• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.1
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• pp.41-48
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• 2015

Being a cost-efficient solution for alleviating the traffic congestion in airspace, Air Traffic Flow Management (ATFM) has drawn more attentions from not only air traffic controllers but also researchers in the field of Air Traffic Management (ATM). Among other ATFM initiatives, it is believed that Ground Delay Program (GDP) could be effectively applied to reduce the congestion particularly in the relatively small airspace with dense traffic demand. This paper introduces a novel way that suggests flights to be delayed on the departing airports together with amount of the delays (in time) for those flights to be delayed. Adopting a fast-time simulation for predicting airspace delay of each flight for a given flight plan, the method is designed to iteratively and incrementally adjust the departure times in the plan towards reducing total airspace delays. Applying the method to Jeju airport with a hypothetically high demand, the paper demonstrates the airspace delay could be significantly reduced by applying GDP at Gimpo airport where more than 60% of Juju-bound flights departure. Although the simulation model needs to be calibrated and validated for the real-world application, the results clearly shows that the approach can possibly implemented as a tool for preparing the daily plan at the pre-tactical stage defined in the ICAO ATFM manual.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.58-65
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• 2017

Global navigation satellite system (GNSS) has a weakness of signal integrity caused by broadcasting type data transmitting direct to user from navigation satellite. Loss of GNSS signal integrity can make a catastrophic event in the operation of unmanned aerial system (UAS) because position decision is only depended on GNSS. So it is required to apply alternative method to reduce a risk and to guarantee a GNSS signal integrity for UAS operation. This paper addressed the reason of loosing GNSS signal integrity, the effectiveness of signal jamming/spoofing and GNSS application trend for UAS. Also suggested the flight safety enhancing method in case of GNSS signal jamming for UAS as technical and political approaches.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.367-374
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• 2018

A trajectory-based scheduling system is proposed for air traffic management using next generation aviation data communication link. Based on the service concept of 4-dimensional trajectory data link (4DTRAD) using air traffic serveices (ATS) datalink Baseline 2, a procedure for trajectory-based operation of an en-route flight is established and described in detail. To mitigate air traffic controllers' workload which might be caused by various and complicated data utilization, a prototype of the scheduling system, which predicts the aircraft trajectory based on the flight intents received by air traffic service system and provides advisory information for air traffic control, was developed. The simulation environment for trajectory based operation was built to validate the scheduling functionality of the prototype.

• Journal of Advanced Navigation Technology
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• v.28 no.5
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• pp.594-600
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• 2024

With the operation of the Korean satellite-based augmentation System (KASS), it has become possible to develop and implement localizer performance with vertical guidance (LPV) instrument approach procedures. In this study, we developed an LPV procedure for Runway 18 at Ulsan Airport, where the installation of an instrument landing system (ILS) is unable due to obstacles, and examined the potential reduction in flight cancellations. The study results suggest that, when developing an LPV instrument approach procedure, the decision altitude would be 380 feet, and the visibility minimum would be 1,200 meters. Consequently, it is expected that flight cancellations for Runway 18, based on 2023 cancellation data, could be reduced by 92% under the given visibility and ceiling conditions if LPV instrument approach procedure is developed. Therefore, the development and operation of the LPV instrument approach procedure for Runway 18 at Ulsan Airport is deemed essential.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.8096-8105
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• 2015

The purpose of this research is to understand influence of personal turnover factors and work turnover factors on job satisfaction in career decision-making and to analyze the moderating effects of supervisor support in their relations. Meaningful difference between one group with high supervisor support and other group with low supervisor support is demonstrated in regard with a course; job burnout ${\rightarrow}$ job satisfaction, and work overload ${\rightarrow}$ job satisfaction. Hence from a perspective of the course of job burnout ${\rightarrow}$ job satisfaction and work overload ${\rightarrow}$ job satisfaction, it can be argued that a group with low supervisor support yields more influence. Also it is shown that conflicts on balancing between job and family do not have influence on job satisfaction for either group with high supervisor support or with low supervisor support. As the result of the research shows, it bears a quite significant meaning that career development/lack of opportunity out of personal turnover intentions disclose difference between these two groups with different levels of supervisor support. Especially, a group of flight attendants which females are consisted of a majority of employees would require that their supervisors have more emotional interactions with each employee, so as that better opportunity would be given to the employees. To this end, utmost efforts are needed that deep and genuine relations with a supervisor can be built up.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.35-48
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• 2018

