• 로봇학회논문지
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• 제19권2호
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• pp.196-202
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• 2024

The ability to understand given environments and plan a sequence of actions leading to goal state is crucial for personal service robots. With recent advancements in deep learning, numerous studies have proposed methods for state representation in planning. However, previous works lack explicit information about relationships between objects when the state observation is converted to a single visual embedding containing all state information. In this paper, we introduce graph-based state representation that incorporates both object and relationship features. To leverage these advantages in addressing the task planning problem, we propose a Graph Neural Network (GNN)-based subgoal prediction model. This model can extract rich information about object and their interconnected relationships from given state graph. Moreover, a search-based algorithm is integrated with pre-trained subgoal prediction model and state transition module to explore diverse states and find proper sequence of subgoals. The proposed method is trained with synthetic task dataset collected in simulation environment, demonstrating a higher success rate with fewer additional searches compared to baseline methods.

• ETRI Journal
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• 제38권4호
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• pp.714-723
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• 2016

Considerable attention has been given to processing graph data in recent years. An efficient method for computing the node proximity is one of the most challenging problems for many applications such as recommendation systems and social networks. Regarding large-scale, mutable datasets and user queries, top-k query processing has gained significant interest. This paper presents a novel method to find top-k answers in a node proximity search based on the well-known measure, Personalized PageRank (PPR). First, we introduce a distribution state transition graph (DSTG) to depict iterative steps for solving the PPR equation. Second, we propose a weight distribution model of a DSTG to capture the states of intermediate PPR scores and their distribution. Using a DSTG, we can selectively follow and compare multiple random paths with different lengths to find the most promising nodes. Moreover, we prove that the results of our method are equivalent to the PPR results. Comparative performance studies using two real datasets clearly show that our method is practical and accurate.

• Journal of Multimedia Information System
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• 제2권3호
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• pp.263-274
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• 2015

The subject of this work is the complex discrete systems simulation special features with the aid of dynamic graph models. The proposed simulation technique allows to determine the ways for tasks solutions in terms of discrete systems analysis and synthesis of various complication: one-dimensional and multidimensional, steady and unstable, with the pulse elements abnormal operating mode and others. Often complex control systems analysis and synthesis task solutions, via classical approach comes out to be insolvent, because of the computational problems. The application of graph models allows to perform clear and strict characterization and computer procedures automation. The optimal controls synthesis algorithm presented in this paper, transferring the discrete system from target initial state to target final state within the minimum time, allows to consider the zero initial conditions systems, with the initial potential energy, with the control actions limitations and complex pulse elements operating mode.

• Journal of Information Processing Systems
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• 제14권5호
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• pp.1254-1271
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• 2018

Keyphrase extraction is one of fundamental natural language processing (NLP) tools to improve many text-mining applications such as document summarization and clustering. In this paper, we propose to use two novel techniques on the top of the state-of-the-art keyphrase extraction methods. First is the anti-patterns that aim to recognize non-keyphrase candidates. The state-of-the-art methods often used the rich feature set to identify keyphrases while those rich feature set cover only some of all keyphrases because keyphrases share very few similar patterns and stylistic features while non-keyphrase candidates often share many similar patterns and stylistic features. Second one is to use the dependency graph instead of the word co-occurrence graph that could not connect two words that are syntactically related and placed far from each other in a sentence while the dependency graph can do so. In experiments, we have compared the performances with different settings of the graphs (co-occurrence and dependency), and with the existing method results. Finally, we discovered that the combination method of dependency graph and anti-patterns outperform the state-of-the-art performances.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2007년도 춘계학술발표대회
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• pp.213-217
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• 2007

소프트웨어 테스팅은 소프트웨어의 개발 과정에 있어서 가장 중요하고 많은 비용이 드는 부분이다. 소프트웨어 테스팅을 수동으로 행하는 것은 많은 문제를 발생시킬 수 있다. 소프트웨어 자동 테스팅을 하기 위해서 최근 활발히 연구되고 있는 부분이 모델 기반 소프트웨어 자동 테스팅 기법이다. 본 논문에서는 UML 모델 기반 테스트 케이스 자동 생성 기법을 제안한다. UML state chart 로 모델링 된 테스트 대상 소프트웨어를 제안된 자료구조에 저장 한 후, 이를 flow graph 로 변환한다. 최종적으로 변환된 flow graph 에서 테스트 케이스를 생성한다.

