• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.232-235
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• 2003

In general, the parameters of climate change include aerosol chemical compounds, aerosol optical depth, greenhouse gases(carbon dioxide, CFCs, methane, nitrous oxide, tropospheric ozone), ozone distribution, precipitation acidity and chemical compounds, persistent organic pollutants and heavy metals, radioactivity, solar radiation including ultra-violet and standard meteorological parameters. Over the last ten years, the monitoring activities of Korea regarding to the climate change have been progressed within the WMO GAW and ACE-Asia IOP programs centered at the observation sites of Anmyeon and Jeju Gosan islands respectively. The Greenhouse gases were pointed out that standard air quality monitoring techniques are required to enhance data comparability and that data presentation formats need to be harmonized and easily understood. Especially, the impact of atmospheric aerosols on climate depends on their optical properties, which, in turn, are a function of aerosol size distribution and the spectral reflective indices. Aerosol optical depth and single scattering albedo in the visible are used as the two basic parameters in the atmospheric temperature variation studies. The former parameter is an indicator of the attenuation power of aerosols, while the latter represents the relative strength of scattering and absorption by aerosols. For aerosols with weak absorption, surface temperature decreases as the optical depth increases because of the domination of backscattering. For aerosols with strong absorption, however, warming could occur as the optical depth increases. The objective of the study is to characterize the means, variability, and trends of Greenhouse gases and aerosol properties on a regional basis using data from its baseline observatories in Korea peninsula. A further goal is to understand the factors that control radiative forcing of the greenhouse and aerosol.

• Journal of the Korean Vacuum Society
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• v.16 no.5
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• pp.338-342
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• 2007

The magnesium oxide (MgO) protective layer plays an important role in plasma display panels (PDPs). In this paper, we describe the structural and discharge properties of MgO thin films, which were prepared by the ion-beam-assisted deposition (IBAD) of oxygen as the protective layer of PDPs. The energy of the oxygen ion beam was used as the parameter to control the deposition. We found that the oxygen ion beam energy was effective in determining in structural and discharge characteristics. The lowest firing inception voltage, the highest brightness and the highest luminous efficiency were obtained when the MgO thin film was deposited with an oxygen ion beam energy of 300 eV. The crystallization of the MgO thin film was also measured by X-ray diffraction analysis, and the surface quality was measured by atomic force microscopy.

• Journal of Korea Water Resources Association
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• v.37 no.1
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• pp.67-75
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• 2004

In this study, real-time forecasting model(Neural Dam Inflow Forecasting Model; NDIFM) based on neural network to predict the dam inflow which is occurred by flood runoff is developed and applied to check its availability for the operation of multi-purpose reservoir Developed model Is applied to predict the flood Inflow on dam Nam-Gang in Nak-dong river basin where the rate of flood control dependent on reservoir operation is high. The input data for this model are average rainfall data composed of mean areal rainfall of upstream basin from dam location, observed inflow data, and predicted inflow data. As a result of the simulation for flood inflow forecasting, it is found that NDIFM-I is the best predictive model for real-time operation. In addition, the results of forecasting used on NDIFM-II and NDIFM-III are not bad and these models showed wide range of applicability for real-time forecasting. Consequently, if the quality of observed hydrological data is improved, it is expected that the neural network model which is black-box model can be utilized for real-time flood forecasting rather than conceptual models of which physical parameter is complex.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.3
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• pp.251-257
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• 2012

The flight controller should meet the flying qualities, stability margins, and time response requirement according to the class of a target aircraft or UAV. Classical design process of PID controller is a very time consuming process and needed trial and erros. The best way is to apply the multi-disciplinary optimization algorithm to meet the numerous constraints of controller requirements. This paper presents how multi-objective parameter optimization (CONDUIT) can be used to determine many design parameters of lateral stability and augmentation system for roll and heading controller of the small UAV. To verify the effectiveness of applying the optimization method, designed controller using optimization are compared with the baseline controller that is designed only considering the time responses.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1251-1264
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• 2018

