• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.2
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• pp.126-130
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• 2002

This paper presents the basic concept of new solid freeform fabrication system using rapid prototyping method. The system could fabricate an arbitrary ceramic form by laser cutting, transferring, stacking, and sintering of each slide. The system consists mainly of laser apparatus. X-Y table, a slide transferring system, and electric oven. The system could fabricate an object that has smooth surface with comparatively short period of time. The system is effective in terms of its direct fabrication capability without second mechanical process. The fabricated shape could directly be used as part of a whole assembly and therefore its method could be applied to various application areas.

• Journal of Fashion Business
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• v.27 no.6
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• pp.147-159
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• 2023

Fashion is the second most polluting industry. We must strive to transition to a form of industry that does not cause environmental pollution. These efforts drive may fashion brands to produce and sell products with redesigned methods that delight the inventory flow. Accordingly, it is necessary to develop creative apparel up-cycling design using the creative thinking method. This study aims to produce clothing redesign works by introducing design idea types for systematic redesign creation. In this research, we conducted a literature review on the concept of up-cycling design and employed heterotopa spacial concept reflected fashion design creation methodology types. The RE;CODE, a leading domestic up-cycling design brand, was used in case analysis. According to the command of shape transformation, it is spreading, stacking, dropping, inverting and crossing, from the creative thinking method reflecting heterotopia spacial concepts, showing designers a concrete way to transform form into new apparel. Seven works of apparel up-cycling design were developed by conducting process of RE;CODE. Also, to establish an apparel up-cycling design creation process for creating works. In this study, we proposed a systematic method for apparel up-cycling design, including a method for reorganizing two or more different materials to create something new and ultimately reversing the structure. The value and significance of this study is that it proposes a systematic method for apparel up-cycling design to make it new.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.1-9
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• 2021

Traditionally, most malicious codes have been analyzed using feature information extracted by domain experts. However, this feature-based analysis method depends on the analyst's capabilities and has limitations in detecting variant malicious codes that have modified existing malicious codes. In this study, we propose a ResNet-Variational AutoEncder-based variant malware classification method that can classify a family of variant malware without domain expert intervention. The Variational AutoEncoder network has the characteristics of creating new data within a normal distribution and understanding the characteristics of the data well in the learning process of training data provided as input values. In this study, important features of malicious code could be extracted by extracting latent variables in the learning process of Variational AutoEncoder. In addition, transfer learning was performed to better learn the characteristics of the training data and increase the efficiency of learning. The learning parameters of the ResNet-152 model pre-trained with the ImageNet Dataset were transferred to the learning parameters of the Encoder Network. The ResNet-Variational AutoEncoder that performed transfer learning showed higher performance than the existing Variational AutoEncoder and provided learning efficiency. Meanwhile, an ensemble model, Stacking Classifier, was used as a method for classifying variant malicious codes. As a result of learning the Stacking Classifier based on the characteristic data of the variant malware extracted by the Encoder Network of the ResNet-VAE model, an accuracy of 98.66% and an F1-Score of 98.68 were obtained.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.68.3-69
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• 2021

We present a novel profile stacking technique based on optimal profile decomposition of a 3D spectral line data cube, and its performance test using the HI data cubes of sample galaxies from HI galaxy surveys, THINGS and LITTLE THINGS. Compared to the previous approach which aligns all the spectra of a cube using their central velocities derived from either moment analysis, single Gaussian or hermite h3 polynomial fitting, the new method makes a profile decomposition of the profiles from which an optimal number of single Gaussian components is derived for each profile. The so-called superprofile which is derived by co-adding all the aligned profiles from which the other Gaussian models are subtracted is found to have weaker wings compared to the ones constructed in a typical manner. This could be due to the reduced number of asymmetric profiles in the new method. A practical test made on the HI data cubes of the THINGS and LITTLE THINGS galaxies shows that our new method can extract more mass of kinematically cold HI components in the galaxies than the previous results. Additionally, we fit a double Gaussian model to the superprofiles whose S/N is boosted, and quantify not only their profile shapes but derive the ratio of the Gaussian model parameters, such as the intensity ratio and velocity dispersion ratio of the narrower and broader Gaussian components. We discuss how the superprofile properties of the sample galaxies are correlated with their other physical properties, including star formation rate, stellar mass, metallicity, and gas mass.

• Geophysics and Geophysical Exploration
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• v.16 no.1
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• pp.6-17
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• 2013

Multicomponent seismic data including both P- and PS-waves have advantages in discriminating the type of pore fluid, characterizing the lithologic attributes and producing the high resolution image. However, multicomponent seismic data recorded at the vertical and horizontal component receivers contain both P- and PS-waves which have different features, simultaneously. Therefore, the wavefield separation of P- and PS-waves as a preprocessing is inevitable in order to use the multicomponent seismic data successfully. In this study, we analyzed the previous study of the wavefield separation method suggested by Jeong and Byun in 2011, where the approximated reflection angle calculated only from one refernce depth is used in rotation transform, and showed its limitation for seismic data containing various reflected events from the multi-layered structure. In order to overcome its limitation, we suggested a new effective wavefield separation method of P- and PS-waves. In new method, we calculate the reflection angles with various reference depths and apply rotation transforms to the data with those reflection angles. Then we stack all results to obtain the final separated data. To verify our new method, we applied it to the synthetic data sets from a multi-layered model, a fault model, and the Marmousi-2 model. The results showed that the proposed method separated successfully P- and PS-reflection events from the multicomponent data from mild dipping layered model as long as the dip is not too steep.

