• Genomics & Informatics
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• v.16 no.4
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• pp.22.1-22.5
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• 2018

In 1966, the International Classification of Viruses (ICNV) was established to standardize the naming of viruses. In 1975, the organization was renamed "International Committee on Taxonomy of Viruses (ICTV)," by which it is still known today. The primary virus classification provided by ICTV in 1971 was for viruses infecting vertebrates, which includes 19 genera, 2 families, and 24 unclassified groups. Presently, the 10th virus taxonomy has been published. However, the early classification of viruses was based on clinical results "in vivo" and "in vitro," as well as on the shape of the Phenotype virus. Due to the development of next-generation sequencing and the accompanying bioinformatics analysis pipelines, a reconstruction of the classification system has been proposed. At a meeting held in Boston, USA between June 9-11, 2016, there was even an in-depth discussion regarding the classification of viruses using metagenomic data. One suggested activity that arose from the meeting was that viral taxonomy should be reconstructed, based on genotype and bioinformatics analysis "in silico." This article describes our efforts to achieve this goal by construction of a web-based system and the extension of an associated database, based on ICTV taxonomy. This virus taxonomy web system was designed specifically to extend the virus taxonomy up to strain and isolation, which was then connected with the NCBI database to facilitate searches for specific viral genes; there are also links to journals provided by the EMBL RESTful API that improves accessibility for academic groups.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.25-34
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• 2017

With the recent spread of smartphones and the introduction of web services, online users can access large-scale content regardless of time or place. However, users have had trouble finding the content they wanted among large-scale content. To solve this problem, user modeling and content recommendation system have been actively studied in various fields. However, in spite of active changes in senior groups according to the changes in information environment, research on user modeling and content recommendation system focused on senior groups are insufficient. In this paper, we propose a method of modeling smart senior based on their preference, and further develop a smart senior classification model using machine learning methods. As a result, we can not only grasp the preferences of smart seniors, but also develop a smart senior classification model, which is the foundation for the research of a recommendation system which will provide the activities and contents most suitable for senior groups.

• Journal of Korean Academy of Nursing Administration
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• v.8 no.3
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• pp.475-488
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• 2002

Purpose : The purpose of this study is to establish a basis of patient classification in the ICU by selecting the determination critical indicator of special nursing activities that show high interrilation with daily total nursing care time. Method : This study is composed of the six steps. The first step is the listing direct nursing activities in the ICU. The last step is the determination indicator of each group were selected on the basis of their relationship to the daily total nursing care time of each patient classification group and each nursing activity. Result : Result shows that: 1. direct nursing activities in the ICU are 149 items of 13 territories. 2. the average time and frequency for each direct nursing activities 3. total direct nursing care time of 42 patients in ICU for 2 days. According to the results of the Cluster analysis, the first group is 10 people, the second group is 13 people, the third group is 16 people, the fourth group is 3 people. 4. Determination critical indicator is the item that is r>0.6(p<0.05) of Pearson Correlation between each patient daily total nursing care time and 149 items of nursing activities. The nursing activities selected were as follows: 2 items in the first group, 17 items in the second group. 16 items in the third group, 8 items in the fourth group. Conclusion : This study can help future studies which measure nursing activities standard time or assigns value to nursing activities time.

• Annual Conference of KIPS
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• 2022.11a
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• pp.478-480
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• 2022

This paper studies human activity image classification using deep transfer learning techniques focused on the inception convolutional neural networks (InceptionV3) model. For this, we used UFC-101 public datasets containing a group of students' behaviors in mathematics classrooms at a school in Thailand. The video dataset contains Play Sitar, Tai Chi, Walking with Dog, and Student Study (our dataset) classes. The experiment was conducted in three phases. First, it extracts an image frame from the video, and a tag is labeled on the frame. Second, it loads the dataset into the inception V3 with transfer learning for image classification of four classes. Lastly, we evaluate the model's accuracy using precision, recall, F1-Score, and confusion matrix. The outcomes of the classifications for the public and our dataset are 1) Play Sitar (precision = 1.0, recall = 1.0, F1 = 1.0), 2), Tai Chi (precision = 1.0, recall = 1.0, F1 = 1.0), 3) Walking with Dog (precision = 1.0, recall = 1.0, F1 = 1.0), and 4) Student Study (precision = 1.0, recall = 1.0, F1 = 1.0), respectively. The results show that the overall accuracy of the classification rate is 100% which states the model is more powerful for learning UCF-101 and our dataset with higher accuracy.

• Child Health Nursing Research
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• v.25 no.3
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• pp.262-272
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• 2019

Purpose: We aimed to identify factors influencing physical activity in adolescents with complex congenital heart disease. Methods: We recruited 92 adolescents with complex congenital heart disease from a tertiary medical center in Seoul, measured their levels of physical activity, and identified factors that influenced their physical activity levels using the Global Physical Activity Questionnaire, the New York Heart Association classification, congenital heart disease complexity, the Self-Efficacy Scale, and the Parental Bonding Instrument scale. Stepwise multiple linear regression was used to determine factors influencing physical activity. Results: Total physical activity was higher in males than in females (t=4.46, p<.001). Adolescents who participated in school physical education classes engaged in more physical activity than those who did not (t=6.77, p<.001). Higher self-efficacy (${\beta}=.41$, p<.001), male gender (${\beta}=.37$, p<.001) and participation in school physical education classes (${\beta}=.19$, p=.042) were associated with a higher likelihood of engagement in physical activity. Conclusion: It is necessary to develop nursing interventions that enhance self-efficacy in order to promote physical activity in adolescents with complex congenital heart disease. Physical activity should also be promoted in an individualized manner, taking into account gender, disease severity, and parental attitude.

