• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.336-339
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• 2007

A new query model is required to match requirements of stream-based applications such as patient monitoring system, since traditional DBMSs are not designed to provide continuous queries over stream data. In the patient monitoring system, there are many types of biomedical signals such as blood pressure and temperature, and these signals gathered by biomedical sensors should be treated as a stream, that is an ordered set of signals. In this paper, we categorized all possible queries to be used in patient monitoring system by four types of queries. Then, we have proposed a new sliding window query model which is capable of expressing these four types of queries.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.2008-2016
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• 2014

With the increased attention about health care and management of heart diseases, ubiquitous healthcare services and related devices have been actively developed recently. In this paper we developed a mobile healthcare system which consists of smartphone and patch-type ECG measuring device. This system is capable of monitoring, storing, and sending bio signals such as ECG, heart rate, heart rate variability as well as exercise management functions through heart rate zones. With monitoring bio signal continuously by mobile healthcare system and wearable device like us, people can prevent chronic disease and maintain good health. Here we report our implementation results on real platforms.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.470-474
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• 2007

U-healthcare는 종래의 헬스케어 영역에 유비쿼터스 기술을 접목하여 개인의 건강상태 관리를 도와주는 서비스이다. 이의 기반이 되는 기술인 질환 유무를 판별하는 기법은 그 동안 헬스케어 영역에 적용시켜 왔다. 하지만, 적시에 언제 어디서나 지속적인 모니터링이 요구되는 U-health환경에서는 기존의 기계학습기법을 그대로 적용하는 데에는 어려움이 있다. 본 논문에서는 통계기반의 질환 유무 판별 기법을 제안한다. 본 판별 기법은 질환 판별에 이용되는 생체신호와 신체증상의 종류로 배열 구조를 설정하고 축적된 데이터로부터 생체신호와 신체증상간의 쌍에 누적 빈도 수를 기록하여 학습한 뒤 고안한 판별식을 적용시켜 사용자의 질환을 판별하는 기법이다. 제한적인 검증이지만 약 360명의 실제 환자 데이터를 이용하여 기법을 검증하였고, 빠른 속도와 지속적인 개선이 가능한 기법임을 알 수 있었다. 추후 정확한 데이터를 기반으로 다른 기법과의 비교 검증으로 엄밀한 검증이 요구된다.

• Journal of Biomedical Engineering Research
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• v.22 no.2
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• pp.187-195
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• 2001

시각자극 유발전위 추론시에 사용되는 평균법은 많은 회수의 단일-시도 유발전위(single-trial evoked potential)의 기록이 필요하다. 본 논문에서는 이러한 평균법의 후처리기로서 Prony 방법을 적용하여 향상된 신호-대-잡음비를 제공하는 방법을 제안하였다. Prony 방법은 유발전위와 같은 잡음이 섞여 있는 신호에서 지수함수를 추론하는데 많이 적용되어져 왔다. 여러 가지 잡음 모델을 이용한 시뮬레이션과 실제 시각자극 유발전위 데이터를 이용한 실험을 통해 Prony 방법이 평균법의 후처리기(post-processor) 기능으로서 사용될 때, 신호의 질적인 향상 측면 뿐 아니라 평균법 사용시 단일-시도 유발전위의 기록 횟수의 단축이라는 결과도 가져옴을 보였다.

• Horticultural Science & Technology
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• v.34 no.1
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• pp.77-83
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• 2016

The measurement of total fresh weight of plants provides an essential indicator of crop growth for monitoring production. To measure fresh weight without damaging the vegetation, image-based methods have been developed, but they have limitations. In addition, the total plant fresh weight is difficult to measure directly in hydroponic cultivation systems because of the amount of nutrient solution. This study aimed to develop a real-time, precise method to measure the total fresh weight of Romaine lettuce (Lactuca sativa L. cv. Asia Heuk Romaine) with growth stage in a plant factory using a nutrient film technique. The total weight of the channel, amount of residual nutrient solution in the channel, and fresh shoot and root weights of the plants were measured every 7 days after transplanting. The initial weight of the channel during nutrient solution supply (Wi) and its weight change per second just after the nutrient solution supply stopped were also measured. When no more draining occurred, the final weight of the channel (Ws) and the amount of residual nutrient solution in the channel were measured. The time constant (${\tau}$) was calculated by considering the transient values of Wi and Ws. The relationship of Wi, Ws, ${\tau}$, and fresh weight was quantitatively analyzed. After the nutrient solution supply stopped, the change in the channel weight exponentially decreased. The nutrient solution in the channel slowly drained as the root weight in the channel increased. Large differences were observed between the actual fresh weight of the plant and the predicted value because the channel included residual nutrient solution. These differences were difficult to predict with growth stage but a model with the time constant showed the highest accuracy. The real-time fresh weight could be calculated from Wi, Ws, and ${\tau}$ with growth stage.

