• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.287-290
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• 2001

최근의 급속한 인터넷 성장에 힘입어 분산처리의 기술 및 환경은 인터넷을 기반으로 광역환경으로 확장될 전망이다. 이러한 환경은 사용자에게 보다 투명한 분산객체간의 효율적인 상호접속이 요구될 뿐 아니라, 광역환경에서 이름이나 속성에 의해 다양한 중복된 성질을 갖고 있는 객체들의 관리가 요구된다. 또한 광역 분산 환경에서 최적의 객체를 선정하는데 분산된 시스템들간의 부하분배를 고려하여 투명성을 제공하는 메카니즘이 필요하게 된다. 따라서, 본 논문에서는 광역분산 컴퓨팅 환경에서 광역 서비스를 지원할 수 있는 이름/속성기반의 중복객체들을 관리를 위한 통합 트리 구성방법을 제안한다. 그리고 이를 통한 혼합(네이밍/트레이더)된 위치서비스(Location service)를 이용하여 무수히 산제한 중복된 분산 객체들을 효율적으로 유지하고, 최적의 객체 선정을 통해 부하균형을 유지할 수 있는 방안을 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.27-30
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• 2021

경제 성장과 함께 자동차의 수요가 늘어남에 따라 교통사고 발생 빈도는 꾸준히 증가하고 있다. 이에, 본 연구에서는 교통사고를 야기하는 도로 및 기상환경과 같은 조건을 활용하여 기계학습 모델을 통해 서울시 교통사고 사상자 수를 예측하는 모형을 찾고자 한다. 활용한 데이터는 도로교통 공단에서 제공하는 교통사고 사상자 수 정보를 포함하는 데이터로 2015년부터 2018년도까지 데이터를 학습에 사용하였고 2019년도 데이터를 테스트 평가에 사용하였다. 실증연구를 통해 트리 기반의 모델 별 성능을 비교하였으며 본 연구에 대한 결과는 사고 발생 시 우선순위에 의한 구조활동이 가능하게 함과 도로상황 및 기상을 고려한 안전운전 가이드 지식으로 활용될 수 있다.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.29 no.6
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• pp.308-316
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• 2019

Electron beam physical vapor deposition (EBPVD) is a conventional method to fabricate thermal barrier coating (TBC) of high temperature airfoil engine parts, such as blade etc. for its high temperature structural stability from the nature of columnar growth behavior. For the high quality of TBC by EBPVD, the structural factors, such as growth behavior, thickness uniformity and so on, should be managed to obtain the coating which satisfied the required specifications of usable level of mechanical and thermal properties. In this study, the growth behavior and structure variations of 7YSZ (7 wt% yttria stabilized zirconia) coatings with different configurational deposition parameters for the specimens which have turbine blade shape mock-up were investigated. Growth behavior of coatings were studied by comparing computational modeling of evaporation behavior with actual deposition process using e-beam source.

• Polymer(Korea)
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• v.27 no.4
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• pp.293-298
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• 2003

The development of the crystalline structure of poly(trimethylene terephthalate) (PTT) in a confined geometry was investigated with optical microscope, small angle light scattering, and X-ray diffraction. The rejected distance, which was represented in terms of the parameter $\delta$, played an important role in determining the morphological patterns of poly (ethylene terethphalate) (PET/PTT) blend. In case of stepwise crystallization, the crystallization of PTT commenced in the interspherulitic region between the grown PET crystals and proceeded until the interspherulitic space was filled with the PTT crystals. The spherulitic surface of the PET crtstals acted as the nucleation sites where the PTT molecules preferentially crystallized, leading to the formation of transcrystalline structure. As a result, a mixed morphological pattern was observed in the PTT-rich phase: one was a typical spherulitic texture and the other was a transcrystalline texture. Some of the molecular conformations of PTT, which could adopt in the absence of the space limitation, were probably forbidden in the interlamellar and/or interfibrillar regions of the PET spherulite. This constraint was responsible for difference in the crystallization and melting behavior of PTT between the intra and interspheulitic regions of PET.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.372-380
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• 2010

Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information that can be used to increase revenue, cuts costs, or both. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining is one of the fastest growing field in the computer industry. Because of According to computer technology has been improving, Massive customer data has stored in database. Using this massive data, decision maker can extract the useful information to make a valuable plan with data mining. Data mining offers service providers great opportunities to get closer to customer. Data mining doesn't always require the latest technology, but it does require a magic eye that looks beyond the obvious to find and use the hidden knowledge to drive marketing strategies. Automotive market face an explosion of data arising from customer but a rate of increasing customer is getting lower. therefore, we need to determine which customer are profitable clients whom you wish to hold. This paper builds model of customer loyalty detection and analyzes customer buying patterns in automotive market with data mining using decision tree as a quinlan C4.5 and basic statics methods.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.71-78
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• 2020

