• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.31-32
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• 2006

A signal conditioning circuit for capacitive sensors was developed using a commercial single chip solution. Since capacitive displacement sensors can achieve high resolution and linearity, they have been widely used as precision sensors within the range of several hundred micrometers. However, they inherently have a limitation in low frequency range and some nonlinearity characteristics and so a specially designed signal conditioning circuit is needed to handle these properties. Up to now, several companies already have succeeded in the development of the capacitive sensors system and they are commercially available in the market. In this research, to construct the signal processing circuits more easily and simply, we used a universal LVDT signal conditioner (AD698). Since the AD698 provides one chip solution for a basic signal processing including modulation and demodulation using various internal components, we can build the processing circuits successfully with minimal additional circuits: a compensation circuits for the drift caused by the bias current of OP amplifiers and a fine adjustment circuit for the elimination of nonlinearity. The signal processing circuits shows nonlinearity less than 0.05% in the comparison with a laser interferometer.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.331-343
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• 2014

We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).

• Journal of Digital Convergence
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• v.6 no.1
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• pp.53-61
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• 2008

For the domestic digital contents, a proactive cooperation system or framework between the government, the businesses and research institutions, which would allow for free flow of interaction among these players, can play that role. We have proposed and realized the Dynamic Coordinating Framework(DCF) to bridge these gaps among the major players in the industry. The the Dynamic Coordinating Framework rests on the following major functions. The first major function of the DCF is to decipher any ambiguity that may be embedded in external inputs by stratified role and bias. The second function is to create cooperative groups that will deal with the ambiguities based on its consequent situation. The third is a feedback function that will draw out a new cooperative way by re-feeding the capacities and the conflicts that stem from the existing organizations and strategies into cooperation and adjustment process. Our DCF has compared and evaluated with England and Australia digital content industry models under AHP(Analytic Hierarchy Process) method. DCF has turned out to be well designed and have strong points based on OECD innovation and cooperation criteria.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.435-443
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• 2015

Two phase sampling design is useful to increase estimation efficiency using deep stratification, improved non-response adjustment and reduced coverage bias. The same sampling units are commonly used for the first and the second phases in complex two-phase sampling design. In this paper we consider a sampling scheme where the first phase sampling units are clusters and the second phase sampling units are list samples. Using selected clusters in first phase requires that we list up elements in the selected clusters from the first phase and then use the list as a secondary sampling frame for the second phase sampling design. Then we select second phase samples from the listed sampling frame. We suggest an estimator based on the complex two-phase sampling design with different sampling units of each phase. Also the estimated variances of the estimator obtained by using classic and replication variance methods are considered and compared using simulation studies. For real data analysis, 2010 Korea Farm Household Economy Survey (KFHES) and 2011 Korea Agriculture Survey (KAS) are used.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.6
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• pp.233-240
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• 2021

The stochastic method is applied to simulate strong ground motions at seismic stations of seven metropolises in South Korea, creating an earthquake scenario based on the causative fault of the 2016 Gyeongju earthquake. Input parameters are established according to what has been revealed so far for the causative fault of the Gyeongju earthquake, while the ratio of differences in response spectra between observed and simulated strong ground motions is assumed to be an adjustment factor. The calculations confirm the applicability and reproducibility of strong ground motion simulations based on the relatively small bias in response spectra between observed and simulated strong ground motions. Based on this result, strong ground motions by a scenario earthquake on the causative fault of the Gyeongju earthquake with moment magnitude 6.5 are simulated, assuming that the ratios of its fault length to width are 2:1, 3:1, and 4:1. The results are similar to those of the empirical Green's function method. Although actual site response factors of seismic stations should be supplemented later, the simulated strong ground motions can be used as input data for developing ground motion prediction equations and input data for calculating the design response spectra of major facilities in South Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.229-235
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• 2020

