• Journal of The Korean Association For Science Education
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• v.43 no.2
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• pp.87-98
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• 2023

In this study, we investigated the change in science core competency perception of high school students and the reason for change when science inquiry classes were conducted using eight 'skills' of the 2015 revised science curriculum. Fifteen first-year high school students in Jeollanam-do participated in the science inquiry class of this study, and the class was conducted for 20 hours (5 hours a day for four days). The inquiry activities used in the class consisted of four activity stages (research problems, research methods, research results, and conclusions) and each stage was constructed to include at least one 'skill (Problem Recognition, Model Development and Use, Inquiry Design and Performance, Data Collection, Analysis and Interpretation, Mathematical Thinking and Computer Application, Conclusion and Evaluation, Evidence-based Discussion and Demonstration, and Communication)'. As a result of the study, students' perception of the five science core competencies increased statistically significantly at the significance level of 0.01 through inquiry classes and more than 93% of students recognized that their science core competencies improved through the classes. However, since the class of this study was conducted for a small number of students, it is difficult to generalize the effect of the class, and so it is necessary to conduct a quantitative study for many students.

• Journal of Environmental Impact Assessment
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• v.33 no.2
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• pp.64-73
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• 2024

As the seriousness of habitat destruction caused by development projects emerges, the importance of environmental impact assessment (EIA) is increasing to preserve biodiversity. In previous studies, research is being conducted to quantitatively evaluate the biodiversity impact of development factors and surrounding environmental factors on the landscape scale, but research on the factors affecting the reduction of biodiversity based on development projects is insufficient. This study examined whether independent variables (size of development project, type of the development, DEM, ecosystem and nature map, distance from the green land, distance from the protected area), which have been proven to effect biodiversity through the previous researches, have a significant effect on the change of richness index (RI) through multi-class logistic regression analysis, T-test, and analysis of the development type. As a result, only the size of development project and the first richness index in EIA showed p-value less than 0.05. And it was confirmed that the reduction in biodiversity was significantly changed in the following construction types: installation of sports facilities, energy development, and development of industrial location and industrial complex. Since the results of this study confirmed that the impact of the variables may be inconsistent depending on the analysis scale, additional study of necessary indicators at the development project is needed to analyze biodiversity changes in EIA accurately.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.115-127
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• 2024

This research aimed to construct models with various structures based on the Transformer module and to perform land cover classification, thereby examining the applicability of the Transformer module. For the classification of land cover, the Unet model, which has a CNN structure, was selected as the base model, and a total of four deep learning models were constructed by combining both the encoder and decoder parts with the Transformer module. During the training process of the deep learning models, the training was repeated 10 times under the same conditions to evaluate the generalization performance. The evaluation of the classification accuracy of the deep learning models showed that the Model D, which utilized the Transformer module in both the encoder and decoder structures, achieved the highest overall accuracy with an average of approximately 89.4% and a Kappa coefficient average of about 73.2%. In terms of training time, models based on CNN were the most efficient. however, the use of Transformer-based models resulted in an average improvement of 0.5% in classification accuracy based on the Kappa coefficient. It is considered necessary to refine the model by considering various variables such as adjusting hyperparameters and image patch sizes during the integration process with CNN models. A common issue identified in all models during the land cover classification process was the difficulty in detecting small-scale objects. To improve this misclassification phenomenon, it is deemed necessary to explore the use of high-resolution input data and integrate multidimensional data that includes terrain and texture information.

• Journal of dental hygiene science
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• v.9 no.3
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• pp.327-338
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• 2009

This study was to develop an instrument for multidimensional measurement of Korean scaling fear (KSF)-1.0 and analyze related factors. A sample of 720 subjects(scaling patients and community people) was studied in Daegu city from November in 2008 to March in 2009. Authors first conceptualized the KSF, item generation, item reduction, and questionnaire formatting were performed in the stage of the development. Item descriptive, missing%, item internal consistency, and item discriminant validity were analyzed in the item-level, also descriptive, floor and ceiling effect were analyzed in the scale-level. Cronbach's alpha, test-retest, inter-dimension correlations, and factor analysis were performed to evaluate the validity and reliability in the new instrument. Confirmative factor analysis was did to evaluate the fit of model. The results for item-level and scale-level were acceptable except item discriminant validity. The reliability for 0.92~0.96 of corelation coefficient range(Cronbach's alpha 0.96~0.98) was high in the test-retest, and there was no significant difference in paired t-test. Item internal consistency(range of pearson corelation coefficient 0.39~0.95) was also high. The result of explanatory factor analysis was the same as the intended dimension structure, also confirmatory factor analysis results revealed that the dimensional structure model were fined well in the evaluation of model fit($x^2$= 1245.66, df=146, p=0.0000; GFI=0.85; AGFI=0.80; RMSEA=0.10). Factors related to KSF by multiple regression were gender($\beta$=0.28, p=0.0004) and teeth brush method($\beta$=-0.15, p=0.0053) in scaling patients, also gender($\beta$=0.25, p=0.0002), educational level($\beta$=0.14, p=0.0155), teeth brush method($\beta$=-0.09, p=0.0229) and time of daily work out($\beta$=-0.10, p=0.0055) were significantly associated with KSF in no scaling group. In conclusion, The results of this study reveal that the new developed measurement scale was reliable and val id instrument for measuring the KSF in dental hygiene patients and community people. We recommend that further research should develop more the instrument for the Korean scaling fear.

