• Journal of the Korean Society of Clothing and Textiles
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• v.7 no.2
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• pp.19-25
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• 1983

The purpose of this study was to investigate the effects of laundry variables and additives on the removal of deposited calcium on the cotton fabric. Samples of calcium deposited fabric was made by treating fabric with $CaC1_2$ and $Na_2CO_3$ solution subsequently. The experimental variables were: 1) NaOH concentration ($0.0001\%$, $0.0005\%$, $0.001\%$, $0.005\%$, $0.01\%$) 2) Alkaline builders(sodium carbonate, sodium meta silicate) 3) Sequestering agents(STPP and EDTA concentration: $0.02\%$, $0.04\%$, $0.06\%$, $0.08\%$, $0.1\%$, $0.15\%$, $0.2\%$) 4) Temperatures($25\pm1^{\circ}C$, $40\pm1^{\circ}C$, $60\pm1^{\circ}C$) 5) Edge-abrasion to the removal of deposited calcium on the cotton fabric. The fabric was washed for 15 minutes in a washing machine(Model: Gold Star WP-3007) or Launder-0-meter(40$\~$45 r.p.m., Toyo Rika Instrument Inc.) and rinsed 3 times per every rinsing time. The amount of calcium deposits on the fabrics was determined by EDTA-back titration methods and edge-abrasion was evaluated by ASTM D 3886 method. The results of this study were as follows: 1) pH of surfactant solution(NaOH concentration) did not influence on the removal of deposited calcium on the cotton fabric. 2) Added alkaline builders did not influence on the removal of deposited calcium on the cotton fabric. 3) It was shown that STPP and EDTA were effective to remove deposited calcium. The removal of deposited calcium on the cotton fabric was proportionally increased with increasing concentration of STPP and EDTA. At high concentration, however, the rate was rather decreased with increasing concentration. 4) The temperature of washing solution did not influence on the removal of dedosited calcium on the cotton fabric. 5) As the removal of deposited calcium on the cotton fabric was increased, the rate of edge-abrasion of the fabric was gradually increased.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.507-516
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• 2013

Mobile devices have limited computing power and resources. Since mobile devices are equipped with rich network connectivity, an approach to subscribe cloud services can effectively remedy the problem, which is called Mobile Cloud Computing (MCC). Most works on MCC depend on a method to offload functional components at runtime. However, these works only consider the limited verion of offloading to a pre-defined, designated node. Moveover, there is the limitation of managing services subscribed by applications. To provide a comprehensive and practical solution for MCC, in this paper, we propose a self-stabilizing process and its management-related methods. The proposed process is based on an autonomic computing paradigm and works with diverse quality remedy actions such as migration or replicating services. And, we devise a pratical offloading mechanism which is still in an initial stage of the study. The proposed offloading mechanism is based on our proposed MCC meta-model. By adopting the self-stabilization process for MCC, many of the technical issues are effectively resolved, and mobile cloud environments can maintain consistent levels of quality in autonomous manner.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.541-549
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• 2008

The fatigue analysis is performed to avoid structural failure in aerospace structures under repeated loads. In this paper, the fatigue life is estimated for the design of tilt rotor UAV. First of all, the fatigue load spectrum for tilt rotor UAV is generated. Fatigue analysis is done for the flaperon joint which may have FCL(fracture critical location). Tilt rotor UAV operates at two modes: helicopter mode such as taking off and landing; fixed wing mode like cruising. To make overall fatigue load spectrum, FELIX is used for helicopter mode and TWIST is used for fixed wing mode. The other hand, the Kriging meta model is used to get S-N regression curve for whole range of material life when S-N test data are analyzed. And then, the second order of S-N curve is accomplished by the least square method. In addition, the coefficient of determination method is used to ensure how accuracy it has. Finally, the fatigue life of flaperon joint is compared with that obtained by MSC. Fatigue.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.169-177
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• 2020

In South Korea, the results of R&D in science and technology are submitted to the National Science and Technology Information Service (NTIS) in reports that have Korea national science and technology standard classification codes (K-NSCC). However, considering there are more than 2000 sub-categories, it is non-trivial to choose correct classification codes without a clear understanding of the K-NSCC. In addition, there are few cases of automatic document classification research based on the K-NSCC, and there are no training data in the public domain. To the best of our knowledge, this study is the first attempt to build a highly performing K-NSCC classification system based on NTIS report meta-information from the last five years (2013-2017). To this end, about 210 mid-level categories were selected, and we conducted preprocessing considering the characteristics of research report metadata. More specifically, we propose a convolutional neural network (CNN) technique using only task names and keywords, which are the most influential fields. The proposed model is compared with several machine learning methods (e.g., the linear support vector classifier, CNN, gated recurrent unit, etc.) that show good performance in text classification, and that have a performance advantage of 1% to 7% based on a top-three F1 score.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.295-306
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• 2016

