• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.597-604
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• 2014

In this study, we investigate to show the limitations of current bus arrival time estimation model based on each bus route, and to propose a bus arrival time estimation model based on a bus stop to overcome these limitations. Using the characteristic of bus arrival time calculated on travel time between two bus stops, we develop a model to estimate bus arrival times with the data of all buses traveling the same section regardless of bus route numbers. In the proposed model, an estimated arrival time is calculated by weighted moving average method, and verification between observed value and estimated time is performed on the basis of RMSE. Error was reduced by up to 20% compared to the existing models and the data update period was reduced by more than half that is related to the accuracy of bus arrival time information. We expect to solve the following problems with the suggested method: sudden increase or decrease in arrival time of the bus, the difference of the expected arrival times at the same stop between two or more buses having different route numbers, and impossibility of offering information of a bus if the bus is not operated with the designated schedule.

• Journal of Environmental Health Sciences
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• v.27 no.1
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• pp.20-26
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• 2001

personal nitrogen dioxide(NO$_2$) exposures for 31 professional drivers were measured using passive sampler and time activity diary in Asan and Chunan area, and were estimated using time-weighted average model. Mean concentrations of driver’s indoor and outdoor were 24.7$\pm$10.7 ppb and 23.3$\pm$8.3 ppb, respectively with indoor/outdoor of 1.1. Mean personal NO$_2$ exposure was 30.3$\pm$9.7 ppb. Personal NO$_2$ exposures were strongly correlated with indoor car NO$_2$ levels ($R^2$=0.80) rather than residential indoor NO$_2$ level ($R^2$=0.55). and outdoor NO$_2$ level ($R^2$=0.50). The driver’s NO$_2$ exposure using LP-gas with 24.4$\pm$8.0 ppb were statistically different from those using diesel with 36.3$\pm$14.1 ppb(p<0.01). The effect of driver’s smoking for personal NO$_2$ exposure was not found. It was considered that the main NO$_2$in driver is transportation. Since drivers mostly spent their times in indoor and inside car, time-weighted average model could be used to estimated personal NO$_2$ exposure using time activity diary, Though we did not measure all microenvironments, the estimated personal NO$_2$ exposures with 26.9$\pm$10.2 ppb were statistically correlated with measured personal NO $_2$ exposures30.3$\pm$9.7 ppb ($R^2$=0.89). The mean and standard deviation of personal NO$_2$ exposure using Mote-Carlo simulation were 26.6$\pm$7.2 ppb.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.24-27
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• 1996

The storage function method(SFM) is one of hydrologic flood routings which has been used most widely in Korea and Japan. This paper presents a storage function method using multiple model adaptive estimation(MMAE), in which a model set is generated by partitioning storage parameters over feasible range, and each storage function model is estimated, and then the weighted average of them is calculated. Finally, the future runoff is predicted in real time by means of observed data of water level at dam and rainfall. Simulation results applied to actual data show that the proposed method has much better performance than that of conventional SFM.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

• Journal of Satellite, Information and Communications
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• v.10 no.4
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• pp.77-82
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• 2015

This paper proposed an accident prediction model in order to prevent accidents in mountain areas using a big data analysis. Data of accidents in mountain areas are shown as graphs. We have analyzed cases: the number of accidents per year, day of week, time of day to find patterns of the negligent accident in mountain areas. The proposed prediction model consists of weighted variables of the accident in mountain through visualized big data analysis. The model of danger index performance is demonstrated by showing accident-prone areas with weighted variables.

• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.336-343
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• 1995

The Self Tuning Regulator(STR) method which is an approach of adaptive control theory, is ap-plied to design the fully automatic power controller of the nonlinear reactor model. The adaptive control represent a proper approach to design the suboptimal controller for nonlinear, time-varying stochastic systems. The control system is based on a third­order linear model with unknown, time-varying parameters. The updating of the parameter estimates is achieved by the recursive extended least square method with a variable forgetting factor. Based on the estimated parameters, the output (average coolant temperature) is predicted one-step ahead. And then, a weighted one-step ahead controller is designed so that the difference between the output and the desired output is minimized and the variation of the control rod position is small. Also, an integral action is added in order to remove the steady­state error. A nonlinear M plant model was used to simulate the proposed controller of reactor power which covers a wide operating range. From the simulation result, the performances of this controller for ramp input (increase or decrease) are proved to be successful. However, for step input this controller leaves something to be desired.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.563-568
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• 2007

