• Journal of the Korean Ceramic Society
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• v.34 no.1
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• pp.31-36
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• 1997

The effects of 0 to 10mol% excess MgO addition on the microstructure and dielectric properties in 30Pb(Mg1/3Nb2/3)O3-20PbTiO3-50Pb(Mg1/2W1/2)O3 ternary system were investigated. Samples were prepared by mixed oxide and precursor methods to compare the role of excess MgO. Excess MgO enhanced grain growth and increased dielectric constant. The dielectric constant and tesmperature dependence of dielectric constant of the sample sintered at 100$0^{\circ}C$ with 5mol% MgO were above 5,000 and +25% to -50% from - 55$^{\circ}C$ to 1$25^{\circ}C$, respectively. For these specimens the phases percent were mainly perovskite and Pb2WO5, which was confirmed by XRD analysis. Also the amount of cubic pyrochlore Pb3Nb4O13 and PbWO4 were de-creased with sintering temperature and MgO addition. BSE image showed the chemical inhomogeneous dis-tribution. Crystal phase formed at each sintering temperature and the chemical inhomogeneous distribution caused the decrease of the temperature dependence of dielectric constant.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.9
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• pp.854-864
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• 2016

The use of small drone platform has become a popular topic in these days but its application for SAR operation has been little known due to the burden of the payload implementation. Drone platforms are distinguished from the conventional UAV system by the increased vulnerability to the turbulences, control-errors and poor motion stability. Consequently, sophisticated motion compensation may be required to guarantee the successful acquisition of high quality SAR imagery. Extremely limited power and mass budgets may prevent the use of additional hardwares for motion compensation and the difficulty of SAR focusing is further aggravated. In this paper, we have carried out a feasibility study of mico-SAR drone operation. We present the image acquisition results from the preliminary flight tests and a quality assessment is followed on the experimental SAR images. The in-flight motion errors derived from the unique drone movements are investigated and attempts have been made to compensate for the geometrical and phase errors caused by motions against the nominal trajectory. Finally, the successful operation of drone SAR system is validated through the focussed SAR images taken over test sites.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.99-108
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• 2005

Interactive electronic technical manual(IETM) for construction projects means an electronic tool that regulations and specifications related to construction method or maintenance process ale described by electronic book type. It has a meaning of integrated information system that includes virtual reality(VR), 3D animation and image contents for representing real construction information so that user can easily understand the construction situation and maintenance process. The basic information and technical manuals of construction facilities are being written as paper documents in our construction industry. As the result, the information management in the maintenance phase of construction projects is inefficient, and maintenance cost is being increased. This study attempts to improve the lack of understanding about construction IETM through the analysis of necessity and unique function of construction IETM comparing with the IETMS in other industry, Finally, this study shows a scenario of construction IErM for mitigating natural disaster of construction facilities to verify applicability of IETM.

• Journal of the Korean earth science society
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• v.24 no.4
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• pp.303-314
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• 2003

Ocean-air observation using an Automatic Weather Station (AWS) and Conductivity Temperature Depth (CTD) was conducted in the Mid-Yellow Sea off Korea during 8-10 July 2002. A water mass lower than 17$^{\circ}C$ around the Taean peninsula and a tidal front between 36$^{\circ}$20'N and 36$^{\circ}$30'N were observed. The horizontal distribution of air temperature was similar to that of sea surface temperature (SST). Hourly observation around Dukjuk island showed the cold and saline southwesterly and the warm and fresh northeasterly in phase with tidal current. Sea fogs two times formed at 2300 LST 8-0130 LST 9, and 0300-0600 LST 9 July 2002 during the observation period, respectively. During the initial stage of fogs, winds became northeasterly at the speed of 2-4m/s$^{-1}$, and air temperature dropped to 18$^{\circ}C$, as the North Pacific High weakened. The satellite image indicated that sea fogs formed over warm water in the western Yellow Sea and moved eastward toward the observation site, which could be called a steam fog. The fogs dissipated when wind speed and air temperature increased.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.2
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• pp.163-170
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• 2021

