• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.255-257
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• 2017

These days automotive markets are launching models that include a variety of IT technologies. Tesla's Tesla model S and Google's unmanned automobiles are emerging one after another. This type of automobile with IT technology provides various convenience to the driver and the driver is getting benefit by various conveience services. on the contrary, it is also true that defects for errors in electronic components cause accidents that threaten the safety of drivers. There is a sudden unintended acceleration among these accidents. The cause of the accident is not clear yet, but the claim that the ECU device caused by the magnetic field causes accident of the car due is the most reliable. But, in Korea, when occur a car sudden unintended acceleration accident, the char maker often claims that an accident occurred due to driver's pedal malfunction. Also most drivers are responsible for the lack of grounds to refute. In this paper, the pedal operation image of the driver is acquired and the sensor is attached to the control part such as the excel and brake so as to discriminate whether the vehicle sudden unintended acceleration accident is the driver's pedal operation error or the fault of. i have implemented a system that can do this.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.8
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• pp.2010-2024
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• 1998

In video coding, it is important to improve the average picture quality as well as to maintain cosistent picture quality between consecutive pictures. In this paper, we propose a distortion-rate estimation method for MPEG-2 video and a forward rate control method, using the proposed estimation result, to be able to obtain the improved and consistent picture quality of CBR (Constant Bit Rate) encoded MPEG-2 video. The proposed distortion-rate estimation enable us to predict the distortion and the bits generated from an encoded picture at a given quantization step size and vice versa. The most attactive features of proposed distortion-rate estimation are its accuracy and low computational complexity enough to be applied to the practical video coding. In addition, the proposed rate control first determined a quantization parameter per frame by following procedure: distortion-rate estimation, target bit allocation, distortion constraint and VBV(Video Buffer Verification) constraint. And then this quantization parameter is applied to the encoding so that improved and consisten picture quality can be obtained. Furthermore the proposed rate control method can solve the error propagation problem caused by scene change or anchor picture degradation by using the B-picture skipping and the guarantee of the minimum bit allocation for the anchor picture. Experimental results, comparing the proposed forward rate control method with TM5 method, show that the proposed method makes more improed and consistent picture quality than TM5.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.681-690
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• 2020

Generally, the design capacity of the rainwater harvesting unit is determined by trial and error method that is repeatedly calculating various analysis scenarios with capacity, reliability, and rainwater utilization ratio, etc. This method not only takes a lot of time to analyze but also involves a lot of calculations, so analysis errors may occur. In order to solve the problem, this study suggested a way to directly determine the minimum capacity to meet arbitrary target reliabilities using the global optimization method. The method was implemented by simulation model with particle swarm optimization (PSO) algorithms using Python language. The pyswarm that is provided as an open-source of python was used as optimization method, that can explore global optimum, and consider constraints. In this study, the developed program was applied to the design data for the rainwater harvesting constructed in Cheongna district 1 in Incheon to verify the efficiency, stability, and accuracy of the analysis. The method of determining the capacity of the rainwater harvesting presented in this study is considered to be of practical value because it can improve the current level of analytical technology.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.53-64
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• 2013

In building construction project, there are numerous information or data parts across many different software applications and professional specialists. BIM (Building Information Modeling), as a medium for managing information generated during construction project, it is intended to enhance the effectiveness of construction management and reap a lot of advantages such as, automatic quantity takeoff, error-free estimation, 4D(3D+Time), 5D(4D+Cost) simulation. Nevertheless, the overall and practical effectiveness of BIM utilization is difficult to justify at this stage. While helpful, there are some limitation when BIM applied to construction management due to the differences of data processing process between BIM and work in the field, limitations of information generated from BIM object and interoperability problem among BIM application. Therefore, this paper propose a framework integrating BIM with cost-schedule information using IFC. And we construct the system prototype based on the framework and performed case study to examine the framework. The proposed framework provides the information basis for BIM based cost-schedule integration. ultimately, the framework increase the utilization of BIM and work efficiency of construction industry by supporting an understanding of information.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.479-487
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• 2004

Biopotential signals have been used as command in systems using electrical stimulation of motor nerves to restore movement after an injury to the central nervous system (CNS). In order to use the voluntary EMG (electromyography) among the biopotentials as a control signal for the electrical stimulation of the same muscle for CNS injury patients, it is necessary to remove M-wave of having high magnitude from raw data. We designed an optimal filter for removing the M-wave and preserving the voluntary EMG and showed that the optimal filter is eigen filter. We also proved that the previous method using the prediction error filter(PEF) is a suboptimal filtering in the sense of preserving the voluntary EMG. On basis of the data obtained from a model for M-wave and voluntary EMG and from actual CNS injury patients, with false-positive rate analysis, the proposed adaptive filter showed a very promising performance in comparison with previous method.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.713-722
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• 2013

