Journal of the Institute of Convergence Signal Processing
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v.8
no.2
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pp.98-105
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2007
In this paper, we propose the method and system which determines the condition for safe and unsafe lane changing. To determine the condition, first, the system sets up the Region of Interest(ROI) on the neighboring lane. Second, a dangerous vehicle is extracted during the line changing. Third, the condition is determined to wm or not by calculating the moving direction, relative distance md relative velocity. To set up the ROI, the only one side lane is detected and the interested region is expanded. Using the coordinate transformation method, the accuracy of the ROI raised. To correctly extract the vehicle on the neighboring lane, the Adaptive Background Update method and Image Segmentation method which uses the feature of the travelling road are used. The object which is extracted by the dangerous vehicle is calculated the relative distance, the relative velocity and the moving average. And then in order to ring, the direction of the vehicle and the condition for safe and unsafe is determined. As minimizes the interested region and uses the feature of the travelling road, the computational quantity is reduced and the accuracy is raised and a stable result on a travelling road images which demands a high speed calculation is showed.
Methods for the seismic demands evaluation of structures require iterative procedures. Many studies dealt with the development of different inelastic spectra with the aim to simplify the evaluation of inelastic deformations and performance of structures. Recently, the concept of inelastic spectra has been adopted in the global scheme of the Performance-Based Seismic Design (PBSD) through Capacity-Spectrum Method (CSM). For instance, the Modal Pushover Analysis (MPA) has been proved to provide accurate results for inelastic buildings to a similar degree of accuracy than the Response Spectrum Analysis (RSA) in estimating peak response for elastic buildings. In this paper, a simplified nonlinear procedure for evaluation of the seismic demand of structures is proposed with its applicability to multi-degree-of-freedom (MDOF) systems. The basic concept is to write the equation of motion of (MDOF) system into series of normal modes based on an inelastic modal decomposition in terms of ductility factor. The accuracy of the proposed procedure is verified against the Nonlinear Time History Analysis (NL-THA) results and Uncoupled Modal Response History Analysis (UMRHA) of a 9-story steel building subjected to El-Centro 1940 (N/S) as a first application. The comparison shows that the new theoretical approach is capable to provide accurate peak response with those obtained when using the NL-THA analysis. After that, a simplified nonlinear spectral analysis is proposed and illustrated by examples in order to describe inelastic response spectra and to relate it to the capacity curve (Pushover curve) by a new parameter of control, called normalized yield strength coefficient (${\eta}$). In the second application, the proposed procedure is verified against the NL-THA analysis results of two buildings for 80 selected real ground motions.
Journal of The Geomorphological Association of Korea
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v.24
no.3
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pp.105-118
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2017
The debris slope landforms which are existent in Korean mountains is generally on the steep slopes and mostly covered by vegetation, it is difficult to investigate the landform. Therefore a scientific method is required to come up with an effective field investigation plan. For this purpose, the use of Remote Sensing and GIS technologies for a spatial analysis is essential. This study has extracted the potential area of debrisslope landform formation using Fuzzy set and Bayesian Predictive Discriminate Model as mathematical data integration methods. The first step was to obtain information about debris locations and their related factors. This information was verified through field investigation and then used to build a database. In the second step, the map that zoning the study area based on the degree of debris formation possibility was generated using two modeling methods, and then cross validation technique was applied. In order to quantitatively analyze the accuracy of two modeling methods, the calculated potential rate of debrisformation within the study area was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). As a result, the prediction accuracy of Fuzzy set model wes 83.1% and Bayesian Predictive Discriminate Model wes 84.9%. It showed that two models are accurate and reliable and can contribute to efficient field investigation and debris landform management.
