• Clinical and Experimental Pediatrics
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• v.53 no.3
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• pp.364-372
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• 2010

Purpose : Good adherence of caregivers is essential for successful health outcomes in the treatment of childhood asthma. The purpose of this study was to identify the factors contributing to good adherence of maintenance treatment in children with well-controlled asthma. Methods : Children with well-controlled asthma being treated with a daily controller for at least 3 months in Korea University Anam Hospital were selected. Their caregivers who had good adherence to maintenance treatment were recruited. Qualitative study through in-depth interviews was conducted with 18 caregivers who agreed to the study. Results : The 18 caregivers (mean age, 40.0 years) consisted of 15 mothers, 2 grandmothers, and 1 father. The resulting consensus were identified and grouped into 2 domains: the caregiver/patient aspect with 8 theme factors and the treatment aspect with 4 theme factors. The main theme factors in the caregiver/patient aspect were enabling participation in physical activities and exercise (77.8%), perceptions regarding asthma and the need for long-term treatment (50.0%), and perceived value of the medications outweighing the risk of side effects (38.9%). The main theme factors in the treatment aspect were trust in the physician (77.8%), general satisfaction with the manner and attitude of the physician (77.8%) and verification of the necessity of further treatment by performing tests (38.9%). Conclusion : Efforts to improve caregivers' adherence to the treatment of childhood asthma must include a range of factors related to both caregiver/patient aspects and treatment aspects. Among all of these factors, it may be most important to establish a physician-caregiver partnership.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.149-162
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• 2014

Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.175-185
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• 2020

Three-dimensional registration is a process of matching data with or without a coordinate system to a reference coordinate system, which is used in various fields such as the absolute orientation of photogrammetry and data combining for producing precise road maps. Three-dimensional registration is divided into a method using points and a method using linear features. In the case of using points, it is difficult to find the same conjugate point when having different spatial resolutions. On the other hand, the use of linear feature has the advantage that the three-dimensional registration is possible by using not only the case where the spatial resolution is different but also the conjugate linear feature that is not the same starting point and ending point in point cloud type data. In this study, we proposed a method to determine the scale and the three-dimensional translation after determining the three-dimensional rotation angle between two data using quaternion to perform three-dimensional registration using linear features. For the verification of the proposed method, three-dimensional registration was performed using the linear features constructed an indoor and the linear features acquired through the terrestrial mobile mapping system in an outdoor environment. The experimental results showed that the mean square root error was 0.001054m and 0.000936m, respectively, when the scale was fixed and if not fixed, using indoor data. The results of the three-dimensional transformation in the 500m section using outdoor data showed that the mean square root error was 0.09412m when the six linear features were used, and the accuracy for producing precision maps was satisfied. In addition, in the experiment where the number of linear features was changed, it was found that nine linear features were sufficient for high-precision 3D transformation through almost no change in the root mean square error even when nine linear features or more linear features were used.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.3
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• pp.226-234
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• 2020

As the average life expectancy of human beings is extended in addition to the entry of the aging society, there is a tendency for the interest in the appearance of men and women in modern society to increase. The most external judgment of human aging is the wrinkles on the facial skin. People are undergoing various procedures to have clean, wrinkled, and resilient healthy skin. Many thread lifting procedures are being implemented because they tend to want simple and effective procedures during the procedure. In this study, in order to improve lifting effect in thread lifting, animal experiments were conducted to confirm the improvement of wrinkles by injecting RF high frequency and CO₂ gas into existing PDO suture procedures. The experimental groups consisted of natural aging groups, PDO treatment groups, groups with RF high frequency in PDO procedures, groups with CO₂ gas injected into PDO procedures, and groups with CO₂ gas and RF injected simultaneously into PDO procedures. The individuals in the natural aging group had an average wrinkle depth of 0.408mm before the procedure, and the average wrinkle depth of the 10th week was 0.68mm. The depth of wrinkles in the PDO treatment group averaged 0.384mm before the procedure, and 0.348mm on the 10th week after the procedure. The average crease depth of pre-procedure objects injected with RF high frequency in PDO was 0.42mm, and the average crease depth for 10 weeks was 0.378mm. The average crease depth of the CO₂ gas injected into the PDO was 0.4mm before the procedure, and the average crease depth was reduced to 0.332mm in the 10th week after the procedure. On average, the number of objects injected with CO₂ gas and RF high frequency in the PDO procedure decreased to 0.412mm before and 0.338mm in the 10th week after the procedure. The procedure of injecting CO₂ gas and RF into the PDO suture showed the highest reduction rate of 17.96%.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.899-915
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• 2018

