• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2001년도 Proceeding of KIN-CIN Joint Symposium 2001 on Satellite Navigation/AIS, lntelligence , Computer Based Marine Simulation System and VDR
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• pp.19-25
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• 2001

At present the identification of vessels is still depending on the OOW (Officer Of Wateh) in VTS (Vessel Traffic Service), which is completed by radar, and also by the combination of VHF radio and VHF direction finder. However, with the development of port transportation and economic, this conventional way of identification can't satisfy more and more request for the information that the VTS needs from the vessels. In such a case, the AIS(Automatic Identification System) precept which is based on STDMA (Self-organized Time Division Multiple Access) technique is put forward by IMO (International Maritime Organization). AIS can automatically provide the information, including own ship's identification, type, position, course, speed, and other information to the appropriately equipped coast station and other ships. At the same time it can also automatically monitor and track the nearby ships similarly fitted with AIS. On the basis of describing the whole comprising and the format of transmission information of AIS, this paper mainly studies the key communication techniques in AIS, such as STDMA protocol, net synchronization and GMSK(Gaussian Minimum Shift Keying)technique, and so on. At last this paper briefly introduces the recommendation decided by IMO on forcing the sea-going ships to fixed with AIS equipments, and it continuos with the unexploited potential of AIS if it applies in VTS.

• International Journal of Internet, Broadcasting and Communication
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• 제12권4호
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• pp.83-92
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• 2020

A recent study to determine the fall is focused on analyzing fall motions using a recurrent neural network (RNN), and uses a deep learning approach to get good results for detecting human poses in 2D from a mono color image. In this paper, we investigated the improved detection method to estimate the position of the head and shoulder key points and the acceleration of position change using the skeletal key points information extracted using PoseNet from the image obtained from the 2D RGB low-cost camera, and to increase the accuracy of the fall judgment. In particular, we propose a fall detection method based on the characteristics of post-fall posture in the fall motion analysis method and on the velocity of human body skeleton key points change as well as the ratio change of body bounding box's width and height. The public data set was used to extract human skeletal features and to train deep learning, GRU, and as a result of an experiment to find a feature extraction method that can achieve high classification accuracy, the proposed method showed a 99.8% success rate in detecting falls more effectively than the conventional primitive skeletal data use method.

• Wind and Structures
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• 제10권6호
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• pp.495-510
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• 2007

Wind pressure data have been collected on the tiled roof of a full-scale test house at Silsoe in the UK. The tiled roof was of conventional UK construction with a batten-space and bitumen-felt underlay beneath the interlocking concrete tiles. Pressures were monitored on the outer surface of selected tiles, at several locations within the batten-space, and beneath the underlay. Data were collected both with and without ventilator tiles installed on the roof. Little information appears to exist on the share of wind load between tiles and underlays which creates uncertainty in the design of both components. The present study has found that for the critical design case of maximum uplifts it would be appropriate to assign 85% of the net roof load to the tiles and 15% to the underlay when an internal pressure coefficient of -0.3 is used, and to assign 60% to the tiles and 50% to the underlay when an internal pressure coefficient of +0.2 is assumed (an element of design conservatism is inherent in the apparent 110% net loading indicated by the latter pair of percentage values). These findings indicate that compared with loads implied by BS 6399-2, UK design loads for underlay are currently conservative by 25% whilst tile loads are unconservative by around 20% in ridge and general regions and by around 45% in edge regions on average over roof slopes of $15^{\circ}-60^{\circ}$.

• 수산경영론집
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• 제23권2호
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• pp.91-99
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• 1992

It has been one of the critical issues that the researchers properly evaluate the fishing rights foregone by the coastal development activities like wetland reclamation. Particularly, estimating the productivity of concerned fishing rights is known to play a significant role in their monetary compensation. As a result, this paper attempts to develop a statistical model characterized by Cobb-Douglas production function in conjunction with the fisheries' productivity estimation. The primary hypotheses involving their statistical production function are as below : 1. The quantity of fisheries production is hypothesized to be expressed as a function of capital (K) and labor(L) put into fishing activities. 2. The estimated parameters of K and L are hypothesized to satisfy the conventional condition of production function as a form of Cobb-Douglas. These statistical tests reveal that the shellfish farming productivity heavily depends on the acre of mariculture while the input of labor force also considerably affects its productivity. In case of the fixed net fishing productivity, both the factors of capital and labor similarly affect the marginal change in its productivity. En addition, the productivity of shellfish (arming turns out to follow the increasing returns to scale, whereas that of fixed net fishing comes up with the decreasing returns to scale.

