• Clean Technology
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• v.24 no.3
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• pp.157-165
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• 2018

In this study, the removal of $Si_3N_4$ particles from the surface of a silicon wafer was investigated by using supercritical carbon dioxide, the IPA co-solvent and cleaning additive chemicals. First, the solubility of several surfactants and binders in supercritical carbon dioxide solubility and particle dispersibility in the binders were evaluated in order to confirm their suitability for the supercritical cleaning process. Particle removal experiments were carried out with adjusting various process parameters and reaction conditions. The surfactants used in the experiment showed little particle removal effect, producing secondary contamination on the surface of wafers. On the other hand, 5 wt% (with respect to $scCO_2$) of the cleaning additive mixture of trimethyl phosphate, IPA, and trace HF resulted in 85% of particle removal efficiency after $scCO_2$ flowing for 4 minutes at $50^{\circ}C$, 2000 psi, and the flow rate of $15mL\;min^{-1}$.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.237-240
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• 2004

In this study, the digital image processing with image enhancement based on homomorphic filtering was performed using geophysical imaging data such as gravity, magnetic data and sub-scenes of satellite images such as LANDSAT, IKONOS, and KOMPSAT. Windows application program for executing homomorphic filtering was designed and newly implemented. In general, homomorphic filtering is technique that is based on Fourier transform, which enhances the contrast of image by removing the low frequencies and amplifying the high frequencies in frequency domain. We can enhance the image selectively using homomorphic filtering as compared with the existing method, which enhance the image totally. Through several experiment using remotely sensed imagery and geophysical image with this program, it is concluded that homomorphic filtering is more effective to reveal distinct characteristics for some complicated and multi-associated features on image data.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.329-333
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• 2005

This paper is concerned with the measurement of low-frequency vibrations of structures using the image processing method. To measure the vibrations visually, the measurement system consists of a camera, an image grabber board, and a computer. The specific target installed on the structure is used to calculate the vibration of structure. The captured image is then converted into a pixel-based data and then analyzed numerically. The limitation of the system depends on the image capturing speed and the size of image. In this paper, we propose the methodology for the vibration measurement using the image processing method. The method enables us to measure the displacement directly without any contact. The current resolution of the vibration measurement is limited to sub centimeter scale. However, the frequency bandwidth and resolution can be enhanced by a high-speed and high-resolution image processing system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.30-39
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• 1994

A 1-chip high quality binarizing VLSI image processor (which has 8 bit ADC. 6 bit flash ADC, 15K standard cell, and 1K word ROM) based on 10 MIPS 16 bit DSP is implemented for FAX. This image processor(IP) performs image pre-processing. image quality improvement in copying and sending mode, and mixed image processing based on the fuzzy theory. And smoothing in sub-scan direction is applied for normal receiving mode data so the received data is enhanced like fine mode data. Each algorithm is processed with the same type of image processing window and 2-D image processing is implemented with a 1-D line buffer. The fabricated chip is applied to a FAX machine and image quality improvement is verified.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.1
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• pp.207-217
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• 1996

Self is well·expressed by clothing, so self-image can be an effective variable for conducting clothing·behavior studies. But there ate some problems in clothing and self-image researches. This paper will be a clue to discuss these problems. The contents of this study are as follows. (1) The notion of self-image is compared with self-concept, and according to this work, self concept comprehends the evaluative properties in addition to self-image illustration. In tai.; part, the problem in translating the terminologies, 'self-concept' and 'self-image', are also discussed. (2) The aspects of self-image are explored, thus physical and social-psychological aspects are determined. (3) Two sub-dimensions of self-image ate recommended relating to clothing researches: actual versus ideal and intrinsic versus phenomenal. (4) Some comments for future studies ate added. It is needed to investigate the relationships of other social- psychological variables and self-image in clothing department.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.45-55
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• 2021

This paper has proposed an algorithm that detecting for dense small vehicle in large image efficiently. It is consisted of two Ensemble Deep-Learning Network algorithms based on Coarse to Fine method. The system can detect vehicle exactly on selected sub image. In the Coarse step, it can make Voting Space using the result of various Deep-Learning Network individually. To select sub-region, it makes Voting Map by to combine each Voting Space. In the Fine step, the sub-region selected in the Coarse step is transferred to final Deep-Learning Network. The sub-region can be defined by using dynamic windows. In this paper, pre-defined mapping table has used to define dynamic windows for perspective road image. Identity judgment of vehicle moving on each sub-region is determined by closest center point of bottom of the detected vehicle's box information. And it is tracked by vehicle's box information on the continuous images. The proposed algorithm has evaluated for performance of detection and cost in real time using day and night images captured by CCTV on the road.

• Applied Microscopy
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• v.50
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• pp.27.1-27.6
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• 2020

Transition metal dichalcogenides (TMD), which is composed of a transition metal atom and chalcogen ion atoms, usually form vacancies based on the knock-on threshold of each atom. In particular, when electron beam is irradiated on a monolayer TMD such as MoS₂ and WS₂, S vacancies are formed preferentially, and they are aligned linearly to constitute line defects. And then, a hole is formed at the point where the successively formed line defects collide, and metal clusters are also formed at the edge of the hole. This study reports a process in which the line defects formed in a monolayer WS₂ sheet expends into holes. Here, the process in which the W cluster, which always occurs at the edge of the formed hole, goes through a uniform intermediate phase is explained based on the line defects and the formation behavior of the hole. Further investigation confirms the atomic structure of the intermediate phase using annular dark field scanning transition electron microscopy (ADF-STEM) and image simulation.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.417-426
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• 2023

To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.235-246
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• 2018

The purpose of this study was to verify the structural relationship between the participation behavior, excercise behavior, sport Image and exercise Continuation of the badminton club members, The results were as follows: First, the variables that affected the sport image for the item were fun among sub-factors of participation behavior, self-esteem and stress relief among sub-factors of exercise behaviors. Second, the sport image was affecting the exercise continuation. Finally, participation and Exercise behaviors indirectly affected the exercise continuation that through sport image. The results of this study proved that sport image plays an important role as a mediator in the relationship between participation behavior, exercise behavior, and exercise continuation, and it is meaningful to provide basic data on the role of the sport image.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.169-172
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.