• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.6
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• pp.1-19
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• 2013

This study tries to review 'Sakuteiki(作庭記)', the Book of Garden Making, compiled at the end of the 11th Century during the Heian Period of Japan, from the East-Asian perspective. 'Sakuteiki' is a Garden Theory Book, the oldest in the world as well as in Asia, and it contains the traditional knowledge of Japanese ancient garden culture, which originated from the continent(Korea and China). Traditional knowledge related to East-Asian garden culture reviewed in this paper is "Fungsu Theory"(風水, Asian traditional ecology: Fengshui in Chinese; Fusui in Japanese), stemmed from the culture to seek sound and blessed places to live in. Viewed from modern landscape architecture, the Fungsu Theory corresponds to ecology(science). The Fungsu Theory was established around the Han Dynasty of China together with the Yinyangwuxing(陰陽五行) Theory and widely used for making human residences including gardens. It was transmitted to Japan via Korea as well as through direct transaction between Japan and China. This study reinterprets garden design principles represented in Sakuteiki, which were selected in 5 key words according to the Fungsu Theory. The 5 key words for the Fungsu Theory are "the place in harmony of four guardian gods(四神相應地)", "planting trees in the four cardinal directions", "flow of Chi(氣)", "curved line and asymmetry", and "mountain is the king, water is the people". Garden design principles of "the place in harmony of four guardian gods(四神相應地)" and "planting trees in the four cardinal directions" are corresponding to "Myeongdang-ron(明堂論, Theory of propitious site)". The place in harmony of four guardian gods mentioned in Sakuteiki is a landform surrounded by the flow of water to the east, the great path to the west, the pond to the south, and the hill to the north. And the Theory originated from Zhaijing(宅經, Classic of dwelling Sites) of China. According to this principle, the city was planned and as a miniature model, the residence of the aristocrat during the Heian period was made. At the residence the location of the garden surrounded by the four gods(the flow of water, the great path, the pond, and the hill) is the Myeongdang(明堂, the propitious site: Mingtang in Chinese; Meido in Japanese). Sakuteiki explains how to substitute for the four gods by planting trees in the four cardinal directions when they were not given by nature. This way of planting originated from Zhaijing(宅經) and also goes back to Qiminyaoshu (齊民要術), compiled in the 6th Century of China. In this way of planting, the number of trees suggested in Sakuteiki is related to Hetu(河圖) and Luoshu(洛書), which are iconography of Yi(易), the philosophy of change, in ancient China. Such way of planting corresponds to that of Yongdoseo(龍圖墅, the villa based on the principle of Hetu) presented in Sanrimgyeongje (山林經濟), an encyclopedia on agriculture and living in the 17th Century of Korea. And garden design principles of "the flow of Chi(氣)", "curved line and asymmetry" is connected to "Saenggi Theory(生氣論, Theory of vitality)". Sakuteiki explains the right flow of Chi(氣) through the proper flow and the reverse flow of the garden stream and also suggests the curved line of the garden stream, asymmetric arrangement of bridges and stones in the garden, and indented shape of pond edges, which are ways of accumulating Chi(氣) and therefore lead to "Saenggi Theory" of the Fungsu Theory. The last design principle, "mountain is the king, water is the people", is related to "Hyeongguk Theory(形局論, Theory of form)" of the Fungsu Theory. Sakuteiki explains the meaning of garden through a metaphor, which views mountain as king, water as the people, and stones as king's retainers. It compares the situation in which the king governs the people with the help of his retainers to the ecological phenomena in which mountain(earth) controls water with the help of stones. This principle befits "Hyeongguk Theory(形局論, Theory of form)" of the Fungsu Theory which explains landform on the analogy of social systems, people, animals and things. As above, major garden design principles represented in Sakuteiki can be interpreted in the context of the Fungsu Theory, the traditional knowledge system in East Asia. Therefore, we can find the significance of Sakuteiki in that the wisdom of ancient garden culture in East-Asia was integrated in it, although it described the knowhow of a specific garden style in a specific period of Japan.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.221-238
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• 2019

