• Journal of the Korean earth science society
• /
• v.42 no.5
• /
• pp.504-513
• /
• 2021

Different physical processes, according to the atmospheric boundary layer types, were used in the Local Data Assimilation and Prediction System (LDAPS) of the Unified Model (UM) used by the Korea Meteorological Administration (KMA). Therefore, it is important to verify the atmospheric boundary layer types in the numerical model to improve the accuracy of the models performance. In this study, the atmospheric boundary layer types were verified using observational data. To classify the atmospheric boundary layer types, summer intensive observation data from radiosonde, flux observation instruments, Doppler wind Light Detection and Ranging(LIDAR) and ceilometer were used. A total number of 201 observation data points were analyzed over the course 61 days from June 18 to August 17, 2019. The most frequent types of differences between LDAPS and observed data were type 1 in LDAPS and type 2 in observed(each 53 times). And type 3 difference was observed in LDAPS and type 5 and 6 were observed 24 and 15 times, respectively. It was because of the simulation performance of the Cloud Physics such as that associated with the simulation of decoupled stratocumulus and cumulus cloud. Therefore, to improve the numerical model, cloud physics aspects should be considered in the atmospheric boundary layer type classification.

• Journal of Korean Elementary Science Education
• /
• v.39 no.2
• /
• pp.155-167
• /
• 2020

This study analyzed reference data for the physics section in science guidebooks for the third-sixth grade in elementary schools, according to the 2015 revised curriculum. It analyzed the reference data by categorizing them in terms of subjects, objectives and presentation forms and the visual data used in the reference data by categorizing their types. The findings show that the ratio of the science knowledge type was highest (53.8%) among the subjects of reference data in guidebooks for the science section, followed by the application to real life, and then, supplementary inquiry experiments and activities. The ratios of other types such as advanced science, environment, scientists and science history were, however, less than 1%, so they need to be improved. The ratio of knowledge provision was highest (40.5%) among the objectives of reference data but the ratios of conceptual supplementation and deepening were similar in ratio. Meanwhile, While the expository type (88.4%) accounted for most of the present forms of reference data, and photographs and illustrations (93.6%) also accounted for most of visual data suggested with reference data. Thus more various types of presentation forms and the extension of visual data seemed to be needed. This study is expected to provide some suggestions for the meaningful use of reference data in guidebooks for teachers and for the development of science guidebooks for teachers in elementary schools.

• Journal of Digital Convergence
• /
• v.16 no.10
• /
• pp.205-212
• /
• 2018

With the development of high performance CPU / GPU, artificial intelligence algorithms such as deep neural networks, and a large amount of data, machine learning has been extended to various applications. In particular, a large amount of data collected from the Internet of Things, social network services, web pages, and public data is accelerating the use of machine learning. Learning data sets for machine learning exist in various formats according to application fields and data types, and thus it is difficult to effectively process data and apply them to machine learning. Therefore, this paper studied a method for building a learning data set for machine learning in accordance with standardized procedures. This paper first analyzes the requirement of learning data set according to problem types and data types. Based on the analysis, this paper presents the reference model to build learning data set for machine learning applications. This paper presents the target standardization organization and a standard development strategy for building learning data set.

• Korean Journal of Remote Sensing
• /
• v.38 no.1
• /
• pp.73-82
• /
• 2022

Marine fisheries resources face major anthropogenic threat from unregulated fishing activities; thus require precise detection for protection through marine surveillance. Korea developed an efficient land-based small fishing vessel monitoring system using real-time V-Pass data. However, those data directly do not provide information on fishing activities, thus further efforts are necessary to differentiate their activity status. In Korea, especially in Busan, longlining is practiced by many small fishing vessels to catch several types of fishes that need to be identified for proper monitoring. Therefore, in this study we have improved the existing fishing status classification method by applying Hidden Markov Model (HMM) on V-Pass data in order to further classify their fishing status into three groups, viz. non-fishing, longlining and other types of fishing. Data from 206 fishing vessels at Busan on 05 February, 2021 were used for this purpose. Two tiered HMM was applied that first differentiates non-fishing status from the fishing status, and finally classifies that fishing status into longlining and other types of fishing. Data from 193 and 13 ships were used as training and test datasets, respectively. Using this model 90.45% accuracy in classifying into fishing and non-fishing status and 88.23% overall accuracy in classifying all into three types of fishing statuses were achieved. Thus, this method is recommended for monitoring the activities of small fishing vessels equipped with V-Pass, especially for detecting longlining.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.66-69
• /
• 2002

This paper proposes a new dynamic storage structure and methods fur geometric data with detail levels. Using geometric data with detail levels, we can search geometric data quickly. However, the previous structures for detail levels form the bottleneck in the design of database and do not support all types of geometric data with detail levels. Our structure supports all types of geometric data with detail levels. Moreover, our structure does not form bottleneck in the design of database. This paper presents the structure and algorithms for searching and updating of geometric data with detail levels. Experiments are then performed.

