• Convergence Security Journal
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• v.6 no.4
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• pp.91-99
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• 2006

Generally, a study of web caching is conducted on a performance improvement with structural approaches and a new hybrid method using existing methods, and studies on caching method itself. And existing analysis of reference-characteristic are conducted on a history analysis and a preference of users, a view point of data mining by log analysis. In this study, we analyze the reference-characteristic of web object on a view point of a characteristic of probability-distribution and a mean value of lifetime of a web-object. And using this result, we propose the new method for a performance improvement of a web-caching.

• International Journal of Contents
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• v.11 no.3
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• pp.47-53
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• 2015

Visual object tracking is a fundamental problem in the field of computer vision, as it needs a proper model to account for drastic appearance changes that are caused by shape, textural, and illumination variations. In this paper, we propose a feature-based visual-object-tracking method with a sparse representation. Generally, most appearance-based models use the gray-scale pixel values of the input image, but this might be insufficient for a description of the target object under a variety of conditions. To obtain the proper information regarding the target object, the following combination of features has been exploited as a corresponding representation: First, the features of the target templates are extracted by using the HOG (histogram of gradient) and LBPs (local binary patterns); secondly, a feature-based sparsity is attained by solving the minimization problems, whereby the target object is represented by the selection of the minimum reconstruction error. The strengths of both features are exploited to enhance the overall performance of the tracker; furthermore, the proposed method is integrated with the particle-filter framework and achieves a promising result in terms of challenging tracking videos.

• The Journal of Information Systems
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• v.16 no.1
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• pp.111-133
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• 2007

The purpose of this study is to present a new function point estimation approach for the Object-Oriented information systems. In order to fulfill this purpose, we first review the literature on Function Point Analysis of IFPUG, Unified Modeling Language, and Unified Process. Then, we derive a method and rules for estimating Function Points based on Use Cases and Class Diagrams. To analyze the appropriateness of the proposed approach, we conduct the empirical testing. 143 use cases are collected from production, marketing, distribution, sales, and other areas from the Object-Oriented systems development projects. We compare our new approach with the existing methods that are usually used for traditional systems development projects. The results show that our proposed approach is more appropriate for the Object-Oriented environment.

• International Journal of Contents
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• v.9 no.1
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• pp.6-10
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• 2013

Foreground estimation in object segmentation has been an important issue for last few decades. In this paper we propose a GrabCut based automatic foreground estimation method using block clustering. GrabCut is one of popular algorithms for image segmentation in 2D image. However GrabCut is semi-automatic algorithm. So it requires the user input a rough boundary for foreground and background. Typically, the user draws a rectangle around the object of interest manually. The goal of proposed method is to generate an initial rectangle automatically. In order to create initial rectangle, we use Gabor filter and Saliency map and then we use 4 features (amount of area, variance, amount of class with boundary area, amount of class with saliency map) to categorize foreground and background. From the experimental results, our proposed algorithm can achieve satisfactory accuracy in object segmentation without any prior information by the user.

• Korean Journal of Child Studies
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• v.7 no.1
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• pp.85-95
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• 1986

The purpose of the present research was to study effects of experimental conditions and developmental tendency in the use of external cues in memory-for-object location in toddlers. This study consisted of two experiments. In study 1, the subjects were 12 toddlers, 18 to 23 months old ; in study 2, 30 toddlers, 24 to 41 months old. The findings showed that memory-for-object location in toddlers was different in accordance with experimental conditions; that is, memory-for-object location in the natural condition was significantly better than in the artificial condition. Effects of external cues were found ; that is, memory-for-object location was best in the condition of spatial cues, and next best in the condition of picture cues, and least good in the no cue condition.

• Korean Journal of English Language and Linguistics
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• v.4 no.1
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• pp.103-116
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• 2004

Chomsky (2001) and Kitahara's (2002) suggestion that object shift occurs prior to movement of the νP-subject to SPEC-T is not on the right track with respect to the Merge operation. According to the Merge operation, TP is necessarily created earlier than CP. Chomsky (2001) suggests that the probe-goal relation between T and SUBJ is evaluated in the CP after it is known whether the position of as has become a trace losing its phonological content. However, the FocP is not a phase (CP). So, Chomsky (2001) and Kitahara's (2002) suggestion is not correct in the case of the movement of OBJ to the spec of Foc in English, either. The aim of this paper is to show that the νP-subject must move to SPEC- T prior to the consecutive movement of the wh-object to SPEC-C via object shift in English. This derivation obeys Chomsky's (2001) so-called probe-goal matching condition.

• Korean Journal of English Language and Linguistics
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• v.2 no.1
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• pp.31-52
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• 2002

This paper discusses the nature of the associate NP of English there constructions and attempts to capture the underlying similarity between the associate NP in English and the nominative object in Korean. Specifically, this paper is centered on the Case property of the associate NP. As the first step, previous proposals on the case of the associate NP are critically reviewed. Through the criticism, this paper opposes to Chomsky's (1995, 2000, 2001) analysis and to Lasnik's (1999) partitive Case analysis. In particular, convincing reason for the partitive Case assignment to the associate NP, other than other cases, cannot be found. This paper, therefore, adopts a recent claim of Boeckx (2000) that the Case under consideration is nominative by Agree. His idea is extended to the analysis of the presentational expletive construction. This paper draws a conclusion that the associate NP of the presentational expletive construction has accusative by Agree. This dichotomy (or split) is also observed in the nominative object construction in Korean. In the nominative object construction, the nominative object has nominative Case by Agree, whereas the regular object has accusative by Agree.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.44-54
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• 2012

In wireless sensor networks, a moving object tracking scheme is one of core technologies for real applications such as environment monitering and enemy moving tracking in military areas. However, no works have been carried out on processing the failure of object tracking in sparse sensor networks with holes. Therefore, the energy consumption in the existing schemes significantly increases due to plenty of failures of moving object tracking. To overcome this problem, we propose a novel moving object tracking scheme based on polynomial regression prediction in sparse sensor networks. The proposed scheme activates the minimum sensor nodes by predicting the trajectory of an object based on polynomial regression analysis. Moreover, in the case of the failure of moving object tracking, it just activates only the boundary nodes of a hole for failure recovery. By doing so, the proposed scheme reduces the energy consumption and ensures the high accuracy for object tracking in the sensor network with holes. To show the superiority of our proposed scheme, we compare it with the existing scheme. Our experimental results show that our proposed scheme reduces about 47% energy consumption for object tracking over the existing scheme and achieves about 91% accuracy of object tracking even in sensor networks with holes.

• Journal of Families and Better Life
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• v.15 no.2
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• pp.173-184
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• 1997

This study identifies the research-object of institutional household and differenciates the family resource management perspectives from the business administration perspectives in the area of management study. This study concludes : for the development of the advanced studies on 'institutional household management' in family resource management the theoretical investigations must be accompanied with the practical work for the enforcement of institutional household manager.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.49-58
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• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.