• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.211-222
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• 1998

Parametric design is an important modeling paradigm in CAD/CAM applications, enabling efficient design modifications and variations. One of the major issues in parametric design is to develop a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this appear, we propose a new approach to geometric constraint solving that employs a graph-based method to solve the ruler-and-compass constructible configurations and a numerical method to solve the ruler-and-compass non-constructible configurations, in a way that combines the advantages of both methods. The geometric constraint solving process consists of two phases: 1) planning phase and 2) execution phase. In the planning phase, a sequence of construction steps is generated by clustering the constrained geometric entities and reducing the constraint graph in sequence. in the execution phase, each construction step is evaluated to determine the geometric entities, using both approaches. By combining the advantages of the graph-based constructive approach with the universality of the numerical approach, the proposed approach can maximize the efficiency, robustness, and extensibility of geometric constraint solver.

• Korean Journal of Computational Design and Engineering
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• v.6 no.2
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• pp.78-88
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• 2001

In order to adopt feature-based parametric modeling, CAD/CAM applications must have a geometric constraint solver that can handle a large set of geometric configurations efficiently and robustly. In this paper, we describe a graph constructive approach to solving geometric constraint problems. Usually, a graph constructive approach is efficient, however it has its limitation in scope; it cannot handle ruler-and-compass non-constructible configurations and under-constrained problems. To overcome these limitations. we propose an algorithm that isolates ruler-and-compass non-constructible configurations from ruler-and-compass constructible configurations and applies numerical calculation methods to solve them separately. This separation can maximize the efficiency and robustness of a geometric constraint solver. Moreover, the solver can handle under-constrained problems by classifying under-constrained subgraphs to simplified cases by applying classification rules. Then, it decides the calculating sequence of geometric entities in each classified case and calculates geometric entities by adding appropriate assumptions or constraints. By extending the clustering types and defining several rules, the proposed approach can overcome limitations of previous graph constructive approaches which makes it possible to develop an efficient and robust geometric constraint solver.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.173-181
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• 2006

In this paper, an integration framework of Geometric Constraint Solving Engine and AutoCAD is presented, and a dynamic geometric constraint system is introduced. According to inherent orientation features of geometric entities and various Object Snap results of AutoCAD, the' proposed system can automatically construct an under-constrained geometric constraint model during interactive drawing. And then the directed constraint graph in a geometric constraint model is realtime modified in order to produce an optimal constraint solving sequence. Due to the open object-oriented characteristics of AutoCAD, a set of user-defined entities including basic geometric elements and graphics constraint relations are defined through derivation. And the custom-made Object Reactor and Command Reactor are also constructed. Several powerful characteristics are achieved based on these user-defined entities and reactors, including synchronously processing geometric constraint information while saving and opening DWG files, visual constraint relations, and full adaptability to Undo/Redo operations. These characteristics of the proposed system can help the designers more easily manage geometric entities and constraint relations between them.

• Korean Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.145-153
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• 1998

An approach has been developed to generate parametric models with Boolean operations. The approach combines Boolean operations and graph manipulation on the constraints imposed on primitives. A Boolean operation is first performed on two primitives and new geometric elements such as vertices and edges are computed. Then to generate the constraint graph of the polygon the each constraints graph of two primitives are merged by adding the new geometric elements with its corresponding constraints. In the merging process, some of the geometric elements belonging to the primitives may be eliminated based on its contribution to the polygon. A computer implementation in a 2D space is described to illustrate the approach with examples.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.267-271
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• 2005

The goal of data mining is to extract new and useful knowledge from large scale datasets. As the amount of available data grows explosively, it became vitally important to develop faster data mining algorithms for various types of data. Recently, an interest in developing data mining algorithms that operate on graphs has been increased. Especially, mining frequent patterns from structured data such as graphs has been concerned by many research groups. A graph is a highly adaptable representation scheme that used in many domains including chemistry, bioinformatics and physics. For example, the chemical structure of a given substance can be modelled by an undirected labelled graph in which each node corresponds to an atom and each edge corresponds to a chemical bond between atoms. Internet can also be modelled as a directed graph in which each node corresponds to an web site and each edge corresponds to a hypertext link between web sites. Notably in bioinformatics area, various kinds of newly discovered data such as gene regulation networks or protein interaction networks could be modelled as graphs. There have been a number of attempts to find useful knowledge from these graph structured data. One of the most powerful analysis tool for graph structured data is frequent subgraph analysis. Recurring patterns in graph data can provide incomparable insights into that graph data. However, to find recurring subgraphs is extremely expensive in computational side. At the core of the problem, there are two computationally challenging problems. 1) Subgraph isomorphism and 2) Enumeration of subgraphs. Problems related to the former are subgraph isomorphism problem (Is graph A contains graph B?) and graph isomorphism problem(Are two graphs A and B the same or not?). Even these simplified versions of the subgraph mining problem are known to be NP-complete or Polymorphism-complete and no polynomial time algorithm has been existed so far. The later is also a difficult problem. We should generate all of 2$^n$ subgraphs if there is no constraint where n is the number of vertices of the input graph. In order to find frequent subgraphs from larger graph database, it is essential to give appropriate constraint to the subgraphs to find. Most of the current approaches are focus on the frequencies of a subgraph: the higher the frequency of a graph is, the more attentions should be given to that graph. Recently, several algorithms which use level by level approaches to find frequent subgraphs have been developed. Some of the recently emerging applications suggest that other constraints such as connectivity also could be useful in mining subgraphs : more strongly connected parts of a graph are more informative. If we restrict the set of subgraphs to mine to more strongly connected parts, its computational complexity could be decreased significantly. In this paper, we present an efficient algorithm to mine frequent subgraphs that are more strongly connected. Experimental study shows that the algorithm is scaling to larger graphs which have more than ten thousand vertices.

