• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.52-60
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• 2005

Generally, a voltage difference or voltage distortion exists between the reference voltage and the practical voltage applied to a motor in a pulse width modulated(PWM) voltage source inverter(VSI). This voltage distortion varies with the operating conditions such as the temperature, DC link voltage, and phase current level. Also the voltage distortion affects the machine current distortion, torque pulsations, and control performance. In this paper, the voltage distortion in a PWM VSI is analyzed and a new on-line estimation method based on the model reference adaptive system(MRAS) is proposed to compensate the time varying voltage distortion, while considering the parameter variations for a permanent magnet synchronous motor (PMSM). The simulation and experimental results show the effectiveness of the proposed voltage difference observer and the compensation method.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.583-598
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• 2015

This paper presents derivation of background temperature from geostationary satellite and its validation based on ground measurements and Geographic Information System (GIS) for future use in weather and surface heat variability. This study only focuses on daily and monthly brightness temperature in 2012. From the analysis of COMS Meteorological Data Processing System (CMDPS) data, we have found an error in cloud distribution of model, which used as a background temperature field, and in examining the spatial homogeneity. Excessive cloudy pixels were reconstructed by statistical reanalysis based on consistency of temperature measurement. The derived Brightness temperature has correlation of 0.95, bias of 0.66 K and RMSE of 4.88 K with ground station measurements. The relation between brightness temperature and both elevation and vegetated land cover were highly anti-correlated during warm season and daytime, but marginally correlated during cold season and nighttime. This result suggests that time varying emissivity data is required to derive land surface temperature.

• Journal of Power Electronics
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• v.19 no.4
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• pp.881-893
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• 2019

This paper proposes a practical sliding-mode controller design for shaping the impedances of cascaded boost-converter power decoupling circuits for reducing the second order harmonic ripple in photovoltaic (PV) current. The cascaded double-boost converter, when used as power decoupling circuit, has some advantages in terms of a high step-up voltage-ratio, a small number of switches and a better efficiency when compared to conventional topologies. From these features, it can be seen that this topology is suitable for residential (PV) rooftop systems. However, a robust controller design capable of rejecting double frequency inverter ripple from passing to the (PV) source is a challenge. The design constraints are related to the principle of the impedance-shaping technique to maximize the output impedance of the input-side boost converter, to block the double frequency PV current ripple component, and to prevent it from passing to the source without degrading the system dynamic responses. The design has a small recovery time in the presence of transients with a low overshoot or undershoot. Moreover, the proposed controller ensures that the ripple component swings freely within a voltage-gap between the (PV) and the DC-link voltages by the small capacitance of the auxiliary DC-link for electrolytic-capacitor elimination. The second boost controls the main DC-link voltage tightly within a satisfactory ripple range. The inverter controller performs maximum power point tracking (MPPT) for the input voltage source using ripple correlation control (RCC). The robustness of the proposed control was verified by varying system parameters under different load conditions. Finally, the proposed controller was verified by simulation and experimental results.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.35-41
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• 2022

Heavy snow damage can be prevented in advance with an appropriate security system. To develop the security system, we developed a model that predicts snow depth after a few hours when the snow depth is observed, and utilized it to calculate a failure probability with various types of greenhouses and observed snow depth data. We compared the Markov chain model and Bayesian long short-term memory models with varying input data. Markov chain model showed the worst performance, and the models that used only past snow depth data outperformed the models that used other weather data with snow depth (temperature, humidity, wind speed). Also, the models that utilized 1-hour past data outperformed the models that utilized 3-hour data and 6-hour data. Finally, the Bayesian LSTM model that uses 1-hour snow depth data was selected to predict snow depth. We compared the selected model and the shifting method, which uses present data as future data without prediction, and the model outperformed the shifting method when predicting data after 11-24 hours.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1863-1871
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• 2022

In the era of Fourth Industrial Revolution, secure networking technology is playing an essential role in the defense weapon systems. Encryption technology is used for information security. The safety of cryptographic technology, according to Kerchoff's principles, is based on secure key management of cryptographic technology, not on cryptographic algorithms. However, traditional centralized key management is one of the problematic issues in battlefield environments since the frequent movement of the forces and the time-varying quality of tactical networks. Alternatively, the system resources of each node used in the IoBT(Internet of Battlefield Things) environment are limited in size, capacity, and performance, so a lightweight key management system with less computation and complexity is needed than a conventional key management algorithm. This paper proposes a novel key escrow scheme in a lightweight manner for the IoBT environment. The safety and performance of the proposed technique are verified through numerical analysis and simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1659-1674
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• 2024

