• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.300-311
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• 2014

According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.

• Korean Journal of Plant Taxonomy
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• v.34 no.2
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• pp.75-85
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• 2004

Here we described and illustrated two new taxa of Allium (Alliaceae) from southern part of Korea. One new species, A koreanum H. J. Choi et B. U. Oh was clearly distinguished from A. splendens of sect. Reticulato-bulbosa by larger and stellately spreading pale pink perianth, apparently exsert filaments, and conical stigma as well as chromosome number. Another new variety, A. thunbergii var. teretifolium H.J. Choi et B.U. Oh was also easily distinguished from its relatives, var. thunbergii and var. deltoides by terete and hollow leaf blade. Keys to the two species of Allium sect. Reticulato-bulbosa and the three varieties of A. thunbergii (sect. Sacculiferum) in Korea were described.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.513-519
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• 2022

The 4th industrial revolution has made our life convenient, and the development of new technologies has brought affluent life. Considering that the 4th industrial revolution is a next-generation industrial revolution led by robot technology, life science, and artificial intelligence, the need for convergence research in sports field stimulated the continuous efforts for the academic foundation of sports. Recently, as interest in home training has increased due to the COVID-19 pandemic, the Pilates has also attracted much attentions demand for related supplies has increased. This is an demonstration that COVID-19 has had an impact on the sports industry ecosystem. The purpose of this study was, accordingly, to identify current trends through accurate patent information related to Pilates and to provide basic data for future studies on sports convergence industry and sports intellectual property. For the purpose, based on the data from Jan. 1 to Dec. 31, 2021 provided by KIPRIS (www.kipris.or.kr), the patent information search service provided by the Korean Intellectual Property Office, patent status analysis, international patent classification (IPC) patent analysis, and detailed patent analysis by classification were performed.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Journal of Nutrition and Health
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• v.43 no.2
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• pp.197-206
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• 2010

Now a days, people eat outside of the home more and more frequently. Menu labeling can help people make more informed decisions about the foods they eat and help them maintain a healthy diet. This study was conducted to develop menu labeling system using Nutri-API (Nutrition Analysis Application Programming Interface). This system offers convenient user interface and menu labeling information with printout format. This system provide useful functions such as new food/menu nutrients information, retrieval food semantic service, menu plan with subgroup and nutrient analysis informations and print format. This system provide nutritive values with nutrient information and ratio of 3 major energy nutrients. MLS system can analyze nutrients for menu and each subgroup. And MLS system can display nutrient comparisons with DRIs and % Daily Nutrient Values. And also this system provide 6 different menu labeling formate with nutrient information. Therefore it can be used by not only usual people but also dietitians and restaurant managers who take charge of making a menu and experts in the field of food and nutrition. It is expected that Menu Labeling System (MLS) can be useful of menu planning and nutrition education, nutrition counseling and expert meal management.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.43-57
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• 2022

In this paper, we propose a method of analyzing research papers published by researchers belonging to university departments in the field of disaster & safety for the scientometric analysis of the research status in the field of disaster safety. In order to conduct analysis research, the dataset constructed in previous studies was newly improved and utilized. In detail, for research papers of authors belonging to the disaster prevention and safety engineering type department of domestic universities, institution identification, cited journal identification of references, department type classification, disaster safety type classification, researcher major information, KSIC(Korean Standard Industrial Classification) mapping information was reflected in the experimental data. The proposed method has a difference from previous studies in the field of disaster & safety and data set based on related keyword searches. As a result of the analysis, the type and regional distribution of organizations belonging to the department of disaster prevention and safety engineering, the composition of co-authored department types, the researchers' majors, the status of disaster safety types and standard industry classification, the status of citations in academic journals, and major keywords were identified in detail. In addition, various co-occurrence networks were created and visualized for each analysis unit to identify key connections. The research results will be used to identify and recommend major organizations and information by disaster type for the establishment of an intelligent crisis warning system. In order to provide comprehensive and constant analysis information in the future, it is necessary to expand the analysis scope and automate the identification and classification process for data set construction.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.245-255
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• 2015

As people are highly interested in health, the number of people who participate in various sports programs is getting increased. But there is no web service which integrates all the information of the public sports facilities in Seoul and it's convenient to use the public sport facilities. So we propose an integrated information system whoever can find the public sports facilities in Seoul. The public APIs for the Seoul public sports facilities provided by Seoul city are used to integrate the information. Also, our web page provides various graphic function using pictures and videos of the facilities on the environment of HTML5. And it is the responsive webpage which can be provided on both desktop and mobile environment. By implementing the wizard page, the managers of the facilities who are not specialized can renew the information about their facilities easily. And for the easier searching, we provides three options of searching: local, subjects, themes.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.43-52
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• 2012

For accurate search on information resources, it is needed to manage gradual changes in ontology efficiently. Recently, because ontology is often written using OWL, techniques that can manage changes in OWL documents are required. To meet these needs, in this paper, we classify changeable elements to detect changes in OWL ontology and propose a storage schema that can manage the changes according to the characteristics of each element. And we suggest the possibility of improving performance of query processing using views that provide information about classes or properties in each ontology version. The proposed storage schema stores changes in metadata associated with each ontology version. In addition, it can manage metadata that must be added or deleted through reasoning when ontology changes. So, the proposed storage schema can support queries about history of changes in ontology and provide accurate and valid metadata that is suitable for user-selected ontology version.

• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.