Now showing items 1-20 of 49
Next PageAbstract: | The Majority Strategy for finding medians of a set of clients on a graph can be relaxed in the following way: if we are at v, then we move to a neighbor w if there are at least as many clients closer to w than to v (thus ignoring the clients at equal distance from v and w). The graphs on which this Plurality Strategy always finds the set of all medians are precisely those for which the set of medians induces always a connected subgraph |
Description: | Report/Econometric Institute, Erasmus University Rotterdam |
URI: | http://dyuthi.cusat.ac.in/purl/4208 |
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The Plurality Strategy on Graphs.pdf | (149.0Kb) |
Abstract: | Following the Majority Strategy in graphs, other consensus strategies, namely Plurality Strategy, Hill Climbing and Steepest Ascent Hill Climbing strategies on graphs are discussed as methods for the computation of median sets of pro¯les. A review of algorithms for median computation on median graphs is discussed and their time complexities are compared. Implementation of the consensus strategies on median computation in arbitrary graphs is discussed |
Description: | Report/Econometric Institute, Erasmus University Rotterdam,EI 2007-34 |
URI: | http://dyuthi.cusat.ac.in/purl/4218 |
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Median computat ... g consensus strategies.pdf | (195.4Kb) |
Abstract: | The median of a profile = (u1, . . . , uk ) of vertices of a graph G is the set of vertices x that minimize the sum of distances from x to the vertices of . It is shown that for profiles with diameter the median set can be computed within an isometric subgraph of G that contains a vertex x of and the r -ball around x, where r > 2 − 1 − 2 /| |. The median index of a graph and r -joins of graphs are introduced and it is shown that r -joins preserve the property of having a large median index. Consensus strategies are also briefly discussed on a graph with bounded profiles. |
Description: | Discrete Applied Mathematics 156 (2008) 2882–2889 |
URI: | http://dyuthi.cusat.ac.in/purl/4216 |
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The median func ... with bounded profiles.pdf | (410.2Kb) |
Abstract: | Antimedian graphs are introduced as the graphs in which for every triple of vertices there exists a unique vertex x that maximizes the sum of the distances from x to the vertices of the triple. The Cartesian product of graphs is antimedian if and only if its factors are antimedian. It is proved that multiplying a non-antimedian vertex in an antimedian graph yields a larger antimedian graph. Thin even belts are introduced and proved to be antimedian. A characterization of antimedian trees is given that leads to a linear recognition algorithm. |
URI: | http://dyuthi.cusat.ac.in/xmlui/purl/2009 |
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Antimedian graphs.pdf | (151.5Kb) |
Abstract: | The set of vertices that maximize (minimize) the remoteness is the antimedian (median) set of the profile. It is proved that for an arbitrary graph G and S V (G) it can be decided in polynomial time whether S is the antimedian set of some profile. Graphs in which every antimedian set is connected are also considered. |
URI: | http://dyuthi.cusat.ac.in/purl/4217 |
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On the generali ... blemantimedian subsets.pdf | (142.4Kb) |
Abstract: | A periphery transversal of a median graph G is introduced as a set of vertices that meets all the peripheral subgraphs of G. Using this concept, median graphs with geodetic number 2 are characterized in two ways. They are precisely the median graphs that contain a periphery transversal of order 2 as well as the median graphs for which there exists a profile such that the remoteness function is constant on G. Moreover, an algorithm is presented that decides in O(mlog n) time whether a given graph G with n vertices and m edges is a median graph with geodetic number 2. Several additional structural properties of the remoteness function on hypercubes and median graphs are obtained and some problems listed |
Description: | University of Ljubljana Institute of Mathematics, Physics and Mechanics Department of Mathematics Preprint series, Vol. 46 (2008), 1046 |
URI: | http://dyuthi.cusat.ac.in/purl/4237 |
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Median Graphs, ... nd Geodetic Number Two.pdf | (256.4Kb) |
Abstract: | The median (antimedian) set of a profile π = (u1, . . . , uk) of vertices of a graphG is the set of vertices x that minimize (maximize) the remoteness i d(x,ui ). Two algorithms for median graphs G of complexity O(nidim(G)) are designed, where n is the order and idim(G) the isometric dimension of G. The first algorithm computes median sets of profiles and will be in practice often faster than the other algorithm which in addition computes antimedian sets and remoteness functions and works in all partial cubes |
Description: | Algorithmica (2010) 57: 207–216 DOI 10.1007/s00453-008-9200-4 |
URI: | http://dyuthi.cusat.ac.in/purl/4193 |