• The Journal of the Korea Contents Association
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• v.11 no.8
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• pp.14-22
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• 2011

It is important for the strategy of service to provide the health information in the environment that the healthcare has been changed focusing on the preventive medicine. Recently, the various applications of u-healthcare have been presented by researchers. In this paper, we proposed the health information monitoring system using the context sensors based band. By wearing the proposed hand, the health status is gathered and vital signals are transmitted to the connected UMPC. It can be easily monitored according to the user locations in real time. To provide the health index according to the temperature, the air conditioning, the illumination, the humidity, and the ultraviolet rays, we use the various XML links extracted from RSS of the Korea Meteorological Administration. The health information is analyzed in terms of factors, such as, the asthma index, the stroke index, the skin disease index, the pulmonary disease index, the pollen concentration index, and the city high temperature index. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed system. Accordingly, the satisfaction and the quality of services will be improved the healthcare.

• The Magazine of the IEIE
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• v.33 no.3 s.262
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• pp.49-55
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• 2006

인간과 로봇의 자연스러운 상호작용을 위하여 영상과 음성을 기반으로 한 인간-로봇 상호작용 (HRI: Human Robot Interaction) 기술들을 소개한다. URC개념의 서버/클라이언트 구조를 갖는 소프트웨어 로봇에 수행 가능한 얼굴 인식 및 검증, 준 생체정보(semi biometrics)를 이용한 사용자 인식, 제스처인식, 화자인식 및 검증, 대화체 음성인식 기술들에 대하여 살펴본다. 이러한 인간-로봇 상호작용 기술들은 초고속 인터넷과 같은 IT 인프라를 이용하는 URC(Ubiquitous Robotic Companion) 기반의 지능형 서비스 로봇을 위한 핵심기술로서 사용되어진다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.685-691
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• 2020

Standard values for fetal bio index measurements should be applied differently depending on the past present and general characteristics of the target population. Therefore, we tried to predict the number of gestational week(GA) and analyze the differences by country based on the measurements of Korean fetal bio index. 480 fetal bio index measurements between 15~38 weeks of pregnancy using ultrasound were compared retrospectively with USA ad Japanese data. One Way ANOVA was used for the analysis of differences by country, and quadratic regression model was designed to predict the GA of fetal bio index in order to predict the standard pregnancy number of Korean fetuses(p<0.005). Mean difference in the 95% confidence interval is BPD was Korea and USA 0.17, Korea and Japan 0.11, AC was Korea and USA -0.35, Korea and Japan 0.42, FL was Korea and USA -0.18, Korea and Japan 0.14. Therefore, fetal bio index for GA predict is considered to be the standard of the fetal growth assessment by applying the country specific standard in consideration of differences between races.

• Journal of Bio-Environment Control
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• v.27 no.4
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• pp.424-430
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• 2018

This study was carried out to estimate growth characteristics of hot pepper and to develop predicted models for the production yield based on the growth parameters and climatic elements. Sigmoid regressions for the prediction of growth parameters in terms of fresh and dry weight, plant height, and leaf area were designed with growing degree days (GDD). The biomass and leaf expansion of hot pepper plants were rapidly increased when 1,000 and 941 GDD. The relative growth rate (RGR) of hot pepper based on dry weight was formulated by Gaussian's equation RGR $(dry\;weight)=0.0562+0.0004{\times}DAT-0.00000557{\times}DAT^2$ and the yields of fresh and dry hot pepper at the 112 days after transplanting were estimated 1,387 and 291 kg/10a, respectively. Results indicated that the growth and yield of hot pepper were predicted by potential growth model under plastic tunnel cultivation. Thus, those models need to calibration and validation to estimate the efficacy of prediction yield in hot pepper using supplement a predicting model, which was based on the parameters and climatic elements.