Gokaraju Rangaraju Institute of Engineering and Technology

Hyderabad, India

Gokaraju Rangaraju Institute of Engineering and Technology

Hyderabad, India

Time filter

Source Type

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.

Padmavathi K.,Gokaraju Rangaraju Institute of Engineering and Technology | Sri Ramakrishna K.,VR Siddardha Engineering College
Procedia Computer Science | Year: 2015

Atrial fibrillation (AF) is a common type of arrhythmia that causes death in the adults. The Auto regressive (AR) coefficients characterize the features of AF. The AR coefficients are measured for every 15 second duration of the ECG and the features are extracted using Burg's method. These features are classified using the different statistical classifiers such as kernel Support Vector Machine (KSVM) and K-Nearest Neighbor (KNN). The performance of these classifiers is evaluated on signals obtained from MIT-BIH Atrial Fibrillation Database. The effect of AR model order and data length is tested on the classification results. © 2015 The Authors.

Pavani K.V.,Gokaraju Rangaraju Institute of Engineering and Technology | Sunil Kumar N.,Gokaraju Rangaraju Institute of Engineering and Technology | Sangameswaran B.B.,Gokaraju Rangaraju Institute of Engineering and Technology
Polish Journal of Microbiology | Year: 2012

In the context of the current demand to develop green technologies in material synthesis, a natural process in the synthesis of lead particles by Aspergillus species to suit such technology is reported. The fungal strain was grown in medium containing different concentrations of lead (0.2-1.5 mM) to determine its resistance to heavy metals. The organism was found to utilize some mechanism and accumulate lead particles outside and inside the cell. The extracellular presence of lead particles in the range of 1.77-5.8 &mu ;m was characterized by scanning electron microscopy. The presence of particles of lead in the 5-20 nm size range was found on the cell surface, in the periplasmic space and in the cytoplasm and was analyzed by transmission electron microscopy.

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.

Nayak P.,Gokaraju Rangaraju Institute of Engineering and Technology | Devulapalli A.,Gokaraju Rangaraju Institute of Engineering and Technology
IEEE Sensors Journal | Year: 2016

Wireless sensor network (WSN) brings a new paradigm of real-time embedded systems with limited computation, communication, memory, and energy resources that are being used for huge range of applications where the traditional infrastructure-based network is mostly infeasible. The sensor nodes are densely deployed in a hostile environment to monitor, detect, and analyze the physical phenomenon and consume considerable amount of energy while transmitting the information. It is impractical and sometimes impossible to replace the battery and to maintain longer network life time. So, there is a limitation on the lifetime of the battery power and energy conservation is a challenging issue. Appropriate cluster head (CH) election is one such issue, which can reduce the energy consumption dramatically. Low energy adaptive clustering hierarchy (LEACH) is the most famous hierarchical routing protocol, where the CH is elected in rotation basis based on a probabilistic threshold value and only CHs are allowed to send the information to the base station (BS). But in this approach, a super-CH (SCH) is elected among the CHs who can only send the information to the mobile BS by choosing suitable fuzzy descriptors, such as remaining battery power, mobility of BS, and centrality of the clusters. Fuzzy inference engine (Mamdani's rule) is used to elect the chance to be the SCH. The results have been derived from NS-2 simulator and show that the proposed protocol performs better than the LEACH protocol in terms of the first node dies, half node alive, better stability, and better lifetime. © 2016 IEEE.

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.

Kumar P.,Gokaraju Rangaraju Institute of Engineering and Technology | Singhal A.,University of Minnesota | Mehta S.,University of Minnesota | Mittal A.,Graphic Era University
Journal of Real-Time Image Processing | Year: 2016

Modern imaging sensors with higher megapixel resolution and frame rates are being increasingly used for wide-area video surveillance (VS). This has produced an accelerated demand for high-performance implementation of VS algorithms for real-time processing of high-resolution videos. The emergence of multi-core architectures and graphics processing units (GPUs) provides energy and cost-efficient platform to meet the real-time processing needs by extracting data level parallelism in such algorithms. However, the potential benefits of these architectures can only be realized by developing fine-grained parallelization strategies and algorithm innovation. This paper describes parallel implementation of video object detection algorithms like Gaussians mixture model (GMM) for background modelling, morphological operations for post-processing and connected component labelling (CCL) for blob labelling. Novel parallelization strategies and fine-grained optimization techniques are described for fully exploiting the computational capacity of CUDA cores on GPUs. Experimental results show parallel GPU implementation achieves significant speedups of ~250× for binary morphology, ~15× for GMM and ~2× for CCL when compared to sequential implementation running on Intel Xeon processor, resulting in processing of 22.3 frames per second for HD videos. © 2013, Springer-Verlag Berlin Heidelberg.

Loading Gokaraju Rangaraju Institute of Engineering and Technology collaborators
Loading Gokaraju Rangaraju Institute of Engineering and Technology collaborators