• 제어로봇시스템학회논문지
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• 제10권8호
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• pp.742-747
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• 2004

Outdoors we can easily acquire our accurate location by GPS. However, the GPS signal can't be acquired indoors because of its weak signal power level. Adequate positioning method is demanded for many indoor positioning applications. At present, wireless local area network (WLAN) is widely installed in various areas such as airport, campus, and park. This paper proposes a positioning algorithm using WLAN signal strength to provide the position of the WLAN user indoors. There are two methods for WLAN based positioning, the signal propagation method uses signal strength model over space and the empirical method uses RF power propagation database. The proposed method uses the probability distribution of the power propagation and the maximum likelihood estimation (MLE) algorithm based on power strength DB. Test results show that the proposed method can provide reasonably accurate position information.

• 한국산학기술학회논문지
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• 제10권1호
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• pp.122-127
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• 2009

본 본 논문은 항공 교통 체계에서 가장 중요하게 고려되는 안전한 항공체계에 대한 연구를 중심으로 보안구조를 검토하고 보안모델을 제시하였다. 분석된 내용은 항공서비스 분야 관련 보안기술을 기반으로 국제적인 기술 동향과 함께 국내의 항공체계에 대한 보안모델을 다루고 있다. 항공통신 네트워크의 보안 프레임워크에서는 항공과 지상 데이터링크 보안기술, 항공체계에 따른 보안구조를 분석하였고 U-information HUB 모델의 보안구조를 제시하였다. U-information HUB 보안구조는 항공사, 공항 네트워크, 항공기, 관련 정부기관 등과 연동범위를 포함하고 있다.

• 한국항행학회논문지
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• 제4권2호
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• pp.114-131
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• 2000

항공사는 항공기단을 편성하거나 특정노선에 투입할 항공기종을 결정할 때 항공기 좌석수가 어느 정도인 항공기로 선택할 것인지 심각하게 고려하지 않을 수 없다. 또한 공항의 혼잡 완화 정책과 같은 외부요인도 항공기 크기 선정에 작용하기도 한다. 이때 두 가지 요인을 고려하여 항공기의 크기를 결정하게 되는데, 첫째는 항공기의 운영비용이고 둘째는 예상되는 수익과 시장 점유율이다. 항공사를 이윤 극대화를 목표로 하는 기업이라고 가정하면 좌석 수에 의한 항공기종별 비용과 수익을 이용해 최적의 항공기종을 선택할 수 있다. 본 연구는 다음과 같은 4단계의 분석을 통하여 항공사의 항공기 크기 선택 행위를 분석한다: (1) 항공기 좌석 수에 따른 운영비 분석 (2) 시장점유율과 수익분석 (3) 비용, 수익분석에 의한 단위노선의 항공기 크기 선정 (4) 네트워크 단위의 항공기 크기 선정, 항공사는 증가하는 수요를 수용하기 위해 운항횟수를 늘리거나, 대형기종으로 교체해야 하는데 이때 항공기 크기 선정 방법을 잘 선택하여 대처해야 할 것이다. 공항이 혼잡한 경우는 운항횟수 증가가 어려워 대형기로의 교체가 불가피한데 이때도 이윤율 증가를 고려한 의사결정이 필요할 것이다.

• 한국지역지리학회지
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• 제21권3호
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• pp.474-488
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• 2015

국책사업의 하나로 추진되는 대규모 공공시설을 둘러싼 갈등은 우리나라가 겪는 많은 갈등에서 중요한 부분을 차지한다. 공공시설의 건설로 인한 환경파괴와 지역공동체의 해체 등에 대한 부정적인 인식이 증가하였고, 일자리와 기업의 투자를 기대할 수 있는 사업의 경우 지역 간 경쟁이 심화되었다. 이러한 이유로 지역 간 경쟁과 갈등은 기존 연구에서 자주 다루어져 왔다. 이를테면, 갈등을 최소화할 수 있는 행정적 절차 및 거버넌스, 이슈를 만들어내는 언론의 역할 등에 대한 다수의 연구가 존재한다. 본 연구는 갈등이 구성되는 공간적 방식을 분석한다. 동남권 신공항을 둘러싼 갈등의 공간적 스케일을 분석한 결과, 실제 신공항 입지에 따른 이익과 손해의 공간적 범역과 갈등의 주체가 되는 공간적 단위는 상이하였다. 또한, 사업의 진행 과정에서 갈등의 주체들은 이합집산을 통해 자신들의 이해관계를 관철시킬 수 있는 공간적 단위를 구성해가는 다양한 스케일의 정치를 보여주고 있다. 이는 지역개발을 둘러싼 갈등은 단순히 지역개발이라는 정책의 집행과 실천의 필연적 부산물이 아닌 지역정치의 역동성과 결합하는 과정으로 바라볼 필요가 있음을 보여준다.

