• Korean Journal of Cognitive Science
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• v.20 no.4
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• pp.507-533
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• 2009

This paper examines the time course and processing patterns of filler-gap dependencies in Korean relative clauses, using an eyetracking method. Participants listened to a short story while viewing four pictures of entities mentioned in the story. Each story is followed by an auditorily presented question involving a relative clause (subject relative or dative relative). Participants' eye movements in response to the question were recorded. Results showed that the proportion of looks to the picture corresponding to a filler noun significantly increased at the relative verb affixed with a relativizer, and was largest at the filler where the fixation duration on the filler picture significantly increased. These results suggest that online resolution of the filler-gap dependency only starts at the relative verb marked with a relativiser and is finally completed at the filler position. Accordingly, they partly support the filler-driven parsing strategy for Korean, as for head-initial languages. In addition, the different patterns of eye movements between subject relatives and dative relatives indicate the role of case markers in parsing Korean sentences.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.121-129
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• 2012

Any development plan of a Korean space-based navigational system has been neither designed nor introduced yet. However, the demand for the development of a domestic regional satellite navigation system can be originated from the outside of market. The growing dependency on satellite navigational systems in Korea eventually requires the retainment and the operation of a domestic navigational satellite system. There is not many choices on the orbit designs and the system design concepts of a regional augmented navigation satellite system or a regional navigation satellite system for the service on the vicinity of the Korean peninsular. Space situational awareness (SSA) has been a rising issue for both national security and more realistic space business in Korea. Also SSA related technologies in Korea is a newly inaugurated area and is necessary to generate a navigation messages and maintain a future Korean navigation satellite system. In this study, the availability of Japanese Quasi Zenith Satellite System (QZSS) expected to be deployed definitely sooner than Korean counter-part is analyzed. The availability of the similar configured system over Korea is investigated with assumed QZSS type orbit. Also, feasible configuration of orbits for domestic navigation satellite system is suggested. And the observability of a ground-based optical tracking system as a secondary tracking capability is analyzed.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.691-698
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• 1996

This paper propose a procedure to estimate the system lifetime distribution using simulation method in a parametric framework and also develop the criterion for terminating the simulation. We assume that a system is composed of many components whose lifetime and repair time distributions are general, and repair of each component is imperfect or not. General simulation algorithms can not be adopted for this case, due to the dependency of successive operating times and the discontinuity in base line intensity function of failure process. Then we propose algorithms for generating failure times subject to imperfect repair. We develop the event time tracking logic for identifying the system failure time, and also develop the criterion for terminating the simulation. Our procedure is composed of two phases. The first phase of the procedure is to generate the system failure times from the inputs. The second phase is to estimate the lifetime distribution of the system. The best model is selected by a fully automated procedure among well-known parametric families, and the required parameters are estimated. We give examples to show the accuracy of our procedure and the effect of repair effect of components to system MTTF(Mean Time To Failure).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1564-1572
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• 2011

In this paper, we propose a new histogram based hand recognition algorithm for augmented reality. Hand recognition system makes it possible a useful interaction between an user and computer. However, there is difficulty in vision-based hand gesture recognition with viewing angle dependency due to the complexity of human hand shape. A new hand recognition system proposed in this paper is based on the features from hand geometry. The proposed recognition system consists of two steps. In the first step, hand region is extracted from the image captured by a camera and then hand gestures are recognized in the second step. At first, we extract hand region by deleting background and using skin color information. Then we recognize hand shape by determining hand feature point using histogram of the obtained hand region. Finally, we design a augmented reality system by controlling a 3D object with the recognized hand gesture. Experimental results show that the proposed algorithm gives more than 91% accuracy for the hand recognition with less computational power.

• Proceedings of the KSRS Conference
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• 2009.03a
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• pp.97-100
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• 2009

The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 and 2000 using a dynamic technique, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series for tracking changes on the ground surface. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Korean Journal of Remote Sensing
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• v.25 no.2
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• pp.95-105
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• 2009

Irregular temporal sampling is a common feature of geophysical and biological time series in remote sensing. This study proposes an on-line system for reconstructing observation image series including bad or missing observation that result from mechanical problems or sensing environmental condition. The surface parameters associated with the land are usually dependent on the climate, and many physical processes that are displayed in the image sensed from the land then exhibit temporal variation with seasonal periodicity. An adaptive feedback system proposed in this study reconstructs a sequence of images remotely sensed from the land surface having the physical processes with seasonal periodicity. The harmonic model is used to track seasonal variation through time, and a Gibbs random field (GRF) is used to represent the spatial dependency of digital image processes. In this study, the Normalized Difference Vegetation Index (NDVI) image was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula, and the adaptive reconstruction of harmonic model was then applied to the NDVI time series from 1996 to 2000 for tracking changes on the ground vegetation. The results show that the adaptive approach is potentially very effective for continuously monitoring changes on near-real time.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.16 no.3
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• pp.162-170
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• 2004

On the basis of the radiotracer technology and the related equipments which have been developed for its industrial application through the nuclear long-term research project, a radiotracer study on sediment transport was carried out as a part of the development of the radiotracer technology for a coastal environment. The crystalline material doped with iridium having a similar composition and specific gravity as those of the bedload sand collected from the research area was produced by the oxide-route method. A radioisotope container was specially designed to inject the radiotracer from 1 m above the sea bedload without radioactive contamination during the transport from the nuclear reactor at KAERI. The position data from the DGPS and the radiation measurement data were collected concurrently and stored by means of the application software programmed with the LabVIEW of the National Instrument. The position data was reprocessed to represent the real position of the radiation probe under water and not that of the DGPS antenna on board. The time dependency of the spatial distribution of the sediment was studied in the area through three tracking measurements after the iridium glass was injected. This trial application showed the potential of the radiotracer technology as an important role for maintaining and developing the coastal environment in the future.

• Progress in Medical Physics
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• v.21 no.4
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• pp.311-322
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• 2010

In proton therapy, the analysis of secondary particles is important due to delivered dose outside the target volume and thus increased potential risk for the development of secondary cancer. The purpose of this study is to analyze the influence of secondary particles from proton beams on fluence and energy deposition in the presence of inhomogeneous material by using Geant4 simulation toolkit. The inhomogeneity was modeled with the condition that the adipose tissue, bone and lung equivalent slab with thickness of 2 cm were inserted at 30% (Plateau region) and 80% (Bragg peak region) dose points of maximum dose in Bragg curve. The energy of proton was varied with 100, 130, 160 and 190 MeV for energy dependency. The results for secondary particles were presented for the fluence and deposited energy of secondary particles at inhomogeneous condition. Our study demonstrates that the fluence of secondary particles is neither influenced insertion of inhomogeneties nor the energy of initial proton, while there is a little effect by material density. The deposited energy of secondary particles has a difference in the position placed inhomogeneous materials. In the Plateau region, deposited energy of secondary particles mostly depends on the density of inserted materials. Deposited energy in the Bragg region, in otherwise, is influenced by both density of inserted material and initial energy of proton beams. Our results suggest a possibility of prediction about the distribution of secondary particles within complex heterogeneity.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.