• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9B
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• pp.1527-1533
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• 2000

Basically, a general characterization procedure based on the extraction of the characteristic impedance and propagation constant for analyzing a single MIS(Metal-Insulator-Semiconductor) transmission line is used. In this paper, an analysis for a new substrate shielding MIS structure consisting of grounded cross-bars at the interface between Si and SiO2 layer using the Finite-Difference Time-Domain (FDTD) method is presented. In order to reduce the substrate effects on the transmission line characteristics, a shielding structure consisting of grounded cross bar lines over time-domain signal has been examined. The extracted distributed frequency-dependent transmission line parameters and corresponding equivalent circuit parameters as well as quality factor have been examined as functions of cross-bar spacing and frequency. It is shown that the quality factor of the transmission line can be improved without significant change in the characteristic impedance and effectve dielectric constant.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.213-225
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• 2018

For constructing three-dimensional (3D) spatial information occlusion region problem arises in the process of taking the texture of the building. In order to solve this problem, it is necessary to investigate the automation method to automatically recognize the occlusion region, issue it, and automatically complement the texture. In fact there are occasions when it is possible to generate a very large number of structures and occlusion, so alternatives to overcome are being considered. In this study, we attempt to apply an approach to automatically create an occlusion region based on learning by patterning the blocked region using the recently emerging deep learning algorithm. Experiment to see the performance automatic detection of people, banners, vehicles, and traffic lights that cause occlusion in building walls using two advanced algorithms of Convolutional Neural Network (CNN) technique, Faster Region-based Convolutional Neural Network (R-CNN) and Mask R-CNN. And the results of the automatic detection by learning the banners in the pre-learned model of the Mask R-CNN method were found to be excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.543-548
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• 2021

The higher the resolution of the image, the higher the satisfaction of the viewers of the image, and the super-resolution imaging has a considerable increase in research value among the fields of computer vision and image processing. In this study, the main features of low-resolution image LR are extracted mainly using deep learning super-resolution models. It learns and reconstructs the extracted features, and focuses on reconstruction-based algorithms that generate high-resolution image HR. In this paper, we investigate SRCNN and VDSR in a super-resolution algorithm model based on reconstruction. The structure and algorithm process of the SRCNN and VDSR model are briefly introduced, and the multi-channel and special form are also examined in the improved performance evaluation function, and understand the performance of each algorithm through experiments. In the experiment, an experiment was performed to compare the results of the SRCNN and VDSR models with the peak signal-to-noise ratio and image structure similarity, so that the results can be easily judged.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.115-126
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• 2023

Due to the fluctuating random and periodical nature of renewable energy generation power quality disturbances occurred more frequently in power generation transformation transmission and distribution. Various power quality disturbances may lead to equipment damage or even power outages. Therefore it is essential to detect and classify different power quality disturbances in real time automatically. The traditional PQD identification method consists of three steps: feature extraction feature selection and classification. However, the handcrafted features are imprecise in the feature selection stage, resulting in low classification accuracy. This paper proposes a deep neural architecture based on Convolution Neural Network and Long Short Term Memory combining the time and frequency domain features to recognize 16 types of Power Quality signals. The frequency-domain data were obtained from the Fast Fourier Transform which could efficiently extract the frequency-domain features. The performance in synthetic data and real 6kV power system data indicate that our proposed method generalizes well compared with other deep learning methods.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.362-369
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• 2006

In this paper, we improve a Physical modeling of sanio gayageum and synthesize sounds by right-hand playing styles. Parameters of loop filter are estimated from decay region of recorded sound. That results in improved accuracy and reduction of computational costs. Body is implemented to a resonator which has characteristics of main resonances extracted from impulse response. Residual signal with main resonances removed is used as excitation signal of proposed model. Amok alter is approximated to frequency response of amok and is implemented to the 15th order all-role digital filter. Beating (by middle and index finger) among the right-hand playing styles is represented by feedforward comb filter. Parameters of this filter are extracted from recorded sound. The synthesized sounds using improved physical model of sanjo gayageum. plucking and beating, are pretty similar to original sounds.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.1
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• pp.34-38
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• 2017

Myelophycus simplex Papenfuss, a type of brown algae, is known to be majorly distributed in along the southern coast of Korea and Japan. The purpose of this study was to investigate the effects of M. simplex Papenfuss methanol extract (MSPME) on melanogenesis in ${\alpha}$-melanocyte-stimulating hormone-stimulated B16F10 melanoma cells. Melanin contents of B16F10 melanoma cells were decreased by 27, 41, and 59% in a dose-dependent manner, upon MSPME treatment at 100, 300, and $500{\mu}g/mL$, respectively. Tyrosinase activities in B16F10 melanoma cells were decreased by 18, 49, and 61% in a dose-dependent manner, upon MSPME treatment at 100, 300, and $500{\mu}g/mL$, respectively. MSPME suppressed expression of tyrosinase, tyrosinase-related protein-1, tyrosinase-related protein-2, and melanocyte-inducing transcription factor in B16F10 melanoma cells. Concentration of $50{\mu}g/mL$ of MSPME especially induced greater decreases in tyrosinase activity, melanin contents, and melanogenic enzyme protein expressions. This results indicate that MSPME inhibits melanin synthesis and tyrosinase activity, and M. simplex Papenfuss extract may be an ideal candidate as a skin whitening agent.

