• Korea journal of population studies
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• v.8 no.1
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• pp.139-170
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• 1985

사망원인통계연보는 사망발생 당년에 신고된 사망 자료만 수록하고 있는데, 본 연구에서는 사망원인통계연보에 수록된 사망(당년신고, 또는 비지연신고)은 물론 수록되지 아니한 사망(지연신고)의 사인구조를 파악하고자 한다. 부차적으로, 사인구조를 평가하기 위해서 지연신고의 다양한 특성을 검토하고 있다. 1983년부터 1993년까지 신고된 모든 사망신고를 기초로, 지연신고와 당년신고라는 신고행태에 따라 사인별 사망구성비, 사망률, 사망률성비를 구하였다. 지연신고율이 지속적으로 감소하고 있지만, 지연신고율은 다른 집단보다 여성, 젊은층, 의사진단사망자, 병원사망자에게서 더 높다. 당년신고 사망자의 성별 사인구조와 비교해 볼 때, 지연신고 사망자의 주요 사인구조는 성별에 따라 달라지는데, 남성에게는 감염성질환, 순환기계질환, 호흡기계질환의 비중이 더 커지고, 여성에게는 감염성질환, 호흡기계질환 및 소화기계질환의 비중이 더 커진다. 1983~1993년 동안 신고된 모든 사망에 대한 주요 발견은 다음과 같다. 첫째, 순환기계질환, 악성 종양, 손상 및 중독이 남녀 모두에게 주요 3대 사인이다. 둘째, 만성 간질환, 각종 사고, 폐암, 자살은 남성에게 치명적인 사인으로서 남녀의 성별 사망력 차이를 넓혀주는 원인이다. 세째, 손상 및 중독, 특히 교통사고는 45세 이하의 젊은 층에게 중요한 사인이 되는데 반해, 순환기계질환, 악성 종양, 소화기계질환은 고령층에게 중요한 사인이 된다.

• Journal of the KSME
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• v.20 no.3
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• pp.164-170
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• 1980

현황에서 도출된 문제점을 요약해 보면 크게 다섯가지로 노정되고 있다. 첫째, 정민계측기기 및 시설의 부족 심화 둘째, 정밀기술에 대한 인식의 부족 및 시책 불재 세째, 정밀계측실의 부족 및 계측환경 유지시설의 미흡 네째, 검비정실시의 부진 및 국가 검교정망의 미비 다섯째, 정밀계측 기술인력의 부족 이상과 같은 점은 오늘날 우리나라 기계공업체 전체가 당면한 기술상의 큰 문 제점들로 되어 있다. 앞의 문제점들이 해결되지 않고서는 기계제품의 고급화는 물론이고 기계 공업발전의 큰지장을 초래하게 될 것이다. 그러므로 우리나라 기계공업의 기술향상과 발전체제를 확립하고 80년대의 기간공업으로서의 기틀을 마련함과 동시에 우리나라 경제발전과 수출입국의 주도적 역할을 다 하게 하기 위해서 다음과 같은 기본방향을 제시한다. 첫째, 정밀계측기기의 적정량 확보 둘째, 국가 검교정체계 확대 세째, 정밀계층기기공업의 육성 네째, 검교정실시 제 고를 위한 제도의 개선 다섯째, 정밀계측기술요원의 확보 의무화 특히 K.S업체, 품질관리지정 업체 방위산업지정업체 여섯째, 정밀기술도입 및 정책의 실천 일곱째, 정밀중화학공업화 정책의 실천 정밀기술산업은 오늘날같이 자원부족과 석유 위기시대에 대처할 수 있는 가장 유리한 국 가정책적 유망산업이다. 자원을 절약하고 에너지를 절약할 수 있으며 수출 증진의 고부가가치 주도업종인 정밀기술 산업의 진흥을 위하여 우리나라는 80년대를 정밀기계공업시대로 전환하는 과감한 정책을 실천에 옮기지 않으면 안될 것이다.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.9
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• pp.52-57
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• 2019

The key technology of the fourth industrial revolution is artificial intelligence and machine learning. In this study, FMEA was performed on fuel pumps used as key items in most systems to identify major failure components, and artificial neural networks were built using big data. The main failure mode of the fuel pump identified by the test was coil damage due to overheating. Based on the artificial neural network built, machine learning was conducted to predict the failure and the mean error rate was 4.9% when the number of hidden nodes in the artificial neural network was three and the temperature increased to $140^{\circ}C$ rapidly.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.28-34
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• 2021