• Journal of Information Technology Applications and Management
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• 제20권1호
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• pp.87-106
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• 2013

This study is to explore the airline network patterns of Incheon and Narita International Airports using passenger flight departure and arrival data of the two airports. The so-called Origin-Destination data is collected from the airports' websites and some of the important data items are flight number, city of origin, destination city, departure/arrival time, number of flights, and delay time. A snowflake schema dimensional model is proposed and implemented. Tableau Public, a well-known visual analytic tool, is used to connect the dimensional model and played an important role in navigating the data space to find interesting and visual patterns among corresponding airports and airlines. For the efficiency of analyzing this spacious data mart, data visualization method was used. Four types of visualization method proposed by Yau was used; visualizing patterns over time, visualizing proportions, visualizing relationships, and visualizing spatial relationships. The strength of connectivity of each flight segments is calculated to evaluate the degree of globalization of Seoul and Tokyo. We anticipate that various patterns and new findings produced by the data mart would provide airline managers, airport authorities, and policy makers in the field of travel and transportation with insightful information.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.190-194
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• 2018

The runway visual range is one of the important factors that decide the possibility of taking offs and landings of the airplane at local airports. The runway visual range is affected by weather conditions like fog, wind, etc. The pilots and aviation related workers check a local weather forecast such as runway visual range for safe flight. However there are several local airfields at which no other forecasting functions are provided due to realistic problems like the deterioration, breakdown, expensive purchasing cost of the measurement equipment. To this end, this study proposes a prediction model of runway visual range for a local airport by applying convolutional neural network that has been most commonly used for image/video recognition, image classification, natural language processing and so on to the prediction of runway visual range. For constituting the prediction model, we use the previous time series data of wind speed, humidity, temperature and runway visibility. This paper shows the usefulness of the proposed prediction model of runway visual range by comparing with the measured data.

• 한국ITS학회 논문지
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• 제19권4호
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• pp.116-125
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• 2020

GNSS 신호를 이용하여 서비스를 제공하는 국가기반 시설이 재밍의 영향을 받는다면 막대한 피해가 발생할 것으로 예상된다. 이를 방지하고자 적절한 방법으로 재밍신호의 발생 감지, 종류판별 및 재밍원 위치추정을 수행하는 범국가적인 GNSS 재밍 모니터링 네트워크 구성이 필요하다. 본 논문에서는 GNSS 신호를 사용하는 자율주행 차량의 테스트베드인 K-시티와 인천 국제 공항에서 GNSS 재밍 신호의 존재 여부 및 종류를 확인하고자 실측실험을 통하여 재밍신호 환경을 확인하는 지표로 2-D 이미지를 생성하고, 분석을 통하여 재밍신호 발생 감지, 종류 판별 및 재밍신호 세기 추정을 수행한다. 그 결과, K-시티에서 L2대역에서 CWI신호가 감지되었고, 인천 국제 공항에서 L5대역에서 CWI신호가 존재하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권1호
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• pp.136-151
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• 2016

Flexible large-scale WLANs are now widely deployed in crowded and highly mobile places such as campus, airport, shopping mall and company etc. But network management is hard for large-scale WLANs due to highly uneven interference and throughput among links. So the traffic is difficult to predict accurately. In the paper, through analysis of traffic in two real large-scale WLANs, Granger Causality is found in both scenarios. In combination with information entropy, it shows that the traffic prediction of target AP considering Granger Causality can be more predictable than that utilizing target AP alone, or that of considering irrelevant APs. So We develops new method -Granger Causality and Vector Auto-Regression (GCVAR), which takes APs series sharing Granger Causality based on Vector Auto-regression (VAR) into account, to predict the traffic flow in two real scenarios, thus redundant and noise introduced by multivariate time series could be removed. Experiments show that GCVAR is much more effective compared to that of traditional univariate time series (e.g. ARIMA, WARIMA). In particular, GCVAR consumes two orders of magnitude less than that caused by ARIMA/WARIMA.

