• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.227-232
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• 2011

The QRS complex in ECG analysis is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. This paper presents the preprocessor method to detect R-peak, RR interval, and HRV in wireless sensor node. The derivative of the electrocardiogram is efficiency of preprocessing method for resource hungry wireless sensor node with low computation. We have implemented R-peak and RR interval detection application based on dECG for wireless sensor node. The sensor node only transfers meaning parameter of ECG. Thus, implementation of sensor node can save power, reduce traffic, and eliminate congestion in a WSN.

• Ocean and Polar Research
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• v.39 no.2
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• pp.73-84
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• 2017

The probability distribution of ichthyoplankton is important for enhancing the precision of sampling while reducing unnecessary surveys. To estimate the ichthyoplankton detection proportion (IDP) and its margin of error (ME), the monitoring information of the chub mackerel's (Scomber japonicus) ichthyoplankton presence-absence sampling data has been were collected over approximately 30 years (from 1982 to 2011) in the Korean coastal seas. Based on the computed spatial distributions of the mackerel's IDP and ME, the confidence interval (CI) range, defined as 2 ME, decreases from approximately 80% to 40% as the sample size n increases from 4 to 24 and the ME is approximately 40% in the typical (seasonal survey) case n = 4 per year. The IDP and ME off Jeju Island are relatively high at the 0.5-degree smoothing level. After increasing the spatial smoothing level to 1.0-degree, the ME decreased, and the spatial distribution pattern also changed due to the over-smoothing effects. In this study, the 0.5-degree smoothing is more suitable for the distribution pattern than the 1.0-degree smoothing level. The area of the high IDP and the low ME on the mackerel's ichthyoplankton was similar to the estimated spawning ground in the Korean peninsula. This information could contribute to enhancing for the spawning ecology surveys.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.136-142
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• 2014

Distinct features in heart rate signals during the driver's wake and sleep states could provide an initiative for the development of a safe driving systems such as drowsiness detecting sensor in a smart wheel. We measured ECG from health subjects ($23.5{\pm}2.5$ in age) during the wake and drowsiness states. The proposed method is able to detect R waves and R-R interval calculation in the ECG even when the signal includes in abnormal signals. Heart rate variability(HRV) was investigated for the time domain and frequency domains. The STD HR(0.029), NN50(0.044) and VLF power(0.0018) of the RR interval series of the subjects were significantly different from those of the control group (p < 0.05). In conclusion, there are changes in heart rate from wake to drowsiness that are potentially to be detected. The results in our study could be useful for the development of drowsiness detection sensors for effective real-time monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.627-633
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• 2007

This paper describes position tracking system of a container trailer approaching to a gantry crane for loading or unloading a container into or from a ship, respectively. Proposed position tracking system informs the trailer driver of right position to stop the car under a gantry crane. To measure the location of a trailer, we used Cricket Mote modules which adopted RF and ultrasound technology. We present an elaborate method to improve position errors occurring at sensing and calculate three dimensional position by triangulation along with how to reduce location tracking interval for real-time monitoring. The location information was transmitted to a Personal Digital Assistant (PDA) periodically through Bluetooth communication for guidance of the trailer driver. In indoor and outdoor tests, position errors were less than 3 cm and location tracking interval was 0.5 second on average.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.6
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• pp.615-622
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• 2017

This study was conducted to evaluate the odor reduction efficacy of the dip injection wet scrubber (DIWS) using tap water as washing fluid. The $NH_3$ and $H_2S$ removal efficiency of 7 day batch operated DIWS was evaluated twice over a total of 14 days of experiment. The $NH_3$ removal efficiency ranged from 26 to 37%. The $H_2S$ removal efficiency was between 22 and 30%. The pH of the washing fluid maintained below 8 and the $NH_4{^+}$ concentration tended to keep constant around 350 ppm after 5 days of washing-fluid replacement. Therefore, the 5-day washing fluid replacement interval is more preferable than the 7-day interval. The $NH_4{^+}$ concentration and the electrical conductivity (EC) showed a high correlation. The EC measurement can be used as an alternative to conventional $NH_4{^+}$ concentration measurement method for real time monitoring of washing fluid condition.

• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.983-991
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• 2003

The Web-based instruction on the internet provides lots of learners with the related information and knowledge beyond time and space. But in the Web-based instruction, there is a problem that the teaming process statuses for learners can be known only through an exam. This paper introduces a web monitoring method to check whether the learner has some problems in learning process and to be able to find out the students with the problems. In the method this paper proposes a learning time prediction model for predicting the proper next study time intervals based on the learner`s learning times and grades on Previous learning units. This method provides the educator with the learning Process statuses for learners. The Loaming prediction model for web-based monitoring can be used to stimulate learners to take the good teaming processes by sending automatically alerting messages if their real teaming times exceeds on his predicted learning time interval. The results of the estimation through case study on the web-based monitoring to use the teaming time prediction model show that most of on-line learners with Poor teaming process statuses get poor grades. In addition, the results show that learner`s poor habits keep going on without change.

• Journal of Advanced Navigation Technology
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• v.18 no.4
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• pp.278-287
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• 2014

ADS-B is a newly developed air surveillance technology to address the consistently increasing air traffic needs. ADS-B attracts attention for replacing or complementing a conventional radar since ADS-B can provide more accurate position information with a shorter interval when compared to the radar. However, as ADS-B uses wireless data links on exchanging information between an aircraft and a ground ADS-B system, and uses protocols without integrity support on exchanging information within the ground ADS-B system, a system which can monitor the operational status of an ADS-B system is essential. In this work, we design and implement an ADS-B monitoring system capable of displaying air traffic situation that can show the comprehensive air traffic situation while monitoring the operational status of the ADS-B system. The implemented ADS-B monitoring system has been verified with a configured ADS-B ground system by displaying ADS-B surveillance data, radar surveillance data, and flight information after receiving live surveillance data of in flight aircrafts, and virtual flight information data.

• Journal of Energy Engineering
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• v.8 no.4
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• pp.605-611
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• 1999

Conventional methods for assessing remaining life of critical high temperature components in fossil power plants rely on nondestructive inspection practices and accompanying life analysis based on fracture mechanics By using these conventional methods. It has been difficult to perform uninterrupted in-service inspection for life prediction. Thus, efforts have been made for developing on-line remaining life monitoring systems employing information on the shape of structures, operating variables and material properties. In thus study, a software for on-line life monitoring system which performs real-time life evaluation of a high temperature system headers was developed. The software is capable of evaluating creep and fatigue life usage from the real-time stress data calculated by using temperatures/stress transfer Green functions derived in advance for the specific headers. The major benefits of the developed software life in determining future operating schedule, inspection interval, and replacement plan by monitoring real-time life usage based on prior operating history.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.675-687
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• 2010

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.333-344
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• 2021

Technique for the long-gap filling that occur frequently in ocean monitoring data is developed. The method estimates the unknown values of the long-gap by the summation of the estimated trend and selected residual components of the given missing intervals. The method was used to impute the data of the long-term missing interval of about 1 month, such as temperature and water temperature of the Ulleungdo ocean buoy data. The imputed data showed differences depending on the monitoring parameters, but it was found that the variation pattern was appropriately reproduced. Although this method causes bias and variance errors due to trend and residual components estimation, it was found that the bias error of statistical measure estimation due to long-term missing is greatly reduced. The mean, and the 90% confidence intervals of the gap-filling model's RMS errors are 0.93 and 0.35~1.95, respectively.