• Journal of the Korean Wood Science and Technology
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• v.48 no.6
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• pp.791-806
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• 2020

In this study, a block shear strength test was conducted to compare and analyze the strength and failure mode on the glued laminated timber, CLT, and Ply-lam CLT, which are mainly used for the construction of wood construction as engineering wood. Through this, the Ply-lam CLT manufacturing conditions for optimum production, such as the type of lamina, plywood, adhesive, and layer composition, were investigated. The results are as follow. Through block shear strength test, it showed high strength in the order of glued laminated timber, Ply-lam CLT and CLT. In particular, the shear strength of Ply-lam CLT, which is made of a composite structure of larch plywood and larch lamina, passed 7.1 N/㎟, which is a Korean industrial standards for block shear strength of structural glued laminated timber. In addition, in this study, there was no different in shear strength according to the adhesive type used for glulam, CLT, and Ply-lam CLT adhesion. However, in the case of Ply-lam CLT, the difference in shear strength of Ply-lam CLT was shown according to the type of lamina and plywood. The results showed high strength in the order of Larix kaempferi > Mixed light hardwood ≒ Pinus densiflora, sieb, et, Zucc plywood. The optimal configuration of Ply-lam CLT is when larch plywood and larch lamina are used, and it is decided that the adhesive can be used by selecting PRF and PUR according to the application. The results of block shear strength failure mode by type of wood based materials were analyzed. The failure mode showed shear parallel-to-grain for glulam, rolling shear for CLT, and shear parallel-to-grain and rolling for ply-lam CLT. This is closely related to shear strength results and is decided to indicate higher shear strength in Ply-lam CLT than in CLT due to rolling shear.

• The Korean Journal of Mycology
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• v.32 no.1
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• pp.31-38
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• 2004

An endophytic bacterial strain EB215 that was isolated from cucumber (Cucumis sativus) roots displayed a potent in vivo antifungal activity against Colletotrichum species. The strain was identified as Burkholderia cepacia based on its physiological and biochemical characteristics, and 16S rDNA gene sequence. Optimal medium and incubation period for the production of antifungal substances by B. cepacia EB215 were nutrient broth (NB) and 3 days, respectively. An antifungal substance was isolated from the NB cultures of B. cepacia EB215 strain by centrifugation, n-hexane partitioning, silica gel column chromatography, preparative TLC, and in vitro bioassay. Its chemical structure was determined to be pyrrolnitrin by mass and NMR spectral analyses. Pyrrolnitrin showed potent disease control efficacy of more than 90% against pepper anthracnose (Colletotrichum coccodes), cucumber anthracnose (Colletotrichum orbiculare), rice blast (Magnaporthe grisea) and rice sheath blight (Corticium sasaki) even at a low concentration of $11.1\;{\mu}g/ml$. In addition, it effectively controlled the development of tomato gray mold (Botrytis cinerea) and wheat leaf rust (Puccinia recondita) at concentrations over $33.3\;{\mu}g/ml$. However, it had no antifungal activity against Phytophthora infestans on tomato plants. Further studies on the development of microbial fungicide using B. cepacia EB215 are in progress.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• 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 the korean academy of Pediatric Dentistry
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• v.35 no.3
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• pp.437-445
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• 2008

The presence of a "prismless" layer on the enamel surface particularly on deciduous teeth has been reported by a number of workers. This structure, which appears to lack the normal prism delineations, could interfere with tag formation and hence, reduce bonding to such surfaces. The purpose of this study was to investigate the relationship of etching times on the effect of acid etching on primary enamel with respect to the quality of etching patterns. Labial surfaces of 32 extracted or exfoliated caries-free primary anterior teeth were used. 35% phosphoric acid gel was used only cervical regions of labial surfaces for each etching time group, 15, 30, 45 and 60 seconds. The surfaces were then washed with water for 20 seconds and dried with air spray for 20 seconds. 1. The Type 3 is 75% when the 15 seconds acid etching time was used. 2. The Type 1 is 38% and Type 2 is 75% when the 30 and 45 seconds acid etching time was used. 3. The Type 1 is 25% and Type 2 is 75% when the 60 seconds acid etching time was used. 4. An etching time of 60 seconds produced a constant and regular etching pattern. 5. There is a significant difference between the groups with respect to the patterns of etch achieved(p<0.05). 6. We confirmed that the acid induced patterns(type 1, 2) became more pronounced when the application time increased(p<0.05). $45{\sim}60$ seconds was the optimal time for etching on the primary enamel.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.109-117
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• 2011

