• Journal of the Korea Furniture Society
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• v.20 no.5
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• pp.533-542
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• 2009

The space is generally the discontinuation space without being understood agreed by some people. In this time, expressing transparency has various significances in furniture design because modern people want transparence and space due to the complication, numerous unreasonable facts and the lack of honesty in the society. Philip Johnson's Glass House in 1946 influenced architecture, interior, furniture and life article to use transparent materials and space that is being until currently development. The transparency which comes to be preferred clearly means to develop the society continuously. It can be more liberal, honest, and transparent society. The trend appeared in furniture design has meaning as the representative product. This research has perceptional transparency(visible transparency), abstract transparency through space(phenomenal transparency), overlap of surface element, display of line element, image using dot, and changing the image of various spaces.

• Journal of Korea Multimedia Society
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• v.22 no.1
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• pp.10-17
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• 2019

In High Dynamic Range (HDR) image processing, tone mapping is the process to compress an input image into a Low Dynamic Range (LDR) image. In most cases, the reason that detail preservation is prior to take over tone mapping is that the dynamic range is significantly different between input and output images. In the case of iCAM06, details are separated by using a bilateral filter, however, it causes noise amplification at the dim surround region. Thus, we suggest that the detail signal, which is separated from the bilateral filter, is combined with the base signal after an adaptive Kalman filter is applied according to the local standard deviation. We confirmed that the proposed method enhances the HDR images quality by checking the noise reduction in a dim surround region.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2359-2376
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• 2022

With the exponential growth of medical image big data represented by high-resolution CT images(CTI), the high-resolution CTI data is of great importance for clinical research and diagnosis. The paper takes lung CTI as an example to study. Retrieving answer CTIs similar to the input one from the large-scale lung CTI database can effectively assist physicians to diagnose. Compared with the conventional content-based image retrieval(CBIR) methods, the CBIR for lung CTIs demands higher retrieval accuracy in both the contour shape and the internal details of the organ. In traditional supervised deep learning networks, the learning of the network relies on the labeling of CTIs which is a very time-consuming task. To address this issue, the paper proposes a Weakly Supervised Similarity Evaluation Network (WSSENet) for efficiently support similarity analysis of lung CTIs. We conducted extensive experiments to verify the effectiveness of the WSSENet based on which the CBIR is performed.

• Computers and Concrete
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• v.34 no.1
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• pp.79-91
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• 2024

In symmetric cryptography, a cryptographically secure Substitution-Box (S-Box) is a key component of a block cipher. S-Box adds a confusion layer in block ciphers that provide resistance against well-known attacks. The generation of a cryptographically secure S-Box depends upon its generation mechanism. In this paper, we propose a novel framework for the construction of cryptographically secure S-Boxes. This framework uses a combination of linear fractional transformation and permutation functions. S-Boxes security is analyzed against well-known security criteria that include nonlinearity, bijectiveness, strict avalanche and bits independence criteria, linear and differential approximation probability. The S-Boxes can be used in the encryption of any grayscale digital images. The encrypted images are analyzed against well-known image analysis criteria that include pixel changing rates, correlation, entropy, and average change of intensity. The analysis of the encrypted image shows that our image encryption scheme is secure.

• Journal of the Korean Society of Radiology
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• v.5 no.2
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• pp.97-101
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• 2011

In this study, the basic research verifying possibility of applications as radiology image sensor in Digital Radiography was performed, the radiology image sensor was fabricated using double layer technique tio decrease dark current. High efficiency material in substitution for a-Se have been studied as a direct method of imaging detector in Digital Radiography to decrease dark current by using Hetero junction already used as solar cell, semiconductor. Particle-In-Binder method is used to fabricate radiology image sensor because it has a lot of advantages such as fabrication convenient, high yield, suitability for large area sensor. But high leakage current is one of main problem in PIB method. To make up for the weak points, double layer technique is used, and it is considered that high efficient digital radiation sensor can be fabricated with easy and convenient process. In this study, electrical properties such as leakage current, sensitivity is measured to evaluate double layer radiation sensor material.

• Journal of the Korean Society of Radiology
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• v.12 no.5
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• pp.637-643
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• 2018

A depth of interaction(DOI) detector module using a block scintillator and a pixellated scintillator was designed, and layer discrimination ability was calculated using DETECT2000. The block scintillator was used to improve the sensitivity and the spatial resolution was improved by measuring the DOI. The DOI was measured by analyzing the signal characteristics of each channel of the changed distribution of light. The detector module was composed to the block scintillator in the top layer and the pixellated scintillator in the bottom layer, which changes the distribution of light generated from a scintillator interacting with a gamma ray. In the flood image, the top layer was able to acquire the image at the position similar to the position of the bottom layer because the bottom layer consist of the pixellated scintillator. By using the Anger algorithm, the 16 channel signal was reduced to 4 channels to facilitate the analysis of the signal characteristics. The layer discrimination was measured using a simple algorithm and the accuracy was about 84% for each layer. When this detector module is used in preclinical PET, the spatial resolution at the outside of the field of view can be improved by measuring the DOI.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.8
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• pp.1103-1112
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• 2001

