• Title/Summary/Keyword: DMAN

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A Study on Taxi Route Extraction Based on a Node-Link Model for Aircraft Movements on Airport Surface (노드링크 모델 기반 항공기 공항 지상이동 경로 추출 기법에 대한 연구)

  • Jeong, Myeongsook;Eun, Yeonju;Kim, Hyounkyoung;Jeon, Daekeun
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.25 no.3
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    • pp.51-60
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    • 2017
  • Estimation of the taxi-out and taxi-in times of aircraft on a airport surface is one of the essential features of Departure Manager (DMAN). Especially for an airport with multiple runways and large ramp areas, estimation of the taxi-out and taxi-in times are mainly dependent on the taxi routes on airport surface. This paper described the method of automatic extraction of the the taxi routes using the ASDE track data and the Dijkstra algorithm based on the node-link model of a airport surface movements. In addition, we analyzed the ground operation status of Incheon International Airport using the extracted taxi routes.

A Development of Data-Driven Aircraft Taxi Time Prediction Algorithm (데이터 기반 항공기 지상 이동 시간 예측 알고리즘 개발)

  • Kim, Soyeun;Jeon, Daekeun;Eun, Yeonju
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.26 no.2
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    • pp.39-46
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    • 2018
  • Departure Manager (DMAN) is a tool to optimize the departure sequence and to suggest appropriate take-off time and off-block time of each departure aircraft to the air traffic controllers. To that end, Variable Taxi Time (VTT), which is time duration of the aircraft from the stand to the runway, should be estimated. In this paper, a study for development of VTT prediction algorithm based on machine learning techniques is presented. The factors affecting aircraft taxi speeds were identified through the analysis of historical traffic data on the airport surface. The prediction model suggested in this study consists of several sub-models that reflect different types of surface maneuvers based on the analysis result. The prediction performance of the proposed method was evaluated using the actual operational data.

Microbial Transformation of Two Prenylated Naringenins

  • Han, Fubo;Lee, Ik-Soo
    • Natural Product Sciences
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    • v.23 no.4
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    • pp.306-309
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    • 2017
  • Microbial transformation of $({\pm})$-6-(1,1-dimethylallyl)naringenin (6-DMAN, 1) and $({\pm})$-5-(O-prenyl) naringenin-4',7-diacetate (5-O-PN, 2) was performed by using fungi. Scale-up fermentation studies with Mucor hiemalis, Cunninghamella elegans var. elegans, and Penicillium chrysogenum led to the isolation of five microbial metabolites. Chemical structures of the metabolites were determined by spectral analyses as $({\pm})$-8-prenylnaringenin (3), (2S)-5,4'-dihydroxy-7,8-[(R)-2-(1-hydroxy-1-methylethyl)-2,3-dihydrofurano]flavanone (4), $({\pm})$-5-(O-prenyl)naringenin-4'-acetate (5), $({\pm})$-naringenin-4'-acetate (6), and $({\pm})$-naringenin (7), of which 5 was identified as a new compound.