• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.235-238
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• 1995

In this paper, we propose an effective coding method of the angiography by using the scalable structure in the frequency domain for MPACS(Medical Picture Archiving and Communication System). We employed the subband decomposition method and MPEG-2 system which is the international standard coding method of the general moving picture. After the subband decomposition is applied to split an input image into 4 bands in the spatial frequency domain, the motion compensated DPCM coding method of MPEG-2 is carried out for each subband. As a result, an easily controllable coding Structure is accomplished by composing the compound hit stream for each subband group. Follows are the simulation results of the proposed sheme for the angiography. A scalable structure which can be easily controlled for a loss of transmission or the band limit can be accomplisbed in the MPEG-2 stucture by the subband decomposition minimizing the side information. And by reducing the search area of the motion vector between -4 and 3, the processing speed of a codec is enhanced by more than two times without a loss of the picture quality compare with the conventional DCT coefficients decompositon method. And the processing speed is considerably improved in the case of the parallel construction of each subband in the hardware.

• Journal of IKEEE
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• v.21 no.3
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• pp.202-210
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• 2017

Recently, some variable length adaptive filters which employ variable lengths taps for the input signal statistics are proposed [1-5]. In this paper, a new subband adaptive filter with variable filter tap length is proposed. The proposed subband variable length adaptive filters can optimize filter length for each subband which can result less computational complexities with respect to the conventional full band adaptive filters. When the signal in the full band has narrow spectrum, the conventional full band adaptive requires very long filter taps, whereas the proposed subband variable filter requires less taps with the spectrum split in subband. The computer simulation results reveals that in many case, in system identification with narrow band system estimation, the proposed adaptive filter has less computational complexities with faster convergence.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.13-20
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• 2001

Adaptive digital filters with long impulse response such as acoustic echo canceller and active noise controller suffer from slow convergence and computational burden. Subband techniques and multirate signal processing have been recently developed to improve the problem of computational complexity and slow convergence in conventional adaptive filter. Any FIR transfer function can be realized as a serial connection of interpolators followed by subfilters with a sparse impulse response. In this case, each interpolator which is related to the column vector of Hadamard matrix has band-pass magnitude response characteristics shifted uniformly. Subband technique using Hadamard transform and decimation of subband signal to reduce sampling rate are adapted to system modeling and acoustic noise cancellation In this paper, delayless subband structure with nonuniform bandwidth has been proposed to improve the performance of the convergence speed without aliasing due to decimation, where input signal is split into subband one using tree-structured filter bank, and the subband signal is decimated by a decimator to reduce the sampling rate in each channel, then subfilter with sparse impulse response is transformed to full band adaptive filter coefficient using Hadamard transform. It is shown by computer simulations that the proposed method can be adapted to general adaptive filtering.

• Current Optics and Photonics
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• v.5 no.3
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• pp.250-260
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• 2021

A tapered As₂S₃ photonic crystal fiber (PCF) with four layers of air holes in a hexagonal array around the core is designed in this paper. Numerical simulation shows that the dispersion D decreases and the nonlinearity coefficient γ increases from the thick to the thin end along the tapered PCF. We simulate the midinfrared pulse compression in the tapered As₂S₃ PCF using the adaptive split-step Fourier method. Initial Gaussian pulses of 4.4 ps and a central wavelength of 2.5 ㎛ propagating in the tapered PCF are located in the anomalous dispersion region. With an average power of assumed input pulses at 3 mW and a repetition frequency of 81.0 MHz, we theoretically obtain a pulse duration of 56 fs and a compression factor of 78 when the pulse propagates from the thick end to the thin end of the tapered PCF. When confinement loss in the tapered PCF is included in the simulation, the minimum pulse duration reaches 72 fs; correspondingly, the maximum compression factor reaches 61. The results show that in the anomalous-dispersion region, midinfrared pulses can be efficiently compressed in a dispersion-decreasing and nonlinearity-increasing tapered As₂S₃ PCF. Due to confinement loss in the tapered fiber, the efficiency of pulse compression is suppressed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.503-509
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• 2022

The purpose of this study is to set the rate of change between the market price of the next day and the previous day to be predicted as the predicted value, and the market price for each section is generated by dividing the stock price ranking of the next day to be predicted at regular intervals, which is different from the previous papers that predict the market price. We would like to propose a new time series data prediction method that predicts the market price change rate of the final next day through a model using the rate of change as the predicted value. The change in the performance of the model according to the degree of subdivision of the predicted value and the type of input data was analyzed.

