• International Journal of Advanced Culture Technology
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• 제8권2호
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• pp.101-108
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• 2020

One difficulty in language learning is the training of reading ability. The improvement on this ability directly affects the process and effect of language learning. At the same time, there are numerous difficulties in actual learning and teaching. Depending on current research, there is two ideas that can utilize to enhance the reading efficiency of learners. One is to amend objective factors; the other is to change subjective factors. Compared with the two ideas, idiosyncratic factors are more manipulable and controllable, so it is more valuable to conduct researches on this. But among the many subjective factors, the degree of their effectiveness is not the same, so this article attempts to compare and analyze the driving effects of two important subjective factors (peer-driven and task-driven) on reading performance. The results show that both factors can have a positive impact on reading comprehension, but different in driving effects. The task-driven has obvious short-term effectiveness; while peer-driven needs to establish its long-term effect on the basis of early coordination and cooperation among team members. Therefore, in order to maximize the achievement of learning, it is necessary to combine strengths and avoid weaknesses according to the characteristics of two factors, so as to help learners improve reading ability most efficiently.

• 한국항행학회논문지
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• 제14권6호
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• pp.874-881
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• 2010

무인기의 자동 비행 제어 시스템은 기체의 형태, 크기, 무게 등의 정적 및 동적 변화에 따라 스스로 비행계수를 조정하여 목표 비행궤적을 정확히 따라가도록 제어할 필요가 있다. 본 논문에서는 PID 제어 기법을 이용하는 비행제어시스템에 기계학습모듈(MLM)을 추가하여 기체의 특성 변화에 따라 제어계수를 비행중 실시간 자동으로 조정하는 시스템을 제안한다. MLM은 선형회귀분석과 보정학습을 이용하여 설계되었으며 MLM을 통해 학습된 제어계수의 적합성을 평가하는 평가모듈(EvM)을 함께 모델링 하였다. 이 시스템은 FDC 비버 시뮬레이터를 기반으로 실험하였으며 그 결과를 분석 제시하였다.

• 수산해양교육연구
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• 제23권1호
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• pp.23-34
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• 2011

The primary purpose of this study was to develop a college adjustment program for freshmen through admission officer system that relies less on test scores and on the various talents evaluated by admissions officers. To help these talented students adjust the new life of the university and enhance their gifts, a college adjustment program was developed with their special needs and characteristics. For that, the survey with 57 students and in-depth interviews with 12 students were conducted. The results revealed that the students wanted to learn study skills, self-management, global mind setting, and life vision and goals setting. Most of the students were worried about their grades because they entered the school with their talents and experience in diverse activities not SAT scores. To promote their academic performance, this program consisted of an academic readiness program which complements students' abilities in primary subjects like math, English, and science, and a potential progress program which is peer-group learning communities based on their own interests like global learning communities, creative learning communities, and service-learning communities. This program was suggested in the context of Comprehensive Development Model. To carry out the program systematically, related organizations and colleges should collaborate with each other.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.51-62
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• 2021

Plant disease is one of the issues that can create losses in the production and economy of the agricultural sector. Early detection of this disease for finding solutions and treatments is still a challenge in the sustainable agriculture field. Currently, image processing techniques and machine learning methods have been applied to detect plant diseases successfully. However, the effectiveness of these methods still needs to be improved, especially in multiclass plant diseases classification. In this paper, a convolutional neural network with a batch normalization-based deep learning approach for classifying plant diseases is used to develop an automatic diagnostic assistance system for leaf diseases. The significance of using deep learning technology is to make the system be end-to-end, automatic, accurate, less expensive, and more convenient to detect plant diseases from their leaves. For evaluating the proposed model, an experiment is conducted on a public dataset contains 20654 images with 15 plant diseases. The experimental validation results on 20% of the dataset showed that the model is able to classify the 15 plant diseases labels with 96.4% testing accuracy and 0.168 testing loss. These results confirmed the applicability and effectiveness of the proposed model for the plant disease detection task.

• 한국BIM학회 논문집
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• 제9권4호
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• pp.31-40
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• 2019

With Building Information Modeling(BIM) becoming the de facto standard for data sharing in the AEC industry, additional needs have increased to ensure the data integrity of BIM models themselves. Although the Industry Foundation Classes provide an open and neutral data format, its generalized schema leaves it open to data loss and misclassifications This research applied deep learning to automatically classify BIM elements and thus check the integrity of BIM-to-IFC mappings. Multi-view CNN(MVCC) and PointNet, which are two deep learning models customized to learn and classify in 3 dimensional non-euclidean spaces, were used. The analysis was restricted to classifying subtypes of architectural walls. MVCNN resulted in the highest performance, with ACC and F1 score of 0.95 and 0.94. MVCNN unitizes images from multiple perspectives of an element, and was thus able to learn the nuanced differences of wall subtypes. PointNet, on the other hand, lost many of the detailed features as it uses a sample of the point clouds and perceived only the 'skeleton' of the given walls.

• 이베로아메리카
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• 제23권2호
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• pp.209-241
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• 2021

Over the last few years, rural areas in northeastern Mexico have present significant changes in social, economic, and territorial aspects linked to the New Rurality. In this context, winemaking has become one of the most dynamic and growing activities in the regional economy. This emerging development has prompted different forms of appropriation and use of this space, but it also highlights the lack of access to knowledge for wine production due to the lack of formal educational centers. As a result, learning communities enable the development of skills and competencies through non-formal educational practices. The objective of this paper is to analyze the role of learning communities in non-formal educational environments, taking as a case study: a collective of small-scale wine producers in Parras de la Fuente, Coahuila. This research focuses on two perspectives of learning: appropriation and technology transfer, and promotion of Mexican wine culture. The main finding was to demonstrate the importance of including educational processes that respond to the context and needs of the community.

