• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.655-660
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• 2016

Smoking is accountable for the fatality of a substantial number of persons and increases the likelihood of cancer and cardiovascular diseases. Although data have shown high prevalence rates of cigarette smoking in Saudi Arabia, relatively little is known about the broader scope. The objectives of this study were to investigate socio-demographic factors, patterns of use and cessation behavior associated with smoking in Saudi Arabia (KSA). The study utilized a cross-sectional, multi-step design of sampling. Residents (N=1,497; aged 15 years and older) were recruited from seven administrative areas in Southwest Saudi Arabia. A pretested questionnaire was utilized to obtain data on participant cigarette smoking, including their daily use, age, education, income, marital status and employment status. The current study is the first of its kind to gather data cessation behavior of Saudi subjects. With the exception of 1.5% females, all the respondents were male. The majority of the respondents were married, had a university level of education, were employed, and were younger than 34 years old. The same trends were also observed among smokers' samples. The current prevalence of cigarette smoking was 49.2% and 65.7% of smokers had smoking at less than 18 years of age. The mean daily use amongst smokers was 7.98 cigarettes (SD=4.587). More than 50% of the study sample had tried at least once to quit smoking. However, 42% of the smokers participating had never. On the other hand, about 25% of the respondents were willing to consider quitting smoking in the future. Modeling of cigarette smoking suggested that the most significant independent predictors of smoking behavior were geographic area, gender, marital status, education, job and age. Considerable variation in smoking prevalence was noted related with participant sociodemographics. Findings recommend the necessity for control and intervention programs in Saudi community.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.219-229
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• 2017

A watershed-river linked modeling system was developed to forecast the water quality, particularly weekly changes in chlorophyll-a concentration, of the Yeongsan River, Korea. Hydrological Simulation Program-Fortran (HSPF) and Environmental Fluid Dynamics Code (EFDC) were adopted as the basic model framework. In this study, the EFDC model was modified to effectively simulate the operational condition and flow of multi-functional weirs constructed in the main channel of rivers. The model was tested against hydrologic, water quality and algal data collected at the right upstream sites of two weirs in 2014. The mean absolute errors (MAEs) of the model calibration on the annual variations of river stage, TN, TP, and algal concentration are 0.03 ~ 0.10 m, 0.65 ~ 0.67 mg/L, 0.03 ~ 0.04 mg/L, and $9.7{\sim}10.8mg/m^3$, respectively. On the other hand, the MAE values of forecasting results for chlorophyll-a level at the same sites in 2015 range from 18.7 to $22.4mg/m^3$, which are higher than those of model calibration. The increased errors in forecasting are mainly attributed to the higher uncertainties of weather forecasting data compared to the observed data used in model calibration.

• Journal of the Korean earth science society
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• v.34 no.1
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• pp.51-58
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• 2013

An appropriate determination of time step is one of the important problems in atmospheric modeling. In this study, we investigate the sensitivity of numerical solutions to time step in a nonlinear atmospheric model. For this purpose, a simple nondimensional dynamical model is employed, and numerical experiments are performed with various time steps and nonlinearity factors. Results show that numerical solutions are not sensitive to time step when the nonlinearity factor is not influentially large and truncation error is negligible. On the other hand, when the nonlinearity factor is large (i.e., in a highly nonlinear regime), numerical solutions are found to be sensitive to time step. In this situation, smaller time step increases the intensity of the spatial filter, which makes small-scale phenomena weaken. This conflicts with the fact that smaller time step generally results in more accurate numerical solutions owing to reduced truncation error. This conflict is inevitable because the spatial filter is necessary to stabilize the numerical solutions of the nonlinear model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.8 no.1
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• pp.53-63
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• 2006

The objective of this study is to analyze the smoke movement and the smoke extraction efficiency using by the partial extraction system for case of tunnel fire. Based on Froude modeling and isothermal model, the 1/20 scaled model tunnel (12m long) was constructed. In the case of the upper critical velocity in the main tunnel, the smoke extraction efficiency shows almost same between group damper and distributed damper. Finally, if the fire occurs on a traffic Jam in a tunnel, it is proposed that the open dampers in partial gallery extract smoke from the main tunnel without jet fan operation. Then, after the passengers have escaped the tunnel, the jet fans work on. On the other hand, If the traffic is uncongested in the tunnel, the jet fans (smoke control system) and partial extraction system (smoke exhaust system) are operated at once in tunnel fire.

• Ocean and Polar Research
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• v.38 no.2
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• pp.149-159
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• 2016

The statistical measures of the coastal environmental data are used in a variety of statistical inferences, hypothesis tests, and data-driven modeling. If the measures are biased, then the statistical estimations and models may also be biased and this potential for bias is great when data contain some outliers defined as extraordinary large or small data values. This study aims to suggest more robust statistical measures as alternatives to more commonly used measures and to assess the performance these robust measures through a quantitative evaluation of more typical measures, such as in terms of locations, spreads, and shapes, with regard to environmental monitoring data in the Busan coastal sea. The detection of outliers within the data was carried out on the basis of Rosner's test. About 5-10% of the nutrient data were found to contain outliers based on Rosner's test. After removal (zero-weighting) of the outliers in the data sets, the relative change ratios of the mean and standard deviation between before and after outlier-removal conditions revealed the figures 13 and 33%, respectively. The variation magnitudes of skewness and kurtosis are 1.36 and 8.11 in a decreasing trend, respectively. On the other hand, the change ratios for more robust measures regarding the mean and standard deviation are 3.7-10.5%, and the variation magnitudes of robust skewness and kurtosis are about only 2-4% of the magnitude of the non-robust measures. The robust measures can be regarded as outlier-resistant statistical measures based on the relatively small changes in the scenarios before and after outlier removal conditions.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.963-978
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• 2020

