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Research Paper

Comparative study on Apriori and FP growth algorithms in big data

A dataset is a collection of data. Today the huge amount of the data is being captured by information sensing devices such as mobiles, computers, sensors etc. These huge amounts of the data are now called as big data. Frequent Itemset mining is a tool for identifying the frequently occurring items together. There are many frequent Itemset mining algorithms like apriori, Eclat and FP growth. In the proposed work we use FP growth algorithm and compare it with Apriori algorithm and we show that FP growth algorithm is better when compared to the apriori algorithm.

Published by: Reena Lobo, Venkatesh

Author: Reena Lobo

Paper ID: V4I3-1318

Paper Status: published

Published: May 8, 2018

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Research Paper

A worthwhile performance framework modeling hinge on lambda architecture for batch and stream big data

The amount of data we are now generating is astonishing. Data has also evolved dramatically in recent years, in type, volume, and velocity. The emerging technologies like smartphones and sensors present opportunities for data exploitation, streaming and collecting from heterogeneous device every second. Analyzing these large datasets can unlock multiple behaviors previously unknown, a help optimizes approaches to many applications. However, collecting and handling of these massive datasets present challenges in how to perform optimized the large data. There are several frameworks available for handling the big data applications. The Lambda Architecture is data processing framework that can handle both batch and stream processing. The batch layer is implemented using Pig and hive, the streaming layer is built by using the Spark streaming and Spark SQL. This presents a need for developing the new framework for handling the big data applications particularly using public clouds to minimize cost, resource availability.

Published by: Athira Soman, Smitha Jacob

Author: Athira Soman

Paper ID: V4I3-1281

Paper Status: published

Published: May 8, 2018

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Research Paper

Protecting information by hiding sensitive data attributes

Data mining aims at extracting hidden information from data. The process of discovering useful patterns and relationships in the large volume of data is called data mining. The goal of the data mining process is to extract information from a data set and transform it into an understandable structure. It involves databases, data management aspects, visualization & online updating. Data mining poses a threat to information privacy. Privacy-preserving data mining hides the sensitive rules and prevents the data from being disclosed to the public. The objective is to propose a novel association rule hiding (ARH) algorithm to hide the sensitive attributes. A function is used to obtain a prior weight for each transaction, by which the order of transactions modified can be efficiently decided. Apriori is used to find the frequent itemset with minimum support and confidence. Sensitive rules are generated based on frequent itemsets and the FHSAR algorithm is used for hiding sensitive association rules. This paper analyses the dataset obtained from SPMF an open source data mining library which is prepared based on real-life data. This paper shows the effectiveness of the algorithm.

Published by: Sighila P, Sangeetha S

Author: Sighila P

Paper ID: V4I3-1286

Paper Status: published

Published: May 8, 2018

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Survey Report

Data collection in health monitoring

Data collection is most important in many industries. The data collection which refers to the collecting a data or information from respective sources. In each and every industry maintain a database with the attributes that are required and necessary. Even for health monitoring, some information about the patients is required for the further decision making or for the treatment. This collected data can be useful for the easy analysis and for the extracting data about the individuals. Here we are briefly explaining the techniques used for data collection in health monitoring systems. There are so many techniques which had been used for data collection and also it involves many kinds of research on the data collection, its security, efficiency, and so on. Data collection is very important to know the information about the individuals.

Published by: Divya K, Harshitha C R, Soumya K N

Author: Divya K

Paper ID: V4I3-1292

Paper Status: published

Published: May 8, 2018

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Research Paper

Automobile immobilization for drunken driving

The epitome of this topic focuses on the problem of drunken driving is one of the major reasons for on-road accidents and deaths. Alcohol affects the drunk driver’s judgmental abilities and driving adversely. Many solutions have been proposed to reduce the after effects of drunk driving. However, most of these solutions were based on certain prototypes which consisted of control units or computerized protection systems including wireless monitoring facilities. This resulted in having systems with lots of demerits, high cost and slow response in the case of remote monitoring and decision making.To avoid all the mentioned disadvantages, this paper introduces a simple, cheap and highly responsive design. The proposed design is based on simple electronic components with processing and decision made locally and does not involve wireless transmission to guarantee the required fast response. This Arduino based system detects the presence of alcohol content in the breath of the driver and immobilizes the vehicle accordingly.

Published by: Chinmay Karnad, Aditya Patnaik, Sneha Singh

Author: Chinmay Karnad

Paper ID: V4I3-1146

Paper Status: published

Published: May 8, 2018

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Research Paper

I and Z shape rectangular patch antenna used for WLAN, Wi-MAX and satellite application

In the current scenario small, compatible and affordable microstrip patch antennas are developed in wireless communication industries keep on improving antenna performance.One of important concept to design antenna is that antenna have small size. For WLAN and WI-MAX applications, one may want that antenna must have small size and must be capable to resonate at multiple frequency bands. There are number of techniques that can be useful for designing of antenna which include making use of fractal geometry, use of slot and DGS. In this research work, I shape along with Z shape slots are inserted on the patch. The dimension of ground and path that are considered in this research work are 32.6mm×27.6mm and 18mm×23mm respectively. Then the performance parameters like gain, return loss, Bandwidth, radiation pattern and NSWR are measured for simple as well as for DGS antenna. The substrate used for the proposed antenna is FR4 with relative permittivity 4.4 and loss tangent is 0.02. The simulation is carried out in HFSS software. At lat the comparison of proposed with existing work is provided.

Published by: Harpreet Singh, Mukta Sharma

Author: Harpreet Singh

Paper ID: V4I3-1163

Paper Status: published

Published: May 7, 2018

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