Recently, companies and public institutions have been actively introducing chatbot services in the field of customer counseling and response. The introduction of the chatbot service not only brings labor cost savings to companies and organizations, but also enables rapid communication with customers. Advances in data analytics and artificial intelligence are driving the growth of these chatbot services. The current chatbot can understand users' questions and offer the most appropriate answers to questions through machine learning and deep learning. The advancement of chatbot core technologies such as NLP, NLU, and NLG has made it possible to understand words, understand paragraphs, understand meanings, and understand emotions. For this reason, the value of chatbots continues to rise. However, technology-oriented chatbots can be inconsistent with what users want inherently, so chatbots need to be addressed in the area of the user experience, not just in the area of technology. The Fourth Industrial Revolution represents the importance of the User Experience as well as the advancement of artificial intelligence, big data, cloud, and IoT technologies. The development of IT technology and the importance of user experience have provided people with a variety of environments and changed lifestyles. This means that experiences in interactions with people, services(products) and the environment become very important. Therefore, it is time to develop a user needs-based services(products) that can provide new experiences and values to people. This study proposes a chatbot development process based on user needs by applying the design thinking approach, a representative methodology in the field of user experience, to chatbot development. The process proposed in this study consists of four steps. The first step is 'setting up knowledge domain' to set up the chatbot's expertise. Accumulating the information corresponding to the configured domain and deriving the insight is the second step, 'Knowledge accumulation and Insight identification'. The third step is 'Opportunity Development and Prototyping'. It is going to start full-scale development at this stage. Finally, the 'User Feedback' step is to receive feedback from users on the developed prototype. This creates a "user needs-based service (product)" that meets the process's objectives. Beginning with the fact gathering through user observation, Perform the process of abstraction to derive insights and explore opportunities. Next, it is expected to develop a chatbot that meets the user's needs through the process of materializing to structure the desired information and providing the function that fits the user's mental model. In this study, we present the actual construction examples for the domestic cosmetics market to confirm the effectiveness of the proposed process. The reason why it chose the domestic cosmetics market as its case is because it shows strong characteristics of users' experiences, so it can quickly understand responses from users. This study has a theoretical implication in that it proposed a new chatbot development process by incorporating the design thinking methodology into the chatbot development process. This research is different from the existing chatbot development research in that it focuses on user experience, not technology. It also has practical implications in that companies or institutions propose realistic methods that can be applied immediately. In particular, the process proposed in this study can be accessed and utilized by anyone, since 'user needs-based chatbots' can be developed even if they are not experts. This study suggests that further studies are needed because only one field of study was conducted. In addition to the cosmetics market, additional research should be conducted in various fields in which the user experience appears, such as the smart phone and the automotive market. Through this, it will be able to be reborn as a general process necessary for 'development of chatbots centered on user experience, not technology centered'.

• Journal of Life Science
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• v.29 no.8
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• pp.861-870
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• 2019

This study was undertaken to establish optimum medium compositions for cost-effective mannitol production by Leuconostoc mesenteroides SRCM201425 isolated from kimchi. L. mesenteroides SRCM21425 from kimchi was selected for efficient mannitol production based on fructose analysis and identified by its 16S rRNA gene sequence, as well as by carbohydrate fermentation pattern analysis. To enhance mannitol production by L. mesenteroides SRCM201425, the effects of carbon, nitrogen, and mineral sources on mannitol production were first determined using Plackett-Burman design (PBD). The effects of 11 variables on mannitol production were investigated of which three variables, fructose, sucrose, and peptone, were selected. In the second step, each concentration of fructose, sucrose, and peptone was optimized using a central composite design (CCD) and response surface analysis. The predicted concentrations of fructose, sucrose, and peptone were 38.68 g/l, 30 g/l, and 39.67 g/l, respectively. The mathematical response model was reliable, with a coefficient of determination of $R^2=0.9185$. Mannitol production increased 20-fold as compared with the MRS medium, corresponding to a mannitol yield 97.46% when compared to MRS supplemented with 100 g/l of fructose in flask system. Furthermore, the production in the optimized medium was cost-effective. The findings of this study can be expected to be useful in biological production for catalytic hydrogenation causing byproduct and additional production costs.

