• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.781-786
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• 2013

Multiplexing information over parallel data channels based on RF MIMO concept is possible to achieve considerable data rates over large transmission ranges with just a single transmitting element. Visual multiplexing MIMO techniques will send independent streams of bits using the multiple elements of the light transmitter array and recording over a group of camera pixels can further enhance the data rates. The proposed system is a combination of the reliance on computer vision algorithms for tracking and OOK cell frame modulation. LED array are controlled to transmit message in the form of digital information using ON-OFF signaling with ON-OFF pulses (ON = bit 1, OFF = bit 0). A camera captures image frames of the array which are then individually processed and sequentially decoded to retrieve data. To demodulated data transmission, a motion tracking algorithm is implemented in OpenCV (Open source Computer Vision library) to classify the transmission pattern. One of the most advantages of proposed architecture is Computer Vision (CV) based image analysis techniques which can be used to spatially separate signals and remove interferences from ambient light. It will be the future challenges and opportunities for mobile communication networking research.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.6
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• pp.1142-1148
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• 2006

Actually, a present traffic accident detection system is subsisting limitation of accurate distinction under the crowded condition at intersection because the system depend upon mainly the image information at intersection and digital image processing techniques nearly all. To complement this insufficiency, this article aims to estimate the level of present technology and a realistic possibility by analyzing the acoustic characteristic of crash sound that we have to investigate fur improvement of traffic accident detection rate at intersection. The skid sound of traffic accident was showed the special pattern at 1[KHz])$\sim$3[KHz] bandwidth when vehicles are almost never operated in and around intersection. Also, the frequency bandwidth of vehicle crash sound was showed sound pressure difference over 30[dB] higher than when there is no occurrence of traffic accident below 500[Hz].

• Transactions of Materials Processing
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• v.31 no.4
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• pp.229-239
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• 2022

Convolution Neural Network(CNN) is a class of deep learning algorithms and can be used for image analysis. In particular, it has excellent performance in finding the pattern of images. Therefore, CNN is commonly applied for recognizing, learning and classifying images. In this study, the surface defect classification performance of Al 6061 extruded material using CNN-based algorithms were compared and evaluated. First, the data collection criteria were suggested and a total of 2,024 datasets were prepared. And they were randomly classified into 1,417 learning data and 607 evaluation data. After that, the size and quality of the training data set were improved using data augmentation techniques to increase the performance of deep learning. The CNN-based algorithms used in this study were VGGNet-16, VGGNet-19, ResNet-50 and DenseNet-121. The evaluation of the defect classification performance was made by comparing the accuracy, loss, and learning speed using verification data. The DenseNet-121 algorithm showed better performance than other algorithms with an accuracy of 99.13% and a loss value of 0.037. This was due to the structural characteristics of the DenseNet model, and the information loss was reduced by acquiring information from all previous layers for image identification in this algorithm. Based on the above results, the possibility of machine vision application of CNN-based model for the surface defect classification of Al extruded materials was also discussed.

• Geomechanics and Engineering
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• v.32 no.6
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• pp.653-671
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• 2023

In practice, the interference influence caused by adjacent footings of structures on geo-reinforced loose soil has a considerable impact on their behavior. Thus, the goal of this study is to evaluate the behavior of two strip footings in close proximity on both geocell and geogrid reinforced soil with different reinforcement layers. Geocell was made from geogrid material used to compare the performance of cellular and planar reinforcement on the bearing pressure of twin footings. Extensive experimental tests have been performed to attain the optimum embedment depth and vertical distance between reinforcement layers. Particle image velocimetry (PIV) analysis has been conducted to monitor the deformation, tilting and movement of soil particles beneath and between twin footings. Results of tests and PIV technique were verified using finite element modeling (FEM) and the results of both PIV and FEM were used to utilize failure mechanisms and influenced shear strain around the loading region. The results show that the performance of twin footings on geocell-reinforced sand at allowable and ultimate settlement ranges are almost 4% and 25% greater than the same twin footings on the same geogrid-reinforced sand, respectively. By increasing the distance between twin footings, soil particle displacements become smaller than the settlement of the foundations.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.297-300
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• 1996

In male reproducible health and fertility and IVF(in-vitro fertilization), semen analysis has been most important. But the traditional tools for semen analysis are subjective, imprecise, inaccurate, difficult to standardize, and difficult to reproduce mainly due to their manually oriented operations. The purpose of a morphometric analysis of sperm is to microscopically type-classify spermatozoa cytologically according to their morphology of heads. Until now, the strict criteria method has long been used in clinic to discriminate normal spermatozoa from abnormal ones. This method cannot classify the diverse groups of abnormal spermatozoa in detail and shows variations in inter-operators and intra-operator In this paper, we developed a new method of a sperm morphometric analysis using artificial neural networks which are widely used in pattern recognition and image processing.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.1
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• pp.12-16
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• 2015

