Earticle

산사태는 인명과 사회 경제적 인프라에 심각한 피해를 초래하는 대표적인 자연재해로, 위험지역의 정밀 한 공간 분할 및 조기 탐지가 재난관리에 필수적이다. 본 연구에서는 U-Net 딥러닝 아키텍처를 기반으로 패치 크기(128×128, 256×256)에 따른 산사태 위험지역 자동 분류 성능을 비교·분석하였다. 연구 대상지는 경북 예천군 보곡면의 급경사지로, 드론 영상 및 포인트 클라우드 자료를 활용해 0.1m 해상도의 디지털 표고 모델(DEM)을 구축하고, 이를 딥러닝 학습 및 평가에 적용하였다. 분석 결과, 128×128 패치 크기 모델은 전체 정확도 70.5%의 정확도를 기록했으며, 비위험과 위험 클래스에서 F1-score 0.582, 0.599를 보여 균형 잡힌 분류 성능을 나타냈다. 반면 256×256 패치 모델은 65.96%의 정확도와 매우 낮은 0.248, 0.007의 F1-score를 기록했으며, NoData 클래스에서는 0.786의 높은 F1-score를 보여 대부분의 예측이 NoData 영역에 집중됨을 나타냈다. 이러한 결과는 작은 패치 크기가 지역적 지형 변동성을 포착하고 산사태 감지 성능을 향상시키는데 더 효과적임을 시사한다.

Landslides are natural disasters that cause severe damage to human life and socio-economic infrastructure, making precise spatial delineation and early detection of hazardous areas essential for disaster management. This study compares automated classification performance of landslide hazard zones using U-Net deep learning architecture with different patch sizes (128×128 and 256×256). The study area is a steep slope in Bogok-ri, Hyoja-myeon, Yecheon-gun, Gyeongbuk Province, where a high-resolution DEM (0.1 m) was constructed using drone imagery and point cloud data. The 128×128 patch model achieved 70.5% accuracy with F1-scores of 0.582 and 0.599 for non-hazard and hazard classes, respectively, indicating balanced performance. In contrast, the 256×256 patch model yielded 65.96% accuracy, much lower F1-scores of 0.248 and 0.007, and a higher NoData F1-score of 0.786, reflecting predictions focused on NoData zones over hazard areas. Results suggest smaller patch sizes better capture local terrain variability and enhance landslide detection performance.

학교 교육 환경은 정보사회의 발달 속도만큼 급격하게 발전을 하고 있다. 한국교육학술정보원(2005)의 ‘U-러닝 코리아 로드맵’ 연구는 u-러닝 교육 연구의 발전 방향을 제시해 주었으며, u-러닝 연구학교를 통한 실험이 지난 3년간 이루어졌다.연구학교들은 개인용 모바일 디바이스가 주어져 학습자들이 이동성을 갖고 능동적으로 무선환경에서 학습 할 수 있었으며, 나아가 사이버 가정학습을 통한 가정에서의 학습활동과 연계가 이루어지게 되었다. 이러한 변화에 따라 각 교과에서도 변화하는 교육환경에 맞추어 새로운 교육 패러다임에 맞는 교육 모델을 개발하여 적용해야 한다.실과 교육은 특히 체험 위주의 학습 활동이 많으며 활동 공간도 교실 외에도 실습실, 재배원 및 교외의 다양한 환경에서 학습이 이루어져야 한다. 그러한 환경 요소의 중요성으로 학교에서 실질적 교육활동을 하기에 어려운 점이 많은 것이 현실이다. u-러닝 환경은 이러한 문제점의 해결에 크게 기여할 것으로 기대 된다.이 연구에서는 지난 3년간에 걸쳐 이루어졌던 u-러닝 시범학교 운영결과를 토대로 u-러닝 교육 관련 요소들을 추출하여 다음 단계의 발전적 u-러닝 환경으로서 Push형 정보제공 서비스, 상황인지 서비스, 행위 제안 서비스를 위한 요소들 간의 서비스 모델을 제안 하였다.제시된 모델은 실과 교육의 체험학습의 활성화와 실과 수업의 질적 향상을 위해 크게 기여하게 될 것으로 예상하며, 다음 단계 u-러닝 연구의 기본 모델이 될 것으로 기대한다.

