• 한국정보시스템학회지:정보시스템연구
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• 제31권3호
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• 한국도로학회논문집
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• 제19권4호
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• pp.1-7
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• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권7호
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• pp.1585-1609
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• 2013

Over recent years, enormous amounts of research in wireless sensor networks (WSNs) have been conducted, due to its multifarious applications such as in environmental monitoring, object tracking, disaster management, manufacturing, monitoring and control. In some of WSN applications dependent the energy-efficient and link reliability are demanded. Hence, this paper presents a routing protocol that considers these two criteria. We propose a new mechanism called Reliable Routing Scheme for Energy-Balanced (RRSEB) to reduce the packets dropped during the data communications. It is based on Swarm Intelligence (SI) using the Ant Colony Optimization (ACO) method. The RRSEB is a self-adaptive method to ensure the high routing reliability in WSNs, if the failures occur due to the movement of the sensor nodes or sensor node's energy depletion. This is done by introducing a new method to create alternative paths together with the data routing obtained during the path discovery stage. The goal of this operation is to update and offer new routing information in order to construct the multiple paths resulting in an increased reliability of the sensor network. From the simulation, we have seen that the proposed method shows better results in terms of packet delivery ratio and energy efficiency.

• 국토계획
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• 제54권3호
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• pp.49-62
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• 2019

In order to balance with supply policy, public housing management and operation policies have been implemented in terms of housing welfare, but citizens have not yet achieved the results that the citizens are experiencing. The purpose of this study is to analysis the residential satisfaction of the including the housing performance through the characteristics of the public housing residents in Seoul. The data used in this study is based on the survey data of public housing panel survey in Seoul (2016). The study method used ordered logistic regression analysis based on the fact that dependent variables appeared as ordered responses. Major research results are as follows. Firstly, housing performance and residential satisfaction may not match. Even though the satisfaction of housing area, type, and management fee is high, satisfaction with residential environment is low if commuting distance, the number of small libraries, and hospitals are small. Secondly, it showed different characteristics of residential environment factors among types of public housing. Rather than focusing on supply, customized supply is needed considering characteristics of public housing types. Thirdly, the policy for public housing needs to be realized by a fair policy on the residential environment. It is necessary to contribute to better housing stability as a customized policy considering the local residential environment.

• 유통과학연구
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• 제20권11호
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• pp.79-88
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• 2022

Purpose: The purpose of this study was to determine the effect of agricultural exports and imports on economic growth in Bangladesh and propose an upgraded and customized model of the supply chain for agribusiness growth in Bangladesh to achieve plain sailing and systematic operation and financial gains at home and abroad. Research design, data, and methodology: All data in the research have been collected from secondary sources. Gross domestic product was used as the dependent variable and exports and imports of agricultural products were used as independent variables. Pairwise Granger causality was utilized to see the impact of the variable responsible for the economic growth in Bangladesh and the causal relationship between the variables analyzed was measured using Johansen co-integration test. Results: From the empirical analysis, the researchers observed that agricultural commodity imports and exports have a unidirectional impact on economic growth in Bangladesh and a long-run causal link with economic growth in Bangladesh. The suggested supply chain model of agribusiness aids in achieving smooth operations, systematic management, and monetary gains both domestically and internationally. Conclusions: This paper contributes to the development of a more effective and profitable agribusiness supply chain in Bangladesh systematically through their theoretical and practical implications.

• 지능정보연구
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• 제26권1호
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• pp.75-95
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• 2020

소셜네트워크서비스(SNS)의 성장과 함께 다양한 형태의 SNS가 등장했다. 상호작용성, 정보 교류, 엔터테인먼트 등 다양한 이용 동기를 바탕으로 SNS 이용자 또한 빠르게 증가하는 추세이다. 그중 페이스북은 대표하는 SNS 채널로서 기업에서도 페이스북 페이지를 활용해 홍보 채널로 활용하기 시작했다. 이를 위해 운영 초기, 기업은 팬 수 확보에 나섰고 그 결과 최근 기업 페이스북 팬 수는 많게는 수백만에 이를 정도로 늘어났다. 기업의 목표는 팬 수 확보를 넘어 콘텐츠를 통해 고객에게 기업 브랜드 이미지를 재고하고, 나아가 소통하는 수단으로 활용하고 있다. 이를 평가하는 주요 수치가 바로 본 연구의 종속변수에 해당하는 페이스북의 '좋아요', '댓글', '공유', '클릭 수' 등이다. 해당 수치 달성을 위해 콘텐츠 제작에 대한 고민이 선행되어야 하는데, 본 연구에서는 콘텐츠 제작 고려 사항을 3가지로 나눠 독립변수를 구성하였다. 콘텐츠 소재, 콘텐츠 구조, 메시지 스타일 등이 페이스북의 이용자 행동에 미치는 영향을 회귀분석을 이용해 분석하였다. 종속변수의 경우, 콘텐츠상에 모든 이용자의 행동 '전체 클릭 수'로 설정하였다. 본 연구에서는 각 독립 변수를 기존 연구 문헌을 통해 정의하고, 종속변수에 미치는 영향을 분석하였는데, '전체 클릭 수'의 경우, '자사연관', '실생활 관여도', '격식 x 관여도' 등의 변수가 유의미한 영향을 갖는 것으로 나타났다. 연구 결과를 통해, 콘텐츠 목적에 따른 최적화된 콘텐츠 전략을 제시함으로써, 기업 페이스북 운영자와 콘텐츠 제작자의 운영, 제작 전략에 기여할 수 있을 것으로 보인다.

