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인공지지체 불량 분류를 위한 기계 학습 알고리즘 성능 비교에 관한 연구
이송연,허용정 한국반도체디스플레이기술학회 2020 반도체디스플레이기술학회지 Vol.19 No.3
In this paper, we create scaffold defect classification models using machine learning based data. We extract the characteristic from collected scaffold external images using USB camera. SVM, KNN, MLP algorithm of machine learning was using extracted features. Classification models of three type learned using train dataset. We created scaffold defect classification models using test dataset. We quantified the performance of defect classification models. We have confirmed that the SVM accuracy is 95 %. So the best performance model is using SVM.
3D프린팅 공정 중 공기 습도에 따른 출력물의 인장 강도에 관한 연구
이송연,허용정 한국반도체디스플레이기술학회 2021 반도체디스플레이기술학회지 Vol.20 No.4
Scaffolds protect the sensor in the body. Scaffolds are made of a bioabsorbable polymer. The polymer process is sensitive to humidity. Inside of the 3D printer has been improved to control the humidity. Specimens were produced by injection molding and 3D printer. 3D printed specimens were printed under various humidity conditions. We measured tensile strength of the injection-molded specimen and tensile strength of the 3d printing specimen. We compared tensile strength of the injection-molded specimen and tensile strength of the 3d printing specimen. Tensile strength of the injection-molded specimen is 557 kgf/㎠. We confirmed tensile strength of the specimen was highest at 741 kgf/㎠ when the humidity was 10 %. We confirmed lower the humidity, higher tensile strength of the polymer product.
3SC 실용트리즈와 머신러닝을 이용한 기공을 가진 인공지지체 제조문제 해결에 관한 연구
이송연,허용정 한국반도체디스플레이기술학회 2019 반도체디스플레이기술학회지 Vol.18 No.3
In this paper, we have analyzed manufacturing problems of the scaffold with pores using FDM 3D printer and PLGA. We suggested the solutions using 3SC practical TRIZ. We selected the final solution used machine learning. We reduced number of experiments using most influential factor after analysis print factors. We printed the scaffold and measured pore size. We created the regression model using python tensorflow. The print condition data of measured pore size was used as training data . We predicted the pore size of printed condition using regression model. We printed the scaffold using the predicted the print condition data. We quantitatively compare the predicted scaffold pore size data and the measured scaffold pore size data. We got satisfactory result.
다중 선형 회귀 기반 기계 학습을 이용한 인공지지체의 사각 기공 형태 진단 모델에 관한 연구
이송연,허용정,Lee, Song-Yeon,Huh, Yong Jeong 한국반도체디스플레이기술학회 2020 반도체디스플레이기술학회지 Vol.19 No.4
In this paper, we found the solution using data based machine learning regression method to check the pore shape, to solve the problem of the experiment quantity occurring when producing scaffold with the 3d printer. Through experiments, we learned secured each print condition and pore shape. We have produced the scaffold from scaffold pore shape defect prediction model using multiple linear regression method. We predicted scaffold pore shapes of unsecured print condition using the manufactured scaffold pore shape defect prediction model. We randomly selected 20 print conditions from various predicted print conditions. We print scaffold five times under same print condition. We measured the pore shape of scaffold. We compared printed average pore shape with predicted pore shape. We have confirmed the prediction model precision is 99 %.
묽은 용액의 성질에 대한 화학전공 예비교사들의 이해 및 화학교사 양성교육에 대한 인식 사례 연구
이송연,김성혜,백성혜,Lee, Song-Yeon,Kim, Soeng-Hye,Paik, Seoung-Hey 대한화학회 2010 대한화학회지 Vol.54 No.6
이 연구에서는 화학교육을 전공하는 4명의 예비교사들과 화학을 전공한 2명의 예비교사들을 대상으로 고등학교 화학II 교과서에 제시된 "묽은 용액의 성질" 단원에 관련된 개념의 이해를 비교하였다. 연구결과, 예비교사들 중에 고등학교 화학II 교과서에 제시된 내용을 깊이 있게 이해하는 예비교사들이 많지 않았으며, 묽은 용액의 성질에 관련된 오개념을 가지고 있는 경우도 나타났다. 그리고 사범대학에서 화학교육을 전공한 예비교사들의 이해수준과 비사범대학에서 화학을 전공한 예비교사들의 이해수준은 차이가 없는 것으로 나타났다. 연구에 참여한 대부분의 예비교사들은 대학과 상관없이 그들의 예비교사 교육과정에서 실천적 지식이 부족하다고 느끼고 있었다. We compared the understanding of 4 pre-service teachers of chemistry education major and 2 pre-service teachers of chemistry major related to conceptions of "properties of dilute solutions" chapter in high school Chemistry II textbooks. As results, few pre-service teachers understood fully the concepts of high school Chemistry II textbooks. Some pre-service teachers had misconceptions related to properties of dilute solutions. We found that few differences existed between the pre-service teachers' understanding regardless of whether they took a major in chemistry education of a education college or a major in chemistry of noneducation college. Most of the pre-service teachers who attended this research recognized the lack of practical knowledge in their pre-service teacher curriculum.