• Tuberculosis and Respiratory Diseases
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• v.61 no.3
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• pp.227-232
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• 2006

Background: In the measurement of bronchodilator reversibility, the forced expiratory volume in one second($FEV_{1}$) and the forced vital capacity(FVC) are commonly used parameters and recommended criteria for the reversibility requiring an increase of more than 200ml and 12% above the baseline, respectively. However, aged patients do not often meet the criteria of an increase in volume(>200ml) even though the medical history of that patient is adequate for asthma. This study investigated the role of the forced expiratory volume in six seconds($FEV_{6}$) in the bronchodilator reversibility test in elderly patients. Methods: A total of 236 patients more than 65 years of age with a $FEV_{1}$/FVC ratio<80% were enrolled in this study. The bronchodilator revesibility tests were examined. With the setting $FEV_{1}$ as the baseline, the patients were divided into three groups; Group I : $$FEV_{1}{\geq_-}80%$$ of the predicted value, Group II : 60%<$FEV_{1}$<80% of the predicted value, Group III : $$FEV_{1}{\leq_-}60%$$ of the predicted value. Results: Positive reversibility in the $FEV_{1}$, $FEV_{6}$, and FVC was in 33(14.0%), 49(20.8%) and 55(23.3%). However, Group III presented with reversibility in the $FEV_{1}$, $FEV_{6}$, and FVC in 15(22.4%), 30(44.8%) and 32(47.8%) respectively. Conclusions: The $FEV_{6}$ might be used as a complementary parameter in bronchodilatror reversibility in elderly patients. However, more study will be needed to determine the usefulness of $FEV_{6}$ in bronchodilator reversibility test.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Journal of the Korean earth science society
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• v.25 no.8
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• pp.774-783
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• 2004

The S wave velocity and Q$s^{-1}$ structure of the uppermost part of the soil in Nakdong Delta area have been obtained to determine the characteristics of the forementioned soil. The phase and attenuation coefficients of multichannel seismic records were inverted to obtain the S wave velocity and Q$s^{-1}$ structure of the soil. The inversion results have been compared with the borehole measurements of the area. The seismic signal of the nearest geophone from a seismic source was used as the source signal to obtain the attenuation coefficients. Amplitude ratios of the signal at each geophone to the source signal wave plotted as a function of distance for the frequency range between 10 Hz and 45 Hz. The slope of a linear regression line which fits amplitude ratio-distance relationship best for a given frequency was used as the attenuation coefficients for the frequency. The dispersion curve of Rayleigh waves and the attenuation coefficients were inverted to obtain the S-wave velocity and Q$s^{-1}$, respectively, in the uppermost 8 meter of soil layer. The borehole measurements of the area show that are two distinct layers; the upper 4 meter of silty-sand and the lower 4 meter of silty-clay. The inversion results indicate that the shear wave velocity of the upper layer is 80 m/sec and 40m/sec in the lower silty-clay layer. The spacial resolution of the shear wave velocity structure is very good down to a depth of 8 meter. The Q$s^{-1}$ in the upper silty-sand layer is 0.02 and increase to 0.03 in the lower silty-sand layer. The spacial resolution of quality factor is relatively good down to a depth of 5 meter, but very poor below the depth. In this study, the S-wave velocity is higher in the silty-clay and the Q$s^{-1}$ is smaller silty-sand than in the silty-clay. However, much more data should be analyzed and accumulated before making any generalization on the shear wave velocity and Q$s^{-1}$ of the sediments.