The study of air defense against North Korean tactical ballistic missiles (TBM) should consider the rapidly changing battlefield environment. The study for target re-designation for intercept missiles enables effective operation of friendly defensive assets as well as responses to dynamic battlefield. The researches that have been conducted so far do not represent real-time dynamic battlefield situation because the hit probability for the TBM, which plays an important role in the decision making process, is fixed. Therefore, this study proposes a target re-designation algorithm that makes decision based on hit probability which considers real-time field environment. The proposed method contains a trajectory prediction model that predicts the expected trajectory of the TBM from the current position and velocity information by using random forest and moving window. The predicted hit probability can be calculated through the trajectory prediction model and the simulator of the intercept missile, and the calculated hit probability becomes the decision criterion of the target re-designation algorithm for the missile. In the experiment, the validity of the methodology used in the TBM trajectory prediction model was verified and the superiority of using the hit probability through the proposed model in the target re-designation decision making process was validated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.8
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• pp.1080-1088
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• 2018

General methods of controlling a drone are divided into manual control and automatic control, which means a drone moves along the route. In case of manual control, a man should be able to figure out the location and status of a drone and have a controller to control it remotely. When people control a drone, they collect information about the location and position of a drone with the eyes and have its internal information such as the battery voltage and atmospheric pressure delivered through telemetry. They make a decision about the movement of a drone based on the gathered information and control it with a radio device. The automatic control method of a drone finding its route itself is not much different from manual control by man. The information about the position of a drone is collected with the gyro and accelerator sensor, and the internal information is delivered to the CPU digitally. The location information of a drone is collected with GPS, atmospheric pressure sensors, camera sensors, and ultrasound sensors. This paper presents an investigation into drone control by a remote computer. Instead of using the automatic control function of a drone, this approach involves a computer observing a drone, determining its movement based on the observation results, and controlling it with a radio device. The computer with a Depth camera collects information, makes a decision, and controls a drone in a similar way to human beings, which makes it applicable to various fields. Its usability is enhanced further since it can control common commercial drones instead of specially manufactured drones for swarm flight. It can also be used to prevent drones clashing each other, control access to a drone, and control drones with no permit.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.255-263
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• 2021

Background: Ecosystem service mapping is an important tool for decision-making in landscape planning and natural resource management. Today, pollination service mapping is based on the Lonsdorf model (InVEST software) that determines the availability of nesting and floral resources for each land cover and estimates pollination according to the foraging range of the desired species. However, it is argued that the Lonsdorf model has significant limitations in estimating pollination in a landscape that can affect the results of this model. Results: This paper presents a free software, named PollMap, that does not have the limitations of the Lonsdorf model. PollMap estimates the pollination service according to a modified version of the Lonsdorf model and assumes that only cells within the flight range of bees are important in the pollination mapping. This software is produced for estimating and mapping crop pollination in agricultural landscapes. The main assumption of this software is that in the agricultural landscapes, which are dominated by forest and agriculture ecosystems, forest patches serve only as a nesting habitat for wild bees and the surrounding fields provide floral resources. Conclusion: The present study provided new software for mapping crop pollination in agricultural landscapes that does not have the limitations of the Lonsdorf model. We showed that the use of the Lonsdorf model for pollination mapping requires attention to the limitations of this model, and by removing these limitations, we will need new software to obtain a reliable mapping of pollination in agricultural landscapes.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.1 s.94
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• pp.53-62
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• 2005

This study presents the NDE (non-destructive evaluation) technique for detecting the loosened bolts on joint steel structures on the basis of TOF (time of flight) and amplitudes of Lamb waves. Probabilistic neural network (PNN) technique which is an effective tool for pattern classification problem was applied to the damage estimation using PZT induced Lamb waves. Two kinds of damages were introduced by dominant damages (DD) which mean loosened bolts within the Lamb waves beam width and minor damages (MD) which mean loosened bolts out of the Lamb waves beam width. They were investigated for the establishment of the optimal decision boundaries which divide each damage class's region including the intact class. In this study, the applicability of the probabilistic neural networks was identified through the test results for the damage cases within and out of wave beam path. It has been found that the present methods are very efficient and reasonable in predicting the loosened bolts on the joint steel structures probabilistically.