• Analytical Science and Technology
• /
• v.34 no.6
• /
• pp.259-266
• /
• 2021

Cannabis (Marijuana) is one of the most widely used drugs in the world, and its distribution has been controlled in South Korea since 1976. Identification of 11-nor-Δ⁹-carboxy-tetrahydrocannabinol (THCCOOH) in urine can provide important proof of cannabis use, and it is considered scientific evidence in the forensic field. In this study, we describe a simultaneous quantitative method for identifying THCCOOH and THCCOOH-glucuronide in urine, using simple liquid-liquid extraction (LLE), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). THCCOOH-D₃ and THCCOOH-glucuronide-D₃ were used as internal standards. Validation results of the matrix effect, as well as recovery, linearity, precision, accuracy, process efficiency, and stability were all satisfactory. No carryover, endogenous or exogenous interferences were observed. The limit of detection (LOD) of THCCOOH and THCCOOH-glucuronide were 0.3 and 0.2 ng/mL, respectively. The developed method was applied to 28 authentic human urine samples that tested positive in immunoassay screening and gas chromatography/mass spectrometry (GC/MS) tests. The ranges of concentrations of THCCOOH and THCCOOH-glucuronide in the samples were less than LOQ~266.90 ng/mL and 6.43~2133.03 ng/mL, respectively. The concentrations of THCCOOH-glucuronide were higher than those of THCCOOH in all samples. This method can be effectively and successfully applied for the confirmation of cannabinoid use in human urine samples in the forensic field.

• Journal of agricultural medicine and community health
• /
• v.47 no.3
• /
• pp.166-180
• /
• 2022

Objective: This study evaluated the effects of a non-face-to-face obesity management program, implemented during the pandemic. Methods: The non-face-to-face obesity management program used the Intervention mapping protocol (IMP). The program was put into effect over the course of eight weeks, from September 14 to November 13, 2020 in 48 overweight and obese adults, who applied to participate through the Daegu Citizen Health Support Center. Results: IMP was first a needs assessment was conducted; second, goal setting for behavior change was established; third, evidence-based selection of arbitration method and performance strategy was performed; fourth, program design and validation; fifth, the program was run; and sixth, the results were evaluated. The average weight after participation in the program was reduced by 1.2kg, average WC decreased by 3cm, and average BMI decreased by 0.8kg/m² (p<0.05). The results of the health behavior survey showed a positive improvement in lifestyle factors, including average daily intake calories, fruit intake, and time spent in walking exercise before and after participation in the program. A statistically significant difference was seen (p<0.05). The satisfaction level for program process evaluation was high, at 4.57±0.63 point. Conclusion: The non-face-to-face obesity management program was useful for obesity management for adults in communities, as it enables individual counseling by experts and active participation through self-body measurement and recording without restriction by time and place. However, the program had some restrictions on participation that may relate to the age of the subject, such as skill and comfort in using a mobile app.

• The Journal of Engineering Geology
• /
• v.32 no.4
• /
• pp.697-723
• /
• 2022

Data-driven models to predict groundwater levels 30 days in advance were developed for 12 groundwater monitoring stations in the middle-Jeju watershed, Jeju Island. Stacked long short-term memory (stacked-LSTM), a deep learning technique suitable for time series forecasting, was used for model development. Daily time series data from 2001 to 2022 for precipitation, groundwater usage amount, and groundwater level were considered. Various models were proposed that used different combinations of the input data types and varying lengths of previous time series data for each input variable. A general procedure for deep-learning-based model development is suggested based on consideration of the comparative validation results of the tested models. A model using precipitation, groundwater usage amount, and previous groundwater level data as input variables outperformed any model neglecting one or more of these data categories. Using extended sequences of these past data improved the predictions, possibly owing to the long delay time between precipitation and groundwater recharge, which results from the deep groundwater level in Jeju Island. However, limiting the range of considered groundwater usage data that significantly affected the groundwater level fluctuation (rather than using all the groundwater usage data) improved the performance of the predictive model. The developed models can predict the future groundwater level based on the current amount of precipitation and groundwater use. Therefore, the models provide information on the soundness of the aquifer system, which will help to prepare management plans to maintain appropriate groundwater quantities.