• Journal of the Korea Fashion and Costume Design Association
• /
• v.14 no.3
• /
• pp.67-77
• /
• 2012

Hanbok of dolls can be a good medium that can given with value of traditional cultural products, however, it is not easy to see hanbok and its pattern from dolls. Especially for the case of rag doll which is closely related to the life of users, it has enough value as traditional cultural contents, however, there have been not sufficient studies on its pattern development and classification of form of dolls. Therefore, by classifying the body type of dolls by its pose, this study aims to provide a basic data for the development of hanbok pattern. This study looks into the origin and meaning of dolls and the definition and features of rag doll, then, it collected pictures and data rag dolls produced by 29 domestic companies. Through the data collected, the six different types of dolls, 'Sitting Style', 'Standing Style', 'Lying Style', 'Cushion Style', 'Quadruped Sitting Style', 'Quadruped Standing Style', were classified into form. In the future, I hope the result of this study can be used as useful data for toy manufactures and cultural business in relation to development of rag doll and at the same time as a basic data for development of hanbok pattern development of rag dolls as traditional cultural goods.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.1
• /
• pp.82-88
• /
• 2017

Recently recommendation methods need personalization and diversity as well as accuracy whereas the traditional researches have been mainly focused on the accuracy of recommendation in terms of quality. The diversity of recommendation is also important to people in terms of quantity in addition to quality since people's desire for content consumption have been stronger rapidly than past. In this paper, we pay attention to similarity of data gathered simultaneously among different types of contents. With this motivation, we propose an enhanced recommendation method using correlation analysis with considering data similarity between two types of contents which are movie and music. Specifically, we regard folksonomy tags for music as correlated data of genres for movie even though they are different attributes depend on their contents. That is, we make result of new recommendation movie items through mapping music folksonomy tags to movie genres in addition to the recommendation items from the typical collaborative filtering. We evaluate effectiveness of our method by experiments with real data set. As the result of experimentation, we found that the diversity of recommendation could be extended by considering data similarity between music contents and movie contents.

• The Mathematical Education
• /
• v.60 no.3
• /
• pp.265-279
• /
• 2021

In this study, by analyzing of types and functions of questions presented in Data and Chance area of the mathematics textbooks for grades 1-6 of the 2015 revised curriculum, the characteristics of the questions presented in the textbook were identified, and implications for teaching and learning related to the questions in this textbook were obtained. Types and functions of the presented questions showed different proportions of appearance according to the grade clusters, and this seems to be related to the learning contents for each grade clusters and the characteristics of grade clusters. In addition, it can be seen that the functions of questions are related to the types of questions. Teachers should have pedagogical content knowledge about Data and Chance area as well as developmental characteristics for each grade clusters. In addition, the teacher should present an suitable question for the level of grade clusters and the nature of the content to be taught so that effective learning can be achieved based on the understanding of the characteristics and functional characteristics of each type of questions. The results of this study can contribute to statistical teaching in a progressive direction by providing a foundation for textbook writing and teaching/learning.

• Journal of The Korean Association For Science Education
• /
• v.29 no.2
• /
• pp.168-178
• /
• 2009

In this study, we investigated the errors that students committed in the processes of constructing graphs on experimental results by the students' science achievement level. A test of constructing a graph about 'the relationship between the pressure and volume of a gas' was administered to 7th graders (N=145). Results revealed that most students committed errors in the processes of constructing the graph, showing 12 error types in the categories of 'Misinterpreting the variables', 'Mismarking the graphical elements', and 'Misusing the data'. The students in the lower achievement level had more errors than those in the higher achievement level in the two error types, that is 'representing the bar graph' and 'marking the scale in the presented data order', but the results were reversed in the three error types, that is 'marking the independent variable and dependent variable reversely', 'adding the data', and 'neglecting the data'. In the other error types, there were little differences in the frequencies of the errors by students' science achievement level.

• The Research Journal of the Costume Culture
• /
• v.28 no.5
• /
• pp.639-651
• /
• 2020

This study utilized data to classify and characterize the body types of plus-size adult men aged in their 30s and 40s. Diversity is an important factor in the era of inclusive design, and discussion about size diversity to include the plus size should be accommodated. Data from 493 adult men classified as obese (with a World Health Organization criterion ≥25 BMI) were used for the analysis. The results of the study are as follows. Six independent factors were extracted using factor analysis for cluster analysis, which were then classified into five types. Type 1 (29.01%) was identified as body type I with the smallest degree of obesity. Type 2 (15.4%) was identified as body type Y with wide shoulders and a thin waist. Type 3 (14.2%) was the largest body volume (body type O), while the fourth (19.27%) identified as body type H has a large height and upper body. Lastly, type 5 (22.11%) has a long lower body and a slim abdomen, referred to as body type X. This study presents a basis for the development of various clothing sizes utilizing the body shape characteristics of plus-size men in their 30s and 40s. Follow-up research is needed to develop patterns for plus size men and to design various products.