• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.336-339
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• 2012

Accurate forecasting of pan evaporation (PE) is very important for monitoring, survey, and management of water resources. The purpose of this study is to develop and apply Kohonen self-organizing feature maps neural networks model (KSOFM-NNM) to forecast the daily PE for the dry climate region in south western Iran. KSOFM-NNM for Ahwaz station was used to forecast daily PE on the basis of temperature-based, radiation-based, and sunshine duration-based input combinations. The measurements at Ahwaz station in south western Iran, for the period of January 2002 - December 2008, were used for training, cross-validation and testing data of KSOFM-NNM. The results obtained by TEM 1 produced the best results among other combinations for Ahwaz station. Based on the comparisons, it was found that KSOFM-NNM can be employed successfully for forecasting the daily PE from the limited climatic data in south western Iran.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.263-274
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• 2016

The exceptional development of electronic device technology, the miniaturization of mobile devices, and the development of telecommunication technology has made it possible to monitor human biometric data anywhere and anytime by using different types of wearable or embedded sensors. In daily life, mobile devices can collect wireless body area network (WBAN) data, and the co-collected location data is also important for disease analysis. In order to efficiently analyze WBAN data, including location information and support medical analysis services, we propose a geohash-based spatial index method for a location-aware WBAN data monitoring system on the NoSQL database system, which uses an R-tree-based global tree to organize the real-time location data of a patient and a B-tree-based local tree to manage historical data. This type of spatial index method is a support cloud-based location-aware WBAN data monitoring system. In order to evaluate the proposed method, we built a system that can support a JavaScript Object Notation (JSON) and Binary JSON (BSON) document data on mobile gateway devices. The proposed spatial index method can efficiently process location-based queries for medical signal monitoring. In order to evaluate our index method, we simulated a small system on MongoDB with our proposed index method, which is a document-based NoSQL database system, and evaluated its performance.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.5
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• pp.583-591
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• 2004

In this study, methodologies for the rational organization of air pollution monitoring network were examined by understanding the characteristics of temporal and spatial distribution of secondary air pollution, whose significance would increase hereafter. The data on $O_3$ and $NO_2$ concentrations during high ozone period in 1998~1999 recorded at the nine air pollution monitoring station in Busan were analysed using principal component analysis (PCA) and cumulative semivariogram. It was found that the ozone concentration was deeply associated with the daily emission characteristics or the $O_3$ precusors, and nitrogen dioxide concentration largely depends on the emission strength of regional sources. According to the spatial distribution analysis of ozone and nitrogen dioxide in Busan using cumulative semivariograms, the number of monitoring stations for the secondary air pollution can be reduced in east-west direction, but reinforced in north-south direction to explain the spacial variability. More scientific and rational relocation of air pollution monitoring network in Busan would be needed to investigate pollution status accurately and to plan and implement the pollution reduction policies effectively.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.808-817
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• 2016

Recently, the wearable computing technology with bio-sensors has been rapidly developed and utilized in various areas such as personal health, care-giving for senior citizens who live alone, and sports activities. In particular, the wearable computing equipment to measure vital signs by means of digital yarns and bio sensors is noticeable. The wearable computing devices help users monitor and manage their health in their daily lives through the customized healthcare service. In this paper, we suggest a system for monitoring and analyzing vital signs utilizing smart healthcare clothing with bio-sensors. Vital signs that can be continuously acquired from the clothing is well-known as unstructured data. The amount of data is huge, and they are perceived as the big data. Vital sings are stored by Hadoop Distributed File System(HDFS), and one can build data warehouse for analyzing them in HDFS. We provide health monitoring system based on vital sings that are acquired by biosensors in smart healthcare clothing. We implemented a big data platform which provides health monitoring service to visualize and monitor clinical information and physical activities performed by the users.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.834-837
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• 2005

In this paper, we describe the method of non-invasive blood pressure measurement using pulse wave transit time(PWTT). PWTT is a new parameter involved with a vascular that can indicate the change of BP. PWTT is measured by continuous monitoring of ECG and pulse wave. No additional sensors or modules are required. In many cases, the change of PWTT correlates with the change of BP. We measure pulse wave using the photo plethysmograph(PPG) sensor in an earlobe and we measure ECG using the ECG monitoring device our made in the chest. The measurement device for detecting pulse wave consists of infrared LED for transmitted light illumination, pin photodiode as light detector, amplifier and filter. We composed 0.5Hz high pass, 60Hz notch and 10Hz low pass filter. ECG measurement device consists of multiplexer, amplifier, filter, micro-controller and RF module. After amplification and filtering, ECG signal and pulse wave is fed through micro-controller. We performed the initial work towards the development of ambulatory BP monitoring system using PWTT. An earlobe is suitable place to measure PPG signal without the restraint in daily work. From the results, we can know that the dependence of PWTT on BP is almost linear and it is possible to monitoring an individual BP continuously after the individual calibration.