병렬 구조의 다중 필터 CNN을 이용한 골절합용 판의 불량 탐지 모델에 관한 연구
이송연,허용정 한국정밀공학회 2023 한국정밀공학회지 Vol.40 No.9
Bone plates are a medical device used for fixing broken bones, which should not have a crack and hole defect. Defect detection is very important because bone plate defect is very dangerous. In this study, we proposed a defect detection model based on a parallel type convolution neural network for detecting bone plate crack and pore deformation. All size filters were different according to the defect shape. A convolution neural network detected pore defects. Another convolution neural network detected the crack. Two convolution neural networks simultaneously detected different defect types. The performance of the defect detection model was measured and used for the F1-score. We confirmed that performance of the defect detection model was 98.4%. We confirmed that the defect detection time was 0.21 seconds.
머신 러닝 회귀 방안을 이용한 인공지지체 기공 크기 예측모델 성능에 관한 연구
이송연,허용정,Lee, Song-Yeon,Huh, Yong Jeong 한국반도체디스플레이기술학회 2020 반도체디스플레이기술학회지 Vol.19 No.1
In this paper, We need to change all print factors when which print scaffold with 400 ㎛ pore using FDM 3d printer. Therefore the print quantity is 10 billion times, So we are difficult to print on workplace. To solve the problem, we used the prediction model based machine learning regression. We preprocessed and learned the securing print condition data, and we produced different kinds of prediction models. We predicted the pore size of scaffolds not securing with new print condition data using prediction models. We have derived the print conditions that satisfy the pore size of 400 ㎛ among the predicted print conditions of pore size. We printed the scaffolds 5 times on the condition. We measured the pore size of the printed scaffold and compared the average pore size with the predicted pore size. We confirmed that error was less than 1%, and we were identify the model with the highest pore size prediction performance of scaffold.
5 Step 실용트리즈 기법을 이용한 PLGA 인공지지체의 변형 문제 해결에 관한 연구
이송연,허용정,박종순 한국반도체디스플레이기술학회 2017 반도체디스플레이기술학회지 Vol.16 No.4
In this paper, we have studied the deformation problem of the scaffold caused by the FDM type 3D printer. The Practical TRIZ technique was used to solve the deformation problem of the scaffold generated from the adhesion surface between the scaffold and the bed. The Practical TRIZ methodology was used to derive the solution and the experiment was conducted on the derived solution. As a result of evaluating the experimental results obtained for the solution, it was found that the deformation of the scaffold was much improved to the satisfactory level.
머신 러닝을 이용한 인공지지체 기공 크기 예측 모델에 관한 연구
이송연,허용정 한국반도체디스플레이기술학회 2019 반도체디스플레이기술학회지 Vol.18 No.4
In this paper, We used the regression model of machine learning for improve the print quantity problem when which print scaffold with 400 ㎛ pore using FDM 3d printer. We have difficult to experiment with changing all factors in the field. So we reduced print quantity by selected two factors that most impact the pore size. We printed and measured scaffold 5 times under same conditions. We created regression model using scaffold pore size and print conditions. We predicted pore size of untested print condition using the regression model. After print scaffold with 400 ㎛ pore, we printed scaffold 5 times under same conditions. We compare the predicted scaffold pore size and the measured scaffold pore size. We confirmed that error is less than 1 % and we verified the results quantitatively.
TRIZ 기법을 이용한 FDM방식 3D프린터 출력물의 휨 현상개선에 관한 연구
이송연,허용정,박종순 한국반도체디스플레이기술학회 2016 반도체디스플레이기술학회지 Vol.15 No.2
3D printer is the equipment of the system for sequentially layer laminated in the materials. Now 3D printer used in various fields such as, semiconductor, electricity automobile, medical and various types of output method and material. In this paper, we studied about the improvement on warpage due to shrinkage of product from 3D printer of FDM(Fused Deposition Modeling) type, we proposed measures systematically to solve warpage problem using of 6SC(6 Step Creativity) method of practical TRIZ. After experimented with product prototypes experiment, we verified effect about solution.