• 품질경영학회지
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• 제45권1호
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• pp.65-92
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• 2017

Purpose: The performance of global major airports is evaluated and several research questions are examined relative to the measures characterizing airport performance. Methods: The two-stage internal structure of airport performance is considered by decomposing it into physical operations and revenue generation. In the physical operations stage, operating costs, number of runways, terminal area and number of employees are used as inputs, while passenger throughput, cargo throughput and aircraft movements are taken as outputs. Subsequently, in the revenue generation stage, the outputs from the preceding stage are taken as inputs, while revenue is used as output. Results: Based upon this two-stage modeling of airport performance, a multiplicative two-stage network data envelopment analysis model is employed to calculate the overall and stage efficiencies of 59 airports using the recent data in the 2014 Airport Benchmarking Report published by the Air Transport Research Society. Several internal and external factors are also considered such as airport size, airport geographical location, proportion of international passengers, ownership (listed or not) and management style, and statistical analysis is performed to examine their impacts on airport performance. Conclusion: It is shown that the airports exhibit statistically significant difference across regions, and also some statistically significant factors affecting airport performance are identified.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.90-97
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• 2014

Nash Cournot Equilibrium (NCE) has been widely used in a competitive electricity market to analyze generation firms' strategic production quantities. Congestion on a transmission network may lead to a mixed strategy NCE. Mixed strategy is complicated to understand, difficult to compute, and hard to implement in practical market. However, Stackelberg model based equilibrium does not have any mixed strategy, even under congestion in a transmission line. A guide to understanding mixed strategy equilibrium is given by analyzing a cycling phenomenon in the players' best choices. This paper connects the concept of leader-follower in Stackelberg model with relations between generation firms on both sides of the congested line. From the viewpoint of social welfare, the surplus analysis is presented for comparison between the NCE and the Stackelberg equilibrium (SE).

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2022년도 춘계학술대회
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• pp.355-357
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• 2022

본 논문에서는 딥러닝 네트워크인 순환신경망(RNN) 모델을 사용해 이동 중인 객체의 이동 경로의 예측을 위한 포지셔닝 기술로서 실내 환경에서 지역 경로 내의 이동 중인 차량의 경로 예측에 연속적인 위치 정보를 이용하여 현재 위치 결정의 오류를 낮출 수 있는 이동 경로 생성 기법을 제안한다. GPS 정보를 사용할 수 없는 실내 환경의 경우 RNN 모델을 적용하기 위해서는 데이터 세트가 연속적이고 순차적이어야 한다. 그러나 Wi-Fi 전파 지문 데이터는 수집 시점의 특정 위치에 대한 특징 정보로서 연속성이 보장되지 않기 때문에 RNN 데이터로 사용할 수 없다. 따라서 RNN 모델에 필요한 순차적 위치의 연속성을 부여하여 실내 환경의 지역 경로를 이동하는 차량의 이동 경로 생성 기법을 제안한다.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2009년도 춘계학술대회 논문집
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• pp.453-457
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• 2009

Distributed Generation (DG) is predicted to play a important role in electric power system in the near future. insertion of DG system into existing distribution network has great impact on real-time system operation and planning. It is widely accepted that micro turbine generation (MTG) systems are currently attracting lot of attention to meet customers need in the distributed power generation market. In order to investigate the performance of MT generation systems, their efficient modeling is required. This paper presents the modeling and simulation of a MT generation system suitable for isolated operation. The system comprises of a Permanent magnet synchronous generator driven by a MT. A brief description of the overall system is given, and mathematical models for the MT and permanent magnet synchronous generator are presented. Also, the use of power electronics in conditioning the power output of the generating system is demonstrated. Simulation studies with MATLAB/Simulink have been carried out in islanding operation mode of a DG system.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.989-995
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• 2017

As is known to all that the output of wind power generation has a character of randomness and volatility because of the influence of natural environment conditions. At present, the research of wind power prediction mainly focuses on point forecasting, which can hardly describe its uncertainty, leading to the fact that its application in practice is low. In this paper, a wind power range prediction model based on the multiple output property of BP neural network is built, and the optimization criterion considering the information of predicted intervals is proposed. Then, improved Particle Swarm Optimization (PSO) algorithm is used to optimize the model. The simulation results of a practical example show that the proposed wind power range prediction model can effectively forecast the output power interval, and provide power grid dispatcher with decision.

