• Geomechanics and Engineering
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• v.21 no.4
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• pp.357-369
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• 2020

Different from the conventional planar fracture and simplified Newton model, for power-law slurries with a lower water-cement ratio commonly used in grouting engineering, flow model in geological rough fractures is built based on ten standard profiles from Barton (1977) in this study. The numerical algorithm is validated by experimental results. The flow mechanism, grout superiority, and water plugging of pseudo plastic slurry are revealed. The representations of hydraulic grouting properties for JRCs are obtained. The results show that effective plugging is based on the mechanical mechanisms of the fluctuant structural surface and higher viscosity at the middle of the fissure. The formulas of grouting parameters are always variable with the roughness and shear movement, which play a key role in grouting. The roughness can only be neglected after reaching a threshold. Grouting pressure increases with increasing roughness and has variable responses for different apertures within standard profiles. The whole process can be divided into three stationary zones and three transition zones, and there is a mutation region (10 < JRCs < 14) in smaller geological fractures. The fitting equations of different JRCs are obtained of power-law models satisfying the condition of -2 < coefficient < 0. The effects of small apertures and moderate to larger roughness (JRCs > 10.8) on the permeability of surfaces cannot be underestimated. The determination of grouting parameters depends on the slurry groutability in terms of its weakest link with discontinuous streamlines. For grouting water plugging, the water-cement ratio, grouting pressure and grouting additives should be determined by combining the flow conditions and the apparent widths of the main fracture and rough surface. This study provides a calculation method of grouting parameters for variable cement-based slurries. And the findings can help for better understanding of fluid flow and diffusion in geological fractures.

• Proceedings of the KWS Conference
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• 2009.11a
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• pp.8-8
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• 2009

알루미늄 합금 Al 6082-T6는 최근에 개발되어 북유럽 등의 선진국에서는 그 뛰어난 해양 내식성과 우수한 강도로 인하여 해양구조물의 헬리데크(Helideck), 타워 갱웨이(Tower gangway), 알루미늄 피팅류(Aluminium fitting)등의 해양구조물과 플랫폼(Flatform), 알루미늄 래더(Aluminium ladder)등의 선박부품, 차량, 기계부품 분야에서 전 세계적으로 널리 사용되기 시작하였다. 그러나 전통적으로 용접금속의 기공은 결함으로 분류 되고, Rakesh Kumar 등의 논문에 따르면 용접 시 용접금속 내에 발생되어진 미세기공이 기계적 성질에 악영향을 미치는 것으로 보고되어졌다. 따라서 용접금속내의 발생하는 기공을 방지하는 용접공정의 개발이 반드시 필요하다. 본 연구의 목적은 Al 6082-T6 고속 MIG용접에서 기공방지를 위한 용접공정을 개발하는 것이다. Al 6082-T6의 7t 플레이트에 Al 5356의 와이어를 사용하여 아크길이 변경 및 용접속도를 60cpm과 120cpm으로 변경하여 실험하였고, 용접속도 120cpm의 고속 MIG용접에서 토치 진행각을 변경하여 실험을 진행하였다. 용접공정 파라메터 변경에 따른 기공율 측정은 이미지 분석 소프트웨어를 사용하여 정량적으로 분석하였다.

• Current Optics and Photonics
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• v.2 no.5
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• pp.422-430
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• 2018

Rolling shutter operation of CMOS cameras can be utilized in optical camera communications in order to transmit data from an LED to mobile devices such as smart-phones. From temporally modulated light, a spatial flicker pattern is obtained in the captured image, and this is used for signal recovery. Due to the degradation of rolling shutter images caused by light smear, motion blur, and focus blur, the conventional decoding schemes for rolling shutter cameras based on the pattern width for 'OFF' and 'ON' cannot guarantee robust communications performance for practical uses. Aside from conventional techniques, such as polynomial fitting, histogram equalization can be used for blurry light mitigation, but it requires additional computation abilities resulting in burdens on mobile devices. This paper proposes a transition-based decoding scheme for rolling shutter cameras in order to offer simple and robust data decoding in the presence of image degradation. Based on the designed synchronization pulse and modulated data symbols according to the LED dimming level, the decoding process is conducted by observing the transition patterns of two sequential symbol pulses. For this, the extended symbol pulse caused by consecutive symbol pulses with the same level determines whether the second pulse should be included for the next bit decoding or not. The proposed method simply identifies the transition patterns of sequential symbol pulses other than the pattern width of 'OFF' and 'ON' for data decoding, and thus, it is simpler and more accurate. Experimental results ensured that the transition-based decoding scheme is robust even in the presence of blurry lights in the captured image at various dimming levels

