• Land and Housing Review
• /
• v.15 no.1
• /
• pp.117-134
• /
• 2024

This study examines the factors contributing to waterfront satisfaction among different generations, utilizing a survey on the use and perception of waterfront areas by residents of apartment houses in Tokyo's coastal region. The variables used in this study are developed through a review of existing literature, focusing on factors related to waterfront usage. Specifically, we select the proximity to the waterfront, duration of stay at the waterfront, and frequency of visits to the waterfront as key variables for investigation. In addition, the study further incorporates aspects related to waterfront recognition, such as the space, user behavior, and management status of the waterfront. Utilizing these variables, we carry out a correlation analysis to investigate the association between generational use and perception of the waterfront and their satisfaction with water-related experiences. The results identify three key factors to enhance waterfront satisfaction: First, to increase visits from both younger and older generations, improving pedestrian access to the waterfront is essential. Second, for middle-aged and older generations, creating waterfront areas closer to their residences can reduce travel distance and time, encouraging more frequent use. Third, maintaining clean and well-kept waterfront spaces is fundamental for all generations to enjoy relaxing experiences, thereby improving overall satisfaction.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.1
• /
• pp.28-43
• /
• 2022

This study classified UAV image-based physical spatial types for parks in urban areas of Changwon City and analyzed thermal comfort characteristics according to physical spatial types by comparing them with ENVI-met thermal comfort results. Physical spatial types were classified into four types according to UAV-based NDVI and SVF characteristics. As a result of ENVI-met thermal comfort, the T_MRT difference between the tree-dense area and other areas was up to 30℃ or more, and it was 19. 6℃ at 16:00, which was the largest during the afternoon. As a result of analyzing UAV-based physical spatial types and thermal comfort characteristics by time period, it was confirmed that the physical spatial types with high NDVI and high SVF showed a similar to thermal comfort change patterns by time when using UAV, and the physical spatial types with dense trees and artificial structures showed a low correlation to thermal comfort change patterns by time when using UAV. In conclusion, the possibility of identifying the distribution of thermal comfort based on UAV images was confirmed for the spatial type consisting of open and vegetation, and the area adjacent to the trees was found to be more thermally pleasant than the open area. Therefore, in the urban planning stage, it is necessary to create an open space in consideration of natural covering materials such as grass and trees, and when using artificial covering materials, it is judged that spatial planning should be done considering the proximity to trees and buildings. In the future, it is judged that it will be possible to quickly and accurately identify urban climate phenomena and establish urban planning considering thermal comfort through ground LIDAR and In-situ measurement-based UAV image correction.

• Journal of the Korean Society of Radiology
• /
• v.16 no.3
• /
• pp.225-231
• /
• 2022

Transcendence of space and time, virtual reality, augmented reality, etc. are being realized through the latest technologies in the era of the 4th industrial revolution. In a situation where they are currently experiencing artificial intelligence, augmented reality, big data, etc., the degree of interest in the latest technologies of the 4th industrial revolution for radiology students, the necessary competencies in the 4th industrial revolution era, and the prospect of the radiation field employment environment in the 4th industrial revolution era The purpose of this study was to find out the level of awareness of From February 7th to February 18th, 2022, surveys on awareness were analyzed using questionnaires for 2nd and 3rd year students in the Department of Radiology at S University in Daegu. As a result of the study, the level of interest in 3D modeling was shown to be the highest with an average of 3.34 ± 1.09 points, and interest in big data and artificial intelligence was also shown with an average of 3.27 ± 1.17 and 3.33 ± 1.07 points. In addition, the correlation between the awareness of the necessary competencies in the 4th industrial revolution era and the awareness of the prospects for employment in the radiation field in the 4th industrial revolution era was the highest (r=0.778, p<0.01), and the interest in the latest technologies in the 4th industrial revolution and the 4th industrial revolution It was found that there was also a correlation between the perceptions of the necessary capabilities of the times (r=0.694, p<0.01). In the era of the 4th industrial revolution, it is judged that it is necessary to strengthen professional education that can handle the latest technologies such as 3D printing, artificial intelligence, and big data, and to strengthen employment capabilities related to the latest technologies in the field of radiation medical technology.

