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신명철,최형섭,최주 대한금속재료학회(대한금속학회) 1974 대한금속·재료학회지 Vol.12 No.3
本硏究는 Ni을 Mn으로 代替시킨 高Mn耐熱鋼의 時效過程中 析出相과 機械約 性質에 關하여 硏究하였다. Mn과 Cr의 含量을 달리하는 鋼에다 높은 含量의 室素를 添加시켰고 그 위에 强化元素인 Nb, Mo, W, B 등을 添加하여 合金의 時效硬化性, 高溫 引張强度, 耐酸化性 및 鍛造性을 調査하였다. 그 結果 위의 諸性質들이 旣存 耐熱鋼에 떨어지지 않았다. 本 合金에서 나타나는 析出相은 M_(23)C_6, Nb(C, N), Cr₂N 및 σ相이었으며 主要 硬化相은 M_(23)C_6 임이 判明되었다. The principal objective of this investigation was to examine precipitated phases during aging sequence and mechanical properties of high manganese heat resisting steels in which manganese was completely substituted for nickel. The influence of alloying elements on the aging hardenability, elevated temperature tensile strength, oxidation resistance and forgeability was investigated by adding elements such as niobium, molybdenum, tungsten, and boron to the steels containing various amounts of manganese and chromium and high content of nitrogen. It was found that the major hardening phase was M_(23)C_6 particles. The other phases identified were Nb(C, N), Cr₂N and σ phase.
신명철,이건중,이승환,조석현,김경래,정진혁 대한이비인후과학회 2011 대한이비인후과학회지 두경부외과학 Vol.54 No.3
Background and Objectives Nitric oxide (NO) is present in high concentrations in the upper respiratory tract. The physiological role of this mediator is to contribute to the local host’s defense, modulate ciliary motility and serve as an aerocrine mediator in helping to maintain adequate ventilation-perfusion matching in the lung. Subjects and Method The purpose of the study was to assess the relationship of nasal NO (nNO) and exhaled NO (eNO) in nasal airway disease patients. NO concentration was measured using a chemiluminescence analyzer. nNO was analyzed by aspiration at a sampling flow rate of 700 mL/min with velum closure. eNO was analyzed during expiration against a constant resistance of 10 cm H2O. Results NO concentration of the normal control group (n=32) was compared with that of the allergic rhinitis group (n=31) and the rhinosinusitis with that of the nasal polyp group (n= 30). The mean nNO level in the control group was 241±89 ppb and eNO was 20.5±6.4 ppb. The mean nNO level was significantly increased in the allergic rhinitis group (332±125 ppb) but decreased in the chronic sinusitis group (89±55 ppb). The mean eNO level was significantly increased both in the allergic rhinitis group (26.9±10.1 ppb) and chronic sinusitis group (29.8±12.8 ppb). Conclusion nNO concentration was increased in patients with allergic rhinitis and decreased in patients with chronic sinusitis; however, eNO was increased in both patients. This shows that patients with upper respiratory inflammation may also have lower respiratory inflammation, supporting the concept of ‘one airway, one disease’. This study shows that measurement of NO is useful for the study or evaluation of nasal diseases.
신명철,송영석,권동승,서정태,이충용,Shin Myeongcheol,Song Young Seog,Kwon Dong-Seung,Seo Jeongtae,Lee Chungyong The Institute of Electronics and Information Engin 2005 電子工學會論文誌-TC (Telecommunications) Vol.42 No.12
본 논문에서는 다중안테나를 갖는 공간 다중화 시스템에서 주어진 채널에 대한 maximum likelihood 검출기의 성능을 수식적으로 유도하였다. 벡터 심볼 오차율을 구하기 위해 nearest neighbor의 방향을 나타내는 에러벡터를 정의하였다. 전송 벡터 심볼이 랜덤한 채널에 의해 변환 될 경우 확정적으로 4개의 nearest neighbor를 가짐을 정의된 에러벡터의 특성을 이용해 입증하였다 변형된 구 검출기로부터 획득 가능한 에러벡터와 최소거리 정보를 바탕으로 주어진 랜덤 채널 하에서 벡터 심볼 오차율을 수식적으로 도출하였다. 유도된 벡터 심볼 오차식을 검증하기 위해, 랜덤 채널을 unitary 채널, dense 채널, sparse 채널로 분류한 후 각 채널 상황에서 유도된 결과 식을 모의 실험 결과와 비교하였다. 모의실험 결과로부터 유도된 벡터 심볼 오차식이 다양한 랜덤 MIMO 채널에서 ML 검출기의 성능을 잘 근사하고 있음을 입증하였다. The performance of maximum likelihood(ML) detection for the given channel is analyzed in spatially multiplexed MIMO system. In order to obtain the vector symbol error rate, we define error vectors which represent the geometrical relation between lattice points. The properties of error vectors are analyzed to show that all lattice points in infinite lattice almost surely have four nearest neighbors after random channel transformation. Using this information and minimum distance obtained by the modified sphere decoding algorithm, we formulate the analytical performance of vector symbol error over the given channel. To verify the result, we simulate ML performance over various random channel which are classified into three categories: unitary channel, dense channel, and sparse channel. From the simulation results, it is verified that the derived analytical result gives a good approximation about the performance of ML detector over the all random MIMO channels.