• 한국GIS학회:학술대회논문집
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• 한국GIS학회 2003년도 공동 춘계학술대회 논문집
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• pp.291-296
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• 2003

This study estimated surface temperature by using split-window technique and NOAA/AVHRR data was used. For surface monitoring, cloud masking procedure was carried out using threshold algorithm. The daily maximum air temperature is estimated by multiple regression method using independent variables such as satellite-derived surface temperature, EDD, and latitude. When the EDD data added, the highest correlation shown. This indicates that EDD data is the necessary element for estimation of the daily maximum air temperature. We derived correlation and experience equation by three approaching method to estimate daily maximum air temperature. 1) non-considering landcover method as season, 2) considering landcover method as season, and 3) just method as landcover. The last approaching method shows the highest correlation. So cross-validation procedure was used in third method for validation of the estimated value. For all landcover type 5, the results using the cross-validation procedure show reasonable agreement with measured values(slope=0.97, intercept=-0.30, R$^2$=0.84, RMSE=4.24$^{\circ}C$). Also, for all landcover type 7, the results using the cross-validation procedure show reasonable agreement with measured values(slope=0.993, Intercept=0.062, R$^2$=0.84, RMSE=4.43$^{\circ}C$).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.943-945
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• 2003

This study is to evaluate the change of intra-abdominal pressure related with intravesical and intrarectal pressure in patients with spinal cord injury according to daily activities and postural changes which make the abdominal pressure elevated. The intravesical and the intrarectal pressures were obtained during patient's speech, sneeze, cough, valsalva and various postural changes with supine to decubitus, derubitus to supine, supine to sit, and sit to supine according to empty and full bladders, respectively. The order of higher intravesical and intrarectal pressure rise during various maneuvers were valsalva, sneeze, supine to sit and cough, respectively. Higher correlation coefficient between the intrvesical and intrarectal pressures were noted during cough, sneeze, valsalva and supine to sit in empty bladder than full one. These results demonstrated that the intravesical and intrarectal pressures were influenced by daily activities and postural changes of increasing the intra-abdominal pressure. The intrarectal pressures according to daily activities such as cough, sneeze, valsalva and postural change were significantly related with intravesical pressures.

• 한국정보시스템학회지:정보시스템연구
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• 제29권4호
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• pp.1-24
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• 2020

Purpose An increase in the number of fitness apps across the world is a testament to the growing interest in health. As focus on medical services shifted from treatment to prevention, this type of app plays an essential role in promoting one's health and exercise management. Yet little has been known about practical effects of fitness apps in existing literature thus this study searches for factors that affect daily use of fitness apps and examine the relationship between app usage and exercise patterns. Design/methodology/approach This study surveyed people who used Cashwalk, the pedometer app for a minimum of a week to analyze reasons why they used the app. Particpants' exercise patterns were also recorded. By examining survey results of fitness app users and developing a research model based on the Customer Value Theory, this study provides real-life factors to the fitness and smart health care industry that will adopt a proactive lifestyle pattern. Findings Empirical analysis proved properties such as the complexity of fitness apps, monetary rewards, exercise monitoring and the enjoyment of using fitness apps contribute to using fitness apps on a daily basis. Furthermore, more daily use of fitness apps was shown to have a greater impact on exercise. This study also confirmed that social comparison does not affect the daily use of fitness apps and the amount of exercise, and the habitual walking was proved to directly affect the amount of exercise.

• Journal of Ecology and Environment
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• 제34권2호
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• pp.149-156
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• 2011

Phenological variables derived from remote sensing are useful in determining the seasonal cycles of ecosystems in a changing climate. Satellite remote sensing imagery is useful for the spatial continuous monitoring of vegetation phenology across broad regions; however, its applications are substantially constrained by atmospheric disturbances such as clouds, dusts, and aerosols. By way of contrast, a tower-based ground remote sensing approach at the canopy level can provide continuous information on canopy phenology at finer spatial and temporal scales, regardless of atmospheric conditions. In this study, a tower-based ground remote sensing system, called the "Phenological Eyes Network (PEN)", which was installed at the Gwangneung Deciduous KoFlux (GDK) flux tower site in Korea was introduced, and daily phenological progressions at the canopy level were assessed using ratios of red, green, and blue (RGB) spectral reflectances obtained by the PEN system. The PEN system at the GDK site consists of an automatic-capturing digital fisheye camera and a hemi-spherical spectroradiometer, and monitors stand canopy phenology on an hourly basis. RGB data analyses conducted between late March and early December in 2009 revealed that the 2G_RB (i.e., 2G - R - B) index was lower than the G/R (i.e., G divided by R) index during the off-growing season, owing to the effects of surface reflectance, including soil and snow effects. The results of comparisons between the daily PEN-obtained RGB ratios and daily moderate-resolution imaging spectroradiometer (MODIS)-driven vegetation indices demonstrate that ground remote sensing data, including the PEN data, can help to improve cloud-contaminated satellite remote sensing imagery.

