• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.731-739
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• 2017

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low complexity video sampling. In DCVS schemes, motion estimation & motion compensation is employed at the decoder side, similarly to distributed video coding (DVC), for a low-complex encoder. However, since a simple BCS-SPL algorithm is applied to a residual arising from motion estimation and compensation in conventional MC-BCS-SPL (motion compensated block compressed sensing with smoothed projected Landweber) scheme, the reconstructed visual qualities are severly degraded in Wyner-Ziv (WZ) frames. Furthermore, the scheme takes lots of iteration to reconstruct WZ frames. In this paper, the conventional MC-BCS-SPL algorithm is improved to be operated in more effective way in WZ frames. That is, first, the proposed algorithm calculates a correlation coefficient between two reference key frames and, then, by selecting adaptively the reference frame, the residual reconstruction in pixel domain is performed to the conventional BCS-SPL scheme. Experimental results show that the proposed algorithm achieves significantly better visual qualities than conventional MC-BCS-SPL algorithm, while resulting in the significant reduction of the decoding time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.600-616
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• 2021

SIMON and SPECK are two families of lightweight block ciphers that have excellent performance on hardware and software platforms. At CRYPTO 2019, Gohr first introduces the differential cryptanalysis based deep learning on round-reduced SPECK32/64, and finally reduces the remaining security of 11-round SPECK32/64 to roughly 38 bits. In this paper, we are committed to evaluating the safety of SIMON cipher under the neural differential cryptanalysis. We firstly prove theoretically that SIMON is a non-Markov cipher, which means that the results based on conventional differential cryptanalysis may be inaccurate. Then we train a residual neural network to get the 7-, 8-, 9-round neural distinguishers for SIMON32/64. To prove the effectiveness for our distinguishers, we perform the distinguishing attack and key-recovery attack against 15-round SIMON32/64. The results show that the real ciphertexts can be distinguished from random ciphertexts with a probability close to 1 only by 2^8.7 chosen-plaintext pairs. For the key-recovery attack, the correct key was recovered with a success rate of 23%, and the data complexity and computation complexity are as low as 2⁸ and 2^20.1 respectively. All the results are better than the existing literature. Furthermore, we briefly discussed the effect of different residual network structures on the training results of neural distinguishers. It is hoped that our findings will provide some reference for future research.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1098-1101
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• 2004

The ordinary stereo image of an object consists of data of left and right views. Therefore, the left and right image pairs have to be transmitted simultaneously in order to display 3-dimentional video at the remote site. However, due to the twice data in comparing with a monoscopic image of the same object, it needs to be compressed for fast transmission and resource saving. Hence, it needs an effective coding algorithm for compressing stereo image. It was found previously that compressing left and right frames independently will achieve the compression ratio lower than compressing by utilizing the spatial redundancy between both frames. Therefore, in this paper, we study the stereo image compression technique based on the multiresolution wavelet transform using varied disparity-block size for estimation and compensation. The size of disparity-block in the stereo pair subbands are scaling on a coarse-to-fine wavelet coefficients strategy. Finally, the reference left image and residual right image after disparity estimation and compensation are coded by using SPIHT coding. The considered method demonstrates good performance in both PSNR measures and visual quality for stereo image.

• Journal of Welding and Joining
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• v.34 no.2
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• pp.11-15
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• 2016

FE analyses for weldment of ship structure are required for various reasons such as stress concentration for bead tow, residual stress and distortion after welding, and hydrogen diffusion for prediction of low temperature crack. These analyses should be done by solid element modeling, but most of ship structures are modeled by shell element. If we are able to make solid element in the shell element FE modeling it is easily to solve the requirement for solid elements in weld analysis of large ship structures. As the nodes of solid element cannot take moments from nodes of shell element, these two kinds of element cannot be used in one model by conventional modeling. The PSCM (Perpendicular shell coupling method) can connect shell to solid. This method uses dummy perpendicular shell element for transferring moment from shell to solid. The target of this study is to develop a FE pre-processing system applicable at welding at ship structure by using PSCM. We also suggested glue-contact technique for controlling element numbers and element qualities and applied it between PSCM and solid element in automatic pre-processing system. The FE weldment modeling through developed pre-processing system will have rational stiffness of adjacent regions. Then FE results can be more reliable when turn-over of ship-block with semi-welded state or ECA (Engineering critical assessment) of weldment in a ship-block are analyzed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.23-32
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• 2011

