• Journal of the Korean Wood Science and Technology
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• v.15 no.3
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• pp.44-55
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• 1987

In order to study the effect of sawdustboard combined with plastic chips, 0.5mm($T_1$), 1mm($T_2$), 1.4mm($T_3$) thick nylon fiber. polypropylene rope fiber(RP), and 0.23mm thick moth-proof polypropylene net fiber(NP) were cut into 0.5, 1, 2cm long plastic chips. Thereafter, sawdustboard combined with plastic chips prepared as the above and plastic non-combined sawdustboard(control) were manufactured into 3 types of one-, two-, and three layer with 5 or 10% combination level. By the discussions and results at this study, the significant conclusions of mechanical and physical properties were summarized as follows: 1. The MORs were shown in the order of 3 layer> 2 layer> 1 layer among plastic non-combined boards, and $T_3$ < $T_2$ < $T_1$ < RP (NP(5%) < NP(l0%) among plastic combined boards. In 2cm long plastic chip in 1 layer board, the highest strength through all the composition was recognized. 1 layer board showing the lower strength with 0.5cm plastic chip rendered to the bending strength improvement by 2 or 3 layer board composition. On the other hand, 2 or 3 layer combined with 1, 2cm long polypropylene net fiber chips incurred MOR's conspicuous decrease requiring optimum plastic chip combined level and consideration to combined type. 2. MOE in plastic non-combined 3 layer board exhibited sandwich construction effect by higher resin content application to surface layer in the order of 3layer>1layer>2layer with the highest stiffness of the board combined with polypropylene chip, while nylon chip-combined board had little difference from plastic non-combined board. In relevant to length and layer effect, 3 layer board combined with the 0.5cm long polypropylene net fiber chip in 5% and 10% combined level presented 34-43% and 44-76% stiffness increase against plastic non-combined board(control), respectively. Moreover, in 1 layer board, 30% stiffness increase with 10% against 5% combined level in the 1 and 2cm long polypropylene net fiber chip was obtained. 3. Stress at proportional limit(Spl) showing the fiber relationship (r: 0.81-0.97) between MOR presented in the order of 1 layer<2 layer<3 layer in plastic non-combined board. Correspondingly, combined effect by layer and plastic chip length was similar to MOR's. 4. Differently from previous properties(MOR, MOE, Spl). work to maximum load(Wml) of 2 layer board approached to that of 3 layer board. Conforming the above phenomenon. 2 layer combined with 0.5cm long polypropylene net fiber chip kept the greater work than 1 layer. The polypropylene combined board superior to nylon -and plastic non - combined board seemed to have greater anti - failing capacity. 5. Internal bond strength(IB), in contrast to MOR's tendency. showed in the order of T1

• Journal of Korea Game Society
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• v.4 no.4
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• pp.11-18
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• 2004

The on-line games in the past were played by only two persons exchanging data based on one-to-one connections, whereas recent ones (e.g. MMORPG: Massively Multi-player Online Role-playings Game) enable tens of thousands of people to be connected simultaneously. Specifically, Korea has established an excellent network infrastructure that can't be found anywhere in the world. Almost every household has a high-speed Internet access. What made this possible was, in part, high density of population that has accelerated the formation of good Internet infrastructure. However, this rapid increase in the use of on-line games may lead to surging traffics exceeding the limited Internet communication capacity so that the connection to the games is unstable or the server fails. expanding the servers though this measure is very costly could solve this problem. To deal with this problem, the present study proposes the load distribution technology that connects in the form of local clustering the game servers divided by their contents used in each on-line game reduces the loads of specific servers using the load balancer, and enhances performance of sewer for their efficient operation. In this paper, a cluster system is proposed where each Game server in the system has different contents service and loads are distributed efficiently using the game server resource information such as CPU utilization. Game sewers having different contents are mutually connected and managed with a network file system to maintain information consistency required to support resource information updates, deletions, and additions. Simulation studies show that our method performs better than other traditional methods. In terms of response time, our method shows shorter latency than RR (Round Robin) and LC (Least Connection) by about 12%, 10% respectively.