Conventional maritime communication struggles to provide high data rate services for Internet of Things (IoT) devices due to the variability of maritime environments, making it challenging to ensure consistent connectivity for onboard sensors and devices. To resolve this, we perform mathematical modeling of the maritime channel and compare it with real measurement data. Through the modeled channel, we verify the received beam gain at buoys on the ocean surface. Additionally, leveraging the modeled wave motions, we estimate future angles of the buoy to use the Extended Kalman Filter (EKF) for design beamforming strategies that adapt to the evolving maritime environment over time. We further validate the effectiveness of these strategies by assessing the results from an outage probability perspective. focuses on improving maritime communication by developing a dynamic model of the maritime channel and implementing a Kalman filter-based buoy motion tracking system. This system is designed to enable precise beamforming, a technique used to direct communication signals more accurately. By improving beamforming, the aim is to enhance the quality of communication links, even in challenging maritime conditions like rough seas and varying sea states. In our simulations that consider realistic wave motions, you've observed significant improvements in link quality due to the enhanced beamforming technique. These improvements are particularly notable in environments with high sea states, where communication challenges are typically more pronounced. The progress made in this area is not just a technical achievement; it has broad implications for the future of maritime communication technologies. This paper promises to revolutionize the way we approach communication in maritime environments, paving the way for more reliable and efficient information exchange on the seas.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.149-160
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• 2023

This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4A
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• pp.421-430
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• 2006

In this paper, we propose a practical implementation of network-adaptive HD(high definition) MPEG-2 video streaming with a cross-layered channel monitoring(CLM) over the IEEE 802.11a WLAN(wireless local area network). For wireless channel monitoring, AP(access point) periodically measures the MAC(medium access control) layer transmission information and sends the monitoring information to a streaming server. This makes that the streaming server reacts more quickly as well as efficiently to the fluctuated wireless channel than that of the end-to-end monitoring(E2EM) scheme for the video adaptation. The streaming sewer dynamically performs the priority-based frame dropping to adjust the video sending rate according to the measured wireless channel condition. For this purpose, our streaming system nicely provides frame-based prioritized packetization by using a real-time stream parsing module. Various evaluation results over an IEEE 802.11a WLAM testbed are provided to verify the intended QoS adaptation capability The experimental results show that the proposed system can effectively mitigate the quality degradation of video streaming caused by the fluctuations of time-varying wireless channel condition.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.244-247
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• 2022

In this paper, the performance of the decoding schemes using linear MMSE filters in the frequency and time domains and the reinforcement Gauss-Seidel algorithm for the orthogonal time frequency space (OTFS) system that can improve robustness under high-speed mobile environments are compared. The reinforcement Gauss-Seidel algorithm can improve the bit error rate performance by suppressing the noise enhancement. The simulation results show that the performance of the decoding scheme using the linear MMSE filter in the frequency domain is severely degraded due to the effect of Doppler shift as the mobile speed increases. In addition, the decoding scheme using the reinforcement Gauss-Seidel algorithm under the channel environment with 120 km/h and 500 km/h speeds outperforms the decoding schemes using linear MMSE filters in the frequency and time domains.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.405-414
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• 2011

The adaptive network-based fuzzy inference system (ANFIS) which had a success for time series prediction and system control was applied for modeling the hourly runoff in the Gapcheon watershed. The ANFIS used the antecedent rainfall and runoff as the input. The ANFIS was trained by varying the various simulation factors such as mean areal rainfall estimation, the number of input variables, the type of membership function and the number of membership function. The root mean square error (RMSE), mean peak runoff error (PE), and mean peak time error (TE) were used for validating the ANFIS simulation. The ANFIS predicted runoff was in good agreement with the measured runoff and the applicability of ANFIS for modelling the hourly runoff appeared to be good. The forecasting ability of ANFIS up to the maximum 8 lead hour was investigated by applying the different input structure to ANFIS model. The accuracy of ANFIS for predicting the hourly runoff was reduced as the forecasting lead hours increased. The long-term predictability of ANFIS for forecasting the hourly runoff at longer lead hours appeared to be limited. The ANFIS might be useful for modeling the hourly runoff and has an advantage over the physically based models because the model construction of ANFIS based on only input and output data is relatively simple.