• 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.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.407-410
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• 2013

Secret sharing is that a dealer distributes a piece of information (called a share) about a secret to each participant such that authorized subsets of participants can reconstruct the secret but unauthorized subsets of participants cannot determine the secret. In this paper, an access structure can be represented by a label graph G, where a vertex denotes a participant and a complete subgraph of G corresponds to a minimal authorized subset. The vertices of G are labeled into distinct vectors uniquely determined by the maximum prohibited structure. Based on such a label graph, a verifiable secret sharing scheme realizing general access structures is proposed. A major advantage of this scheme is that it applies to any access structure, rather than only structures representable as previous graphs, i.e., the access structures of rank two. Furthermore, verifiability of the proposed scheme can resist possible internal attack performed by malicious participants, who want to obtain additional shares or provide a fake share to other participants.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.218-223
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• 2012

Maintenance and improvement of the graph connectivity is very important for decentralized multi-agent systems. Although the CBBA (Consensus-Based Bundle Algorithm) guarantees suboptimal performance and bounded convergence time, it is only valid for connected graphs. In this study, we apply a decentralized estimation procedure that allows each agent to track the algebraic connectivity of a time-varying graph. Based on this estimation, we design a decentralized gradient controller to maintain the graph connectivity while agents are traveling to perform assigned tasks. Simulation result for fully-actuated first-order agents that move in a 2-D plane are presented.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.65-67
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• 2004

Change of state of Channel between two wireless terminals which is caused by noise and multiple environmental conditions for happens frequently from the Wireles Network. So, When it is like that planning a wireless network protocol or performance analysis, it follows to change of state of time-varying channel and packet the analysis against a transmission efficiency is necessary. In this paper, analyzes transmission time of a packet and a packet in a time-varying and packet based Wireless Network. To reflecte the feature of the time-varying channel, we use a Signal Flow Graph model. From the model the mean of transmission time and the mean of queue length of the packet are analyzed in terms of the packet distribution function, the packet transmission service time, and the PER of the time-varying channel.

• Convergence Security Journal
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• v.22 no.3
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• pp.87-99
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• 2022

Cyber attacks have become more difficult to detect and track as sophisticated and advanced APT attacks increase. System providence graphs provide analysts of cyber security with techniques to determine the origin of attacks. Various system provenance graph techniques have been studied to reveal the origin of penetration against cyber attacks. In this study, we investigated various system provenance graph techniques and described about data collection and analysis techniques. In addition, based on the results of our survey, we presented some future research directions.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.383-385
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• 2023

Single-machine-based 그래프 엔진의 state-of-the-art 모델인 RealGraph 는 쓰레드를 이용한 병렬화로 성능을 향상하였으나 쓰레드 내부에서의 병렬성은 고려되지 않았다. 본 논문은 SIMD 명령어를 이용해 RealGraph 의 병렬성을 향상시켰다. 쓰레드 내부의 효율성을 높이기 위해 RealGraph 의 구조와 그래프 알고리즘의 분석을 통한 SIMD 명령어의 적용 가능한 영역을 탐색하였다. 실험으로 SIMD 명령어의 적용을 통해 쓰레드 내부에서 벡터 연산을 수행하여 평균 7.6%, 11.7%, 9.2%의 수행 시간 단축을 이끌어냈으며 SIMD 명령어의 적용이 그래프 엔진의 분석 성능에 얼마나 도움이 될 수 있는지 확인하였다.

• Korean Journal of Construction Engineering and Management
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• v.16 no.5
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• pp.3-11
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• 2015

This paper aims to review and discuss a graph-based approach for the representation and analysis of building circulation using BIM models. To propose this approach, the authors survey diverse researches and developments which are related to building circulation issues such as circulation requirements in Korea Building Act, spatial network analysis, as well as BIM applications. As the basis of this paper, UCN (Universal Circulation Network) is the main reference of the research, and the major goal of this paper is to extend the coverage of UCN with additional features we examined in the survey. In this paper we restructured two major perspectives on top of UCN: 1) finding major factors of graph-based circulation analysis based on UCN and 2) restructuring the UCN approach and others for adjusting to Korean Building Act. As a result of the further studies in this paper, two major additions have demonstrated in the article: 1) the most remote point-based circulation representation, and 2) virtual space-based circulation analysis.

• Journal of KIISE
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• v.45 no.1
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• pp.15-21
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• 2018

Low-Rank Representation (LRR) based methods are widely used in many practical applications, such as face clustering and object detection, because they can guarantee high prediction accuracy when used to constructing graphs in graph - based semi-supervised learning. However, in order to solve the LRR problem, it is necessary to perform singular value decomposition on the square matrix of the number of data points for each iteration of the algorithm; hence the calculation is inefficient. To solve this problem, we propose an improved and faster LRR method based on the recently published Fast LRR (FaLRR) and suggests ways to introduce and optimize additional constraints on the underlying optimization goals in order to address the fact that the FaLRR is fast but actually poor in classification problems. Our experiments confirm that the proposed method finds a better solution than LRR does. We also propose Fast MLRR (FaMLRR), which shows better results when the goal of minimizing is added.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.67-80
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• 2021

The node embedding technique for learning graph representation plays an important role in obtaining good quality results in graph mining. Until now, representative node embedding techniques have been studied for homogeneous graphs, and thus it is difficult to learn knowledge graphs with unique meanings for each edge. To resolve this problem, the conventional Triple2Vec technique builds an embedding model by learning a triple graph having a node pair and an edge of the knowledge graph as one node. However, the Triple2 Vec embedding model has limitations in improving performance because it calculates the relationship between triple nodes as a simple measure. Therefore, this paper proposes a feature extraction technique based on a graph convolutional neural network to improve the Triple2Vec embedding model. The proposed method extracts the neighborliness vector of the triple graph and learns the relationship between neighboring nodes for each node in the triple graph. We proves that the embedding model applying the proposed method is superior to the existing Triple2Vec model through category classification experiments using DBLP, DBpedia, and IMDB datasets.

• Journal of The Korean Association For Science Education
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• v.39 no.5
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• pp.655-668
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• 2019

In this study, we investigated the middle school students' processes of scientific graph construction from the perspective of the problem solving process. Ten 9th graders participated in this study. They constructed a scientific graph based on pictorial data depicting precipitation reaction. The think-aloud method was used in order to investigate their thinking processes deeply. Their activities were videotaped, and semi-structured interviews were also conducted. The analysis of the results revealed that their processes of scientific graph construction could be classified into four types according to the problem solving strategy and the level of representations utilized. Students using the structural strategy succeeded in constructing scientific graph regardless of the level of representation utilized, by analyzing the data and identifying the trend based on the propositional knowledge about the target concept of the graph. Students of random strategy-higher order representation type were able to succeed in constructing scientific graph by systematically analyzing the characteristics of the data using various representations, and considering the meaning of the graph constructed in terms of the scientific context. On the other hand, students of random strategy-lower order representation type failed to construct correct scientific graph by constructing graph in a way of simply connecting points, and checking the processes of graph construction only without considering the scientific context. On the bases of the results, effective methods for improving students' ability to construct scientific graphs are discussed.