• Journal of the Korean Institute of Educational Facilities
• /
• v.8 no.5
• /
• pp.5-16
• /
• 2001

This paper presents results from analysis of architectural plan drawings of 355 elementary schools recently designed for 4 years. Theses plans are analyzed by factors such as local distribution, number of classes, type of plan, total construction area, area per a class, area per a student, and area status of each space. The purpose of this study is to provide fundamental resources for architectural designing and planning of elementary schools through finding trend and status of elementary school buildings that have no detailed data of area index. The results of this study are as follows: 1. As a result from analyzing number of classes in the surveyed schools, schools having 36 classes are dominant and schools having 72 classes are also shown. Average number of classes is 34.1. This result reflect s that elementary schools have been planned as large-scale schools. 2. In terms of type of plan, we found out that instead of disappearing traditional single corridor type building, the open school building that have multi-purpose spaces are mainly designed. In addition to that, there are few schools with large class rooms. 3. In the status of area of each school, they have much larger areas than areas provided by building guidelines. Secondly, there are some schools with two times area difference even though they have same class number. Therefore, it needs to adjust the school building guidelines to practical needs in the consideration of elementary school building for compulsory education. Though the plans of recently designed school for 4 year s are more differentiated than past, there are few schools planned by appropriate plan design and area distribution scheme. As a consequence, some improvements like improvement of building guidelines are desperate.

• Journal of the Korean Institute of Educational Facilities
• /
• v.27 no.3
• /
• pp.33-39
• /
• 2020

The purpose of this study is to understand the classroom facilities of England and USA in the 19th century. This kind of study can provide the meaning of past, present, and future on classroom facilities. The results of the study are as follows. First, England classroom in the 19th century was made up of a large space, a gallery, that could teach a large number of students at the same time. Second, the classroom facilities of USA in the 19th century were developed by reformers for the purpose of training the labor force of educational thought and industrial development. Third, some characteristics of classroom facilities of England and USA in the 19th century were also found in school facilities of Korea at the same time. Fourth, large gallery classes began to disappear in the mid-19th century and were transformed into small 'class' facilities to improve efficiency. Fifth, the word 'class' did not appear as a substitute for the school, but as a meaning of subdividing within the school. Sixth, these classrooms consisted of smaller classes, and they began to create and teach common and unified curriculums to harmonize the differences between classes and to manage all students efficiently and effectively. Seventh, the basis of the classroom of England and USA in the 19th century was the design of one teacher to efficiently teach a large number of students, and there was a difference in size, but the current classroom facilities have been maintained to some extent. Eighth, since the end of the 19th century, the compulsory education system has been discussed and gradually introduced, requiring more schools and classroom facilities, and labor and capital have been emphasized by the development of industrialization. Ninth, follow-up studies are needed to analyze how classroom facilities have been universally transformed since then, based on class facilities in the 19th century, and what educational, social and political contexts have been added in the process.

• Journal of the Korea Society for Simulation
• /
• v.22 no.3
• /
• pp.71-79
• /
• 2013

Web server cluster systems are widely used, where a large number of PC level servers are interconnected via network. This paper focuses on forecasting an appropriate number of web servers which can serve four different classes of user requests, simple web page viewing, knowledge query, motion picture viewing and motion picture uploading. Two ways of serving different classes of web service requests are considered, commonly used web servers and service dedicated web servers. Computer simulation experiments are performed in order to find a good way of allocating web servers among different classes of web service requests, maintaining certain levels of resource utilization and response time.

• Korean Journal of Child Studies
• /
• v.33 no.3
• /
• pp.149-175
• /
• 2012

This study is designed to positively transform a teacher's emotional state whilst teaching their classes and be able to create happier lessons for preschool children. To do this, a teacher needs to reflect upon current problems and take steps to deal with them. The data for this study was collected from participatory observation and in-depth interviews, making use of photos, a reflective teacher's journal and interview records from Mar. 28, 2011 through Oct. 7, 2011. The problems identified were, (1) teacher centered classes, (2) a daily routine filled with large group activities, (3) disruptive students, and (4) repetitiveness. The routes to greater classroom "happiness" are (1) rearranging seats, (2) "story sharing activities" in small groups, (3) making a separate "story sharing activity" area, (4) using small groups instead of large groups, (5) changing the daily routine. The role of the teacher in finding greater "happiness" are (1) meaningful, 'real observation', (2) discovering genuine change from small points, (3) power sharing, and (4) growing and developing with children.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.14 no.1
• /
• pp.39-47
• /
• 1996

This paper is to provide land cover classification techniques for large area ranged in different pathos by classifying Landsat TM data of Jeonnam province. The analyses proceeded by individual scene because acquired dates are not same in different pathes. In this processing, troubles had happened something like variation of classes can be classified in two scenes and choice problem about overlapped area. Since spatial effects in large area affect data values, it was difficult to make a selection of classes and training fields. we could present a solution about these problems by trial and error method, and found that Bayesian maximum likelihood classification and majority filtering were effective to improve classification accuracy.

