• 대한기계학회논문집A
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• 제29권4호
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• pp.534-539
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• 2005

Nodal displacements are referred to the initial configuration in the total Lagrangian formulation and to the last converged configuration in the updated Lagrangian furmulation. This research proposes a relative nodal displacement method to represent the position and orientation for a node in truss structures. Since the proposed method measures the relative nodal displacements relative to its adjacent nodal reference frame, they are still small for a truss structure undergoing large deformations for the small size elements. As a consequence, element formulations developed under the small deformation assumption are still valid for structures undergoing large deformations, which significantly simplifies the equations of equilibrium. A structural system is represented by a graph to systematically develop the governing equations of equilibrium for general systems. A node and an element are represented by a node and an edge in graph representation, respectively. Closed loops are opened to form a spanning tree by cutting edges. Two computational sequences are defined in the graph representation. One is the forward path sequence that is used to recover the Cartesian nodal displacements from relative nodal displacement sand traverses a graph from the base node towards the terminal nodes. The other is the backward path sequence that is used to recover the nodal forces in the relative coordinate system from the known nodal forces in the absolute coordinate system and traverses from the terminal nodes towards the base node. One open loop and one closed loop structure undergoing large deformations are analyzed to demonstrate the efficiency and validity of the proposed method.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2005년도 추계학술대회논문집
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• pp.788-791
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• 2005

Nodal displacements are referred to the Initial configuration in the total Lagrangian formulation and to the last converged configuration in the updated Lagrangian formulation. This research proposes a relative nodal displacement method to represent the position and orientation for a node in truss structures. Since the proposed method measures the relative nodal displacements relative to its adjacent nodal reference frame, they are still small for a truss structure undergoing large deformations for the small size elements. As a consequence, element formulations developed under the small deformation assumption are still valid fer structures undergoing large deformations, which significantly simplifies the equations of equilibrium. A structural system is represented by a graph to systematically develop the governing equations of equilibrium for general systems. A node and an element are represented by a node and an edge in graph representation, respectively. Closed loops are opened to form a spanning tree by cutting edges. Two computational sequences are defined in the graph representation. One is the forward path sequence that is used to recover the Cartesian nodal displacements from relative nodal displacements and traverses a graph from the base node towards the terminal nodes. The other is the backward path sequence that is used to recover the nodal forces in the relative coordinate system from the known nodal forces in the absolute coordinate system and traverses from the terminal nodes towards the base node. One closed loop structure undergoing large deformations is analyzed to demonstrate the efficiency and validity of the proposed method.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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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.

• 한국CDE학회논문집
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• 제14권2호
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• pp.69-76
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• 2009

The development of a simulation system requires many sub modules such as a dynamic module, a visualization module, etc. If a different freeware is used for each sub modules, it is hard to develop the simulation system by incorporating them because they use their own data structures. To solve this problem, a high-level data structure, called Dynamics Scene Graph Data structure (DSGD) is proposed, by wrapping data structures of two freeware; an Open Dynamics Engine (ODE) for the dynamic module and an Open Scene Graph (OSG) for the visualization module. Finally, to evaluate the applicability of the proposed data structure, it is applied to the block erection simulation in shipbuilding. The result shows that it can be used for developing the simulation system.

• 한국경영과학회지
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• 제30권1호
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• pp.187-198
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• 2005

The structure of a Web site can prevent the search robots or crawling agents from confusion in the midst of huge forest of the Web pages. We formalize the view on the World Wide Web and generalize it as a hierarchy of Web objects such as the Web as a set of Web sites, and a Web site as a directed graph with Web nodes and Web edges. Our approach results in the optimal hierarchical structure that can maximize the weight, tf-idf (term frequency and inverse document frequency), that is one of the most widely accepted content centric measures in the information retrieval community, so that the measure can be used to embody the semantics of search query. The experimental results represent that the optimization model is an effective alternative in the dynamically changing Web environment by replacing conventional heuristic approaches.

• 로봇학회논문지
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• 제16권2호
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• pp.122-129
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• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• Smart Structures and Systems
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• 제3권1호
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• pp.1-22
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• 2007

The energy efficiency of a self-powered wireless sensing system for pressure monitoring in injection molding is analyzed using Bond graph models. The sensing system, located within the mold cavity, consists of an energy converter, an energy modulator, and a ultrasonic signal transmitter. Pressure variation in the mold cavity is extracted by the energy converter and transmitted through the mold steel to a signal receiver located outside of the mold, in the form of ultrasound pulse trains. Through Bond graph models, the energy efficiency of the sensing system is characterized as a function of the configuration of a piezoceramic stack within the energy converter, the pulsing cycle of the energy modulator, and the thicknesses of the various layers that make up the ultrasonic signal transmitter. The obtained energy models are subsequently utilized to identify the minimum level of signal intensity required to ensure successful detection of the ultrasound pulse trains by the signal receiver. The Bond graph models established have shown to be useful in optimizing the design of the various constituent components within the sensing system to achieve high energy conversion efficiency under a compact size, which are critical to successful embedment within the mold structure.