• Development and Reproduction
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• v.12 no.1
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• pp.31-39
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• 2008

Neural tissue has limited intrinsic capacity of repair after injury, and the identification of alternate sources of neural stem cells has broad clinical potential. We isolated mesechymal-like stem cells from human adipose tissues (AT-MSCs), and studied on transdifferentiation-promoting conditions in neural cells. Dopaminergic and cholinergic neuron induction of AT-MSCs was also studied. Neural differentiation was induced by adding bFGF, EGF, dimethyl sulphoxide (DMSO) and butylated hydroxyanisole(BHA) in N2 Medium and N2 supplement. The immunoreactive cells for $\beta$-tubulin III, a neuron-specific marker, GFAP, an astrocyte marker, or Gal-C, an oligodendrocyte marker, were found. AT-MSCs treated with bFGF, SHH and FGF8 were differentiatied into dopaminergic neurons that were immunopositive for TH antibody. Differentiation of MSCs to cholinergic neurons was induced by combined treatment with basic fibroblast growth factor (bFGF), retinoic acid (RA) and sonic hedgehog (Shh). AT-MSCs treated with DMSO and BHA rapidly assumed the morphology of multipolar neurons. Both immunocytochemistry and RT-PCR analysis indicated that the expression of a number of neural markers including neuro D1, $\beta$-tubulin III, GFAP and nestinwas markedly elevated during this acute differentiation. While the stem cell markers such as SCF, C-kit, and Stat-3 were not expressed after preinduction medium culture, we confirmed the differentiation of dopaminergic and cholinergic neurons by TH/$\beta$-tubulin III or ChAT/ $\beta$-tubulin III positive cells. Conclusively, AT-MSCs can be differentiated into dopaminergic and cholinergic neuronsand these findings suggest that AT-MSCs are alternative cell source of treatment for neurodegenerative diseases.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.154-166
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• 2009

Database query and reporting tools, OLAP tools and data mining tools are typical front-end tools in Business Intelligence environment which is able to support gathering, consolidating and analyzing data produced from business operation activities and provide access to the result to enterprise's users. Traditional reporting tools have an advantage of creating sophisticated dynamic reports including SQL query result sets, which look like documents produced by word processors, and publishing the reports to the Web environment, but data source for the tools is limited to RDBMS. On the other hand, OLAP tools and data mining tools have an advantage of providing powerful information analysis functions on each own way, but built-in visualization components for analysis results are limited to tables or some charts. Thus, this paper presents a system that integrates three typical front-end tools to complement one another for BI environment. Traditional reporting tools only have a query editor for generating SQL statements to bring data from RDBMS. However, the reporting tool presented by this paper can extract data also from OLAP and data mining servers, because editors for OLAP and data mining query requests are added into this tool. Traditional systems produce all documents in the server side. This structure enables reporting tools to avoid repetitive process to generate documents, when many clients intend to access the same dynamic document. But, because this system targets that a few users generate documents for data analysis, this tool generates documents at the client side. Therefore, the tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the report viewer in the client side. Also, this reporting tool has data structure for integrating data from three kinds of data sources into one document. Finally, most of traditional front-end tools for BI are dependent on data source architecture from specific vendor. To overcome the problem, this system uses XMLA that is a protocol based on web service to access to data sources for OLAP and data mining services from various vendors.

• Korean Journal of Agricultural Science
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• v.5 no.2
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• pp.136-144
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• 1978

A series of experiments over three years was planned for practical application of rhizobia in farms and grass lands in Korea. This is the report for the studies of the first year mainly on the isolation and characterization of rhizobial strains, and on the assessment of their nodulation abilities and nitrogen fixation capacities. 1. Total number of 88 strains for soybean group and 22 st ra ins for pea and vetch group was isolated from nodules which were taken from legumes grown in Daekwanyong, Cheju and various places in Korea. 2. Morphological and cultural characteristics of the strains were studied, and attempts were also made to investigate their antigenic properties and to demonstrate lysogenic strains in these groups. The results were : i) the isolates varied in cultural characteristics on yeast mannitol broth and agar, and in degree of congo reel absorption ; ii) similarities in their antigenic properties were found between/among the strains: G-3/G-9/D216, G-20/G-52 in soybean group; iii) no lysogeny was found in the strains of these groups. 3. Plant infection tests by test tube and bottle method in light room were carried out to elucidate the ability of the strains to nodulate specific legumes and of the capacity of such nodules to fix atmospheric nitrogen. The isolates were grouped into non- invasive, ineffective, or effective to the legumes. Those strains which produced effective nodules, supporting similar level of growth as nitrate control, were: P-3, 4 and 8 in pea and vetch group; G-23, 27, and, D-216 in soybean group.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.4
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• pp.723-729
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• 2004