• International Journal of Aeronautical and Space Sciences
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• 제9권1호
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• 한국정보과학회논문지:시스템및이론
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• 제29권2호
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• pp.57-64
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• 2002

본 연구에서는 고속의개인용 컴퓨터와 초고속 통신장비를 이용한 부산/병렬 계산을 위한 클러스터를 구현하였다. 먼저 16강 PC의 1세대의 클러스터를 구현하여 현재 현업(제주 지방기상처)에서 실시 간으로 운영중이며 1세대 클러스터의 성능 분석을 통하여 효율적으로 성능이 개선된 2CPU의 16PC로 구성된 2세대 클러스터를 구현하였다. 본 연구서는 다른 속도의 CPU및 통신 장비로 구성된 두 가지 형태의클러스터를 실제로 기상 예보를 위하여 사용되는 병렬모델인 MM5 를 이용하여 계산 시간 및 통신에 대한 다양한 분석을 하였다.

• 한국컴퓨터정보학회논문지
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• 제24권3호
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• pp.41-47
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• 2019

In this paper, we propose a application of conditional generative adversarial network (cGAN) for generation of contrast enhanced computed tomography (CT) image. Two types of CT data which were the enhanced and non-enhanced were used and applied by the histogram equalization for adjusting image intensities. In order to validate the generation of contrast enhanced CT data, the structural similarity index measurement (SSIM) was performed. Prepared generated contrast CT data were analyzed the statistical analysis using paired sample t-test. In order to apply the optimized algorithm for the lymph node cancer, they were calculated by short to long axis ratio (S/L) method. In the case of the model trained with CT data and their histogram equalized SSIM were $0.905{\pm}0.048$ and $0.908{\pm}0.047$. The tumor S/L of generated contrast enhanced CT data were validated similar to the ground truth when they were compared to scanned contrast enhanced CT data. It is expected that advantages of Generated contrast enhanced CT data based on deep learning are a cost-effective and less radiation exposure as well as further anatomical information with non-enhanced CT data.

• 정보처리학회논문지C
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• 제9C권5호
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• pp.775-782
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• 2002

본 논문은 정책 서버를 이용한 네트워크 보안 시스템에서 정책 정보 모델에 기반하여 구현한 정책 관리 도구를 소개한다. 본 논문이 기술하는 네트워크 보안 시스템은 특정 도메인을 보호하기 위해 정책을 관리하고 정책을 내리는 정책 서버와 정책 서버로부터 받은 정책들을 기반으로 침입을 탐지하고 대응하는 정책 클라이언트로 구성된다. 정책 서버와 정책 클라이언트간에 송수신되는 정책은 NSPIM(Network Security Policy Information Model)을 기반으로 구축된 정책 관리 도구를 이용하여 LDAP을 통해 디렉토리 형태로 데이터베이스에 저장된다. NSPIM은 본 네트워크 보안 시스템에서 사용하는 정책에 맞게 IETF의 PCIM과 PCIMe를 확장하여 구축한 정책 정보 모델이다. NSPIM 기반의 정책 관리 도구는 정책 생성, 수정, 삭제 등의 기능을 제공하여 정책을 관리할 뿐 아니라 재사용 객체 개념을 이용한 편집 기능, 객체 이름의 자동 생성 기능, 차단 정책의 자동 생성 기능 등을 통해 사용자에게 편리성을 제공한다.

• 대한산업공학회지
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• 제29권4호
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• pp.292-303
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• 2003

An efficient mobility management for mobile stations plays an important role in mobile communication network. Two basic operations of mobility management are location registration and paging. A zone-based registration (ZBR) is implemented in most of mobile communication systems and we consider the mobility management scheme that combines a zone-based registration and a selective paging (SP). We propose new analytical model that can reflect on the characteristics of the ZBR based on 2-dimensional random walk mobility model and more efficient paging schemes considering the proposed model. We evaluate the performance of the mobility management scheme with our mobility model to determine the optimal size of location area that will result in the minimum signaling traffic on radio channels. Numerical results are provided to demonstrate that our mobility model is useful to evaluate the ZBR more exactly.