• Journal of Distribution Science
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• v.21 no.3
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• pp.13-23
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• 2023

Purpose: Low-Cost Carrier airlines attempt to provide the best service for their customers. However, the pandemic has forced airline companies to keep developing new strategies. Moreover, in this digital era, airlines must intensely market their service through social media to reach as many customers as possible. This research aims to study the impact of advertisements on Instagram and the customer experience concerning customer loyalty and satisfaction in the aviation industry. Research design, data, and methodology: This study uses a quantitative explanatory with the combination of the positivism paradigm. The data collection technique is by distributing questionnaires to related airline Instagram followers. Meanwhile, the sample calculation uses using the Slovin formula in which 414 respondents are gained. The collected data is analyzed with Structural Equation Model and using Smart-PLS software. Results: The study results indicate that advertising on Instagram and customer experience significantly positively affect customer satisfaction and loyalty. In addition, the variable customer satisfaction has a significant positive on customer loyalty. Conclusions: The study results indicate that the ease of obtaining information via Instagram can affect satisfaction and will increase when customers have made a flight so that they will become loyal customers.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1325-1332
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• 2023

Recently, much research is being conducted based on point cloud data for the growth of innovations such as construction automation in the transportation field and virtual national space. This data is often measured through remote control in terrain that is difficult for humans to access using devices such as UAVs and UGVs. Drones, one of the UAVs, are mainly used to acquire point cloud data, but photogrammetry using a vision camera, which takes a lot of time to create a point cloud map, is difficult to apply in construction sites where the terrain changes periodically and surveying is difficult. In this paper, we developed a point cloud mapping system by adopting non-repetitive scanning LiDAR and attempted to confirm improvements through field application. For accuracy analysis, a point cloud map was created through a 2 minute 40 second flight and about 30 seconds of software post-processing on a terrain measuring 144.5 × 138.8 m. As a result of comparing the actual measured distance for structures with an average of 4 m, an average error of 4.3 cm was recorded, confirming that the performance was within the error range applicable to the field.

• Korean Journal of Artificial Intelligence
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• v.12 no.2
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• pp.17-23
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• 2024

Various methods have been developed to predict the flight path of an air-launched weapon to intercept a fast-moving target in the air. However, it is also getting more challenging to predict the optimal firing zone and provide it to a pilot in real-time during engagements for advanced weapons having new complicated guidance and thrust control. In this study, a method is proposed to develop an optimized weapon engagement zone by the SCG (Scaled Conjugate Gradient) algorithm to achieve both accurate and fast estimates and provide an optimized launch display to a pilot during combat engagement. SCG algorithm is fully automated, includes no critical user-dependent parameters, and avoids an exhaustive search used repeatedly to determine the appropriate stage and size of machine learning. Compared with real data, this study showed that the development of a machine learning-based weapon aiming algorithm can provide proper output for optimum weapon launch zones that can be used for operational fighters. This study also established a process to develop one of the critical aircraft-weapon integration software, which can be commonly used for aircraft integration of air-launched weapons.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4039-4047
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• 2023

This contribution describes the application of HPGe detector for the airborne quantitative analysis. The hardware of the airborne HPGe system was designed from the commercial components with only exception of the newly designed AirHPGeSpec special software to control, measure and process the data. The system was calibrated for the local air kerma rates measured on helicopter board and its conversion to the air kerma rates at 1 m above the ground was proposed. Two examples of the air kerma rates measured over the former uranium mining areas are presented and compared with the results of other airborne system on the board. This airborne HPGe system could be also used for measuring the surface activities in a radiation event. The nuclides of ¹³¹I, ¹³²Te - ¹³²I, ¹³³I, ¹³⁴I, ¹³⁵I, ¹³⁷Cs, ¹³⁴Cs, ⁸⁸Rb and ¹⁰³Ru were selected from possible nuclear power plant emergency scenarios. The Monte Carlo simulation was used to calculate HPGe detector efficiencies for the flight altitudes from 25 to 300 m for the energies from 300 keV to 3 MeV of the nuclides in question. Also, the detection limits according to the Currie method as well as ISO 11929-2010 for selected nuclides are presented.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.2
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• pp.199-206
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• 2024

The GEO-KOMPSAT-2A (GK2A) satellite, which was launched in December 2018, carries weather observation payloads and uses the image navigation and registration system to calibrate the observation images. The calibration system requires accurate orbit prediction data and depends on the accuracy of the orbit determination accuracy. In order to find a possible way to improve the current orbit determination accuracy of the GK2A flight dynamic subsystem module, orbit determination software was developed to independently evaluate the orbit determination accuracy. A comprehensive satellite dynamic model is applied for a batch-type least squares filter. When determining the orbit, thrust firing during station-keeping maneuvers and wheel-off loading maneuvers is taken into account. One month of GK2A ranging data were processed to estimate the satellite position on a daily basis. The orbit determination error was evaluated by comparing estimates during overlapping estimation intervals.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.352-352
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• 2017