• Journal of Nutrition and Health
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• v.49 no.3
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• pp.179-188
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• 2016

Purpose: This cross-sectional study aimed to document the dietary behaviors, dietary changes, and health status of female marriage immigrants residing in Gwangju, Korea. Methods: The survey included 92 female immigrants attending Korean language class at a multi-cultural family support center. General characteristics, health status, anthropometric data, dietary behaviors, and dietary changes were collected. Results: Mean age of subjects was 31.3 years, and home countries of subjects were Vietnam (50.0%), China (26.0%), Philippines (12.0%), and others (12.0%). Frequently reported chronic diseases were digestive diseases (13.2%), anemia (12.1%), and neuropsychiatry disorder (8.9%). Seventeen percent of the subjects was obese ($BMI{\geq}25kg/m^2$). Dietary score by Mini Dietary Assessment was 3.45 out of 5 points. Dietary scores for dairy foods, meat/fish/egg/bean intake, meal regularity, and food variety were low, and those for fried foods and high fat meat intake were also low. Thirty-three percent of subjects answered that they have changed their diet and increased their consumption of fruits and vegetables after immigration. Length of residence in Korea was positively associated with BMI and waist circumference. Length of residence tends to be positively associated with dietary changes and obesity as well as inversely associated with disease prevalence. Conclusion: The study shows that length of residence is inversely related to disease prevalence. However, this association is thought to be due to the relatively short period of residence in Korea and thus the transitional phase to adapting to dietary practices. As the length of residence increases, disease patterns related to obesity are subject to change. Healthy dietary behaviors and adaptation to dietary practices in Korea in female marriage immigrants will not only benefit individuals but also their families and social structure. Therefore, varied, long-term, and target-specific studies on female marriage immigrants are highly needed.

• Progress in Medical Physics
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• v.22 no.1
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• pp.52-58
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• 2011

Our goal is to assess the suitability of a glass dosimeter on detection of high-energy electron beams for clinical use, especially for radiation therapy. We examined the dosimetric characteristics of glass dosimeters including dose linearity, reproducibility, angular dependence, dose rate dependence, and energy dependence of 5 different electron energy qualities. The GD was irradiated with high-energy electron beams from the medical linear accelerator andgamma rays from a cobalt-60 teletherapy unit. All irradiations were performed in a water phantom. The result of the dose linearity for high-energy electron beams showed well fitted regression line with the coefficient of determination; $R^2$ of 0.999 between 6 and 20 MeV. The reproducibility of GDs exposed to the nominal electron energies 6, 9, 12, 16, and 20 MeV was ${\pm}1.2%$. In terms of the angular dependence to electron beams,GD response differences to the electron beam were within 1.5% for angles ranging from $0^{\circ}$ to $90^{\circ}$ and GD's maximum response differencewas 14% lower at 180o. In the dose rate dependence, measured dose values were normalized to the value obtained from 500 MU/min. The uncertainties of dose rate were measured within ${\pm}1.5%$ except for the value from 100 MU/min. In the evaluation of the energy dependence of the GD at nominal electron energies between 6 and 20 MeV, we obtained lower responses between 1.1% and 4.5% based on cobalt-60 beam. Our results show that GDs have a considerable potentiality for measuring doses delivered by high-energy electron beams.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.633-638
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• 2017

The amount of radioactive waste has been rapidly increased with development of radiation treatment in medical field. Recently, it has been a common practice to use I-131 for thyroid cancer, F-18 for PET/CT and Tc-99m for diagnosis of nuclear medicine. All the wastes concerned have been disposed of by means of the self-disposal method, for example incineration, after storage enough to decay less than clearance level. IAEA proposed criteria for clearance level of waste which depends on the individual ($10{\mu}Sv/y$) and collective dose (1 man-Sv/y), and concentration of each nuclide (IAEA Safety Series No 111-P-1.1, 1992 and IAEA RS-G-1.7, 2004). In this study, specific radioactivity of radioactive waste contaminated with Re-186 was measured to confirm whether it meets the clearance level. Re-186 has long half life of 3.8 days relatively and emits beta and gamma radiation, therefore it can be applied in treatment and imaging purposes. The specific radioactivity of contaminated gloves weared by radiation workers was measured by MCA(Multi-channel Analyzer) which was calibrated by reference materials in accordance with the measuring procedure. As a result, comparison evaluation of decay storage period between the half-life which was calculated by attenuation curve based on real measurement and physical half-life was considered, and it is showed that the physical half-life is longer than induced half-life. Therefore, the storage period of radioactive waste for self-disposal may be curtailed in case of application of induced half-life. The result of this study will be proposed as ISO standard.