Educational environment of school has rapidly changed as fast as the development of information technology. The Report of KERIS(2005), u_learning Korea Load-Map, shows the direction of u-Learning research and u-Learning research schools have applied and studied as the map for the last three years(2005~2007). At the research schools, students can use the personal mobile devices- PDA, T-PC, UMPC, etc- for learning. Furthermore blended learning in school has connected students with their home learning by LMS. According to this change of new paradigm, the school education must be developed and applied the new educational model towards ubiquitous society. Especially there are a lot of classes based on the experiential learning method using various practical laboratories, school garden or off-school learning facilities in the practical course. However these subjects could not realized in school because of the environment condition. We expect that u-Learning make solve these problems for a practical course. This study extracts the educational elements from the case studies of the research schools for the last three years and presents the new service model of the educational elements for u-school based on u-information service, context-aware service and u-behavior proposal service as the next step of u-Learning. The proposed service model is expected to improve the realization of the practical classes based on the experiential learning method and to be a basic model for a study of the next stage.

컴퓨터와 통신기술이 발전함에 따라 최근의 교육환경은 학습자 스스로 학습내용, 학습 시간 및 학습 순서를 선택하고 조작하는 유비쿼터스 학습방향으로 발전하고 있다. 이러한 유비쿼터스 학습에서는 학습의 효과를 높이기 위하여 전문가의 도움이나 조언 등이 절실히 필요하다. 따라서 유비쿼터스 학습에 스케폴딩과 멘토링의 방법을 접목시키면 학습효과를 극대화 시킬 수 있다. 본 논문에서는 스캐폴딩과 e-멘토링을 활용한 u-SM(Ubiquitous Scaffolding and Mentoring) 교수학습모형을 설계한다. 또한 설계된 u-러닝 교수학습모형을 구현하고 적용하여 학생들의 학업성취도와 학습태도에 미치는 영향을 알아보고, u-러닝 환경에서 다양한 교수학습 방법의 적용 가능성을 검증해보았다.

According to develop the computer and communication technology, recently educational environment is growing to ubiquitous learning with direction which select the studying content, studying time and a studying order oneself. In order to raise effect of studying in the ubiquitous learning(u-Learning), the help or advice of the specialist is necessary earnestly. Accordingly, if it will combine the scaffolding and the mentoring in the u-Learning, a studying effect will be maximize. This paper design the u-SM(Scaffolding and Mentoring) teaching and learning model which applies the scaffolding and e-mentoring. In addition, it embodies and applies the designed u-SM model. Then it examines it affects in studying achievements and attitudes of students and verifies the application possibility of the u-SM teaching and learning.

정보통신기술의 발전과 지식정보 사회의 등장은 교육 및 훈련분야에도 거대한 변화를 가져왔다. 특히, 유비쿼터스 시대가 다가옴에 따라 e-Learning 또한 u-Learning으로 진화하려 하고 있다. 이는 지금까지와는 또 다른 형태로 교수-학습자 환경이 변화함을 말한다. 본 논문에서는 교육환경의 발전에 따른 다양한 학습 콘텐츠의 관리 방법을 제안, 구현하고 운영플랫폼 분석을 통하여 콘텐츠의 활용을 극대화 할 수 있는 LCMS를 제안하였다.

Development of Information Technology and knowledge information society transfer brought huge change of education training field. According as Ubiquitous society approaches, e-Learning will be evolving by u-Learning. This presages in other form with present that professor-learner environment may change. This study proposes and embodied administration method of various studying contents by development of Learning environment, And through operation platform analysis, proposed LMS that can do practical use of contents efficiently.

