• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.623-632
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• 2021

Through this study, we studied how to consider environment variables (such as temperatures, weekend, holiday) closely related to electricity demand, and how to consider the characteristics of Korea electricity demand. In order to conduct this study, Smoothing method, Seasonal ARIMA model and regression model with AR-GARCH errors are compared with mean absolute error criteria. The performance comparison results of the model showed that the predictive method using AR-GARCH error regression model with environment variables had the best predictive power.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2835-2841
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• 2024

Real-time analysis of metallic mineral grade and slurry concentration is significant for improving flotation efficiency and product quality. This study proposes an online detection method of ore slurry combining the Prompt Gamma Neutron Activation Analysis (PGNAA) technology and artificial neural network (ANN), which can provide mineral information rapidly and accurately. Firstly, a PGNAA analyzer based on a D-T neutron generator and a BGO detector was used to obtain a gamma-ray spectrum dataset of ore slurry samples, which was used to construct and optimize the ANN model for adaptive analysis. The evaluation metrics calculated by leave-one-out cross-validation indicated that, compared with the weighted library least squares (WLLS) approach, ANN obtained more precise and stable results, with mean absolute percentage errors of 4.66% and 2.80% for Fe grade and slurry concentration, respectively, and the highest average standard deviation of only 0.0119. Meanwhile, the analytical errors of the samples most affected by matrix effects was reduced to 0.61 times and 0.56 times of the WLLS method, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.8
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• pp.759-766
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• 2016

This paper is on a system design of recognizing sound sources and tracing locations from detecting a section of sound sources which is strong in surrounding environmental sounds about sound sources occurring in an abnormal situation by using signals within the section. In detection of the section with strong sound sources, weighted average delta energy of a short section is calculated from audio signals received. After inputting it into a low-pass filter, through comparison of values of the output result, a section strong in background sound is defined. In recognition of sound sources, from data of the detected section, using an HMM(: Hidden Markov Model) as a traditional recognition method, learning and recognition are realized from creating information to recognize sound sources. About signals of sound sources that surrounding background sounds are included, by using energy of existing signals, after detecting the section, compared with the recognition through the HMM, a recognition rate of 3.94% increase is shown. Also, based on the recognition result, location grasping by using TDOA(: Time Delay of Arrival) between signals in the section accords with 97.44% of angles of a real occurrence location.

• Journal of Environmental Science International
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• v.10 no.3
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• pp.195-200
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• 2001

The personal exposures of nitrogen dioxide(NO$_2$), microenvironmental levels and daily time activity patterns on Seoul subway station workers were measured from February 10 to March 12, 1999. Personal NO$_2$exposure for 24 hours were 29.40$\pm$9.75 ppb. NO$_2$level of occupational environment were 27.87$\pm$7.15 ppb in office, 33.60$\pm$8.64 ppb in platform and 50.13$\pm$13.04 ppb in outdoor. Personal exposure time of subway station workers was constituted as survey results with $7.94\pm$3.00 hours in office, $2.82\pm$1.63 hours in platform and 1 hours in outdoor. With above results, personal $NO_2$exposure distributions on subway station workers in Seoul were estimated with Monte Carlo simulation which uses statistical probabilistic theory on various exposure scenario testing. Some of distributions which did not have any formal patterns were assumed as custom distribution type. Estimated personal occupational $NO_2$exposure using time weighted average (TWA) model was 31.$29\pm$5.57 ppb, which were under Annual Ambient Standard (50ppb) of Korea. Though arithmetic means of measured personal $NO_2$exposure was lower than that of occupational $NO_2$exposure estimated by TWA model, considering probability distribution type simulated, probability distribution of measured personal $NO_2$exposures for 24 hours was over ambient standard with 3.23%, which was higher than those of occupational exposure(0.02%). Further research is needed for reducing these 24 hour $NO_2$personal excess exposures besides occupational exposure on subway station workers in Seoul.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.57-65
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• 2010

In this paper, we propose a new real-time algorithm detecting the flame and smoke in digital CCTV images. Because the forest fire causes the enormous human life and damage of property, the early management according to the early sensing is very important. The proposed algorithm for monitoring forest fire is classified into the flame sensing and detection of smoke. The flame sensing algorithm detects a flame through the conditional test at YCbCr color model from the single frame. For the detection of smoke, firstly the background range is set by using differences between current picture and the average picture among the adjacent frames in the weighted value, and the pixels which get out of this range and have a gray-scale are detected in the smoke area. Because the proposed flame sensing algorithm is stronger than the existing algorithms in the change of the illuminance according to the quantity of sunshine, and the smoke detection algorithm senses the pixel of a gray-scale with the smoke considering the amount of change for unit time, the effective early forest fire detection is possible. The experimental results indicate that the proposed algorithm provides better performance than existing algorithms.

