• Journal of Information Processing Systems
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• v.14 no.3
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• pp.709-726
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• 2018

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.263-270
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• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Journal of applied mathematics & informatics
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• v.41 no.4
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• pp.839-848
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• 2023

Let G be a simple undirected graph. A planar graph known as a Halin graph(HG) is characterised by having three connected and pendent vertices of a tree that are connected by an outer cycle. A subset S of V is said to be a dominating set of the graph G if each vertex u that is part of V is dominated by at least one element v that is a part of S. The domination number of a graph is denoted by the γ(G), and it corresponds to the minimum size of a dominating set. A dominating set S is called a secure dominating set if for each v ∈ V＼S there exists u ∈ S such that v is adjacent to u and S₁ = (S＼{v}) ∪ {u} is a dominating set. The minimum cardinality of a secure dominating set of G is equal to the secure domination number γ_s(G). In this article we found the secure domination number of Halin graph(HG) with perfet k-ary tree and also we determined secure domination of rooted product of special trees.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.488-498
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• 2007

This paper presents a novel approach for representing the spatio-temporal topology of the camera network with overlapping and non-overlapping fields of view (FOVs) in Ubiquitous Smart Space (USS). The topology is determined by tracking moving objects and establishing object correspondence across multiple cameras. To track people successfully in multiple camera views, we used the Merge-Split (MS) approach for object occlusion in a single camera and the grid-based approach for extracting the accurate object feature. In addition, we considered the appearance of people and the transition time between entry and exit zones for tracking objects across blind regions of multiple cameras with non-overlapping FOVs. The main contribution of this paper is to estimate transition times between various entry and exit zones, and to graphically represent the camera topology as an undirected weighted graph using the transition probabilities.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.107-113
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• 2015

This paper presents a polynomial time algorithm to the minimum cardinality feedback edge set and minimum weight feedback edge set problems. The algorithm makes use of the property wherein the sum of the minimum spanning tree edge set and the minimum feedback edge set equals a given graph's edge set. In other words, the minimum feedback edge set is inherently a complementary set of the former. The proposed algorithm, in pursuit of the optimal solution, modifies the minimum spanning tree finding Kruskal's algorithm so as to arrange the weight of edges in a descending order and to assign cycle-deficient edges to the maximum spanning tree edge set MXST and cycle-containing edges to the feedback edge set FES. This algorithm runs with linear time complexity, whose execution time corresponds to the number of edges of the graph. When extensively tested on various undirected graphs both with and without the weighed edge, the proposed algorithm has obtained the optimal solutions with 100% success and accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.1
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• pp.173-182
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• 2001

In this paper, we discuss how ontology Plays roles in building a distributed and heterogeneous knowledge-base system. First, we discuss relationship between ontology and agent in the Knowledgeable Community which is a framework of knowledge sharing and reuse based on a multi-agent architecture. Ontology is a minimum requirement for each agent to join the Knowledgeable Community. Second we explain mediation by ontology to show how ontology is used in the Knowledgeable Community. A special agent called mediation analyzes undirected messages and infer candidates of recipient agents by consulting ontology and relationship between ontology and agents. Third we model ontology as combination of aspects each of which can represent a way of conceptualization. Aspects are combined either as combination aspect which means integration of aspects or category aspect which means choice of aspects. Since ontology by aspect allows heterogeneous and multiple descriptions for phenomenon in the world, it is appropriate for heterogeneous knowledge-base systems. We also show translation of messages as a wave of interpreting multiple aspects. A translation agent can translate a message with some aspect to one with another aspect by analyzing dependency of aspects. Mediation and translation of messages are important to build agents easily and naturally because less knowledge on other agents is requested for each agent.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.358-377
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• 2015

In this paper, we propose a novel approach for trajectory recovery. Our system uses a triangulation procedure for skeletonization and graph theory to extract the trajectory. Skeletonization extracts the polyline skeleton according to the polygonal contours of the handwritten characters, and as a result, the junction becomes clear and the characters that are touching each other are separated. The approach for the trajectory recovery is based on graph theory to find the optimal path in the graph that has the best representation of the trajectory. An undirected graph model consisting of one or more strokes is constructed from a polyline skeleton. By using the polyline skeleton, our approach accelerates the process to search for an optimal path. In order to evaluate the performance, we built our own dataset, which includes testing and ground-truth. The dataset consist of thousands of handwritten characters and word images, which are extracted from five handwritten documents. To show the relative advantage of our skeletonization method, we first compare the results against those from Zhang-Suen, a state-of-the-art skeletonization method. For the trajectory recovery, we conduct a comparison using the Root Means Square Error (RMSE) and Dynamic Time Warping (DTW) in order to measure the error between the ground truth and the real output. The comparison reveals that our approach has better performance for both the skeletonization stage and the trajectory recovery stage. Moreover, the processing time comparison proves that our system is faster than the existing systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.171-176
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• 2020

This paper proposes polynomial-time algorithm for maximum weighted independent set(MWIS) problem that is well known as NP-hard. The known algorithms for MWIS problem are polynomial-time to specialized in particular graph type, distributed, or clustering method. But there is no unified algorithm is suitable to all kinds of graph types. Therefore, this paper suggests unique polynomial-time algorithm that is suitable to all kinds of graph types. The proposed algorithm merges the maximum weighted vertex v_i and maximum weighted vertex v_j that is not adjacent to v_i. As a result of apply to undirected graphs and trees, this algorithm can be get the optimal solution. This algorithm improves previously known solution to new optimal solution.

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.64-76
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• 2020

Scientometrics and social network analysis (SNA) measures were used to analyze the international scientific collaboration (ISC) of All India Institute of Medical Sciences (AIIMS) for a period of 10 years (2009-2018). The dataset consists of 19,622 records retrieved from the Scopus database. The mean degree of collaboration 0.95 implied that researchers of AIIMS tend to collaborate domestically (80.29%) and internationally (14.67%). The data exhibits a hyper authorship pattern, and a medium-size research team consists of 4 to 10 authors who contributed a maximum of 62.08% (12,182) publications. 71.97% of research findings are scattered in journal articles. The most preferred journals published 58.55% of medical literature. An undirected collaboration network is constructed in Pajek to study the ISC of AIIMS during the period 2009-2018 which consists of 179 vertices (Vn) and 11,938 edges. The degree centrality (Dc) identified that the United States of America (Dc - 54; CC - 0.99) and United Kingdom (Dc - 41; 0.98) are the most collaborative countries in the whole network as well as the most influential countries. The Louvain community detection method is used to detect influential research groups of AIIMS. The temporal evolution of ISC of AIIMS studied through scientometrics and SNA measures shed light on the structure and properties of ISC networks of AIIMS. It revealed that AIIMS, India has taken keen steps to enrich the quality of research by extending and encouraging the collaboration between institutions and industries at the international level.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.403-410
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• 2021

Given an undirected simple graph, k-club is one of the proposed structures to model social groups that exist in various types in Social Network Analysis (SNA). Maximum k-Club Problem (MkCP) is to find a k-club of maximum cardinality in a graph. This paper introduces a Genetic Algorithm called HGA+DROP which can be used to approximate maximum k-club in graphs. Our algorithm modifies the existing k-CLIQUE & DROP algorithm and utilizes Heuristic Genetic Algorithms (HGA) to obtain multiple k-clubs. We experiment on DIMACS graphs for k = 2, 3, 4 and 5 to compare the performance of the proposed algorithm with existing algorithms.