• Korean Educational Research Journal
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• v.43 no.1
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• pp.125-152
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• 2022

The purpose of this study is to examine the differences of perceptions of teachers and students regarding teaching skills. For the analysis, data was collected by ICALT(International Comparative Analysis of Learning and Teaching) class observation tool and students survey called My Teacher Questionnaire. a student survey. The data of teachers and students can be compared because as the two tools have seven common domains(Safe and stimulating learning climate, Efficient organization, Clear and structured instructions, Intensive and activating teaching, Adjusting instructions and learner processing to inter-learner differences, Teaching learning strategies, Learner engagement). In 2016, in Daejeon, Chungbuk and Chungnam. trained teachers collected data from 106 classes, and 2,866 students responded the survey. The reliability and validity of the two tools, class observation and MTQ(My Teacher Questionnaire) are proven to be satisfactory for use in Korean schools. Students perception on teaching was high, particularly when students are in lower grades and learning major subjects like English, Korean, and math. The domain of higher teaching skills, male students show higher perceptions while female students reported higher perceptions on lower-level teaching skill domains. To compare the perceptions of teachers and students, the predictive reliability of students engagement against teaching skill domains was used. Teachers showed higher predictive reliability on lower teaching skill domains while students showed higher predictive reliability on higher teaching skill domains. It is recommended for further study to develop a professional development model using a teacher class observation tool and the My Teacher Questionnaire for pre-service teachers and school teachers.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1298-1311
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• 2022

Purpose To develop and validate a deep learning-based screening tool for the early diagnosis of scoliosis using chest radiographs with a semi-supervised generative adversarial network (GAN). Materials and Methods Using a semi-supervised learning framework with a GAN, a screening tool for diagnosing scoliosis was developed and validated through the chest PA radiographs of patients at two different tertiary hospitals. Our proposed method used training GAN with mild to severe scoliosis only in a semi-supervised manner, as an upstream task to learn scoliosis representations and a downstream task to perform simple classification for differentiating between normal and scoliosis states sensitively. Results The area under the receiver operating characteristic curve, negative predictive value (NPV), positive predictive value, sensitivity, and specificity were 0.856, 0.950, 0.579, 0.985, and 0.285, respectively. Conclusion Our deep learning-based artificial intelligence software in a semi-supervised manner achieved excellent performance in diagnosing scoliosis using the chest PA radiographs of young individuals; thus, it could be used as a screening tool with high NPV and sensitivity and reduce the burden on radiologists for diagnosing scoliosis through health screening chest radiographs.

• Journal of Environmental Health Sciences
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• v.35 no.1
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• pp.45-52
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• 2009

In recent years, pharmaceuticals in the aquatic environment have become a matter of increasing public concern. Environmental risk assessment (ERA), including an exposure assessment, is considered the best scientifically based approach for evaluating the potential effects of pharmaceuticals on ecosystems. Computerized exposure models constitute an important tool in predicting environmental exposures of pharmaceuticals. This paper presents the applicability of an exposure model by comparing measured data of selected pharmaceuticals with predicted environmental concentrations from an exposure model. $PhATE^{TM}$ (Pharmaceutical Assessment and Transport Evaluation) model developed by the Pharmaceutical Research and Manufacturers of America (PhRMA) was adapted to run simulations for the Keum River. A set of 7 pharmaceuticals of high production in Korea was modeled. The PECs generated by the $PhATE^{TM}$ model that were then compared to the measured concentrations. The $PhATE^{TM}$ model predicted concentrations for 7 pharmaceuticals including acetaminophen, acetylsalicylic acid, erythromycin, ibuprofen, lincomycin, mefenamic acid, and naproxen were in good agreement with actual measured concentrations, which demonstrated the utility of $PhATE^{TM}$ as a predictive tool. In conclusion, $PhATE^{TM}$, although it does not intend to accurately represent reality, could be utilized for rapid predictions of the environmental concentrations of pharmaceuticals.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.833-847
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• 2021

