• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.167-174
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• 2020

The aim of this study is to find out how the mathematics activities linked to outdoor movement activities affect children's motor abilities. S kindergarten located in Gyeonggido do conducted a fifteen week program for young children aged five years. In this study, young children's motor perfromenace test scale of Ji Sungae(2007) was conducted. Each area consists of a five-point scale. There were a total of thirty-three questions. pre-tests and post-tests were performed for young children's motor performance. t-test was used. As a result of this study, it was found that mathematics activities in connection with outdoor movement activities had a positive effect on the improvement of overall exercise ability, non-movement exercise ability, and mobility exercise ability of young children. Based on the results of this study, it is expected that various programs for young children integrated with outdoor motor activities will be developed and applied to the site.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.871-874
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• 2016

본 논문은 실내 환경에서 스마트 워치(smart watch)를 이용하여 사용자의 원시 데이터를 수집, 가공하고, 이를 통해 사용자의 다양한 복합 동작을 인식하는 방법을 제안한다. 사용자의 동작을 인식하는 방법들은 다양하다. 특히 최근 웨어러블 기기(wearable device)들이 각광받으면서 웨어러블 기기를 이용하여 인체 동작이나 활동 상태 등의 생체신호를 인식하려는 다양한 시도가 일어나고 있다. 하지만 동작이나 활동 상태에 관한 많은 연구들이 센서를 허리에 부착하는 등의 특정한 상황만을 상정하거나 위성항법장치(GPS, global positioning system)에 의존한 실외 환경에 국한되어 있는데, 이는 대부분의 시간을 가정과 직장, 이동 수단 등의 실내 환경에서 소비하는 현대인들의 시간 소비 패턴과는 거리가 있다. 본 연구에서는 스마트 워치의 가속도계(accelerometer), 각속도계(gyroscope), 심박계(heart bit), 압력계(barometer) 등 다양한 센서를 통해 원시데이터를 수집, 가공하여 사용자의 앉기, 서기, 오르막이나 내리막의 걷고 뛰기, 계단의 오르내리기 등 실내에서 일어날 수 있는 복합 동작을 인식하는 방법을 제안한다.

• Journal of Creative Information Culture
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• v.7 no.4
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• pp.235-242
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• 2021

Recently, many human activity recognition(HAR) researches using smartphone sensor data have been studied. HAR can be utilized in various fields, such as life pattern analysis, exercise measurement, and dangerous situation detection. However researches have been focused on recognition of basic human behaviors or efficient battery use. In this paper, exercising activities performed indoors and outdoors were defined and recognized. Data collection and pre-processing is performed to recognize the defined activities by SVM, random forest and gradient boosting model. In addition, the recognition result is determined based on voting class approach for accuracy and stable performance. As a result, the proposed activities were recognized with high accuracy and in particular, similar types of indoor and outdoor exercising activities were correctly classified.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.83-92
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• 2019

The particulate matters show high values in winter and spring season, it has a bad influence on the outdoor people. That's why government needs to come up with countermeasures for social weak people like elementary school students. In this paper, new particulate matter stations select ed about elementary schools using spatial analysis. Seoul city areas were divided with 608 hexagon grids(500m), and then implement spatial analysis such as kernel analysis. Finally, new particulate matter stations select through the results of kernel density analysis and point displacement. The results show that, 10 hexagon grids about new particulate matter stations were selected and listed 15 elementary schools including 10 hexagon grids. The 15 elementary schools were including Gangbuk gu, Eunpyeong gu, Guro gu, Dong gu, Geumcheon gu, Dongdaemun gu, Gangdong gu, Songpa gu, Gwangjin gu and Gangnam gu. The results suggests a new management plan direction according to the spatial analysis, result in the process of selecting the measures for the '2018 School Fine Dust Comprehensive Management Measures' announced by the Ministry of Education. Also, this study can be expanded by adding specific buildings as well as the school.