• 대한기계학회논문집
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• 제16권10호
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• pp.1833-1840
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• 1992

본 연구에서는 자동차의 발달에 따른 정비 전문가의 상대적인 능력 감퇴를 보 완하고 진단의 정확성을 높일 수 있도록 소음계측에 의한 인공 지능적 뉴로-퍼지 진단 기법을 연구하였다. 이를 위하여 진단결과에 영향을 미치는 많은 작용변수와 다양한 차량상태 등을 고려함으로서 보다 신뢰성 있는 결과를 산출해내기 위한 퍼지(fuzzy) 추론 방식의 판단법을 도입하였으며, 진단이 실패했을 경우나 입력된 데이터가 충분하 지 못할 경우에 시스템 자체의 지식을 확장시켜 나갈 수 있도록 해밍네트(hamming net )에 의한 패턴인식 기법을 적용하였다. 그리고 컴퓨터 시뮬레이션과 자동차를 대상 으로 고장진단 실험을 실시하여 기존의 진단기법과의 비교를 통한 뉴로-퍼지 진단기법 의 효율성과 알고리즘의 타당성을 검증하였다.

• 한국멀티미디어학회논문지
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• 제21권10호
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• pp.1150-1161
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• 2018

Classification is widely used in medical images to categorize patients and non-patients. However, conventional classification requires a complex procedure, including some rigid steps such as pre-processing, segmentation, feature extraction, detection, and classification. In this paper, we propose a novel convolutional neural network (CNN), called LeukemiaNet, to specifically classify two different types of leukemia, including acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), and non-cancerous patients. To extend the limited dataset, a PCA color augmentation process is utilized before images are input into the LeukemiaNet. This augmentation method enhances the accuracy of our proposed CNN architecture from 96.9% to 97.2% for distinguishing ALL, AML, and normal cell images.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권1호
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• pp.19-30
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• 2015

스마트 TV 제조사들은 스마트 TV 테스트 비용을 줄이기 위하여 테스트 스크립트 자동 실행 환경을 구축하고 있다. 그러나 기존의 테스트 방법은 테스트 스크립트가 테스터에 의해 수동으로 작성되기 때문에, 테스트 스크립트의 재사용성은 높지 않다. 이는 새로운 TV 모델을 위한 테스트 스크립트가 새롭게 작성되어야 함을 의미한다. 본 논문에서는 재사용성이 높은 스마트 TV 테스트 모델 작성법을 제안하고 이를 이용한 스마트 TV 테스트 스크립트 생성 방법을 소개한다. 그리고 NetCast TV에 모델 기반 테스트 스크립트 생성 방법을 적용하여 유효성을 확인하였다.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• 한국농공학회지
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• 제27권4호
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• pp.31-41
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• 1985

This paper compares the estimated total construction and maintenance costs for irrigation canals in six irrigation districts near Pyongtaek. Three conventional canal types were considered: concrete bench flumes, concrete-lined canals, and earth canals. The total expenses for each type were grouped to four catagories: the net construction, land acquisition, maintenance, and other expenses. The construction costs included the assumed costs for conveyance losses from each type of canals. The results from this study support earlier studies that the bench flumes are economically feasible. Initially cheaper conveyance systems like concrete-lined and earth canals demand 'higher maintenance costs and thus, their total expenses are summed to exceed those for the bench flumes within a few years following the construction. Banch flumes are economically justifiable for the main canals of the studying districts. Sensitivity analyses were executed to evaluate the relative importance of each expense to the total cost. The analyses show that total expenses very significantly with the change of the following costs: cost for conveyance losses, net construction, maintenance, and land acquisition, in that order However, other expenses contribute little if not at all to the total. The results indicate that bench flumes should be adopted as main canal structures for most irrigation districts in the Republic.

• 한국철도학회논문집
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• 제10권2호
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• pp.137-145
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• 2007

In traditional financial theory, the discount cash flow model(DCF or NPV) operates as the basic framework for most analyses. In doing valuation analysis, the conventional view is that the net present value(NPV) of a project is the measure of the present value of expected net cash flows. Thus, investing in a positive(negative) NPV project will increase(decrease) firm value. Recently, this framework has come under some fire for failing to consider the options of the managerial flexibilities. Real option valuation(ROV) considers the managerial flexibility to make ongoing decisions regarding the implementation of investment projects and the deployment of real assets. The appeal of the framework is natural given the high degree of uncertainty that firms face in their technology investment decisions. This paper suggests an algorithm for estimating volatility of logarithmic cash flow returns of real assets based on the Black-Sholes option pricing model, the binomial option pricing model, and the Monte Carlo simulation. This paper uses those models to obtain point estimates of real option value with the G7- HSR350X(high-speed train).