This study was conducted to create a technology to remove acne bacteria with human-friendly materials. First, the Cutibacterium acnes (C. acnes) were adsorbed to the mica disc to grow, and then the biofilm was checked through an atomic microscope to see if the biofilm had grown. Based on the topographic image, the shape changed round, the size was 17% longer on average, and the phase value of the resonance frequency separating materials was observed as a single value, the biofilm grown by covering the extracellular polymeric substrate (EPS). As a result of processing 50 mM of amino acids in the matured biofilm, the concentration of C. acnes decreased when valine, serine, arginine and leucine were treated. Scanning with nanoindentation and AFM contact modes confirmed that the hardness of biofilms treated with Valine (Val) increased. This indicates that an AFM tip measured cell which may have more solidity than that of EPS. The experiment of fluorescent tagged to EPS displays an existence of EPS at the condition of 10 mM Val, but an inhibition of growth of EPS at the 50 mM Val. Number of C. acnes was also reduced above 10 mM of Val. Weak adhesion of biofilm generated from an inhibition of EPS formation seems to induce decrease of C. acnes. Accordingly, we elucidated that Val has an efficiency which eliminates C. acnes by approach of an inhibition of EPS.

• Journal of Popular Narrative
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• v.27 no.2
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• pp.13-44
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• 2021

This article describes the fear of infection through the Covid19 pandemic and the rapid phase change of human species with H. P. Lovecraft's fiction and "Project LC. RC". Pandemic and climate change, which can be called global weirding, fundamentally question the status and history of human species in the ecosystem. The horror creature and cosmological indifferentism in Lovecraft's weird fiction are contemporary in that they help shed light on today's global weirding. But Lovecraft's racism allows him to ask more fundamental questions about the logjam of his cosmic horror. "Project LC. RC" are a Korean writers's works of cultural variation that rewrites controversial racism and misogyny in Lovecraft's fiction. Such variation becomes the task of creating a mutation in Lovecraft as it becomes infected with the affection of Lovecraft's writing. This article first noted the creative power of Lovecraft's fiction that induces such a mutation. And under this premise, this article wanted to reveal the meaning of Lee Seo young, Eun rim, and Kim Bo young's recreates of Lovecraft's fiction through the analysis of images and motifs of abject, plant creature and symbiosis. Specifically, Lovecraft's creature, which evokes phallic fear, turns into an image of an abject embracing and comforting women's despair("I Want You to Stay Low"), a plant creature that provides women with refuge("Color in the Well"), and a creature of care and symbiotic life("A Sea of Plague"). This recreate/rewriting has contemporary significance in that it embodies values such as labor, care, and solidarity in their works. The conclusion noted another power of creative variation in Lovecraft's fiction, which is not reduced to recreate/rewriting.

• Korean Journal of Radiology
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• v.23 no.11
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• pp.1055-1066
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• 2022

Objective: The clinical relevance of myosteatosis has not been well evaluated in patients with pancreatic ductal adenocarcinoma (PDAC), although sarcopenia has been extensively researched. Therefore, we evaluated the prognostic value of muscle quality, including myosteatosis, in patients with resectable PDAC treated surgically. Materials and Methods: We retrospectively evaluated 347 patients with resectable PDAC who underwent curative surgery (mean age ± standard deviation, 63.6 ± 9.6 years; 202 male). Automatic muscle segmentation was performed on preoperative computed tomography (CT) images using an artificial intelligence program. A single axial image of the portal phase at the inferior endplate level of the L3 vertebra was used for analysis in each patient. Sarcopenia was evaluated using the skeletal muscle index, calculated as the skeletal muscle area (SMA) divided by the height squared. The mean SMA attenuation was used to evaluate myosteatosis. Diagnostic cutoff values for sarcopenia and myosteatosis were devised using the Contal and O'Quigley methods, and patients were classified according to normal (nMT), sarcopenic (sMT), myosteatotic (mMT), or combined (cMT) muscle quality types. Multivariable Cox regression analyses were conducted to assess the effects of muscle type on the overall survival (OS) and recurrence-free survival (RFS) after surgery. Results: Eighty-four (24.2%), 73 (21.0%), 75 (21.6%), and 115 (33.1%) patients were classified as having nMT, sMT, mMT, and cMT, respectively. Compared to nMT, mMT and cMT were significantly associated with poorer OS, with hazard ratios (HRs) of 1.49 (95% confidence interval, 1.00-2.22) and 1.68 (1.16-2.43), respectively, while sMT was not (HR of 1.40 [0.94-2.10]). Only mMT was significantly associated with poorer RFS, with an HR of 1.59 (1.07-2.35), while sMT and cMT were not. Conclusion: Myosteatosis was associated with poor OS and RFS in patients with resectable PDAC who underwent curative surgery.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.35-41
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• 2001