Earthquakes can induce a large number of landslides and cause very serious property damage and human casualties. There are two issues in study on earthquake-induced landslides: (1) slope stability analysis under seismic loading and (2) debris flow run-out analysis. This study aims to review technical studies related to the development and application of earthquake-induced landslide models (seismic slope stability analysis). Moreover, a pilot application of a physics-based slope stability model to Mt. Umyeon, in Seoul, with several earthquake scenarios was conducted to test regional scale seismic landslide mapping. The earthquake-induced landslide simulation model can be categorized into 1) Pseudo-static model, 2) Newmark's dynamic displacement model and 3) stress-strain model. The Pseudo-static model is preferred for producing seismic landslide hazard maps because it is impossible to verify the dynamic model-based simulation results due to lack of earthquake-induced landslide inventory in Korea. Earthquake scenario-based simulation results show that given dry conditions, unstable slopes begin to occur in parts of upper areas due to the 50-year earthquake magnitude; most of the study area becomes unstable when the earthquake frequency is 200 years. On the other hand, when the soil is in a wet state due to heavy rainfall, many areas are unstable even if no earthquake occurs, and when rainfall and 50-year earthquakes occur simultaneously, most areas appear unstable, as in simulation results based on 100-year earthquakes in dry condition.

• Smart Structures and Systems
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• v.28 no.6
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• pp.745-760
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• 2021

Dynamic buckling of structure is one of the failure modes that needs to be considered since it may result in catastrophic failure of the structure in a short period of time. For a thin fiber-reinforced polymer (FRP) plate under compression, buckling is an inherent hazard which will be intensified by the existence of defects like holes, cracks, and delamination. On the other hand, the growth of the delamination is another prime concern for thin FRP plates. In the current paper, reinforcing the plates against buckling is realized by using SMA wires in the form of stitches. A numerical framework is proposed to simulate the dynamic instability emphasizing the effect of the SMA stitches in suppressing delamination growth. The suggested algorithm is more accurate than the other methods when considering the transformation point of the SMA wires and the modeling of the cohesive zone using simple and yet reliable technique. The computational design of the method by producing the line by line orders leads to a simple algorithm for simulating the super-elastic behavior. The Lagoudas constitutive model of the SMA material is implemented in the form of user material subroutines (VUMAT). The normal bilinear spring model is used to reproduce the cohesive zone behavior. The nonlinear finite element formulation is programmed into FORTRAN using the Newmark-beta numerical time-integration approach. The obtained results are compared with the results obtained by the finite element method using ABAQUS/Explicit solver. The obtained results by the proposed algorithm and those by ABAQUS are in good agreement.

• Journal of Information Technology Services
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• v.22 no.5
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• pp.71-86
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• 2023

Recently, various geographic information systems have been used based on spatial information of geographic information systems. Accordingly, it is essential to produce a large-scale map as a small-scale map for various uses of spatial information. However, maps currently being produced have inconsistencies between data due to production timing and limitations in expression, and productivity efficiency is greatly reduced due to errors in products or overlapping processes. In order to improve this, various efforts are being made, such as publishing research and reports for automating domestic mapping, but because there is no specific result, it relies on editors to make maps. This is mainly done by hand, so the time required for mapping is excessive, and quality control for each producer is different. In order to solve these problems, technology that can be automatically produced through computer programs is needed. Research has been conducted to apply the rule base to geometric generalization. The algorithm tolerance setting applied to rule-based modeling is a factor that greatly affects the result, and the level of the result changes accordingly. In this paper, we tried to study the effectiveness of mapping according to tolerance setting. To this end, the utility was verified by comparing it with a manually produced map. In addition, the original data and reduction rate were analyzed by applying generalization algorithms and tolerance values. Although there are some differences by region, it was confirmed that the complexity decreased on average. Through this, it is expected to contribute to the use of spatial information-based services by improving tolerances suitable for small-scale mapping regulations in order to secure spatial information data that guarantees consistency and accuracy.

• Journal of Korean Neurosurgical Society
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• v.67 no.2
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• pp.166-176
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• 2024

Objective : Three-dimensional (3D) printing in vascular surgery is trending and is useful for the visualisation of intracranial aneurysms for both surgeons and trainees. The 3D models give the surgeon time to practice before hand and plan the surgery accordingly. The aim of this study was to examine the effect of preoperative planning with 3D printing models of aneurysms in terms of surgical time and patient outcomes. Methods : Forty patients were prospectively enrolled in this study and divided into two groups : groups I and II. In group I, only the angiograms were studied before surgery. Solid 3D modelling was performed only for group II before the operation and was studied accordingly. All surgeries were performed by the same senior vascular neurosurgeon. Demographic data, surgical data, both preoperative and postoperative modified Rankin scale (mRS) scores, and Glasgow outcome scores (GOS) were evaluated. Results : The average time of surgery was shorter in group II, and the difference was statistically significant between the two groups (p<0.001). However, no major differences were found for the GOS, hospitalisation time, or mRS. Conclusion : This study is the first prospective study of the utility of 3D aneurysm models. We show that 3D models are useful in surgery preparation. In the near future, these models will be used widely to educate trainees and pre-plan surgical options for senior surgeons.