The purpose of this paper is both to analyze research trends and to predict industrial flows using the meta-data from the previous studies on data quality. There have been many attempts to analyze the research trends in various fields till lately. However, analysis of previous studies on data quality has produced poor results because of its vast scope and data. Therefore, in this paper, we used a text mining, social network analysis for time series network analysis to analyze the vast scope and data of data quality collected from a Web of Science index database of papers published in the international data quality-field journals for 10 years. The analysis results are as follows: Decreases in Mathematical & Computational Biology, Chemistry, Health Care Sciences & Services, Biochemistry & Molecular Biology, Biochemistry & Molecular Biology, and Medical Information Science. Increases, on the contrary, in Environmental Sciences, Water Resources, Geology, and Instruments & Instrumentation. In addition, the social network analysis results show that the subjects which have the high centrality are analysis, algorithm, and network, and also, image, model, sensor, and optimization are increasing subjects in the data quality field. Furthermore, the industrial connection analysis result on data quality shows that there is high correlation between technique, industry, health, infrastructure, and customer service. And it predicted that the Environmental Sciences, Biotechnology, and Health Industry will be continuously developed. This paper will be useful for people, not only who are in the data quality industry field, but also the researchers who analyze research patterns and find out the industry connection on data quality.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.

• Journal of Life Science
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• v.21 no.9
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• pp.1251-1258
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• 2011

Multiparous Hanwoo cull cows have been generally regarded to have poor meat quality compared to young and primiparous Hanwoo in Korea, and there have been few studies attempting to understand various feeding programs for the multiparous Hanwoo cull cow. In this study, the effects of a feeding program consisting of two different diets for multiparous Hanwoo cull cows on meat production and quality were tested in comparison to a commercially used diet. Diets for treatment consisted of two levels of crude protein contents, 14.28% and 12.70% for early fattening and finishing, respectively. For a control, commercially used fattening feed (12.39% crude protein) was used. Feeding trials were performed at three different farms. In farm A, 29 herds of multiparous Hanwoo cull cows were used for the treatment group and 3 herds for the control. In farms B and C, the number of animal herds for treatment and control were 8 vs. 3 and 11 vs. 4 herds, respectively. Experiment diets were fed for an average of 211 days and in treatment, early fattening diet was fed for 4 months and then finishing feed was fed until slaughter. Average daily gains, thickness of back fat, area of Longissimus dorsi, carcass weight, index of carcass weight, intramuscular fat, meat color and texture were analyzed after slaughter. Random effect model [8] was employed in effect analysis. Positive effects of treatment were found in terms of average daily gain, back fat thickness, Longissimus dorsi area, carcass weight, and intramuscular fat. Carcass yield index, meat color and texture showed a negative effect. In this study, significant results were not found in all factors analyzed because the variance between experiment farms was large, however the 90% confidence interval of summary effects of ADG, back fat thickness, Longissimus dorsi area and carcass weight were significant and that of carcass yield index, intramuscular fat, meat color and texture were less so. Conclusively, a high protein diet fed early during the fattening period in multiparous Hanwoo cull cows could have positive effects on meat production.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• The Journal of the Petrological Society of Korea
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• v.9 no.4
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• pp.211-237
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• 2000

Major element zoning has been analyzed in garnet porphroblasts obtained from the Grt-St and Ky-Grt-St grade assemblages in Zones I on the northern flank of the Pelham Dome, north central Massachusetts. These porphyroblasts grew during multiple phases of deformation and meta-morphism revealed by the inclusion trail geometry plus the chemical zoning patterns within garnet porphyroblasts. Unusual zoning patterns, including zoning reversals and gradient changes in XMn, zlgzag patterns in Fe/(Fe +Mg) and staircase-shaped patterns in XCa, are coincident with textural truncations and other changes in microstructure within the garnet porphrublasts. Chemical variations in plagioclase, biotite, muscovite and staurolite combined with inclusion trail geometry and petrography reveal that the garnet zoning patterns are modified by combinations of the following. (1) Uni-and divariant reactions involving garnet consumption(Grt+ Chl+Ms=St+Bt+Qtz + $H_2$O) and production(St+Ms + Qtz= Bt+ Grt +A1$_2$$SiO_{5}$ + $H_2$O). (2) Deformation induced episudic ionit dissolution, preferential diffusion and re-distribution during foliation development. (3) P-T changes during growth of the porphyroblasts. The P-T paths combined with petrographic and inclusion trail morphology observations consist of two pattens; (1) heating/compression during NW-SE shortening; and (2) decompression with cooling during NNW-SSE shortening. Based on temperature-time(T-t) geochronological data and late-Paleozoic tectonic model, Alleghanian metamorphism, which is the result of heterogeneous shearing concentrated along the boundary between the Abalone Terrane(Pelham dome) and cover rocks(Bronson Hill Terrane), has produced Ky-St-Ms mineral assemblage during Pennsylvanian(290-300 Ma) in Shutesbury area. However, temperature of alleghanian metamorphism was not high enough to form garnet and staurolite in the Northfiled syncline area. Alleghanian metamorphism has affected only the matrix due to heterogeneous shearing in the study area.