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오판진(Oh, Pan-jin),유상언(Yoo, Sang-eon) 학습자중심교과교육학회 2022 학습자중심교과교육연구 Vol.22 No.7
Objectives The purpose of this study is to analyze how to hold a pencil in the first grade of elementary school Korean and to find ways to help students write correctly. Methods A case study method was used among the qualitative studies, and interviews with Yoo Sang-eon for a single case of how to hold a pencil, Hangul files related to his claims, YouTube materials, student handwriting materials, and testimonials were used in this study. Textbooks and teacher s guides were analyzed in a multi-layered manner, along with texts and letters. Results As a result, it was found that there was a problem with the position of the finger guiding in the current 2015 revised curriculum for the first grade textbook. In other words, if you look at the position of your fingers when writing, holding a pencil while holding your thumb and index finger in a circle is not the optimal way. Also, it is not appropriate to place your elbows on the desk when writing, so it is a guideline that needs to be corrected. On the other hand, Yoo Sang-eon s method of holding a pencil is a better way to help students write correctly. Here s how to hold a pencil correctly, as he suggests. First, put the tip of the thumb and middle finger together to make a round shape, and then place the pencil on the nail area of the middle finger and the area next to the bone where the index finger begins. Second, lift your thumb upwards, bend it at a right angle, and press the pencil gently from above. Third, bend the forefinger close to a right angle and put it lightly between the thumb and middle finger without straining. Fourth, write in such a way that the wrist or arm where you are writing extends slightly over the edge of the desk. Conclusions If you write according to the shape and position of the finger holding the pencil as suggested by Yoo Sang-eon, the force of the finger applied to the pencil is maintained evenly, so that you can write more correctly. 목적 이 연구의 목적은 초등국어 1학년의 연필 잡는 법을 분석하고, 학생들이 바른 글씨를 쓰도록 돕는 방안을 모색하는 데 있다. 방법 이 연구에서는 질적 연구 가운데 사례 연구라는 연구 방법을 사용하였고, 유상언의 연필 잡는 법이라는 단일 사례를 대상으로 그와의 인터뷰 자료와 그가 주장하는 내용과 관련한 한글 파일, 유튜브 자료, 학생들의 글씨 자료, 소감문이나 편지글 등과 함께 교과서와 교사용지도서를 다층적으로 분석하였다. 결과 그 결과 현행 2015 개정 교육과정 1학년 교과서에서 안내하고 있는 손가락의 위치에 문제가 있다는 것을 발견하였다. 즉, 글씨를 쓸 때 손가락의 위치를 보면, 엄지와 검지를 둥그렇게 모으면서 연필을 잡는 방법은 최적의 방법이 아니라는 것이다. 그리고 글씨를 쓸 때 팔꿈치를 책상 위에 올리도록 한 것도 적절하지 못해서 수정해야 할 지침이다. 이와 달리 유상언이 제안하는 연필을 바르게 잡는 방법은 학생들이 글씨를 바르게 쓰는 데 도움을 주는 더 나은 방법이다. 그가 제안하는 연필을 바르게 잡는 방법은 다음과 같다. 첫째, 엄지손가락과 가운뎃손가락 끝을 맞잡아 둥글게 만든 후 가운뎃손가락의 손톱 부위와 집게손가락이 시작되는 뼈 옆 부위에 연필을 올린다. 둘째, 엄지손가락을 위로 들어서 직각으로 꺾은 후 연필을 위에서 지그시 눌러 준다. 셋째, 집게손가락도 직각 가깝게 꺾어서 엄지와 가운뎃손가락의 사이에 힘주지 않고 살짝 붙여만 준다. 넷째, 글씨 쓰는 손목이나 팔이 책상 모서리에 약간 걸치는 정도로 해서 글씨를 쓴다. 결론 유상언이 제안하는 연필 잡는 손가락의 모양과 위치에 따라 글씨를 쓰면, 연필에 가해지는 손가락의 힘이 균등하게 유지되어 편안한 자세로 글씨를 더 바르고 쉽게 쓸 수 있다.
오상언(Sang-Eon Oh),박종안(Jong-An Park) 한국정보기술학회 2016 한국정보기술학회논문지 Vol.14 No.5
In this paper, we propose a efficient method to formalize vehicle number plate by using radon transform to detect the object and by rotating the plate angle according to horizontal-vertical projection. The proposed method is as follows. Firstly, we get composition of line and determine the contour of vehicle number plate using radon transform. Secondly, we show histograms of horizontal-vertical projection from processed image of vehicle plate without out of contour. And we get rotation angle using histogram equalization decision. Thirdly, we can get a formalized plate using rotation angle. Simulation results showed that our proposed method is superior to the vehicle number plate extraction and formalization based on rate of formalization 96.25%.
그레이레벨과 영역 성장법을 이용한 CT 복부 영상의 장기 자동 분할
오상언(Sang-Eon Oh),강성관(Sung-Kwan Kang),장민혁(Min-Hyuk Chang),박종안(Jong-An Park) 한국정보기술학회 2014 한국정보기술학회논문지 Vol.12 No.1
In this paper, we propose a useful method to devide the organs automatically in the abdominal CT images. The proposed method is using that each organs in the abdominal CT images has the different gray-level and calculating the accumulation. We extract the organ’s seed point by calculating the 1/4 accumulation on the basis of the histogram of the foreground by Otsu method. Based on the extracted seed points, we detect liver area and kidney/spine area by using the automatic region growing method for image segmentation. Finally, It re-extract the seed points through a process of thinning in the detected area and apply it to a adjacent slice by doing so, it detect another liver area and kidney/spine area. For accuracy assessment of the proposed method, we compare it with the manual segmentation result, and that we verify that the result of the proposed method for liver and kedney/spine segmentation is sufficiently accurate based on 5.7% VOE and 2.3% AVME.
오상언(Sang-Eon Oh),박종안(Jong-An Park) 한국정보기술학회 2015 한국정보기술학회논문지 Vol.13 No.6
In this paper, when a object contour is detected in images, we propose a new method to compensate impulsive chain-code and to linearize contour using chain-code. The proposed method is followed these steps. Chain-code is get using contour’s direction from the contour detected image through the image preprocessing process. If continuous same chain-codes have over 3 pixels length, assume that the codes are impulsive contour and replace with non-linear value. When continuous branchs have same value based on compensated chain-code, connect the contour on the basis of a branch that has 10 over pixels. When similar chain-codes are repeated, they are redistributed with steady repetitiveness. For accuracy assessment of the proposed method, we compare it with contour detecting result of sobel filter, and that we verify that the result of the proposed method compensate impulsive contour and it is accurate to contour based on 0.944 Precision and 0.927 Recall.
오상언(Sang-Eon Oh),이용은(Yong-Eun Lee),박종안(Jong-An Park) 한국정보기술학회 2017 한국정보기술학회논문지 Vol.15 No.7
It is an important task to obtain features and algorithms for the query image in image retrieval. In this paper, we propose a novel retrieval technique that analyzes the features of the query image and gives the corresponding adaptive weighted value. First we go through preprocessing of the query image and seek objects based labeling. Then area, corners, color, and compactness as the features are extracted. After that, we give adaptive weighted value according to the features. And we retrieve similar images based the query image features. The simulation is applied to such single object images, multiple objects images, simple background images and complex images. The results showed that our proposed algorithm is excellent in terms of precision and recall in case of obscure query features.