• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.100-110
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• 2007

When compressed video data is transmitted over error-prone network such as wireless channel, data is likely to be lost, so the quality of reconstructed picture is severely decreased. It is specially so in case that important information such as motion vector or macroblock mode is lost. H.264/AVC standard includes DP as error resilient technique for protecting important information from error in which data is labeled according to its relative importance. But DP technique requires a network that supports different reliabilities of transmitted data. In general, the benefits of UEP is sought by sending multiple times of same packets corresponding to important information. In this paper, we propose MDC technique based on data partitioning technique. The proposed method encodes motion vector of H.264/AVC standard into multiple parts using MDC and transmits each part as independent packet. Even if partial packet is lost, the proposed scheme can decode the compressed bitstream by using estimated motion vector with partial packets correctly transmitted, so that achieving improved performance of error concealment with minimal effect of channel error. Also in decoding process, the proposed multiple description matching increases the accuracy of estimated lost motion vector and quality of reconstructed video.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.499-501
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• 2016

In this paper, we suggest an advance method for maintaining a perceived behavior as triangle formation and preventing collision between each other in case of a flying drone. In the existing studies, the collision of the drone is only controlled by using light entered in the camera or the image processing. However, when there is no light, it is difficult to confirm the position of each other and they can collide because this system can not confirm the each other's position. Therefore, in this paper, we propose the system to solve the problems by using the distance and the relative coordinates of the three drones that were determined using the ALPS(Ad hoc network Localized Positioning System) algorithm. This system can be a new algorithm that will prevent collisions between each other during flying the drone object. The proposed algorithm is that we make drones maintaining a determined constant value of the distance between coordinates of each drone and the measured center of the drone of triangle formation. Therefore, if the form of fixed formation is disturbed, they reset the position of the drone so as to keep the distance between each drone and the center coordinates constant. As a result of the simulation, if we use the system where the supposed algorithm is applied, we can expect that it is possible to prevent malfunction or an accident due to collisions by preventing collisions of drones in advanced behavior system.

• Korea journal of population studies
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• v.20 no.2
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• pp.67-98
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• 1997

This study examines multi-level factors geographic proximities between elderly parents and their children in the United States and Japan. Despite their similar economies, the United States and Japan show a significant difference in their patterns of generational proximity. In 1993, half of US non-Hisapnic white parents aged 70 or over lived separately but within 10 miles of their nearest children and a majority of them lived far from their non-nearest children. The family geographic network for Japanese elderly parents is more hierarchial. In 1989, 74 percent of Japanese parents aged 70 and over lived with their nearest children but most of them lived far from their non-nearest children. To explain this distinctive pattern of inter- and intra-family differences in generational proximities in the two societies, this study employs a multi-level analysis which compares the relative importance of life course conditions of elderly parents and their children and economic and ecological characteristics of elderly parent's places of residence in influencing generational proximities.

• Journal of the Korean Magnetics Society
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• v.8 no.5
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• pp.300-307
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• 1998

The $Co_{90}Fe_{10}$ single layer films were deposited on various substrates (glass, Si, polymide) using high vacuum RF magnetron sputtering system and nominall 1000 $\AA$ thick $Co_{90}Fe_{10}$ alloy films had a good high frequency characteristic. $M_S$ and $H_{an}$ values obtained from the B-H characteristic of the $10{\times}[100 nm \;Co_{90}Fe_{10}/100 nm\; SiO_2]$ multilayers agreed well with those obtained by calculation. Complex relative permeability $(={\{\mu}_r={\mu}_r',-j{\mu}$\mu$_r")$ at frequency f was measured from the transmission characteristics $(S_{11},\; S_{21}\;parameters)$ of the microstrip line which has a stacked structure consisting of sample magnetic films and a conductor and is connected to a network analyzer. The ${\mu}_r'-f$ characteristic was abtained from the megnetic absorption, which was analyzed from the S-parameter characteristics of the microstrip line. The ${\mu}_r'-f$ characteristic was also calculated from the ${\mu}_r"-f$-f characteristic using the Kramers-Kronig relation. The measurement results were confirmed to agree well with those obtained by calculations.culations.

• The Journal of Engineering Geology
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• v.13 no.4
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• pp.405-418
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• 2003

Measurements of volumetric water content and saturation of porous media are very important factors in understanding the physical characteristics of soil, groundwater recharge by rainfall, pollutant movement, and slope failure. To measure such physical parameters, a permittivity method using electromagnetic wave is applied and use is made of the special permittivity response of understand to water and ethanol. In particular, the estimation is required because permittivity is influenced by the nature of the underground environment. In this study, we carried out experiments on the relative dependency of soil density, temperature and salinity of standard sand and granitic weathered soil using FDR-V system (Frequency domain reflectometry with vector network analyzer) within a frequency range of 1 - 18 GHz. The results of the study showed that the dielectric constants of standard sand and granitic weathered soil increased with increased volumetric water content of soil. However, the dependency of soil density was found to be a little low. Changes of dielectric constant with temperature appeared definitely in the real part of 1 GHz. That is, the dielectric constant of real part at 1 GHz of water and standard sand increased with the rise of temperature. However, ethanol showed decreased tendency. The study also showed that dielectric constant increased with increase in salinity at imaginary part of 1 GHz. It could be concluded from this study FDR-V system can adequately measure the physical properties of soil and the degree of salinity concentration of porous media within 1 GHz frequency range using dielectric constant.

