• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.257-265
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• 2023

The purpose of this study was to vaccinate every year according to the general characteristics of COVID-19, whether to vaccinate every year according to the vaccination experience, whether to vaccinate every year according to knowledge/attitude about vaccination, and negative responses to the vaccinate every year In order to understand the factors affecting the vaccination physician every year by identifying the factors of Statistical analysis is based on general characteristics, variables based on vaccination experience, and knowledge/attitudes related to vaccination. The doctor calculates the frequency and percentage, A square test (-test) was performed, and if the chi-square test was significant but the expected frequency was less than 5 for 25% or more, a ratio difference test was performed with Fisher's exact test. Through multiple logistic regression analysis using variables that were significant in simple analysis, a predictive model for future vaccination and the effect size of each independent variable were estimated. As statistical analysis software, SAS 9.4 (SAS Institute Inc., Cary, NC, USA) was used, and because the sample size was not large, the significance level was set at 10%, and when the p-value was less than 0.10, it was interpreted as statistically significant. In the simple logistic regression analysis, the reason why they answered that they would not be vaccinated every year was that they answered 'to prevent infection of family and hospital guests' rather than 'to prevent my infection' as the reason for the vaccination. It was 11.0 times higher and 3.67 times higher in the case of 'for the formation of collective immunity of the local community and the country'. The adverse reactions experienced after the 1st and 2nd vaccination were 8.42 times higher in those who did not experience pain at the injection site than those who did not, 4.00 times higher in those who experienced swelling or redness, and 5.69 times higher in those who experienced joint pain. There was a 5.57 times higher rate of absenteeism annually than those who did not. In addition, the more anxious they felt about vaccination, the more likely they were to not get the vaccine every year by 2.94 times.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.5
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• pp.335-347
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• 2013

In February 2008, high storm waves due to a developed atmospheric low pressure system propagating from the west off Hokkaido, Japan, to the south and southwest throughout the East Sea (ES) caused extensive damages along the central coast of Japan and along the east coast of Korea. This study consists of two parts. In the first part, we estimate extreme storm wave characteristics in the Toyama Bay where heavy coastal damages occurred, using a non-hydrostatic meteorological model and a spectral wave model by considering the extreme conditions for two factors for wind wave growth, such as wind intensity and duration. The estimated extreme significant wave height and corresponding wave period were 6.78 m and 18.28 sec, respectively, at the Fushiki Toyama. In the second part, we perform numerical experiments on wave-structure interaction in the Fushiki Port, Toyama Bay, where the long North-Breakwater was heavily damaged by the storm waves in February 2008. The experiments are conducted using a non-linear shallow-water equation model with adaptive mesh refinement (AMR) and wet-dry scheme. The estimated extreme storm waves of 6.78 m and 18.28 sec are used for incident wave profile. The results show that the Fushiki Port would be overtopped and flooded by extreme storm waves if the North-Breakwater does not function properly after being damaged. Also the storm waves would overtop seawalls and sidewalls of the Manyou Pier behind the North-Breakwater. The results also depict that refined meshes by AMR method with wet-dry scheme applied capture the coastline and coastal structure well while keeping the computational load efficiently.

• Journal of The Korean Association For Science Education
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• v.38 no.3
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• pp.305-317
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• 2018

In this study, we investigated the characteristics of participant students' modeling with the blackbox simulation program and epistemic criteria. For this research, we developed a blackbox simulation program, which is an ill-structured problem situation reflecting the scientific practice. This simulation program is applied in the activities. 23 groups, 89 second year students of an education college participated in this activity. They visualized, modeled, modified, and evaluated their thoughts on internal structure in the blackbox. All of students' activities were recorded and analyzed. As a result, the students' models in blackbox activities were categorized into four types considering their form and function. Model evaluation occurred in group model selection. Epistemic criteria such as empirical coherence, comprehensiveness, analogy, simplicity, and implementation were adapted in model evaluation. The educational implications discussed above are as follows: First, the blackbox simulation activities in which the students participated in this study have educational implications in that they provide a context in which the nature of scientific practice can be experienced explicitly and implicitly by constructing and testing models. Second, from the beginning of the activity, epistemic criteria such as empirical coherence, comprehensiveness, analogy, simplicity, and implementation were not strictly adapted and dynamically flexibly adapted according to the context. Third, the study of epistemic criteria in various contexts as well as in the context of this study will broaden the horizon of understanding the nature of scientific practice. Simulation activity, which is the context of this study, can lead to research related to computational thinking that will be more important in future society. We expect to be able to lead more discussions by furthering this study by elaborating and systematizing its context and method.

• Journal of Internet Computing and Services
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• v.17 no.4
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• pp.35-42
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• 2016

Recently many researches have been focused on the use of the markerless augmented reality system using face, foot, and hand of user's body to alleviate many disadvantages of the marker based augmented reality system. In addition, most existing augmented reality systems have been utilized rigid objects since they just desire to insert and to basic interaction with virtual object in the augmented reality system. In this paper, unlike restricted marker based augmented reality system with rigid objects that is based in display, we designed and implemented the markerless augmented reality system using deformable objects to apply various fields for interactive situations with a user. Generally, deformable objects can be implemented with mass-spring modeling and the finite element modeling. Mass-spring model can provide a real time simulation and finite element model can achieve more accurate simulation result in physical and mathematical view. In this paper, the proposed markerless augmented reality system utilize the mass-spring model using tetraheadron structure to provide real-time simulation result. To provide plausible simulated interaction result with deformable objects, the proposed method detects and tracks users hand with Kinect SDK and calculates the external force which is applied to the object on hand based on the position change of hand. Based on these force, 4th order Runge-Kutta Integration is applied to compute the next position of the deformable object. In addition, to prevent the generation of excessive external force by hand movement that can provide the natural behavior of deformable object, we set up the threshold value and applied this value when the hand movement is over this threshold. Each experimental test has been repeated 5 times and we analyzed the experimental result based on the computational cost of simulation. We believe that the proposed markerless augmented reality system with deformable objects can overcome the weakness of traditional marker based augmented reality system with rigid object that are not suitable to apply to other various fields including healthcare and education area.