This research understands an ubiquitous technology and space in terms of the convergence of the electronic space and the physical space. Accordingly, we analyzed the ubiquitous schoolroom space and introduced the space factors for the implement of actuality u-learning environment. Also, we developed the ubiquitous schoolroom design component based on proposed space factors, and presented the schoolroom space model by the actuality example. And, we presented u-learning properties based on 21th century modern space development for forecasting the future u-learning environment. The following is the analyzing contents and the result in this study. First, we analyzed the property of the physical space, the electronic space, and the ubiquitous space created by convergence of these space. We could know that ubiquitous schoolroom space have major property such as flexibility, softness, communication, simultaneity and also have space structure of neuron and rhizome. Additionally, we know that the ubiquitous schoolroom space becomes the optimization when these two structures exist simultaneously. Accordingly, a ubiquitous schoolroom space model based on neuron structure and rhizome structure has to be developed in the future. Second, the realizable ubiquitous schoolroom space is designed by teaching and learning models including ubiquitous technology. These factors are based on flexibility. Accordingly, we described the ubiquitous schoolroom space is reconstructed by teaching and learning models. Third, we represented the ubiquitous schoolroom space have to structure of communication. And structure of communication is enable to integrate private learning spaces and group learning spaces. Therefore, the developed ubiquitous schoolroom space design will be based on communication of variety learning spaces. Fourth, we analyzed the ubiquitous schoolroom space have a lot of learning resources and accesses without barriers. And also ubiquitous schoolroom space have social space enable to communication between teacher and leaner. Accordingly, the ubiquitous learning space have to multi communication spaces not only desk and chair arrangement but also soft spaces arrangements.

This paper presents the concepts of ubiquitous computing technology to construct a ubiquitous learning environment that enables learning to take place anywhere at any time. This ubiquitous learning environment is described as an environment that supports students’ learning using digital media in geographically distributed environments. The u-learning model is a web-based e-learning system that could enable learners to acquire knowledge and skills through interaction between them and the ubiquitous learning environment. Students are allowed to be in an environment of their interest. The communication between devices and the embedded computers in the environment allows learner to learn while they are moving, hence, attaching them to their learningenvironment.

The purpose of this research is for the establishment of Ubiquitous learning (U-learning) based synchronous, asynchronous and hybrid mode. This paper proposed the implementation of learning between student and teacher of service provider in u-space, which is not limited to traditional e-learning system. Student-focused testing services include: excellent test paper creation/deletion/registration; 7 phase framework; database development; and PDA page design. This system allows students to be supported with an electronic input, authentication, distribution, monitor, gathering, grading and inquiring phase and supports learning session dependent multicasting. The devices used include PDAs, mobile phones, portable computers and tablet PDAs. This system is to become a more capable student learning environment so that student can get student’s learning done more efficiently. The development of a ubiquitous learning environment combines the advantages of an adaptive learning environment with the benefits of ubiquitous computing and the flexibility of mobile devices.

U-learning, which is based on ubiquitous learning environment, is a more creative and more individually suited learning model that the learner can study anytime and/or anywhere. The project-based learning using ubiquitous environment is the use of in-depth and rigorous classroom projects to facilitate learning and assess student competence. Project-based learning needs to allow students to not only make real life connections but also implement decision making skills, interacting with others, learning and applying new techniques. To provide individually suited skin-care services to customers, it is essential that the estheticians get enough experiences and new techniques through field practice. To meet the demand of the customers, the esthetitian might acquire the latest techniques through u-learning. In this study, u-learning based project teaching and learning model, which may be able to conduct education that meet for demander's request in these days, are suggested. From Skin Care subject, the unit-The skin care theory and practice-is selected. Among the 3 chapters in this unit, the 1st chapter-The caring methods according to skin types-is applied to this teaching and learning model.

This study examined the U3A, the learning organization of older people in the UK. The characteristics of U3A in the UK were examined from the multilevel analysis framework, adapted from Bray(2004). This british model was the 'self-help model', which was initiated due to neo-liberalism in 1970s. UK U3A had the bottom-up style of management; flexible role of teacher and student; and buffet or cafeteria style of subjects. U3A was connected to the tradition of adult liberal education, having no assessment, non-vocational programme and independent curriculum. In U3As, members preferred discussion method and academic subjects like philosophy, psychology, and history etc. Considering members' background, many of them used to have professional jobs; high educational level; and currently have good financial and health condition. Therefore, as Findsen(2005) pointed out, the UK U3A was related to middle-class culture.