This paper proposes a method of using depth information to detect the hand region in real-time based on the cascade method. In order to ensure stable and speedy detection of the hand region even under conditions of lighting changes in the test environment, this study uses only features based on depth information, and proposes a method of detecting the hand region by means of a classifier that uses boosting and cascading methods. First, in order to extract features using only depth information, we calculate the difference between the depth value at the center of the input image and the average of depth value within the segmented block, and to ensure that hand regions of all sizes will be detected, we use the central depth value and the second order linear model to predict the size of the hand region. The cascade method is applied to implement training and recognition by extracting features from the hand region. The classifier proposed in this paper maintains accuracy and enhances speed by composing each stage into a single weak classifier and obtaining the threshold value that satisfies the detection rate while exhibiting the lowest error rate to perform over-fitting training. The trained classifier is used to classify the hand region, and detects the final hand region in the final merger stage. Lastly, to verify performance, we perform quantitative and qualitative comparative analyses with various conventional AdaBoost algorithms to confirm the efficiency of the hand region detection algorithm proposed in this paper.

• Korean Journal of Remote Sensing
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• v.20 no.2
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• pp.65-76
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• 2004

This study aims to estimate daily maximum air temperature estimated using satellite-derived surface temperature and Elevation Derivative Database (EDD). The analysis is focused on the establishment of a semi-empirical estimation technique of daily maximum air temperature through the multiple regression analysis. This tests the contribution of EDD in the air temperature estimation when it is added into regression model as an independent variable. The better correlation is shown with the EDD data as compared with the correlation without this data set. In order to provide a progressive estimation technique, we propose and compare three approaches: 1) seasonal estimation non-considering landcover, 2) seasonal estimation considering landcover, and 3) estimation according to landcover type and non-considering season. The last method shows the best fit with the root-mean-square error between 0.56$^{\circ}C$ and 3.14$^{\circ}C$. A cross-validation procedure is performed for third method to valid the estimated values for two major landcover types (cropland and forest). For both landcover types, the validation results show reasonable agreement with estimation results. Therefore it is considered that the estimation technique proposed may be applicable to most parts of South Korea.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.555-561
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• 2020

In this study, the applicability of Hunt's analytical solution for a two-layered leaky aquifer system, which was developed to estimate stream depletion due to the groundwater pumping of the upper shallow aquifer, was evaluated. The 5-year averaged stream depletions were estimated using Hunt's analytical solution for various combinations of hydraulic characteristic values such as transmissivity, storage coefficient of the two aquifers, interlayer leakage coefficient, stream-well distance, hydraulic conductivity of the streambed, and stream width. Through comparison with the numerical solution accurately simulated with a MODFLOW groundwater flow model, the analytical solution derived by regarding the stream width as a point was evaluated. It was found that the error in the stream depletion calculated by the analytical solution can be reduced to less than 0.05 when the stream-well distance is greater than the stream width or when the stream depletion factor (SDF) is more than about 3,000 days. In addition, when the streambed hydraulic conductivity is less than 1 m/d, the hydraulic diffusion coefficient of the lower aquifer layer is less than 100 ㎡/d, the hydraulic diffusion coefficient ratio of the upper and lower aquifer layers is 5 or more, and the leakage coefficient between the layers is less than 0.0004 m/d, the overall analytical solutions were overestimated compared with the numerical solutions.

• Journal of the Korean Geotechnical Society
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• v.38 no.3
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.1-13
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• 2024

The southwestern part of the East Sea is known to have a high primary productivity compared to those in the northern and eastern parts, which is attributed to nutrients supplies either by Tsushima Warm Current or by coastal upwelling. However, research on the biological pump in this area is limited. We developed machine learning models to estimate net community production (NCP), a measure of biological pump, with high spatial and time scales of 4 km and 8 days, respectively. The models were fed with the input parameters of sea surface temperature, chlorophyll-a, mixed layer depths, and photosynthetically active radiation and trained with observed NCP derived from high resolution measurements of surface O₂/Ar. The root mean square error between the predicted values by the best performing machine model and the observed NCP was 6 mmol O₂ m^-2 d^-1, corresponding to 15% of the average of observed NCP. The NCP in the central part of the Ulleung Basin was highest in March at 49 mmol O₂ m^-2 d^-1 and lowest in June and July at 18 mmol O₂ m^-2 d^-1. These seasonal variations were similar to the vertical nitrate flux based on the ³He gas exchange rate and to the particulate organic carbon flux estimated by the ²³⁴Th disequilibrium method. To expand this method, which produces NCP estimate for spring and summer, to autumn and winter, it is necessary to devise a way to correct bias in NCP by the entrainment of subsurface waters during the seasons.