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Computing median and antimedian sets in median.pdf | (290.4Kb) |
Abstract: | A graph G is strongly distance-balanced if for every edge uv of G and every i 0 the number of vertices x with d.x; u/ D d.x; v/ 1 D i equals the number of vertices y with d.y; v/ D d.y; u/ 1 D i. It is proved that the strong product of graphs is strongly distance-balanced if and only if both factors are strongly distance-balanced. It is also proved that connected components of the direct product of two bipartite graphs are strongly distancebalanced if and only if both factors are strongly distance-balanced. Additionally, a new characterization of distance-balanced graphs and an algorithm of time complexity O.mn/ for their recognition, wheremis the number of edges and n the number of vertices of the graph in question, are given |
Description: | European Journal of Combinatorics 30 (2009) 1048- 1053 |
URI: | http://dyuthi.cusat.ac.in/purl/4198 |
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Strongly distan ... phs and graph products.pdf | (373.0Kb) |
Abstract: | A profile on a graph G is any nonempty multiset whose elements are vertices from G. The corresponding remoteness function associates to each vertex x 2 V.G/ the sum of distances from x to the vertices in the profile. Starting from some nice and useful properties of the remoteness function in hypercubes, the remoteness function is studied in arbitrary median graphs with respect to their isometric embeddings in hypercubes. In particular, a relation between the vertices in a median graph G whose remoteness function is maximum (antimedian set of G) with the antimedian set of the host hypercube is found. While for odd profiles the antimedian set is an independent set that lies in the strict boundary of a median graph, there exist median graphs in which special even profiles yield a constant remoteness function. We characterize such median graphs in two ways: as the graphs whose periphery transversal number is 2, and as the graphs with the geodetic number equal to 2. Finally, we present an algorithm that, given a graph G on n vertices and m edges, decides in O.mlog n/ time whether G is a median graph with geodetic number 2 |
Description: | Discrete Applied Mathematics 157 (2009) 3679- 3688 |
URI: | http://dyuthi.cusat.ac.in/purl/4197 |
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On the remoteness function in median graphs.pdf | (609.5Kb) |
Abstract: | Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task. |
Description: | Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on |
URI: | http://dyuthi.cusat.ac.in/purl/4190 |
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Speech Recognition of Malayalam Numbers.pdf | (243.0Kb) |
Abstract: | This work proposes a parallel genetic algorithm for compressing scanned document images. A fitness function is designed with Hausdorff distance which determines the terminating condition. The algorithm helps to locate the text lines. A greater compression ratio has achieved with lesser distortion |
Description: | 2010 International Conference on Electronics and Information Engineering (ICEIE 2010) vol 2,V2-483-V2-487 |
URI: | http://dyuthi.cusat.ac.in/purl/4215 |
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Parallel Geneti ... mpression Optimization.pdf | (793.8Kb) |
Abstract: | The distance DG(v) of a vertex v in an undirected graph G is the sum of the distances between v and all other vertices of G. The set of vertices in G with maximum (minimum) distance is the antimedian (median) set of a graph G. It is proved that for arbitrary graphs G and J and a positive integer r 2, there exists a connected graph H such that G is the antimedian and J the median subgraphs of H, respectively, and that dH(G, J) = r. When both G and J are connected, G and J can in addition be made convex subgraphs of H. |
Description: | Networks vol 56(2),pp 90-94 |
URI: | http://dyuthi.cusat.ac.in/purl/4203 |
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Simultaneous Em ... d Antimedian Subgraphs.pdf | (146.2Kb) |
Abstract: | The aim of this study is to show the importance of two classification techniques, viz. decision tree and clustering, in prediction of learning disabilities (LD) of school-age children. LDs affect about 10 percent of all children enrolled in schools. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Decision trees and clustering are powerful and popular tools used for classification and prediction in Data mining. Different rules extracted from the decision tree are used for prediction of learning disabilities. Clustering is the assignment of a set of observations into subsets, called clusters, which are useful in finding the different signs and symptoms (attributes) present in the LD affected child. In this paper, J48 algorithm is used for constructing the decision tree and K-means algorithm is used for creating the clusters. By applying these classification techniques, LD in any child can be identified |
URI: | http://dyuthi.cusat.ac.in/purl/4192 |
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Significance Of ... Learning Disabilities.pdf | (200.4Kb) |
