• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1183-1193
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• 2010

The pyramid graph is well known in parallel processing as a interconnection network topology based on regular square mesh and tree architectures. The enhanced pyramid graph is an alternative architecture by exchanging mesh into the corresponding torus on the base for upgrading performance than the pyramid. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square torus as a basic sub-graph constituting of each layer in the enhanced pyramid graph. Edge set in the torus graph is considered as two disjoint sub-sets called NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or sharing in the upper layer of the enhanced pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges within the shrunk super-vertex on the resulting shrink graph. In this paper, we analyze that the lower and upper bounds on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n{\times}2^n$ torus is $2^{2n-2}$ and $3{\cdot}2^{2n-2}$ respectively. By expanding this result into the enhanced pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}$-2n+1 in the n-dimensional enhanced pyramid.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.111-123
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• 2013

To verify software vulnerability, the method of conjecturing software structure and then testing the software based on the conjectured structure has been highlighted. To utilize the method, an efficient way to conjecture software structure is required. The popular graph and tree methods such as DFG(Data Flow Graph), CFG(Control Flow Graph) and CFA(Control Flow Automata) have a serious drawback. That is, they cannot express software in a hierarchical fashion. In this paper, we propose a method to overcome the drawback. The proposed method applies various input data to a binary code, generate CFG's based on the code output and construct a HCFG (Hierarchical Control Flow Graph) to express the generated CFG's in a hierarchical structure. The components required for HCFG and progressive algorithm to construct HCFG are also proposed. The proposed method is verified through constructing the software architecture of an open SMTP(Simple Mail Transfer Protocol) server program. The structure generated by the proposed method and the real program structure are compared and analyzed.

• Journal of the Korean Institute of Landscape Architecture
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• v.32 no.1
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• pp.47-56
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• 2004

Rapid economic development in Korea caused functions of city functions such as concentration of population, deterioration of the quality of living environment and traffic congestion. Korean cities have lost their identity becausr they are merged functionally and physically with neighboring cities, forming one mesa-city. Unified shape and disorganized streets of cities often cause confusion among foreigners and visitors. It is very difficult for them to find their image in strange cities. It is, however, important to correctly analyze the image and meaning of cities for understanding its identity. The purpose of this study is to develop a method to analyze the city image by focusing on some of the main cities in Korea. For this purpose, the adjective questionnaire and multi-dimension scaling (MDS) are applied to the analysis of city image. Image analysis graph by MDS can visually present the general and integrate images. The results of this study are summarized as follows: The important factors for interpretation of city image are historical and industrial character. Seoul, Taegu and Pusan have industrial and complex city images. Kongju has historical city image, while Changwon has a modern image. Chuncheon belongs to a soft and small image. Each city has an alternative solution against a negative image, according to the image analysis graph.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.2
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• pp.53-64
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• 2018

This study aims to quantitatively evaluate the conservation priorities of unexecuted urban parks in Seoul both from an ecological and public perspective. To this end, two methodologies, ecological network analysis based on graph and circuit theory and accessibility analysis, were employed in order to assess ecological connectivity of and public accessibility to unexecuted parks, respectively. This study applied linkage-mapping methods (shortest path and current flow betweenness centrality) of connectivity analysis to an integrated map of landscape permeability. The population-weighted accessibility to unexecuted parks was measured based on a negative exponential distance decay function. As a result, for both ecological connectivity and accessibility, Gwanaksan, Suraksan, and Bulamsan urban natural parks are found to be the most important (rank 1-3) to be conserved. For these sites, inner park areas with conservation priorities for connectivity and accessibility were identified. The findings of the study can be used for giving conservation priority to the unexecuted urban parks in terms of long-term sustainable urban planning.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.73-77
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• 2007

In this paper, we propose a VLSI architecture of an LMS filter based on a Cyclo-static scheduler for fast computation of LMS filteing algorithm which is widely used in adptive filtering area. This process is composed of two steps: scheduling and circuit synthesis. The scheduling step accepts a fully specified flow graph(FSFG) as an input, and generates an optimal Cyclo-static schedule in the sense of the sampling rate, the number of processors, and the input-output delay. Then the generated schedule is transformed so that the number of communication edges between the processors. The circuit synthesis part translates the modified schedule into a complete circuit diagram by performing resource allocations. The VLSI layout generation can be performed easily by an existing silicon compiler.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.9-20
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• 2021

Abstraction applied in computer networking hides network details behind a well-defined representation by building a model that captures an essential aspect of the network system. Two current methods of representation are available, one based on graph theory, where a network node is reduced to a point in a graph, and the other the use of non-methodological iconic depictions such as human heads, walls, towers or computer racks. In this paper, we adopt an abstract representation methodology, the thinging machine (TM), proposed in software engineering to model computer networks. TM defines a single coherent network architecture and topology that is constituted from only five generic actions with two types of arrows. Without loss of generality, this paper applies TM to model the area of network monitoring in packet-mode transmission. Complex network documents are difficult to maintain and are not guaranteed to mirror actual situations. Network monitoring is constant monitoring for and alerting of malfunctions, failures, stoppages or suspicious activities in a network system. Current monitoring systems are built on ad hoc descriptions that lack systemization. The TM model of monitoring presents a theoretical foundation integrated with events and behavior descriptions. To investigate TM modeling's feasibility, we apply it to an existing computer network in a Kuwaiti enterprise to create an integrated network system that includes hardware, software and communication facilities. The final specifications point to TM modeling's viability in the computer networking field.