• The Korean Journal of Rehabilitation Nursing
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• v.18 no.2
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• pp.107-117
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• 2015

Purpose: This study was conducted to identify the effects of a self-monitoring rehabilitation program based on the Bandura's self-efficacy theory on the activities of daily living (ADL), 6-minute walking distances, self-efficacy and quality of life (QoL) among stroke patients after three to six months. Methods: The participants consisted of 29 patients in the experiment group and 28 patients in the control group who admitted at rehabilitation specific hospital. Self-monitoring program developed by the researcher lasted twice a week for 8 weeks from August to September, 2013. Results: ANCOVA showed that all of dependent variables of this study, ADL and 6-minute walking distances as a physical function, self-efficacy and QoL for intervention group were higher than those for control group(p<.001). Conclusion: The self-monitoring rehabilitation program based on the self-efficacy theory was found to be effective in improving physical function, self-efficacy and QoL for early post-stroke patients. Early rehabilitation program for stroke patients was recommended to consider the self-monitoring of current physical and psychosocial status as a strategy of self-management.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.240-242
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• 2001

On this research, to catch up with international trend on the power system utilities move to be digitalized and move to network is certainly technological on the global business world, to compete with advanced foreign countries in the range of transmit and distribute power system and to take possession of first market share within country, we talked over a monitoring system to diagnose, monitor ACB(Air Circuit Breaker) only which is operated on the low level voltage Power plant. AMS(ACB Monitoring System) have be configured with several modules such as engine module which acquire engineering data from HICM360/860(Communication Control Units) and analyze and save it, database module which restore data and can be inquired, system monitoring view module which reflects fields information within a second, realtime trend window, historical trend window, reports as daily and yearly. In a near future, AMS must upgrade GUI to have easy to handle and have to have a field test to fit on real plants, so it will have faith in system reliability as it can apply power plant monitoring system in wide.

• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.345-365
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• 2020

At present, many machine leaning and data mining methods are used for analyzing and predicting structural response characteristics. However, the platform that combines big data analysis methods with online and offline analysis modules has not been used in actual projects. This work is dedicated to developing a multifunctional Hadoop-Spark big data platform for bridges to monitor and evaluate the serviceability based on structural health monitoring system. It realizes rapid processing, analysis and storage of collected health monitoring data. The platform contains offline computing and online analysis modules, using Hadoop-Spark environment. Hadoop provides the overall framework and storage subsystem for big data platform, while Spark is used for online computing. Finally, the big data Hadoop-Spark platform computational performance is verified through several actual analysis tasks. Experiments show the Hadoop-Spark big data platform has good fault tolerance, scalability and online analysis performance. It can meet the daily analysis requirements of 5s/time for one bridge and 40s/time for 100 bridges.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.48-50
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• 2005

Urodynamics describes a collection of tests designed to evaluate lower urinary tract function and can be performed using retrograde filling of the bladder within a room. In this study, we designed and calibrated the potable urodynamics monitoring system using DSP chip (TMS320VC33, Texas Instrument$^{TM}$, U.S.) and collected pressure and EMG using calibration kit (DPT9022K0122, Medtronics$^{TM}$, U.S.). This system can make patients more comportable and monitor spontaneous urination during daily life.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.199-206
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• 2013

An emergency monitoring system for the elderly, which uses acceleration data measured with an accelerometer, angular velocity data measured with a gyroscope, and heart rate measured with an electrocardiogram, is proposed. The proposed fall detection algorithm uses multiple parameter combinations in which all parameters, calculated using tri-axial accelerations and bi-axial angular velocities, are above a certain threshold within a time period. Further, we propose an emergency detection algorithm that monitors the movements of the fallen elderly person, after a fall is detected. The results show that the proposed algorithms can distinguish various types of falls from activities of daily living with 100% sensitivity and 98.75% specificity. In addition, when falls are detected, the emergency detection rate is 100%. This suggests that the presented fall and emergency detection method provides an effective automatic fall detection and emergency alarm system. The proposed algorithms are simple enough to be implemented into an embedded system such as 8051-based microcontroller with 128 kbyte ROM.