• 한국정보교육학회:학술대회논문집
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• 한국정보교육학회 2021년도 학술논문집
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• pp.7-11
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• 2021

본 연구는 초등학교에서 쉽게 적용할 수 있는 소리 데이터를 활용한 블록 기반의 머신러닝 교육 프로그램을 설계하였다. 교육 프로그램은 ADDIE 모형에 따라 사전에 초등학교 교사 70명을 대상으로 실시한 요구 분석을 결과를 바탕으로 그 목표와 방향을 설계하였다. 머신러닝 포 키즈 중 블록 기반의 프로그래밍을 위해 스크래치를 사용하였고 소리 데이터를 활용하여 데이터값의 규칙성을 발견하고 인공지능의 원리를 학습하고 직접 문제를 해결하는 프로그래밍 과정에서 컴퓨팅 사고력을 향상할 수 있도록 교육 프로그램을 설계하였다. 추후의 연구에서 본 교육 프로그램을 적용하고 인공지능에 대한 태도와 컴퓨팅 사고력에 어떤 변화가 있는지 검증이 필요하다.

• 스마트미디어저널
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• 제12권5호
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• pp.88-101
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• 2023

As the definition and role of design changes over time with the times and society, design education needs to update teaching methods to match it. The course design in this study began with an optimisation of the learning model based on previous research and analysis, followed by in-depth interviews, the application of the interview results to the final curriculum design, and finally a questionnaire to verify the positive effects of this teaching model. This teaching model has been applied to teach a pilot class in a university of applied sciences in China. The main characteristics of the course design are Project-Based Learning (PJBL) oriented, team cooperation centric, and an educational model developed based on peer assessment. In every stage of the UI design course, realistic project simulations are adopted, enhancing students' abilities through practical experience, teamwork, and peer assessment. The innovation lies in validating the effectiveness and advantages of this model at every stage of the UI design course, innovating existing teaching methods, optimizing learning models, and combining practice with evaluation. This research found that a project-oriented team course design based on PJBL has a high degree of effectiveness and relevance in each stage of the UI design course, significantly improving students' overall competence. It is expected that the results of this study can be applied in various ways to the course design of the courses that similar to design majors.

• 디지털융복합연구
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• 제18권5호
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• pp.1-8
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• 2020

본 연구는 교사관점에서 초등학교의 지역 위치에 따른 온라인 방과후학교에 대한 요구차이를 파악하여 지역간 우선적으로 추진해야 하는 정책적 사안에 대한 요구도를 도출함으로써, 온라인 방과후학교 프로그램 도입을 위한 단초를 마련하고자 한다. 이를 위한 논의를 체계화하기 위하여 방과후학교 운영 경험이 있는 교사들을 대상으로 설문조사를 실시(n=155)하였다. 이후, 교사가 인식하고 있는 요구와 우선순위를 IPA모형 매트릭스로 분석하였다. 분석결과를 요약하면, 수도권의 경우 '온라인기반교육환경', '행정 운영 효율성', '전문강사 수급'의 대한 요구가 높았다. 반면 비수도권의 경우, '전문 강사 수급', '우수 콘텐츠', '온라인기반교육환경'이 높은 수준의 향상 요구도를 나타내고 있다. 본 연구 결과는 향후 온라인 방과후학교 도입 시, 실질적이면서도 실천가능한 정책을 입안·추진하는데 시사점을 제시할 것이며, 지역별 방과후학교 온라인 프로그램 운영 활성화 및 운영체제 개선을 위한 기초 자료로 참고할 수 있을 것으로 기대한다.

• 한국가정과교육학회지
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• 제15권4호
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• pp.1-22
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• 2003

본 연구는 가정과 교사들의 교수 능력 개선에 대한 일반적인 인식을 조사하고 선행 연구에서 규명된 가정과 교사들의 교수 능력에 대한 인식에 기초하여 가정과 교사의 교수 능력에 관한 교육 요구를 파악하는데 목적을 두었다. 조사 자료는 전국의 중ㆍ고등학교 가정과 교사들을 모집단으로 하였으며, 지역과 학교 급별, 학교 규모 등을 고려한 유층 표집 방법으로 1,104개교를 선정하였다. 분석에는 417개교로부터 접수된 설문조사 자료 616 부가 활용되었으며. 조사 도구는 중요도와 수행 정도를 각각 7단계, 5단계 리커트 척도로 구성되었다. 가정과 교사들이 인식한 교수 능력에 대한 중요도와 수행 정도를 기초로 교수 능력 향상에 필요한 교육 요구를 분석한 결과 7가지 영역 중 ‘지역 사회 및 다양한 인적 자원과의 연계 능력’, ‘학습 공간 및 학습 자료 구성 관리 능력’, ‘다양한 수업 전개 및 평가 능력’ 등 세 영역에서 교육 요구가 큰 것으로 나타났다. 가정과 교사들의 교수 능력 개선을 위한 일반적인 인식으로는 ‘가정과 교사 양성 프로그램 개선(4.13)’보다 ‘현직 가정과 교사 연수 프로그램의 다양화 및 전문화(4.50)’에 대한 동의 정도가 높았다. 가정과 교사들은 이들 두 가지 요구에 대하여 교직 경력과 학교 설립 유형에 따라 유의한 차이를 나타냈다.