• Korean Journal of Heritage: History & Science
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• v.53 no.4
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• pp.136-149
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• 2020

It is generally believed that Douglas Fir timber imported from North America is used in repair work for Korean wooden heritage sites due to an insufficient supply of extra-large sized Korean pine timber. Based on this understanding in the cultural heritage repair field, Cultural Heritage Repair Business Entities ("CHRBE") prefer North American Douglas Fir timber which is more easily acquired on the market than large Korean pine timber. However, if CHRBE use large quantities of foreign-origin wood in the heritage repair field, this presents the threat of negative domestic impacts on cultural heritage such as breaching the preservation principal and ultimately weakening material authenticity. Therefore, this study aims to investigate the current supply status of large Korean pine timber through examination of existing research, interviews with experts engaged in CHRBE, and timber mills. With this information, the authors seek to identify whether the market supply of large Korean pine timber is indeed insufficient or not. In addition to this, this paper identifies the reasons why large Korean pine timber is not widely used if such timber supply is actually sufficient. In order to propose suggestions regarding the issues above, the authors study the distribution channel for large Korean pine timber and the price spectrum of this timber through examination of price information from the public agencies under the Korea Forest Service, research papers from the Cultural Heritage Administration, and estimation documents from timber mills. This paper also identifies two main opinions about why Korean timber has not been commonly used in the Korean heritage repair field. The first opinion is that the supply of large Korean pine timber really is insufficient in Korea. However, the second opinion is that it is hardly used due to inappropriateness of the government's procurement and estimation system, despite the fact that the supply of the timbers on the market is actually sufficient. Through the aforementioned research, this paper comes to the conclusion that the second opinion has strong grounds in many aspects. In terms of suggestions, alternative routes are proposed to stimulate the use of large Korean pine timber via supply by the 'Korea Foundation for Traditional Architecture and Technology' and surveys of the price spectrum of the timber, etc.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.515-529
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• 2020

Constructed wetlands undergo biological and physical changes such as an increase in the proportion of arid plants due to the natural succession process after formation. It can adversely affect not only the purification function but also the habitat of species. As such, this study aims to identify environmental factors affecting biodiversity and propose management plans based on the monitoring results of physical environmental changes and the emergence of species in seven constructed wetlands selected based on the water depth and surrounding conditions among the lands purchased by the Nakdong River basin. We examined the environmental conditions and emergence of the Odonata, which is a wetland-dependent species, to predict the trend of changes in biodiversity and abundance. The results showed that the open water area decreased as the emergent plants spread to the deep water in 2015 compared to 2012 when they were initially restored to a depth of 0.2 to 1 m. While a total of 54 dragonfly species were observed, the habitat diversity, such as vegetation, water surface, and grassland, remained similar to the initial formation of the wetlands despite the expansion of the emergent plants. On the other hand, the number of Agrionidae species, which prefer areas with fewer aquatic plants, decreased between 2012 and 2015 due to the diminished water surface. The p-values of the differences in the number of species and population between wetlands by year were 2.568e-09 and 1.162e-08, respectively, indicating the statistically significant differences. The decrease in open water surface was found to have the greatest effect on the biodiversity and habitat density of dragonflies. The time-series survey of constructed wetlands confirmed that the spread of Phragmites communis, P. japonica, Typha orientalis, etc., caused a decrease in species diversity. It suggests that environmental management to maintain the open water surface area is necessary.

• Journal of the Korea Institute of Building Construction
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• v.22 no.5
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• pp.473-483
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• 2022

BIM(Building Information Modeling) is a technology that can manage information throughout the entire life cycle of the construction industry and serves as a platform for improving productivity and integrating the entire construction industry. Currently, BIM is actively applied in developed countries, and its use at various overseas construction sites is increasing This is unclear. due to air shortening and budget savings. However, there is still a lack of institutional basis and technical limitations in the domestic construction sector, which have led to the lack of utilization of BIM. Various activation measures and institutional frameworks will need to be established for the early establishment of these productive BIMs in Korea. Therefore, as part of the research for the domestic settlement and revitalization of BIM, this study derived a number of key factors necessary for the development of the construction industry through brainstorming and expert surveys using AHP techniques and analyzed the relative importance of each factor. In addition, prior surveys by a group of experts resulted in 1, 3 items in level, 2, 9 items in level, and 3, 27 items in level, and priorities analysis was performed through pairwise comparisons. As a result of the AHP analysis, it was found that the relative importance weight of policy aspects was highest in level 1, and the policy factors in level 2 and the cost-based and incentive system introduction factors were considered most important in level 3. These findings show that the importance of the policy guidance or institutions underlying the activation of BIM rather than research and development or corporate innovation is relatively high, and that the preparation of policy plans by public institutions should be the first priority. Therefore, it is considered that the development of a policy system or guideline must be prioritized before it can be advanced to the next activation stage. The use of BIM technologies will not only contribute to improving the productivity of the construction industry, but also to the overall development of the industry and the growth of the construction industry. It is expected that the results of this study can provide as useful information when establishing policies for activating BIM in central government, relevant local governments, and related public institutions.