In this paper, we develop a method for generating thumbnail images at hybrid domain combined the spatial domain and transform domain. The proposed method generates a pixel of a thumbnail image by adding a DC value of residual transform coefficients and an average value of an estimate block. For effectively calculating average values of estimate blocks, we propose a method for reconstructing the boundary pixels of a block. In comparison to the conventional method of decoding the bit stream then scaling down the decoded images, the developed method reduces the complexity by more than 60% while producing identical thumbnail images.

• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1805-1815
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• 2019

While nickel-based alloys have been widely used for power plants due to corrosion resistance and good mechanical properties, during the last couple of decades, failures of nuclear components increased gradually. One of main degradation mechanisms was primary water stress corrosion cracking at dissimilar metal welds of piping and reactor head penetrations. In this context, precise estimation of welding effects became an important issue for ensuring reliability of them. The present study deals with a series of finite element analyses and crack growth rate evaluation of Alloys 690/152. Firstly, variation of residual stresses and equivalent plastic strains was simulated taking into account welding of a cylindrical block. Subsequently, extraction and pre-cracking of compact tension (CT) specimens were considered from different locations of the block. Finally, crack growth curves of the alloys and heat affected zone were developed based on analyses results combined with experimental data in references. Characteristics of crack growth behaviors were also discussed in relation to mechanical and fracture parameters.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.97-97
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• 2009

The use of thin plate increases due to the need for light weight in large ship. Thin plate is easily distorted and has residual stress by welding heat. Therefore, the thin plate should be carefully joined to minimize the welding deformation which costs time and money for repair. For one effort to reduce welding deformation, it is very useful to predict welding deformation before welding execution. There are two methods to analyze welding deformation. One is simple linear analysis. The other is nonlinear analysis. The simple linear analysis is elastic analysis using the equivalent load method or inherent strain method from welding experiments. The nonlinear analysis is thermo-elastic analysis which gives consideration to the nonlinearity of material dependent on temperature and time, welding current, voltage, speed, sequence and constraint. In this study, the welding deformation is analyzed by using thermo-elastic method for PCTC(Pure Car and Truck Carrier) which carries cars and trucks. PCTC uses thin plates of 6mm thickness which is susceptible to welding heat. The analysis dimension is 19,200mm(length) * 13,825mm(width) * 376mm(height). MARC and MENTAT are used as pre and post processor and solver. The boundary conditions are based on the real situation in shipyard. The simulations contain convection and gravity. The material of the thin block is mild steel with $235N/mm^2$ yield strength. Its nonlinearity of conductivity, specific heat, Young's modulus and yield strength is applied in simulations. Welding is done in two pass. First pass lasts 2,100 second, then it rests for 900 second, then second pass lasts 2,100 second and then it rests for 20,000 second. The displacement at 0 sec is caused by its own weight. It is maximum 19mm at the free side. The welding line expands, shrinks during welding and finally experiences shrinkage. It results in angular distortion of thin block. Final maximum displacement, 17mm occurs around welding line. The maximum residual stress happens at the welding line, where the stress is above the yield strength. Also, the maximum equivalent plastic strain occurs at the welding line. The plastic strain of first pass is more than that of second pass. The flatness of plate in longitudinal direction is calculated in parallel with the direction of girder and compared with deformation standard of ${\pm}15mm$. Calculated value is within the standard range. The flatness of plate in transverse direction is calculated in perpendicular to the direction of girder and compared with deformation standard of ${\pm}6mm$. It satisfies the standard. Buckle of plate is calculated between each longitudinal and compared with the deformation standard. All buckle value is within the standard range of ${\pm}6mm$.

