• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1066-1077
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• 2004

Dramatic increase in the number of Internet users want highly qualified service of continuous media contents on the web. To solve these problems, we present two network caching schemes(PPC, PPCwP) which consider the characteristics of continuous media objects and user access pattern in this paper. While there are plenty of reasons to create rich media contents, delivering this high bandwidth contents over the internet presents problems such as server overload, network congestion and client-perceived latency. PPC scheme periodically calculates the popularity of objects based on the playback quantity and determines the optimal size of the initial fraction of a continuous media object to be cached in proportion to the calculated popularity. PPCwP scheme calculates the expected popularity using the series information and prefetches the expected initial fraction of newly created continuous media objects. Under the PPCwP scheme, the initial client-perceived latency and the data transferred from a remote server can be reduced and limited cache storage space can be utilized efficiently. Trace-driven simulation have been performed to evaluate the presented caching schemes using the log-files of iMBC. Through these simulations, PPC and PPCwP outperforms LRU and LFU in terms of BHR and DSR.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.979-994
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• 2008

Moving objects are spatio-temporal data that change their location or shape continuously over time. Generally, if continuously moving objects are managed by a conventional database management system, the system cannot properly process the past and future location which is not stored in the database. Up to now, for the purpose of location tracking which is not stored, the linear interpolation to estimate the past location has been usually used. It is suitable for the moving objects on linear route, not curved route. In this paper, we propose a past location tracking algorithm for a moving object on curved routes, and also suggest a future location tracking algorithm using some past location information. We found that the proposed location tracking algorithm has higher accuracy than the linear interpolation function.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.157-162
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• 2000

Discriminant analysis is a method to relate whether the objects have a specific characteristic or not with their 'continuous' attribute values and, for given objects, to estimate whether they have a specific characteristic or not by their values of discriminant scores gotten from their attribute values. The author developed the new 'computational' method of discriminant analysis without specific hypotheses or assumptions and, by this new method, we can find 'feasible' solutions under the conditions required by our actual problems. In this paper, the author tried to apply this new method to the discrimination of logical relations. If this trial could be a success, we can apply this new method of discriminant analysis to the problems about relating the specific characteristic of the objects with their 'discrete' attribute values. The result was successful and the applicability of discriminant analysis could be expanded as a method for constructing the models for "estimating impressions".

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

• Journal of the Korea Computer Graphics Society
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• v.6 no.1
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• pp.11-17
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• 2000

We present collision-handling method that includes self-penetration in the case of the colliding between rigid and deformable objects. The collision between objects is detected through the overlap test to the hierarchical structures of the objects. For detecting the collision between the objects at in-between frame, we try overlap test using the structures of a dummy and the rigid objects in addition to the test between the rigid and deformable objects. The dummy object is made from the rigid objects moving direction. When collision occurs, a deformable object must be deformed, as the object doesn't permit penetration. Self-penetration may occur during the object is deformed. It is rapidly detected between the object and a dummy object of another type. The dummy object is made from the object's deformation area between two continuous frames. We constrain the object is deformed until it is self-contacted. Our method can be applied without concerning of the shape of a object.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.6
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• pp.1-17
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• 2001

Nowadays, spatiotemporal data models deal with objects which can be potentially useful for wide range applications in order to describe complex objects with spatial and/or temporal facilities. However, the information needed by each application usually varies, specially in the geographic information which depends on the kind of time oriented views, as defined in the modeling phase of the spatiotemporal geographic data design. To be able to deal with such diverse needs, geographic information systems must offer features that manipulate geometric, space-dependent(i.e, thematic), and spatial relationship positions with multiple time oriented views. This paper addresses problems of the formal definition of relationships among spatiotemporal objects and their properties on geographic information systems. The geographical data are divided in two main classes : geo-objects and geo-fields, which describe discrete and continuous representations of the spatial reality. I study semantics and syntax about the temporal changes of attributes and the relationship roles on geo-objects and non-geo-objects, This result will contribute on the design of object oriented spatiotemporal data model which is distinguishied from the recent geographic information system of the homogeneously anchored spatial objects

• The Research Journal of the Costume Culture
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• v.15 no.1 s.66
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• pp.68-80
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• 2007

Surrealism's method of expression and inspiration has been a continuous influence on fashion. What is important is how to identify and research a source of inspiration, and how to use this inspiration to guide the designs that can be worn on a real human body. Therefore, the purpose of this study was to show how to develop ideas and designs from Surrealist objects and how to contribute to the development of designs to the diversity in visual and functional effects along with the changes in consumer's interest. Documentary studies about Surrealism and Surrealist-inflected fashion applying the works of Surrealist and fashion images as a tool of historical research were proceeded. And the ideas for theme, the motifs for print patterns, and the concept of designs were borrowed from Surrealist objects touching on the imagery between the real and reflected, optical and artificial, and the designs were developed with several different visual and functional effects changing color, pattern, size, and length with the function of zippers in each item. It also gives the person wearing it amusement because it includes the concept of play and D.I.Y. With effective planning, it is possible to attract consumer's interest in the market.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.63.1-63.1
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• 2019

Solar system small bodies are unusual objects in astronomical survey data in that they are moving on the celestial sphere. In addition, even in a normal status, their magnitudes are changing over time, firstly because their relative positions with respect to the Sun and Earth are continually changing, secondly because they are rotating bodies with non-spherical shapes. Furthermore, some of them might exhibit unexpected activities, which could be caused by mass ejection or disintegration. Detections and observations of such activities are challenging due to their abrupt nature. Therefore, continuous monitoring observations of large number of Solar system small bodies are required to systematically obtain detailed/transient information about them. Since 2018/2019 winter, we have launched a new project using Korea Microlensing Telescope Network (KMTNet) for detecting such transient phenomena of Solar system objects. Our main goal is to monitor the magnitudes and detect sudden brightness changes. We also plan to discover interesting new objects, and monitor rotational brightness oscillations of asteroids. We intend to monitor the magnitudes of ~ 20,000 known Solar system small bodies per night, and acquire lightcurves of ~ 1,000 asteroids.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.40-41
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• 2023

This paper introduces the design of detection, recognition, and tracking algorithms for VTS radar image-based objects. The detection of objects in radar images utilizes artificial intelligence technology to determine the presence or absence of objects, and can classify the type of object using AI technology. Tracking involves the continuous tracking of detected objects over time, including technology to prevent confusion in the movement path. In particular, for land-based radar, there are unnecessary areas for detection depending on the terrain, so the function of detecting and recognizing vessels within the region of interest (ROI) set in the radar image is included. In addition, the extracted coordinate information is designed to enable various applications and interpretations by calculating speed, direction, etc.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.13-23
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• 2024

For the purpose of predicting credit card customer churn accurately through data analysis Detecting and tracking objects in continuous video is essential in self-driving cars, security and surveillance systems, sports analytics, medical image processing, and more. Correlation tracking methods such as Normalized Cross Correlation(NCC) and Sum of Absolute Differences(SAD) are used as an effective way to measure the similarity between two images. NCC, a representative correlation tracking method, has been useful in real-time environments because it is relatively simple to compute and effective. However, correlation tracking methods are sensitive to rotation and size changes of objects, making them difficult to apply to real-time changing videos. To overcome these limitations, this paper proposes an object tracking method using the Histogram of Oriented Gradients(HOG) feature to effectively obtain object data and the Convolution Neural Network(CNN) algorithm. By using the two algorithms, the shape and structure of the object can be effectively represented and learned, resulting in more reliable and accurate object tracking. In this paper, the performance of the proposed method is verified through experiments and its superiority is demonstrated.