• 대한수학회논문집
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• 제34권2호
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• pp.415-427
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• 2019

Let R be an associative ring with nonzero identity. The annihilator ideal graph of R, denoted by ${\Gamma}_{Ann}(R)$, is a graph whose vertices are all nonzero proper left ideals and all nonzero proper right ideals of R, and two distinct vertices I and J are adjacent if $I{\cap}({\ell}_R(J){\cup}r_R(J)){\neq}0$ or $J{\cap}({\ell}_R(I){\cup}r_R(I)){\neq}0$, where ${\ell}_R(K)=\{b{\in}R|bK=0\}$ is the left annihilator of a nonempty subset $K{\subseteq}R$, and $r_R(K)=\{b{\in}R|Kb=0\}$ is the right annihilator of a nonempty subset $K{\subseteq}R$. In this paper, we assume that R is a semicommutative ring. We study the structure of ${\Gamma}_{Ann}(R)$. Also, we investigate the relations between the ring-theoretic properties of R and graph-theoretic properties of ${\Gamma}_{Ann}(R)$. Moreover, some combinatorial properties of ${\Gamma}_{Ann}(R)$, such as domination number and clique number, are studied.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제27권4호
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• pp.324-341
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• 2023

Topological data analysis (TDA) is a data analysis technique, recently developed, that investigates the overall shape of a given dataset. The mapper algorithm is a TDA method that considers the connectivity of the given data and converts the data into a mapper graph. Compared to persistent homology, another popular TDA tool, that mainly focuses on the homological structure of the given data, the mapper algorithm is more of a visualization method that represents the given data as a graph in a lower dimension. As it visualizes the overall data connectivity, it could be used as a prediction method that visualizes the new input points on the mapper graph. The existing mapper packages such as Giotto-TDA, Gudhi and Kepler Mapper provide the descriptive mapper algorithm, that is, the final output of those packages is mainly the mapper graph. In this paper, we develop a simple predictive algorithm. That is, the proposed algorithm identifies the node information within the established mapper graph associated with the new emerging data point. By checking the feature of the detected nodes, such as the anomality of the identified nodes, we can determine the feature of the new input data point. As an example, we employ the fraud credit card transaction data and provide an example that shows how the developed algorithm can be used as a node prediction method.

• 지능정보연구
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• 제25권3호
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• pp.161-177
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• 2019

질의응답 시스템은 크게 사용자의 질의를 분석하는 방법인 질의 분석과 문서 내에서 적합한 정답을 추출하는 방법인 정답 추출로 이루어지며, 두 방법에 대한 다양한 연구들이 진행되고 있다. 본 연구에서는 문장의 의존 구문 분석 결과를 이용하여 질의응답 시스템 내 정답 추출의 성능 향상을 위한 연구를 진행한다. 정답 추출의 성능을 높이기 위해서는 문장의 문법적인 정보를 정확하게 반영할 필요가 있다. 한국어의 경우 어순 구조가 자유롭고 문장의 구성 성분 생략이 빈번하기 때문에 의존 문법에 기반한 의존 구문 분석이 적합하다. 기존에 의존 구문 분석을 질의응답 시스템에 반영했던 연구들은 구문 관계 정보나 구문 형식의 유사도를 정의하는 메트릭을 사전에 정의해야 한다는 한계점이 있었다. 또 문장의 의존 구문 분석 결과를 트리 형태로 표현한 후 트리 편집 거리를 계산하여 문장의 유사도를 계산한 연구도 있었는데 이는 알고리즘의 연산량이 크다는 한계점이 존재한다. 본 연구에서는 구문 패턴에 대한 정보를 사전에 정의하지 않고 정답 후보 문장을 그래프로 나타낸 후 그래프 정보를 효과적으로 반영할 수 있는 Graph2Vec을 활용하여 입력 자질을 생성하였고, 이를 정답 추출모델의 입력에 추가하여 정답 추출 성능 개선을 시도하였다. 의존 그래프를 생성하는 단계에서 의존 관계의 방향성 고려 여부와 노드 간 최대 경로의 길이를 다양하게 설정하며 자질을 생성하였고, 각각의 경우에 따른 정답추출 성능을 비교하였다. 본 연구에서는 정답 후보 문장들의 신뢰성을 위하여 웹 검색 소스를 한국어 위키백과, 네이버 지식백과, 네이버 뉴스로 제한하여 해당 문서에서 기존의 정답 추출 모델보다 성능이 향상함을 입증하였다. 본 연구의 실험을 통하여 의존 구문 분석 결과로 생성한 자질이 정답 추출 시스템 성능 향상에 기여한다는 것을 확인하였고 해당 자질을 정답 추출 시스템뿐만 아니라 감성 분석이나 개체명 인식과 같은 다양한 자연어 처리 분야에 활용 될 수 있을 것으로 기대한다.