• Korean Journal of School Psychology
• /
• v.17 no.3
• /
• pp.401-419
• /
• 2020

The purpose of this study was to validate the Korean Implementation Fidelity Checklist of Tier 1 School-Wide Positive Behavior Support (KIFC-T1) for use in the Korean educational system. Tier 1 support, which is universal supports, within a multi-tiered, school-wide positive behavior support (SWPBS) model, aims to provide support to and prevent problem behaviors among all students in a school. The initial KIFC-T1 consisted of 48 items and 11 factors and was developed based on a literature review. Its content was validated by experts. The validated KIFC-T1 was introduced to 185 special school teachers who had experience implementing SWPBS and who used the instrument to assess the degree to which their schools had implemented Tier 1 support. Based on their responses, the construct validity of the KIFC-T1 was examined using factor, item, and internal consistency reliability analyses. The concurrent validity of the tool was examined using the PBS Evaluation Tool, School Climate Questionnaire, School Discipline Practice Scale, and PBS Effectiveness Scale. The analyses revealed that KIFC-T1 had a stable five-factor structure with 35 items, had good reliability (Cronbach's α=.956, each factor's Cronbach's α=.834-.951), and its results were statistically significantly correlated with those of the PBS Evaluation Tool, School Discipline Practice Scale, and the PBS Effectiveness Scale. However the KIFC-T1's results were not statistically significantly correlated with the results of the School Climate Questionnaire. These results suggest that KIFC-T1 is a reliable and valid tool for assessing the fidelity of universal support implementations.

• Journal of Korean Home Economics Education Association
• /
• v.34 no.1
• /
• pp.59-80
• /
• 2022

The purpose of this study was to develop a workbook that can support the class and evaluation of the subject, 「Food safety and health」 and to verify its validity. The development direction of the workbook was set by analyzing the 「Food safety and health」 curriculum, dietary education materials, and previous studies related to the workbook, and the overall structure was designed by deriving the activity ideas for each area. Based on this, the draft was developed, and the draft went through several rounds of cross-review by the authors and the examination and revision by the Ministry of Food and Drug Safety, before the final edited version was developed. The workbook was finalized with corrections and enhancements based on the advice of 9 experts and 44 home economics teachers. The workbook consists of 4 areas: the 'food selection' area, with 10 learning topics and 36 lessons, the 'food poisoning and food management' area, with 10 learning topics and 36 lessons, the 'cooking' area, with 11 learning topics and 43 lessons, and the 'healthy eating' area, with 11 learning topics and 55 lessons, resulting in a total of 42 learning topics, 170 lessons. The workbook was designed to evenly cultivate practical problem-solving competency, self-reliance capacity, creative thinking capacity, and community capacity. In-depth inquiry-learning is conducted on the content, and the context is structured so that self-diagnosis can be made through evaluation. According to the validity test of the workbook, it was evaluated to be very appropriate for encouraging student-participatory classes and evaluations, and to create a class atmosphere that promotes inquiry by strengthening experiments and practices. In the current situation where the high school credit system is implemented and individual students' learning options are emphasized, the results of this study is expected to help expand the scope of home economics-based elective courses and contribute to realizing student-led classrooms with a focus on inquiry.

• Economic and Environmental Geology
• /
• v.55 no.5
• /
• pp.551-561
• /
• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.

• Korean Journal of Ecology and Environment
• /
• v.55 no.4
• /
• pp.274-284
• /
• 2022

Through sample-size-based rarefaction analyses, we tried to suggest the appropriate degree of sample concentration and sub-sample extraction, as a way to estimate more accurate zooplankton species diversity when assessing biodiversity. When we collected zooplankton from three reservoirs with different environmental characteristics, the estimated species richness (S) and Shannon's H' values showed different changing patterns according to the amount of sub-sample extracted from the whole sample by reservoir. However, consequently, their zooplankton diversity indices were estimated the highest values when analyzed by extracting the largest amount of sub-sample. As a result of rarefaction analysis about sample coverage, in the case of deep eutrophic reservoir (Juam) with high zooplankton species and individual numbers, it was analyzed that 99.8% of the whole samples were represented by only 1 mL of sub-sample based on 100 mL of concentrated samples. On the other hand, in Soyang reservoir, which showed very small species and individual numbers, a relatively low representation at 97% when 10 mL of sub-sample was extracted from the same amount of concentrated sample. As such, the representation of sub-sample for the whole zooplankton sample varies depending on the individual density in the sample collected from the field. If the degree of concentration of samples and the amount of sub-sample extraction are adjusted according to the collected individual density, it is believed that errors that occur when comparing the number of species and diversity indices among different water bodies can be minimized.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.121-142
• /
• 2023

