Gokaraju Rangaraju Institute of Engineering and Technology

Hyderabad, India

Gokaraju Rangaraju Institute of Engineering and Technology

Hyderabad, India
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Ettikyala K.,Chaitanya Bharathi Institute of Technology | Latha Y.V.,Gokaraju Rangaraju Institute of Engineering and Technology
Proceedings of 2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016 | Year: 2016

Cloud data centers have become crucial infrastructure for computing and data storage that facilitate the development of varied services offered by the cloud. In every datacenter, thousands of virtual servers or virtual machines run at any instance of time which hosts many tasks and in parallel cloud system should keep receiving the batches of task requests. In this context, out of many powered on servers only few targeted servers should fulfill batch of incoming tasks. Hence, task scheduling is an important issue which greatly influences the performance of cloud. The main objective of the scheduling algorithms in cloud environment is to utilize the resources efficiently while balancing the load between resources, to get the minimum execution time. In this paper we designed a rank based efficient task scheduler which effectively utilizes resources and provides high performance than spaceshared and timeshared task schedulers. This algorithm has been tested using CloudSim toolkit and results were compared with spaceshared and timeshared task schedulers. © 2016 IEEE.

Pramodh K.C.,Gokaraju Rangaraju Institute of Engineering and Technology | Vijayalata Y.,Information Technology Gokaraju Rangaraju Institute of Engineering and Technology
2016 IEEE International Conference on Advances in Computer Applications, ICACA 2016 | Year: 2017

Automatic personality recognition aims to assign a personal profile to the author by measuring the Big Five personality factors automatically. The present paper focuses on an approach developed to recognize the personality of the author by evaluating their writings. The score for each of the Big-Five personality traits is computed programmatically. Based on the essays of the author as an input, parse trees for the sentences are constructed to identify negations. Later, stopwords are removed, the text is tokenized and stemming is performed. Only the required information is extracted by using the parts of speech tagging in English language and the stemmed data is compared to the terms in the dataset which are categorized according to the Big Five Factors of personality. Finally, the matched percentage of words is calculated and scaled proportionately to obtain results. © 2016 IEEE.

Kumar Y.J.N.,Gokaraju Rangaraju Institute of Engineering and Technology | Kanth T.V.R.,SNIST
International Journal of Electrical and Computer Engineering | Year: 2017

The rainfall conditions across wide geographical location and varied topographic conditions of India throw challenge to researchers and scientists in predicting rainfall effectively. India is Agriculture based country and it mainly depends on rainfall. Seasons in India are divided into four, which is winter in January and February, summer is from March to May, monsoon is from June to September and post monsoon is from October to December. India is Agriculture based country and it mainly depends on rainfall. It is very difficult to develop suitable rainfall patterns from the highly volatile weather conditions. In this Paper, it is proposed that Map based Spatial Analysis of rainfall data of Andhra Pradesh and Telangana states is made using R software apart from Hybrid Machine learning techniques. A Study will be made on rainfall patterns based on spatial locations. The Visual analytics were also made for effective study using statistical methods and Data Mining Techniques. This paper also introduced Spatial mining for effective retrieval of Remote sensed Data to deal with retrieval of information from the database and presents them in the form of map using R software. Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved.

Karthikeyan R.,Gokaraju Rangaraju Institute of Engineering and Technology | Balasubramaian V.,Annamalai University
Materials Today: Proceedings | Year: 2017

Electrical resistance spot welding (ERSW) is an ideal process for joining sheet metal assemblies. Nowadays, aluminum alloys are increasingly being used in automotive industries in order to minimize the inertia. It is known that the process parameters play a vital role to determine the desired weld strength. In this study, an empirical relationship was established to predict the tensile shear fracture load (TSFL) of electrical resistance spot welded AA2024-T3 aluminum alloy joints with sheet thickness of 2.7 mm. A central composite rotatable design with four factors and five levels was chosen to minimize the number of experiments. Response surface methodology was used to optimize the process parameters. And TSFL of optimized electrical resistance spot welded joint was compared with TSFL of optimized friction stir spot welded AA2024-T3 aluminum alloy joint. However, ERSW could be used for joining of aluminum alloys; FSSW exhibited the maximum TSFL at the optimized condition. © 2017 Elsevier Ltd.

Nayak P.,Gokaraju Rangaraju Institute of Engineering and Technology
IEEE Sensors Journal | Year: 2017

Lifetime enhancement has always been a crucial issue as most of the wireless sensor networks (WSNs) operate in unattended environment where human access and monitoring are practically infeasible. Clustering is one of the most powerful techniques that can arrange the system operation in associated manner to attend the network scalability, minimize energy consumption, and achieve prolonged network lifetime. To conquer this issue, current researchers have triggered the proposition of many numerous clustering algorithms. However, most of the proposed algorithms overburden the cluster head (CH) during cluster formation. To overcome this problem, many researchers have come up with the idea of fuzzy logic (FL), which is applied in WSN for decision making. These algorithms focus on the efficiency of CH, which could be adoptive, flexible, and intelligent enough to distribute the load among the sensor nodes that can enhance the network lifetime. But unfortunately, most of the algorithms use type-1 FL (T1FL) model. In this paper, we propose a clustering algorithm on the basis of interval type-2 FL model, expecting to handle uncertain level decision better than T1FL model. © 2017 IEEE.