In this study, in order to construct an eco-friendly advanced road transportation network, the multi-layer tunnel, which is a small-sized car road, is designed to have a height of less than 60 cm. However, the shape of the tunnel is low and the height of the traffic sign is small. In order to solve these problems, traffic sign characters were designed in three dimensions, and the possibility of applying the design of the three - dimensional sign that can obtain greater visibility than the existing signs at the same distance and the possibility verification through virtual simulation were performed. The three-dimensional sign is horizontally installed on the ceiling of the multi-layer tunnel. To be seen vertically, it is enlarged by a certain ratio by the perspective, and the width and height are enlarged. Respectively. In addition, 3D simulation was performed to verify the visibility of the stereoscopic signs when the driver ran through the stereoscopic sign design specifications. As a result of the design and experimental study, it was confirmed that the stereoscopic sign could be designed through the theoretical formula and that it could provide the driver with a larger traffic sign character because there is no limitation of the facility limit compared to the existing vertical traffic sign. Also, we confirmed that it can be implemented in the side wall by using the stereoscopic sign design principle installed on the ceiling part. It was confirmed that the design of the stereoscopic sign can be designed to be smaller as the distance that the driver visually recognizes the sperm is shorter, the height of the protrusion vertically at the lower part of the stereoscopic sign becomes higher. As a result of 3D simulation running experiment based on the design information of the stereoscopic sign, it was confirmed that the stereoscopic sign is visually the same as the vertical sign at the planned distance. Although the detailed research and institutional improvement of stereoscopic signs have not been made in Korea and abroad, it is evolved into a core technology of new road traffic facilities through various studies through the possibility of designing and applying stereoscopic signs developed through this study Expect.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.44-62
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• 2024

The development of online funeral services and social issues of eco-friendly funeral culture have raised awareness of the new need for online funeral culture. There have been several attempts to revitalize online funeral services in domestic institutions and companies, but the effect is weak. The purpose of this study is to propose a design that can improve the accessibility and usability of online memorial services by analyzing the usability problem factors through a First Time User Experience analysis of the online memorial platform. Therefore, in this study, in order to identify the problem factors of the online memorial platform, a literature review on the UX, OOBE, and FTUE theories was conducted. The subject of the study was the app 'Memorial'. Before analyzing the First-Time User-Experience, IA was compared and analyzed with other similar services to understand the characteristics of the UX service of the app 'Memorial', which is the subject of the study. In addition, tasks corresponding to the Unpack-Setup/Configure-First Use stage were performed on 10 subjects who had no experience using the online memorial platform. The experimental process was expressed as the UX Curve to identify factors that caused negative experiences. As a result, the major problem factors included unnecessary UI elements, the need for sensitive personal information at the membership stage, and lack of immersion in the service. The improvements included strengthening community functions to facilitate the sharing of emotions and promote smooth communication between users. We proposed UI/UX service developments that enhanced the app by incorporating these insights. In order to verify the effectiveness, serviceability, and value of the developed prototype, an interview with a expert was conducted. The interviewes consisted of three service design experts. This study was conducted to contribute to the quality improvement and activation of the recently emerging online funeral services. The study is significant as it aims to understand the current status of these services and identify the factors necessary to improve service accessibility and usability. Subsequent studies require in-depth user verification of how much the proposed improvement plan affects the actual user experience.

• Journal of Korean Home Economics Education Association
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• v.28 no.3
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• pp.47-63
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• 2016