• New & Renewable Energy
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• v.16 no.1
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• pp.15-24
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• 2020

For mechanical load testing of wind turbines, capture matrix is constructed for various range of wind speeds according to the international standard IEC 61400-13. The conventional method wastes considerable amount of data by its invalid data policy -segment data into 10 minutes then remove invalid ones. Previously, we have suggested an alternative way to save the total amount of data to build a capture matrix, but the efficient selection of data has been still under question. The paper introduces optimization algorithms to construct capture matrix with less data. Heuristic algorithm (simple stacking and lowest frequency first), population method (particle swarm optimization) and Q-Learning accompanied with epsilon-greedy exploration are compared. All algorithms show better performance than the conventional way, where the distribution of enhancement was quite diverse. Among the algorithms, the best performance was achieved by heuristic method (lowest frequency first), and similarly by particle swarm optimization: Approximately 28% of data reduction in average and more than 40% in maximum. On the other hand, unexpectedly, the worst performance was achieved by Q-Learning, which was a promising candidate at the beginning. This study is helpful for not only wind turbine evaluation particularly the viewpoint of cost, but also understanding nature of wind speed data.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.688-697
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• 2014

In this study, electrode bonding technology needed for high density of rechargeable battery is studied, which is recently researched for electric vehicle, the small leisure vessel. For the alternative overcoming the limit of stacking amount able to be stacked by conventional ultrasonic welding, the low temperature bonding method, eligible for minimum of degeneration of chemical activator on the electrode surface which is generated by thermal effect as well as the increase of conductivity and tension strength caused by electrode bonding using filler metal, not using conventional direct heating on the electrode material method, is studied. Specifically to say, recently used more generally the ultrasonic welding and spot welding method are not usable for satisfying stable electric conductivity and bonding strength when much electrode is stacking bonded. If the electrical power is unreasonably increased for the welding, due to the effect of welding temperature, deformation of electrode and activating material degeneration are caused, and after the last packaging, decline of electrical output and generating heat cause to reduce stability of battery. Therefore, in this study, induction heating system bonding method using high frequency heating and differentiated electrode method using filler metal pre-treatment of hot dipping are introduced.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.3
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• pp.141-148
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• 2023

Accurate overlay metrology is essential to achieve high yields of semiconductor products. Overlay metrology performance is greatly affected by overlay target design and measurement method. Therefore, in order to improve the performance of the overlay target, measurement methods applicable to various targets are required. In this study, we propose a new algorithm that can measure image-based overlay. The proposed measurement algorithm can estimate the sub-pixel position by using a motion vector. The motion vector may estimate the position of the sub-pixel unit by applying a quadratic equation model through polynomial expansion using pixels in the selected region. The measurement method using the motion vector can calculate the stacking error in all directions at once, unlike the existing correlation coefficient-based measurement method that calculates the stacking error on the X-axis and the Y-axis, respectively. Therefore, more accurate overlay measurement is possible by reflecting the relationship between the X-axis and the Y-axis. However, since the amount of computation is increased compared to the existing correlation coefficient-based algorithm, more computation time may be required. The purpose of this study is not to present an algorithm improved over the existing method, but to suggest a direction for a new measurement method. Through the experimental results, it was confirmed that measurement results similar to those of the existing method could be obtained.

• Geophysics and Geophysical Exploration
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• v.17 no.2
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• pp.66-73
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• 2014

To estimate the shear-velocity ($v_s$) structure beneath the WIZ station on White Island in New Zealand, we applied receiver function (RF) inversion and H-${\kappa}$ stacking methods to 362 teleseismic events (Mw > 5.5) recorded during April 20, 2007 to September 6, 2013. Using 71 RFs with errors less than 20% after 200 iterative computations, we determined that the depth to Moho of $v_s$ = 4.35 km/s is $24{\pm}1km$ within a 15 km radius of the station. In an 1-d $v_s$ model derived by RF inversions, a 4-km thick low-velocity layer (LVL) at depths of 18 ~ 22 km was identified in the lower crust. This LVL, which is 0.15 km/s slower than the rocks above and below it, may indicate the presence of a deep magma reservoir. The H-${\kappa}$ stacking method yielded an estimate of the depth to the Moho of 24.5 km, which agrees well with the depth determined by RF inversions. The low $v_p/v_s$ ratio of 1.64 may be due to the presence of gas-filled rock or hot crystallizing magma.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.1
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• pp.222-233
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• 1995

For effective module generation, a detailed router which can handle complicated routing regions on multimple layers of interconnection under various constraints is necessary. In this paper, a new improved maze routing technique is described, which can find the shortest path for each net without allowing stacked vias. In this method, two cost values are stored at each grid point. The cost values represent the routing costs from the terminal of the net being routed to the grid point. One cost value shows the cost of the shortest path without making a via at the grid point and the other cost value shows that with making a via at the grid point. This is the first systematic maze routing technique which can find the shortest path without via-stacking.