• Korean Journal of Heritage: History & Science
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• v.45 no.1
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• pp.148-173
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• 2012

The rear garden in Donggwol Palace which shared with the Changdeok Palace and the Changgyeong Palace is the salient places of technology and idea reflected the phases of the times of the Joseon Dynasty, so it is certainly one of the best Korean garden cultures. The rear garden in Donggwol which was not only the secret garden for the rest of royal family but also used as symbolic places for the various ceremonies and training its human resources has been considerably destroyed through the period of Japanese colonial rule. Thus the rear garden areas at north of Changkyung Palace were entirely transformed and a few territory from Juhabru(宙合樓) to Ongnyucheon(玉流川) keep up its surviving as the rear garden. The area of Jondeokjeong(尊德亭) which become subject on this studies from among these was constructed as flower garden after development of Ongnyucheon. The areas of Simchujeong(深秋亭), Cheoknoedang(滌惱堂), Pyemwoosa(?愚?), Mangchunjeong(望春亭), Chunhyagak(天香閣), Chungsimjeong(淸心亭) around Jondeokjeong, were situated among the beautiful scenery with the flowers and ponds. But there are only Jondeokjeong and Pyemwoosa at this moment, and the other pavilions was destroyed and transformed. For these reasons, in this studies, the formative purposes were investigated through analysing water elements, planting, ornaments and so on. According to these reasons, historical records and realities of garden construction of five pavilions : Simchujeong, Mangchunjeong, Cheoknoedang, Chunhyagak, Chungyeongak(淸燕閣) were considered to give authenticity to the restoration and reorganization as well as to accumulate basic knowledge about the conservation of environment surrounded garden architectures. These pavilions appeared at Gunggwolgi(宮闕志) and Joseonwangzosilok(朝鮮王朝實), but their names were not appeared at Donggwoldo(東闕圖). So they were ascertained through all of literatures on Donggwol Palace. Cheoknoedang and Simchujeong among these buildings could be found out as the existed buildings and the uncertain building at the northwest of Jondeokjeong was estimated as the name to Chunhyagak or Mangchunjeong. And the hypothesis that the wall surrounding Taichungmoon(太淸門) should be belong to Chungyeongak was supported. In addition, the area which did not known in connection with name and use on northeast at the Changdeok Palace, and had regarded as an impasses in the studies of Donggwoldo and the rear garden in Donggwol Palace, but the historical records of using by Yeonsangun(燕山君) and Sukjong(肅宗) were discovered at this study. And it could be uncovered that the obscure spatial space was a separate house only for king and he enjoyed play there unnoticing to others belong to palace.

• Science of Emotion and Sensibility
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• v.22 no.1
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• pp.23-34
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• 2019

The U-Healthcare era has evolved with the development of the Internet of things (IoT) in the early stages of being connected as a society. Already, many changes such as increased well-being and the extension of human life are becoming evident across cultures. Korea entered the growing group of aging societies in 2017, and its silver industry is expected to grow rapidly by adopting the IoT of a super-connected society. In particular, the senior shift phenomenon has resulted in increased interest in the promotion of the health and well-being of the emergent silver generation which, unlike the existing silver generation, is highly active and wields great economic power. This study conducted in-depth interviews to investigate the characteristics of the new silver generation, and to develop the design for a wearable serious game that intends to boost the interest of the elderly in exercise and fitness activities according to their personalized physical training regimes as prescribed by the U-Hospital service. The usage scenario of this wearable serious game for the 'U-silver generation' is derived from social necessity. Medical professionals can utilize this technology to conduct health examinations and to monitor the rehabilitation of senior patients. The elderly can also use this tool to request checkups or to interface with their healthcare providers. The wearable serious game is further aimed at mitigating concerns about the deterioration of the physical functions of the silver generation by applying personalized exercise prescriptions. The present investigation revealed that it is necessary to merge the on / off line community activities to meet the silver generation's daily needs for connection and friendship. Further, the sustainability of the serious game must be enhanced through the inculcation of a sense of accomplishment as a player rises through the levels of the game. The proposed wearable serious game is designed specifically for the silver generation that is inexperienced in using digital devices: simple game rules are applied to a familiar interface grounded on the gourmet travels preferred by the target players to increase usability.

