• Journal of the Korean Society of Costume
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• v.38
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• pp.17-29
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• 1998

The purpose of this paper is to explore a new methodology for the historiography of Korean cos-tumes. In particular, I focus on the possibility for systematic, historical methods appropriate for the history of Korean costumes. First, I characterize the general historiography of costumes as involving two aspects-one as the social science and the other as historical science(Geschichteswissenschaft). My contention is that any historical study of costume should be established on the intersection of social and historical studies, and their entangling relations with many a neighboring field of sciences. It requires in other words, an interdisciplinary approach that combines various methodologies of social sciences as well as those of history. Second, I present an overall review of the historical methodology with a special emphasis on the“Quellenkunde”of orthodox historiography. Building on the review, third, I pay attention to recent innovations in historical methodologies, such as“New History”that draws on history, sociology and social history, and their applicability to the history of Korean costmes. In this regards. I adress among others, the following theoretical perspectives : 1) comparioson and comparative history, 2) the formatived and paternal approaches toward the history of costume, 3) particulartiy and universality of Korean costume. I conclued that the history of Korean costumes should broaden its theoretical horizon in order to accomodate a wider range of research agenda, including costumes of neighboring cultures, while remaining sensitive to new theories and methods of the neighboring social historical sciences. For this purpose, it is emphasized that an international collaboration among researchers of the region, as well as that across the different disciplinnary boundaries, is indispensable for successful studies that can embrace diverse fields and areas.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.179-189
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• 2009

We present a novel shadow culling algorithm for interactive ray tracing. Our approach exploits frame-to-frame coherence instead of preprocessing of building shadow data, so this algorithm is suitable for dynamic ray raying. In this algorithm, shadow processing results are stored to each primitive and used in the next frames. We also present a novel occlusion testing method. This method corrects potential shadow errors in our culling algorithm and requires low overhead. Experiment results show that our algorithm reduced both the traversal cost by 7-19 percent and the intersection cost by 9-24 percent.

• Proceedings of the KOR-KST Conference
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• 1998.10a
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• pp.236-244
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• 1998

When the capacity and traffic operation at signalized intersections are analyzed in Korea, the unprotected left-turn saturation flow rate, which is an important parameter for the analysis, is estimated form the USHCM model. thus, exact analysis of the left-turn is not possible because of the difference of traffic environments between two contries. In order to improve this problem, it is undertaken in this study to develop techniques for the estimation of unprotected left-turn saturation flows based on Korean drivers' data. As study intersections, signalized or unsignalized intersections on the 6, 4 and 2 lane streets are selected. the data for the saturation flow measurement and gap-acceptance behavior analysis are inputed in a notebook computer on the sites. The critical acceptance gaps of the 6, 4, and 2 lane streets are analyzed to be 6.0 secs, 4.6 secs, and 4.3 secs respectively. the average minimum headway of the left-turn vehicle was observed to be 2.6 secs. As the model to estimate unportected left-turn saturation flows, the drew model is recommended for 6 and 4 lane streets, and a graph is suggested for the 2-lane street. As the values of the parameters of the Drew model, the 2.6 secs of this study is recommended for the average minimum headway of the left-turn. But, the critical acceptance gap varies according to the approach speed of opposing traffic and driver population, it requires field survey to measure the gap of an intersection; however, the values of the gaps studied in this study may be used for the general intersections in urban area in Korean.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2144-2165
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• 2016

In a vehicular ad hoc network, the communication links are unsteady due to the rapidly changing topology, high mobility and traffic density in the urban environment. Most of the existing geographical routing protocols rely on the continuous transmission of beacon messages to update the neighbors' presence, leading to network congestion. Source-based approaches have been proven to be inefficient in the inherently unstable network. To this end, we propose an opportunistic beaconless packet forwarding approach based on a modified handshake mechanism for the urban vehicular environment. The protocol acts differently between intersections and at the intersection to find the next forwarder node toward the destination. The modified handshake mechanism contains link quality, forward progress and directional greedy metrics to determine the best relay node in the network. After designing the protocol, we compared its performance with existing routing protocols. The simulation results show the superior performance of the proposed protocol in terms of packet delay and data delivery ratio in realistic wireless channel conditions.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.117-124
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• 2008

We suggest CBIR(Content Based Image Retrieval) method using color and shape information. Using just one feature information may cause inaccuracy compared with using more than two feature information. Therefore many image retrieval system use many feature informations like color, shape and other features. We use two feature, HSI color information especially Hue value and CSS(Curvature Scale Space) as shape information. We search candidate image form DB which include feature information of many images. When we use two features, we could approach better result.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.234-241
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• 2007

