• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.29-32
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• 1999

In this study, the time delay model were simulated using the well-known AR model. Frequency response of the time delay model can be obtained by mapping AR model to JTC model in the time domain. That is, from the few measurement data in JTC model, the channel frequency response can be obtained by the estimation of AR model parameters. From this channel frequency response, the time delay model can be obtained using Fourier transformation. To prove the validity of the suggested method, three models of JTC were shown and analyzed.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2486-2488
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• 1998

In this paper, Prameters esimated t using AR model in order to approach linearly the heart sound which include the nonlinear characteristic from the characteristics based on a statistical theory. The parameters which is figured out using AR model is a very important information which show the characteristic heart sound In this paper parameters estimated using autocorrelation method and order selected by proposed Akaike[6] method. Compared the similirities of the spectrums between estimated by using AR model and estimated by using FFT method.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.191-198
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• 2020

In this study, we proposed a real-time ECG analytical method for predicting stress and dangerous heart condition using the ECG signal in playing AR/VR device. A real-time diagnosis is used as R-R interval based HRV(:Heart rate variability), BPM(:Beats Per Minitue) and autonomic nervous research with through mapping method of two-dimensional planes. The ECG data were analyzed every 5 minutes and derived from autonomic nervous system diagnosis.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.141-150
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• 2003

This paper presents the multiple testing method of an autoregressive parameter in stationary AR(1) model using the usual Bayes factor. As prior distributions of parameters in each model, uniform prior and noninformative improper priors are assumed. Posterior probabilities through the usual Bayes factors are used for the model selection. Finally, to check whether these theoretical results are correct, simulated data and real data are analyzed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.449-452
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• 2023

본 연구는 신산업분야 특화 선도전문대학 지원사업 연구를 통해 개발된 CK-AR/VR PBL 교수법을 팀 프로젝트 기반의 캡스톤디자인 정규 교과목 수업에 적용해봄으로써, 해당 교수법의 장점 및 문제점을 파악하고 활용방안을 모색하기 위해 진행되었다. CK-AR/VR PBL 교수법은 기존 PBL(문제중심수업) 교수법의 특징과 장점을 유지하고 AR/VR 게임콘텐츠 특성에 맞는 특징을 중심으로 구축된 교수법으로 15주 정규교과목 수업인 '취업과창업을위한차세대게임창작프로젝트(캡스톤디자인)' 수업과 '취업과창업을위한차세대게임 포스트프로덕션(캡스톤디자인)' 수업을 수강한 200여 명의 학생에게 적용하였고 장단점을 파악하게 되었다. 이를 바탕으로 게임 개발 팀 프로젝트 교육과정을 운영 중인 교육 관계자들이나 앞으로 유사한 교육과정을 운영하기 위해 준비 중인 교육 관계자들에게 조금이나마 도움을 주고자 한다.

• Journal of the Korean Chemical Society
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• v.44 no.3
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• pp.190-193
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• 2000

ab initio calculations are presented for M-Rg and M-Rg2 (M=Li, Na, Rg=He, Ar) van der Waals clusters.InternucIear distances and binding energies of LiHe, LiAr and NaAr obtained by all-electron MP2(6-311++G(3df,3pd)) method are in good agreement with experimental values. Calculated properties of LiHe$_2$, LiAr$_2$, NaHe$_2$ and NaAr$_2$ are also reported.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.34 no.8
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• pp.87-94
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• 2018

Hwaseong Fortress was designated as a World Heritage Site by UNESCO in 1997 in recognition of its architectural, cultural, and historical significance. In order to provide a compelling and active experience to the visitors of Hwaseong Fortress more effectively and intuitively, an augmented reality (AR) mobile application is developed. The main objective of this paper is to describe the implementation of AR technology in the developed application; and most importantly, how the application is designed for the visitors to actively and intuitively experience the various architectural and historical contents of Hwaseong. The tour routes and their point of interests were selected carefully after deliberation of their contents. To maximize the user interaction with the application and the architectural contents of Hwaseong, not only the conventional AR technology (marker method), but also the markerless AR method is adopted in the developed application. It is expected that visitors of Hwaseong Fortress enjoy the tour, while learning the architectural, historical, and cultural contents through the active and intuitive interaction with the developed AR mobile application.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.713-719
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• 2009

In this paper, we develope a water demand forecasting algorithm using AR(Auto-regressive) and MLP(Multi-layer perceptron). To show effectiveness of the proposed method, we analyzed characteristics of time-series data collected in "A" purification plant at Jeon-Buk province during 2007-2008, and then performed the proposed method with various input factors selected through various analyses. As noted in experimental results, the performance of three types model such as multi-regressive, AR(Auto-regressive), and AR+MLP(Auto-regressive + Multi-layer perceptron) show 5.1%, 3.8%, and 3.6% with respect to MAPE(Mean Absolute Percentage Error), respectively. Thus, it is noted that the proposed method can be used to predict short-term water demand for the efficient operation of a water purification plant.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.4
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• pp.545-554
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• 2019

The purpose of this study is to develop a method of applying AR(Augmented Reality)/VR(Virtual Reality) to educational and training systems from a comprehensive perspective, rather than applying AR/VR technology to specific education and training systems. We suggested whether to apply AR or VR technology to education and training system, the level of application of technology when constructing using AR/VR technology, and the criteria of priority among many education and training systems. To do this, we presented the framework of application of AR/VR technology, the evaluation criteria for selecting priority of education and training system applying AR/VR, and the systematic procedure for utilization of developed method. This study is significant in that it has developed a method to determine the direction of systematic AR/VR technology application for all education and training systems operated by the military or organization. This is expected to contribute to the overall efficiency of the organization in terms of economical utilization of the limited budget as well as the various benefits of utilizing basic AR/VR technology.

• Journal of Biomedical Engineering Research
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• v.31 no.3
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• pp.177-186
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• 2010

In 3D ultrasound color Doppler imaging (CDI), 8-16 pulse transmissions (ensembles) per each scanline are used for effective clutter rejection and flow estimation, but it yields a low volume acquisition rate. In this paper, we have evaluated three flow estimation methods: autoregression (AR), eigendecomposition (ED), and autocorrelation combined with adaptive clutter rejection (AC-ACR) for a small ensemble size (E=4). The performance of AR, ED and AC-ACR methods was compared using 2D and 3D in vivo data acquired under different clutter conditions (common carotid artery, kidney and liver). To evaluate the effectiveness of three methods, receiver operating characteristic (ROC) curves were generated. For 2D kidney in vivo data, the AC-ACR method outperforms the AR and ED methods in terms of the area under the ROC curve (AUC) (0.852 vs. 0.793 and 0.813, respectively). Similarly, the AC-ACR method shows higher AUC values for 2D liver in vivo data compared to the AR and ED methods (0.855 vs. 0.807 and 0.823, respectively). For the common carotid artery data, the AR provides higher AUC values, but it suffers from biased estimates. For 3D in vivo data acquired from a kidney transplant patient, the AC-ACR with E=4 provides an AUC value of 0.799. These in vivo experiment results indicate that the AC-ACR method can provide more robust flow estimates compared to the AR and ED methods with a small ensemble size.