• Journal of Mushroom
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• v.19 no.3
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• pp.225-233
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• 2021

In this study, we evaluated the anti-inflammatory effect of extract from Cudrania tricuspidata twig sawdust fermented with Ganoderma lucidum mycelium. Fermented Cudrania tricuspidata twig sawdust extracted with 70% ethanol and elucidated the potential signaling pathway in lipopolysaccharide (LPS)-induced RAW264.7 cells. Fermented Cudrania tricuspidata twig sawdust inhibits LPS-stimulated nitric oxide (NO) production without affecting cell viability in a dose-dependent manner and production of LPS-induced pro-inflammatory cytokines such as interleukin (IL)-1β, tumor necrosis factor (TNF)-α and prostaglandin2 (PGE₂). Fermented Cudrania tricuspidata twig sawdust also suppressed the expression of the pro-inflammatory mediators such as inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) in LPS-stimulated RAW264.7 cells. Moreover, Fermented Cudrania tricuspidata twig sawdust significantly attenuated LPS-induced IkappaB (IκB) degradation and suppressed nuclear factor kappa B (NF-κB) nuclear translocation. These results suggest that fermented Cudrania tricuspidata twig sawdust may have great potential for the development of anti-inflammatory agent.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.121-132
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• 2011

A healthcare system is a type of medical information system that performs early detection and prevention in diseases by checking one's health condition periodically. Such a healthcare system is based on the signal obtained from the body. However, the developed existing system represents certain differences in the storage and description of vital signs according to medicare devices and the evaluation method of the system. It brings some disadvantages, such as lacks in the interoperability between systems, increases in the development cost of systems, and absence of a unified system. Thus, this study develops a healthcare system based on a meta model. For establishing this objective, this study describes and stores vital sign data based on the standard meta model of HL7 and applies OCL, which is a mathematical specification language, for defining wellness indexes and extracting data in order to evaluate health risk appraisals in health. In addition, this study implements components based on OSGi and assemble them in order to easily extend various devices and systems. By describing vital data based on the meta model, it represents some advantages that it makes possible to ensure the interoperability between systems and introduce the standardization of the evaluation method of health conditions through defining the wellness index using OCL. Also, it provides dear specifications.

• Korean Journal of Food Science and Technology
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• v.50 no.5
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• pp.555-563
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• 2018

Barley has nutritional benefits due to its high dietary fiber content; therefore, the intake of whole barley grains is recommended. However, barley is often consumed in the fermented form because of the improved texture and digestibility. The present study was designed to elucidate the intracellular signaling pathway for macrophage activation by the polysaccharide BF-CP from fermented barley. BF-CP is a neutral polysaccharide, composed of neutral sugars, including glucose (70.7%), xylose (11.4%), and arabinose (9.0%). BF-CP exhibited macrophage-stimulatory activity by inducing the production of interleukin (IL)-6, tumor necrosis factor $(TNF)-{\alpha}$, and nitric oxide in RAW 264.7 macrophages. Further, BF-CP treatment strongly increased the IL-6 and $TNF-{\alpha}$ gene expression in a concentration-dependent manner. Signal transduction experiments using immunoblotting showed that BF-CP phosphorylated mitogen-activated protein kinases (MAPKs), such as c-Jun N-terminal kinase, extracellular signal-regulated kinase, and p38, and nuclear factor $(NF)-{\kappa}B$, in RAW 264.7 cells in a concentration-dependent manner. These results suggest that BF-CP activates the macrophages via MAPK and $NF-{\kappa}B$ pathways, and also induces an increase in the production of cytokines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.7
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• pp.49-53
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• 2016

Recently, the use of signal compression methods to improve the efficiency of wireless networks have increased. In particular, the MPC system was used in the pitch extraction method and the excitation source of voiced and unvoiced to reduce the bit rate. In general, the MPC system using an excitation source of voiced and unvoiced would result in a distortion of the synthesis speech waveform in the case of voiced and unvoiced consonants in a frame. This is caused by normalization of the synthesis speech waveform in the process of restoring the multi-pulses of the representation segment. This paper presents an ACFBD-MPC (Amplitude Compensation Frequency Band Division-Multi Pulse Coding) using amplitude compensation in a multi-pulses each pitch interval and specific frequency to reduce the distortion of the synthesis speech waveform. The experiments were performed with 16 sentences of male and female voices. The voice signal was A/D converted to 10kHz 12bit. In addition, the ACFBD-MPC system was realized and the SNR of the ACFBD-MPC estimated in the coding condition of 8kbps. As a result, the SNR of ACFBD-MPC was 13.6dB for the female voice and 14.2dB for the male voice. The ACFBD-MPC improved the male and female voice by 1 dB and 0.9 dB, respectively, compared to the traditional MPC. This method is expected to be used for cellular telephones and smartphones using the excitation source with a low bit rate.