This paper describes Linear Discriminant Analysis and common vector extraction for speech recognition. Voice signal contains psychological and physiological properties of the speaker as well as dialect differences, acoustical environment effects, and phase differences. For these reasons, the same word spelled out by different speakers can be very different heard. This property of speech signal make it very difficult to extract common properties in the same speech class (word or phoneme). Linear algebra method like BT (Karhunen-Loeve Transformation) is generally used for common properties extraction In the speech signals, but common vector extraction which is suggested by M. Bilginer et at. is used in this paper. The method of M. Bilginer et al. extracts the optimized common vector from the speech signals used for training. And it has 100％ recognition accuracy in the trained data which is used for common vector extraction. In spite of these characteristics, the method has some drawback-we cannot use numbers of speech signal for training and the discriminant information among common vectors is not defined. This paper suggests advanced method which can reduce error rate by maximizing the discriminant information among common vectors. And novel method to normalize the size of common vector also added. The result shows improved performance of algorithm and better recognition accuracy of 2％ than conventional method.

• Journal of the Korean earth science society
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• v.32 no.3
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• pp.276-293
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• 2011

In this study a modeling system consisting of Weather Research and Forecasting (WRF), Sparse Matrix Operator Kernel Emissions (SMOKE), the Community Multiscale Air Quality (CMAQ) model, and the CMAQ-Model of Aerosol Dynamics, Reaction, Ionization, and Dissolution (MADRID) model has been applied to estimate enhancements of $PM_{10}$ during Asian dust events in Korea. In particular, 5 experimental formulas were applied to the WRF-SMOKE-CMAQ (MADRID) model to estimate Asian dust emissions from source locations for major Asian dust events in China and Mongolia: the US Environmental Protection Agency (EPA) model, the Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model, and the Dust Entrainment and Deposition (DEAD) model, as well as formulas by Park and In (2003), and Wang et al. (2000). According to the weather map, backward trajectory and satellite image analyses, Asian dust is generated by a strong downwind associated with the upper trough from a stagnation wave due to development of the upper jet stream, and transport of Asian dust to Korea shows up behind a surface front related to the cut-off low (known as comma type cloud) in satellite images. In the WRF-SMOKE-CMAQ modeling to estimate the PM10 concentration, Wang et al.'s experimental formula was depicted well in the temporal and spatial distribution of Asian dusts, and the GOCART model was low in mean bias errors and root mean square errors. Also, in the vertical profile analysis of Asian dusts using Wang et al's experimental formula, strong Asian dust with a concentration of more than $800\;{\mu}g/m^3$ for the period of March 31 to April 1, 2007 was transported under the boundary layer (about 1 km high), and weak Asian dust with a concentration of less than $400\;{\mu}g/m^3$ for the period of 16-17 March 2009 was transported above the boundary layer (about 1-3 km high). Furthermore, the difference between the CMAQ model and the CMAQ-MADRID model for the period of March 31 to April 1, 2007, in terms of PM10 concentration, was seen to be large in the East Asia area: the CMAQ-MADRID model showed the concentration to be about $25\;{\mu}g/m^3$ higher than the CMAQ model. In addition, the $PM_{10}$ concentration removed by the cloud liquid phase mechanism within the CMAQ-MADRID model was shown in the maximum $15\;{\mu}g/m^3$ in the Eastern Asia area.