• 한국환경보건학회지
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• 제43권4호
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• pp.267-272
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• 2017

Objectives: The purposes of the study were to analyze the temporal variation of carbon dioxide ($CO_2$) and particulate matter (PM) in daycare centers and evaluate the appropriateness of the official test method of one-time measurement. Methods: Indoor air quality in 46 daycare centers in the Seoul Metropolitan Area was measured as specified in the official test method of Indoor Air Quality Management law. In addition, indoor air quality in the 46 daycare centers was measured over 37 days using a real-time monitor (AirGuard K). Results: The daily means of $CO_2$ and PM in the 46 daycare centers were $1042.74{\pm}134.45ppm$ and $67.60{\pm}18.25{\mu}g/m^3$, respectively. Indoor air quality in the daycare centers showed significant temporal fluctuation. Measurements for single days were significantly different from the 37-day average exposure. Relative error of short term exposure decreased with an increase in the number of sampling days. The noncompliance rate for $CO_2$ using the official testing method was 2.17%, and none exceeded the $PM_{10}$ standard of $100{\mu}g/m^3$. With monitoring over 37 days, the daily noncompliance rate for $CO_2$ was 50.4% and the daily noncompliance rate for PM was 13.8%. Conclusions: When the official test method evaluates the indoor air at daycare centers one day per year, the results may not represent actual indoor air quality over a longer period of time. Real-time monitoring devices could be an alternative for managing indoor air quality.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.265-269
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• 2008

Home health care with compact wearable units sounds to be a convenient solution for the elderly people living independently. This paper presents a method to detect fall from the other activities of daily living and also to classify those activities. This kind of ambulatory monitoring enables them to get an emergency help in the case of the fatal fall event and can provide their general health status by observing the activities being performed in daily life. A tri-axial accelerometer sensor is used to get the acceleration anomalies associated with the user's movements. The three axis acceleration data are transferred to the base station sensor node via an IEEE 802.15.4 compliant zigbee module. The base station sensor node sends the data to base station PC for an offline processing. This work shows the feature set preparation using the principal component analysis (PCA) for the designing of neural network. The work includes the most common activities of daily living (ADL) like Rest, Walk and Run along with the detection of fall events from ADL. The angle from the vertical is found to be the most significant feature parameter for classification of fall while mean, standard deviation and FFT coefficients were used as the feature parameter for classifying the other activities under consideration. The accuracy for detection of fall events is 86%. The overall accuracy for ADL and fall is 94%.

• 한국농림기상학회지
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• 제3권3호
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• pp.156-162
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• 2001

In order to monitor local climatic information, twelve automated weather stations (AWS) were installed in alpine area by the Alpine Agricultural Experiment Station, Rural Development Administration (RDA), at the field of major crop located in around highland area, and collected data from 1993 to 2000. Hourly measurements of air and soil temperature (underground 10 cm,20 cm), relative humidity, wind speed and direction, precipitation, solar radiation and leaf wetness were automatically performed and the data could be collected through a public phone line. Datalogger was selected as CR10X (Campbell scientific, LTD, USA) out of consideration for sensers' compatibility, economics, endurance and conveniences. All AWS in alpine area were combined for net work and daily climatic data were analyzed in text and graphic file by program (Chumsungdae, LTD) on 1 km $\times$ 1 km grid tell basis. In this analysis system, important multi-functionalities, monitoring and analysis of local climatic information in alpine area was emphasized. The first objective was to obtain the output of a real time data from AWS. Secondly, daily climatic normals for each grid tell were calculated from geo-statistical relationships based on the climatic records of existing weather stations as well as their topographical informations. On 1 km $\times$ 1 km grid cell basis, real time climatic data from the automated weather stations and daily climatic normals were analyzed and graphed. In the future, if several simulation models were developed and connected with this system it would be possible to precisely forecast crop growth and yield or plant disease and pest by using climatic information in alpine area.

