• 반도체디스플레이기술학회지
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• 제19권1호
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• pp.36-41
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• 2020

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.

• 반도체디스플레이기술학회지
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• 제18권4호
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• pp.46-50
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• 2019

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.

• 반도체디스플레이기술학회지
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• 제19권4호
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• pp.59-64
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• 2020

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 %.

• 반도체디스플레이기술학회지
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• 제19권2호
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• pp.26-30
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• 2020

In this paper, we studied the problem if the experiment number occurring in order to identify defect in scaffold. We need to change each of the 5 print factor to predict defect when printing disk type scaffold using FDM 3d printer. So then the number of scaffold print will be more than 100,000 times. This experiment number is difficult to perform in the field. In order to solve this problem, we have produced a prediction model based on machine learning multiple linear regression using print conditions and defect scaffold data for print conditions. The prediction model produced was verified through experiments. The verification confirmed that the error was less than 0.5 %. We have confirmed that satisfied within the target margin of error 5 %.

• 문화기술의 융합
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• 제8권2호
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• pp.337-342
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• 2022

최근 프린팅 기술은 디스플레이나 연료전지를 포함한 IT 분야에 폭넓게 사용되고 있지만 핵심 부품인 프린터 헤드의 박막을 적층하는 제조공정에서 발생하는 잔류응력 및 열응력으로 인해 기판이 변형되거나 노즐층이 파손되어 잉크가 새거나 원하는 영역으로 토출되지 않는 문제가 발생하고 있다. 따라서 본 논문에서는 보다 견고하고 신뢰할수 있는 구조를 가진 열전사 잉크젯 프린트 헤드 형상을 제안하고자 한다. 기판과 노즐층의 변형을 줄이기 위해 리브, 기둥, 지지벽 및 개별 피드홀과 같은 다양한 형태의 잉크젯 프린트 헤드 구조가 설계되었으며, FEA 해석을 통해 타당성을 검증하였다. 해석 결과 헤드의 최대 응력 및 노즐층 변형이 최소 40~50%로 급격히 감소하였으며 기둥 및 지지벽 형태의 프린터 헤드를 제작하여 노즐층 변형에 의한 균열 및 잉크 누출이 없는 것을 확인하였다. 따라서 제안된 헤드 형상이 정상 방향의 잉크 토출에 기여하며 대면적 프린팅 기술에도 적용될 수 있을 것으로 기대된다.

• 전기학회논문지P
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• 제65권1호
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• pp.57-65
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• 2016

This paper was analyzed the characteristics of piezoelectric inkjet print head using finite element method(FEM). It showed the bending node driving of piezoelectric and relation theory principle consider piezoelectric material characteristics and ink characteristics. From such result we were had the piezoelectric head design and manufacture. It got a this head characteristics through experiment, we confirmed that proper voltage control is possible to through ink drop control experiment of piezoelectric print head. This paper was obtained the suitable ink jetting characteristics that manufacture the control circuit and piezoelectric inkjet print head. This practice product was applied to improvement of PCB electric circuit pattern by etching resist ink that PCB manufactured to complex process over traditional 6 stages can be simpled to 1 stage by inkjet printing technology.

• 펄프종이기술
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• 제44권3호
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• pp.56-62
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• 2012

Recycled pulp therefore play a very important role in the paper industry today as a substitute for virgin pulp. In many countries of the world, the paper industry could not exist as it does without recycled pulp. Because, this is mainly due to economic reasons. Particularly in our country, the additional reason is the scarcity of native pulpwood resources. Therefore, the use of recycled pulp is very important. This study was aimed to apply recycled pulp to textbook paper. So we made a paper containing 30% recycled pulp and investigated about print quality, such as color reproduction, trapping, contrast, dot gain, gloss and print through. The results showed that is similar to existing textbook papers.

• 펄프종이기술
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• 제29권3호
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• pp.60-68
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• 1997

To develop paper coating technology for preventing print mottling, which is recognized as the most common printing problems in using coated papers, ink absorption properties of various coated papers were examined by employing K 8T N and Croda ink absorption tests. The influences of pigment compositions, coat weights and drying methods on these ink absorption properties were examined, and then the variations of ink absorption ratio were analyzed and discussed. It is demonstrated that the variation of Croda ink absorption ratio induced by coat weight variation can be utilized most succesfully to predict print mottling propensity of coating formulations. A systematic analysis approach was suggested that can be employed in the development of the most desirable coating color formulation to achieve target optical properties with the least print mottling.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.633-637
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• 2013

A wide range of applications for Foot Print Recognition System is discussed in this paper. The whole concept works under the principle that foot print is a parameter associated with biometrics that is very common as well as distinct. Its foremost application is at the government hospitals in the under developed and third world nations where there aren't the best of facilities. This system can be applied in the maternity ward of the hospitals for the identification or differentiation of the infants. Till date there has been no specialized system adopted for this purpose. The Foot Print Recognition System will overcome all the defects of any biometrics when applied here. Since the child will be very delicate for an iris scan and it will not be able to open its eyes wide or to correctly place its finger print on the sensor since the hands of a new born infant will be closed for a while. The Foot Print Recognition system can also be implemented in temples where there are cases of theft often reported. This can be used to grant access to the karpagraham of the deity by authorized users alone. These 2 applications of FPRS are discussed in this paper.

• 반도체디스플레이기술학회지
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• 제18권3호
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• pp.25-30
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• 2019

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.