• Smart Structures and Systems
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• 제26권2호
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• pp.241-251
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• 2020

Due to the undeniable importance of approximating the concrete compressive strength (CSC) in civil engineering, this paper focuses on presenting four novel optimizations of multi-layer perceptron (MLP) neural network, namely artificial bee colony (ABC-MLP), grasshopper optimization algorithm (GOA-MLP), shuffled frog leaping algorithm (SFLA-MLP), and salp swarm algorithm (SSA-MLP) for predicting this crucial parameter. The used dataset consists of 103 rows of information concerning seven influential parameters (cement, slag, water, fly ash, superplasticizer, fine aggregate, and coarse aggregate). In this work, the best-fitted complexity of each ensemble is determined by a population-based sensitivity analysis. The GOA distinguished its self by the least complexity (population size = 50) and emerged as the second time-effective optimizer. Referring to the prediction results, all tested algorithms are able to construct reliable networks. However, the SSA (Correlation = 0.9652 and Error = 1.3939) and GOA (Correlation = 0.9629 and Error = 1.3922) performed more accurately than ABC (Correlation = 0.7060 and Error = 4.0161) and SFLA (Correlation = 0.8890 and Error = 2.5480). Therefore, the SSA-MLP and GOA-MLP can be promising alternatives to laboratorial and traditional CSC evaluative methods.

• Journal of Korea Trade
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• 제25권8호
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• pp.57-74
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• 2021

Purpose - This study aims to analyze the characteristics of network construction by Norwegian Air and AirAsia X, which are recognized as leading airlines in the long-haul LCC market. Based on this analysis, this study intends to provide implications for networking strategies for Korean LCCs that seek to enter the long-haul market when the aviation market stabilizes again upon the end of the COVID-19 pandemic. Design/methodology - To conduct the network analysis on long-haul low-cost airlines, the Official Airline Guide (OAG) Schedule Analyzer was used to extract long-haul data of Norwegian Air and AirAsia X. To analyze the trend of the long-haul route network, we obtained the data from 3 separate years between 2011 and 2019. The network was analyzed using UCINET 6.0 in order to examine the network structure of long-haul low-cost airlines and the growth trend of each stage. Findings - Analyzing the network of long-haul routes by visualizing the network structure of low-cost carriers showed the following results. In its early years, Norwegian Air's long-haul route network, centering on regional airports in Spain and Sweden, connected European regions, the Middle East, and Africa. As time passed, however, the network expanded and became steadily strong as the airline connected airports in other European countries to North America and Asia. In addition, in 2011, AirAsia X showed links to parts of Europe, such as London and Paris, the Middle East and India, and Australia and Northeast Asia, centering on the Kuala Lumpur Airport. Although the routes in Europe were suspended, the network continued to expand while concentrating on routes of less than approximately 7,000 km. It was found that instead of giving up on ultra-long-haul routes such as Europe, the network was further expanded in Northeast Asia, such as the routes in Korea and Japan centering on China. Originality/value - Until the COVID-19 pandemic broke out, Norwegian Air actively expanded long-haul routes, resulting in the number of long-haul routes quintupling since 2011. The unfortunate circumstance, wherein the world aviation market was rendered stagnant due to the outbreak of COVID-19, hit Norwegian Air harder than any other low-cost carriers. However, in the case of AirAsia X, it was found that it did not suffer as much damage as Norwegian Air because it initially withdrew from unprofitable routes over 7,000 km and grew by gradually increasing profitable destinations over shorter distances. When the COVID-19 pandemic ends and the aviation market stabilizes, low-cost carriers around the world, including Korea, that enter the long-haul route market will need to employ strategies to analyze the marketability of potential routes and to launch the routes that yield the highest profits without being bound by distance. For stable growth, it is necessary to take a conservative stance; first, by reviewing the business feasibility of the operating a small number of highly profitable routes, and second, by gradually expanding these routes.