• Korean Journal of Materials Research
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• v.9 no.12
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• pp.1234-1239
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• 1999

Electromagnetic wave asorbing properties of the $Ni_{0.5}-Zn_{0.4}-X_{0.1}{\cdot}Fe_2O_4$, where X was replaced by substitution elements Cu, Mg, Mn, have been studied. The structure, shape, size and magnetic properties of the $Ni_{0.5}-Zn_{0.4}-X_{0.1}{\cdot}Fe_2O_4$ were analyzed by XRD, SEM, VSM. The relative complex permittivity, permeability, and electromagnetic wave absorbing properties were measured by Network Analyzer. The structure, shape, size and magnetization value of the $Ni_{0.5}-Zn_{0.4}-X_{0.1}{\cdot}Fe_2O_4$ were found to be similar in spite of substitution elements. The coercive force and hysteresis-loss showed maximum value when Mg was substituted for X. The dielectric loss(${\varepsilon}_r"/{\varepsilon}_r'$) was found to be maximum value when Mn was substituted for X. Also the magnetic loss(${\mu}_r"/{\mu}_r'$} was found to be maximum with Cu substitution. The electromagnetica wave absorbing property of the $Ni_{0.5}-Zn_{0.4}-X_{0.1}{\cdot}Fe_2O_4$-Rubber composite with 4mm thickness was excellent as over - 40dB at 9GHz, and the $Ni_{0.5}-Zn_{0.4}-X_{0.1}{\cdot}Fe_2O_4$-Rubber composite with 8mm thickness was over-40dB at 2GHz. Those composites also showed superior microwave absorbing properties.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.63-73
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• 2015

In the end to end data transfer protocols, it is very important to correctly estimate available bandwidth. In UDT (UDP based Data Transfer), receiver estimates the MTR (Maximum Transfer Rate) of the current link using pair packets transmitted periodically from sender and, then sender finally decides the MTR through EWMA (Exponential Weighted Moving Average) algorithm. Here, MTR has to be exactly estimated because available bandwidth is calculated with difference of MTR and current transfer rate. However, when network is congested due to traffic load and where competing flows are coexisted, it bring about a severe fairness problem. This paper proposes a congestion degree based MTR estimation algorithm. Here, the congestion degree stands a relative index for current congestion status on bottleneck link, which is calculated with arriving intervals of a pair packets. The algorithm try to more classify depending on the congestion degree to estimate more actual available bandwidth. With the network simulation results, our proposed method showed that the fairness problem among the competing flows is significantly resolved in comparison with that of UDT.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.137-147
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• 2022

Diagnosis and management of skin condition is a very basic and important function in performing its role for workers in the beauty industry and cosmetics industry. For accurate skin condition diagnosis and management, it is necessary to understand the skin condition and needs of customers. In this paper, we developed SCIS, a big data-based skin care information system that supports skin condition diagnosis and management using social media big data for skin condition diagnosis and management. By using the developed system, it is possible to analyze and extract core information for skin condition diagnosis and management based on text information. The skin care information system SCIS developed in this paper consists of big data collection stage, text preprocessing stage, image preprocessing stage, and text word analysis stage. SCIS collected big data necessary for skin diagnosis and management, and extracted key words and topics from text information through simple frequency analysis, relative frequency analysis, co-occurrence analysis, and correlation analysis of key words. In addition, by analyzing the extracted key words and information and performing various visualization processes such as scatter plot, NetworkX, t-SNE, and clustering, it can be used efficiently in diagnosing and managing skin conditions.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.342-350
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• 2022

In this paper, actual drone noise samples are collected for speech processing in disaster environments to build noise-corrupted speech database, and speech enhancement performance is evaluated by applying spectrum subtraction and mask-based speech enhancement techniques. To improve the performance of VoiceFilter (VF), an existing deep neural network-based speech enhancement model, we apply the Self-Attention operation and use the estimated noise information as input to the Attention model. Compared to existing VF model techniques, the experimental results show 3.77%, 1.66% and 0.32% improvements for Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligence (STOI), respectively. When trained with a 75% mix of speech data with drone sounds collected from the Internet, the relative performance drop rates for SDR, PESQ, and STOI are 3.18%, 2.79% and 0.96%, respectively, compared to using only actual drone noise. This confirms that data similar to real data can be collected and effectively used for model training for speech enhancement in environments where real data is difficult to obtain.