• Journal of KIBIM
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• v.12 no.4
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• pp.19-31
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• 2022

With the development of 3D-based CAD (Computer Aided Design), attempts at freeform building design have expanded to small and medium-sized buildings in Korea. However, a standardized system for continuous utilization of shape data and BIM conversion process implemented with 3D-based NURBS is still immature. Without accurate review and management throughout the Freeform building project, interference between members occurs and the cost of the project increases. This is very detrimental to the project. To solve this problem, we proposed a continuous utilization process of 3D shape information based on BIM parameters. Our process includes algorithms such as Auto Split, Panel Optimization, Excel extraction based on shape information, BIM modeling through Adaptive Component, and BIM model utilization method using ID Code. The optimal cutting reference point was calculated and the optimal material specification was derived using the Panel Optimization algorithm. With the Adaptive Component design methodology, a BIM model conforming to the standard cross-section details and specifications was uniformly established. The automatic BIM conversion algorithm of shape data through Excel extraction created a BIM model without omission of data based on the optimized panel cutting reference point and cutting line. Finally, we analyzed how to use the BIM model built for automatic conversion. As a result of the analysis, in addition to the BIM utilization plan in the general construction stage such as visualization, interference review, quantity calculation, and construction simulation, an individual management plan for the unit panel was derived through ID data input. This study suggested an improvement process by linking the existing research on atypical panel optimization and the study of parameter-based BIM information management method. And it showed that it can solve the problems of existing Freeform building project.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.83-95
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• 2022

This paper proposes a system that performs object detection and distance estimation for application to autonomous vehicles. Object detection is performed by a network that adjusts the split grid to the input image ratio using the characteristics of the recently actively used deep learning model YOLOv4, and is trained to a custom dataset. The distance to the detected object is estimated using a bounding box and homography. As a result of the experiment, the proposed method improved in overall detection performance and processing speed close to real-time. Compared to the existing YOLOv4, the total mAP of the proposed method increased by 4.03%. The accuracy of object recognition such as pedestrians, vehicles, construction sites, and PE drums, which frequently occur when driving to the city center, has been improved. The processing speed is approximately 55 FPS. The average of the distance estimation error was 5.25m in the X coordinate and 0.97m in the Y coordinate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.115-119
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• 2023

The natural language processing models used in current artificial intelligence are huge, causing various difficulties in processing and analyzing data in real time. In order to solve these difficulties, we proposed a method to improve the efficiency of processing by using less memory and checked the performance of the proposed model. The technique applied in this paper to evaluate the performance of the proposed model is to divide the large corpus by adjusting the number of attention heads and embedding size of the BERT[1] model to be small, and the results are calculated by averaging the output values of each forward. In this process, a random offset was assigned to the sentences at every epoch to provide diversity in the input data. The model was then fine-tuned for classification. We found that the split processing model was about 12% less accurate than the unsplit model, but the number of parameters in the model was reduced by 56%.

• Advances in concrete construction
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• v.13 no.2
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• pp.123-132
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• 2022

This paper aims to adapt Multilinear regression (MLR) to predict the strength and toughness of SIFCON containing various pozzolanic materials. Slurry Infiltrated Fibrous Concrete (SIFCON) is one of the most common terms used in concrete manufacturing, known for its benefits such as high ductility, toughness and high ultimate strength. Assessment of compressive strength (CS.), flexural strength (F.S.), splitting tensile strength (STS), dynamic elasticity modulus (DME) and impact energy (I.E.) using the experimental approach is too costly. It is time-consuming, and a slight error can lead to a repeat of the test and, to solve this, alternative methods are used to predict the strength and toughness properties of SIFCON. In the present study, the experimentally investigated SIFCON data about various mix proportions are used to predict the strength and toughness properties using regression analysis-multilinear regression (MLR) models. The input parameters used in regression models are cement, fibre, fly ash, Metakaolin, fine aggregate, blast furnace slag, bottom ash, water-cement ratio, and the strength and toughness properties of SIFCON at 28 days is the output parameter. The models are developed and validated using data obtained from the experimental investigation. The investigations were done on 36 SIFCON mixes, and specimens were cast and tested after 28 days of curing. The MLR model yields correlation between predicted and actual values of the compressive strength (C.S.), flexural strength, splitting tensile strength, dynamic modulus of elasticity and impact energy. R-squared values for the relationship between observed and predicted compressive strength are 0.9548, flexural strength 0.9058, split tensile strength 0.9047, dynamic modulus of elasticity 0.8611 for impact energy 0.8366. This examination shows that the MLR model can predict the strength and toughness properties of SIFCON.

• Archives of Plastic Surgery
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• v.51 no.1
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• pp.30-35
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• 2024

Background Breast aesthetics evaluation often relies on subjective assessments, leading to the need for objective, automated tools. We developed the Seoul Breast Esthetic Scoring Tool (S-BEST), a photometric analysis software that utilizes a DenseNet-264 deep learning model to automatically evaluate breast landmarks and asymmetry indices. Methods S-BEST was trained on a dataset of frontal breast photographs annotated with 30 specific landmarks, divided into an 80-20 training-validation split. The software requires the distances of sternal notch to nipple or nipple-to-nipple as input and performs image preprocessing steps, including ratio correction and 8-bit normalization. Breast asymmetry indices and centimeter-based measurements are provided as the output. The accuracy of S-BEST was validated using a paired t-test and Bland-Altman plots, comparing its measurements to those obtained from physical examinations of 100 females diagnosed with breast cancer. Results S-BEST demonstrated high accuracy in automatic landmark localization, with most distances showing no statistically significant difference compared with physical measurements. However, the nipple to inframammary fold distance showed a significant bias, with a coefficient of determination ranging from 0.3787 to 0.4234 for the left and right sides, respectively. Conclusion S-BEST provides a fast, reliable, and automated approach for breast aesthetic evaluation based on 2D frontal photographs. While limited by its inability to capture volumetric attributes or multiple viewpoints, it serves as an accessible tool for both clinical and research applications.