• Korean Journal of Ecology and Environment
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• v.52 no.3
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• pp.210-220
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• 2019

Population growth and the increase of energy consumption due to civilization caused global warming. Temperature on the Earth rose about $0.7^{\circ}C$ for the last 100 years, the rate is accelerated since 2000. Temperature is a factor, which determines physiological action, growth and development, survival, etc. of the plant together with light intensity and precipitation. Therefore, it is expected that global warming would affect broadly geographic distribution of the plant as well as structure and function ecosystem. In order to understand the effect of global warming on the ecosystem, a study about the effect of temperature rise on germination and growth in the plant is required necessarily. This study was carried out to investigate the effects of experimental warming on the germination and growth of two oak species(Quercus mongolica and Q. serrata) in temperature gradient chamber(TGC). This study was conducted in control, medium warming treatment($+1.7^{\circ}C$; Tm), and high warming treatment ($+3.2^{\circ}C$; Th) conditions. The final germination percentage, mean germination time and germination rate of two oak species increased by the warming treatment, and the increase in Q. serrata was higher than that in Q. mongolica. Root collar diameter, seedling height, leaf dry weight, stem dry weight, root dry weight, and total biomass were the highest in Tm treatment. Butthey were not significantly different in the Th treatment. In the Th treatment, Q. serrata had significantly higher H/D ratio, S/R ratio, and low root mass ratio (RMR) compared with control plot. Q. mongolica had lower RMR and higher S/R ratio in the Tm and Th treatments compared with control plot. Therefore, growth of Q. mongolica are expected to be more vulnerable to warming than that of Q. serrata. The main findings of this study, species-specific responses to experimental warming, could be applied to predict ecosystem changes from global warming. From the result of this study, we could deduce that temperature rise would increase germination of Q. serrata and Q. mongolica and consequently contribute to increase establishment rate in the early growth stage of the plants. But we have to consider diverse variables to understand properly the effects that global warming influences germination in natural condition. Treatment of global warming in the medium level increased the growth and the biomass of both Q. serrata and Q. mongolica. But the result of treatment in the high level showed different aspects. In particular, Q. mongolica, which grows in cooler zones of higher elevation on mountains or northward in latitude, responded more sensitively. Synthesized the results mentioned above, continuous global warming would function in stable establishment of both plants unfavorably. Compared the responses of both sample plants on temperature rise, Q. serrata increased germination rate more than Q. mongolica and Q. mongolica responded more sensitively than Q. serrata in biomass allocation with the increase of temperature. It was estimated that these results would due to a difference of microclimate originated from the spatial distribution of both plants.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of Life Science
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• v.29 no.5
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• pp.537-544
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• 2019

Genome editing technology employing gene scissors has generated interest in molecular breeding in various fields, and the development of the third-generation gene scissors of the clustered, regularly interspaced short palindromic repeat (CRISPR) system has accelerated the field of molecular breeding through genome editing. In this study, we analyzed the possibility of silkworm molecular breeding using gene scissors by genomic and phenotypic analysis after editing the biogenesis of lysosome-related organelles (BmBLOS) gene of Bakokjam using the CRISPR/Cas9 system. Three types of guide RNAs (gRNA) were synthesized based on the BmBLOS gene sequence of Bakokjam. Complexes of the prepared gRNA and Cas9 protein were formed and introduced into Bombyx mori BM-N cells by electroporation. Analysis of the gene editing efficiency by T7 endonuclease I analysis revealed that the B4N gRNA showed the best efficiency. The silkworm genome was edited by microinjecting the Cas9/B4N gRNA complex into silkworm early embryos and raising the silkworms after hatching. The hatching rate was as low as 18%, but the incidence of mutation was over 40%. In addition, phenotypic changes were observed in about 70% of the G0 generation silkworms. Sequence analysis showed that the BmBLOS gene appeared to be a heterozygote carrying the wild-type and mutation in most individuals, and the genotype of the BmBLOS gene was also different in all individuals. These results suggest that although the possibility of silkworm molecular breeding using the CRISPR/Cas9 system would be very high, continued research on breeding and screening methods will be necessary to improve gene editing efficiency and to obtain homozygotes.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.292-299
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• 2018