The Fourth Industrial Revolution has led to the development of drones for commercial and private applications. Therefore, the malfunction of drones has become a prominent problem. Failure mode and effect analysis was used in this study to analyze the primary cause of drone failure, and blade breakage was observed to have the highest frequency of failure. This was tested using a vibration sensor placed on drones along the breakage length of the blades. The data exhibited a significant increase in vibration within the drone body for blade fracture length. Principal component analysis was used to reduce the data dimension and classify the state with machine learning algorithms such as support vector machine, k-nearest neighbor, Gaussian naive Bayes, and random forest. The performance of machine learning was higher than 0.95 for the four algorithms in terms of accuracy, precision, recall, and f1-score. A follow-up study on failure prediction will be conducted based on the results of fault diagnosis.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.9
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• pp.35-41
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• 2021

A rotor is a crucial component in various mechanical assemblies. Additionally, high-speed and high-efficiency components are required in the automotive industry, manufacturing industry, and turbine systems. In particular, the failure of high-speed rotating bearings has catastrophic effects on auxiliary systems. Therefore, bearing reliability and fault diagnosis are essential for bearing maintenance. In this work, we performed failure mode and effect analysis on bearing rotors and determined that corrosion is the most critical failure type. Furthermore, we conducted experiments to extract vibration characteristic data and preprocess the vibration data through principle component analysis. Finally, we applied a machine learning algorithm called support vector machine to diagnose the failure and observed a classification performance of 98%.

• Journal of the Semiconductor & Display Technology
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• v.17 no.3
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• pp.70-74
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• 2018

In typical spectroscopic ellipsometry, the optical and geometrical properties of thin film and nano pattern can be obtained by measuring the polarization state of light reflected/transmitted from the object by rotating a analyzer or a compensator. We proposed a snapshot spectroscopic ellipsometric system based on a modified Michelson interferometer to overcome the time-consuring measurement principle due to rotating part. The proposed system provides spectral ellipsometric parameters (psi, delta) in real time by using a single spectral interference signal generated in the interferometric polarization module. However, it has a long-term stability problem resulting in delta(k) drift. In this paper, it is experimentally proved that the drift problem is caused by anisotropic refractive index change of the beam intersection layer in beam splitter of interferometer.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.71-76
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• 2019

The diffusion of the drug component of the inflammatory patch into the living tissue was analyzed by laser induced plasma spectroscopy (LIBS). Calcium element, which is a diffusion catalyst of the drug in the inflammatory analgesic patch, is transferred into the body through the diffusion process of the substance. The test pieces used in the experiment are pig skin tissues which are similar to human skin. As a result, the diffusion coefficient D of the calcium element was found to be average $8.24{\times}10^{-2}({\mu}m^2/s)$. Experimental results showed that the most influential factors on the diffusion of materials were temperature variables.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.7
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• pp.48-55
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• 2019

Soldiers have been exposed to the risk of chilblains in cold winters. Recent studies have described sensors and IOT devices that use independent power sources based on piezoelectric energy harvesting. Therefore, the heated shoes with an independent power source have been developed. For the application of energy harvesting to shoes, it is necessary to develop a unique harvester by considering human gait characteristics. Energy harvesters and ceramics were designed and fabricated in this study. The performances of these harvesters and ceramics were evaluated experimentally. Then, the harvesters and ceramics with superior performance were selected and applied to the system. Thereafter, the heating and charging performance of the system was tested under real walking conditions. The results show that the developed system can generate adequate energy to charge the battery and heat the shoes.

• Journal of ILASS-Korea
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• v.26 no.3
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• pp.111-119
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• 2021

Deteriorated agricultural diesel engines using mechanical fuel injection systems have low fuel injection pressures. And they are not equipped with an exhaust gas abatement device, so it produces a lot of exhaust gas. Remanufactured used injectors can reduce emissions because spray characteristics are improved. In addition, remanufacturing is environmentally friendly and economical compared to producing new parts. For efficient injector remanufacturing, it is necessary to conduct a comparison experiment on the spray characteristics of an used mechanical injector and a new injector of the same model. In this study, the spray characteristics of the two injectors were compared by performing an injection quantity measurement and a spray visualization experiment. As a result, the used injector had a larger injection quantity, a shorter spray tip penetration, a wider spray angle and a smaller spray area than the new injector.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.10
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• pp.59-67
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• 2020

Polycarbonate thermoplastic composite materials are anisotropic and exhibit physical properties in the longitudinal direction. Therefore, the physical properties depend on the type and direction of reinforcements. The thermal conductivity, electrical conductivity, and resin impregnation can be controlled by adding carbon nanotubes to polycarbonate resin. However, the carbon fiber used as a reinforcing material is expensive, interfacial adhesion issues occur, and simulation values are different from actual values, making it difficult to perform mathematical analysis. However, carbon nanotubes have advantages such as light weight, rigidity, impact resistance, and reduced number of parts compared to metals. Due to these advantages, it has been applied to various products to reduce weight, improve corrosion resistance, and increase impact durability. As the content of carbon nanotubes or carbon fibers increases, the mechanical properties and antistatic and electromagnetic shielding performance improve. It is expected that the amount of carbon nanotubes or carbon fibers can be optimized and applied to various industrial products.