• Progress in Medical Physics
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• v.30 no.1
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• pp.22-31
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• 2019

Purpose: To develop a new diffusion-based functional MRI (fMRI) sequence to generate apparent diffusion coefficient (ADC) maps in single excitation and evaluate the contribution of b0 signal on neuronal changes. Materials and Methods: A diffusion-based fMRI sequence was designed with single measurement that can acquire images of three directions at a time, obtaining $b=0s/mm^2$ during the first baseline condition (b0_b), followed by 107 diffusion-weighted imaging (DWI) with $b=600s/mm^2$ during the baseline and visual stimulation conditions, and another $b=0s/mm^2$ during the last activation condition (b0_a). ADC was mapped in three different ways: 1) using b0_b (ADC_b) for all time points, 2) using b0_a (ADC_a) for all time points, and 3) using b0_b and b0_a (ADC_ba) for baseline and stimulation scans, respectively. The fMRI studies were conducted on the brains of 16 young healthy volunteers using visual stimulations in a 3T MRI system. In addition, the blood oxygen level dependent (BOLD) fMRI was also acquired to compare it with diffusion-based fMRI. A sample t-test was used to investigate the voxel-wise average between the subjects. Results: The BOLD data consisted of only activated voxels. However, ADC_ba data was observed in both deactivated and activated voxels. There were no statistically significant activated or deactivated voxels for DWI, ADC_b, and ADC_a. Conclusions: With the new sequence, neuronal activations can be mapped with visual stimulation as compared to the baseline condition in several areas in the brain. We showed that ADC should be mapped using both DWI and b0 images acquired with the same conditions.

• Journal of Broadcast Engineering
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• v.23 no.1
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• pp.138-145
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• 2018

In this paper, we propose a new motion estimation algorithm for frame rate up-conversion. The proposed algorithm uses the variance of errors in addition to SAD in motion estimation to find more accurate motion vectors. Then, it decides which motion vectors are wrong using the variance of neighbor motion vectors and the variance between current motion vector and neighbor's average motion vector. Next, incorrect motion vectors are corrected by weighted sum of eight neighbor motion vectors. Additionally, we propose adaptive search range algorithm, so we can find more accurate motion vectors and reduce computational complexity at the same time. As a result, proposed algorithm improves the average peak signal-to-noise ratio and structural similarity up to 1.44 dB and 0.129, respectively, compared with previous algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.560-570
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• 2006

This paper proposes a selectively cumulative sum (S-CUSUM) control chart with variable sampling intervals (VSI) for detecting shifts in the process mean. The basic idea of the VSI S-CUSUM chart is to adjust sampling intervals and to accumulate previous samples selectively in order to increase the sensitivity. The VSI S-CUSUM chart employs a threshold limit to determine whether to increase sampling rate as well as to accumulate previous samples or not. If a standardized control statistic falls outside the threshold limit, the next sample is taken with higher sampling rate and is accumulated to calculate the next control statistic. If the control statistic falls within the threshold limit, the next sample is taken with lower sampling rate and only the sample is used to get the control statistic. The VSI S-CUSUM chart produces an 'out-of-control' signal either when any control statistic falls outside the control limit or when L-consecutive control statistics fall outside the threshold limit. The number L is a decision variable and is called a 'control length'. A Markov chain model is employed to describe the VSI S-CUSUM sampling process. Some useful formulae related to the steady state average time-to signal (ATS) for an in-control state and out-of-control state are derived in closed forms. A statistical design procedure for the VSI S-CUSUM chart is proposed. Comparative studies show that the proposed VSI S-CUSUM chart is uniformly superior to the VSI CUSUM chart or to the Exponentially Weighted Moving Average (EWMA) chart with respect to the ATS performance.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.615-620
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• 2009

Nowadays, wireless infrastructures such as sensor networks are widely used in many different areas. In case of sensor networks, the wirelessly connected sensors can execute different kind of tasks in a diversity of environments, and one of the most important parameter for a successful execution of such tasks is the location information of each node. As to localization problems in WSNs, there are ToA (Timer of Arrival), RSS (Received Signal Strength), AoA (Angle of Arrival), etc. In this paper, we propose a modification of existing ToA and RSS based methods, adding a weighted average scheme to measure more precisely the distance between nodes. The comparison experiments with the traditional ToA method show that the average error value of proposed method is reduced by 0.1 cm in indoor environment ($5m{\times}7m$) and 0.6cm in outdoor environment ($10{\times}10m$).

• The Journal of the Acoustical Society of Korea
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• v.19 no.8
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• pp.68-77
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• 2000

Line special frequency (LSF) parameters have been widely used in low bit-rate speech coding due to their efficiency for representing the short-time speech spectrum. In this paper, a new distance measure based on the masking properties of human ear is proposed for quantizing LSF parameters whereas most conventional quantization methods are based on the weighted Euclidean distance measure. The proposed method derives the perceptual distance measure from the definition of noise-to-mask ratio (NMR) which has high correspondence with the actual distortion received in the human ear and uses it for quantizing LSF parameters. In addition, we propose an adaptive bit allocation scheme, which allocates minimal bits to LSF parameters maintaining the perceptual transparency of given speech frame for reducing the average bit-rates. For the performance evaluation, we has shown the ratio of perceptually transparent frames and the corresponding average bit-rates for the conventional and proposed methods. By jointly combining the proposed distance measure and adaptive bit allocation scheme, the proposed system requires only 770 bps for obtaining 95.5% perceptually transparent frames, while the conventional systems produce 89.9% at even 1800 bps.