• 한국항행학회논문지
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• 제14권6호
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• pp.975-983
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• 2010

본 논문에서는 하노이의 탑 (Tower of Hanoi; ToH) 문제를 확장한 문제들을 소개하고, ToH 문제의 상태 공간을 그래프로 표현하기 위한 새로운 방안을 제시하고자 한다. 확장한 문제들로는 기둥의 수를 늘린 경우, 디스크 스택의 수를 늘린 경우, 그리고 일반 상태 간의 이동에 대한 세 가지를 소개하고, 다른 변종 문제들을 소개하고자 한다. 우리가 본 논문에서 제시한 새로운 표현 방안은 기존의 하노이 그래프 표현에 대해 확장된 방식의 그래프 표현을 제시하는 것이다. 제안된 표현에서는 각 디스크마다 하나의 직교좌표를 부여해 줌으로써 링크의 표시와 상태의 변화가 디스크가 어느 기둥에 배치되어 있는가와 시각적으로 일치된 시각화를 가능하게 해 준다. 제안된 표현을 기존의 하노이 그래프와 비교해 보면, 제안된 표현에서 디스크를 옮길 수 없는 링크를 제거하면 기존의 하노이 그래프와 isomorphic하다. 따라서, 제안된 표현은 기존의 하노이 그래프를 확장하여 표현력을 고도화한 것임을 알 수 있다. 제안된 표현에 대한 독자들의 이해를 돕기 위해, 우리는 본 논문에서 디스크의 개수가 2와 3인 경우에 대한 제안된 표현의 시각화 예를 제시하였다.

• 한국항해학회지
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• 제22권2호
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• pp.81-87
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• 1998

On this paper, the methods of optimization research of the fishing navigation using the graph theory are substantiated on the basis of the proposed probable model of the fishing vessel navigator's activity. The graph theory is concered about the transitionform the top graph to the rib one. And the definition of the additional system elements (quasi elements) necessary to provide the effectiveness during the fishing navigation are also substantiated herein. This approach helps to optimize the structure of any fishing vessel monitoring system.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.425-430
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• 2002

An automatic transmission model using the bond graph techniques is developed for analyzing shift characteristics of vehicles. Bond graph models can be systemically manipulated to yield state space equations of standard form. Bond graph techniques are applied for modeling overall automatic transmission systems and shift models. A fuzzy controller is synthesized for the verification of a shifting model in the ${1^st} gear to the {2^nd}$ gear. Simulation results show the fitness of models by the bond graph techniques.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.43-47
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• 1997

A procedure presented in this paper generates test sequences to check the conformity of an implementation with a protocol specification, which is modeled as a deterministic finite state machine (FSM). Given a FSM, a common procedure of test sequence generation, first, constructs a directed graph which edges include the state check after each transition, and produces a symmetric graph G* from and, finally, finds a Euler tour of G*. We propose a technique to determine a minimum-cost tour of the transition graph of the FSM. The proposed technique using Multiple Unique State Signature (MUSS) solves an open issue that one MUIO sequence assignment may lead to two more edges of unit cost being replicated to from G* while an optimal assignment may lead to the replication of a single edge of high cost. In this paper, randomly generated FSMs have been studied as test cases. The result shows that the proposed technique saves the cost 4∼28% and 2∼21% over the previous approach using MUIO and MUSP, respectively.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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• pp.450-456
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• 1990

In this paper, production system is implemented with the inferential neural network model using semantic network and directed graph. Production system can be implemented with the transform of knowledge representation in production system into semantic network and of semantic network into directed graph, because directed graphs can be expressed by neural matrices. A concept node should be defined by the state vector to calculated the concepts expressed by matrices. The expressional ability of neunal network depends on how the state vector is defined. In this study, state vector is overlapped and each overlapping part acts as a inheritant of concept.