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.245-254
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• 2021

Purpose: In order to accurately reach an underwater projectile to a target point, reliable INS and accurate arrangement of INS between master and slave INS is paramount. Unlike terrestrial and aerial environments, underwater projectile will operates in a restricted environment where location information cannot be received or sent through satellites. In this report, we review the factors affecting the transfer alignment of master and slave INS, as well as how to improve the positional error between INS through improved transfer alignment algorithms. Methods: In this work, we propose an improvement algorithm and verify it through simulation and driving test. The simulation confirmed the difference in the transfer alignment azimuth by fitting the MINS and SINS indoors, displacement in posture, and the process of transfer alignment between MINS and SINS through a driving test to confirm algorithm can improve the arrangement. Results: According to this study, reason for the error in the transfer alignment between MINS/SINS is the factors of the system where movements such as roll, pitch, yaw are not inter locked in real time due to the delay in transmit/receive system. And confirm that the improved algorithm has a desirable effect on accuracy. Conclusion: Through this work, it is possible to identify ways to improve the accuracy of underwater projectiles to reach their target points under various underwater environments and launch condition.

• Nano
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• v.13 no.11
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• pp.1850126.1-1850126.10
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• 2018

Flexible strain sensors, as the core member of the family of smart electronic devices, along with reasonable sensing range and sensitivity plus low cost, have rose a huge consumer market and also immense interests in fundamental studies and technological applications, especially in the field of biomimetic robots movement detection and human health condition monitoring. In this paper, we propose a new flexible strain sensor based on thick CVD graphene film and its low-cost fabrication strategy by using the commercial adhesive tape as flexible substrate. The tensile tests in a strain range of ~30% were implemented, and a gage factor of 30 was achieved under high strain condition. The optical microscopic observation with different strains showed the evolution of cracks in graphene film. Together with commonly used platelet overlap theory and percolation network theory for sensor resistance modeling, we established an overlap destructive resistance model to analyze the sensing mechanism of our devices, which fitted the experimental data very well. The finding of difference of fitting parameters in small and large strain ranges revealed the multiple stage feature of graphene crack evolution. The resistance fallback phenomenon due to the viscoelasticity of flexible substrate was analyzed. Our flexible strain sensor with low cost and simple fabrication process exhibits great potential for commercial applications.

• Structural Engineering and Mechanics
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• v.69 no.6
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• pp.627-635
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• 2019

In order to study the axial compression performance of sand-lightweight concrete-filled steel tube (SLCFST) stub columns, three circular SLCFST (C-SLCFST) stub column specimens and three SLCFST square (S-SLCFST) stub column specimens were fabricated and static monotonic axial compression performance testing was carried out, using the volume ratio between river sand and ceramic sand in sand-lightweight concrete (SLC) as a varying parameter. The stress process and failure mode of the specimens were observed, stress-strain curves were obtained and analysed for the specimens, and the ultimate bearing capacity of SLCFST stub column specimens was calculated based on unified strength theory, limit equilibrium theory and superposition theory. The results show that the outer steel tubes of SLCFST stub columns buckled outward, core SLC was crushed, and the damage to the upper parts of the S-SLCFST stub columns was more serious than for C-SLCFST stub columns. Three stages can be identified in the stress-strain curves of SLCFST stub columns: an elastic stage, an elastic-plastic stage and a plastic stage. It is suggested that AIJ-1997, CECS 159:2004 or AIJ-1997, based on superposition theory, can be used to design the ultimate bearing capacity under axial compression for C-SLCFST and S-SLCFST stub columns; for varying replacement ratios of natural river sand, the calculated stress-strain curves for SLCFST stub columns under axial compression show good fitting to the test measure curves.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.143-159
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• 2019

