• International conference on construction engineering and project management
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• 2022.06a
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.33-39
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• 2024

In a previous study we proceeded to the remodularization architecture based on classes and packages using the Formal Concept Analysis (FCA)[13] [14] [30]. we then got two possible remodularized architectures and we explored the issue of redistributing classes of a package to other packages, we used an approach based on Oriented Graph to determine the packages that receive the redistributed classes and we evaluated the quality of a remodularized software architecture by metrics [31] [28] [29]. In this paper, we will address the issue of the efficiency of the Oriented Graph in the remodularization of software architectures compared to the Formal Concept Analysis FCA method. The formal method of FCA concept is not popularized among scientists as opposed to the use of the labeled directed graph. It is for this reason that our directed graph approach is more effective in its simplicity and popularity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2101-2123
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• 2023

Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.

• Korean Institute of Interior Design Journal
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• v.18 no.4
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• pp.97-104
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• 2009

This thesis analyzed arrangement and mixture method of function elements, which are getting more important in museum planning. It used quantitative method, Space Syntax and Visibility Graph Analysis tool to analyze five case museums. Through this analysis, advantages and disadvantages of two methods were derived and case museums' arrangement and mixture attributes were grasped. Results of the analysis were derived differently by two kinds of plan form which were room to room type and open type. Open typed museum recorded similar graphs of Integration, Visual Integration and Visual Connectivity. Since whole space structures were relatively simple and structure of exhibition halls were opened, the results of Space Syntax and Visibility Graph Analysis had similar graphs. Room to room typed museum showed differences in Integration, Visual Integration and Visual Connectivity. In the result, the most accessible space was lobby and Mediation Space became the center of visibility. Also, the exhibition hall, where the opening of room to room typed exhibition hall was penetrated visually, became a center of visibility. Lobby space, which was close to entrance, had the highest Visibility Connectivity. As Space Syntax could analyze the museum as whole space structure, Space Syntax showed strength in room to room typed museum analysis compared to open typed museum analysis which has relatively simple structure. Visibility Graph Analysis could expect the flow of exhibit distance including visibility analysis unlike the flow of exhibit distance with space arrangement. The exhibition hall, which secures the sight to penetration of an opening, couldn't be analyzed in existing Space Syntax. However, it became the biggest advantages in Visibility Graph Analysis of room to room typed museum. Visibility Graph Analysis derived detailed results in exhibit arrangement so it will be the useful method not only for architecture but also for planning of exhibit arrangement in open typed museum. Through this study, various possibilities on Quantitative Analysis Method of Museum Architecture could be verified. However, the analysis still has limitation of second dimension. Therefore, diverse and liberal following study will be expected to accomplish.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.06a
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• pp.73-78
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• 2003

This paper proposes the simulator synthesis scheme which is based on the exploration of the total design space in attributed AND-OR graph. Attributed AND-OR graph is a systematic design space representation formalism which enables to represent all the design space by decomposition rule and specialization rule. In addition, attributes attached to the design entity provides flexible modeling. Based on this design space representation scheme, a pruning algorithm which can transform the total design space into sub-design space that satisfies the user requirements is given. We have shown the effectiveness of our framework by (ⅰ) constructing the design space of superscalar processor in attributed AND-OR graph (ⅱ) pruning it to obtain the ARM9 processor architecture. (ⅲ) modeling the components of the architecture and (ⅳ) simulating the ARM9 model.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.389-391
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• 2000

A representation technique of a given track topology is required by many software applications in railway technology such as signalling system simulator. To achieve these, the concept of double vertex graph architecture is proposed. These are composed of pairs of vertices and node between the single vertices. Double vertex graph architecture can be understood as a extension of classical graphs. In developed railway signalling simulation software, it is shown that track topology can be represented by proposed algorithm in a efficient way. Especially it makes sure that these are suitable technique for representing and implementing of switch, routes which can be introduced some mistake in classical graph algorithm.

• Journal of KIISE:Software and Applications
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• v.32 no.1
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• pp.10-21
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• 2005

Software architecture is increasingly being viewed as a key design in developing complex software systems, which largely affects the achievement of quality attributes. During the architecture-based software development, therefore, architectural transformation is needed to achieve quality attributes. Due to the variety of design alternatives and the poor predictability of the effects of the transformation, however, it is not easy to apply architectural transformation. Therefore, the method is needed to support architectural transformation through systematically analyzing the effects of applying various design alternatives to the architecture. This paper proposes an approach to support software architecture transformation. Based on architectural design decisions and the constraints on them included in the architecture, our approach defines a decision constraint graph representing the dependencies among architectural design decisions. Through using the decision constraint graph, architectural transformation can be systematically performed by understanding the effects of applying a transformation. While this work supports more understanding of applying architectural transformation, it also helps reconstruct a software architecture to improve the quality of the software.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.649-654
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• 2023

This paper proposes the design of a neural network structure search model using graph convolutional neural networks. Deep learning has a problem of not being able to verify whether the designed model has a structure with optimized performance due to the nature of learning as a black box. The neural network structure search model is composed of a recurrent neural network that creates a model and a convolutional neural network that is the generated network. Conventional neural network structure search models use recurrent neural networks, but in this paper, we propose GC-NAS, which uses graph convolutional neural networks instead of recurrent neural networks to create convolutional neural network models. The proposed GC-NAS uses the Layer Extraction Block to explore depth, and the Hyper Parameter Prediction Block to explore spatial and temporal information (hyper parameters) based on depth information in parallel. Therefore, since the depth information is reflected, the search area is wider, and the purpose of the search area of the model is clear by conducting a parallel search with depth information, so it is judged to be superior in theoretical structure compared to GC-NAS. GC-NAS is expected to solve the problem of the high-dimensional time axis and the range of spatial search of recurrent neural networks in the existing neural network structure search model through the graph convolutional neural network block and graph generation algorithm. In addition, we hope that the GC-NAS proposed in this paper will serve as an opportunity for active research on the application of graph convolutional neural networks to neural network structure search.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3236-3238
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• 1999

This paper proposes a new face recognition technique in the dynamic link architecture which shows robustness against size variation and distortion. The face recognition technique in the dynamic link architecture so far was not appropriate for the recognition of various size of faces because of the fixed size of the graph and the fixed value of a of the Gabor filter not considering the size of the face. The proposed face recognition algorithm can represent the input facial image by a suitable size of labeled graph, and it can also adjust the dilation width and the height of the vibrating amplitude of the Gabor filter, thus face recognition in the dynamic link architecture is even applicable regardless of the size of the face.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.709-714
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• 2023

A flexible planning system is an important element for the robot to perform various tasks. In this paper, we introduce an automated planning system architecture that can deal with the changing environment. PDDL is used for symbolic-based task planning, and a graph database is used for real-time environment information updates for automated PDDL generation. The proposed framework was verified through scenario-based experiments.