정보 통신 기술의 발달은 전산화, 정보화, 지식 정보화 과정을 거쳐 현재 차세대 패더다임인 유비쿼터스화 단계에 이르렀다. 시간과 장소에 구애받지 않고 언제 어디서나 창의적이고 효율적인 학습자 중심의 교육환경을 제공할 수 있는 u-러닝 기술은 7차 교육과정 수행과 함께 필수적인 요소로 부각되고 있다. 최근 교육과정이 u-러닝 환경으로의 변화에 따라 교수 학습 체계 역시 변화가 예상된다. 그리고 ICT를 활용한 교수 학습 모형과 교과별 콘텐츠에 대한 개발이 활발한 이유도 현재 u-러닝이 적극 추진되면서 교육환경에 대한 새로운 요구와 필요성이 증대되고 있기 때문이다. 따라서 교육환경인 u-러닝 시대에 맞추어 교과목에 대한 교수-학습 모형 연구가 이루어 져야 할 것이다. 본 연구에서는 선행 연구된 학습모형을 비교, 분석하여 유비쿼터스와 u-러닝에 대한 특성과 기능, 유비쿼터스 컴퓨팅 기술에 대해 고찰한다. 그리고 기존 컴퓨터 교과 분석을 통하여 컴퓨터교과의 중요성과 교육방법 영역, 컴퓨터교과 교수-학습 모형에 대한 연구를 통해 u-러닝 환경에서의 컴퓨터 교육을 위한 프로젝트 기반 교수-학습 모형을 설계하고 구현한다.

정보 통신 기술의 발달은 전산화, 정보화, 지식 정보화 과정을 거쳐 현재 차세대 패더다임인 유비쿼터스화 단계에 이르렀다. 시간과 장소에 구애받지 않고 언제 어디서나 창의적이고 효율적인 학습자 중심의 교육환경을 제공할 수 있는 u-러닝 기술은 7차 교육과정 수행과 함께 필수적인 요소로 부각되고 있다. 최근 교육과정이 u-러닝 환경으로의 변화에 따라 교수 학습 체계 역시 변화가 예상된다. 그리고 ICT를 활용한 교수 학습 모형과 교과별 콘텐츠에 대한 개발이 활발한 이유도 현재 u-러닝이 적극 추진되면서 교육환경에 대한 새로운 요구와 필요성이 증대되고 있기 때문이다. 따라서 교육환경인 u-러닝 시대에 맞추어 교과목에 대한 교수-학습 모형 연구가 이루어 져야 할 것이다. 본 연구에서는 선행 연구된 학습모형을 비교, 분석하여 유비쿼터스와 u-러닝에 대한 특성과 기능, 유비쿼터스 컴퓨팅 기술에 대해 고찰한다. 그리고 기존 컴퓨터 교과 분석을 통하여 컴퓨터교과의 중요성과 교육방법 영역, 컴퓨터교과 교수-학습 모형에 대한 연구를 통해 u-러닝 환경에서의 컴퓨터 교육을 위한 프로젝트 기반 교수-학습 모형을 설계하고 구현한다.

Recently building up of u-learning oriented teaching and learning system has been expanded rapidly, However domestic junior college's challenging for adapting it might be slower than other educational body's doing, and in that result it might be paid more or be taken longer time to improve their old system effectively. Now, it is very time for them to develop and implement u-learning oriented teaching and learning system quickly. This paper offers and draws the core factors to design ubiquitous teaching and learning model systematically through investigation of worldwide recent technology and R&D, patent, service and standardization tendency related with u-learnig modeling.

