• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.464-469
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• 2009

This paper discusses a robust observer-based output-feedback stabilization of an uncertain Takagi-Sugeno (T-S) fuzzy system in a network. In the networked control system, the input delay occurs inevitably and it is expressed by the Markovian stochastic process. To design robust sampled-data observer-based output-feedback controller, we discretize the T-S fuzzy system and represent as a jump system. Stochastic robust stabilization condition is formulated in terms of linear matrix inequalities.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.109.1-109.1
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• 2012

In the past few years, two-planet circumbinary systems (e.g., HW Vir, NN Ser, DP Leo and HU Aqr) have been detected around short-period eclipsing binaries using ground-based telescopes. The existence of these planets has been inferred by interpreting the O-C variations of the mid-eclipse times. We have tested the orbital stability of these systems and propose to use Light Travel Time Effect (LITE) to detect such circumbinary planets from the ground. We generated synthetically the LITE signal of a two-planet circumbinary system with the aim to apply an analytic LITE model to recover the underlying synthetic system. To mimic a degree of realism inherent to ground-based observations, we added to the synthetic LITE data white noise with a Gaussian distribution and sampled the synthetic LITE signal randomly. We successfully recovered the original system demonstrating that two-planet circumbinary systems can be detected using ground-based telescopes, provided the timing measurements of the mid-eclipses are sufficiently accurate and the observing baseline is long enough to ensure a sufficient coverage of all involved periods. We used HU Aqr as a test system and applied our model to its proposed planetary bodies considering near-circular orbits. We present the results of our calculations and discuss the LITE-detectability of a HU Aqr-like system.

• Journal of the Korea Computer Industry Society
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• v.8 no.4
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• pp.281-288
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• 2007

In this paper, we set 6 interesting points around lips. Analyzed and characterized is the distance change of these 6 interesting points when people pronounces 5 vowels of Korean language. 450 data are gathered and analyzed. Based on this analysis, the system is constructed and the recognition experiments are performed. In this system, we used the camera connected to computer to measure the distance vector between 6 interesting points. In the experiment, 80 normal persons were sampled. The observational error between samples was corrected using normalization method. We analyzed with 30 persons and experimented with 50 persons. We constructed three recognition systems and of those the neural net system gave the best recognition result of 87.44 %.

• The Korean Journal of Health Service Management
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• v.7 no.4
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• pp.243-257
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• 2013

This study was conducted in order to survey in healthcare worker's recognition of diagnosis related group(below; DRG) effect from July 1, 2012, to examine their recognition, expectation of the DRG system, and to provide the basic data necessary for the enforcement of the settlement. The subjects of this study were workers at clinics and hospitals sampled from hospital with DRG applying 7 diseases in Busan and Kyung-nam. A questionnaire of survey was conducted with the subjects working at clinics and hospitals from July, 25, 2012 to September 7, 2012, and the subjects were limited to doctors, officers, nurses, medical technicians and nurse assistants, and a total of 618 subjects were enrolled in this study. In the result of this study, generally, the healthcare workers recognized the DRG system. But their knowledge about that was not clear. Expanding enforcement DRG system at the present time, to provide accurate information to the healthcare consumer, workers need to know about DRG system clearly. To this end, for national health policy and medical institutions, workers should be educated constantly about providing medical service as well as the duty of enough explanation about the healthcare consumer's right to know.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1168-1176
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• 2024

For reusable Temporary Structure Elements such as scaffolding and temporary supports, quality control tasks are currently carried out through visual inspections by quality management workers and subjective judgments. Regarding quality tests based on the KOSHA(Korea Occupational Safety & Health Agency) system, only three pieces are sampled regardless of the quantity received at the site. On the other hand, although there is ongoing technological research on an automatic quality inspection of temporary structure elements, relevant stakeholders' introduction of such systems is hindered by issues such as cost. Therefore, this study aims to review a business model for introducing a quantitative and automated quality inspection system for reusable temporary structure elements. The study intends to propose application methods for each component according to a template and establish the business model by conducting interviews and collecting basic data for each template component. The results of this research are expected to serve as a foundation for implementation and expanding the adoption of quality management for temporary structure elements using smart technologies in the future.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4272-4279
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• 2022

In this study, a cross section stochastic sampling (S.S.) capability is implemented into both the McCARD continuous energy Monte Carlo code and MIG multiple-correlated data sampling code. The ENDF/B-VII.1 covariance data based 30 group cross section sets and the SCALE6 covariance data based 44 group cross section sets are sampled by the MIG code. Through various uncertainty quantification (UQ) benchmark calculations, the McCARD/MIG results are verified to be consistent with the McCARD stand-alone sensitivity/uncertainty (S/U) results and the XSUSA S.S. results. UQ analyses for Three Mile Island Unit 1, Peach Bottom Unit 2, and Kozloduy-6 fuel pin problems are conducted to provide the uncertainties of k_eff and microscopic and macroscopic cross sections by the McCARD/MIG code system. Moreover, the SNU S/U formulations for uncertainty propagation in a MC depletion analysis are validated through a comparison with the McCARD/MIG S.S. results for the UAM Exercise I-1b burnup benchmark. It is therefore concluded that the SNU formulation based on the S/U method has the capability to accurately estimate the uncertainty propagation in a MC depletion analysis.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.48 no.1
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• pp.29-39
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• 2012

Currently, environment-friendly and sustainable fisheries are one of the major issues among fisheries authorities. A variety of alternative management policies and projects are going on to enhance fisheries management systems and fishery resources such as a TAC management program and a VDS (Vessel Day Scheme) management scheme for distant water fishing nations in Western and Central Pacific Fisheries Commission (WCPFC) convention area. These kinds of efforts among fisheries management authorities are aimed at limiting fishing capacity or fishing power. In terms of fisheries management, Fishing capacity and fishing power have increased the importance of the impact on a fishery and level of the resources. Increased fishing capacity and fishing power have caused not only depletion of fisheries resource, but also additional fishing cost. therefore, there is a clear need for authorities to manage fishing capacity and fishing power. It is also help ensure the conservation and sustainability of the fishery resources. Because of lack of data, absolute fishing power is difficulty to measure. The notion of relative fishing power is frequently used. In this study, relative fishing power was assessed using Mastuda (1991) method for fishing power index. The raw data for assessment was based on fishermen's logbook data from sampled fishing vessels in coastal snow crab gillnet fishery. Data Envelopment Analysis (DEA) method was used to assess fishing capacity. DEA is a linear programming methodology to measure the efficiency of a set of entities called Decision-Making Units (DMUs). It was recommended by FAO for assessing capacity in fisheries.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.315-333
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.