• Journal of the Korea Society for Simulation
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• v.12 no.2
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• pp.25-34
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• 2003

Because of explosive growth in demand for web-based multimedia applications, proper proxy caching for large multimedia object (especially video) has become needed. For a video object which is much larger in size and has different access characteristics than the traditional web object such as image and text, caching the whole video file as a single web object is not efficient for the proxy cache. In this paper, we propose a proxy caching strategy with the constant-sized segment for video file and an improved proxy cache replacement policy. Through the event-driven simulation under various conditions, we show that our proposal is more efficient than the variable-sized segment strategy which has been proven to have higher hit ratio than other traditional proxy cache strategies.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.307-312
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• 2001

In this paper, we proposed the object-tracking algorithm that recognizes and estimates the any shaped and size objects using vision system. For the extraction of the object from the background of the acquired images, spatio-temporal filter and signature parsing algorithm are used. Specially, for the solution of correspondence problem of the multiple objects tracking, we compute snake energy and position information of the target objects. Through the real-time tracking experiment, we verified the effectiveness of the suggested tracking algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.536-546
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• 2003

We propose an object extraction technique adequate for the radial shape's radar signal structure for the purpose of implementing ARPA(Automatic Radar Plotting Aid) installed in the vessel. The radar signal data are processed by interpolation and accumulation to acquire a qualified image. The objects of the radar image have characteristics of having different shape and size as it gets far from the center, and it is not adequate for clustering generally. Therefore, this study designs a new vigilance distance model of elliptical shape and adopts this model in the ART2 neural network. We prove that the proposed clustering method makes it possible to extract objects adaptively and to separate the connected objects effectively.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.106-111
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• 2005

LCC(Launch Control Center) in NARO Space Center perform a data monitoring and control through the interface to the external system of launch vehicle. Launch Control function needs a high reliability and processing speed. Hence, LCC's remote control system configure a real time system. An important role of the Simulation system is discovering a risk element and minimize it When developing a launch control system. Also, secure a development technique to solve the risks. Launch Vehicle simulator is composed of various component at characteristic of the Launch Vehicle. To be like this each function component the developer will be able to develop easily in order, it using the LabVIEW which is a Graphical Program and it programs, The LabVIEW GOOP(Graphical Object-orinted Programming) which supports an Object-orinted programming it uses with the Component it develops will have a strong point which reusability and a unit test, maintenance, size of program and individual developments.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2008.05a
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• pp.46-49
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• 2008

This research does Complexity form, Interior epidermis cell re-organization, Object discovery that have correct numerical value concept by purpose. Research applied by Grid re-organization in form generation, Parameter variation of cell unit (morphor, tweener), Symbol, pattern of variation, self-organization cell substitution order. Representation through 3d digital modeler of polygon, Nurbs and street-sheet program(x,y,z coordinates & Network way of points) etc. of main work. Investigator specified numbers of U profiles*30, V point-20 that is 600 Paramaters individual in volume, and define circle radius of lighting in object, Projection size variously and tried difference. Transposition cell to point and Heightened brightness of color using pointillism of painting. Led lighting cell object is expressed being decoded by digital code.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.524-534
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• 2022

In this paper, we produce Trash Object Detection (TOD) dataset to solve trash detection problems. A well-organized dataset of sufficient size is essential to train object detection models and apply them to specific tasks. However, existing trash datasets have only a few hundred images, which are not sufficient to train deep neural networks. Most datasets are classification datasets that simply classify categories without location information. In addition, existing datasets differ from the actual guidelines for separating and discharging recyclables because the category definition is primarily the shape of the object. To address these issues, we build and experiment with trash datasets larger than conventional trash datasets and have more than twice the resolution. It was intended for general household goods. And annotated based on guidelines for separating and discharging recyclables from the Ministry of Environment. Our dataset has 10 categories, and around 33K objects were annotated for around 5K images with 1280×720 resolution. The dataset, as well as the pre-trained models, have been released at https://github.com/jms0923/tod.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.226-231
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• 2007

This paper presents a method of colored object extraction from an image using the fuzzy neural network. Fuzzy neural network divides an image into two clusters. It extracts the prototypes of Cb and Cr of object and background by controlling the vigilance parameter. The proposed method extracted object regardless of the position, the size, and the intensity of object. We compared the performance of the proposed method with that of the method of using subjective threshold value. And, we compared the performance of the proposed method with that of the method of using subjective threshold value by using several images with added noises.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1271-1281
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• 2017

It is essential to collect and analyze target information around the vehicle for autonomous driving of the vehicle. Based on the analysis, environmental information such as location and direction should be analyzed in real time to control the vehicle. In particular, obstruction or cutting of objects in the image must be handled to provide accurate information about the vehicle environment and to facilitate safe operation. In this paper, we propose a method to simultaneously generate 2D and 3D bounding box proposals using LiDAR Edge generated by filtering LiDAR sensor information. We classify the classes of each proposal by connecting them with Region-based Fully-Covolutional Networks (R-FCN), which is an object classifier based on Deep Learning, which uses two-dimensional images as inputs. Each 3D box is rearranged by using the class label and the subcategory information of each class to finally complete the 3D bounding box corresponding to the object. Because 3D bounding boxes are created in 3D space, object information such as space coordinates and object size can be obtained at once, and 2D bounding boxes associated with 3D boxes do not have problems such as occlusion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.325-327
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• 2007

We report a simple area measurement device for 3 dimensional object using 3 degree of freedom sensor. The surface of 3D object can be divided into a number of triangles, and the surface area of 3D object could be measured by the sum of the divided triangle area. We applied 6DOF sensor to measure the coordinate of triangle vertex, and calculated each triangle area on the surface of 3D object. The many we divide the area to triangles, the correct we will get the result. This method shows 7.78% in error on the measurement of 3 dimensional object area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5888-5903
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• 2019

The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.