Abstract: | This paper attempts to develop an improved tool, which would read two dimensional(2D) cardiac MRI images and compute areas and volume of the scar tissue. Here the computation would be done on the cardiac MR images to quantify the extent of damage inflicted by myocardial infarction on the cardiac muscle (myocardium) using Interpolation |
Description: | PROCEEDINGS OF ICETECT 2011 |
URI: | http://dyuthi.cusat.ac.in/purl/4236 |
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Area and Volume ... rt using Interpolation.pdf | (2.006Mb) |
Abstract: | In our study we use a kernel based classification technique, Support Vector Machine Regression for predicting the Melting Point of Drug – like compounds in terms of Topological Descriptors, Topological Charge Indices, Connectivity Indices and 2D Auto Correlations. The Machine Learning model was designed, trained and tested using a dataset of 100 compounds and it was found that an SVMReg model with RBF Kernel could predict the Melting Point with a mean absolute error 15.5854 and Root Mean Squared Error 19.7576 |
Description: | PROCEEDINGS OF ICETECT 2011 |
URI: | http://dyuthi.cusat.ac.in/purl/4235 |
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Using Neural Ne ... Drug – like compounds.pdf | (1.156Mb) |
Abstract: | Performance of any continuous speech recognition system is dependent on the accuracy of its acoustic model. Hence, preparation of a robust and accurate acoustic model lead to satisfactory recognition performance for a speech recognizer. In acoustic modeling of phonetic unit, context information is of prime importance as the phonemes are found to vary according to the place of occurrence in a word. In this paper we compare and evaluate the effect of context dependent tied (CD tied) models, context dependent (CD) and context independent (CI) models in the perspective of continuous speech recognition of Malayalam language. The database for the speech recognition system has utterance from 21 speakers including 11 female and 10 males. Our evaluation results show that CD tied models outperforms CI models over 21%. |
Description: | Procedia Engineering,vol 30,pp 1081-1088 |
URI: | http://dyuthi.cusat.ac.in/purl/4211 |
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Development & e ... ous speech recognition.pdf | (444.9Kb) |
Abstract: | This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees. |
Description: | (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 2 (2) , 2011, 829-835 |
URI: | http://dyuthi.cusat.ac.in/purl/4202 |
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Prediction of L ... SVM and Decision Tree.pdf | (385.3Kb) |
Abstract: | Content Based Image Retrieval is one of the prominent areas in Computer Vision and Image Processing. Recognition of handwritten characters has been a popular area of research for many years and still remains an open problem. The proposed system uses visual image queries for retrieving similar images from database of Malayalam handwritten characters. Local Binary Pattern (LBP) descriptors of the query images are extracted and those features are compared with the features of the images in database for retrieving desired characters. This system with local binary pattern gives excellent retrieval performance |
Description: | Neural Computing and Applications Vol 21(7),pp 1757-1763 |
URI: | http://dyuthi.cusat.ac.in/purl/4207 |
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Content Based I ... Handwritten Characters.pdf | (547.1Kb) |
Abstract: | This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children |
Description: | International Journal of Computer and Electrical Engineering, Vol.3, No.1, February, 2011 1793-8163 |
URI: | http://dyuthi.cusat.ac.in/purl/4194 |
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Prediction of K ... ldren Using Rough Sets.pdf | (1.457Mb) |
Abstract: | An antimedian of a pro le = (x1; x2; : : : ; xk) of vertices of a graph G is a vertex maximizing the sum of the distances to the elements of the pro le. The antimedian function is de ned on the set of all pro les on G and has as output the set of antimedians of a pro le. It is a typical location function for nding a location for an obnoxious facility. The `converse' of the antimedian function is the median function, where the distance sum is minimized. The median function is well studied. For instance it has been characterized axiomatically by three simple axioms on median graphs. The median function behaves nicely on many classes of graphs. In contrast the antimedian function does not have a nice behavior on most classes. So a nice axiomatic characterization may not be expected. In this paper such a characterization is obtained for the two classes of graphs on which the antimedian is well-behaved: paths and hypercubes. |
Description: | Discrete Mathematics, Algorithms and Applications |
URI: | http://dyuthi.cusat.ac.in/purl/4201 |
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Axiomatic Chara ... n Paths and Hypercubes.pdf | (173.6Kb) |
Now showing items 1-20 of 49
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