The exhibition industry, as technology-intensive, eco-friendly industry, contributes to regional and national development and enhancement of its image as well, if it joins cultural and tourist industry. Therefore, We need to revitalize the exhibition industry, as actively holding an exhibition event. However, to attract a number of exhibition audience, the work of enhancing audience satisfaction and awareness of value for participation should be prioritized after improving quality of service within exhibition hall. As one way to enhance the quality of service, it is thought that the way providing personalized service geared toward each audience is needed. that is, if audience avoids the complexity in exhibition space and it affords them service to enable effective time and space management, it will improve the satisfaction. All such personalized service affordable lets the audience's preference on the basis of each audience profile registered in advance online grasp. and Based on this information, it is provided with exhibition-related information suited their purpose that is the booth for the interesting audience, the shortest path to go to the booth and event via audience's smart phone. and it collects audience's reaction information, such as visiting the booth, participating the event through offered the information in this way and location information for the flow of movement, the present position so that it makes revision of existing each audience profile. After correcting the information, it extracts the individual's preference. hereunder, it provides recommend booth and event information. in other words, it provides optimal information for individual by amendment based on reaction information about recommending information built on basic profile. It provides personalized service dynamic and interactive with audience. This paper will be able to provide the most suitable information for each audience through circular and interactive structure and designed smart-phone application supportable for updating dynamic and interactive personalized service that is able to afford surrounding information in real time, as locating movement position through sensing. The proposed application collects user‘s context information and carrys information gathering function collecting the reaction about searched or provided information via sensing. and it also carrys information gathering function providing needed data for user in exhibition hall. In other words, it offers information about recommend booth of position foundation for user, location-based services of recommend booth and involves service providing detailed information for inside exhibition by using service of augmented reality, the map of whole exhibition as well. and it is also provided with SNS service that is able to keep information exchange besides intimacy. To provide this service, application is consisted of several module. first of all, it includes UNS identity module for sensing, and contain sensor information gathering module handling and collecting the perceived information through this module. Sensor information gathered like this transmits the information gathering server. and there is exhibition information interfacing with user and this module transmits to interesting information collection module through user's reaction besides interface. Interesting information collection module transmits collected information and If valid information out of the information gathering server that brings together sensing information and interesting information is sent to recommend server, the recommend server makes recommend information through inference with gathered valid information. If this server transmit by exhibition information process, exhibition information process module is provided with user by interface. Through this system it raises the dynamic, intelligent personalized service for user.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.9
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• pp.1320-1324
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• 2005

Soybean (Glycine max L.) is an increasingly important food source and functional food. Platelet aggregation plays an important role in thrombogenesis and atherosclerosis. Here, we studied the anti-platelet aggregating effects of solvent extracts from Korean soybean varieties and isoflauone derivatives. Nine Korean soybean varieties were extracted by solvents (methanol and buthanol and their extracts was investigated for the inhibition against tile aggregation of washed rabbit platelets induced by collagen or thrombin. Maximal inhibition of buthanol extracts against platelet aggregation induced by collagen was $95\%$ in Black-kong and Jinpum - kong. The potency of their inhibition was in the following order : Black > Jinpum > Bokwang > Hwangkum > Pureun > Malli > Danbaek > Danyeob > Jangsu - kong. The Black - kong only seemed to produce the maximal inhibition against platelet aggregation induced by thrombin. Total isoflavone content measured was Jinpum-kong ($1347.8{\mu}g/g$) and Black-kong ($918.7{\mu}g/g$). Maximal inhibition of isoflavone derivatives against platelet aggregation induced by collagen was $97\%$ in genistein. The potency of their inhibition was in the following order: genistein>daidzein>genistin. The isoflavone derivatives did not affect the platelet aggregation induced by thrombin. However, Black-kong cortex seemed to Produce the optimal inhibition against platelet aggregation induced by collagen. These results suggest that Black-kong and Jinpum-kong may be a good source for antiplatelet agents, and their antiplatelet effect be related to tile content and the chemical structure with the number of -OH group and the attached glycoside in the isoflavone derivative.

• Journal of Korea Spatial Information System Society
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• v.7 no.3 s.15
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• pp.67-81
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• 2005

Recently, the interest and research on the development of new application services such as the Location Based Service and Telemetics providing the emergency service, neighbor information search, and route search according to the development of the Geographic Information System have been increasing. User's search in the spatio-temporal database which is used in the field of Location Based Service or Telemetics usually fixes the current time on the time axis and queries the spatial and aspatial attributes. Thus, if the range of query on the time axis is extensive, it is difficult to efficiently deal with the search operation. For solving this problem, the snapshot, a method to summarize the location data of moving objects, was introduced. However, if the range to store data is wide, more space for storing data is required. And, the snapshot is created even for unnecessary space that is not frequently used for search. Thus, non storage space and memory are generally used in the snapshot method. Therefore, in this paper, we suggests the Hash-based Spatio-Temporal Clustering Algorithm(H-STCA) that extends the two-dimensional spatial hash algorithm used for the spatial clustering in the past to the three-dimensional spatial hash algorithm for overcoming the disadvantages of the snapshot method. And, this paper also suggests the knowledge extraction algorithm to extract the knowledge for the path search of moving objects from the past location data based on the suggested H-STCA algorithm. Moreover, as the results of the performance evaluation, the snapshot clustering method using H-STCA, in the search time, storage structure construction time, optimal path search time, related to the huge amount of moving object data demonstrated the higher performance than the spatio-temporal index methods and the original snapshot method. Especially, for the snapshot clustering method using H-STCA, the more the number of moving objects was increased, the more the performance was improved, as compared to the existing spatio-temporal index methods and the original snapshot method.