Purpose Principal component analysis (PCA) is a method often used in the neuroimagre analysis as a multivariate analysis technique for describing the structure of high dimensional correlation as the structure of lower dimensional space. PCA is a statistical procedure that uses an orthogonal transformation to convert a set of observations of correlated variables into a set of values of linearly independent variables called principal components. In this study, in order to investigate the usefulness of PCA in the brain PET image analysis, we tried to analyze C[11]-PIB PET image as a representative case. Materials and Methods Nineteen subjects were included in this study (normal = 9, AD/MCI = 10). For C[11]-PIB, PET scan were acquired for 20 min starting 40 min after intravenous injection of 9.6 MBq/kg C[11]-PIB. All emission recordings were acquired with the Biograph 6 Hi-Rez (Siemens-CTI, Knoxville, TN) in three-dimensional acquisition mode. Transmission map for attenuation-correction was acquired using the CT emission scans (130 kVp, 240 mA). Standardized uptake values (SUVs) of C[11]-PIB calculated from PET/CT. In normal subjects, 3T MRI T1-weighted images were obtained to create a C[11]-PIB template. Spatial normalization and smoothing were conducted as a pre-processing for PCA using SPM8 and PCA was conducted using Matlab2012b. Results Through the PCA, we obtained linearly uncorrelated independent principal component images. Principal component images obtained through the PCA can simplify the variation of whole C[11]-PIB images into several principal components including the variation of neocortex and white matter and the variation of deep brain structure such as pons. Conclusion PCA is useful to analyze and extract the main pattern of C[11]-PIB image. PCA, as a method of multivariate analysis, might be useful for pattern recognition of neuroimages such as FDG-PET or fMRI as well as C[11]-PIB image.

• Applied Microscopy
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• v.38 no.4
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• pp.363-374
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• 2008

In this paper we have examined the usefulness of IWFR (the iterative wave-function reconstruction) analysis for through-focal series of high-resolution images for a relative thick crystal. In the work we employed JEOL ARM 1300S, and observed the high-resolution images for a Si crystal at the two orientations of [01-1] and [11-2] having 30 nm and 35 nm thickness respectively. As a result of applying IWFR method on the images we found out that even for a thick crystal by the method we can retrieve the exit-surface wave function. However because of the strong dynamical scattering effect, the image pattern of the function reflects only qualitatively the atomic column structure of the crystal examined. Nevertheless it is no doubt that the pattern would give important clue for the crystal structure.

• Journal of the Korean Society of Safety
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• v.27 no.3
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• pp.57-62
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• 2012

The purpose of this paper is to find dangerous factors of a water purifier when water leaks due to inappropriate use and analyze the patterns of damaged parts in order to provide data for the examination of the cause of the problem. If the water purifier is inspected and managed by a non-specialist, when the FLC(Float Level Controller) at the top is inclined, water leakage may occur to the water purifier. The leaked water flows onto the cables and hoses and enters the thermostat terminal, heater, PCB, power supply connection connector, etc., becoming a dangerous factor that may cause a system failure, fire, etc. Due to the water that entered the input terminal, low noise and white smoke were generated at first. However, the flame gradually propagated due to the continuous inflow of moisture. It was found that when moisture reached the PCB, a carbonized conductive path was formed at the varistor terminal, input terminal, semiconductor device terminal, etc., and the flame became larger, which might result in a fire. From the metal microscope analysis of a damaged condenser terminal, it was found that the amorphous structure unique to copper cable disappeared, and voids, boundary surface and disorderly fine particles occurred. Also, in the case of the connector into which moisture penetrated, fusion and deformation occurred at the cable connection clips. The result of analysis of the power supply cable connector using a thermal image camera showed that most of the heat was generated from the cable connection clips and the temperature at the connection center was normal.

• Fashion & Textile Research Journal
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• v.23 no.6
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• pp.709-725
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• 2021

The study focused on the design features of Chanel and Fendi, directed by Carl Lagerfeld, creative director of Chanel and Fendi until his recent death. The range of the study was from the 2017 S/S Collection to the 2019 F/W Collection, which collected a total of 767 fashion photographs, including 483 Chanel, 284 Fendi, with tops, bottoms and dresses at VOGUE (https://www.vogue.com). According to the data analysis criteria organized based on prior research and related literature, it was classified in the order of form, color, material, pattern, decoration, fashion image, item and coordination, and content analysis was conducted based on statistical analysis. Overall, the design characteristics of the Chanel collection, directed by Karl Lagerfeld, were rectangle form, tone in tone coloring, combination of identical materials, geometric patterns, and classical images as the main design characteristics of the Chanel collection. The design characteristics shown in the Fendi collection directed by Karl Lagerfeld were rectangle form, tone in tone coloration, hard material combination, abstract pattern, and total coordination. Comparing the design features of Chanel and Fendi, directed by Karl Lagerfeld, is as follows. Chanel and Fendi's designs show a lot of rectangle form, tone-in-tone colors, hard-materials and combination of the same material.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.10
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• pp.38-45
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• 2004

In this paper, a parallel visualization algorithm is proposed for efficient visualization of the massive data generated from large-scale parallel finite element analysis through investigating the characteristics of parallel rendering methods. The proposed parallel visualization algorithm is designed to be highly compatible with the characteristics of domain-wise computation in parallel finite element analysis by using the sort-last-sparse approach. In the proposed algorithm, the binary tree communication pattern is utilized to reduce the network communication time in image composition routine. Several benchmarking tests are carried out by using the developed in-house software, and the performance of the proposed algorithm is investigated.