As the number and weight of imported food are steadily increasing, safety management of imported food to prevent food safety accidents is becoming more important. The Ministry of Food and Drug Safety conducts on-site inspections of foreign food facilities before customs clearance as well as import inspection at the customs clearance stage. However, a data-based safety management plan for imported food is needed due to time, cost, and limited resources. In this study, we tried to increase the efficiency of the on-site inspection by preparing a machine learning prediction model that pre-selects the companies that are expected to fail before the on-site inspection. Basic information of 303,272 foreign food facilities and processing businesses collected in the Integrated Food Safety Information Network and 1,689 cases of on-site inspection information data collected from 2019 to April 2022 were collected. After preprocessing the data of foreign food facilities, only the data subject to on-site inspection were extracted using the foreign food facility_code. As a result, it consisted of a total of 1,689 data and 103 variables. For 103 variables, variables that were '0' were removed based on the Theil-U index, and after reducing by applying Multiple Correspondence Analysis, 49 characteristic variables were finally derived. We build eight different models and perform hyperparameter tuning through 5-fold cross validation. Then, the performance of the generated models are evaluated. The research purpose of selecting companies subject to on-site inspection is to maximize the recall, which is the probability of judging nonconforming companies as nonconforming. As a result of applying various algorithms of machine learning, the Random Forest model with the highest Recall_macro, AUROC, Average PR, F1-score, and Balanced Accuracy was evaluated as the best model. Finally, we apply Kernal SHAP (SHapley Additive exPlanations) to present the selection reason for nonconforming facilities of individual instances, and discuss applicability to the on-site inspection facility selection system. Based on the results of this study, it is expected that it will contribute to the efficient operation of limited resources such as manpower and budget by establishing an imported food management system through a data-based scientific risk management model.

• Journal of Nutrition and Health
• /
• v.56 no.1
• /
• pp.35-53
• /
• 2023

Purpose: The purpose of the first part of this study was to evaluate the validity of the physical activity classification table for youth (Youth-PACT). The second part of this study was aimed at comparing the estimated energy requirement (EER) with the total energy expenditure (TEE) and evaluating the physical activity patterns of Korean children and adolescents. Methods: The subjects of the first part of the study were 17 children aged 10 to 12 years, and their total energy expenditure (TEE_DLW) was measured using the double labeled water (DLW) method. A total of 166 children and adolescents aged 6-18 years participated in the second part of this study. Their resting energy expenditure (REE) was measured using indirect calorimetry and the TEE_Youth-PACT and physical activity level were calculated by applying the Youth-PACT to the physical activity diary prepared by the subjects. Results: In the first part of this study, there were no significant differences between the TEE_DLW and the TEE_Youth-PACT. The TEE_Youth-PACT accurately predicted TEE_DLW in 37.5% of the subjects. In the second part of the study, the rates at which EER accurately predicted TEE _YouthPACT and overestimated TEE _Youth-PACT were 29.6% and 47.3%, respectively. The time spent based on intensity of physical activity and the physical activity categories which were obtained using Youth-PACT showed different patterns according to sex and age group. Age showed significant positive correlations with REE, TEE, and the time spent in sedentary behavior, but age was significantly negatively correlated with REE/body weight, TEE/body weight, and the time spent in low-intensity and high-intensity activities. Conclusion: The results of this study showed that the Youth-PACT can be used to evaluate the TEE and PAL of children and adolescents. However, further studies are needed to validate the TEE_Youth-PACT and to set the EER for children and adolescents.

• Journal of Christian Education in Korea
• /
• v.72
• /
• pp.245-271
• /
• 2022

The purpose of this study is to develop a nursing clinical practice education model that applies case-based learning and co-teaching to nursing students, and to secure the validity of the developed model. To verify the validity of the nursing clinical practice education model, it was applied to the subject of 'Health Response and Nursing VI (Perception/ Cognition) Practice' in the 2nd semester of 2021 at J University in Jeonju, and the instructor's response to the model was evaluated. Surveys and focus group interviews were conducted on confidence in clinical practice and teaching and learning models. After deriving the case-based learning stage and co-teaching elements through a review of precedent literature and case studies, an initial model was devised after expert review, and the devised model was reviewed for internal validity by nursing education experts, and then modified and supplemented. As a result of the learner response evaluation conducted after applying the model to the clinical practice subject for external validation verification, the confidence in clinical performance was 4.22 points and the satisfaction with the teaching-learning model was 4.68 points. Summarizing the results of the focus group interview, the importance of prior learning and the learning of selected cases based on actual cases, learning terminology and professional knowledge, eliminated fear of the practice field, felt familiar, and learned various cases. He said that he was able to think critically through the time to organize the knowledge learned in the practice field. In addition, through co-teaching, it was found that field leaders and advisors taught the theoretical and practical aspects at the same time through examples, thereby experiencing practical education closer to practice. It is expected that the nursing clinical practice education model developed through this study, applying case-based learning and co-teaching, will be an effective teaching and learning model that can reduce the gap between theory and practice and improve the clinical performance of nursing students.