JNTUHCE

Hyderabad, India
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Ramesh B.,KITS | Asharani M.,JNTUHCE | Srujana V.,KITS | Chaithanya P.,KITS | Rajaiah U.,KITS
Proceedings of the 2016 2nd International Conference on Contemporary Computing and Informatics, IC3I 2016 | Year: 2017

Quantum dot Cellular Automata (QCA) is one of the emerging technologies for implementing the combinational and sequential circuits. From the past few decades CMOS technology is being used in IC industry. But CMOS technology having certain limitations like high power, low-speed, switching losses etc, to overcome these limitations and to meet the requirements of the industry parameters QCA is used. Adder is the basic building block to perform arithmetic and logical operations. In this paper QCA based BCD adder is designed with less number of Quantum cells. By reducing the QCA cells improvement in the circuit parameters like frequency, area and power consumption. To implement BCD adder 3-input majority gate and inverter is used with different clock inputs. © 2016 IEEE.


Fatima S.K.,Jawaharlal Nehru Technological University | Sreenivasa Rao D.,JNTUHCE
International Journal of Applied Engineering Research | Year: 2015

Nowadays Mobile Adhoc Network (MANET) is becoming more popular due to its mobile and ease of deployment nature. However due to wireless and dynamic nature of network topology, it make them more exposed to various types of attacks. The main issue is to assure secure network services. In order to overcome this issue, a Secure Cluster based Architecture for MANET with Threshold Signature and certificate Revocation is proposed. In this technique, a secure cluster is formed based on the trust value. The node with high trust value is considered as the Cluster Head. In order to increase the security, the selected Cluster Head CH is verified by using Threshold Signature. Also, a certification revocation technique is implemented to stop the participation of any attackers in further activities. © Research India Publications.


Madhavi K.R.,JNTUA | Babu A.V.,JNTUHCE | Rao A.A.,JNTUACE | Raju S.V.N.,JNTUH College of Engineering
ACM International Conference Proceeding Series | Year: 2012

Identification of useful clusters in large datasets has attracted considerable interest in clustering process. Since data in the World Wide Web is increasing exponentially that affects on clustering accuracy and decision making, change in the concept between every cluster occurs named concept drift. This newly added time based data must be assigned/labeled into generated clusters at our hand. To say that the data labeling was performed well, the clusters must be efficient. Selecting initial cluster center (centroid) is the key factor that has high affection in generating effective clusters. The existing clustering methods selects centroid randomly. Different centroids results in different clusters. To avoid this random selection, we are proposing methods in selecting the centroid by analyzing the properties of data since the data with different properties exists in real world. Our previous work was concentrated in the identification centroid for the functions of single variable and two variable functions. This paper proposes methods in finding optimal cluster centroid for the multi-variable functions and then apply any existing clustering algorithm to generate clusters by using suitable distance measure. © 2012 ACM.


Reddy Madhavi K.,JNIAS | Vinaya Babu A.,JNTUHCE | Anand Rao A.,JNTUACE | Viswanadha Raju S.,Jawaharlal Nehru Technological University Anantapur
IET Conference Publications | Year: 2012

Identification of useful clusters in large datasets has attracted considerable interest in clustering process. Since data in the World Wide Web is increasing exponentially that affects on clustering accuracy and decision making, change in the concept between every cluster occurs named concept drift. To perfectly handle these drifting concepts, assigning new data to existing cluster must be performed called data labeling. For efficient data labeling the existing clusters must be efficient. Selecting initial cluster center (centroid) is the key factor that has high affection in generating effective clusters. The insufficiency of traditional clustering methods in selecting initial cluster center has been motivated towards this work. Our previous work focus on selecting optimal cluster centroid for multivariable functions that does not require gradient information. This paper extends selecting optimal cluster centroid for unconstrained nonlinear multivariable gradient functions and then apply any existing clustering algorithm.


SivaKumar A.P.,JNTUACE | Premchand P.,Osmania University | Govardhan A.,JNTUHCE
Communications in Computer and Information Science | Year: 2011

Retrieving information from different languages may lead to many problems like polysemy and synonymy, which can be resolved by Latent Semantic Indexing (LSI) techniques. This paper uses the Singular Value Decomposition (SVD) of LSI technique to achieve effective indexing for English and Hindi languages. Parallel corpus consisting of both Hindi and English documents is created and is used for training and testing the system. Removing stop words from the documents is performed followed by stemming and normalization in order to reduce the feature space and to get language relations. Then, cosine similarity method is applied on query document and target document. Based on our experimental results it is proved that LSI based CLIR gets over the non-LSI based retrieval which have retrieval successes of 67% and 9% respectively. © 2011 Springer-Verlag.