• Journal of Korean Public Health Nursing
• /
• v.31 no.2
• /
• pp.352-364
• /
• 2017

Purpose: The aim of this study was to explain the burnout among health teachers in elementary schools with large class sizes, and to explore the nature and meaning of those experiences. Methods: This study used the four steps of Giorgi's descriptive phenomenology. Data were collected through in-depth interviews regarding the experiences of burnout of 9 participants, which were recorded, transcribed, and analyzed. Results: The participants' experiences of teaching large classes were categorized into 4 themes and 9 domains. The themes were "difficult and lethargic," "gradual deterioration conditions," "losing work-life balance," and "enduring for a short time and leaving." Conclusion: Burnout not only affected the teachers at work but also had a negative impact on the teachers' personal and family lives outside of school. This study found that the current teacher assignment criteria were the strongest factors influencing burnout, which contribute to physical exhaustion. Health teachers are assigned based on different criteria that do not consider the number of students. Another factor contributing to burnout among health teachers is a work environment conducive to with emotional exhaustion. Health teachers and content teachers are not sufficiently knowledgeable regarding the specifics of each other's work.

• The KIPS Transactions:PartA
• /
• v.13A no.1 s.98
• /
• pp.71-78
• /
• 2006

For using XML data in programming languages, there is a data binding method, which generates classes from XML type definitions. However, since existing binding frameworks for this method generate all classes for element definitions, the number of generated classes becomes large and the complexity of the overall application system gets high. In this research, we propose an inline binding method for selecting necessary classes from element definitions. In the proposed method, classes are created only for elements with repetitions and recursions, and they include fields for values of terminal elements. We introduce a generation algorithm for binding classes and the marshaling methods for recovering the omitted paths. We develop IBinder system to validate the proposed method and compare the generated codes with the ones of existing systems. As a result, we carl show that the number of generated classes decrease substantially compared to other systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2017.10a
• /
• pp.638-640
• /
• 2017

The study analyzed the impact of classroom classes on classroom attitude and satisfaction in classes related to students' computing incidents in college. The classroom environment referred to in this study considered the number of persons per division and seating arrangement. The university compared the number of universities with a large number of college graduates, compared with the back and rear of the same division. This study aims to improve the classroom environment for classes of liberal arts courses.

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.2
• /
• pp.45.3-46
• /
• 2021

Supernovae classes have been defined phenomenologically, based on spectral features and time series data, since the specific details of the physics of the different explosions remain unrevealed. However, the number of these classes is increasing as objects with new features are observed, and the next generation of large-surveys will only bring more variety to our attention. We apply the machine learning technique of multi-label classification to the spectra of supernovae. By measuring the probabilities of specific features or 'tags' in the supernova spectra, we can compress the information from a specific object down to that suitable for a human or database scan, without the need to directly assign to a reductive 'class'. We use logistic regression to assign tag probabilities, and then a feed-forward neural network to filter the objects into the standard set of classes, based solely on the tag probabilities. We present STag, a software package that can compute these tag probabilities and make spectral classifications.

• The Korean Journal of Applied Statistics
• /
• v.24 no.5
• /
• pp.847-859
• /
• 2011

cDNA microarray-based comparative genomic hybridization(CGH) data includes low-intensity spots and thus a statistical strategy is needed to detect subtle differences between different cancer classes. In this study, genes displaying a high frequency of alteration in one of the different classes were selected among the pre-selected genes that show relatively large variations between genes compared to total variations. Utilizing copy-number changes of the selected genes, this study suggests a statistical approach to predict patients' classes with increased performance by pre-classifying patients with similar genetic alteration scores. Two-stage logistic regression model(TLRM) was suggested to pre-classify homogeneous patients and predict patients' classes for cancer prediction; a decision tree(DT) was combined with logistic regression on the set of informative genes. TLRM was constructed in cDNA microarray-based CGH data from the Cancer Metastasis Research Center(CMRC) at Yonsei University; it predicted the patients' clinical diagnoses with perfect matches (except for one patient among the high-risk and low-risk classified patients where the performance of predictions is critical due to the high sensitivity and specificity requirements for clinical treatments. Accuracy validated by leave-one-out cross-validation(LOOCV) was 83.3% while other classification methods of CART and DT performed as comparisons showed worse performances than TLRM.