Proceedings of the Korea Water Resources Association Conference
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2016.05a
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pp.259-259
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2016
This study examined Artificial Neurons Networks model (ANNs) for forecast flash discharge at Southern part of Thailand by using rainfall data and discharge data. The Sungai Kolok River Basin has meant the border crossing between Thailand and Malaysia which watershed drains an area lies in Thailand 691.88 square kilometer from over all 2,175 square kilometer. The river originates in mountainous area of Waeng district then flow through Gulf of Thailand at Narathiwat Province, which the river length is approximately 103 kilometers. Almost every year, flooding seems to have increased in frequency and magnitude which is highly non-linear and complicated phenomena. The purpose of this study is to forecast runoff on Sungai Kolok at X.119A gauge station (Sungai Kolok district, Narathiwat province) for 3 days in advance by using Artificial Neural Networks model (ANNs). 3 daily rainfall stations and 2 daily runoff station have been measured by Royal Irrigation Department and Meteorological Department during flood period 2000-2014 were used as input data. In order to check an accuracy of forecasting, forecasted runoff were compared with observed data by pursuing Coefficient of determination ($R^2$). The result of the first day gets the highest accuracy and then decreased in day 2 and day 3, consequently. $R^2$values for first day, second day and third day of runoff forecasting is 0.71, 0.62 and 0.49 respectively. The results confirmed that the ANNs model can be used when the range of collected dataset is short and real-time operated. In conclusion, the ANNs model is suitable to runoff forecasting during flood incident of Sungai Kolok river because it is straightforward model and require with only a few parameters for simulation.
Purpose: This paper compares practical first aid training and theoretical first aid training in elementary schools. Methods: Research subjects were randomly selected and sorted into experimental and control groups. The former is one class (28 students) of the fifth grade students, and the latter is another class (30 students). In order to verify the effect of first aid training, we conducted theoretical as well as practical first-aid instruction about foreign body airway obstruction to the experimental group, but conducted only theoretical instruction with the control group. Data were analyzed by the ${\chi}^2$-test and t-test, one-way using the SPSS / win 12.0 program. The results were as follows (p=.05). Results: The first hypothesis was that the knowledge of an experimental group would be better than that of a control group. The analysis showed a significant difference (p=.000) between the two groups, supporting this hypothesis. The second hypothesis was that the experimental group would be more accurate than the control group. There was no because of (p=.000) between the two groups on this measure. The third hypothesis, that the two groups would vary over time on the measure of accuracy, was supported by the following observations: the experimental results were accumulated before, two days after and two weeks after the training (experimental group, p=.000, and control group, p=.000). This supports the third hypothesis that the technical performance accuracy levels of complete respiratory obstruction first aid vary over time. Conclusion: First aid training has to include practical education as well as theoretical education in the future, as part of a school's health education for elementary students. Health education classrooms should be prepared to teach first-aid theory and be supplied with equipment for practical exercises. Schools, communities, and private organizations need to carry out the practical education component periodically.
Journal of The Korean Society of Integrative Medicine
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v.10
no.1
/
pp.149-155
/
2022
Purpose : This study investigated the effects of wearing a mask and different mask filters on the respiratory function of stroke patients. Methods : A total of 15 stroke patients were selected according to the inclusion and exclusion criteria. The respiratory functions were compared between participants with and without masks and among respiratory functions with three different mask filters. The order of using masks was non-wearing masks, Dental masks, KF80 masks, and KF94 masks; the difference in respiratory volumes among these conditions were measured. For accuracy of the measurement, sufficient education on the respiratory measurement method was provided to the researcher, and the heart rate of the participants was estimated to confirm their stability before the measurements. To ensure accuracy, the subjects were educated on the researchers' respiratory measurement methods. Each measurement was followed by 10 min breathing stability before replacing the next mask. Results : The results of this study showed that the difference in respiratory functions, including forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), and maximal voluntary ventilation (MVV), in stroke patients was statistically significant among different masks (p<.05). Afterwards, the values of FVC, FEV1, and MVV in stroke patients wearing masks were significantly lower than those of the non-masked control group (p<.05). The difference in respiratory functions with different mask filters showed no statistical significance (p<.05). Conclusion : This study showed that participants wearing any of the masks presented a lower respiratory function than that of those without using masks; additionally, no difference in respiratory functions was observed with differences in mask filters. Therefore, wearing a mask for a prolonged period is confirmed to affect breathing in stroke patients with weak respiratory function.
