• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1538-1545
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• 1998

System reliability has been a major concern since the beginning age of the electronic digital computers. One of the modest ways of increasing reliability is to design fault-tolerant system. This paper propose a construction mechanism of fault-tolerant system for the general graph topology. This system has several spare nodes. Up to date, fault-tolerant system design is applied only to loop and tree networks. But they are very limited cases. New algorithm of this paper tried to have a capability which can be applied to any kinds of topologies without such a many restriction. the algorithm consist of several steps : minimal diameter spaning tree extraction step, optimal node decision step, original connectivity restoration step and finally redundancy graph construction step.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.876-880
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• 2009

A control flow graph(CFG) is an essential data structure for program analyses based on graph theory or control-/data- flow analyses. Esterel is an imperative synchronous language and its synchronous parallelism makes it difficult to construct a CFG of an Esterel program. In this work, we present a method to construct over-approximated CFGs for Esterel. Our method is very intuitive and generated CFGs include not only exposed paths but also invisible ones. Though the CFGs may contain some inexecutable paths due to complex combinations of parallelism and exception handling, they are very useful for other program analyses.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.1-15
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• 2024

The construction of smart communities is a new method and important measure to ensure the security of residential areas. In order to solve the problem of low accuracy in face recognition caused by distorting facial features due to monitoring camera angles and other external factors, this paper proposes the following optimization strategies in designing a face recognition network: firstly, a global graph convolution module is designed to encode facial features as graph nodes, and a multi-scale feature enhancement residual module is designed to extract facial keypoint features in conjunction with the global graph convolution module. Secondly, after obtaining facial keypoints, they are constructed as a directed graph structure, and graph attention mechanisms are used to enhance the representation power of graph features. Finally, tensor computations are performed on the graph features of two faces, and the aggregated features are extracted and discriminated by a fully connected layer to determine whether the individuals' identities are the same. Through various experimental tests, the network designed in this paper achieves an AUC index of 85.65% for facial keypoint localization on the 300W public dataset and 88.92% on a self-built dataset. In terms of face recognition accuracy, the proposed network achieves an accuracy of 83.41% on the IBUG public dataset and 96.74% on a self-built dataset. Experimental results demonstrate that the network designed in this paper exhibits high detection and recognition accuracy for faces in surveillance videos.

• Journal of the Korean Mathematical Society
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• v.45 no.5
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• pp.1243-1253
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• 2008

In this paper, we construct one-factorizations of given complete graphs of even order. These constructions partition the edges of the complete graph into one-factors and triples. Our new constructions of one-factors and triples can be applied to a recursive construction of Steiner triple systems for all possible orders ${\geq}$15.

• Journal of Korean Elementary Science Education
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• v.31 no.3
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• pp.321-333
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• 2012

The purpose of this study was to examine elementary school students' characteristics and difficulties in drawing and interpreting a line graph, and to present educational implications. Twenty five students(4th grader: 6, 5th grader: 9, and 6th grader: 10) at an elementary school participated in this study. We used a student's task which was about graphing on a given data table and interpreting his/her graph. The data table was on heating 200mL and 500mL of water and measuring their temperature at regular time intervals. We collected multiple source of data, and data analyzed based on the sub-variables of TOGS. The some results of this study are as follows: First, five children (20.0%), especially two of 10 sixth graders (20.0%), could not construct a line graph about a given data table. Second, twenty students (80.0%) had the ability on 'Scaling axes' and on 'Assigning variables to the axes', however, only a student understood why the time is on the longitudinal axis and the temperature is on the vertical axis. Third, in the case of 'Plotting points', twelve children (48.0%) could drew two graphs on a coordinate. Fourth, in the case of 'Selecting the corresponding value for Y (or X)', twenty student had little difficulty. on 'Describing the relationship between variables', seventeen students (68.0%) understood the relationship between time and temperature of water, and the relationship between temperature and amount of water. Finally, eleven students (44%) had the ability on 'Interrelating and extrapolation graphs.' Educational implications are also presented in this paper.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.256-264
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• 2020

Industrial Wireless Sensor Networks (IWSNs) is exploited to achieve various objectives such as improving productivity and reducing cost in the diversity of industrial application, and it has requirements such as low-delay and high reliability packet transmission. To accomplish the requirement, the network manager performs graph construction and resource allocation about network topology, and determines the transmission cycle and path of each node in advance. However, this network management scheme cannot treat mobile devices that cause continuous topology changes because graph reconstruction and resource reallocation should be performed as network topology changes. That is, despite the growing need of mobile devices in many industries, existing scheme cannot adequately respond to path failure caused by movement of mobile device and packet loss in the process of path recovery. To solve this problem, a network management scheme is required to prevent packet loss caused by mobile devices. Thus, we analyse the location and movement cycle of mobile devices over time using machine learning for predicting the mobility pattern. In the proposed scheme, the network manager could prevent the problems caused by mobile devices through performing graph construction and resource allocation for the predicted network topology based on the movement pattern. Performance evaluation results show a prediction rate of about 86% compared with actual movement pattern, and a higher packet delivery ratio and a lower resource share compared to existing scheme.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.05a
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• pp.171-172
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• 2013

An operation planning of lift car is crucial in tall building construction especially it's arrangement plans, because it is related with transportation distance of finishing materials affecting construction productivity. Since tall building construction, composed of complicating and huge plane have complex traffic lines of finishing materials, to determine the position of lift car empirically or intuitively has limits. Therefore this paper suggest an optimum layout model of lift car minimizing the transportation distance both at site-level and floor-level using Graph theory and Dijkstra algorithm.

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.45-55
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• 2022

BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.135-142
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• 2022

In this paper, we propose a graph-based user route control for rapidly conducting virus inspections in emergency situations (eg, COVID-19) and a framework that can simulate this on a city map. A^* and navigation mesh data structures, which are widely used pathfinding algorithms in virtual environments, are effective when applied to CS(Computer science) problems that control Agents in virtual environments because they guide only a fixed static movement path. However, it is not enough to solve the problem by applying it to the real COVID-19 environment. In particular, there are many situations to consider, such as the actual road traffic situation, the size of the hospital, the number of patients moved, and the patient processing time, rather than using only a short distance to receive a fast virus inspection.

• Journal of the Korea Society for Simulation
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• v.15 no.2
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• pp.31-39
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• 2006

The visibility graph is a well-known method for efficient path-finding with the minimum search space modelling the game world. The generalized visibility graph is constructed on the expanded obstacle boundaries to eliminate the "wall-hugging" problem which is a major disadvantage of using the visibility graph. The paths generated by the generalized visibility graph are guaranteed to be near optimal and natural-looking. In this paper we propose the method to apply the generalized visibility graph efficiently for game characters who moves among static obstacles between varying start and goal points. Even though the space is minimal once the generalized visibility graph is constructed, the construction itself is time-consuming in checking the intersection between every two links connecting nodes. The idea is that we build the map for static obstacles first and then incorporate start and goal nodes quickly. The incorporation of start and goal nodes is the part that must be executed repeatedly. Therefore we propose to use the rotational plane-sweep algorithm in the computational geometry for incorporating start and goal nodes efficiently. The simulation result shows that the execution time has been improved by 39%-68% according to running times in the game environment with multiple static obstacles.