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Research Paper

Review on evolution of storage devices

With the Fast development of the internet, Decrease in the cost of storage and the improvement made to the storage devices with greater capacity resulted in the creation of an environment with a large amount of data. Things like Consistency, Performance, Data Preservation, Manageability, Security etc. have become extremely important for storage devices. We explain in this research paper how storage devices have evolved over the years.

Published by: Shubham Sharma, Sagar Mundra, Kapil Malakar, P. Sanjeevi

Author: Shubham Sharma

Paper ID: V4I6-1215

Paper Status: published

Published: November 17, 2018

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Research Paper

Survey on parallel data cloning and parallel programming

This paper review about parallel data processing and parallel programming a parallel processing is now become extremely famous for improving the speed to process something in the paper we evaluated.1. Different features of parallel computing.2. Parallel programming models.3. And structured parallel programming. We will be also discussing the machine learning and the important area where parallel computing can be useful in enhancing the capabilities of what machine learning can do and the generated models and method of parallel programming. We will be also simulating the advantage of parallel computing by comparing it with existing methods and how Hadoop can help for cluster handling.

Published by: Abhay Nigam, Kartik Bansal, Devdutta Basu, Pranay Kavishwar, P. Sanjeevi

Author: Abhay Nigam

Paper ID: V4I6-1214

Paper Status: published

Published: November 17, 2018

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Research Paper

Review on memory divisions in computer architecture

This Research Paper is totally concentrated to define different memory systems that are present in the market, and what is their importance in today’s generation. In this paper, we review the different hierarchies of the memory systems. It talks about cache-memory based systems and its various levels. Cache memories along with the virtual memories and processor registers form a field of memory hierarchies that depends on the principle of locality of reference. Most applications show the temporal and spatial zones among order and data. Then it describes about RAM (Random Access Memory) and its types which include DRAM (Dynamic Random-Access Memory) and SRAM (Static Random-Access Memory), it also describes the flash memory and its importance because of its small size and large memory containing abilities Memory hierarchies are intended to keep most likely referenced items in the fastest devices.

Published by: Mudit Jain, Devansh Patil, Tanay Parikh, Ayush Naidu, P Sanjeevi

Author: Mudit Jain

Paper ID: V4I6-1213

Paper Status: published

Published: November 17, 2018

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Case Study

Influence of polypropylene fibers with admixtures in strengthening of concrete

This current project work involves an experimental and laboratory study of the Polypropylene fibers with two types of admixtures those are Quarry dust and Fly ash on the mechanical properties of the concrete used construction. In this experimental study involves two types of concrete mixes were prepared individually. Polypropylene fiber of 1% to 3% with Quarry dust of 0.1% to 0.3% and Polypropylene fiber of 1% to 4% with Fly ash of 0.1% to 0.4% by weight of cement were added to the mixes. After that, a comparative analysis has been carried out for conventional concrete to that of the fiber reinforced in relation to their compressive, split tensile and flexural properties. By the experimental work the compressive, split tensile and flexural strengths are proportionally increased both Polypropylene + Quarry dust and Polypropylene +Fly ash usage. It is observed that the optimum dosages of Polypropylene + Quarry dust is 3% + 0.3% Polypropylene +Fly ash is 4%+ 0.4% by weight of cement. In this project cost analysis is also determined for conventional concrete and fiber reinforced with admixtures individually using experimental test reports.

Published by: Kutikuppala Vidyasagar, Chappa Damodar Naidu

Author: Kutikuppala Vidyasagar

Paper ID: V4I6-1221

Paper Status: published

Published: November 17, 2018

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Research Paper

Parameter tuning in firefly algorithm

Optimization means to find the best solution for any situation under given constraints. In today’s era, the problems are huge and complex. Nature always finds a way to deal with such problems efficiently in an optimized way. The computational algorithms which are inspired by nature to find solutions for such problems are called Nature inspired optimization algorithms. There are various nature-inspired algorithms and Firefly Algorithm (FA) is one among them. FA is a bio-inspired population-based stochastic algorithm which imitates the behavior of fireflies shown when they attract other fireflies. FA is an algorithm with many parameters that affect the accuracy and the convergence speed. A number of variants and parameter tuning related papers are available in the literature. In this paper first an introduction of Optimization, specifically Nature inspired optimization has been provided. Then, a detailed discussion about FA has been given. It is followed by a brief literature survey in which the work has been compared in tabular form to provide the readers with a better understanding. Further, we intend to improve the accuracy of Firefly algorithm by tuning the parameters namely α and βmin. A range of values of the above parameters is tested by forming their combinations to find out the mutual effect of both these parameters. These values are tested on a test bed of nine benchmark functions. The result is a combination of optimized values of both the parameters. The results are quite clear and provide a pair of optimized values of both the parameters.

Published by: Kavitha Rathore

Author: Kavitha Rathore

Paper ID: V4I6-1225

Paper Status: published

Published: November 17, 2018

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Research Paper

High performance computing v/s big data

Simulation has become a “must have” item in the technology toolbox for manufacturers who wish to optimize the product development process, reduce production costs, and speed-time-to market. Along with Big Data insights and HPC solutions, simulation can enhance the product design process by leveraging to drive product innovation, improve time to time value. These models (Big data and HPC) provide the advanced capabilities that are needed by the manufacturers to get to the market faster than their competition. In this paper, we analyze the ecosystems of the two prominent paradigms for data-intensive applications, hereafter referred to as the high-performance computing and the Big data paradigm. Further, the characteristics of the two paradigms have been discussed, along with comparisons and contrasts of the two approaches. It also covers the scope of these paradigms and sheds light upon the specific workloads that utilize them. At last, we discuss the convergence of both paradigms; the best of both world’s approach.

Published by: Nikita Mutreja, Sanyam Jhamb

Author: Nikita Mutreja

Paper ID: V4I6-1139

Paper Status: published

Published: November 16, 2018

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