• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.263-275
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• 2017

Integrated numerical approaches with physically-based conceptualization are required for accurate urban inundation simulation. In this study, we described, applied and analyzed an integrated 1-dimensional (1D) sewerage system and 2-dimensional (2D) surface flow model, which was suggested by Lee et al. (2015). This model was developed based on dual-drainage concept, and uses storm drains as an discharge exchange spot rather than manholes so that interaction phenomena between surface flow and sewer pipe flow are physically reproduced. In addition, the building block concept which prevents inflows from outside structures is applied in order to consider building effects. The capability of the model is demonstrated via reproducing the past flooding event at the Sadang-cheon River catchment, Seoul, South Korea. The results show the plausible causes of the inundation could be analysed in detail by integrated 1D-2D modeling.

• Bulletin of the Korean Chemical Society
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• v.4 no.1
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• pp.28-36
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• 1983

We considered the tunneling effect on the rate constants calculated from transition-state theory for the H + $D_2$ and D + $H_2$ reactions. A method for evaluating the important parameter Ec (potential barrier height) was proposed. A tunnel-effect correlation factor (TECF) ${\Gamma}_{t}exp{\theta}_t$ was estimated from experimental data, and compared with the corresponding values obtained from many theoretical methods. According to our results, the tunneling effect cannot be negligible around $800^{\circ}$K where the TECF value is ca. 0.8 whereas the factor approaches to unity at T > $2400^{\circ}$K where the tunneling completely disappears. In addition to the above fact, we also found that the TECF for the D + $H_2$ reaction is greater than that of the H + $D_2$ reaction in agreement with Garrett and Truhlar's result. In contrast to our result, however, Shavitt found that the order is reversed, i.e., TECF for (D + $H_2$) is greater than that for (H + $D_2$). We discussed about the Shavitt's result.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.28-35
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• 2006

Statistical models of shape variability based on active shape models (ASMs) have been successfully utilized to perform segmentation and recognition tasks in two-dimensional (2D) images. Three-dimensional (3D) model-based approaches are more promising than 2D approaches since they can bring in more realistic shape constraints for recognizing and delineating the object boundary. For 3D model-based approaches, however, building the 3D shape model from a training set of segmented instances of an object is a major challenge and currently it remains an open problem in building the 3D shape model, one essential step is to generate a point distribution model (PDM). Corresponding landmarks must be selected in all1 training shapes for generating PDM, and manual determination of landmark correspondences is very time-consuming, tedious, and error-prone. In this paper, we propose a novel automatic method for generating 3D statistical shape models. Given a set of training 3D shapes, we generate a 3D model by 1) building the mean shape fro]n the distance transform of the training shapes, 2) utilizing a tetrahedron method for automatically selecting landmarks on the mean shape, and 3) subsequently propagating these landmarks to each training shape via a distance labeling method. In this paper, we investigate the accuracy and compactness of the 3D model for the human liver built from 50 segmented individual CT data sets. The proposed method is very general without such assumptions and can be applied to other data sets.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.229-234
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• 2006

Acquisition is to detect the presence of the GPS signal. Once the signal is detected, the estimated frequency and code phase are passed to a tracking loop to demodulate the navigation data. In order to detect the weak signal, multiple length of data integration is always needed. In this paper, we present five different acquisition approaches based on circular correlation and Fast Fourier Transform (FFT), using coherent as well as non-coherent integration techniques for the multiple length of collected GPS satellite signal. Moreover a general approach of determining the acquisition threshold is introduced based on noise distribution which has been proved effective, and independent of the hardware. In the end of this paper, the processing speed and acquisition gain of each method are illustrated, compared, and analyzed. The results show that coherent approach is much more time consuming compared to noncoherent approaches, and in the case of multiple length of data integration from 2ms to 8ms, the processing times consumed by the fastest non-coherent acquisition method are only 25.87% to 1.52% in a single search, and 34.76% to 1.06% in a global search of those in the coherent acquisition. However, coherent acquisition also demonstrates its better performance in the acquisition gain, and in the case of 8ms of data integration it is 4.23 to 4.41 dB higher than that in the non-coherent approaches. Finally, an applicable scheme of combining coherent and non-coherent acquisition approaches in the development of a real-time Software GPS receiver in the University of Tokyo is provided.

