• Informatization Policy
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• v.26 no.1
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• pp.46-61
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• 2019

The Fourth Industrial Revolution has been revolutionizing industry and education. This paper proposes an education platform, Smart Space EduPlatform (SSEP), for the real estate industry, aimed at educating the basic real estate technology (RETech) for workers in the real estate industry so they can achieve the highest and best use of the real estate in the smart environment. The habitat of SSEP is driven by the donation system ensuring sustainability, various technical functions such as tools for content production and learning participation, and learning behavior frameworks each in form of a learner, a teacher, and a helper. Services of SSEP consist of 17 important RETech lectures under 6 categories-planning and design, decision-making, management, economics, construction, and equipment-and project-based learning (PBL) curriculums. The lectures are provided along with video contents, additional learning materials and learning management service, while teachers' workshops, learner invitation and registration management, curriculum operation services are offered for the PBL curriculums.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• Journal of the Korean Institute of Educational Facilities
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• v.12 no.5
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• pp.13-24
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• 2005

This study is the second that aims at offering the basic information on the appropriate spatial organization of the special classes by looking at the relationship between a group of learning activities and a group of playing activities in Elementary and Middle Schools The learning space unit of the special classes should be more flexible for the various learning activities and be prepared in order to correspond to the needs of a territory for different learning appeared according to the degree of handicap, learning ability and the contents of learning. This study dealt with the learning space unit to tackle the problems of special classes. In fact, it is unwise to offer so many different kinds of learning spaces in every school. Due to the manifold and multiple characteristics of handicap, the problem of special classes should be approached by the overall educational system of special educational facilities rather than by a special classes space alone. In this respect, it can be said that this problem should be tackled by reorganization of the special classes in the community through specialization and network system of special class facilities in order to make more effective educational environment.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.4
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• pp.67-74
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• 2014

Departmentalized Classroom System is new school operating system to apply social needs. Recent social needs are characterized as learning environment and self-learning system. The purpose of this study is to provide basic data for equal learning environment condition in middle school applying departmentalized classroom system. This study has progressed through analyzing on 11 remodelling case of middle school in Gangwon-Do. The method of this study is visiting middle schools that operate the system, grasping the condition for environment composition, and investigating and analyzing practical use of the environment. The results of this study are summarized as follows: 1) The space compositions for departmentalized classroom system are generally desirable, but some schools take irrational space composition, especially on home base-teacher laboratory, classroom-teacher laboratory. 2) The space area distributions are different in every school. This result is based on not taking standard criterion on space area distribution.

• Journal of the Korea Furniture Society
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• v.24 no.1
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• pp.42-50
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• 2013

The objective of this study is to explore basic type of character of humans and to suggest a design method of establishing a spatial construction environment for developing effective learning ability based on such type of character. As a range of research, spatial formative language was deduced and space design strategy for the children was suggested through an analysis of spatial requirements by exploring connectivity depending on features of 9 types of character through Enneagram. As a method of research, a process of suggesting a concrete method after defining an element of spatial construction and deducing a formative language for developing and strengthening effective learning ability for each type of character. As a result of research, the methods of children space design strategy for enhancing learning ability for leadership in a future specific fields were suggested through 9 different type of character with image of case study.

• Journal of the Korean Institute of Rural Architecture
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• v.13 no.2
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• pp.47-54
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• 2011

According to the master plan of the Ministry of Education, Science and Technology, departmentalized class system will be extended to all general middle & high schools by 2014 with the exception only of those having less than 6 classes located in small cities in rural areas. Under departmentalized class system, according to class timetable, students need to move from classroom to another classroom and areas where homebases, lounges, media spaces, rest places, and etc. This study has been undertaken to provide architectural data required in planning for student & learning support space for schools operating departmentalized class system, by investigating and analyzing cases in use at schools operating the system in Chungbuk area. As departmentalized class system is increasingly introduced, student & learning support space should be understood newly as spaces indispensable for students.

• Journal of the Korean Institute of Educational Facilities
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• v.5 no.3
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• pp.11-16
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• 1998

The size and location of spaces need to be changed for teaching & learning activities in open education. This study is aimed to investigate how school facilities should be rearranged when the open education is implemented in elementary school. Some considerations such as enlargement of classroom, establishment of open space, and provision of various self-learning spaces are proposed for the rearrangement. It is also recommended that (1) a space for research and conference for teachers, (2) a multi-learning space to be utilized by connecting general and special classrooms, and (3) an open space for exclusive use of one grade or two grades be established.

• Journal of the Korean Institute of Educational Facilities
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• v.10 no.3
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• pp.27-36
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• 2003

This paper aims to analyse facilities and characteristics of management for 21 model schools' open education system. So, we analyzed the class management and the methods of open education, teacher's mind, the shape and form of study group and we investigated teachers' satisfaction rate about the physical space. As a result, it is considered that the change for structure of learning space unit is needed because of the limitation in standard class size by the rule for construction. Considering the decrease of real using space by the space of learning materials or learning furniture, it should enlarge the structure of learning space unit or decrease the number of students. And to use multipurpose space practically as a place of study, it need that the multiple support of study program for teachers by government, support in course of study, giving training opportunity to teachers, distribution of personal management.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.42.1-42.1
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• 2021

In this study, we present a visual explanation of a deep learning solar flare forecast model and its relationship to physical parameters of solar active regions (ARs). For this, we use full-disk magnetograms at 00:00 UT from the Solar and Heliospheric Observatory/Michelson Doppler Imager and the Solar Dynamics Observatory/Helioseismic and Magnetic Imager, physical parameters from the Space-weather HMI Active Region Patch (SHARP), and Geostationary Operational Environmental Satellite X-ray flare data. Our deep learning flare forecast model based on the Convolutional Neural Network (CNN) predicts "Yes" or "No" for the daily occurrence of C-, M-, and X-class flares. We interpret the model using two CNN attribution methods (guided backpropagation and Gradient-weighted Class Activation Mapping [Grad-CAM]) that provide quantitative information on explaining the model. We find that our deep learning flare forecasting model is intimately related to AR physical properties that have also been distinguished in previous studies as holding significant predictive ability. Major results of this study are as follows. First, we successfully apply our deep learning models to the forecast of daily solar flare occurrence with TSS = 0.65, without any preprocessing to extract features from data. Second, using the attribution methods, we find that the polarity inversion line is an important feature for the deep learning flare forecasting model. Third, the ARs with high Grad-CAM values produce more flares than those with low Grad-CAM values. Fourth, nine SHARP parameters such as total unsigned vertical current, total unsigned current helicity, total unsigned flux, and total photospheric magnetic free energy density are well correlated with Grad-CAM values.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.174-174
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• 2000

Q-learning, based on discrete state and action space, is a most widely used reinforcement Learning. However, this requires a lot of memory and much time for learning all actions of each state when it is applied to a real mobile robot navigation using continuous state and action space Region-based Q-learning is a reinforcement learning method that estimates action values of real state by using triangular-type action distribution model and relationship with its neighboring state which was defined and learned before. This paper proposes a new Region-based Q-learning which uses a reward assigned only when the agent reached the target, and get out of the Local optimal path with adjustment of random action rate. If this is applied to mobile robot navigation, less memory can be used and robot can move smoothly, and optimal solution can be learned fast. To show the validity of our method, computer simulations are illusrated.