• 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 The Korean Society of Agricultural Engineers
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• v.61 no.6
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• pp.111-121
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• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• Journal of Korean Society of Steel Construction
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• v.16 no.2 s.69
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• pp.285-293
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• 2004

As a special infrastructure, it is important that the suspension bridges which were designed by using the cable are carefully maintained and safely inspected after their construction, more than what is done in other cases of bridge structures. However, the structural analysis for their design and maintenance has considered only the simplified geometric shape of the structure. Particularly, it is not easy to make the modeling analyze the bridge structure including detailed steel deck plates. In this paper, we evaluated the structural behaviors and performances of the completed earth-anchored suspension bridge that was in a completed state through both the tension of hanger member and their computational analysis. We considered the frame system and the detailed steel deck plates that were especially added into the modeling to take more precision analysis about it. We also applied hanger tensions converted by the natural frequency and the natural frequency of the bridge when in normal vibration. Results of the vehicle loading test were used in the analysis. We compared the results by using our modeling with the result of the loading test and the hanger tension. Our prediction on the behavior of the structure emulates the behavior of the real structure. In applying the data measured by the typhoon "Maemi" which arrived in-land last year, we confirmed our analysis model for the possibility of applying effectively into the preliminary design and maintenance plan.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.30-39
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• 2012

In this paper, a safe driving assistance system is proposed by detecting the status of driver's doze based on face and eye detection. By the level of the fatigue, safe driving system alarms or set the seatbelt on vibration. To reduce the effect of backward light and too strong solar light which cause a decrease of face and eye detection rate and false fatigue detection, post processing techniques like image equalization are used. Haar transform and PCA are used for face detection. By using the statistic of the face and eye structural ratio of normal Koreans, we can reduce the eye candidate area in the face, which results in reduction of the computational load. We also propose a new eye status detection algorithm based on Hough transform and eye width-height ratio, which are used to detect eye's blinking status which decides doze level by measuring the blinking period. The system alarms and operates seatbelt on vibration through controller area network(CAN) when the driver's doze level is detected. In this paper, four algorithms are implemented and proposed algorithm is made based on the probability model and we achieves 84.88% of correct detection rate through indoor and in-car environment experiments. And also we achieves 69.81% of detection rate which is better result than that of other algorithms using IR camera.

• The Journal of Korean Association of Computer Education
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• v.16 no.2
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• pp.9-18
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• 2013

In secondary education, learning a computer science subject has the purpose to improve creative problem solving ability of students by learning computational thinking and principles. In particular, learning algorithm has been emphasized for this purpose. There are studies that learning algorithm has the effect of creative problem solving based on the leading studies that learning algorithm has the effect of problem solving. However, relatively the importance of the learning algorithm can weaken, because these studies depend on creative problem solving model or special contents for creativity. So this study proves that learning algorithm has the effect of creative problem solving in the view that common problem solving and creative problem solving have the same process. For this, analogical reasoning was selected among common thinking skills and divide-and-conquer algorithm was selected among abstractive principles for analogical reasoning in sorting algorithm. The frequency which solves the search problem by using the binary search algorithm was higher than the control group learning only sequence of sorting algorithm about the experimental group learning divide-and-conquer algorithm. This result means that learning algorithm including abstractive principle like divide-and-conquer has the effect of creative problem solving by analogical reasoning.

• KIEAE Journal
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• v.8 no.5
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• pp.49-54
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• 2008

The experimental of temperature, humidity and velocity was taken from the underground pit which utilized the system of ground heat source quite similar to the cool-pit system. Also, through CFD analysis, one could review the effectiveness of analysis of future alternatives. Furthermore, the temperature range of mock up cool-pit system was analyzed by inputting the weather data of annual average soil temperature provided by KMA(Korea Meteorological Administration) into the fluid simulation of anticipated heat distribution. Firstly, the difference between the temperature of air exhaust of the pit or the temperature of air supply of the compressor room and the experimental data for the month of May from the CFD analysis came out to be $0.6^{\circ}C$ and $0.9^{\circ}C$ respectively with tolerance of 3.1% and 4.7%. Secondly, the difference between the temperature of air exhaust of the Pit or the temperature of air supply of the compressor room and the experimental data for the month of July from the CFD analysis came out to be $0.8^{\circ}C$ and $1.1^{\circ}C$ respectively with tolerance of 3.3% and 4.5%. Thirdly, for the month of May, the difference between the experimental data taken for the air exhaust of the Pit or the air supply of the compressor room and soil temperature provided by KMA for monthly and yearly average temperature of Jeonju region came out be $1.9^{\circ}C$ and $1.8^{\circ}C$ respectively with tolerance of 10.7% and 9.8%. Fourthly, for the month of July, the difference between the experimental data taken for the air exhaust of the Pit or the air supply of the compressor room and soil temperature provided by KMA for monthly and yearly average temperature of Jeonju region came out be $1.1^{\circ}C$ and $1.4^{\circ}C$ respectively with tolerance of 4.5% and 5.8%. The result of above experiments allowed us to establish CFD model set up as a verification tool that is based on experimental data collected within the Pit area. Also, one could confirm the possibility to apply weather data of soil temperature provided by KMA in order to anticipate proper value for CFD analysis.