The purpose of this study is to suggest the basic information for diverse and balanced research and development in this field with understanding research trends related to safety education in home economics. In order to so, this study makes population and sampling by targeting cases which refer to 'safety' on 15 papers of academic journals related to home economics registered in the National Research Foundation from 2001 to 2015, 244 papers related to safety education area and 179 master doctorate thesis by searching keyword as 'safety'. Analysis contents are research trends of papers related to safety education by year and by subject and research trends of safety education by area and by research method. As a result of the study, first, the number of research papers related to safety education by year on home economics curriculum repeated increase and decrease and there have been consistent studies conducted on safety education with 14-52 papers per every year and yearly average 28.2 papers. On the other hand, the most number of studies conducted in 2015 with 52 papers which are twice as much of 26 papers in 2014. This seems to be affected by the announcement of safety comprehensive countermeasures from government and the emphasis of safety subject on 2015 curriculum revision of the Ministry of Education. Second, with regards to research trends by topic, 137 papers are related to safety education (29%), 336 papers are related to safety actual condition (71%). Accidents and recognition had a greater percentage in a paper before 2009 (74.4%) and studies are increased after 2009 (from 21 papers to 53 papers) in terms of development or evaluation of safety education program, development of education materials, development of education method etc. Subject area dealt with the most on the research of safety actual condition is regarding safety accidents or effective variables (23.2%). Subject regarding the variables are researches related to factors influencing family violence, internet addiction, spouse violence, willingness to purchase unsafe food, age harassment, or suicidal attempt etc. Next, researches related to safety recognition (13.9%), safety knowledge and attitude (7.4%), safety behaviors (6.3%), safety consciousness (2.3%) show in sequence. Subject area dealt with the most on the researches regarding safety education is development and evaluation of safety education program (11%) and this appears the most in 2015 by year (21.5%). Third, with regards to eight areas of safety education, there are 143 papers regarding public safety (33.8%), 106 papers regarding violence and personal safety (25.1%), 93 papers regarding general subject on safety or whole safety area (22%) and 58 papers regarding drug and internet addiction (13.7%) in sequence. And there is no paper related to first aid and 1 paper is related to occupational safety (0.2%). Occupational safety area is less researched nevertheless its included in home economic curriculum as relative chapter. First aid does not directly correlate with home economics curriculum but should be studied in preparation for accident which could happen in practical class. Forth, with regards to research trends by research method, quantitative research (89.1%) is mostly used and both research study (70.4%) and experimental research (18.7%) are used the most frequently. In particular, researches on the actual condition of safety education and experimental studies for effectiveness verification take most of research method. As qualitative studies, there are phenomenological study (3.1%) and case study (3.1%) related to actual conditions of safety accidents. 10 papers (2.4%) are mixture of quantitative and qualitative research and some research conducted research study and experimental research at the same time (0.9%). With regards to subject of study, human environments (87.5%) are more than physical environments (12.5) and students (48.4%) are more than teachers and school parents (20.6%). As the subject of physical environments, school (6.5%) is the most but home environment is none. As a result of the study, research for the development of evaluation tool for evaluating safety education, occupational safety and lifelong education should be conducted from this time forward. In addition, the object of study shall be expanded to both human environments in terms of entire life and physical environments for home. An in-depth qualitative research should be needed by observing and meeting with each student.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.141-173
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• 2007