• Korean Journal of Organic Agriculture
• /
• v.24 no.4
• /
• pp.719-733
• /
• 2016

This study was carried out to investigate the effect of no-tillage on sequential cropping supported from recycling of first crop ridge on the productivity of crop and physical properties of soil under green house condition. This study is a part of "No-tillage agriculture of Korea-type on recycled ridge". From results for distribution of soil particle size with time process after tillage, soil particles were composed with granular structure in both tillage and no-tillage. No-tillage soil in distribution of above 2 mm soil particle increased at top soil and subsoil compared with tillage soil. Tillage and one year of no-tillage soil were not a significant difference at above 0.25 mm~below 0.5 mm, above 0.5 mm~below 1.0 mm, and above 1.0 mm of water-stable aggregate. Two years of no-tillage soil was significantly increased by 8.2%, 4.5%, and 1.7% at above 0.25 mm~below 0.5 mm, above 0.5 mm~below 1.0 mm, and above 1.0 mm of water-stable aggregate, respectively, compared with one year of no-tillage. Bulk density of top soil was $1.10MG\;m^3$ at tillage and $1.30MG\;m^3$ at one year of no-tillage. Bulk density of top soil was $1.14MG\;m^3$ at two years and $1.03MG\;m^3$ at three years of no-tillage, respectively. Bulk density of subsoil was a similar tendency. Solid phase ratio in top soil and subsoil was increased at one year of no-tillage compared with tillage soil, while soil phase ratio decreased at two and three years of no-tillage. Pore space ratio in tillage top soil (58.5%) was decreased by 8.5% at compared with no-tillage soil (51.0%). Pore space ratio was 56.9% and 61.2% at two and three years of no-tillage soil, respectively. Subsoil was a similar tendency. Gaseous phase ratio was decreased at one year of no-tillage soil, and increased at two and three years of no-tillage soil compared with tillage soil. Liquid phase ratio in top soil was increased at one year of no-tillage (28.3%), and decreased at two years (23.4%) and at three years (18.3 %) of no-tillage soil compared with tillage soil (24.2%). Subsoil was a similar tendency. Liquid phase ratio in subsoil was increased than top soil.

• The Korean Journal of Air & Space Law and Policy
• /
• v.26 no.2
• /
• pp.149-179
• /
• 2011

Statistics of aviation accident in Korea show that safety level of training flights is high. However, more than 80% of aviation accidents happen owing to human factors. And because most reasons of them are concerned with pilot error, it is very important for student pilots who will transport a lot of passengers to develop the knowledge of safety and abilities of risk management for preventing accidents. In this study, in order to investigate the Human Factors which affect safety in training student pilots for flight, verified the correlationbetween experiences of accident, the differences according to the experience level of training flight and the differences between college student pilots and ordinary student pilots on the basis of human factors that composes the SHELL models. For the study, Using SPSS 17.0, conducted Correlation Analysis, Analysis of Variance(ANOVA) and t-test. To sum up the result of this study, student pilot's ability and equipment in the cockpit are the important factors for safety when pilots are training flight. Also the analysis of the differences between human factors according to the characters of student pilots' groups shows that college student pilots are affected by immanent factors and organizational cultures. So far, there haven't been any accidents which is related with human casualties when training at the ATO(Approved Training Organization). But accidents can occur at any time and anywhere. Especially the human factors which comprises most of aviation accident have a wide reach and are impossible to be eliminated, therefore, it is best to minimize them. Because ATO is the starting point to lead the aviation industry of Korea, we will have to be aware of problems and improve education/training of human factors.

• Journal of the Korean Geographical Society
• /
• v.40 no.2 s.107
• /
• pp.221-241
• /
• 2005

Land Use and Land Cover Changes (LUCC) occur over a wide range of space and time scales, and involve complex natural, socio-economic, and institutional processes. Therefore, modelling and predicting LUCC demands an understanding of how various measured properties behave when considered at different scales. Understanding spatial and temporal variability of driving forces and constraints on LUCC is central to understanding the scaling issues. This paper aims to 1) assess the heterogeneity of land cover change processes over the landscape in northern Ghana, where intensification of agricultural activities has been the dominant land cover change process during the past 15 years, 2) characterise dominant land cover change mechanisms for various spatial scales, and 3) identify the optimal spatial scale for LUCC modelling in a savanna landscape. A multivariate statistical method was first applied to identify land cover change intensity (LCCI), using four time-sequenced NDVI images derived from LANDSAT scenes. Three proxy land use change predictors: distance from roads, distance from surface water bodies, and a terrain characterisation index, were regressed against the LCCI using a multi-scale hierarchical adaptive model to identify scale dependency and spatial heterogeneity of LUCC processes. High spatial associations between the LCCI and land use change predictors were mostly limited to moving windows smaller than 10$\times$10km. With increasing window size, LUCC processes within the window tend to be too diverse to establish clear trends, because changes in one part of the window are compensated elsewhere. This results in a reduced correlation between LCCI and land use change predictors at a coarser spatial extent. The spatial coverage of 5-l0km is incidentally equivalent to a village or community area in the study region. In order to reduce spatial variability of land use change processes for regional or national level LUCC modelling, we suggest that the village level is the optimal spatial investigation unit in this savanna landscape.

• Journal of Intelligence and Information Systems
• /
• v.16 no.3
• /
• pp.181-199
• /
• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.