본 연구의 목적은 유비쿼터스 테크놀로지 컴퓨팅에 기반하여 성공적인 미래교실학습을 위한 교수학습모델을 제시하려는 데에 있다. 이를 위해 본 연구에서는 먼저 미래교실의 특성을 유비쿼터스의 공간적 특성에 따라 분산성, 융합성, 상황성의 세 가지 측면에서 살펴보고, 미래교실에서의 u-러닝 학습을 위한 주요 교수설계원리들을 도출한 후, 이를 구체화할 수 있는 교수학습전략들을 제안하였다. 구체적으로 미래교실학습을 위한 교수학습설계원리로 첫째, 학습과제 측면에서 실제적이고 복잡한 과제를 제시하여야 하며, 둘째, 학습절차 측면에서 상황에 대한 인지, 자기 주도적 및 협동적 학습을 통한 자료의 수집, 자료 분석 및 해결책 고안, 일반화와 추론의 단계를 거치고, 셋째, 학습매체 측면에서 유비쿼터스 컴퓨팅 테크놀로지의 잠재적 가능성을 극대화하고, 넷째, 상호작용 측면에서 유비쿼터스 컴퓨팅을 통한 가상 학습공동체를 형성하고 지원하는 것과 함께 안내된 참여를 통하여 인지활동을 조장하여야 함을 제시하였다.

The purpose of this study is to develop an instructional design model designed for ubiquitous learning at future classrooms. To achieve this purpose, the characteristics of future classrooms, first were examined. The future classrooms using ubiquitous computing technology were characterized by distributed cognition, an unity of both electronic spaces and physical spaces, and situated contexts equipped with artificial intelligence. An instructional design model for ubiquitous learning was built based on extensive literature reviews on the field of distributed intelligence. Instructional design elements, first were identified. The identified elements include authentic task, affordance of ubiquitous learning, distributed learning procedure, interaction strategies with guided inquiry and social learning, and authentic evaluation. Next, specific instructional-learning strategies were suggested for learning task, media use, interaction strategies, respectively. Finally, some recommendations for future studies were suggested in order to build a more valid instructional design model for u-learning at future classrooms.

Computer Education form is rapidly growing and has been developed in a variety of forms such as off-line. on-line, multimedia, ICT education . These forms are changed to E-Learning, Blended-Learning and Ubiquitous-Learning. Ubiquitous-Learning model schools have already been running on a national scale according to the policy of the Ministry of Education. In this study, to understand the necessity for the Ubiquitous-Learning and Ubiquitous-Environment, the awareness of the Ubiquitous environment and U-learning in model schools and general schools is analyzed and compared. Through this study, a desirable model about Ubiquitous-Learning and Environment will be explored.

본 연구의 목적은, U-net 딥러닝 모델을 이용하여 CT 영상에서의 노이즈 감소 효과를 다양한 하이퍼 파라미터를 적용하여 평가하였다. 노이즈가 포함된 입력 영상 생성을 위하여 Gaussian 노이즈를 적용하였고, 총 1300장의 CT 영상에서 train, validation, test 셋의 비율을 8:1:1로 유지하여 U-net 모델을 적용하여 학습하였다. 연구에서 적용된 하이퍼파라미터는 최적화 함수 Adagrad, Adam, AdamW와 학습횟수 10회, 50회, 100회와 학습률 0.01, 0.001, 0.0001을 적용하였으며, 최대 신호 대 잡음비와 영상의 변동계수 값을 계산하여 정량적으로 분석하였다. 결과적으로 U-net 딥러닝 모델을 적용한 노이즈 감소는 영상의 질을 향상시킬 수 있으며 노이즈 감소 측면에서 유용성을 입증하였다.

In this study, the performance evaluation of image quality for noise reduction was implemented using the U-net deep learning architecture in computed tomography (CT) images. In order to generate input data, the Gaussian noise was applied to ground truth (GT) data, and datasets were consisted of 8:1:1 ratio of train, validation, and test sets among 1300 CT images. The Adagrad, Adam, and AdamW were used as optimizer function, and 10, 50 and 100 times for number of epochs were applied. In addition, learning rates of 0.01, 0.001, and 0.0001 were applied using the U-net deep learning model to compare the output image quality. To analyze the quantitative values, the peak signal to noise ratio (PSNR) and coefficient of variation (COV) were calculated. Based on the results, deep learning model was useful for noise reduction. We suggested that optimized hyper parameters for noise reduction in CT images were AdamW optimizer function, 100 times number of epochs and 0.0001 learning rates.