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일반품질연구 : 무전도 금속 증착을 위한 하전 입자빔 전처리 공정의 타당성 연구
나명환 ( Myung Hwan Na ),박영식 ( Young Sik Park ),심하몽 ( Ha Mong Shim ),전영호 ( Young Ho Chun ) 한국품질경영학회 2014 품질경영학회지 Vol.42 No.2
Purpose: Since several problems were found when present non-conducting metal coating process was appliedto mass production, we study and develop to improve those problems. Methods: In this paper, a couple of analysis methods such as surface hardness, XPS spectrum analysis, morphology,and reflection ratio were used. Results: This paper suggest a new possibility of Non-conducting thin metal coating method that has qualityof mass production phase without UV coating process. Conclusion: By the result of analysis, we can set optimized process conditions of the electro deposition coatingusing electron beam.
딥러닝 알고리즘을 이용한 토마토에서 발생하는 여러가지 병해충의 탐지와 식별에 대한 웹응용 플렛폼의 구축
나명환 ( Na¸ Myung Hwan ),조완현 ( Cho¸ Wanhyun ),김상균 ( Kim¸ Sangkyoon ) 한국품질경영학회 2020 품질경영학회지 Vol.48 No.4
Purpose: purpose of this study was to propose the web application platform which can be to detect and discriminate various diseases and pest of tomato plant based on the large amount of disease image data observed in the facility or the open field. Methods: The deep learning algorithms uesed at the web applivation platform are consisted as the combining form of Faster R-CNN with the pre-trained convolution neural network (CNN) models such as SSD_mobilenet v1, Inception v2, Resnet50 and Resnet101 models. To evaluate the superiority of the newly proposed web application platform, we collected 850 images of four diseases such as Bacterial cankers, Late blight, Leaf miners, and Powdery mildew that occur the most frequent in tomato plants. Of these, 750 were used to learn the algorithm, and the remaining 100 images were used to evaluate the algorithm. Results: From the experiments, the deep learning algorithm combining Faster R-CNN with SSD_mobilnet v1, Inception v2, Resnet50, and Restnet101 showed detection accuracy of 31.0%, 87.7%, 84.4%, and 90.8% respectively. Finally, we constructed a web application platform that can detect and discriminate various tomato deseases using best deep learning algorithm. If farmers uploaded image captured by their digital cameras such as smart phone camera or DSLR (Digital Single Lens Reflex) camera, then they can receive an information for detection, identification and disease control about captured tomato disease through the proposed web application platform. Conclusion: Incheon Port needs to act actively paying
나명환(Myung Hwan Na),박영지(Youngji Park),위소영(So Young Wi),신보미(Bomi Shin),김미은(Mieun Kim) 한국신뢰성학회 2011 신뢰성응용연구 Vol.11 No.2
Traditionally, one uses a method of straight-line recognition to evaluate quality of product or service. One can satisfy with the product or service if their physical requirement of are met some criterions and can not satisfy them if their physical requirement are not met. Kano, et al(1984) introduce two dimensional Quality model to evaluate quality of product or service. They classify Quality Characteristic of product and service to three categories; satisfying quality, attractive quality, expected quality. In this paper, 17 evaluation features in 6 categories of smart-card are obtained from Focus-interview and Brainstorming and classified into 3 categories of quality model by Kano"s two dimensional method. This classification is expected to provide a guideline for evaluation of smart-card.
나명환(Myung Hwan Na),함상민(Sang Min Ham) 한국신뢰성학회 2011 신뢰성응용연구 Vol.11 No.3
In this paper, we analyze statistically the data set of first leak time of water pipeline. We classify first the leak time data by pipe type, location, diameter of pipe and, length of pipe. We perform the analysis of variance to indicate that there are significant difference of mean of the time between levels of the factor and also compare the distribution of levels using the multiple box-plot. When there are the difference of the mean, we perform the least significant test to find out what levels of the facor has a different mean.
이은경,나명환,이윤동,Lee Eun-Kyung,Na Myung Hwan,Lee Yoon-Dong 한국통계학회 2005 응용통계연구 Vol.18 No.1
본 연구에서는 얼랑(Erlang)분포의 규모모수에 대 한 축차확률비검정(SPRT)과 관련된 적분방정식의 정학한 해를 구하는 법을 살펴보기로 한다. 축차확률비검정에서 그 평균 표본 개수, 그리고 1종 오류 확률과 2종 오류 확률은 프레돔 형태의 적분 방정식으로 나타나게 된다. 이러한 적분 방정식은 보통 가우시안 쿼드러쳐(qudrature)를 이용하여 근사적으로 그 해를 구하는 것이 일반적이다. 얼랑분포의 경우 이러한 적분방정식의 해가 정확하게 구할 수 있음이 알려져 있다. 본 연구에서는 얼랑분포에서 그 해를 구하는 구체적 방법을 살펴보기로 한다. In this paper, we propose a method to evaluate the solutions of the renewal equations related to SPRT for Erlang distribution. In SPRT, the Average Sample Number(ASN) and type I or type II error probabilities are shown in Fredholm type integral equations. The integral equations are generally solved by the approximation method using Gaussian quadrature. For Erlang distribution, it has been known that the exact solutions of the equations exist. We propose the algorithm to solve the equations.
박영식,심하몽,나명환,송호천,윤상후,장근삼,Park, Young Sik,Shim, Ha-Mong,Na, Myung Hwan,Song, Ho-Chun,Yoon, Sanghoo,Jang, Keun Sam 한국통계학회 2014 응용통계연구 Vol.27 No.4
최근 휴대단말기 시장에서는 블루투스, GPRS, EDGE, 3GSM, HSDPA 등과 같은 높은 대역폭의 RF를 사용하고 있다. 높은 대역폭의 RF 영역에서는 높은 면저항(Sheet resistance)을 갖는 무전도 금속박막 코팅 방법이 사용되고 있는데, 기존의 무전도 금속증착은 사출물 세정, UV 하도 코팅, 금속증착, UV 중도 코팅, 상도 코팅 등 다수의 복합 공정으로 이루어져 있다. 특히 하도공정은 금속 증착(Sputtering)과 일괄 처리가 어려워 생산성이 낮고 생산원가 상승의 원인이기도 하다. 따라서 이를 극복하기 위하여 최근 Na 등 (2014)은 무전도 금속코팅에서 Primer 대체를 위한 전자빔의 표면처리의 가능성을 가능함을 보였다. In this paper, 플라즈마 생성 전자빔 소스(Plasma generated electron beam source)를 활용하여 PC/ABS 수지 사출물의 공정을 실험계획법에 의한 전자빔 조사 조건을 탐색하여, 즉, 수지 표면처리공정 조건을 탐색하여, 그 실험 결과를 분석하여, 진공전처리공정 개발 및 양산공정라인의 처리의 최적 조건을 찾고자 한다. High bandwidth RF such as Bluetooth, GPRS, EDGE, 3GSM, HSDPA is papular in the mobile phone market. A non-conducting metal coating process requires an e-beam deposition of metal, two steps of UV hard coating primer and top coating; however, it is inefficient. We navigate to the electron beam irradiation conditions(resin surface treatment conditions) in the PC/ABS resin injection process. By analyzing the experimental results, we find the optimum development conditions for the electro deposition pre-treatment process and mass production lines using the plasma generated electron beam source.