Qaseem M.S.,Acharya Nagarjuna University | Govardhan A.,JNTUHCE
Proceedings - 2011 Annual IEEE India Conference: Engineering Sustainable Solutions, INDICON-2011 | Year: 2011

Predefined categories can be assigned to the natural language text using Text categorization. This paper explores the effect of other types of values, which express the distribution of a word in the document. These values are called distributional features. These different features are calculated for Window passage using distinctive classifiers. The classifier which gives the more accurate result is selected for categorization. Experiments show that the distributional features are useful for text categorization. These results are simulated using Weka tool. © 2011 IEEE.


Naik P.P.S.,JNTUK | Gopal T.V.,JNTUHCE
2015 International Conference on Communication and Signal Processing, ICCSP 2015 | Year: 2015

Segmentation is a process of partitioning the image into several objects. It plays a vital role in many fields such as satellite, remote sensing, object identification, face tracking and most importantly medical applications. Here in this paper, we here supposed to propose a novel image segmentation using iterative partitioning mean shift clustering algorithm, which overcomes the drawbacks of conventional clustering algorithms and provides a good segmented images. Simulation performance shows that the proposed scheme has performed superior to the existing clustering methods. © 2015 IEEE.


Kavitha Ch.,Alstom | Rao M.B.,Alstom | Rao B.P.,JNTUK | Govardhan A.,JNTUHCE
Communications in Computer and Information Science | Year: 2011

In this paper we propose a new and efficient technique to retrieve images based on multi-resolution color and texture features of image sub-blocks. Firstly the image is divided into sub blocks of equal size in two resolutions. The size of the sub-block is fixed in two resolutions. Color of each sub-block is extracted by quantifying the HSV color space into non-equal intervals and the color feature is represented by cumulative histogram. Similarly the texture of the sub-block is extracted based on edge oriented gray tone spatial dependency matrix (GTSDM). An integrated matching scheme based on Most Similar minimum cost (MSMC) principle is used to compare the query and target image. The adjacency matrix of a bipartite graph is formed using the sub-blocks of query and target image. This matrix is used for matching the images. The experimental results show that the proposed method has achieved highest retrieval performance. © 2011 Springer-Verlag.


Singh V.,Konkuk University | Sivaramaiah G.,Government College for Men A | Rao J.L.,Sri Venkateswara University | Sripada S.,JNTUHCE | Kim S.H.,Konkuk University
Ceramics International | Year: 2014

The BaAl12O19 powders doped with Cr3+ ions have been prepared by a low-temperature combustion synthesis method. As prepared combustion synthesized powder was characterized using powder X-ray diffraction and energy dispersive analysis of X-ray methods. The diffuse reflectance spectrum exhibits three bands characteristic of Cr3+ ions in distorted octahedral symmetry. The EPR spectra exhibit signals with the effective g values at g=1.96, 2.27 and 4.85. The signals with the effective g values at g=2.27 and 4.85 have been attributed to the isolated Cr3+ ions. The signal at g=1.96 has been attributed to the exchange coupled Cr 3+ ions. The excitation spectrum exhibits bands characteristic of Cr3+ ions in distorted octahedral symmetry. The ligand field parameter Dq and the Racah interelectronic repulsion parameters B and C have been evaluated from the excitation spectrum. The emission spectrum exhibits an intense band centered at 700 nm (14,286 cm-1) and this band has been attributed to 2Eg→4A2g transition. © 2014 Elsevier Ltd and Techna Group S.r.l.


Suresh S.,JNTUHCE | Gayathri Pavani P.,Osmania University | Chandra Mouli V.,Osmania University
Materials Research Bulletin | Year: 2012

xTeO 2 + (70 - x)B 2O 3 + 5TiO 2 + 24R 2O:1CuO (x = 10, 35 and 60; R = Li, Na and K) glass system were studied by spectroscopic techniques such as ESR, optical absorption, Raman and IR. From ESR spectra, the spin Hamiltonian parameter values indicate that the ground state of Cu 2+ is d x2- y2 and the site symmetry around the Cu 2+ ion is tetragonally distorted octahedral coordination. Bonding parameters calculated from optical absorption and ESR data are found to change with alkali oxide and TeO 2 content. Bonding parameters indicate a slight covalency for the in-plane σ bonding as compared to in-plane and out-of-plane π bonds. Both Raman and IR results show that glass network consists of TeO 3, TeO 4, BO 3, BO 4 and RiO 4 group as basic structural groups. BO 3-BO 4 - ring structure interconnected by TeO 3 - and TeO 4 - groups, where the BO 4 - groups are neighbors of the TeO 3 - groups. BO 3 → BO 4 transition is also observed, which correlates with the transition of TeO 4 → TeO 3 via TeO 3+1. © 2011 Elsevier Ltd. All rights reserved.

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