• Journal of The Korean Association For Science Education
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• v.31 no.5
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• pp.709-719
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• 2011

The purpose of this study was to identify the differences in classification skills shown in classification activities between the gifted and regular students in elementary schools. The subjects for the research consisted of six gifted students in an institute for the gifted for science annexed to P school district in Gangwon-do and 6 students at B and M general elementary schools. Results were as follows: The time taken for classification activities of the gifted was shorter than regular regardless of subjects for classifying. The number of standards for classifying for the gifted was more than regular students. Coefficient for measuring classification skills of the gifted was higher than regulars regardless of age. Consequently, there was a difference in the time taken for classifying and generating the number of standards and in a numerical index of classification activities performed at science classes between the science gifted and the regular students.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.1
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• pp.81-88
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• 2011

A real time monitoring system from a PC has been developed which can be accessed through transmitted data, which incorporates an established low powered transport system equipped with a single chip combined with wireless sensor network technology from a three-axis acceleration sensor. In order to distinguish between static posture and dynamic posture, the extracted parameter from the rapidly transmitted data needs differentiation of movement and activity structures and status for an accurate measurement. When results interpret a static formation, statistics referring to each respective formation, known as the K-mean algorithm is utilized to carry out a determination of detailed positioning, and when results alter towards dynamic activity, fuzzy algorithm (fuzzy categorizer), which is the relationship between speed and ISVM, is used to categorize activity levels into 4 stages. Also, the ISVM is calculated with the instrumented acceleration speed on the running machine according to various speeds and its relationship with kinetic energy goes through correlation analysis. With the evaluation of the proposed system, the accuracy level stands at 100% at a static formation and also a 96.79% accuracy with kinetic energy and we can easily determine the energy consumption through the relationship between ISVM and kinetic energy.

• The Journal of Korean Physical Therapy
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• v.24 no.4
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• pp.282-289
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• 2012

Purpose: The purpose of this study is to analyze the home-stay disability's activity, as well as the participation domains and the environment factor domains of international classification of functioning (ICF), in order to examine the effect of the home visiting physical therapy and the disability's activity. Methods: A total of 211 home-stay disabled subjects with brain lesions or crippled disorder, living in 5 cities and districts of Jeollanam-do, underwent 90 minutes of home visiting physical therapy per week during a 6-month period, and using the ICF checklist, evaluated the subject's activity and participation domains and environmental factor domains. Results: The performance qualifier showed a significant statistical change in the movement, self-care, domestic life, interpersonal interactions and relationships, community, society and civic life domains (p<0.05); and the capacity qualifier showed a significant change only in the mobility domains in the before and after of the home visiting physical therapy (p<0.05). The barrier factor in the order of services, systems and policies domains, product and technology domains, and attitude domains it influenced significantly in the performance (p<0.05), and in the facilitator factor in the order of product and technology domains, support and relationships domains, services, systems and policies domains it influenced significantly in the performance of the disabled (p<0.05). Conclusion: The visiting physical therapy can help in the improvement of the activity and participation of the home-stay disabled subjects, and for the accurate evaluation of the home-stay disabled subjects, it is considered that an evaluation including various environmental factors, such as ICF, must be fulfilled.

• Journal of Korean Biological Nursing Science
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• v.13 no.3
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• pp.245-252
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• 2011

Purpose: This study was designed to find the correlations between physical activity and insulin resistance of the middle-aged adults. Methods: One hundred thirty one subjects participated in this study were age 40-60 from Y university's center for physical exercise in W city. The data were collected from August 5 to October 5, 2009. To measure physical activity, the contracted Korean version of the Self-Report of Physical Activity Questionnaires of IPAQ was used. Insulin resistance was measured using fasting glucose levels, serum insulin levels, and HOMA method (serum insulin${\times}$fasting glucose/22.5). Results: The continuous physical activity overall in this study was on average $1,792.30{\pm}2,216.81$ MET (min/week), and as a result of categorical classification: no activity was 66 subjects (50.4%); minimum activity, 41 (31.3%); and health-improving activity, 24 (18.3%), respectively. The overall degree of insulin resistance in these subjects was $2.20{\pm}2.62$(0.28-12.74). There was negative correlation between moderate intensity activity and insulin resistance (r= -.189, p<.05). Conclusion: These results revealed that promoting moderate-intensity physical activity is important in preventing and improving insulin resistance and possibly other metabolic risk factors in the middle-aged adults.

• Journal of Service Research and Studies
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• v.8 no.1
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• pp.89-102
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• 2018

The Industrial Classification is a systematic taxonomy of industrial activities and the Standard Industrial Classification is used in all country by their own a consistent classification method. Therefore, it is employed to analyze current status of industry affairs using statistical investigations in terms industrial activities for making industrial policies and to compare industrial activity among countries. Since the Second Industrial Revolution, the need for the homogenous standard of industrial classification among countries emerged as the economic and industrial exchanges between the countries have became more active. In 1940, Colin Clark who british economist divided the industry into the first (primitive), second (processed), and third (service) industries. Based on this, the United Nations Office for Statistics (UNSD) established International Standard Industry Classification (ISIC) in 1948, which most countries invoke it. ISIC(International Standard Industry Classification) and the standard industry classifications of countries have reached the present after several revisions since the enactment of the Act. In the 2000s, the standard industry classification is amended to reflect the emergence of new industries and changes in industrial structure, mainly featuring the creation and segmentation of sections in the tertiary industry domains. It also shows that primary and secondary sectors are shifting to tertiary industry. In this study, the causes of these common phenomena are systematically identified and the problems present classification systems have been analyzed. Also proposed is the direction of formation of the industrial classification system from a service economy point of view and the conceptual model of the new classification system. In the future, it is necessary to validate the proposed model through this study and to carry out various new classification system studies.