• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.467-484
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• 2017

Objective: The purpose of this paper is to review, with the main focus on aviation safety technology and management program, how human factors are currently taken into consideration within transportation sectors, especially aviation, and to further share related information. Background: Human factors account for the majority of aviation accidents/incidents. Thus, the aviation sector has been comparatively quick in developing and applying technologies and management programs that deal with human factors. This paper reviews the latest safety technologies and management programs regarding human factors and aims to identify the trend. Method: This paper, based on literature research and practical experience, examines the latest international standards on technologies and management programs, those that deal with human factors and are adopted by international and domestic aviation organization. The main focus of discussion is how human factors are reflected during the system design and operation process. Results: The current most important issue in designing is the consideration of human factors in Cockpit, Automation, and Safety system technology design. From an operational point of view, the issues at hand are screening and training aviation workers to promote aviation safety, providing education on human factors and CRM/TEM, and running a safety management program to implement SMS. They were discussed based on the operational experience within the aviation sector. Conclusion: Major examples of a human factors approach to promote aviation safety are safety programs and various safety and monitoring technologies applied to aviation personnel for error management. These programs must be managed in an integrated manner that takes both the system designing and operational point of view into account. Application: It is thought that the human factors approach for promoting aviation safety reviewed in this paper can be extended and applied to safety management programs in other transportation sectors such as the railroad, maritime, road traffic etc.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.11
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• pp.63-70
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• 2008

In this paper, a smart sensor system for the MEMS pressure sensor was developed. A compensation algorithm and programmable calibration circuits were presented to eliminate errors caused by temperature drift of piezoresistive pressure sensors in itself. This system consisted of signal conditioning, calibration, temperature detection, microprocessor, and communication parts and these were integrated into a SOC. A RS-232 interface was employed for monitoring and control of a smart sensor system. The area of fabricated IC is $4.38{\times}3.78\;mm^2$ and a $0.35{\mu}m$ high voltage CMOS process was used. Compensation error for temperature drift of 50 KPa pressure sensors was measured into ${\pm}0.48%$ in the range of $-40^{\circ}C{\sim}150^{\circ}C$. Total power consumption was 30.5 mW.

• Atmosphere
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• v.25 no.1
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• pp.117-127
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• 2015

The presences of clouds significantly influence the accuracy of ozone retrievals from satellite measurements. This study focuses on the influence of clouds on Ozone Monitoring instrument (OMI) ozone profile retrieval based on an optimal estimation. There are two operational OMI cloud products; OMCLDO2, based on absorption in $O_2-O_2$ at 477 nm, and OMCLDRR, based on filling in Fraunhofer lines by rotational Raman scattering (RRS) at 350 nm. Firstly, we characterize differences between $O_2-O_2$ and RRS effective cloud pressures using MODIS cloud optical thickness (COT), and then compare ozone profile retrievals with different cloud input data. $O_2-O_2$ cloud pressures are significantly smaller than RRS by ~200 hPa in thin clouds, which corresponds to either low COT or cloud fraction (CF). On the other hand, the effect of Optical centroid pressure (OCP) on ozone retrievals becomes significant at high CF. Tropospheric ozone retrievals could differ by up to ${\pm}10$ DU with the different cloud inputs. The layer column ozone below 300 hPa shows the cloud-induced ozone retrieval error of more than 20%. Finally, OMI total ozone is validated with respect to Brewer ground-based total ozone. A better agreement is observed when $O_2-O_2$ cloud data are used in OMI ozone profile retrieval algorithm. This is distinctly observed at low OCP and high CF.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1286-1293
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• 2014

Typically, studies through the simulation system have been progressed, because the evaluation of the driver's arousal state about the service of a actual train has risk of safety for the driver. When configured event same as the real in simulation system, the ability to cope with an accident situation may be the same each other. But the difference in the state of tension or arousal will occur. In this study, requested to cooperate with the railways in order to escape from these constraints, and the target of the experiment was to real engineer service. I was set about experiment when the train was stopped as safe as possible. As a result, the beta wave of EEG signals that representing complex calculations or anxiety is increased rapidly on the basis of a flag station from at the time of departure. The size of the electrodermal activity signal in response to movement of the body gave a noticeable. In terms of HRV, if the train approach a flag station gradually and the R-R interval is narrowed. So that the driver can be estimated as arousal state. In accordance with this study, if the quantitative standard of arousal state be based on the driver's biosignals will provide, it will be able to take advantage of development the system that would prevent train accidents caused by human error.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.85-90
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• 2013

Currently, the electric fire prediction system uses PIC(Peripheral Interface Controller) for controller microprocessor. PIC has a slower computing speed than DSP does, so its real-time computing ability is inadequate. So with the basic characteristics waveform during arc generation as the standard reference, the comparison to this reference is used to predict and alarm electric fire from arc. While such alarm can be detected and taken care of from a remote central server, that prediction error rate is high and remote control in mobile environment is not available. In this article, the arc detection of time domain and frequency domain and wavelet-based adaptation algorithm executing the adaptation algorithm in conversion domain were applied to develop an electric fire prediction system loaded with new real-time arc detection algorithm using DSP. Also, remote control was made available through iPhone environment-based app development which enabled remote monitoring for arc's electric signal and power quality, and its utility was verified.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.1
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• pp.1-11
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• 2007

