• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.10
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• pp.2403-2408
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• 2013

This paper has analyzed the change of forward and backward current for channel doping concentration to analyze off-current of double gate(DG) MOSFET. The Gaussian function as channel doping distribution has been used to compare with experimental ones, and the two dimensional analytical potential distribution model derived from Poisson's equation has been used to analyze the off-current. The off-current has been analyzed for the change of projected range and standard projected range of Gaussian function with device parameters such as channel length, channel thickness, gate oxide thickness and channel doping concentration. As a result, this research shows the off-current has greatly influenced on forward and backward current for device parameters, especially for the shape of Gaussian function for channel doping concentration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.4
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• pp.903-908
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• 2015

This paper has analyzed threshold voltage shift for doping profile of asymmetric double gate(DG) MOSFET. Ion implantation is usually used in process of doping for semiconductor device and doping profile becomes Gaussian distribution. Gaussian distribution function is changed for projected range and standard projected deviation, and influenced on transport characteristics. Therefore, doping profile in channel of asymmetric DGMOSFET is affected in threshold voltage. Threshold voltage is minimum gate voltage to operate transistor, and defined as top gate voltage when drain current is $0.1{\mu}A$ per unit width. The analytical potential distribution of series form is derived from Poisson's equation to obtain threshold voltage. As a result, threshold voltage is greatly changed by doping profile in high doping range, and the shift of threshold voltage due to projected range and standard projected deviation significantly appears for bottom gate voltage in the region of high doping concentration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.145-150
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• 2013

This paper has presented the analysis for threshold voltage and drain induced barrier lowering among short channel effects occurred in subthreshold region for double gate(DG) MOSFET as next-generation devices, based on scaling theory. To obtain the analytical solution of Poisson's equation, Gaussian function has been used as carrier distribution to analyze closely for experimental results, and the threshold characteristics have been analyzed for device parameters such as channel thickness and doping concentration and projected range and standard projected deviation of Gaussian function. Since this potential model has been verified in the previous papers, we have used this model to analyze the threshold characteristics. As a result to apply scaling theory, we know the threshold voltage and drain induced barrier lowering are changed, and the deviation rate is changed for device parameters for DGMOSFET.

• Smart Structures and Systems
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• v.24 no.2
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• pp.243-256
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• 2019

Determination of the most meaningful structural modes and gaining insight into how these modes evolve are important issues for long-term structural health monitoring of the long-span bridges. To address this issue, modal parameters identified throughout the life of the bridge need to be compared and linked with each other, which is the process of mode tracking. The modal frequencies for a long-span bridge are typically closely-spaced, sensitive to the environment (e.g., temperature, wind, traffic, etc.), which makes the automated tracking of modal parameters a difficult process, often requiring human intervention. Machine learning methods are well-suited for uncovering complex underlying relationships between processes and thus have the potential to realize accurate and automated modal tracking. In this study, Gaussian mixture model (GMM), a popular unsupervised machine learning method, is employed to automatically determine and update baseline modal properties from the identified unlabeled modal parameters. On this foundation, a new mode tracking method is proposed for automated mode tracking for long-span bridges. Firstly, a numerical example for a three-degree-of-freedom system is employed to validate the feasibility of using GMM to automatically determine the baseline modal properties. Subsequently, the field monitoring data of a long-span bridge are utilized to illustrate the practical usage of GMM for automated determination of the baseline list. Finally, the continuously monitoring bridge acceleration data during strong typhoon events are employed to validate the reliability of proposed method in tracking the changing modal parameters. Results show that the proposed method can automatically track the modal parameters in disastrous scenarios and provide valuable references for condition assessment of the bridge structure.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.327-341
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• 2022

Cloud removal is often required to construct time-series sets of optical images for environmental monitoring. In regression-based cloud removal, the selection of an appropriate regression model and the impact analysis of the input images significantly affect the prediction performance. This study evaluates the potential of Gaussian process (GP) regression for cloud removal and also analyzes the effects of cloud-free optical images and spectral bands on prediction performance. Unlike other machine learning-based regression models, GP regression provides uncertainty information and automatically optimizes hyperparameters. An experiment using Sentinel-2 multi-spectral images was conducted for cloud removal in the two agricultural regions. The prediction performance of GP regression was compared with that of random forest (RF) regression. Various combinations of input images and multi-spectral bands were considered for quantitative evaluations. The experimental results showed that using multi-temporal images with multi-spectral bands as inputs achieved the best prediction accuracy. Highly correlated adjacent multi-spectral bands and temporally correlated multi-temporal images resulted in an improved prediction accuracy. The prediction performance of GP regression was significantly improved in predicting the near-infrared band compared to that of RF regression. Estimating the distribution function of input data in GP regression could reflect the variations in the considered spectral band with a broader range. In particular, GP regression was superior to RF regression for reproducing structural patterns at both sites in terms of structural similarity. In addition, uncertainty information provided by GP regression showed a reasonable similarity to prediction errors for some sub-areas, indicating that uncertainty estimates may be used to measure the prediction result quality. These findings suggest that GP regression could be beneficial for cloud removal and optical image reconstruction. In addition, the impact analysis results of the input images provide guidelines for selecting optimal images for regression-based cloud removal.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.398-401
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• 1997