Investors aim to maximize the return rate for their own investment, utilizing various information as possible as they can access. However those investors, especially individual investors, have limitations of interpretation of the domain-specific information or even the acquisition of the information itself. Thus, individual investors tend to make decision affectively and frequently, which may cause a loss in returns. This study aims to analyze analysts' target price and to suggest the strategy that could maximize individual's return rate. Most previous literature revealed that the optimistic bias exists in the analysts' target price and it is also confirmed in this study. In this context, this study suggests the upper limit of target rate of returns and the optimal value named 'alpha(α)' which performs the adjustment of proposed target rate to maximize excess earning returns eventually. To achieve this goal, this study developed an optimization problem using linear programming. Specifically, when the analysts' proposed target rate exceeds 30%, it could be adjusted to the extent of 59% of its own target rate. As apply this strategy, the investors could achieve 1.2% of excess earning rate on average. The result of this study has significance in that the individual investors could utilize analysts' target price practically.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1121-1121
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• 2001

A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.5
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• pp.467-474
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• 2019

In this paper, we propose a novel method to improve FPS while maintaining the accuracy of YOLO v2 model in NVIDIA Jetson TX1. In general, in order to reduce the amount of computation, a conversion to an integer operation or reducing the depth of a network have been used. However, the accuracy of recognition can be deteriorated. So, we use methods to reduce computation and memory consumption through adjustment of the filter size and integrated computation of the network The first method is to replace the $3{\times}3$ filter with a $1{\times}1$ filter, which reduces the number of parameters to one-ninth. The second method is to reduce the amount of computation through CBR (Convolution-Add Bias-Relu) among the inference acceleration functions of TensorRT, and the last method is to reduce memory consumption by integrating repeated layers using TensorRT. For the simulation results, although the accuracy is decreased by 1% compared to the existing YOLO v2 model, the FPS has been improved from the existing 3.9 FPS to 11 FPS.

• Journal of Digital Convergence
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• v.6 no.3
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• pp.45-52
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• 2008

For the domestic digital contents, it is particularly important that the planning and mediating functions should cover the whole Industries so that dividends and assistance to reach all the way back to the primary contents-creating level, where economic risks are especially high. A proactive cooperation system or framework between the government, the businesses and research institutions, which would allow for free flow of interaction among these players, can play that role. We can broadly define cooperation frameworks into two; one between the central and the local governments and another among private-sector groups, such as companies, associations and groups. These players in the framework have differing, sometimes, conflicting views regarding the digital contents industry whether the digital contents should aim for skilled applicability or the abstract or whether the emphasis should rest on public interest or profitability. Immature competition and lack of trust among these players also give rise to such inefficiencies as overlap in investments, inexpertness and inefficient use of resources. We have proposed and realized the National Integrated Cooperation System to bridge these gaps among the major players in the industry. The National Integrated Cooperation System rests on the following major functions. The first major function of the NICS is to decipher any ambiguity that may be embedded in external Inputs by stratified role and bias. The second function is to create cooperative groups that will deal with the ambiguities based on its consequent situation. The third is a feedback function that will draw out a new cooperative way by re-feeding the capacities and the conflicts that stem from the existing organizations and strategies into cooperation and adjustment process. Our NICS has compared and evaluated with England and Australia digital content industry models under AHP(Analytic Hierarchy Process) method. NICS has turned out to be well designed and have strong points based on OECD innovation and cooperation criteria.

• Korean Journal of Remote Sensing
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• v.29 no.3
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• pp.275-291
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• 2013

Monitoring the global Gross Primary Pproduction (GPP) is relevant to understanding the global carbon cycle and evaluating the effects of interannual climate variation on food and fiber production. GPP, the flux of carbon into ecosystems via photosynthetic assimilation, is an important variable in the global carbon cycle and a key process in land surface-atmosphere interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) is one of the primary global monitoring sensors. MODIS GPP has some of the problems that have been proven in several studies. Therefore this study was to solve the regional mismatch that occurs when using the MODIS GPP global product over Korea. To solve this problem, we estimated each of the GPP component variables separately to improve the GPP estimates. We compared our GPP estimates with validation GPP data to assess their accuracy. For all sites, the correlation was close with high significance ($R^2=0.8164$, $RMSE=0.6126g{\cdot}C{\cdot}m^{-2}{\cdot}d^{-1}$, $bias=-0.0271g{\cdot}C{\cdot}m^{-2}{\cdot}d^{-1}$). We also compared our results to those of other models. The component variables tended to be either over- or under-estimated when compared to those in other studies over the Korean peninsula, although the estimated GPP was better. The results of this study will likely improve carbon cycle modeling by capturing finer patterns with an integrated method of remote sensing.