• Journal of Internet Computing and Services
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• v.7 no.5
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• pp.109-121
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• 2006

In this paper, we suggest lattice based role graph security management model which changes security level in mandatory access control model as well as constraint and role hierarchy systematically in role base access control model. In this model, we solved privilege abuse of senior role that is role graph model's problem, and when produce conflict between privileges, we can keep integrity of information by reseting grade of subject through constraint. Also, we offer strong security function by doing to be controlled by subject's security level as well as privilege inheritance by role hierarchy, Finally, we present the role graph algorithms with logic to disallow roles that contain conflicting privileges.

• Journal of the Korea Computer Graphics Society
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• v.22 no.4
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• pp.11-19
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• 2016

In this paper, we propose an automatic segmentation method of renal parenchyma on abdominal CT image using graph-cuts with shape constraint based on multi-probabilistic atlas. The proposed method consists of following three steps. First, to use the various shape information of renal parenchyma, multi-probabilistic atlas is generated by cortex-based similarity registration. Second, initial seeds for graph-cuts are extracted by maximum a posteriori (MAP) estimation and renal parenchyma is segmented by graph-cuts with shape constraint. Third, to reduce alignment error of probabilistic atlas and increase segmentation accuracy, registration and segmentation are iteratively performed. To evaluate the performance of proposed method, qualitative and quantitative evaluation are performed. Experimental results show that the proposed method avoids a leakage into neighbor regions with similar intensity of renal parenchyma and shows improved segmentation accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.267-270
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• 2001

A lot of efforts have been made to analyze the performance of the vehicle equipped with automatic transmission through simulation. It might be necessary to understand the different types of transmissions, i.e., different power flows, for different models. If there is a module that can be applied to different types of automatic transmission, it could be helpful to transmission-related engineers. This study has started up from this idea. The common bond graph has been obtained from several types of the automatic transmission. The overall generalized equations and kinematic constraint equations have been derived using virtual power sources on common bond graph. They are used to derive state equations and constraints. These equations have been applied as an application to the vehicle equipped with two simple planetary gear set type of Ravigneaux gear type automatic transmission. The state equation, kinematic constraints, and dynamic constraints have been derived in every gear and shift operation using overall generalized equations and kinematic constraint equations. Simulations for constraint speed running, standing-start running, rolling-start running, and LA-4 mode have been conducted to analyze the performance of the vehicle powertrain using GVPS(Generalized Vehicle Powertrain Simulation) program wit pull down menus.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.5
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• pp.73-85
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• 1997

An automatic transmission is an important element of automotive power systems that allows a driving convenience. Compared to a manual transmission, however, it has a few problems in efficiency, shift feel, and maintenance. To improve these, it is imperative to understand the dynamics of automatic transmissions. This paper develops a dynamically-correct model of an automatic transmission, using the bond graph method. The bond graph method is ideally suited for modeling power systems, because the method is based on generalized power variables. The bond graph method is capable of providing correct dynamic constraints and kinematic constraints, as well as the governing differential equations of motion. The bond graph method is applied to 1-4 in-gear ranges, as well as various upshifts and downshifts of an automatic transmission, which allows an accurate simulation of an automatic transmission. Conventional automatic transmission models have no dynamic constraint, which do not allow correct simulation studies.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.115-123
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• 1989

This paper describes a new method of mask compaction to formulate a mixed integer linear programming problem from a user defined stick diagram. By solving this mixed integer program, a compacted and design rule violation free layout is obtained. Also, a new efficient algorithm is given which solves the longest problem in the constraint graph.