The study examines how the environmental factors of store influence service brand personality and repurchase intention in the service environment. The service industry has been experiencing the intensified competition with the industry's continuous growth and the influence from rapid technological advancement. Under the circumstances, it has become ever more important for the brand competitiveness to be distinctively recognized against competition. A brand needs to be distinguished and differentiated from competing companies because they are all engaged in the similar environment of the service industry. The differentiation of brand achievement has become increasingly important to highlight certain brand functions to include emotional, self-expressive, and symbolic functions since the importance of such functions has been further emphasized in promoting consumption activities. That is the recent role of brand personality that has been emphasized in the service industry. In other words, customers now freely and actively express their personalities or egos in consumption activities, taking an important role in construction of a brand asset. Hence, the study suggests that it is necessary to disperse the recognition and acknowledgement that the maintenance of the existing customers contributes more to boost repurchase intention when it is compared to the efforts to create new customers, particularly in the service industry. Meanwhile, the store itself can offer a unique environment that may influence the consumer's purchase decision. Consumers interact with store environments in the process of,virtually, all household purchase they make (Sarel 1981). Thus, store environments may encourage customers to purchase. The roles that store environments play are to provide informational cues to customers about the store and goods and communicate messages to stimulate consumers' emotions. The store environments differentiate the store from competing stores and build a unique service brand personality. However, the existing studies related to brand in the service industry mostly concentrated on the relationship between the quality of service and customer satisfaction, and they are mostly generalized while the connective studies focused on brand personality. Such approaches show limitations and are insufficient to investigate on the relationship between store environment and brand personality in the service industry. Accordingly, the study intends to identify the level of contribution to the establishment of brand personality made by the store's physical environments that influence on the specific brand characteristics depending on the type of service. The study also intends to identify what kind of relationships with brand personality exists with brand personality while being influenced by store environments. In addition, the study intends to make meaningful suggestions to better direct marketing efforts by identifying whether a brand personality makes a positive influence to induce an intention for repurchase. For this study, the service industry is classified into four categories based on to the characteristics of service: experimental-emotional service, emotional -credible service, credible-functional service, and functional-experimental service. The type of business with the most frequent customer contact is determined for each service type and the enterprise with the highest brand value in each service sector based on the report made by the Korea Management Association. They are designated as the representative of each category. The selected representatives are a fast-food store (experimental-emotional service), a cinema house (emotional-credible service), a bank (credible-functional service), and discount store (functional-experimental service). The survey was conducted for the four selected brands to represent each service category among consumers who are experienced users of the designated stores in Seoul Metropolitan City and Gyeonggi province via written questionnaires in order to verify the suggested assumptions in the study. In particular, the survey adopted 15 scales, which represent each characteristic factor, among the 42 unique characteristics developed by Jennifer Aaker(1997) to assess the brand personality of each service brand. SPSS for Windows Release 12.0 and LISREL were used in the analysis of data verification. The methodology of the structural equation model was used for the study and the pivotal findings are as follows. 1) The environmental factors ware classified as design factors, ambient factors, and social factors. Therefore, the validity of measurement scale of Baker et al. (1994) was proved. 2) The service brand personalities were subdivided as sincerity, excitement, competence, sophistication, and ruggedness, which makes the use of the brand personality scales by Jennifer Aaker(1997) appropriate in the service industry as well. 3) One-way ANOVA analysis on the scales of store environment and service brand personality showed that there exist statistically significant differences in each service category. For example, the social factors were highest in discount stores, while the ambient factors and design factors were highest in fast-food stores. The discount stores were highest in the sincerity and excitement, while the highest point for banks was in the competence and ruggedness, and the highest point for fast-food stores was in the sophistication, The consumers will make a different respond to the physical environment of stores and service brand personality that are inherent to the corresponding service interface. Hence, the customers will make a different decision-making when dealing with different service categories. In this aspect, the relationships of variables in the proposed hypothesis appear to work in a different way depending on the exposed service category. 4) The store environment factors influenced on service brand personalities differently by category of service. The factors of store's physical environment are transferred to a brand and were verified to strengthen service brand personalities. In particular, the level of influence on the service brand personality by physical environment differs depending on service category or dimension, which indicates that there is a need to apply a different style of management to a different service category or dimension. It signifies that there needs to be a brand strategy established in order to positively influence the relationship with consumers by utilizing an appropriate brand personality factor depending on different characteristics by service category or dimension. 5) The service brand personalities influenced on the repurchase intention. Especially, the largest influence was made in the sophistication dimension of service brand personality scale; the unique and characteristically appropriate arrangement of physical environment will make customers stay in the service environment for a long time and will lead to give a positive influence on the repurchase intention. 6) The store environment factors influenced on the repurchase intention. Particularly, the largest influence was made on the social factors of store environment. The most intriguing finding is that the service factor among all other environment factors gives the biggest influence to the repurchase intention in most of all service types except fast-food stores. Such result indicates that the customers pay attention to how much the employees try to provide a quality service when they make an evaluation on the service brand. At the same time, it also indicates that the personal factor is directly transmitted to the construction of brand personality. The employees' attitude and behavior are the determinants to establish a service brand personality in the process of enhancing service interface. Hence, there should be a reinforced search for a method to efficiently manage the service staff who has a direct contact with customers in order to make an affirmative improvement of the customers' brand evaluation at the service interface. The findings suggest several managerial implications. 1) Results from the empirical study indicated that store environment factors have a strong positive impact on a service brand personality. To increase customers' repurchase intention of a service brand, the management is required to effectively manage store environment factors and create a friendly brand personality based on the corresponding service environment. 2) Mangers and researchers must understand and recognize that the store environment elements are important marketing tools, and that brand personality influences on consumers' repurchase intention. Based on such result of the study, a service brand could be utilized as an efficient measure to achieve a differentiation by enforcing the elements that are most influential among all other store environments for each service category. Therefore, brand personality established involving various store environments will further reinforce the relationship with customers through the elevated brand identification of which utilization to induce repurchase decision can be used as an entry barrier. 3) The study identified the store environment as a component of service brand personality for the store's effective communication with consumers. For this, all communication channels should be maintained with consistency and an integrated marketing communication should be executed to efficiently approach to a larger number of customers. Mangers and researchers must find strategies for aligning decisions about store environment elements with the retailers' marketing and store personality objectives. All ambient, design, and social factors need to be orchestrated so that consumers can take an appropriate store personality. In this study, the induced results from the previous studies were extended to the service industry so as to identify the customers' decision making process that leads to repurchase intention and a result similar to those of the previous studies. The findings suggested several theoretical and managerial implications. However, the situation that only one service brand served as the subject of analysis for each service category, and the situation that correlations among store environment elements were not identified, as well as the problem of representation in selection of samples should be considered and supplemented in the future when further studies are conducted. In addition, various antecedents and consequences of brand personality must be looked at in the aspect of the service environment for further research.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.