The effect of pressure gradients on the hairpin structures in three different turbulent boundary layers (ZPG : Re(sub)$\theta$=910, FPG : Re(sub)$\theta$=575, APG : Re(sub)$\theta$=1290) has been examined with instantaneous velocity fields obtained in streamwise-wall-normal planes using PIV (particle image velocimetry) method. In the outer layer hairpin vortices occur in streamwise-aligned packets that propagate with small velocity dispersion. The signature pattern of the hairpin consists of a spanwise vortex core located above a region of strong second quadrant fluctuation (u<0 and v>0 : Q2 event) is clearly observed. The formation of packets explains the occurrence of multiple VITA events in turbulent burst. Noticeable differences are found in the average inclination angles of hairpin vortex packets which are 45$^{\circ}$, 35.7$^{\circ}$, and 51.9$^{\circ}$in the case of ZPG, FPG and APG, respectively. It is found that the large, time-varying, irregularly shaped zones with nearly constant streamwise momentum exist throughout the boundary layer. Within the interior of the envelope the spatial coherence between the velocity fields induced by the individual vortices leads to strongly retarded streamwise momentum, explaining the zones of uniform momentum. The formation of the uniform momentum zone is remarkably different with respect to the pressure gradients especially in the logarithmic layer.

• The Journal of Korean Institute of Information Technology
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• v.16 no.12
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• pp.75-83
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• 2018

Recently, autonomous vehicles have been actively studied. Pedestrian detection and recognition technology is important in autonomous vehicles. Pedestrian detection using CNN(Convolutional Neural Netwrok), which is mainly used recently, generally shows good performance, but there is a performance degradation depending on the environment of the image. In this paper, we propose a pedestrian detection system applying long-term memory structure of hippocampal neural network based on CNN network with LGP-FL (Local Gradient Pattern-Feature Layer) added. First, change the input image to a size of $227{\times}227$. Then, the feature is extracted through a total of 5 layers of convolution layer. In the process, LGP-FL adds the LGP feature pattern and stores the high-frequency pattern in the long-term memory. In the detection process, it is possible to detect the pedestrian more accurately by detecting using the LGP feature pattern information robust to brightness and color change. A comparison of the existing methods and the proposed method confirmed the increase of detection rate of about 1~4%.

• Journal of the Korean Society of Radiology
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• v.15 no.2
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• pp.153-158
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• 2021

X-ray image analysis is a very important field to improve the early diagnosis rate and prediction accuracy of periodontal disease. Research on the development and application of artificial intelligence-based algorithms to improve the quality of such dental X-ray images is being widely conducted worldwide. Thus, the aim of this study was to design a super-resolution algorithm for predicting periodontal disease and to evaluate its applicability in dental X-ray images. The super-resolution algorithm was constructed based on the convolution layer and ReLU, and an image obtained by up-sampling a low-resolution image by 2 times was used as an input data. Also, 1,500 dental X-ray data used for deep learning training were used. Quantitative evaluation of images used root mean square error and structural similarity, which are factors that can measure similarity through comparison of two images. In addition, the recently developed no-reference based natural image quality evaluator and blind/referenceless image spatial quality evaluator were additionally analyzed. According to the results, we confirmed that the average similarity and no-reference-based evaluation values were improved by 1.86 and 2.14 times, respectively, compared to the existing bicubic-based upsampling method when the proposed method was used. In conclusion, the super-resolution algorithm for predicting periodontal disease proved useful in dental X-ray images, and it is expected to be highly applicable in various fields in the future.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.763-764
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• 2013

A three-dimensional image capturing device and its signal processing algorithm and apparatus are presented. Three dimensional information is one of emerging differentiators that provides consumers with more realistic and immersive experiences in user interface, game, 3D-virtual reality, and 3D display. It has the depth information of a scene together with conventional color image so that full-information of real life that human eyes experience can be captured, recorded and reproduced. 20 Mega-Hertz-switching high speed image shutter device for 3D image capturing and its application to system prototype are presented[1,2]. For 3D image capturing, the system utilizes Time-of-Flight (TOF) principle by means of 20MHz high-speed micro-optical image modulator, so called 'optical resonator'. The high speed image modulation is obtained using the electro-optic operation of the multi-layer stacked structure having diffractive mirrors and optical resonance cavity which maximizes the magnitude of optical modulation[3,4]. The optical resonator is specially designed and fabricated realizing low resistance-capacitance cell structures having small RC-time constant. The optical shutter is positioned in front of a standard high resolution CMOS image sensor and modulates the IR image reflected from the object to capture a depth image (Figure 1). Suggested novel optical resonator enables capturing of a full HD depth image with depth accuracy of mm-scale, which is the largest depth image resolution among the-state-of-the-arts, which have been limited up to VGA. The 3D camera prototype realizes color/depth concurrent sensing optical architecture to capture 14Mp color and full HD depth images, simultaneously (Figure 2,3). The resulting high definition color/depth image and its capturing device have crucial impact on 3D business eco-system in IT industry especially as 3D image sensing means in the fields of 3D camera, gesture recognition, user interface, and 3D display. This paper presents MEMS-based optical resonator design, fabrication, 3D camera system prototype and signal processing algorithms.