Recently, the South Korean government encourages the cultivation of upland crops in the paddy field to maintain an adequate level of rice production and then to balance the demand and supply of rice. This is mainly because the rice consumption per capita per year has continued to decline from 135 kg in 1979 to 61.9 kg in 2016, although the rice production was relatively stable. As a result, the rice overproduction became a big social problem. As a part of that, various upland crops such as soybean, maize, minor cereals and forage crops are planted in the paddy field 10 years ago. The cultivation of these crops may settle the problem of short supply and mass import of the crops to some extent. However, a systematic remote observation of upland crops in the paddy field is very scarce. This study investigated the cultivation status of upland crops and any changes of crop harvesting in the paddy field by using an unmanned aerial vehicle (UAV). Also, we analyzed the kind of upland crops and cultivation area in the paddy field by utilizing time series observation images. A fixed wing UAV is used for the investigation. This is because it is easy to use the flight operation and to control flight management software, and it can automatically cope with various emergency states such as a strong wind and battery discharge. The material of UAV is expanded polypropylene, which has an advantage of less equipment damage and risk during takeoff and landing. We acquired observed images in Buljeong-myeon, Goesan-gun, Chungcheongbuk-do, South Korea by using fixed wing UAV in 2015 and 2016. The total investigated area reaches 6,045 ha, and among them the agricultural area was 1,377 ha. For the next step, we created an orthoimage from all images taken using Pix 4D mapper program. According to the results of image analyses in 2015, the paddy field covered total 577 ha (75.9%) with crop plant. The cultivation area of beans, ginseng, maize, tobacco and peach was 256 ha (36.6%), 63 ha (9.2%), 37 ha (5.4%), 31 ha (4.5%) and 27 ha (3.8), respectively. And in 2016, the total covered area was 586 ha (77.1%), and it was comprised of 253 ha (35.5%), 88 ha (12.3%), 29 ha (4.1%), 22 ha (3.1%) and 32 ha (4.5%) in the same order. In this study, we focused on identifying the paddy field which was converted to the cultivation of upland crops by using UAV. And, it has been indicated that the cultivation area of rice decreased from 141 ha in 2015 to 127 ha in 2016, although that of ginseng increased by 25 ha. As a result, it is expected that a lot of paddy field could be replaced by high-income crops such as ginseng and fruit tree (peach) instead of relative low-income rice. More specific and widespread research on the remote sensing in the paddy field needs to be done.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.437-447
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• 2020

The purpose of this study is to research the countermeasures and expected effects through the use of drones in the field of disaster prevention as a drone-based smart quarantine performance method. The environmental, market, and technological approaches to the review of the current quarantine performance task and its countermeasures are as follows. First, in terms of the environment, the effectiveness of the quarantine performance business using drone-based control is to broaden the utilization of forest, bird flu, livestock, facility areas, mosquito larvae, pests, and to simplify and provide various effective prevention systems such as AI and cholera. Second, in terms of market, the standardization of livestock and livestock quarantine laws and regulations according to the use of disinfection and quarantine missions using domestic standardized drones through the introduction of new technologies in the quarantine method, shared growth of related industries and discovery of new markets, and animal disease prevention It brings about the effect of annual budget savings. Third, the technical aspects are (1) on-site application of disinfection and prevention using multi-drone, a new form of animal disease prevention, (2) innovation in the drone industry software field, and (3) diversification of the industry with an integrated drone control / control system applicable to various markets. (4) Big data drone moving path 3D spatial information analysis precise drone traffic information ensures high flight safety, (5) Multiple drones can simultaneously auto-operate and fly, enabling low-cost, high-efficiency system deployment, (6) High precision that this was considered due to the increase in drone users by sector due to the necessity of airplane technology. This study was prepared based on literature surveys and expert opinions, and the future research field needs to prove its effectiveness based on empirical data on drone-based services. The expected effect of this study is to contribute to the active use of drones for disaster prevention work and to establish policies related to them.

• 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.

• Journal of Satellite, Information and Communications
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• v.4 no.2
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• pp.12-19
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• 2009

In the modern UAV systems, the role of radar payload has been increasing with its unique performance of day-and-night operation and see-through capability over hidden obstacles. Contrary to the satellite reconnaissance, UAV is expected to provide high resolution target detection and recognition capability while frequent flight missions would deliver enhanced SAR image and local information over the target area. STK(Satellite Tool Kit) is a professional space-analysis software widely used in all phases of a space system's life cycle. The simulation of STK is efficient and accurate relatively. In this paper, the author attempt to model the UAV operation and measure the expected SAR image quality. STK(Satellite Tool Kit) is employed to analyze UAV operation and produce SAR raw data. A SAR simulator is developed to produce high resolution SAR image for various ground targets.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.475-477
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• 2005

국내에서 개발된 저궤도 관측위성에는 인텔계열의 프로세서가 사용되어 졌다. 인텔계열의 프로세서를 이용한 임베디드 시스템은 다양하고 상세한 기술문서들이 많이 제공될 수 있고 국내에도 관련된 기술 습득이 이루어져 있다는 장점이 있다. 그러나 프로세서에 대한 새로운 기술의 개발 및 적용이 단기간에 이루어지기 때문에 이를 이용한 시스템 개발에 계속적으로 개발비용 부담이 가중되고 선진국의 첨단기술 유출 방지를 위한 여러 규제들로 인해 인텔 계열의 프로세서를 사용한 위성용 임베디드 시스템 개발에 걸림돌이 되고 있다. 이러한 문제점들을 해결하기 위해 차세대 위성에 사용 가능한 탑재컴퓨터에 대한 조사 및 기술분석을 수행하였으며, 유럽에서 자체적으로 개발하여 위성용 탑재컴퓨터로 사용하고 있는 MCM-ERC52가 차세대 위성개발에 적합한 것으로 판단되었다. MCM-ERC32는 SPARC v.7을 기반으로 한 ERC32SC 프로세서를 이용한 탑재컴퓨터 보드로 향후 위성에 요구되는 다양한 기능들을 수행하기에 충분한 고성능 탑재컴퓨터이다. 국내에서는 MCM-ERC32를 이용한 개발 경험이 전무한 상황이며, 관련된 기술자료도 충분하지 않은 실정이다. 이에 따라 MCM-ERC32에 적합한 저궤도 위성용 탑재소프트웨어 개발을 위한 연구가 진행되고 있으며. 본 논문에서는 MCM-ERC32를 이용한 탑재소프트웨어 개발에 필요한 특징적인 ERC32 프로세서의 개념과 기능에 대해 소개하고자 한다.