• 한국물환경학회지
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• 제27권5호
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• pp.572-579
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• 2011

We have examined the runoff characteristics of nonpoint source (NPS) in fields. Two monitoring sites were equipped with an automatic velocity meter and water sampler. Monitoring was conducted at fields 1 and field 2 during the rainfall event. Ten rainfall-runoff events were monitored and analyzed during the study period. The results show that runoff occurred if daily rainfall and intensity were higher than 40 mm and 1.6 mm/hr except a few extreme rainfall events with very high intensity. Runoff of field 1 was approximately twice of that of field 2. Event mean concentrations (EMC) and pollution load of analyzed water quality indices were also higher in field 2 than in field 1. Especially, TN load from field 2 was $75.4 mg/m^2$ and was about 5 times higher than that from field 1. Analysis of Pearson correlation coefficient of water quality parameter indicates that besides of TN all items in fields 1 have tight relationship respectively (p < 0.01). But those of fields 2 have a significant (p < 0.05). Estimating units loading of NPS, we suggested that variable such as soil texture, rainfall amount and intensity and slope were needed to be considered from agricultural landuses. The results of this study can be used as a basic data in the development and implementation of total maximum daily loads (TMDL) in Korea.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.173-177
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• 2009

일상생활에서 활용 가능한 다양한 종류의 생체 신호 획득 및 분석 방법이 연구되고 있다. 기존의 생체 신호 분석 방법은 표준화된 임계치를 사용하여 해석한 결과를 제공하며 신호 측정 당시의 상황이 고려되지 않아 잡음 혹은 외부 환경의 영향을 받기 쉬운 단점이 있다. 본 논문에서는 생체 신호뿐만 아니라 기타 정황정보를 기반으로 하여 개인화된 신호를 분석하기 위한 모델(Personalized Decision Making method, PDM)을 제안한다. 개인화된 신호 해석 모델은 사용자의 맥락 정보, 사용자의 맥락 정보, 사용자의 나이, 성별, 현재의 몸 및 정신 상태, 음식 및 카페인의 섭취 여부, 측정 시간 및 측정 요일 등을 기반으로 각 맥락 간의 연관 관계를 나타내고, 이상적인 사용자의 생체 신호 예측치를 베이즈 정리를 기반으로 획득한다. 개인화된 해석 모델(ACM)을 통해 표준 임계치를 적용한 해석에 비해 인식의 정확도를 높일 수 있으며, 다양한 측정시의 조건을 알면 현재 사용자의 건강상태를 개인화된 분석과 유사한 정확도로 예측이 가능하다. 제안한 방법은 현재 관측된 관측치의 분포를 모르더라도, 현재 사용자의 상태를 맥락정보를 기반으로 하여 예측할 수 있으므로, 일반적인 데이터 모델을 기반으로 개개인에 맞는 얼굴 표정을 인식하는 연구 등에 활용이 가능하다.

• Journal of Computing Science and Engineering
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• 제5권3호
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• pp.246-256
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• 2011

Due to the increasingly aging population, there is a rising demand for assistive living technologies for the elderly to ensure their health and well-being. The elderly are mostly chronic patients who require frequent check-ups of multiple vital signs, some of which (e.g., blood pressure and blood glucose) vary greatly according to the daily activities that the elderly are involved in. Therefore, the development of novel wearable intelligent systems to effectively monitor the vital signs continuously over a 24 hour period is in some cases crucial for understanding the progression of chronic symptoms in the elderly. In this paper, recent development of Wearable Intelligent Systems for e-Health (WISEs) is reviewed, including breakthrough technologies and technical challenges that remain to be solved. A novel application of wearable technologies for transient cardiovascular monitoring during water drinking is also reported. In particular, our latest results found that heart rate increased by 9 bpm (P < 0.001) and pulse transit time was reduced by 5 ms (P < 0.001), indicating a possible rise in blood pressure, during swallowing. In addition to monitoring physiological conditions during daily activities, it is anticipated that WISEs will have a number of other potentially viable applications, including the real-time risk prediction of sudden cardiovascular events and deaths.