• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.294-298
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• 2019

Pulsed laser-based optical sensor monitoring systems for real time microplastic particle counting are proposed and developed in this study. To develop our real time monitoring system, we used a 450 nm pulsed laser and a photomultiplier with very high quantum efficiency. First, we demonstrated that the microplastic particle counting system could detect standard micro bead samples of 100, 250, and $500{\mu}m$ in river water. We then performed research concerning pulsed laser-based optical spectral sensor systems for real time microplastic monitoring. Additionally, we demonstrated that the real time microplastic remote monitoring system using LoRa communications could detect microplastic in the tap water resource protection area.

• Journal of Biomedical Engineering Research
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• v.26 no.2
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• pp.87-93
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• 2005

A new method for real-time estimating left ventricular relaxation time constant (T) from the left ventricular (LV) pressure waveform, based on the isovolumic relaxation model, is proposed. The presented method uses a recursive least squares (RLS) algorithm to accomplish real-time estimation. A new criterion to detect the end-point of the isovolumic relaxation period (IRP) for the estimation of T is also introduced, which is based on the pattern analysis of mean square errors between the original and reconstructed pressure waveforms. We have verified the performance of the new method in over 4,600 beats obtained from 70 patients. The results demonstrate that the proposed method provides more stable and reliable estimation of τ than the conventional 'off-line' methods.

• Korean Journal of Remote Sensing
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• v.37 no.4
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• pp.815-831
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• 2021

Drought forecasting is crucial to minimize the damage to food security and water resources caused by drought. Satellite-based drought research has been conducted since 1980s, which includes drought monitoring, assessment, and prediction. Unlike numerous studies on drought monitoring and assessment for the past few decades, satellite-based drought forecasting has gained popularity in recent years. For successful drought forecasting, it is necessary to carefully identify the relationships between drought factors and drought conditions by drought type and lead time. This paper aims to provide an overview of recent research trends and challenges for satellite-based drought forecasts focusing on lead times. Based on the recent literature survey during the past decade, the satellite-based drought forecasting studies were divided into three groups by lead time (i.e., short-term, sub-seasonal, and seasonal) and reviewed with the characteristics of the predictors (i.e., drought factors) and predictands (i.e., drought indices). Then, three major challenges-difficulty in model generalization, model resolution and feature selection, and saturation of forecasting skill improvement-were discussed, which led to provide several future research directions of satellite-based drought forecasting.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.111-115
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• 2024

This study builds a machine learning model optimized for clocks among various techniques in the field of artificial intelligence and applies it to clock stabilization or synchronization technology based on atomic clock noise characteristics. In addition, the possibility of providing stable source clock data is confirmed through the characteristics of machine learning predicted values during holdover of atomic clocks. The proposed machine learning model is evaluated by comparing its performance with the AutoRegressive Integrated Moving Average (ARIMA) model, an existing statistical clock prediction model. From the results of the analysis, the prediction model proposed in this study (MSE: 9.47476) has a lower MSE value than the ARIMA model (MSE: 221.2622), which means that it provides more accurate predictions. The prediction accuracy is based on understanding the complex nature of data that changes over time and how well the model reflects this. The application of a machine learning prediction model can be seen as a way to overcome the limitations of the statistical-based ARIMA model in time series prediction and achieve improved prediction performance.

• Journal of Navigation and Port Research
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• v.30 no.4
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• pp.285-290
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• 2006

Shipping companies consider most of the ship turnaround time as a critical factor when selecting a rolling port for reducing costs. So, many researchers have been studying for the optimization of preplanning and high~performance of the Gantry Cranes (GCs) in container terminals for faster loading and unloading. Therefore, in this paper, we propose an RFID (Radio Frequency Identification) based RTLS (Real-Time Location System) for reducing the ship turnaround time in ubiquitous port environment. In addition, pre-planning based on ubiquitous computing environment will support the GC and Yard Tractors (YTs), and reduce ship turnaround time more effectively. Especially, the proposed method enormously enhances the productivity of loading for the twin-lift system It will reduce the whole lead-time in the process of port logistics.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.367-370
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• 2006

A GPS-based time synchronization technique employing a refined HW circuitry and SW algorithm is considered as fine time-management system for Low Earth Orbit (LEO) remote sensing satellites. By synchronizing the On-Board Time (OBT) within satellites to the GPS 1PPS, a very expensive, highly accurate on-board clock is not required to determine the precise on-board time management. Also, the satellite command generation in ground stations and postprocessing of earth observation data which a particular image is acquired. This paper analyses on-orbit verification of the existing satellite time sync architecture and presents a new time sync architecture, operation and relation between the OBT and the GPS time.

• Korean Management Science Review
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• v.24 no.1
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• pp.113-126
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• 2007

This paper deals with a mathematical approach for finding the time-fractions for the time-fraction based scheduling method in multimedia wireless networks. By introducing a constraint that regulates the performance fairness amongst users, we present a systematic method for harmonizing both the system and user performance. Numerical results show that the time-fraction based scheduling method reinforced with our scheme is very effective especially in multimedia environments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.10a
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• pp.268-271
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• 2000

In these days, the technical advances and complexities have generated much of the difficulties in managing the project resources, both time and costing to accomplish the project in the most efficient manner. The project manager is frequently required to render judgements concerning the schedule and resource adjustments. This research develops an analytical model for a schedule-cost and risk analysis based on visual PERT/CPM. We used a two-step approaches ：in the step 1, a deterministic PERT/CPM model for the critical path and estimating the project time schedule and related resource planning, In the second step, we developed a heuristic model for crash and stretch out analysis based upon a time-cost trade-off associated with the crash and stretch out of the project. Computer implementation of this model is provided based on GUI-Type objective-oriented programming for the users and provided displays of all the inputs and outputs in the form of visual graphical. Also developed GUI-type program, Dongeui Visual-PERT/CPM. The results of this research will provide the project managers with an efficient management tool.

• The Journal of Engineering Research
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• v.3 no.1
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• pp.123-129
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• 1998

This paper examines the application of imprecise computation technique in the context of rule-based systems and the development of a shell for building rule-based real-time control systems. Research issues to be addressed in order to build such a shell include acquisition and expression of resource information, development of a software architecture to support resource-based selectivity, and acceptability criteria for validating results obtained.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.261-272
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• 2020

A Kalman filter algorithm is used for the generation of an ensemble timescale with three hydrogen masers maintained in KRISS. Allan deviation curves of three pairs of clocks were obtained by a three-cornered hat method and were used as reference curves for determination of parameters of the Kalman filter-based timescale. The ensemble timescale equation of a 3-clock system was established, and the clocks' phases estimated by the Kalman filter were used as the prediction time of each clock in the equation. The weight of each clock was determined inversely proportional to the Allan variance calculated with the clocks' phases. The Allan deviation of the weighted mean was 1.2×10^-16 at the averaging time of 57,600 s. However when we made fine adjustments of the clocks' weight, the minimum Allan deviation of 2×10^-17 was obtained. To find out the reason of the great improvement in the frequency stability, additional researches are in progress theoretically and experimentally.