The EMG signal of spinal cord injured patient is very feeble because that the information from central nervous system is not sufficiently transmitted to molter neuron or muscle fiber. Therefore the observer can not observe contraction and relaxation movement of muscle from the raw EMG signal. In this paper, we propose the muscle contraction and relaxation pattern analysis method of spinal cord injured patient whose EMG signal is composed of the sum of motor unit action potential train with additive white Gaussian noise and impulsive noise. From the EMG model, we denoise impulsive noise using median filter which is a kind of nonlinear filter and the output of median filter is transformed to wavelet transform domain for denoising additive white Gaussian noise using threshold level removal technique. As a result, we can obtain the clear contraction and relaxation pattern.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.917-921
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• 2013

This paper have analyzed the change of breakdown voltage for conduction path of double gate(DG) MOSFET. The low breakdown voltage among the short channel effects of DGMOSFET have become obstacles of device operation. The analytical solution of Poisson's equation have been used to analyze the breakdown voltage, and Gaussian function been used as carrier distribution to analyze closely for experimental results. The change of breakdown voltages for conduction path have been analyzed for device parameters such as channel length, channel thickness, gate oxide thickness and doping concentration. Since this potential model has been verified in the previous papers, we have used this model to analyze the breakdown voltage. Resultly, we know the breakdown voltage is greatly influenced on the change of conduction path for device parameters of DGMOSFET.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.48 no.4
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• pp.261-268
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• 1999

Laser-induced thermochemical etching has been recognized as a new powerful method for processing a variety of materials, including metals, semiconductors, ceramics, insulators and polymers. This study presents characteristics of direct etching for Si substrate using focused argon ion laser beam in aqueous KOH and $CCl_2F_2$ gas. In order to determine process conditions, we first theoretically investigated the temperature characteristics induced by a CW laser beam with a gaussian intensity distribution on a silicon surface. Major process parameters are laser beam power, beam scan speed and reaction material. We have achieved a very high etch rate up to $434.7\mum/sec$ and a high aspect ratio of about 6. Potential applications of this laser beam etching include prototyping of micro-structures of MEMS(micro electro mechanical systems), repair of devices, and isolation of opto-electric devices.

• Bulletin of the Korean Chemical Society
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• v.34 no.4
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• pp.1051-1054
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• 2013

Closo-carborane has been considered as an efficient boron-carrier for boron neutron capture therapy (BNCT) and an attractive surrogate of lipophilic phenyl or cyclohexyl ring in drug design. Despite a great number of carborane-containing ligands have been synthesized and evaluated, molecular modeling studies of carborane ligands with macromolecules have been rarely reported. We herein describe a facile docking and scoring-function strategy of 16 carborane ligands with an estrogen receptor by using the commercial Gaussian, Chem3D Pro and Discovery Studio (DS) computational programs. Docked poses of the carborane ligands in silico exhibited similar binding modes to that of the crystal ligand in the active site of estrogen receptor. Score analysis of the best docked pose for each ligand indicated that the Ligscore1 and the Dockscore have a moderate correlation with in vitro biological activity. This is the first report on the scoring-correlation studies of carborane ligands with macromolecules. The integrated Gaussian-DS approach has a potential application for virtual screening, De novo design, and optimization of carborane ligands in medicinal chemistry.

• Journal of the Optical Society of Korea
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• v.16 no.3
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• pp.305-312
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• 2012

We numerically demonstrate the performance of a plasmonic lens composed of an array of nanoslits perforated on thin metallic film with slanted cuts on the output surface. Embedding Kerr nonlinear material in nanoslits is employed to modulate the output beam. A two dimensional nonlinear-dispersive finite-difference time-domain (2D N-D-FDTD) method is utilized. The performance parameters of the proposed lens such as focal length, full-width half-maximum, depth of focus and the efficiency of focusing are investigated. The structure is illuminated by a TM-polarized plane wave and a Gaussian beam. The effect of the beam waist of the Gaussian beam and the incident light intensity on the focusing effect is explored. An exact formula is proposed to derive electric field E from electric flux density D in a Kerr-Dispersive medium. Surface plasmon (SPs) modes and Fabry-Perot (F-P) resonances are used to explain the physical origin of the light focusing phenomenon. Focused ion beam milling can be implemented to fabricate the proposed lens. It can find valuable potential applications in integrated optics and for tuning purposes.