In this paper, a new fully digital control method for UPS inverter, which is based on the double control loop such as the outer voltage control loop and inner current control loop, is proposed. In the proposed control system, overshoots and oscillations due to the computation time-delay are compensated by explicit incorporation of the time-delay in the current control loop transfer function. The inner current control loop is adopted by an internal model controller. The internal model controller is designed to a second order deadbeat reference-to-output response which means that its response reaches the reference in two sampling time including computational time-delays. The outer voltage control loop employing P-Resonance controller is proposed. The resonance controller has an infinite gain at resonant frequency, and the resonant frequency is set to the fundamental frequency of the reference voltage in this paper. Thus the outer voltage control loop causes no steady state error as regard to both magnitude and phase. The effectiveness of the proposed control system has been verified by the simulation and experimental results respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.465-468
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• 2007

An intelligent home network system using low-power and low-cost sensor nodes was designed and implemented. In Intelligent Home Network System, active home appliances control is composed of RSSI (Received Signal Strength Indicator) based user indoor location tracking, dynamic multi-hop routing, and learning integration remote-control. Through the remote-control learning, home appliances can be controlled in wireless network environment. User location information for intelligent service is calculated using RSSI based Triangle measurement method, and then the received location information is passed to Smoothing Algorithm to reduce error rate. In order to service Intelligent Home Network, moreover, the sensor node is designed to be held by user. The gathered user data is transmitted through dynamic multi-hop routing to server, and real-time user location & environment information are displayed on monitoring program.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.6
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• pp.53-61
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• 2014

For monitoring the flight trajectory and the status of a launch vehicle, the mission control system in NARO space center process data acquired from the ground tracking system, which consists of two tracking radars, four telemetry stations, and one electro-optical tracking system. Each tracking unit exhibits its own tracking error mainly due to multi-path, clutter and radio refraction, and by utilizing only one among transmitted informations, it is not possible to determine the actual vehicle trajectory. This paper presents a way of generating flight trajectory via post-processing the data received from the ground tracking system. The post-processing algorithm is divided into two parts: compensation for atmosphere radio refraction and multi-sensor fusion, for which a decentralized Kalman filter was adopted and implemented based on constant acceleration model. Applications of the present scheme to real data resulted in the flight trajectory where the tracking errors were minimized than done by any one sensor.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.1-8
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• 2024

Busan is the 6th largest port city in the world, where nitrogen dioxide (NO₂) emissions from transportation and port industries are significant. This study aims to assess the NO₂ products of the Geostationary Environment Monitoring Spectrometer (GEMS) over Busan using ground-based instruments (i.e., surface in-situ network and Pandora). The GEMS vertical column densities of NO₂ showed reasonable consistency in the spatiotemporal variations, comparable to the previous studies. The GEMS data showed a consistent seasonal trend of NO₂ with the Korea Ministry of Environment network and Pandora in 2022, which is higher in winter and lower in summer. These agreements prove the capability of the GEMS data to monitor the air quality in Busan. The correlation coefficient and the mean bias error between the GEMS and Pandora NO₂ over Busan in 2022 were 0.53 and 0.023 DU, respectively. The GEMS NO₂ data were also positively correlated with the ground-based in-situ network with a correlation coefficient of 0.42. However, due to the significant spatiotemporal variabilities of the NO₂, the GEMS footprint size can hardly resolve small-scale variabilities such as the emissions from the road and point sources. In addition, relative biases of the GEMS NO₂ retrievals to the Pandora data showed seasonal variabilities, which is attributable to the air mass factor estimation of the GEMS. Further studies with more measurement locations for longer periods of data can better contribute to assessing the GEMS NO₂ data. Reliable GEMS data can further help us understand the Asian air quality with the diurnal variabilities.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.4
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• pp.365-369
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• 2016

Red sorrel (Rumex acetosella L.), as one of exotic weeds in Korea, was dominated in grassland and reduced the quality of forage. Improving current pasture productivity by precision management requires practical tools to collect site-specific pasture weed data. Recent development in unmanned aerial vehicle (UAV) technology has offered cost effective and real time applications for site-specific data collection. To map red sorrel on a hill pasture, we tested the potential use of an UAV system with digital cameras (visible and near-infrared (NIR) camera). Field measurements were conducted on grazing hill pasture at Hanwoo Improvement Office, Seosan City, Chungcheongnam-do Province, Korea on May 17, 2014. Plant samples were obtained at 20 sites. An UAV system was used to obtain aerial photos from a height of approximately 50 m (approximately 30 cm spatial resolution). Normalized digital number values of Red, Green, Blue, and NIR channels were extracted from aerial photos. Multiple linear regression analysis results showed that the correlation coefficient between Rumex content and 4 bands of UAV image was 0.96 with root mean square error of 9.3. Therefore, UAV monitoring system can be a quick and cost effective tool to obtain spatial distribution of red sorrel data for precision management of hilly grazing pasture.