• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.97-104
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• 2016

In this paper, we propose spatial information based simulator for user experience optimization and minimize real space complexity. We focus on developing simulator how to design virtual space model and to implement virtual character using real space data. Especially, we use expanded events-driven inference model for SVM based on machine learning. Our simulator is capable of feature selection by k-fold cross validation method for optimization of data learning. This strategy efficiently throughput of executing inference of user behavior feature by virtual space model. Thus, we aim to develop the user experience optimization system for people to facilitate mapping as the first step toward to daily life data inference. Methodologically, we focus on user behavior and space modeling for implement virtual space.

• Journal of the Korean housing association
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• v.18 no.2
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• pp.49-58
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• 2007

Kitchen space is one of the most dangerous places for the elderly. Modifications of kitchen space for improving safety and independence for older residents are very important factor for aging in place. The purpose of this study was to identify the current situations and modifications of kitchen space by elderly-headed households. The sample included 108 respondents over the age 65 who consisted of elderly-couple or single person household with homeownership in Seoul. The data were analyzed by descriptive statistics. Based on the findings of the study, the present incidence and recognition of future need in kitchen modifications were identified. Changes made in kitchen space tended to be nonstructural or relatively inexpensive items. In conclusion, this study suggests several ideas for improving current physical problems of kitchen space to support safe and independent daily living of older residents.

• Korean Journal of Agricultural and Forest Meteorology
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• v.7 no.2
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• pp.171-183
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• 2005

In order to monitor the global terrestrial carbon cycle, NASA (National Aeronautics and Space Administration) provides 8-day GPP images by use of satellite remote-sensing reflectance data from MODIS (Moderate Resolution Imaging Spectroradiometer) at l-km nadir spatial resolution since December, 1999. MODIS GPP algorithm adopts DAO (Data Assimilation Office) meteorological data to calculate daily GPP. By evaluating reliability of DAO data with respect to surface weather station data, we examined the effect of errors from DAO data on MODIS GPP estimation in the Korean Peninsula from 2001 to 2003. Our analyses showed that DAO data underestimated daily average temperature, daily minimum temperature, and daily vapor pressure deficity (VPD), but overestimated daily shortwave radiation during the study period. Each meteorological variable resulted in different spatial patterns of error distribution across the Korean Peninsula. In MODIS GPP estimation, DAO data resulted in overestimation of GPP by $25\%$ for all biome types but up to $40\%$ for forest biomes, the major biome type in the Korean Peninsula. MODIS GPP was more sensitive to errors in solar radiation and VPD than in temperatures. Our results indicate that more reliable gridded meteorological data than DAO data are necessary for satisfactory estimation of MODIS GPP in the Korean Peninsula.

• Korean Journal of Child Studies
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• v.37 no.1
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• pp.49-60
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• 2016

Objective: The purpose of the study was to explore the relationship between the daily routines and physical environments of daycare centers. Methods: A total of 20 classes at 8 different daycare centers from the metropolitan city of Daejeon were investigated. Trained observers visited each daycare center more than 3 times and collected data about daily routines using the Observational Log for Daily Routines in Daycare Centers. Also, the physical environments of each class were investigated in terms of actual size, layout of activity center, etc. Results and Conclusion: Results of the study were: first, daily routines of daycare centers could be divided into 2 distinguishable types by cluster analysis- 'free play oriented' and 'group activity oriented' Second, the amount of space each child has in a classroom differed according to the total size of the classroom. An average of 7 activity centers existed in each classroom. Third, there was a difference between free play oriented and group activity oriented groups in terms of the classroom size allocated for each child and the organization of the activity centers.

• Journal of the Korean Institute of Rural Architecture
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• v.10 no.1
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• pp.93-100
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• 2008

The purpose of this study is to clarify the actual condition of the daily living activities of the elderly with dementia in skilled nursing facilities. The thorough investigation and observation works were made from the view points of daily living behaviors and behavioral places of the recuperating elderly with dementia. This article discusses about the basic characteristics of the elderly and the actual condition of the daily living activities of the elderly with dementia in 2 skilled nursing facilities. The results of this study are summarized as follows; There is no wide difference between skilled nursing facilities on the characteristic of living behaviors of the elderly with dementia. Daily living activities and the use of spaces are largely influenced by the daily program and the operation policy of each skilled nursing facilities in addition to human relationship of the elderly with dementia. Common spaces such as day room, dining room plays an important role for their daily living activities, because that most of the elderly with dementia stay long during daytime. Layout of each private room and common space seems very crucial point in designing these facilities, in order to enable demented people to live their lives more independently.