Machine learning (ML) is a method of fitting given data to a mathematical model to derive insights or to predict. In the age of big data, where the amount of available data increases exponentially due to the development of information technology and smart devices, ML shows high prediction performance due to pattern detection without bias. The feature engineering that generates the features that can explain the problem to be solved in the ML process has a great influence on the performance and its importance is continuously emphasized. Despite this importance, however, it is still considered a difficult task as it requires a thorough understanding of the domain characteristics as well as an understanding of source data and the iterative procedure. Therefore, we propose methods to apply deep learning for solving the complexity and difficulty of feature extraction and improving the performance of ML model. Unlike other techniques, the most common reason for the superior performance of deep learning techniques in complex unstructured data processing is that it is possible to extract features from the source data itself. In order to apply these advantages to the business problems, we propose deep learning based methods that can automatically extract features from transaction data or directly predict and classify target variables. In particular, we applied techniques that show high performance in existing text processing based on the structural similarity between transaction data and text data. And we also verified the suitability of each method according to the characteristics of transaction data. Through our study, it is possible not only to search for the possibility of automated feature extraction but also to obtain a benchmark model that shows a certain level of performance before performing the feature extraction task by a human. In addition, it is expected that it will be able to provide guidelines for choosing a suitable deep learning model based on the business problem and the data characteristics.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.40-53
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• 2019

Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research questions, namely (1) Is the dissemination of fake news supported by machines through the automatic construction of filter bubbles, and (2) Are echo chambers of fake news manmade, and if yes, what are the information behavior patterns of those individuals reacting to fake news? We discuss the role of filter bubbles by analyzing social media's ranking and results' presentation algorithms. To understand the roles of individuals in the process of making and cultivating echo chambers, we empirically study the effects of fake news on the information behavior of the audience, while working with a case study, applying quantitative and qualitative content analysis of online comments and replies (on a blog and on Reddit). Indeed, we found hints on filter bubbles; however, they are fed by the users' information behavior and only amplify users' behavioral patterns. Reading fake news and eventually drafting a comment or a reply may be the result of users' selective exposure to information leading to a confirmation bias; i.e. users prefer news (including fake news) fitting their pre-existing opinions. However, it is not possible to explain all information behavior patterns following fake news with the theory of selective exposure, but with a variety of further individual cognitive structures, such as non-argumentative or off-topic behavior, denial, moral outrage, meta-comments, insults, satire, and creation of a new rumor.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.813-821
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• 2020

Recently, research using unstructured data such as images and videos has been actively conducted in various fields. Edge detection is one of the most useful image enhancement techniques to improve the quality of the image process. However, it is very difficult to perform edge detection in noise images because the edges and noise having high frequency components. This paper uses a linear model and standard deviation as an effective edge detection method for noise images. The edge is detected by the difference between the standard deviation of the pixels included in the pixel block and the standard deviation of the residual obtained by fitting the linear model. The results of edge detection are compared with the results of the Sobel edge detector. In the original image, the Sobel edge detection result and the proposed edge detection result are similar. Proposed method was confirmed that the edge with reduced noise was detected in the various levels of noise images.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.75-81
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• 2021

With the development of advanced information and communication technology, Generation Z, familiar with digital culture, is drawing keen attention as a major consumer of the fashion industry. In this study, casual wear for Generation Z, who is proficient in digital devices and prefers information acquisition and lifestyle over the Internet, was designed using 3D virtual simulation and developed into four looks: Gulish, Sportive, Easy and Contemporary. The use of simulation of 3D virtual clothing in costume design can build digitalization of future fashion industry through convergence with digital fashion design planning and production process in fandemic environment and strengthen online platform distribution. In a business environment that continues to innovate to enhance work efficiency by introducing an Untouch fashion production system, the use of 3D virtual clothing technology can increase the efficiency of sustainable management through 3D sample production, online fitting, modification, and final critic processes to reduce the time and cost of human and physical resources and review.