This study presents the plans to derive quality items for develop the data quality standard for ensuring the quality of 3D building geospatial data in NDT(National Digital Twin). This paper is organized as follows. The first section briefly examines various factors that impact the quality of 3D geospatial data, and proposes the role and necessity of the data quality standard as a means of addressing the data errors properly and also meeting the minimum requirements of stakeholders. The second section analyzes the relationship between the standards - building data model for NDT and ISO 19157: Geospatial data quality - in order to consider directly relevant standards. Finally, we suggest three plans on developing NDT data quality standard: (1) the scope for evaluating data quality, (2) additional quality elements(geometric integrity, geometric fidelity, positional accuracy and semantic classification accuracy), and (3) NDT data quality items model based on ISO 19157. The plans reveled through the study would contribute to establish a way for the national standard on NDT data quality as well as the other standards associated with NDT over the coming years.
In this paper, we focused on training to create and optimize a basic data prediction model. And we proposed a gradient descent training method of machine learning that is widely used to optimize data prediction models. It visually shows the entire operation process of gradient descent used in the process of optimizing parameter values required for data prediction models by applying the differential method and teaches the effective use of mathematical differentiation in machine learning. In order to visually explain the entire operation process of gradient descent, we implement gradient descent SW in a spreadsheet. In this paper, first, a two-variable gradient descent training method is presented, and the accuracy of the two-variable data prediction model is verified by comparison with the error least squares method. Second, a three-variable gradient descent training method is presented and the accuracy of a three-variable data prediction model is verified. Afterwards, the direction of the optimization practice for gradient descent was presented, and the educational effect of the proposed gradient descent method was analyzed through the results of satisfaction with education for non-majors.
This paper presents an efficient method for automatically detecting objects in a given image. The GHT is a robust template matching algorithm for automatic object detection in order to find objects of various shapes. Many different templates are applied by the GHT in order to find objects of various shapes and size. Every boundary detected by the GHT scan be used as an initial outline for more precise contour-finding techniques. The main weakness of the GHT is the excessive time and memory requirements. In order to overcome this drawback, the proposed algorithm uses a multiresolution search by scaling down the original image to half-sized and quarter-sized images. Using the information from the first iterative GHT on a quarter-sized image, the range of nuclear sizes is determined to limit the parameter space of the half-sized image. After the second iterative GHT on the half-sized image, nuclei are detected by the fine search and segmented with edge information which helps determine the exact boundary. The experimental results show that this method gives reduction in computation time and memory usage without loss of accuracy.
In order to simulate a free surface flow in a trench channel, a three-dimensional incompressible unsteady Reynolds-averaged Navier-Stokes (RANS) equations are closed with the ${\kappa}-{\epsilon}$ model. The artificial compressibility (AC) method is used. Because the pressure fields can be coupled directly with the velocity fields, the incompressible Navier-Stokes (INS) equations can be solved for the unknown variables such as velocity components and pressure. The governing equations are discretized in a conservation form using a second order accurate finite volume method on non-staggered grids. In order to prevent the oscillatory behavior of computed solutions known as odd-even decoupling, an artificial dissipation using the flux-difference splitting upwind scheme is applied. To enhance the efficiency and robustness of the numerical algorithm, the implicit method of the Beam and Warming method is employed. The treatment of the free surface, so-called interface-tracking method, is proposed using the free surface evolution equation and the kinematic free surface boundary conditions at the free surface instead of the dynamic free surface boundary condition. AC method in this paper can be applied only to the hydrodynamic pressure using the decomposition into hydrostatic pressure and hydrodynamic pressure components. In this study, the boundary-fitted grids are used and advanced each time the free surface moved. The accuracy of our RANS solver is compared with the laboratory experimental and numerical data for a fully turbulent shallow-water trench flow. The algorithm yields practically identical velocity profiles that are in good overall agreement with the laboratory experimental measurement for the turbulent flow.
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