

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Research Paper

Prediction of compressive strength of concrete using artificial neural network

The present-day structures are being made with the use of a number of different building materials with varying strength properties that govern their mechanical strength and correspondingly their durability and life. There are a number of techniques available to determine the compressive strength of these materials. However, use of an artificial neural network provides a non-destructive way to predict the compressive strength of the same. In the present study, the compressive strength of concretes prepared with two different cement types i.e. PPC and PSC with manufactured sand and natural sand as aggregate for four different water-cement (w/c) ratios have been undertaken using an artificial neural network (ANN). The predicted strength was compared with that obtained in the laboratory for the same.

Published by: Naman Veer

Author: Naman Veer

Paper ID: V4I4-1516

Paper Status: published

Published: August 28, 2018

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