• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.226-233
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• 2023

Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis. Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected. A pretrained convolutional neural network was fine-tuned to classify active and inactive TB. The model was pretrained with 8,964 pneumonia and 8,525 normal cases from the National Institute of Health (NIH) dataset. During the pretraining phase, the DL model learns the following tasks: pneumonia vs. normal, pneumonia vs. active TB, and active TB vs. normal. The performance of the DL model was validated using three external datasets. Receiver operating characteristic analyses were performed to evaluate the diagnostic performance to determine active TB by DL model and radiologists. Sensitivities and specificities for determining active TB were evaluated for both the DL model and radiologists. Results: The performance of the DL model showed area under the curve (AUC) values of 0.980 in internal validation, and 0.815 and 0.887 in external validation. The AUC values for the DL model, thoracic radiologist, and general radiologist, evaluated using one of the external validation datasets, were 0.815, 0.871, and 0.811, respectively. Conclusion: This DL-based algorithm showed potential as an effective diagnostic tool to identify TB activity, and could be useful for the follow-up of patients with inactive TB in high TB burden countries.

• Korean Journal of Community Nutrition
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• v.10 no.6
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• pp.905-919
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• 2005

This study raised the necessity of developing performance indicators for measuring the management efficiency and effectiveness of school food service, and as a means of helping its implementation, a balanced score card (BSC) approach developed by Norton and Kaplan was adopted. This study established BSC in seven phases through literature: Phase 1 Defining a school food service and the scope of working activities, Phase 2 Establishing the vision of a school food service, Phase 3 Setting strategic goals, Phase 4 Identifying critical success factors (CSFs), Phase 5 Developing Key Performance Indicators (KPIs), Phase 6 Extracting cause and effect relationship, and Phase 7 Completing a preliminary BSC. The preliminary BSC was fumed into a survey, which was administered to food service related people working at the Office of Education and School Food Service including 16 offices,209 dietitians, 48 school administrators both from self-operated and contract-managed, and 9 experts in areas related to school food service. They were asked questions about strategies from 4 different perspectives,12 CSFs, 39 KPls, and the cause and effect relationships among them. As a result, among the CSFs based on 4 different perspectives, all factors other than ' zero sum on profit/loss ' from the financial perspective turned out to be valid. In terms of KPIs, manufacturing cost percentages, casualty loss count/reduction rates, school foodervice participation rates, and sales goal achievement rates were found to be valid from the financial perspective, while student satisfaction index, faculty satisfaction index, leftover ratio, nutrition educational performance count, index of evaluating nutrition education, customer claim count/reduction rate, handling customer claim count/reduction rate, and parent satisfaction index were found to be valid from the customers' perspective. Besides, nutritional requirement sufficient ratio, nutritional management score, food poisoning outbreak count, employee safety accident count, sanitary inspection assessment index, meals per labor hour (productivity index), computerization ratio, operational management index, and purchase management assessment index were also found to be valid from the perspective of internal business processes. From the perspective of innovation and learning, employee turnover ratio/rate of absenteeism, annual education and training count, employee satisfaction index, human resource management assessment index, annual menu-related customer feedback, food service information index for employees and parents/schools were also found to be valid. The significance of this study is to present indices for measuring overall performance of school lunch food service operations without putting any limitation on types of school food service management, and to help correctly assess the contribution of the current types of school food service management to schools and students. (Korean J Community Nutrition 10(6) : $905\∼919$, 2005)

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.3
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• pp.1-13
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• 2018