• Journal of Navigation and Port Research
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• v.35 no.6
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• pp.489-494
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• 2011

Present study introduces an implementation of product data management (PDM) that can be applied to the design of ship propulsion system. The PDM system is developed based on both object oriented software development environment and Open Scene Graph (OSG) library while the system architecture is modeled by the unified modeling language (UML). Suggested PDM system also integrates the modeling & simulation components required to estimate the performance of ship propulsion system as the product information is represented based on the 3-dimensional digital mock-up (DMU). Finally, functions of the implemented PDM system that is integrated with the M&S softwares are illustrated in order to suggest a practical guidance for the efficient design of ship propulsion system.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.55-59
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• 2022

Recently, IoT technology has great attention and plays a key role in 4^th industrial revolution in order to design customized products and services. Additive Manufacturing (AM) is applied to fabricate IoT sensor directly or IoT sensor embedded structure. Also, design methods for AM are developing to consolidate various parts of IoT devices. Part consolidation leads to assembly time and cost reduction, reliability improvement, and lightweight. Therefore, a design method was proposed to guide designers to consolidate parts. The design method helps designers to define product architecture that consists of functions and function-part relations. The product architecture is converted to a network graph and then Girvan Newman algorithm is applied to cluster the graph network. Parts in clusters are candidates for part consolidation. To demonstrate the usefulness of the proposed design method, a case study was performed with e-bike fabricated by additive manufacturing.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.419-437
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• 2023

As the number of thin filers in Korea surpasses 12 million, there is a growing interest in enhancing the accuracy of assessing their credit default risk to generate additional revenue. Specifically, researchers are actively pursuing the development of default prediction models using machine learning and deep learning algorithms, in contrast to traditional statistical default prediction methods, which struggle to capture nonlinearity. Among these efforts, Graph Neural Network (GNN) architecture is noteworthy for predicting default in situations with limited data on thin filers. This is due to their ability to incorporate network information between borrowers alongside conventional credit-related data. However, prior research employing graph neural networks has faced limitations in effectively handling diverse categorical variables present in credit information. In this study, we introduce the Transformer embedded Graph Convolutional Network (TeGCN), which aims to address these limitations and enable effective default prediction for thin filers. TeGCN combines the TabTransformer, capable of extracting contextual information from categorical variables, with the Graph Convolutional Network, which captures network information between borrowers. Our TeGCN model surpasses the baseline model's performance across both the general borrower dataset and the thin filer dataset. Specially, our model performs outstanding results in thin filer default prediction. This study achieves high default prediction accuracy by a model structure tailored to characteristics of credit information containing numerous categorical variables, especially in the context of thin filers with limited data. Our study can contribute to resolving the financial exclusion issues faced by thin filers and facilitate additional revenue within the financial industry.

• Korean Institute of Interior Design Journal
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• v.23 no.2
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• pp.166-173
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• 2014

This study analyzed visual-perceptual centrality as a measure to solve the confusion that might occur in visitor's movement in analyzing contemporary museums that have recently expand. Also, this study proposed a new methodology to understand the relationships of the occurrence and convergence of visual-perceptual power. The existing visibility graph analysis mostly ends up in identifying nodes corresponding to the physical environment of museums while the newly proposed visibility graph analysis is a methodology that can analyze the landmark on which the visual-perceptual power occurs and converges, by setting visible space elements as analysis variables, which showed a possibility to draw more reliable results in parallel to the existing analysis, and the results of this analysis are as follows. A public museum located in downtown has a limitation that it cannot but be multi-layered as a way to enlarge for the accommodation of a variety of programs on a limited site. Also, this study found that the problem of visitor orientation occurring in the multi-layer process was solved by a major space which was visual-perceptually void. Also, its types can be summarized into two types: One is setting parameter spaces (ramps, staircases, hallways) linked visual-perceptually to the major space and the other is solving the confusion of the visitor's movement by composing a simple exhibition space. In particular, it is judged that the type solving the confusion of the visitor's movement by composing a simple exhibition space also had a relationship with changes in the characteristics of the exhibited works by period. In addition, it was found that the entrance also appeared in two types: dependent type and independent type in the major space according to the characteristics of the major space.