• 전기전자학회논문지
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• 제23권1호
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• pp.80-90
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• 2019

최근에 소개된 비휘발성 메모리(Non-Volatile Memory)를 저장장치로 사용하는 경우에도 데이터를 접근하기 위해서는 페이지 테이블이 구축되어야 한다. 이 점에 착안하여 본 논문에서는 페이지 테이블 자체를 비휘발성 메모리에 유지하는 영속적 페이지 테이블 (Persistent Page Table) 기법을 설계한다. 실제 페이지 테이블의 구조는 프로세서마다 다르다. 또한 비휘발성 메모리의 물리주소와 가상주소는 종종 저장장치가 시스템에 연결되기 전까지 알 수 없기 때문에 연결 시점까지는 실제로 동작하는 페이지 테이블을 만들 수 없다. 따라서 영속적 페이지 테이블은 주소와 시스템으로부터 독립적인 구조를 가져야 하며, 저장장치가 동작하는 시점에 영속적 페이지 테이블을 기반으로 시스템 종속적인 페이지 테이블이 생성되어야 한다. 또한 영속적 페이지 테이블 엔트리는 원자적으로 변경되어야 하며, 본 논문에서는 이러한 영속적 페이지 테이블의 설계에 대해 설명한다. 다음으로 파일시스템이 영속적 페이지 테이블이 제공하는 교환 연산을 활용하여 저널링 오버헤드를 감소시킬 수 있음을 보인다. 교환 연산을 활용하도록 Linux Ext4 파일시스템을 변경하였으며, Filebench 워크로드를 이용한 성능 측정 결과를 보면 영속적 페이지 테이블과 교환 연산은 파일시스템의 성능을 최대 60% 향상시킨다.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• 한국항행학회논문지
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• 제27권5호
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• pp.552-560
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• 2023

항공기 공중 충돌사고는 대규모 인명 피해를 초래할 수 있는 위험한 사건이다. 이를 예방하기 위해 민간 항공에서는 TCAS(traffic alert and collision avoidance system) 장착을 의무화하였으며, 새로운 기술의 도움을 받아 더욱 정밀하게 발전하고 있다. 한국에서 개인적으로 TCAS 연구를 위한 데이터를 수집하는데는 절차적인 어려움이 있다. 이를 해결하기 위해 ADS-B(automatic dependent surveillance-broadcast)와 Mode-S(mode-select)를 활용하면 TCAS RA(resolution advisory)의 정보 획득이 가능하다. ADS-B Exchange와 Opensky-Network에서 보관중인 데이터베이스를 제공받아 연구에 활용하였으며, 3건의 TCAS RA 발생 사례를 시각화하였다. 또한 2023년 전반기 국내 TCAS RA 발생사례를 분류한 후 그 특징을 분석하였다. 이를 통해 ADS-B와 Mode-S 데이터의 유효성을 확인하고, 발전방향을 모색하였다.

• 한국컴퓨터정보학회논문지
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• 제25권6호
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• pp.17-23
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• 2020

본 논문에서는 자동화 설비 장비의 HMI와 PLC간 RS232 통신 시에 발생하는 실시간 데이터 프레임의 수집을 위하여, 별도의 HMI 혹은 PLC의 수정 없이 MCU를 통하여 실시간 정보 데이터 프레임을 스니핑 함으로서, 사용자가 PLC, HMI 시스템의 수정 작업에 종속되지 않고 데이터를 수집할 수 있는 방법을 제안한다. 사용자는 스니핑 데이터로부터 파싱작업을 통하여 필요한 정보를 수집하고 해당 스니핑 프레임을 목적지로 송신함으로서 본래의 통신 인터페이스를 유지한다. RS232 통신규격으로 MCU의 UART통신 인터페이스 회로를 물리적으로 설계하고, 더불어 MCU내부 DMA장치를 사용함으로서 인터럽트기반 시스템 보다 효율을 개선한다. 또한 환형큐를 사용하여 DMA인터럽트 서비스 루틴의 작업과 메인 스레드의 작업을 논리적으로 분리함으로서 데이터 프레임 IO 작업 처리를 수행한다. 이 방법을 통하여, 사용자는 RS232 규격으로 HMI, PLC간 스니핑 데이터 프레임을 수신하고 PLC와 HMI 간의 프레임 전송이 원래의 목적지에 정상적으로 도착하며 PLC와 HMI의 추가적인 수정 없이 데이터 프레임을 스니핑 함으로서 사용자 시스템에 정상적으로 도착함을 확인할 수 있다.