• The Journal of Korean Academy of Prosthodontics
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• v.61 no.1
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• pp.1-17
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• 2023

Purpose. The purpose of this study was to examine the correlation between the finish line designs and the marginal adaptation of nonprecious metal alloy coping produced by different digital manufacturing methods. Materials and methods. Nonprecious metal alloy copings were made respectively from each master model with three different methods; SLS, milling and casting by computer aided design and computer aided manufacturing (CAD-CAM). Twelve copings were made by each method resulting in 72 copings in total. The measurement was conducted at 40 determined reference points along the circumferential margin with the confocal laser scanning microscope at magnification ×150. Results. Mean values of marginal gap of laser sintered copings were 11.8 ± 7.4 ㎛ for deep chamfer margin and 6.3 ± 3.5 ㎛ for rounded shoulder margin and the difference between them was statistically significant (P < .0001). Mean values of marginal gap of casted copings were 18.8 ± 20.2 ㎛ for deep chamfer margin and 33 ± 20.5 ㎛ for rounded shoulder margin and the difference between them was significant (P = .0004). Conclusion. Within the limitation of this study, the following conclusions were drawn. 1. The variation of finish line design influences the marginal adaptation of laser sintered metal coping and casted metal coping. 2. Laser sintered copings with rounded shoulder margin had better marginal fit than deep chamfer margin. 3. Casted copings with deep chamfer margin had better marginal fit than rounded shoulder margin. 4. According to the manufacturing method, SLS system showed the best marginal fit among three different methods. Casting and milling method followed that in order.

• Journal of Korea Port Economic Association
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• v.36 no.2
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• pp.63-86
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• 2020

The tax lease scheme for ships is an advanced ship financing tool that generates tax benefits through accelerated depreciation of capital allowances and transferring them to the ship operator (leasee) via reductions in rental payments. The scheme was introduced by Japan in 1978 and by France in 1998 to support their shipping and shipbuilding industries. The size of tax benefits varies by country depending on the depreciation rate for ships, corporate tax rate, and the tax system on profits from the sale of ship. This study uses a virtual model of the Korean tax lease scheme for ships based on the French tax lease scheme. The size of tax benefits is calculated and compared to those in the French and Japanese tax lease schemes. According to the analysis, the size of the tax benefit was approximately 19% for France, 14% for Japan, and 12% for Korea. This is differentiated by the country's depreciation rate and corporate tax rate, which have the greatest impact on the size of tax benefits. For the Korean virtual model, if the tax benefits are distributed by the operator and the investor at the rate of 75:25, the operator is expected to enjoy tax benefits equivalent to about 9% of the ship price and the investor to enjoy 3%. Despite limited information and data regarding the tax lease scheme for ships, this study was the first attempt in Korea to design a virtual model of the Korean tax lease scheme based on some predictable assumptions. Therefore, a group of shipping, financing, and legal experts will follow up on more professional and practical reviews of the model in the near future. Hence, this study will serve as a small contribution to the early introduction of the Korean tax lease scheme for ships.

• Asia pacific journal of information systems
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• v.21 no.1
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• pp.81-101
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• 2011

In today's rapidly changing and increasingly competitive business environment, new product development in tune with market trends in a timely manner has been a matter of the utmost concern for all enterprises. Indeed, developing a sustainable new business has been a top priority for not only business enterprises, but also for the government policy makers accountable for the health of Its national economy as well as for decision makers in what type of organizations. Further, for a soft landing of new businesses, building a government-initiated industry base has been claimed to be necessary as a way to effectively boost corporate activities. However, the existing methodology in new service and new product development is not suitable for nurturing industry, because it is mainly focused on the research and development of corporate business activities instead of new product development. The approach for developing new business is based on 'innovation' and 'convergence.' Yet, the convergence among technologies, supplies, businesses and industries is believed to be more effective than innovation alone as a way to gain momentum. Therefore, it has become more important than ever to study a new methodology based on convergence in industrial quality new product development (NPD) and new service development (NDS). In this research, therefore, we reviewed any restrictions in the existing new product and new service development methodology and the existing business model development methodology. In doing so, we conducted industry standard collaboration analysis on a new service model development methodology in the private sector and the public sector. This approach is fundamentally different from the existing one in that ours focuses on new business development under private management. The suggested framework can be categorized into industry level and service level. First, in the industry level, we define new business opportunities In occurrence of convergence between businesses. For this, we analyze the existing industry at the industry level to identify the opportunities in a market and its business attractiveness, based on which the convergence industry is formulated. Also, through the analysis of environment and market opportunity at the industry level. we can trace how different industries are lined to one another so as to extend the result of the study to develop better insights into industry expansion and new industry emergence. After then, in the service level, we elicit the service for the defined new business, which is composed of private service and supporting service for nurturing industry. Private service includes 3steps: plan-design-do; supporting service for nurturing industry has 4 steps: selection-make environment- business preparation-do and see. The existing methodology focuses on mainly securing business competitiveness, building a business model for success, and offering new services based on the core competence of companies. This suggested methodology, on other hand, suggests the necessity of service development, when new business opportunities arise, in relation to the opportunity analysis of supporting service based on the clear understanding of new business supporting infrastructure optimization. Meanwhile, we have performed case studies on the printing and publishing field with the restrict procedure and development system to assure the feasibility and practical application. Even though the printing and publishing industry is considered a typical knowledge convergence industry, it is also known as a low-demand and low-value industry in Korea. For this reason, we apply the new methodology and suggest the direction and the possibility of how the printing and publishing industry can be transformed as a core dynamic force for new growth. Then, we suggest the base composition service for industry promotion(public) and business opportunities for private's profitability(private).