This paper presents a methodology for predicting nonlinear time series based on the neural network with weighted fuzzy membership functions (NEWFM). The degree of classification intensity is obtained by bounded sum of weighted fuzzy membership functions extracted by NEWFM, then weighted average defuzzification is used for predicting nonlinear time series. The experimental results demonstrate that NEWFM has the classification capability of 92.22% against the target class of GDP. The time series created by NEWFM model has a relatively close approximation to the GDP which is a typical business cycle indicator, and has been proved to be a useful indicator which has the turning point forecasting capability of average 12 months in the peak point and average 6 months in the trough point during 5th to 8th cyclical period. In addition, NEWFM measures the efficiency of the economic indexes by the feature selection and enables the users to forecast with reduced numbers of 7 among 10 leading indexes while improving the classification rate from 90% to 92.22%.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.7
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• pp.25-35
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• 2002

In this study, the effect of DEM (Digital Elevation Model) resolution (15m, 30m, 50m, 70m, 100m, 200m, 300m) on the hydrological simulation was examined using the BASINS (Better Assessment Science Integrating point and Nonpoint Source) for the Heukcheon watershed (303.3 ㎢) data from 1998 to 1999. Generally, as the cell size of DEM increased, topographical changes were observed as the original range of elevation decreased. The processing time of watershed delineation and river network needed more time and effort on smaller cell size of DEM. The larger DEM demonstrated had some errors in the junction of river network which might affect on the simulation of water quantity and quality. The area weighted average watershed slope became milder but the length weighted average channel slope became steeper as the DEM size increased. DEM resolution affected substantially on the topographical parameter but less on the hydrological simulation. Considering processing time and accuracy on hydrological simulation, DEM grid size of 100m is recommended for this range of watershed size.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.15-22
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• 2020

In this study, we propose an improvement method that can create U-Net model which detect fine concrete cracks by applying a weighted loss function. Because cracks in concrete are a factor that threatens safety, it is important to periodically check the condition and take prompt initial measures. However, currently, the visual inspection is mainly used in which the inspector directly inspects and evaluates with naked eyes. This has limitations not only in terms of accuracy, but also in terms of cost, time and safety. Accordingly, technologies using deep learning is being researched so that minute cracks generated in concrete structures can be detected quickly and accurately. As a result of attempting crack detection using U-Net in this study, it was confirmed that it could not detect minute cracks. Accordingly, as a result of verifying the performance of the model trained by applying the suggested weighted loss function, a highly reliable value (Accuracy) of 99% or higher and a harmonic average (F1_Score) of 89% to 92% was derived. The performance of the learning improvement plan was verified through the results of accurately and clearly detecting cracks.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1607-1616
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• 2006

The growing market of multimedia and digital signal processing requires significant data-path portions of SoCs. However, the common models for verification are not suitable for SoCs. A novel model--WGL (Weighted Generalized List) is proposed, which is based on the general-list decomposition of polynomials, with three different weights and manipulation rules introduced to effect node sharing and the canonicity. Timing parameters and operations on them are also considered. Examples show the word-level WGL is the only model to linearly represent the common word-level functions and the bit-level WGL is especially suitable for arithmetic intensive circuits. The model is proved to be a uniform and efficient model for both bit-level and word-level functions. Then Based on the WGL model, a backward-construction logic-verification approach is presented, which reduces time and space complexity for multipliers to polynomial complexity(time complexity is less than $O(n^{3.6})$ and space complexity is less than $O(n^{1.5})$) without hierarchical partitioning. Finally, a construction methodology of word-level polynomials is also presented in order to implement complex high-level verification, which combines order computation and coefficient solving, and adopts an efficient backward approach. The construction complexity is much less than the existing ones, e.g. the construction time for multipliers grows at the power of less than 1.6 in the size of the input word without increasing the maximal space required. The WGL model and the verification methods based on WGL show their theoretical and applicable significance in SoC design.