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Kishor D.R.,Jawaharlal Nehru Technological University | Venkateswarlu N.B.,AITAM
Advances in Intelligent Systems and Computing | Year: 2017

The present work experiments with the K-means (partitional), expectation-maximization, and fuzzy C-means (model-based) techniques, and some of their hybridizations to study their behavior. Experiments are carried out on three different datasets of which one is synthetic dataset. On each dataset, experiments are carried out with varying number of clusters. To measure the clustering performance, the experiments compute clustering fitness and sum of squared errors (SSE). Execution time is also taken into consideration for all the algorithms with all the datasets. Though the algorithm for K-means (StKM) is taking less execution time as it involves in computing only one parameter, i.e., cluster means, the algorithm for K-means followed by standard fuzzy c-means (KMFCM) may be preferred when we consider high intracluster similarity with a good separation of clusters also. © Springer Science+Business Media Singapore 2017.

Prasan U.D.,AITAM | Murugappan S.,Annamalai University
International Journal of Applied Engineering Research | Year: 2016

Vehicular Ad Hoc Networks is a class of special wireless ad-hoc network with the characteristics of high node mobility and fast topology changes. The Vehicular Networks can provide wide variety of services, range from safety-related warning systems to improved navigation mechanisms as well as information and entertainment applications. So lot of research work is being conducted to study the problems related to the vehicular communications including network architecture, protocols, routing algorithms, as well as security issues. In order to stimulate the ‘beginners in research’, here we present a paper on an overview of Vehicular Ad-hoc Networks. VANETs comprise vehicle-to-vehicle and vehicle-to-infrastructure communications based on wireless local area network technologies. The distinctive set of candidate applications, resources, and the environment make the VANET a unique area of wireless communication. Due to their unique characteristics such as high dynamic topology and predictable mobility, VANETs attract so much attention of both academia and industry. In this paper, we provide an overview of the main aspects of VANETs from a research perspective. This paper starts with the basic architecture of networks, then discusses research issues and general research methods, and ends up with the analysis on challenges and applications of VANETs. © 2016, Research India Publications.

Athota K.,JNTUH College of Engineering | Athota K.,University of Hyderabad | StalinBabu G.,AITAM | Negi A.,University of Hyderabad
Communications in Computer and Information Science | Year: 2012

Wireless Mesh Networks(WMNs) with multiradio multichannel capability have received much attention from research community. Routing in WMNs has been active area of research for many years. Routing metrics that have been proposed for WMN provide better path selection in comparision with hop count which is popular in wired networks. Expected Transmission Time (ETT) was proposed as better metric as compared to ETX so as to give weighting to throughput. Weighted Cumulative ETT(WCETT) allows accounting for concatenated links that interfere when using the same channel. Adhoc on demand distance vector (AODV) is a popular routing protocol design for MANETs which is also considered applicable as a routing protocol for WMNs. Further, an extension of AODV may support Multiple Radios and Multiple channels. In this paper we integrate WCETT and AODV to realize better routing for WMNs. We attempt to study and investigate performance of above said routing metrics using simulations from NS2 simulator. © 2012 Springer-Verlag.

Raja Kishor D.,Jawaharlal Nehru Technological University | Venkateswarlu N.B.,AITAM
Cybernetics and Information Technologies | Year: 2016

The present work proposes hybridization of Expectation-Maximization (EM) and K-means techniques as an attempt to speed-up the clustering process. Even though both the K-means and EM techniques look into different areas, K-means can be viewed as an approximate way to obtain maximum likelihood estimates for the means. Along with the proposed algorithm for hybridization, the present work also experiments with the Standard EM algorithm. Six different datasets, three of which synthetic datasets, are used for the experiments. Clustering fitness and Sum of Squared Errors (SSE) are computed for measuring the clustering performance. In all the experiments it is observed that the proposed algorithm for hybridization of EM and K-means techniques is consistently taking less execution time with acceptable Clustering Fitness value and less SSE than the standard EM algorithm. It is also observed that the proposed algorithm is producing better clustering results than the Cluster package of Purdue University.

Kishor D.R.,Jawaharlal Nehru Technological University | Venkateswarlu N.B.,AITAM
International Journal of Ambient Computing and Intelligence | Year: 2016

Expectation Maximization (EM) is a widely employed mixture model-based data clustering algorithm and produces exceptionally good results. However, many researchers reported that the EM algorithm requires huge computational efforts than other clustering algorithms. This paper presents an algorithm for the novel hybridization of EM and K-Means techniques for achieving better clustering performance (NovHbEMKM). This algorithm first performs K-Means and then using these results it performs EM and K-Means in the alternative iterations. Along with the NovHbEMKM, experiments are carried out with the algorithms for EM, EM using the results of K-Means and Cluster package of Purdue University. Experiments are carried out with datasets from UCI ML repository and synthetic datasets. Execution time, Clustering Fitness and Sum of Squared Errors (SSE) are computed as performance criteria. In all the experiments the proposed NovHbEMKM algorithm is taking less execution time by producing results with higher clustering fitness and lesser SSE than other algorithms including the Cluster package.