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.2 s.314
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• pp.37-46
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• 2007

In this paper, we propose technologies for enhancing the immersive realization of virtual objects in AR-based product design. Generally, multimodal senses such as visual/auditory/tactile feedback are well known as a method for enhancing the immersion in case of interaction with virtual objects. By adapting tangible objects we can provide touch sensation to users. A 3D model of the same scale overlays the whole area of the tangible object so the marker area is invisible. This contributes to enhancing immersion. Also, the hand occlusion problem when the virtual objects overlay the user's hands is partially solved, providing more immersive and natural images to users. Finally, multimodal feedback also creates better immersion. In our work, both vibrotactile feedback through page motors, pneumatic tactile feedback, and sound feedback are considered. In our scenario, a game-phone model is selected, by way of proposed augmented vibrotactile feedback, hands occlusion-reduced visual effects and sound feedback are provided to users. These proposed methodologies will contribute to a better immersive realization of the conventional AR system.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.103-119
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• 2023

Since the Korean government has decided to apply the policy of BIM (Building Information Modeling) to the entire construction industry, it has experienced a positive trend in adoption and utilization. BIM can reduce workloads by building model objects into libraries that conform to standards and enable consistent quality, data integrity, and compatibility. In the domestic architecture, civil engineering, and the overseas landscape architecture sectors, many BIM library standardization studies have been conducted, and guidelines have been established based on them. Currently, basic research and attempts to introduce BIM are being made in Korean landscape architecture field, but the diffusion has been delayed due to difficulties in application. This can be addressed by enhancing the efficiency of BIM work using standardized libraries. Therefore, this study aims to provide a starting point for discussions and present a classification system for objects and attribute information that can be referred to when creating landscape libraries in practice. The standardization of landscape BIM library was explored from two directions: object classification and attribute information items. First, the Korean construction information classification system, product inventory classification system, landscape design and construction standards, and BIM object classification of the NLA (Norwegian Association of Landscape Architects) were referred to classify landscape objects. As a result, the objects were divided into 12 subcategories, including 'trees', 'shrubs', 'ground cover and others', 'outdoor installation', 'outdoor lighting facility', 'stairs and ramp', 'outdoor wall', 'outdoor structure', 'pavement', 'curb', 'irrigation', and 'drainage' under five major categories: 'landscape plant', 'landscape facility', 'landscape structure', 'landscape pavement', and 'irrigation and drainage'. Next, the attribute information for the objects was extracted and structured. To do this, the common attribute information items of the KBIMS (Korean BIM Standard) were included, and the object attribute information items that vary according to the type of objects were included by referring to the PDT (Product Data Template) of the LI (UK Landscape Institute). As a result, the common attributes included information on 'identification', 'distribution', 'classification', and 'manufacture and supply' information, while the object attributes included information on 'naming', 'specifications', 'installation or construction', 'performance', 'sustainability', and 'operations and maintenance'. The significance of this study lies in establishing the foundation for the introduction of landscape BIM through the standardization of library objects, which will enhance the efficiency of modeling tasks and improve the data consistency of BIM models across various disciplines in the construction industry.