Sandhya N.,Gokaraju Rangaraju Institute of Engineering and Technology | Govardhan A.,JNTUH College of Engineering
Advances in Intelligent and Soft Computing | Year: 2012

Text Document Clustering aids in reorganizing the large collections of documents into a smaller number of manageable clusters. While several clustering methods and the associated similarity measures have been proposed in the past, the partition clustering algorithms are reported performing well on document clustering. Usually cosine function is used to measure the similarity between two documents in the criterion function, but it may not work well when the clusters are not well separated. Word meanings are better than word forms in terms of representing the topics of documents. Thus, here we have involved ontology into the text clustering algorithm. In this research WordNet based document representation is attempted by assigning each word a part-ofspeech (POS) tag and by enriching the 'bag-of-words' data representation with synset concept which corresponds to synonym set that is introduced by WordNet. After replacing the 'bag of words' with their respective Synset IDs a variant of K-Means algorithm is used for document clustering. Then we compare the three popular similarity measures (Cosine, Pearson Correlation Coefficient and extended Jaccard) in conjunction with different types of vector space representation (Term Frequency and Term Frequency-Inverse Document Frequency) of documents. © 2012 Springer-Verlag GmbH Berlin Heidelberg.

Vagdevi K.,Gokaraju Rangaraju Institute of Engineering and Technology | Radhika Devi V.R.,MLR Institute of Technology
Materials Today: Proceedings | Year: 2015

In the present work we study the electrical characteristics of graphene layer at various temperatures adsorbed with one beryllium. Negative differential conductance is observed which can be exploited for applications in analog electronics. It is observed that for 0. v and -1. v applied at 900k the negative differential conductance appears to increase. For -2. v the conductance starts from 300k. The negative differential conductance in graphene can be attributed to its intrinsic nonlinear carrier transport under a strong electric field. © 2015 Elsevier Ltd.

Kosaraju S.,Gokaraju Rangaraju Institute of Engineering and Technology | Chandraker S.,National Institute of Technology Warangal
Materials Today: Proceedings | Year: 2015

Maraging steels are evoked tremendous interest due to its extraordinary combination of structural strength and fracture toughness, at the same time ready to weld and heat-treated. Therefore, in the present study, an attempt has been made to investigate the effect of process parameters on performance characteristics in finish hard turning of MDN350 steel using cemented carbide tool and there by optimization of turning of MDN350 steel by taguchi method. The cutting speed, feed and depth of cut were used as the process parameters whereas the cutting force and surface roughness ware selected as performance characteristics. The L9 orthogonal array based on design of experiments was used to conduct experiments. The degree of influence of each process parameter on individual performance characteristic was obtained from Analysis of variance. The cutting speed was identified as the most influential process parameter on cutting force and feed was identified as the most influential process parameter on surface roughness. © 2015 Elsevier Ltd.

Ganesh R.,Gokaraju Rangaraju Institute of Engineering and Technology | Subbiah R.,Gokaraju Rangaraju Institute of Engineering and Technology | Chandrasekaran K.,RMK Engineering College
Materials Today: Proceedings | Year: 2015

This paper aims to study the effect of sintering temperature on physical, mechanical and wear properties of Al 2219 alloy matrix reinforced with SiC particulates of average particle size 23. μm for different weight fractions 10%, 15% and 20% fabricated by powder metallurgy (PM) method. The influence of sintering temperature on mechanical behavior and dry sliding wear behavior were investigated. Wear tests were performed under the loads of 10. N, 20N and 30N and sliding distances of 1960 m, 2448 m and 2934 m at the room temperature. A detailed investigation was done to study the effect of sintering temperature on wear of the composite material during the wear test. It was found that the better wear performance for the composite material was obtained with finer size of the reinforcement, high weight fraction and high sintering temperature where the pooling of reinforcement can be avoided to an appreciable amount. © 2015 Elsevier Ltd.

Velide L.,Gokaraju Rangaraju Institute of Engineering and Technology
International Journal of Pharma and Bio Sciences | Year: 2013

Pebrinedisease found to be highly virulent and harm the larval and cocoon characters of tropical tasar silkworm Antheraeamylitta Drury (Daba TV).Therefore an attempt has been made to evaluate the effect of 2% bleaching powder solution in controlling the pebrine disease attained through secondary contamination by studying larval and cocoon characters. In comparison with the healthy control (T1 batch larvae reared on untreated plantation), the results reveal a significant decrease in larval span, larvalweight, number of cocoons harvested, effective rate of rearing, cocoonweight, shellweight, shellratio, filament length, reelability, weight of silkreeled, length of shell, width of shell, shell thickness, peduncle thickness, peduncle length, peduncle weight, peduncle diameter in T2 batch (infected larvae reared on untreated Terminaliaarjuna plants) but a slight decrease was observed in T3 batch (healthy and infected larvae reared combined on 2% bleaching powder solution treated plantation).The results also show that maximum mortality in T1 batch and T3 batch larvae was due to viral and bacterial infections and other factors rather than pebrine disease whereas in case of T2 batch nearly 50% of larval mortality was due to pebrinedisease. Based on the results obtained from present study 2% bleaching powder solution is found efficient in controlling pebrine disease attained through secondary contamination in Daba TV.

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