• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.471-476
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• 2024

With the spread of various smart devices and computing devices, big data generation is occurring widely. Machine learning is an algorithm that performs reasoning by learning data patterns. Among the various machine learning algorithms, the algorithm that attracts attention is deep learning based on neural networks. Deep learning is achieving rapid performance improvement with the release of various applications. Recently, among deep learning algorithms, attempts to analyze data using graph structures are increasing. In this study, we present a graph generation method for transferring to a deep learning network. This paper proposes a method of generalizing node properties and edge weights in the graph generation process and converting them into a structure for deep learning input by presenting a matricization We present a method of applying a linear transformation matrix that can preserve attribute and weight information in the graph generation process. Finally, we present a deep learning input structure of a general graph and present an approach for performance analysis.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1250-1260
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• 2020

This study proposes a novel deep neural network model that can accurately detect objects and their relationships in an image and represent them as a scene graph. The proposed model utilizes several multimodal features, including linguistic features and visual context features, to accurately detect objects and relationships. In addition, in the proposed model, context features are embedded using graph neural networks to depict the dependencies between two related objects in the context feature vector. This study demonstrates the effectiveness of the proposed model through comparative experiments using the Visual Genome benchmark dataset.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.633-652
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• 2024

Software testing is an important phase as it ensures the software quality. The software testing process comprises of three steps: generation, execution, and evaluation of test cases. Literature claims the usage of single and multiple 'Unified Modeling Language' (UML) diagrams to generate test cases. Using multiple UML diagrams increases test case coverage. However, the existing approaches show limitations in test case generation from UML diagrams. Therefore, in this research study, we propose an approach to generate the test cases using UML State Chart Diagram (SCD), Activity Diagram (AD), and Sequence Diagram (SD). The proposed approach transforms UML diagrams into intermediate forms: SCD Graph, AD Graph, and SD Graph respectively. Furthermore, by integrating these three graphs, a System Testing Graph (STG) is formed. Finally, test cases are identified from STG by using a traversal algorithm such as Depth First Search (DFS) that is an optimization method. The results show that the proposed approach is better compared to existing approaches in terms of coverage and performance. Moreover, the generated test cases have the ability to detect faults at the unit level, integration, and system level testing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2476-2495
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• 2021

Model-based software architecture verification and test scenarios generation are becoming more and more important in the software industry. Based on the existing temporal graph grammar, this paper proposes a new formalization method of the context-sensitive graph grammar for aiming at UML activity diagrams, which is called the UML Activity Graph Grammar, or UAGG. In the UAGG, there are new definitions and parsing algorithms. The proposed mechanisms are able to not only check the structural correctness of the UML activity diagram but also automatically generate the test scenario according to user constraints. Finally, a case study is discussed to illustrate how the UAGG and its algorithms work.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.524-529
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• 2002

In this paper, we report the development of two DEM (digital elevation model) generation algorithms over urban areas from an IKONOS stereo pair. One ("EpiMatch") is originally developed for SPOT images and modified for IKONOS images. It uses epipolar geometry for accurate DEM generation. The other is based on graph-cut algorithm in 3D voxel space. This algorithm is believed to work better on height discontinuities than EpiMatch. An IKONOS image pair over Taejon city area was used for tests. Using ground control points obtained from differential GPS, camera model was set up and stereo matching applied. As a result, two DEMs over urban areas were produced. Within a DEM from EpiMatch small houses appear as small "cloudy" patches and large apartment and industrial buildings are visually identifiable. Within the DEM from graph-cut we could achieve better height information on building boundaries. The results show that both algorithms can generate DEMs from IKONOS images although more research is required on handling height discontinuities (for "EpiMatch") and on faster computation (for "Graph-cut").

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.114-124
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• 2004

In this paper, we present an automatic C source code generation system for DirectShow based multimedia application programming. In this system, C source code is automatically synthesized from the filter connection graph edited with GraphEdit, a utility tool provided with DirectShow SDK package from Microsoft. In traditional DirectShow programming environments, program design and brief testing steps are usually done with GraphEdit tool just by inserting filters and connecting them properly, while actual implementation of the program should be done separately. The filter connection graph information from GraphEdit is used just as a reference in such the implementation step. Therefore, our system which automatically generates C source code directly from the filter connection graph of GraphEdit seems very useful and many programmers can develop DirectShow based multimedia application programs more effectively and quickly using our system. In addition, our system supports more various media stream control functions for the generated application programs than the existing system such as Wizard which supports limited and fixed number of media control functions only. This feature allows more flexibility in the user interface of the generated source program and makes our system more practical for DirectShow based programming.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• International Journal of Aeronautical and Space Sciences
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• v.8 no.2
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• pp.107-120
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• 2007

Coordination of multiple UAVs is an essential technology for various applications in robotics, automation, and artificial intelligence. In general, it includes 1) waypoints assignment and 2) trajectory generation. In this paper, we propose a new method for this problem. First, we modify the concept of the standard visibility graph to greatly improve the optimality of the generated trajectories and reduce the computational complexity. Second, we propose an efficient stochastic approach using simulated annealing that assigns waypoints to each UAV from the constructed visibility graph. Third, we describe a method to detect collision between two UAVs. FinallY, we suggest an efficient method of controlling the velocity of UAVs using A* algorithm in order to avoid inter-UAV collision. We present simulation results from various environments that verify the effectiveness of our approach.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1188-1195
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• 2014

This paper presents an analytical technique for reliability evaluation of electrical distribution network (EDN) containing distributed generation (DG). Based on hierarchical levels of circuit breaker controlling zones and feeder sections, a directed-relation-graph (DRG) for an END is formed to describe the hierarchical structure of the EDN. The reliability indices of EDN and load points can be evaluated directly using the formed DRG, and the reliability evaluation of an EDN containing DGs can also be done without re-forming the DRG. The proposed technique incorporates multi-state models of photovoltaic and diesel generations, as well as weather factors. The IEEE-RBTS Bus 6 EDN is used to validate the proposed technique; and a practical campus EDN containing DG was also analyzed using the proposed technique.

• 한국정보교육학회:학술대회논문집
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• 2010.08a
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• pp.227-233
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• 2010

Graph is applied to GIS, Network, AI and so on. We use graph concept in our daily life unconsciously. So this paper describe how graph concept is used when robot searches shortest path between two distinct vertices. It is performed in real world. For this, it consists of three step; maze traverse, graph generation, and shortest path search. Maze traverse steps is that robot navigates maze. It is most difficult step. Graph generation step is to represent structural information into graph. Shortest path search step is to that robot move between two vertices. It is not implemented yet. So we introduce process in design level.