The horizontal porous baffle and its effect as an anti-slosh device have been investigated intensively in a swaying and rolling rectangular tank. To accurately assess the level at which porous baffles reduce liquid sloshing, the Matched Eigenfunction Expansion Method (MEEM) has been utilized as an analytical tool. The velocity potentials in the horizontal baffle-covered fluid region are expressed by the sum of the homogeneous and particular solutions to avoid solving the complex dispersion equation. By applying an equivalent linearized quadratic loss model, the nonlinear algebraic equation is derived and solved by implementing the Newton-Raphson iterative scheme. To prove the validity of the present theoretical model, a series of experiments have been conducted with different centered horizontal porous baffles with varying porosities and submerged depths in a swaying and rolling rectangular tank. Reasonably good agreements are obtained regarding the analytical solutions and the experiment's findings. The influence of porosity, submerged depth, and length of a centered horizontal porous baffle on anti-slosh performance have been analyzed, especially at resonance modes. The developed predictive tool can potentially provide guidelines for optimal design of the horizontal porous baffle.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.85-90
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• 2023

Data analysis methodology in the healthcare field is shifting from traditional statistics-oriented research methods to predictive research using machine learning. In this study, we survey various machine learning tools, and compare several programming models, which utilize R and Spark, for applying R, a statistical tool widely used in the health care field, to machine learning. In addition, we compare the performance of linear regression model using scala, which is the basic languages of Spark and R. As a result of the experiment, the learning execution time when using SparkR increased by 10 to 20% compared to Scala. Considering the presented performance degradation, SparkR's distributed processing was confirmed as useful in R as the traditional statistical analysis tool that could be used as it is.

• Clinical and Experimental Pediatrics
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• v.50 no.11
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• pp.1061-1066
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• 2007

Purpose : Early identification of developmental disabilities allows intervention at the earliest possible point to improve the developmental potential. The Ages and Stages Questionnaire (ASQ), a parent- completed questionnaire, can be used as a substitute for formal screening tests. The purpose of this study was to evaluate the validity of the Korean version of the ASQ (K-ASQ) as a screening tool for detecting developmental delay of young Korean children in the setting of a busy pediatric outpatient clinic. Methods : Parents completed the K-ASQ in the waiting room of the pediatric outpatient clinic of St. Mary's Hospital, Catholic University Medical College. Out of 150 completed the ASQ, 67 who were born term and had no previous diagnosis of developmental delay, congenital anomalies, or neurological abnormalities were enrolled. The cut-off values of less than 2 standard deviations (SD) below the mean for the ASQ were used to define a "fail", and children who failed in one or more domains tested were classified as "screen-positive". Diagnosis of developmental delay was made when the developmental indices fell below -1 SD of the Bayley Scales of Infant Development-II. Results : (1) The mean age of children was $16.4{\pm}7.4$ months. Ten children (14.9%) were small-for- gestational age infants. The mean birth weight and gestational age were $3.1{\pm}0.6kg$ and $38.8{\pm}1.4$ weeks. Nine children (13.4%) were twins and 33 (49.0%) were male. The mean maternal education in years was $13.6{\pm}2.4$, and 31.3% had full-time jobs. The time for completing the ASQ was $10.2{\pm}3.0$ minutes. (2) Seventeen children (25.4%) were classified as screen-positive, four of them were delayed in development. Among eight children diagnosed with developmental delay, four were screen-positive and the other four were screen-negative by the ASQ. (3) The test characteristics of the ASQ were as follows: sensitivity (50.0%); specificity (78.0%); positive predictive value (23.5%); negative predictive value (92.0%). Conclusion : The high negative predictive value of the K-ASQ supports its use as a screening tool for developmental delay in the setting of a pediatric outpatient clinic.

• Radiation Oncology Journal
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• v.29 no.3
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• pp.191-198
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• 2011