Recently, as the issue of gentrification emerges, it becomes important to understand the dynamics of local commercial district, which plays the important role for facilitating the local economy and building the community in a city. This paper attempts to provide the framework for systemically analyzing and understanding the local commercial district. Then, this paper empirically analyzes the patterns of sales and flow of floating population by focusing on two representative local commercial districts in Seoul. In addition, the floating population data from telecommunication bases is further modeled with Markov chain for systemically understanding the local commercial districts. Finally, the transition patterns and consumption amounts of floating population are comprehensively analyzed for providing the implications on the evolutions of local commercial districts in a city. We expect that findings of our study could contribute to the economic growth of local commercial district, which could lead to the continuous development of city economy.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.183-185
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• 2015

Recently, big data analysis based on machine learning has gained popularity and many machine learning techniques have been applied to the field of agriculture. By using machine learning technique to analyze huge number of samples of biological and environmental data, new observations can be found. In this research, we consider the estimation of proportional daily weight increase (PDWI) based on measurement data from experimental swine farm. In order to derive the exact formulation for PDWI estimation, we have used measured value of mean, daily maximum, daily minimum of temperature, humidity, CO2, wind speed and measured PDWI values. Based on collected data, we have derived equation for PDWI estimation using tree-based algorithm. In the derived formulation, we have found that the daily average temperature is the most dominant factor that affects PDWI. Our results can be applied to pig farms to estimate the PDWI of swine.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.415-427
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• 2021

This technical report briefly introduced the rock cutting splitting method under development. This method is a method of excavating the rock by splitting the block after the rock cutting process. After designing the cutting geometry of the rock face, the chisel is press-fitted to remove the rock block. At this time, when the cutting block is properly designed, the tensile crack propagates smoothly at the bottom of the rock block. An analytical solution was devised to estimate the indentation force required for splitting rock blocks using fracture toughness mode 1 required for tensile crack growth. The impact force of the hydraulic breaker of the excavator was analyzed, and the grade of the excavator that can be constructed according to the rock block design geometry was analyzed.

• Journal of Mushroom
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• v.22 no.3
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• pp.92-101
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• 2024

Hair dyeing, hair perming, and daily hair dryer use can substantially damage hair. Consequently, the demand for products containing natural ingredients for the care of damaged hair is growing. Although polyphenols with antioxidant effects are often used for hair conditioning, few studies have focused on hair conditioning, and the potential of Sparassis latifolia mushroom extract for hair improvement has not been evaluated to date. In this study, the antioxidant activity of and polyphenol content in hot water, 70% and 100% ethanol (EtOH), n-hexane, ethyl acetate (EtOAc), and water extracts of S. latifolia were analyzed. A hair treatment containing S. latifolia extract was prepared, and its effect on damaged hair was evaluated. The highest antioxidant activity was observed in the hot water and EtOAc extracts. Moreover, polyphenol analysis using high-performance liquid chromatography and liquid chromatography-mass spectroscopy confirmed that the EtOAc fraction has relatively high contents of specific polyphenols beneficial for hair. Based on these results, a hair treatment containing S. latifolia extract was applied to damaged hair, and hair improvement was evaluated using hair thickness, tensile strength, and scanning electron microscopy. The hair treatment containing 70% EtOH extract effectively improved hair condition. We postulate that this improvement was caused by the high hydrophobic polyphenol content in the 70% EtOH extract.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.7 no.3
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• pp.377-383
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• 1997

Yttria-stabilized TZP alloyed with pentavalent oxides $(Ta_2O_5,\;Nb_2O_5)$ were fabricated by the conventional sintering method at $1500^{\circ}C$ in air to construct the simplified ternary phase diagram. The phase stability of tetragonal -$ZrO_2$ from the quasi-binary system $ZrO_2-YTa(Nb)O_4$, which do not transform to monoclinic-$ZrO_2$ even for a wide range of grain size and annealing temperature, was investigated to determine composition region of the non-transformable $t-ZrO_2$ solid solution$(NT_{ss})$. Phase stability of $NT_{ss}$ was probably due to the enhanced stability of $_YTa(Nb)O4$ having the tetragonal fergusonite structure. It was experimentally found that mixtures having $NT_{ss}$ alloyed with $T_{ss}$ by weight%% showed both excellent phase stability of $t-ZrO_2$ and fracture toughness even though the calculated composition of the mixture /was located outside $NT_{ss}$ composition region.