To develop foods using dried persimmon, hot-water extracts of dried persimmons were added into strong wheat flour in the ratio of 10, 20, 30, and 40% and the quality characteristics of baked products were investigated. The proximate compositions of dried persimmons hot-water extracts were 70.37% of moisture, 1.72% of crude protein, 0.18% of crude lipids, 1.99% of crude ash and 4.37% of crude fiber, respectively. With increasing the addition of dried persimmons hot-water extracts, moisture content of the added breads was increased to 47.20% from 41.12% of non-added bread and water activity to 0.576 from 0.495. Water binding capacity of the added dried persimmons hot-water extracts rasied weight of the bread but decreased specific volume. In the hunter's color values the more dried persimmons hot-water extracts was added, the lower L vaules we, and the higher a and b values we. In the texture property, the addition of dried persimmons hot-water extracts increased hardness, gumminess and chewiness, while decreased adhesiveness and fracturability. Judging from texture, taste and overall acceptability of the product, recommended substitution level for hot-water extracts of dried persimmons in bread was 30% or less.

• Journal of the Korean Electrochemical Society
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• v.19 no.3
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• pp.80-86
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• 2016

High Ni content layered oxide materials for the positive electrode in lithium-ion batteries have high specific capacity. However, their poor electrochemical and thermal stability at elevated temperature restrict the practical use. A small amount of $Al_2O_3$ was added to the mixture of transition metal hydroxide and lithium hydroxide. The $LiNi_{0.6}Co_{0.2}Mn_{0.2}O_2$ was simultaneously doped and coated with $Al_2O_3$ during heat-treatment. Electrochemical characteristics of modified $LiNi_{0.6}Co_{0.2}Mn_{0.2}O_2$ were evaluated by the galvanostatic cycling and the LSTA(linear sweep thermmametry) at the constant voltage conditions. The nano-sized $Al_2O_3$ added materials show better cycle performance at elevated temperature than that of micro-sized $Al_2O_3$. As the added amount of nano-$Al_2O_3$ increased, the thermal stability of electrode also enhanced, but the use of 2.5 mol% Al showed the best high temperature performance.

• Journal of Environmental Impact Assessment
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• v.29 no.2
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• pp.79-92
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• 2020

This study aimed at analyzing the current status and further needs of ecological information which is provided with the civil servants in the process of climate change adaptation planning in ecosystem sector and at providing suggestions for future development of ecological knowledge on climate change. Therefore, we conducted a questionary survey titled as "the knowledge-base and information needs for climate change adaptation in ecosystem sector" with the civil servants who are engaged with adaptation practices in the ecology related divisions in 17 regional local governments (RLG) and the affiliated basic local governments (BLG) in Korea. As a result, the characteristics of ecological information which is applied in public practices was analyzed and strategies for improved utilization was suggested. 75% of the respondents (RLG 85% and BLG 72%) were aware of the relativeness between the existence and utilization of ecological information and the execution of climate adaptation practices in ecosystem sector. They were agreed with the necessity of ecological information not only in adaptation practices but also overall affairs in the ecological related division in the local government (RLG 82% and BLG 72%). The current situation of utilizing ecological information which is produced from central orlocal government to civil affairs were only represented as 64 persons (28%) in RLG and 42 persons (18%) in BLG. One of the major obstacles that the respondents confront with when applying ecological information to public practices was deficit of prior knowledge on the ecological information itself, such as awareness of the characteristics of ecological information and the link with public affairs for adaptation plans. Therefore, delivering current knowledge and ecological information on climate change by educational and promotional method is an urgent priority to the civil servant. The future needs on ecological information for local government servants were deduced as basic information on local ecosystem and applied knowledge on local development to meet the biodiversity conservation and ecosystem services at the same time. The respondents expected not only the specific guidelines for using ecological information to apply on the adaptation plans in the relevant divisions of the local governments but also the institution where the usage activation of ecological information would be operated and managed to enhance the information utilizing structure in the local government. In the nation-wide, the capacity of local governments should be enhanced with adaptation knowledge and the application of appropriate information to the public practices by central government's aiding with the better quality of information, its public promotion, and the applicability to civil affairs.