• Journal of The Korean Society of Grassland and Forage Science
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• v.16 no.4
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• pp.260-266
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• 1996

To find out the residual effect of phosphate fertilization level on the dry matter yield and nutrient plloductivity of pasture plants, this experiment was arranged as a randomized complete block design with six treatments(0-0, 50-50, 100-65, 150-65, 200-65 and 250-65kg $P_2O_5$), those were composed of three $P_2O_5$ fertilization level(0,50 and 65kg $P_2O_5$ after phosphate fertilization trial with six treatments(0, 50, 100, 150, 200 and 250kg $P_2O_5$/ha) from 1989 to 1992, and conducted at hilly land in Kwangju, Kyonggi Province from 1993 to 1994. The results obtained are summarized as follows : As the available phosphate of soil increase, the early growth and cover degree of pasture plants wintered were more favorable. With 150-65kg $P_2O_5$ application for two years, the average dry matter yield of grasses, 9,862kglha was similared to that of 200-65kg $P_2O_5$/ha. The crude protein and energy productivity of pasture plants tended to increase as available phosphate of soil was increased, but those were not different between 150-65 and 250-65kg P 2 0 4 a Efficiency of $P_2O_5$ was highest at $P_2O_5$ 150-65kg/ha fertilization, wHich produced dry matter 11 1.8kg. net energy lactation(NEL) 67 1.2M.f per I kg P205. Therefore, phosphate fertilization is recommended strongly application with 150kg/ha for three years after pasture establishment, and then 65kg/ha for two years a reasonabl management in hilly grassland.

• Korean Journal of Agricultural Science
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• v.44 no.3
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• pp.359-365
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• 2017

Biochar has the ability to mitigate climate change, improve crop productivity, and adsorb various contaminants. The aim of this work was to confirm the effect of biochar as a soil amendment on growth of Chinese cabbage (Brassica chinensis) using a pot experiment. Biochar was produced from residual-wood burnt at a pyrolytic temperature of $400^{\circ}C$ and consisted of 51.6 % carbon (C) by mass. The biochar was added to the soil at 0, 1, 3, and 5% by weight, which represent about 0, 18, 54, and $90t\;ha^{-1}$, respectively. The treatments were arranged in a randomized complete block design with 3 replications. The Chinese cabbage was grown for 49 days in a glasshouse in pots filled with sandy loam soil. Experimental results showed that the residual-wood biochar used for the experiment was slightly alkaline (pH 7.5). The fresh weights of Chinese cabbage were 86.22 g, 84.1 g, 63.23 g and 70.87 g, respectively, for biochar applications at 0, 18, 54, and $90t\;ha^{-1}$. Compared with the control (i.e., no biochar), biochar application increased soil pH and electrical conductivity (EC). Addition of biochar (54 and $90t\;ha^{-1}$) to sandy loam soil had no effect on growth of Chinese cabbage. This might be due to excessive increase of soil pH from the biochar application, leading to reduced availability of plant nutrients. Based on these results, the authors conclude that an excessive addition of biochar may have negative effects on the healthy growth of Chinese cabbage.

• Korean Journal of Materials Research
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• v.32 no.8
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• pp.345-353
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• 2022

In this study, using deep learning, super-resolution images of transmission electron microscope (TEM) images were generated for nanomaterial analysis. 1169 paired images with 256 × 256 pixels (high resolution: HR) from TEM measurements and 32 × 32 pixels (low resolution: LR) produced using the python module openCV were trained with deep learning models. The TEM images were related to DyVO₄ nanomaterials synthesized by hydrothermal methods. Mean-absolute-error (MAE), peak-signal-to-noise-ratio (PSNR), and structural similarity (SSIM) were used as metrics to evaluate the performance of the models. First, a super-resolution image (SR) was obtained using the traditional interpolation method used in computer vision. In the SR image at low magnification, the shape of the nanomaterial improved. However, the SR images at medium and high magnification failed to show the characteristics of the lattice of the nanomaterials. Second, to obtain a SR image, the deep learning model includes a residual network which reduces the loss of spatial information in the convolutional process of obtaining a feature map. In the process of optimizing the deep learning model, it was confirmed that the performance of the model improved as the number of data increased. In addition, by optimizing the deep learning model using the loss function, including MAE and SSIM at the same time, improved results of the nanomaterial lattice in SR images were achieved at medium and high magnifications. The final proposed deep learning model used four residual blocks to obtain the characteristic map of the low-resolution image, and the super-resolution image was completed using Upsampling2D and the residual block three times.