Lakshmi K.,AITAM | Chitambara Rao K.,AITAM
International Journal of Applied Engineering Research | Year: 2015

Digital filters are used extensively in all areas of electronic industry in which FIR filters are most widely used. This paper presents a design of FIR filter by using BOOTH multiplier and CARRY SKIP adder. Optimizing the speed and area of a multiplier is a major design issue. The area and speed are the conflicting constraints because the faster speed results in the larger area. The faster execution speed and smaller area are the important factors in designing the DSP systems. In this paper the multiplier considered is the Booth Multiplier. And the adder is the carry skip adder. So mentioned multiplier is combined with the adders in the design of FIR filter so that they occupy less amount of space when compared with the normal multiplier. This criterion is very important in the fabrication of the chips and the high performance system requires components which are as small as possible. Finally the simulation and synthesis results obtained are compared with the results of previous methods and to say which one is the best. © Research India Publications.

Janardhana Rao K.,AITAM | Srinivasa Rao A.S.,AITAM
International Journal of Applied Engineering Research | Year: 2015

Signal handover is the foremost thing in communication engineering task where decision making plays a crucial role by taking all the available attributes into account of distinct technology. In order to correlate dissimilar access technologies, vertical handoff algorithms came into existence in diverse forms. In pursuance of upgrading the accuracy of vertical handoff decision making for radio heterogeneous technologies, this work initiates multi criteria vertical handoff decision algorithm. Our work involves with the fuzzy logic controller with mamdani type inference engine by considering cost, bandwidth, throughput, received signal strength etc.., as semantic variables for different kind of networks and we also decide the index of networks which will be further utilized in handover management process for good decision making. © Research India Publications.

Kalpana P.,AITAM | Rajasekhara Rao C.,AITAM
International Journal of Applied Engineering Research | Year: 2015

The clock distribution network in digital integrated circuits distributes the clock signal which acts as a timing reference controlling data flow within the system. Since the clock signal has highest capacitance and operates at high frequencies, the clock distribution network consumes a large amount of total power in synchronous system. In this paper introduce a new flip-flop for use in a low swing LC resonant clocking scheme. The proposed low-swing differential conditional capturing flip-flop (LS-DCCFF) operates with a low-swing sinusoidal clock through the utilization of reduced swing inverters at the clock port. The functionality of the proposed flip-flop was verified at extreme corners through simulations with parasitic extracted from layout. The LS-DCCFF enables 6.5% reduction in power compared to the full swing flip-flop with 19% area overhead. The functionality of low-swing differential conditional flip-flop can be tested and verified using H-spice tool. Resonant clocking enables the generation of clock signals with reduced power consumption. © Research India Publications.

Divya G.,AITAM | Sekhar C.C.,AITAM
International Journal of Electrical and Computer Engineering | Year: 2015

Images are integral part in our daily lives. With a normal camera it is not possible to get a wide angle panorama with high resolution. Image Mosaicing is one of the novel techniques, for combining two or more images of the same scene taken in different views into one image. In the dark areas, the obtained image is a panoramic image with high resolution without mask. But in the case of lighting areas, the resultant image is generating mask. In order to gets wide angle panorama, in the existing system, extracting feature points, finding the best stitching line, Cluster Analysis (CA) and Dynamic Programming (DP) methods are used. Also used Weighted Average (WA) method for smooth stitching results and also eliminate intensity seam effectively. In the proposed system, to get feature extraction and feature matching SIFT (Scaled Invariant Feature Transform) algorithm used. In this process, outliers can be generated. RANSAC (Random Sample Consensus) is used for detecting the outliers from the resultant image. Masking is significantly reduced by using Algebraic Reconstruction Techniques (ART). © 2015 Institute of Advanced Engineering and Science. All rights reserved.

Madhavi D.,AITAM | Ramana B.V.,AITAM
International Journal of Electrical and Computer Engineering | Year: 2015

Hadoop technology plays a vital role in improving the quality of healthcare by delivering right information to right people at right time and reduces its cost and time. Most properly health care functions like admission, discharge, and transfer patient data maintained in Computer based Patient Records (CPR), Personal Health Information (PHI), and Electronic Health Records (EHR). The use of medical Big Data is increasingly popular in health care services and clinical research. The biggest challenges in health care centers are the huge amount of data flows into the systems daily. Crunching this Big Data and de-identifying it in a traditional data mining tools had problems. Therefore to provide solution to the de-identifying personal health information, Map Reduce application uses jar files which contain a combination of MR code and PIG queries. This application also uses advanced mechanism of using UDF (User Data File) which is used to protect the health care dataset. De-identified personal health care system is using Map Reduce, Pig Queries which are needed to be executed on the health care dataset. The application input dataset that contains the information of patients and de-identifies their personal health care. De-identification using Hadoop is also suitable for social and demographic data. © 2015 Institute of Advanced Engineering and Science. All rights reserved.

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