The systematic and effective design method of a Class-D current-source resonant inverter for use in an induction cooker with zero-ripple line current is presented. The design procedure is based on the principle of the Class-D current-source resonant inverter with a simplified load network model that is a parallel equivalent circuit. An induction load characterization is obtained from a large-signal excitation test-bench based on parallel load network, which is the key to an accurate design for the induction cooker system. Accordingly, the proposed scheme provides a systematic, precise, and feasible solution than the existing design method based on series-parallel load network under low-signal excitation. Moreover, a zero-ripple condition of utility-line input current is naturally preserved without any extra circuit or control. Meanwhile, a differential-mode input electromagnetic interference (EMI) filter can be eliminated, high power quality in utility-line can be obtained, and a standard-recovery diode of bridge-rectifier can be employed. The step-by-step design procedure explained with design example. The devices stress and power loss analysis of induction cooker with a parallel load network under large-signal excitation are described. A 2,500-W laboratory prototype was developed for $220-V_{rms}/50-Hz$ utility-line to verify the theoretical analysis. An efficiency of the prototype is 96% at full load.

• Journal of Power Electronics
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• v.11 no.3
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• pp.360-368
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• 2011

This paper proposes an active frequency with a positive feedback in the d-q frame anti-islanding method suitable for a robust phase-locked loop (PLL) algorithm using the FFT concept. In general, PLL algorithms for grid-connected PV PCS use d-q transformation and controllers to make zero an imaginary part of the transformed voltage vector. In a real grid system, the grid voltage is not ideal. It may be unbalanced, noisy and have many harmonics. For these reasons, the d-q transformed components do not have a pure DC component. The controller tuning of a PLL algorithm is difficult. The proposed PLL algorithm using the FFT concept can use the strong noise cancelation characteristics of a FFT algorithm without a PI controller. Therefore, the proposed PLL algorithm has no gain-tuning of a PI controller, and it is hardly influenced by voltage drops, phase step changes and harmonics. Islanding prediction is a necessary feature of inverter-based photovoltaic (PV) systems in order to meet the stringent standard requirements for interconnection with an electrical grid. Both passive and active anti-islanding methods exist. Typically, active methods modify a given parameter, which also affects the shape and quality of the grid injected current. In this paper, the active anti-islanding algorithm for a grid-connected PV PCS uses positive feedback control in the d-q frame. The proposed PLL and anti-islanding algorithm are implemented for a 250kW PV PCS. This system has four DC/DC converters each with a 25kW power rating. This is only one-third of the total system power. The experimental results show that the proposed PLL, anti-islanding method and topology demonstrate good performance in a 250kW PV PCS.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.980-993
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• 2020

Deep-learning based style transfer has recently attracted great attention, because it provides high quality transfer results by appropriately reflecting the high level structural characteristics of images. This paper deals with the problem of providing more stable and more diverse style transfer results of such deep-learning based style transfer method. Based on the investigation of the experimental results from the wide range of hyper-parameter settings, this paper defines the problem of the stability and the diversity of the style transfer, and proposes a partial loss normalization method to solve the problem. The style transfer using the proposed normalization method not only gives the stability on the control of the degree of style reflection, regardless of the input image characteristics, but also presents the diversity of style transfer results, unlike the existing method, at controlling the weight of the partial style loss, and provides the stability on the difference in resolution of the input image.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.369-377
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• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.70-76
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• 2009

In speech communications in noisy environments, speech intelligibility is seriously degraded due to the masking effect of ambient noise. In this paper, a new method to improve speech intelligibility in noisy environments is proposed. Based on the perception theory that the temporal envelope plays a major role in determining intelligibility, the proposed method uses a novel operation that enhances the fluctuation of band-wise temporal envelope and also contains pitch enhancement for improving speech naturalness. In addition, a new subjective evaluation scheme employing binaural listening is proposed in order to measure more reliable performance. The subjective performance measured with the proposed scheme shows that the proposed method improves both intelligibility and naturalness in various environments, whereas a function parameter can control the performance trade-off between intelligibility and naturalness.