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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B. V. S. Srikanth ¹, V. Krishna Reddy ¹

Affiliations
1 Department of Computer Science and Engineering, K L University, Green Fields, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN

Abstract

Background/Objectives: In this paper, there are real-time stream & big data stream applications running on a large amount of clusters & live migration of data using intensive & interactive tasks. Methods/Statistical Analysis: Traditionally, there are many stream processing engines which are going to manage the processing data in this streaming scenario, ongoing stream processing the data must be handle due to faults & stragglers within a second-scale latency. At present, there are efficient stream processing engines which can avoid these faults & stragglers by using the stream processing engines like APACHE SPARK & APACHE FLINK. Findings: In the real-time data stream processing there are some problem occurrences while processing the data, those are data latency, fault-tolerance, mutable data-sets and more stragglers. To avoid all these issues there is an efficient stream processing engines with additional added mechanisms like dolly retreat mechanism for avoiding stragglers and process data efficiently. Application/Improvements: Now a day’s demand for stream processing is increasing a lot which may be real-time streaming or normal cluster data transformation. Data has to be processed fast, so that companies are integrating these stream processing engines to changing their business conditions effectively in realtime for analyze their data more effectively with help of Fast Stream Processing Engines.

Keywords

Fault-Tolerance, RDD, Second-Scale Latency and Immutable Datasets, Stragglers

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V. Krishna Reddy ¹, K. Deva Surya ¹, M. Sai Praveen ¹, B. Lokesh ¹, A. Vishal ¹, K. Akhil ¹

Affiliations
1 Department of CSE, K L University, Vaddeswaram, Guntur - 522502, Andhra Pradesh, IN

Abstract

Background/Objectives: In this paper, the performance of cloud computing system is greatly influenced by the problem of load balancing. The complexity class of the load balancing problem with respect to the complexity class belongs to the NP-system complete which involves intensely huge search space with huge number of potential solutions and also to find the optimal solution, it takes longer time. Based on these circumstances, there is no methodology to solve the problem. Methods/Statistical Analysis: In the cloud, we can find a near optimal solution, within a brief span of time. In this situation IT practitioners are focusing on heuristic methods. This paper proposes a multi objective load balancing in a cloud computing environment. Findings: This model can be applied to schedule the tasks on to the distinct data center resources. Ant Colony Optimization (ACO) algorithm is considered to know the optimal solution. Application/Improvements: Experimental results show that proposed model exceeds existing models in terms of reduction in energy consumption, improving pool utilization, minimizing the number of active nodes.

Keywords

Ant Colony Optimization (ACO), Cloud Computing, FCFS Algorithm, Genetic Algorithm.

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V. Krishna Reddy ¹, V. Nagabhusan Reddy ²

Affiliations
1 Dept of Mechanical Engineering, Krishna Chaitanya Institute of Technology & Sciences, Markapur, A.P, IN
2 P.R.Poly Technical College, Giddalur, A.P, IN

Abstract

Solar energy is a clean, renewable way to provide electrical power available abundant and it is , inexhaustible among all of renewable energy resources. Photo voltaic power (PV) system (direct conversion of solar energy to electricity by means of solar cells) appears more flexible to meet the wide range of small scale energy needs of rural villages, particularly in the agricultural sector in developing countries like India. To make PV systems more economical to the rural users, many works in the areas of research, technological growth, manufacture field . This paper reviews the availability, present status, strategies, major realizations, existing performance models and future predictions of solar options in India. Efforts have been made to summarize the photovoltaic technology, capability, solar cell materials, environmental aspect, system performance and reliability, and present and future predictable costs. This review would be useful for Photo voltaic system producers, researchers and academicians for developing new technologies, comparing cell materials, cost comparisons to give better services to users over a wide range of applications and from the available research works it is also concluded that PV technology provide a better option for energy needs in the near and long term for our country.

Keywords

PV Power, Cell, Renewable Energy.

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