Purpose: Although the role of squamous cell carcinoma antigen (SCC-Ag) as a predictive and prognostic factor for uterine cervical cancer has been identified in previous studies, 1) the effective patient group of screening for recurrence with SCC-Ag, 2) the relationship between SCC-Ag and recurrence site, and 3) the relationship between the change of SCC-Ag and treatment outcome or recurrence have not been described. Materials and Methods: The study included 506 patients with histologically proven uterine cervical cancer between January 1994 and December 2010. We determining the serum SCC-Ag level before treatment and after treatment, and conducted a retrospective review of the patients' records. We evaluated the sensitivity and specificity of SCC-Ag for the detection of tumor recurrence by comparing biochemical recurrence with clinical recurrence. Results: The pretreatment SCC-Ag level and the proportion of patients over 1.5 ng/mL were higher in poor prognostic patient group. In the univariate and multivariate analysis, pretreatment SCC-Ag showed a statistically significant correlation with tumor size, International Federation of Gynecology and Obstetrics (FIGO) stage, pathology. In patients with biochemical recurrence vs. those without, 5-year DFS and OS were 27.6 vs. 92.7% (p ${\leq}$ 0.001) and 53.7 vs. 92.5% (p ${\leq}$ 0.001), respectively. Conclusion: Our study reconfirmed the known function of pretreatment SCC-Ag, but could not confirm the function of biochemical response as a predictive factor for treatment and as a prognostic factor. There was no statistically significant relationship between SCC-Ag level and recurrence site. We confirmed the role of SCC-Ag as a follow-up tool for recurrence of disease and which patient groups SCC-Ag was more useful for.

• Korean Journal of Adult Nursing
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• v.25 no.1
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• pp.24-32
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• 2013

Purpose: The aim of the study was to identify the most appropriate fall-risk assessment tool for neurological patients in an acute care setting. Methods: This descriptive study compared the reliability and validity of three fall-risk assessment tools (Morse Fall Scale, MFS; St Thomas's Risk Assessment Tool in Falling Elderly Inpatients, STRATIFY; Hendrich II Fall Risk Model, HFRM II). We assessed patients who were admitted to the Department of Neurology, Neurosurgery, and Rehabilitation at Asan Medical Center between July 1 and October 31, 2011, using a constructive questionnaire including general and clinical characteristics, and each item from the three tools. We analyzed inter-rater reliability with the kappa value, and the sensitivity, specificity, predictive value, and the area under the curve (AUC) of the three tools. Results: The analysis included 1,026 patients, and 32 falls occurred during this study. Inter-rater reliability was above 80% in all three tools. and the sensitivity was 50.0% (MFS), 84.4%(STRATIFY), and 59.4%(HFRM II). The AUC of the STRATIFY was 82.8. However, when the cutoff point was regulated as not 50 but 40 points, the AUC of the MFS was higher at 83.7. Conclusion: These results suggest that the STRATIFY may be the best tool for predicting falls for acute neurological patients.

• Journal of Korean Critical Care Nursing
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• v.15 no.3
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• pp.75-87
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• 2022

Purpose : This retrospective investigation study aimed to determine the predictive validity of superficial surgical site infection assessment tools by measuring the risk score at the surgical site. Methods : This study included patients hospitalized to the general surgery department of a Hospital from January 2021 to December 31, 2021. The inclusion criteria were age ≥19 years, general abdominal surgery under general anesthesia, and hospital stay longer than 2 days. Patients who had undergone transplantation were excluded. Results : Tool validity results showed that tools including surgical time and operative procedure were more accurate than previously developed tools, with a sensitivity of 71.1%, specificity of 71.4%, positive prediction of 12.3%, negative prediction of 97.8%, and area under the curve of 0.743 (95% confidence interval, 0.678~0.745). The tool's cut-off score was 15, and the risks of infection was increased by 6.14 times at or above this cut-off point. Preoperative hair removal period, surgical wound classification, surgery time, body temperature on the second day after surgery, drainage tube type, and suture type affected the risk of infection at the surgical site. Conclusion : The incidence of healthcare-associated infections has been declining in the past decade; however, surgical site infections still account for a considerable proportion. Therefore, early identification of high-risk groups for surgical site infection is crucial for reducing the incidence of surgical site infection using appropriate management.

• Bulletin of the Korean Chemical Society
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• v.33 no.9
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• pp.2930-2936
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• 2012

A three-dimensional pharmacophore hypothesis was developed for atypical antipsychotics in order to map common structural features of highly active compounds by using HipHop in CATALYST program. The pharmacophore hypotheses were generated using 12 compounds as training set and validated using 11 compounds as test set. The most predictive hypothesis (Hypo1) comprises five features viz. two hydrophobic regions, two hydrogen bond acceptor lipid and one aromatic ring. In the absence of information like crystallized structure of 5-$HT_{2A}$ receptor and binding mode of antipsychotics with 5-$HT_{2A}$ receptor, this hypothesis will serve as a potentially valuable tool in the design of novel atypical antipsychotics acting primarily at 5-$HT_{2A}$ and $D_2$ receptors.