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정무영 ( Moo Young Jung ),정재호 ( Jae Ho Chung ) 한국손해사정학회 2010 손해사정연구 Vol.4 No.-
본 연구에서는 간접투자시장에서 부동산펀드 현황을 분석하고 발전방안을 연구하고자 한다. 분석결과에 의하면 부동산펀드가 주식형펀드와 채권형펀드에 비하여 경기호황기뿐만 아니라 경기침체기에도 안정적인 수익률을 실현하고 있음을 확인할 수 있다. 본 연구결과에 의하면 부동산펀드시장의 문제점으로는 부동산펀드에 대한 인식부족, 부동산인덱스미비, 물법 사모펀드 방지를 위한 제도의 미비, 전문성과 투명성 부족, 공모펀드의 부족 등으로 조사되었다. 이러한 문제점을 해결하는 부동산펀드의 발전 방안으로 부동산펀드에 대한 인식제고가 필요하며, 부동산관련 자료의 축적과 인덱스개발이 우선되어야 한다고 본다. 또한 사모펀드를 활용한 투자 상품의 다양화가 필요하며, 자산운용의 전문성과 투명성 제고와 다수의 투자자 참여유도를 위해 사모, 공모제도의 보완의 필요성을 제시하고 자 한다. With world economy recession, real estate investment market were facing difficulties despite fast link of real estate market and finance market, also real estate indirect investment will emerge as a alternative to real estate direct investment. Indirect real estate investment can expect not only stable profit by investment to various kinds of real estate with small amount fund, also has different feature with bond and stock that has profit risk. Real estate fund is expected to grow the most stable investment alternative based on indirect investment service portfolio in an aspect that real estate fund does its job as an alternative investment service investment market despite recent world recession. In terms of real estate fund which was operated by concentrating as the public form not private form, public form is expected to increase as an incentive to public fund is expanded. As a result, diverse real estate funds will be established will grow continually in aspect of scale as well. Also, if protection for investors is intensified by being applied ``principle of relevance`` recognitions of real estate fund will be improved. In case that recession is ended and fund industry emerges again, share of real estate fund in whole fund market will be increased.
Characterization of Electro-deposited Ni-P Layer by Using Dynamic Nano-Indentation Method
Moo Young Jung(정무영),Youl Baik(백열),Bo Kyeong Kang(강보경),Yong Choi(최용),Hyuk Joo Kwon(권혁주) 한국표면공학회 2018 한국표면공학회지 Vol.51 No.4
Dynamic nano-indentation method was applied to characterize thin electroformed Ni-P layers. The Ni-P layers were produced in a sulphamic acid bath at 50℃ in 0.02 A/cm² for 10-60 minutes. The chemical analyses by XRD and EDX showed that the Ni-P layers were very fine grains with mainly Ni3P with Ni. The surface roughness determined by atomic force microscopy increased with thickness, which was relative to the surface morphology. The nano-hardness and the stiffness of the thin Ni-P layers with thickness of 1.9, 6.2 and 7.5 μm were 5.52, 6.52 and 6.77 [GPa] and 56.7, 76.2 and 108.0 [μN/nm], respectively. The elastic modulus of the Ni-P layer increased with thickness such as 37.29, 54.50 and 78.76 [GPa], respectively. The surface roughness of the electroplated Ni-P layers with diverse thickness was 8.66, 18.56 and 35.22 [nm], respectively. The enhanced nano-mechanical properties were related to mainly residual stress of the Ni-P layers.
회전형상 부품에서의 가공형상 특징의 자동인식에 관한 연구
이경휘(Kyung-Huy Lee),정무영(Moo-Young Jung) 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
This paper presents a comprehensive methodology of automatic feature recognition for rotational parts. The parts of interest are rotational without deviation. In stage one, IGES formatted data of 2D engineering drawings are transformed into three independent graphs through upperhalf profile. In stage two, recursive evaluations are made to recognize features and relevant information is acquired. Finally, an example is evaluated to demonstrate the recognition power of the developed algorithm for rotational features.
김의석(Eui-Suk Kim),정무영(Moo-Young Jung) 대한전자공학회 1992 대한전자공학회 학술대회 Vol.1992 No.10
This paper presents a methodology for automatic feature extraction used in a vision system of FMC (Flexible Manufacturing Cell). To implement a robot vision system, it is important to make a feature database for object recognition, location, and orientation. For industrial applications, it is necessary to extract feature information from CAD database since the detail information about an object is described in CAD data. Generally, CAD description is three dimensional information but single image data from camera is two dimensional information. Because of this dimensional difference, many problems arise. Our primary concern in this study is to convert three dimensional data into two dimensional data and to extract some features from them and store them into the feature database. Secondary concern is to construct feature selecting system that can be used for part recognition in a given set of objects.