In a survey in which farmers were asked about their levels of satisfaction with agricultural machines, Japanese products scored higher than local products by 1.2, 1.3, and 1.4 times for tractors, combine harvesters, and rice transplanter, respectively. Japanese products corresponded to generally high satisfaction levels in terms of operating performance, operability, frequency of breakdowns, and durability, excluding sales price and after-sales services. Effective countermeasures through quality improvement are therefore necessary for Korean products. Furthermore, a survey of dealers showed that the components and consumables for core agricultural machines had high frequencies of breakdowns and repairs. Four major components of tractors represented 85.3% of all breakdowns and repairs, five components of combine harvesters represented 89.6%, and three components of rice transplanters represented 80.5%. Moreover, a comparison of the technological levels between local and imported machines showed that the local machines' levels were at 60-100% for tractors, 70-100% for combine harvesters, and 70-95% for rice transplanters. Small and mid-sized tractors, 4 interrow combine harvesters, and 6 interrow rice transplanters showed similar levels of technology. The results of the analysis suggest that action is urgently needed at a policy level to establish an agricultural machinery component research center for the development, production, and supply of commonly-used components, with the participation of manufacturers of agricultural machines and components, in order to enhance the competitiveness of local manufacturers and to revitalize the agricultural machine market.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.157-173
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• 2021

With the development of information technology, the amount of available information increases daily. However, having access to so much information makes it difficult for users to easily find the information they seek. Users want a visualized system that reduces information retrieval and learning time, saving them from personally reading and judging all available information. As a result, recommendation systems are an increasingly important technologies that are essential to the business. Collaborative filtering is used in various fields with excellent performance because recommendations are made based on similar user interests and preferences. However, limitations do exist. Sparsity occurs when user-item preference information is insufficient, and is the main limitation of collaborative filtering. The evaluation value of the user item matrix may be distorted by the data depending on the popularity of the product, or there may be new users who have not yet evaluated the value. The lack of historical data to identify consumer preferences is referred to as data sparsity, and various methods have been studied to address these problems. However, most attempts to solve the sparsity problem are not optimal because they can only be applied when additional data such as users' personal information, social networks, or characteristics of items are included. Another problem is that real-world score data are mostly biased to high scores, resulting in severe imbalances. One cause of this imbalance distribution is the purchasing bias, in which only users with high product ratings purchase products, so those with low ratings are less likely to purchase products and thus do not leave negative product reviews. Due to these characteristics, unlike most users' actual preferences, reviews by users who purchase products are more likely to be positive. Therefore, the actual rating data is over-learned in many classes with high incidence due to its biased characteristics, distorting the market. Applying collaborative filtering to these imbalanced data leads to poor recommendation performance due to excessive learning of biased classes. Traditional oversampling techniques to address this problem are likely to cause overfitting because they repeat the same data, which acts as noise in learning, reducing recommendation performance. In addition, pre-processing methods for most existing data imbalance problems are designed and used for binary classes. Binary class imbalance techniques are difficult to apply to multi-class problems because they cannot model multi-class problems, such as objects at cross-class boundaries or objects overlapping multiple classes. To solve this problem, research has been conducted to convert and apply multi-class problems to binary class problems. However, simplification of multi-class problems can cause potential classification errors when combined with the results of classifiers learned from other sub-problems, resulting in loss of important information about relationships beyond the selected items. Therefore, it is necessary to develop more effective methods to address multi-class imbalance problems. We propose a collaborative filtering model using CGAN to generate realistic virtual data to populate the empty user-item matrix. Conditional vector y identify distributions for minority classes and generate data reflecting their characteristics. Collaborative filtering then maximizes the performance of the recommendation system via hyperparameter tuning. This process should improve the accuracy of the model by addressing the sparsity problem of collaborative filtering implementations while mitigating data imbalances arising from real data. Our model has superior recommendation performance over existing oversampling techniques and existing real-world data with data sparsity. SMOTE, Borderline SMOTE, SVM-SMOTE, ADASYN, and GAN were used as comparative models and we demonstrate the highest prediction accuracy on the RMSE and MAE evaluation scales. Through this study, oversampling based on deep learning will be able to further refine the performance of recommendation systems using actual data and be used to build business recommendation systems.