• Korea Science and Art Forum
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• v.19
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• pp.293-305
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• 2015

At the same time the unique cultural traits of each country are valued, it has become an essential element to establish the cultural identity of a country. This study is aimed at comparing the residence architectural cultures in East-Asia and thus identifying Korea's own unique traits by determining the application characteristics of traditional architectures of Korea, China and Japan through practical investigation of materials, a basic element of architectural shaping. Literature survey and field study were conducted in parallel for this study, and architectural buildings under investigation included Mucheomdang House in Korea, Prince Gong Mansion in China and Dokyudo Building in Japan. Construction materials in Korea, China and Japan include natural materials such as wood, stone and clay, and artificial materials such as metals, paper, roof tiles, plug and glass. and the buildings were constructed with the combination of these materials. This commonality can be often found in the architectural composition. However, in the interior composition, the choice and application of different materials were clear between three countries, which were shown to be different depending on climates, processing methods and living culture of each country. First of all, since each country selected materials under the influence of its own vegetation and climates, living environment of each country could be seen via its residence. Also, it could be seen that while Korea and Japan show a certain similarity such as the traits of standing-sitting culture and the finish of paper in the interior, China is clearly different. In particular, regarding the material processing, the artificial processing was minimized in Korea, which mainly gave rough and crude feelings while due to the use of straight timbers, the architectural representation with organized and refined feelings was made in Japan. China showed the highest percentage of artificial processing of materials among three countries, which was highly associated with the coloring culture of China. Also, it could be seen that technology related to fine architectural materials such as bricks and glass was greatly advanced in China. Thus, how immaterial elements such as natural characteristics, functionality and aesthetics were applied in relation to residence in Korea, Japan and China could be determined through the comparison of architectural materials.

• Research in Plant Disease
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• v.30 no.2
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• pp.103-113
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• 2024

Since 2009, the Korean Society of Plant Pathology has established the Committee on Common Names of Plant Disease to systematically review and determine plant disease names and related terminologies. The committee published the 6th edition of the List of Plant Diseases in Korea (LPDK) in 2022, and the list has been made publicly accessible online. The online database has significantly enhanced user accessibility, expedited update processes, and improved interoperability with other databases. As a result, the 6.1 edition of the list was released by online LPDK in 2023, detailing new disease names added over the preceding year and revisions to existing names. Subsequently, in 2024, the 6.2 edition was published, encompassing 6,765 diseases caused by 2,503 pathogen taxa across 1,432 host species. The public release of the online database has, however, introduced several challenges and tasks. Addressing these issues necessitates the development of modern, standardized nomenclature guidelines and a robust system for the registration of new disease names. Open communication and collaboration among the diverse members of the Korean Society of Plant Pathology are required to ensure the reliability of the LPDK.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.4
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• pp.225-232
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• 2024

This study focuses on the determination of the fracture mode in composite laminates using deep learning. With the increase in the use of laminated composites in numerous engineering applications, the insurance of their integrity and performance is of paramount importance. However, owing to the complex nature of these materials, the identification of fracture modes is often a tedious and time-consuming task that requires critical domain knowledge. Therefore, to alleviate these issues, this study aims to utilize modern artificial intelligence technology to automate the fractographic analysis of laminated composites. To accomplish this goal, scanning electron microscopy (SEM) images of fractured tensile test specimens are obtained from laminated composites to showcase various fracture modes. These SEM images are then categorized based on numerous fracture modes, including fiber breakage, fiber pull-out, mix-mode fracture, matrix brittle fracture, and matrix ductile fracture. Next, the collective data for all classes are divided into train, test, and validation datasets. Two state-of-the-art, deep learning-based pre-trained models, namely, DenseNet and GoogleNet, are trained to learn the discriminative features for each fracture mode. The DenseNet models shows training and testing accuracies of 94.01% and 75.49%, respectively, whereas those of the GoogleNet model are 84.55% and 54.48%, respectively. The trained deep learning models are then validated on unseen validation datasets. This validation demonstrates that the DenseNet model, owing to its deeper architecture, can extract high-quality features, resulting in 84.44% validation accuracy. This value is 36.84% higher than that of the GoogleNet model. Hence, these results affirm that the DenseNet model is effective in performing fractographic analyses of laminated composites by predicting fracture modes with high precision.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Wetlands Research
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• v.25 no.1
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• pp.35-47
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• 2023

Korean facility horticulture and hydroponic cultivation methods increase, requiring the management of waste water generated. In this study, the amount of fertilizer contained in the discharged waste liquid was determined. By evaluating this as a price, it was suggested to reduce water treatment costs and recycle fertilizer components. It was evaluated based on the results of major water quality analysis of waste liquid by crop, such as tomatoes, paprika, cucumbers, and strawberries, and in the case of P component, it was analyzed by converting it to the amount of phosphoric acid (P₂O₅). The amount of nitrogen (N) can be calculated by discharging 1,145.90kg·ha^-1 of tomatoes, 920.43kg·ha^-1 of paprika, 804.16kg·ha^-1 of cucumbers, 405.83kg·ha^-1 of strawberries, and the fertilizer content of P₂O₅ is 830.65kg·ha^-1 of paprika, 622.32kg·ha^-1 of tomatoes, 477.67kg·ha^-1 of cucumbers. In addition, trace elements such as potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), and manganese (Mn) were also analyzed to be emitted. The price per kg of each item calculated by averaging the price of fertilizer sold on the market can be evaluated as KRW, N 860.7, P 2,378.2, K 2,121.7, Ca 981.2, Mg 1,036.3, Fe 126,076.9, Mn 62,322.1, Zn 15,825.0, Cu 31,362.0, B 4,238.0, Mo 149,041.7. The annual fertilizer loss amount for each crop was calculated by comprehensively considering the price per kg calculated based on the market price of fertilizer, the concentration of waste by crop analyzed earlier, and the average annual emission of hydroponic cultivation. As a result of the analysis, the average of the four hydroponic crops was 5,475,361.1 won in fertilizer ingredients, with tomatoes valued at 6,995,622.3 won, paprika valued at 7,384,923.8 won, cucumbers valued at 5,091,607.9 won, and strawberries valued at 2,429,290.6 won. It was expected that if hydroponic drainage is managed through self-treatment or threshing before discharge rather than by leaking it into a river and treating it as a pollutant, it can be a valuable reusable fertilizer ingredient along with reducing water treatment costs.