• Journal of the Korea Society of Computer and Information
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• 제4권3호
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• pp.13-19
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• 1999

In this paper, we suggests a WIP (Work In Process) of FMC (Flexible Manufacturing Cell) analysis methods based on the TPN (Time Petri Nets) unfolding. Unfolding of PN is a partial order-based method for the verification of concurrent system without the state space explosion. The aim of this work is to formulate the general cyclic state scheduling problem to minimize the WIP to satisfy economical constraints. The method is based on unfolding of the original net into the equivalent acyclic description.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 한국방송∙미디어공학회 2021년도 추계학술대회
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• pp.132-133
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• 2021

XR(가상 및 확장현실)에서의 리얼타임 그래픽은 조명이 제 역할을 하지 못하면 인물이 공간감이 느껴지지 않거나 스킨톤이 맞지 않아 이질감을 초래한다. 본 논문에서는 Art-Net 시스템을 활용하여 실제 조명과 가상조명에서의 배경 및 인물의 컬러를 동기화하는 방법을 제안하였다. 제안된 Art-Net 시스템을 통해 인물의 공간감을 향상 시킬 수 있을 뿐만 아니라 보는 이의 몰입감을 높였다.

• Journal of Korean Tunnelling and Underground Space Association
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• 제6권4호
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• pp.357-365
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• 2004

Tunnel portals are often located in areas where the risk of rock fall and/or detachement of rock fragments from rocky slopes is high. In this case it is necessary to design the portals so as to protect the road (i.e. using an artificial tunnel) or to instal structures that are able to intercept falling blocks on the slope. This paper deals with the design problems of these structures and includes a special analysis of net fences which have undergone a remarkable technological improvement over recent years.

• Journal of Astronomy and Space Sciences
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• 제13권2호
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• pp.134-148
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• 1996

In this paper, in order to verify KITSAT 1/2 packet communication protocols, we model the AX.25 protocol and PACSAT protocol by using an extended Petri net and then verify the correctness, boundedness, liveness and deadlock freeness of packet protocols by utilizing reachability trees.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.483-497
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• 2023

Depth estimation is one of the most complicated and difficult problems to deal with in the light field. In this paper, a compound attention convolutional neural network (CAttNet) is proposed to extract depth maps from light field images. To make more effective use of the sub-aperture images (SAIs) of light field and reduce the redundancy in SAIs, we use a compound attention mechanism to weigh the channel and space of the feature map after extracting the primary features, so it can more efficiently select the required view and the important area within the view. We modified various layers of feature extraction to make it more efficient and useful to extract features without adding parameters. By exploring the characteristics of light field, we increased the network depth and optimized the network structure to reduce the adverse impact of this change. CAttNet can efficiently utilize different SAIs correlations and features to generate a high-quality light field depth map. The experimental results show that CAttNet has advantages in both accuracy and time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권1호
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• pp.64-88
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• 2024

Security and reliability are the utmost importance facts in intelligent networked vehicles. Stochastic Petri Net and Z (SPZN) as an excellent formal verification tool for modeling concurrent systems, can effectively handles concurrent operations within a system, establishes relationships among components, and conducts verification and reasoning to ensure the system's safety and reliability in practical applications. However, the application of a system with numerous nodes to Petri Net often leads to the issue of state explosion. To tackle these challenges, a refinement and abstraction method based on SPZN is proposed in this paper. This approach can not only refine and abstract the Stochastic Petri Net but also establish a corresponding relationship with the Z language. In determining the implementation rate of transitions in Stochastic Petri Net, we employ the interval average and weighted average method, which significantly reduces the time and space complexity compared to alternative techniques and is suitable for expert systems at various levels. This reduction facilitates subsequent comprehensive system analysis and module analysis. Furthermore, by analyzing the properties of Markov Chain isomorphism in the case study, recommendations for minimizing system risks in the application of intelligent parking within the intelligent networked vehicle system can be put forward.