• Journal of Astronomy and Space Sciences
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• v.37 no.3
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• pp.165-170
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• 2020

Muons and neutrons are representative secondary particles that are generated by interactions between primary cosmic ray particles (mostly protons) and the nuclei of atmospheric gas compounds. Previous studies reported that muons experience seasonal variations because of the meteorological effects of temperature. The intensity of neutrons has a typical modulation with various periods and reasons, such as diurnal and solar variation or transient events. This paper reports that cosmic ray particles, which were observed by neutron monitors, have seasonal variations using the daily data at the Oulu neutron monitor. To eliminate the effects of solar activity across time, the daily data were normalized by two different transformations: transformations with respect to the grand mean and yearly mean. The data after transformation with respect to the yearly mean showed more statistical stability and clear seasonal variations. On the other hand, it is difficult to determine if the seasonal variation results from terrestrial effects, such as meteorological factors, or extraterrestrial effects, such as the position of the Earth in its orbit of revolution.

• Proceedings of the Korean Institute of Interior Design Conference
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• 2007.11a
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• pp.22-25
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• 2007

The purpose is to analyze space through phenomenological features of museum space with the background of studying patterns and characteristics appearing in modern museum space based on Perceptional Phenomenology by Merleau Phonty, and then giving meanings to our daily-life space and offering new museum space. This research studies about recognizing phenomenological cognitive experiences not as conception fixed in modern museum, analyzes phenomenological particularities based on Phenomenological conception by Merleau Phonty, and studies on the features appearing in museum space by phenomenological language focusing on museums since 1990's.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.1
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• pp.42.1-42.1
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• 2021

In this study, we present a visual explanation of a deep learning solar flare forecast model and its relationship to physical parameters of solar active regions (ARs). For this, we use full-disk magnetograms at 00:00 UT from the Solar and Heliospheric Observatory/Michelson Doppler Imager and the Solar Dynamics Observatory/Helioseismic and Magnetic Imager, physical parameters from the Space-weather HMI Active Region Patch (SHARP), and Geostationary Operational Environmental Satellite X-ray flare data. Our deep learning flare forecast model based on the Convolutional Neural Network (CNN) predicts "Yes" or "No" for the daily occurrence of C-, M-, and X-class flares. We interpret the model using two CNN attribution methods (guided backpropagation and Gradient-weighted Class Activation Mapping [Grad-CAM]) that provide quantitative information on explaining the model. We find that our deep learning flare forecasting model is intimately related to AR physical properties that have also been distinguished in previous studies as holding significant predictive ability. Major results of this study are as follows. First, we successfully apply our deep learning models to the forecast of daily solar flare occurrence with TSS = 0.65, without any preprocessing to extract features from data. Second, using the attribution methods, we find that the polarity inversion line is an important feature for the deep learning flare forecasting model. Third, the ARs with high Grad-CAM values produce more flares than those with low Grad-CAM values. Fourth, nine SHARP parameters such as total unsigned vertical current, total unsigned current helicity, total unsigned flux, and total photospheric magnetic free energy density are well correlated with Grad-CAM values.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.815-819
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• 2023

Currently, China's urban space is gradually changing from gradual development to inventory transformation. The planning and development goals of urban communities have also shifted from material space construction to the direction of sustainable development of humanities and society. Currently, community planning and construction at a single latitude, which focuses on residential life, overlooks the multidimensional elements of community life production, causing many problems such as cold relationships between communities and difficulties in forming relationships between humans and the environment. Therefore, this article re-recognizes the sociality of the community in the continuous unification of the community in time and space, clarifies the central and private aspects of the community, and re-explores the dynamic creation and methods of the community as the starting point of daily life.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.11-19
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• 2012

The purpose of this study is to categorize elderly people's behavior using the questionnaire filling up by oneself for 24hours and to analyze the time required according to behavior and space. Also, through analytical researches, we find a way to develop smart home service. In this study, we carry out a questionnaire targeting a number of 20 elderly people. The questionnaire is to survey elderly people's behaviors for 24hours. Questionnaire items consist of three parts : items for checking time required about a daily behavior, items for analyzing a space in daily lives, generalities. This study is analyzed through descriptive statistics. The results of this study were as follows. Firstly, the elderly people's behaviors were eight categories. Among these behavior's categories, the highest portion is the behavior related to Individual maintenance such as sleep, personal hygiene, nap, etc. by 49%. Secondly, the portion of time required in residence based on daily lives is higher than outside of residence by 73%. Lastly, analyzing each space in residence focused on time required of elderly people's behaviors, bed room is the highest portion by 49%, and followed by living room with 29% and kitchen with 15%, and bath room with 7%.