Informatics Publishing Limited

S. Sobha ¹, M. Swetha ¹, P. Raveendra Reddy ¹, V. Krishna Reddy ¹

Affiliations
1 Department of Chemistry, Sri Krishnadevaraya University, Anantapur, 515003 (A.P), IN

Abstract

A highly sensitive and selective spectrophotometric method was developed for the determination of trace amount of chromium (VI) in aqueous DMF medium. The chromate ion forms a light brown colored complex with 5-Bromo salicylaldehyde isonocotinoyl hydrazone (5-BrSAINH) in an acidic buffer of pH 6.0. The complex has an absorbance maximum at 430nm, was stable for more than 72 hours. Beer's law is obeyed in the range 0.16 - 3.90 μgml-1. The molar absorptivity and sandell's sensitivity of the colored solution were found to be 2.0 x 104 L.mol-1cm-1 and 2.6 X 10-3 μgcm-2, respectively. The light brown colored complex has 1:1 (Chromium (VI) - 5BrSAINH) Stoichiometry. The stability constant of the complex was determined as 1.40 X 106 by Job's method. The effect of foreign ions on the determination was studied. A sensitive and selective first and second order derivative spectrophotometry has also been proposed for the determination of Cr (VI). The interference of various cations and anions were studied. The developed methods were successfully employed in the determination of Cr (VI) in soil and standard steel samples.

Keywords

Spectrophotometry, 5-BrSAINH, Determination of Chromium (VI), Soil Samples, Standard Steel Samples

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Anusha Vasudevan ¹, M. Swetha ¹, H. Hyba ¹, G. Rajiv Suresh Kumar ¹

Affiliations
1 Computer Science and Engineering, JCT College of Engineering and Technology, Anna University, Chennai, Tamilnadu, IN

Abstract

The amount of data in our world has been exploding, and analyzing large data sets-so-called big data-will become a key basis of competition, reinforcement new waves of productivity growth, innovation, and consumer surplus. Big data refers to the size of a dataset that has grown too large to be manipulated through traditional methods. These methods include capture, storage, and processing of the data in a tolerable amount of time. Apache Hadoop is an open-source software framework for storage and large scale processing of data-sets on clusters of hardware. It works with Map Reduce software framework for easily writing applications which process vast amounts of data (multi-terabyte data-sets) in-parallel on large clusters (thousands of nodes) of commodity hardware in a reliable, fault-tolerant manner. Clustering analysis is an unsupervised learning task that consist on classify objects into group. Then, the objects from one group share similar feature and are different from objects belonging to other groups. This paper shows that Map Reduce framework K-means clustering algorithm can obtain a higher performance when handling large scale document automatic classification in a multimode environment.

Keywords

Bigdata, Hadoop, Map-Reduce, Clustering, HDFS.

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K. Uma ¹, M. Swetha ¹, M. Manisha ¹, S. V. Revathi ¹, Anand Kannan ²

Affiliations
1 School of Information Technology and Engineering, VIT University, Vellore – 632014, Tamil Nadu, IN
2 Department of Electricals and Computers, KTH Technical University, Swedan

Abstract

Objectives: The Embedded Technology is currently in its primary and the affluence of Knowledge offered is amazing. Embedded System is a permutation of hardware and software. Embedded technology plays a most important role in integrating the variety of functions coupled with it. Methods: This desire to bind up the variety of sources of the Department in a closed loop structure. This proposal significantly reduces the manpower, saves time and operates efficiently without individual interfering. This project puts out the first action in achieving the desired target. With the advent in technology, the existing systems are developed to contain inbuilt intelligence. This system will automatically broadcast the real time surroundings data. Findings: In this project we are going to observe the environment circumstances using the smart sensors in embedded technology, using this project we can analyze the climate and pollution state of our surrounding, using this data we can recover our surroundings from pollution. Applications: The Arduino as the prime controller which uses ATMEGA328 microcontroller, temperature, humidity, gas, sound sensors are used to sense the environment condition and provide the data to the Microcontroller which is used to observe the level and send the data to the cloud server via IOT module.

Keywords

Arduino, Embedded Technology, Internet of Things, Sensors

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