Effective tools which can alleviate the complexity and computational load problem in collision-free motion planning for multi-agent system have steadily been demanded in robotics field. To reduce the complexity, the extended collision map (ECM) which adopts decoupled approach and prioritization is already proposed. In ECM, the collision regions which represent the potential collision of robots are calculated using the computational power; the complexity problem is not resolved completely. In this paper, we propose a mathematical analysis of the extended collision map; as a result, we formulate the collision region as an equation with 5-8 variables. For mathematical analysis, we introduce realistic assumptions as follows; the path of each robot can be approximated to a straight line or an arc and every robot moves with uniform velocity or constant acceleration near the intersection between paths. Our result reduces the computational complexity in comparison with the previous result without losing optimality, because we use simple but exact equations of the collision regions. This result can be widely applicable to coordinated multi-agent motion planning.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.277-285
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• 2010

This paper describes an approach to analyze geometrical information of building images for understanding outdoor environment of autonomous navigation robot. Line segments and color information are used to classily a building with the other objects such as sky, trees, and roads. The line segments and their two neighboring regions are extracted from detected edges in image. The model of line segment (MLS) consists of color information of neighbor regions. This model rules out the line segments of non-building face. A building face converges into dominant vanishing points (DVPs) which include one vertical point and one of five horizontal points in maximum. The intersection of vertical and horizontal lines creates a facet of building. The geometrical characteristics such as the center coordinates, area, aspect ratio and aligned coexistence are used for extracting the windows in the building facet. In experiments, 150 building faces and 1607 windows were detected from the database of outdoor environment. We found that this result shows 94.46% detection rate. These experimental images were all taken in Ulsan metropolitan city in Korea under difference of viewpoints, daytime, camera system and weather condition.

• Journal of Korea Multimedia Society
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• v.17 no.10
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• pp.1220-1228
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• 2014

Emergency Warning Service will be the most important service of VANET. Transmission delay is the most important performance criteria of the warning service. Most legacy research takes a way to minimize the packet collision. However those approach has a critical weak point on urban environment where there is a blind area of electric wave. So another issue is required in order to provide enhanced warning message propagation technique to overcome the urban environment problem. In this paper, I proposed an enhanced warning message propagation scheme in the poor electric wave environment as the intersection area. Proposed scheme forwards the warning message to the blind area by enhanced forwarding node selection technique. For efficiency of warning message propagation, I suggest forwarding priority for decision of forwarding node. And the node has a direct mode or redirect mode depending on neighbor nodes. The simulation was carried out to evaluate the performance. The simulation results show that proposed scheme has the superior performance compared to legacy warning message technique.

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.601-607
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• 2022

In recent years, monitoring of spent nuclear fuel inside dry cask storage has become an important area of national security. Muon tomography is a useful method for monitoring spent nuclear fuel because it uses high energy muons that penetrate deep into the target material and provides a 3-D structure of the inner materials. We designed a muon tomography system consisting of four 2-D position sensitive detector and characterized and optimized the system parameters. Each detector, measuring 200 × 200 cm², consists of a plastic scintillator, wavelength shifting (WLS) fibers and, SiPMs. The reconstructed image is obtained by extracting the intersection of the incoming and outgoing muon tracks using a Point-of-Closest-Approach (PoCA) algorithm. The Geant4 simulation was used to evaluate the performance of the muon tomography system and to optimize the design parameters including the pixel size of the muon detector, the field of view (FOV), and the distance between detectors. Based on the optimized design parameters, the spent fuel assemblies were modeled and the line profile was analyzed to conduct a feasibility study. Line profile analysis confirmed that muon tomography system can monitor nuclear spent fuel in dry storage container.

• Smart Structures and Systems
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• v.29 no.1
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• pp.207-220
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• 2022

Structural health monitoring (SHM) plays a vital role in the maintenance and operation of constructions. In recent years, autonomous inspection has received considerable attention because conventional monitoring methods are inefficient and expensive to some extent. To develop autonomous inspection, a potential approach of crack identification is needed to locate defects. Therefore, this study exploits two deep learning-based segmentation models, DeepLabv3+ and Mask R-CNN, for crack segmentation because these two segmentation models can outperform other similar models on public datasets. Additionally, impacts of label quality on model performance are explored to obtain an empirical guideline on the preparation of image datasets. The influence of image cropping and label refining are also investigated, and different strategies are applied to the dataset, resulting in six alternated datasets. By conducting experiments with these datasets, the highest mean Intersection-over-Union (mIoU), 75%, is achieved by Mask R-CNN. The rise in the percentage of annotations by image cropping improves model performance while the label refining has opposite effects on the two models. As the label refining results in fewer error annotations of cracks, this modification enhances the performance of DeepLabv3+. Instead, the performance of Mask R-CNN decreases because fragmented annotations may mistake an instance as multiple instances. To sum up, both DeepLabv3+ and Mask R-CNN are capable of crack identification, and an empirical guideline on the data preparation is presented to strengthen identification successfulness via image cropping and label refining.