• Smart Media Journal
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• v.1 no.3
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• pp.15-21
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• 2012

Depth information is necessary for various three dimensional contents generation. Depth acquisition techniques can be categorized broadly into two approaches: active, passive depth sensors depending on how to obtain depth information. In this paper, we take a look at several ways of depth acquirement. We present not only depth acquisition methods using discussed ways, but also hybrid methods which combine both approaches to compensate for drawbacks of each approach. Furthermore, we introduce several matching cost functions and post-processing techniques to enhance the temporal consistency and reduce flickering artifacts and discomforts of users caused by inaccurate depth estimation in 3D video.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.44-54
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• 2008

In this paper, an iterative multiple symbol differential detection for turbo coded differential unitary space-time modulation using a posteriori probability (APP) demodulator is investigated. Two approaches of different complexity based on linear prediction are presented to utilize the temporal correlation of fading for the APP demodulator. The first approach intends to take account of all possible previous symbols for linear prediction, thus requiring an increase of the number of trellis states of the APP demodulator. In contrast, the second approach applies Viterbi algorithm to assist the APP demodulator in estimating the previous symbols, hence allowing much reduced decoding complexity. These two approaches are found to provide a trade-off between performance and complexity. It is shown through simulation that both approaches can offer significant BER performance improvement over the conventional differential detection under both correlated slow and fast Rayleigh flat-fading channels. In addition, when comparing the first approach to a modified bit-interleaved turbo coded differential space-time modulation counterpart of comparable decoding complexity, the proposed decoding structure can offer performance gain over 3 dB at BER of $10^{-5}$.

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.45-54
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• 2018

This paper presents a vision-based fall detection system to automatically monitor and detect people's fall accidents, particularly those of elderly people or patients. For video analysis, the system should be able to extract both spatial and temporal features so that the model captures appearance and motion information simultaneously. Our approach is based on 3-dimensional convolutional neural networks, which can learn spatiotemporal features. In addition, we adopts a thermal camera in order to handle several issues regarding usability, day and night surveillance and privacy concerns. We design a pan-tilt camera with two actuators to extend the range of view. Performance is evaluated on our thermal dataset: TCL Fall Detection Dataset. The proposed model achieves 90.2% average clip accuracy which is better than other approaches.

• Journal of the Korean Society of Combustion
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• v.22 no.2
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• pp.27-35
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• 2017

This paper reviews the previous industrial solid bed process simulations to provide a better understanding of the modeling approaches to the particle reactions in the bed. Previous modeling studies on waste incinerator, iron ore sintering bed, blast furnace, iron ore pellet indurator, and biomass combustor can be seen on the common ground of unsteady 1-D modeling scheme. Approaches to the particle reaction modeling have been discussed in terms of the status of solid particles in the bed, types of reaction progression in a particle, and the consideration of the intra-particle temperature gradient.

• Research in Mathematical Education
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• v.13 no.3
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• pp.197-216
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• 2009

The purpose of this study was to investigate middle and high school mathematics teachers' levels and multiple approaches in United States practicing their abstraction levels and, different strategies and method of solutions towards given number theory problems. The mathematics teachers taking part in this study are consisted of 25 members of online graduate and undergraduate course (MAE 5641 and MAE 4813) delivered through Online Learning System called as the Blackboard (http://www.blackboard.com). Data collection methods include journal entries, written solutions to problems, the teachers' reflections on said problems, and post interviews. Data analysis was done based on [Hazzan, O. & Zazkis, R. (2005). Reducing abstraction: The case of school mathematics. Educ. Stud. Math. 58(1), 101-119]. Analysis of students' written solutions revealed that transitions among the solution methods have major effect on abstraction levels. Elevation and reducing abstraction is a dynamic process.

• Journal of Communications and Networks
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• v.12 no.1
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• pp.5-10
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• 2010

This paper introduces a new fast motion estimation based on estimating a block matching error (i.e., sum of absolute difference (SAD)) between blocks which can eliminate an impossible candidate block much earlier than a conventional partial distortion elimination (PDE) scheme. The basic idea of the proposed scheme is based on predicting the total SAD of a candidate block using its partial SAD. In particular, in order to improve prediction accuracy and computational efficiency, a sub-sample based block matching and a selective pixel-based approaches are employed. In order to evaluate the proposed scheme, several baseline approaches are described and compared. The experimental results show that the proposed algorithm can reduce the computations by about 44% for motion estimation at the cost of 0.0005 dB quality degradation versus the general PDE algorithm.