• Journal of the Korean Association of Geographic Information Studies
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• 제25권4호
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• pp.63-80
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• 2022

As a technology to analyze and predict an issue has been developed by constructing real space into virtual space, it is becoming more important to acquire precise spatial information in complex cities. In this study, images were acquired using an unmanned aerial vehicle for urban area with complex landscapes, and land cover classification was performed object-based image analysis and semantic segmentation techniques, which were image classification technique suitable for high-resolution imagery. In addition, based on the imagery collected at the same time, the replicability of land cover classification of each artificial intelligence (AI) model was examined for areas that AI model did not learn. When the AI models are trained on the training site, the land cover classification accuracy is analyzed to be 89.3% for OBIA-RF, 85.0% for OBIA-DNN, and 95.3% for U-Net. When the AI models are applied to the replicability assessment site to evaluate replicability, the accuracy of OBIA-RF decreased by 7%, OBIA-DNN by 2.1% and U-Net by 2.3%. It is found that U-Net, which considers both morphological and spectroscopic characteristics, performs well in land cover classification accuracy and replicability evaluation. As precise spatial information becomes important, the results of this study are expected to contribute to urban environment research as a basic data generation method.

• Journal of KIISE
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• 제43권9호
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• pp.1034-1042
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• 2016

Together with machine-learning frameworks, area-based imagery registration techniques can be easily applied to diverse types of image pairs without predefined features and feature descriptors. However, feature detectors are often used to quickly identify candidate image patch pairs, limiting the applicability of these registration techniques. In this paper, we propose a ConvNet (Convolutional Network) "Dart" that provides not only the matching metric between patches, but also information about their distance, which are helpful in reducing the search space of the corresponding patch pairs. In addition, we propose a ConvNet "Fad" to identify the patches that are difficult for Dart to improve the accuracy of registration. These two networks were successfully implemented using Deep Learning with the help of a number of training instances generated from a few registered image pairs, and were successfully applied to solve a simple image registration problem, suggesting that this line of research is promising.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제8권6호
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• pp.1480-1490
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• 2007

This study implemented a remote control system using PDA based on WINDOWS CE. NET. In existing remote control systems, the user generally controls remote objects and obtain data using a computer, which is a local system connected to the internet, and the remote objects are connected to server computers. In order to control remote objects, the user has to have a computer, a space to use the Internet, and wired internet. The system proposed in this study uses an embedded board as a server and PDA as a client. Thus, the user can control remote objects at any place as long as wireless internet is available. In addition, because an embedded board is used as a server, the system has the characteristics of high performance and low power consumption. The proposed system provides not only remote control environment using PDA but also conventional control environment using a computer as a client. In case PDA is not available, remote objects still can be controlled from any place as long as there are wired internet and a computer.

• The Journal of the Convergence on Culture Technology
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• 제8권5호
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• pp.155-160
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• 2022

This paper intends to focus on the practical activities and historical significance of network art, that is, 'net art' as an artistic form that depends on network technology. This is because the appearance of net art, which constructs a new interactive art that cooperates and exchanges with each other beyond the boundaries of time and space, can be a contemporary alternative in overcoming the limitations of traditional art. Another important research area to be considered in this paper is net art curating, as well as considering the significance of net art in art history. As new media art that is defined as a 'process' rather than a complete object, net art is a digital art that requires functions such as aesthetic appropriation, dissemination, and mediation performed online, unlike physical presentations with high perfection in exhibition halls. It is accompanied by a new social and cultural curatorial. This appearance requires both artists and curators to reorganize the strategy that net art curating in technoculture should have. Therefore, this paper attempts to question the creative strategies of net art in the wave of globalization in the 21st century, and to examine the artistic meaning and critical value of the experimental net art curatorial method that emerged through the realm of new technology and media. For this purpose, this paper demonstrated key examples of net art works and exhibition projects that started with Fluxus in the 1960s and are spreading all over the world in the 2000s.