Landscape Architecture is a minority manpower field that requires wide knowledge and experience. Therefore, the service market is narrower than other fields, and education service for practitioners is lacking. The purpose of this study is to propose e-learning content development methodology that can provide customized landscaping practical education according to the level of education and increase the economic efficiency of the development process. First, in theoretical review, the ADDIE model was modified to select the curriculum development model that pursues efficiency and introduced the concept of reusing learning objects in the SCORM-based model. In particular, to overcome the problems presented in the precious studies, the analysis and design stages have been strengthened and faculty designers with integrated knowledge of Landscape Architecture and ICT have led the overall phase. The actual development process is based on a step by step procedure--analysis of landscaping practitioners needs and environments, etc., teaching and learning procedures and the design of activities considering contents reuse, the first development such as actual shooting and editing, and the second development reusing the first development content--and was done in the order of evaluation and revision of professionalism and satisfaction. As a result of the study, the space-based courses composed of modular learning objects were first developed as 216 courses in 8 subjects, as 208 courses in 3 subjects in total, in which the modularized learning object are crossed and combined in units and difficulty-based courses were second developed in 216 courses with 3 subjects in total. As a result of the evaluation the satisfaction assessment of the overall satisfaction was 4.20 and the average value of the eight measures was 3.97, both being close to 4.0. For the professional assessment, the scores of 8 subjects were very high at 84.8 to 96.4 points. in context, the scores of 5 subjects were equal to from 89.9 to 96.4 points. In conclusion, as the study was conducted based on a clear understanding of the digital characteristics of e-learning contents and general characteristic of the landscaping industry, it was possible to develop a curriculum by developing a course composed of modular learning objects and reusing learning objects by unit. In particular, it has been proven to be effective in conveying professional knowledge and experiences via general procedures and provided an opportunity to overcome some analog problems that may occur in offline education. In the future, further studies need to be done by expanding the content and by focusing on segmented subjects.

• Korean Journal of Culture and Social Issue
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• v.10 no.3
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• pp.37-59
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• 2004

This study examines longitudinally influences that parents have on their children's academic achievement and the mediating role of various psychological factors. In terms of parents-child relationship, the following variables are examined: Social support from parents, achievement pressure, parental expectation, sense of indebtedness to parents, and respect for parents. For adolescents functioning, the following variables are examined: Efficacy for self-regulated learning, achievement motivation, studying time, and academic achievement. In the first phase of the longitudinal study, a total of 961 Grade 6 students completed a questionnaire. In the second phrase, a total of 856 students completed a questionnaire when they were Grade 7. In the third phrase, a total of 830 students completed a questionnaire when they were Grade 9. In the third phase, a matched sample of 722 fathers and 767 mothers of the adolescents completed a questionnaire. From the sample, 694 matched sample of adolescents, mothers, and fathers have been selected for the following analysis. The results of the path analysis indicate that adolescents' past academic grade was the most powerful predictor of adolescents' current academic achievement. Second, a sense of indebtedness felt towards the parents increased adolescents' achievement motivation, which increased their studying time and which in turn positively affected their academic achievement. Third, adolescents' respect for their parents increased their efficacy for self-regulated learning, which had a positive effect on their academic achievement. Fourth, parental social support increased adolescents' efficacy for self-regulated learning and parental achievement pressure increased adolescents' achievement motivation. Fifth, parental expectation had positive influence on adolescents' academic achievement. Sixth, efficacy for self-regulated learning had direct positive influence on academic achievement. These results indicate that the past achievement is the most important predictor of adolescents' current academic achievement and parent-child relationship and efficacy for self-regulated learning are also important variables that influence adolescents' achievement.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.140-148
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• 1996

This paper proposes a combined feedforward/feedback controller which uses jacobians of neural network. The jacobians are calculated form the neural network that identifies the nonlinear plant, which are used for designing a jacobian controller and for training a neural network controller. Normally, it takes much time to train the neural network controller. Combining the neural and the jacobian controller, it can be a stable controller from the beginning of training phase of neural network, and it can be implemented as a learning-while-functioning controller. Simulated resutls for the proposed controller show its effectiveness and better performances.

• Journal of The Korean Association For Science Education
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• v.15 no.4
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• pp.429-436
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• 1995

The purpose of this study is to identify students' alternative frameworks about tide concept, to investigate some characters of them and students' understanding types with increasing grade in secondary school earth science course. The objective questionnaire method was used, and the subjects of this study are 528 students selected randomly in secondary school. The results are as follow. 1) Thirteen alternative frameworks about tide concept, related to the phase change of the moon and the motion of the earth are identified. 2) The alternative frameworks needed mechanical and causal reasoning have the trend reinforced or sophisticated with increasing the grade. And alternative frameworks needed phenomenal and mechanical, phenomenal and causal reasoning are changed little but ones needed phenomenal, variative and basic reasoning change scientifically. The rates of the alternative frameworks needed definitional, empirical, phenomenal reasoning decrease at the learning grade of that concept but increase after that grade. 3) Middle school students have the definitional, phenomenal, empirical and qualitative understanding types but high school students have the causal, analytic, quantitative and mechanical ones on tide concept.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.35-44
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• 2024

Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

• 대한공업교육학회지
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• v.42 no.1
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• pp.106-124
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• 2017

This study used the secondary Delphi method for experts, in order to propse a proper formation plan for the goal and curriculum of elementary and secondary invention/intellection property education. Its results are as following; First, the key objective of invention/intellectual property education for each school level is evaluated as appropriate. With regard to the key objective, elementary schools are aiming at 'fostering awareness and attitude for invention'(M=4.5), middle schools, 'understanding of invention process and method'(M=4.2), general high schools, 'application and evaluation of invention method'(M=4.1), and specialized high schools, 'understanding and application of Employee Invention'(M=4.6). The objective and goal of education for each school level are also evaluated as appropriate. Second, although the proper formation plans for a key learning element of elementary and secondary invention/intellectual property education were almost identical to an actual formation of preceding literature, overall change is required for the formation balance of each learning element, according to the objective and goal of school-leveled invention/intellectual property education. An appropriate formation shall be focusing on basic learning elements (A, B, C, D, E, and F) for elementary and middle schools(73.2%, 65.1%), lowering somewhat the former elements and increasing expanded learning elements for high schools(51.0%), which are connected to the invention, course(H), and patent application(K). Third, elementary and secondary invention/intellectual property education system should be oriented to its objective and goal. In order to reach this, an appropriate formation plan should be made for each school level, based on the principle of Tyler's learning organization, such as continuity, sequence and integration, which are key learning element. Specialized high schools, in particular, need to be differentiated from general ones, as well as elementary and middle schools. Additionally, for understanding and applying an employee invention, invention/intellectual property education system needs to be established in the phase of secondary occupational education.

• Journal of The Korean Association For Science Education
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• v.40 no.4
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• pp.385-398
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• 2020

This study aims to examine genetics problem-solving processes of high school students with different learning approaches. Two second graders in high school participated in a task that required solving the complicated pedigree problem. The participants had similar academic achievements in life science but one had a deep learning approach while the other had a surface learning approach. In order to analyze in depth the students' problem-solving processes, each student's problem-solving process was video-recorded, and each student conducted a think-aloud interview after solving the problem. Although students showed similar errors at the first trial in solving the problem, they showed different problem-solving process at the last trial. Student A who had a deep learning approach voluntarily solved the problem three times and demonstrated correct conceptual framing to the three constraints using rule-based reasoning in the last trial. Student A monitored the consistency between the data and her own pedigree, and reflected the problem-solving process in the check phase of the last trial in solving the problem. Student A's problem-solving process in the third trial resembled a successful problem-solving algorithm. However, student B who had a surface learning approach, involuntarily repeated solving the problem twice, and focused and used only part of the data due to her goal-oriented attitude to solve the problem in seeking for answers. Student B showed incorrect conceptual framing by memory-bank or arbitrary reasoning, and maintained her incorrect conceptual framing to the constraints in two problem-solving processes. These findings can help in understanding the problem-solving processes of students who have different learning approaches, allowing teachers to better support students with difficulties in accessing genetics problems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.85-90
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• 2019

This paper related with the M-CMA adaptive equalization algorithm which is possible to improve the residual isi and robustness performance compare to the current MMA algorithm that is reduce the intersymbol interference occurs in channel when transmitting the QAM signal. The current MMA algorithm depend on the cost function and error function using fixed signal dispersion constant, but the M-CMA algorithm depend on the new proposed cost function and error function using multiple dispersion constant. By this, it is possible to having robustness of the CMA and simultaneous compensation of amplitude and phase of MMA. The computer simulation was performed in the same channel and noise environment for compare the proposed M-CMA and current MMA algorithm. The equalizer output signal constellation, residual isi, MD, MSE learning courves and SER, represents the robustness were used for performance index. As a result of simulation, the M-CMA has more superior to the MMA in robustness and other performance index.