• Research in Plant Disease
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• v.11 no.2
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• pp.128-134
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• 2005

This study was conducted to elucidate effect of environmental factors on the development of white rot. In order to identify the causal agents causing white rot of Allium crops, we compared DNA profiles of a representative isolate, Sclerotium cepivorum, introduced from foreign country with Korean isolates using UP-PCR. As a result, Sclerotium isolates forming round-shaped sclerotia were identified as Sclerotium cepivorum pertaining in UP-PCR b group and Sclerotium isolates farming anamorphic-shaped sclerotia presumed to be a novel species of Sclerotium based on DNA profiles of UP-PCR. There was a big difference in DNA band pattern between two species of Sclerotium isolated in Korea. Electron micrographs of scanning electron microscope and transmission electron microscope showed morphological differences in sclerotial surface structure and rind layers between two species of Sclerotium. There were more wrinkles and pore spaces on sclerotial surface of Sclerotium sp. forming anamorphic-shaped sclerotia than that of Sclerotium cepivorum forming round-shaped sclerotia. Both of two white rot pathogens grew well at the temperature range of $10-25^{\circ}C$ with optimal temperature of $20^{\circ}C$. Sclerotia of the two pathogens were well formed at $20^{\circ}C$ and well germinated at the temperature range of $20-24^{\circ}C$, Effect of pre-incubation of sclerotia on destruction of sclerotial dormancy of two pathogens was evaluated through storing sclerotia under different temperature condition. The sclerotia of the two pathogens showed an increased capacity to germinate on potato dextroise agar when the sclerotia were incubated for 7 days at $10^{\circ}C$ after pre-treatment at $35^{\circ}C$ for 7 days. At that time, germination rate of Sclerotium sp. and 5. cepivorum was $100\%\;and\;70\%$, respectively. Flooding period and treatment temperature had an effect on sclerotial survival rate of the two pathogens. As flooding period and treatment temperature increased, sclerotial germination rate of the two pathogens decreased. It was confirmed that soil humidity played an important role on development of white rot. It was the highest disease incidence of garlic white rot when garlic were sown at potted soils infested with the two pathogens and adjusted soil humidity to $15\%$ (field moisture capacity, about -300 mb). As soil humidity increase or decrease based on $15\%$ of soil humidity, disease incidence decreased move and more.

• Korean Journal of Weed Science
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• v.15 no.1
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• pp.85-98
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• 1995

Six malformin B's produced by Aspergillus niger van Tiegh. were separated by HPLC. Their structures determined by the methods of amino acid analyses, mass spectrometry, and two-dimensional NMR were revealed as cyclic pentapeptides structurally related to malformin $A_1$. Both the NMR and MS/MS data suggest that the respective structures of separated malformin B's were as follows; cyclo-D-Cys-D-Cys-L-Val-D-Leu-L-allo-Ile for $B_{1a}$, cyclo-D-Cys-D-Cys-L-Val-D-Leu-L-Leu for $B_{1b}$, cyclo-D-Cys-D-Cys-L-Val-D-Val-L-Leu for $B_2$, cyclo-D-Cys-D-Cys-L-Val-D-Ile-L-Leu for $B_3$, cyclo-D-Cys-D-Cys-L-Val-D-Ile-L-Ile for $B_4$, and cyclo-D-Cys-D-Cys-L-Val-D-Val-L-Ile for $B_5$. Among the malformin B's, the structure of $B_{1b}$ was the same as that of malformin $A_3$ or C. All the malformin B's showed physiological activities in the two assay systems using corn(Zea mays L.) roots and mung bean(Phaseolus aureus Roxb.) hypercotyl segments. The malformin B's with molecular weight 529 were more effective for inducing corn root curvature than those with molecular weight 515. The difference in molecular weight of malformin B's, i.e., the retention time on HPLC, results in the polarity change of the whole malformin molecule which affects the revealation of the malformin activities. In addition, the disulfide form of the malformin B's gives the rigidity of the molecule, whereas the combination of the fourth and the fifth amino acid residues provides the optimal three-dimensional configuration to the malformin receptor of plants. Presumably, these two factors are appeared to be essential for the greatest physiological activity of malformin B's. malformin $B_{1a}$ caused the corn root curvature by 90% at a concentration of $0.25{\mu}M$. However, such differential activities with molecular weight of 529 or 515 of malformin B's were not found in the mung bean hypercotyl segment test. Maximum stimulation of mung bean hypercotyl growth was observed at $0.1{\mu}M$ concentration of malformin B's. The growth of the segments treated with $B_5$ was 154% greater than that of the control.