• Journal of Practical Agriculture & Fisheries Research
• /
• v.23 no.1
• /
• pp.89-104
• /
• 2021

Based on the TF-IDF weighted value that evaluates the importance of words that play a key role, the semantic network analysis(SNA) was conducted on the self-introduction letter of freshman at Korea National College of Agriculture and Fisheries(KNCAF) in 2020. The top three words calculated by TF-IDF weights were agriculture, mathematics, study (Q. 1), clubs, plants, friends (Q. 2), friends, clubs, opinions, (Q. 3), mushrooms, insects, and fathers (Q. 4). In the relationship between words, the words with high betweenness centrality are reason, high school, attending (Q. 1), garbage, high school, school (Q. 2), importance, misunderstanding, completion (Q.3), processing, feed, and farmhouse (Q. 4). The words with high degree centrality are high school, inquiry, grades (Q. 1), garbage, cleanup, class time (Q. 2), opinion, meetings, volunteer activities (Q.3), processing, space, and practice (Q. 4). The combination of words with high frequency of simultaneous appearances, that is, high correlation, appeared as 'certification - acquisition', 'problem - solution', 'science - life', and 'misunderstanding - concession'. In cluster analysis, the number of clusters obtained by the height of cluster dendrogram was 2(Q.1), 4(Q.2, 4) and 5(Q. 3). At this time, the cohesion in Cluster was high and the heterogeneity between Clusters was clearly shown.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.1-21
• /
• 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
• /
• v.40 no.5
• /
• pp.100-108
• /
• 2012

The purpose of the study was to evaluate the influence of shading and ventilation on Mean Radiant Temperature(MRT) of the outdoor space at a summer outdoor. The Wind Speed(WS), Air Temperature(AT) and Globe Temperature(GT) were recorded every minute from $1^{st}$ of May to the $30^{th}$ of September 2011 at a height of 1.2m above in four experimental plots with different shading and ventilating conditions, with a measuring system consisting of a vane type anemometer(Barini Design's BDTH), Resistance Temperature Detector(RTD, Pt-100), standard black globe(${\O}$ 150mm) and data acquisition systems(National Instrument's Labview and Compfile Techs' Moacon). To implement four different ventilating and shading conditions, three hexahedral steel frames, and one natural plot were established in the open grass field. Two of the steel frames had a dimension of $3m(W){\times}3m(L){\times}1.5m(H)$ and every vertical side covered with transparent polyethylene film to prevent lateral ventilation(Ventilation Blocking Plot: VP), and an additional shading curtain was applied on the top side of a frame(Shading and Ventilation Blocking Plot: SVP). The third was $1.5m(W){\times}1.5m(L){\times}1.5m(H)$, only the top side of which was covered by the shading curtain without the lateral film(Shading Plot: SP). The last plot was natural condition without any kind of shading and wind blocking material(Natural Open Plot: NP). Based on the 13,262 records of 44 sunny days, the time serial difference of AT and GT for 24 hour were analyzed and compared, and statistical analysis was done based on the 7,172 records of daytime period from 7 A.M. to 8 P.M., while the relation between the MRT and solar radiation and wind speed was analyzed based on the records of the hottest period from 11 A.M. to 4 P.M.. The major findings were as follows: 1. The peak AT was $40.8^{\circ}C$ at VP and $35.6^{\circ}C$ at SP showing the difference about $5^{\circ}C$, but the difference of average AT was very small within${\pm}1^{\circ}C$. 2. The difference of the peak GT was $12^{\circ}C$ showing $52.5^{\circ}C$ at VP and $40.6^{\circ}C$ at SP, while the gap of average GT between the two plots was $6^{\circ}C$. Comparing all four plots including NP and SVP, it can be said that the shading decrease $6^{\circ}C$ GT while the wind blocking increase $3^{\circ}C$ GT. 3. According to the calculated MRT, the shading has a cooling effect in reducing a maximum of $13^{\circ}C$ and average $9^{\circ}C$ MRT, while the wind blocking has heating effect of increasing average $3^{\circ}C$ MRT. In other words, the MRT of the shaded area with natural ventilation could be cooler than the wind blocking the sunny site to about $16^{\circ}C$ MRT maximum. 4. The regression and correlation tests showed that the shading is more important than the ventilation in reducing the MRT, while both of them do an important role in improving the outdoor thermal comfort. In summary, the results of this study showed that the shade is the first and the ventilation is the second important factor in terms of improving outdoor thermal comfort in summer daylight hours. Therefore, it can be apparently said that the more shade by the forest, shading trees etc., the more effective in conditioning the microclimate of an outdoor space reducing the useless or even harmful heat energy for human activities. Furthermore, the delicately designed wind corridor or outdoor ventilation system can improve even the thermal environment of urban area.