• Journal of Korean Society of Forest Science
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• v.109 no.4
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• pp.477-483
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• 2020

We constructed a stand yield table for Chamaecyparis obtusa based on data from an actual forest. The previous stand yield table had a number of disadvantages because it was based on actual forest information. In the present study we used data from more than 200 sampling plots in a stand of Chamaecyparis obtusa. The analysis included theestimation, recovery and prediction of the distribution of values for diameter at breast height (DBH), and the result is a valuable process for the preparation ofstand yield tables. The DBH distribution model uses a Weibull function, and the site index (base age: 30 years), the standard for assessing forest productivity, was derived using the Chapman-Richards formula. Several estimation formulas for the preparation of the stand yield table were considered for the fitness index, and the optimal formula was chosen. The analysis shows that the site index is in the range of 10 to 18 in the Chamaecyparis obtusa stand. The estimated stand volume of each sample plot was found to have an accuracy of 62%. According to the residuals analysis, the stands showed even distribution around zero, which indicates that the results are useful in the field. Comparing the table constructed in this study to the existing stand yield table, we found that our table yielded comparatively higher values for growth. This is probably because the existing analysis data used a small amount of research data that did not properly reflect. We hope that the stand yield table of Chamaecyparis obtusa, a representative species of southern regions, will be widely used for forest management. As these forests stabilize and growth progresses, we plan to construct an additional yield table applicable to the production of developed stands.

• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• Korean Chemical Engineering Research
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• v.59 no.1
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• pp.127-137
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• 2021

Air emission charge for nitrogen oxide as a precursor of fine dust has been introduced and implemented within the country from 2020. Therefore, the development of economical combustion technology for NOx reduction has got more needed urgently. This study investigated the air-staging effect as a way to reduce the NOx during combustion of domestic unused forest biomass, recently possible to secure REC (Renewable Energy Certification) as a substitute for overseas wood pellets in a 0.1 MWth circulating fluidized bed combustion test-rig. Operating conditions were comparison with and without air-staging, the supply position of tertiary air (6.4 m, 8.1 m, 9.4 m in the combustor) and variation of air-staging ratio (Primary air:Secondary air:Tertiary air=91%:9%:0%, 82%:9%:9%, 73%:9%:18%). NO and CO concentrations in flue gas, profiles of temperature and pressure at the height of the combustion, unburned carbon in sampled fly ash and combustion efficiency on operating conditions were evaluated. As notable results, NO concentration with air-staging application under tertiary air supply at 9.4 m in the combustor reduced 100.7 ppm compared to 148.8 ppm without air-staging while, CO concentration increased from 52.2 ppm without air-staging to 99.8 ppm with air-staging. However, among air-staging runs, when tertiary air supply amount at 6.4 m in the combustor increased by air-staging ratio (Primary air:Secondary air:Tertiary air=73%:9%:18%), NO and CO concentrations decreased the lowest 90.8 ppm and 66.1 ppm, respectively. Furthermore, combustion efficiency at this condition was improved to 99.3%, higher than that (98.3%) of run without air-staging.