• Journal of the Korea Institute of Military Science and Technology
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• v.10 no.3
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• pp.129-138
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• 2007

Recently, Direction Finding(DF) System is using switching DF algorithm to reduce system-weight by eliminating RF cable as much as possible. Also, Correlation Vector Direction Finding(CVDF) algorithms is being used for Fast Direction finding in tactical environment. In this paper, I will give you burst error elimination algorithms and compare the performance in case we use switching CVDF algorithm. Although antenna array is not working, we will successfully perform direction finding when we use this burst error elimination algorithms. Also, we will be completely capable of DF mission despite of meeting the unwanted situation that the monitoring signal disappear in case we use Switching Direction Finding algorithms. That situation frequently occurs under the Frequency Hopping signal circumstances.

• Journal of information and communication convergence engineering
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• v.3 no.2
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• pp.90-92
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• 2005

As the result of the study shows, Round Robin Algorithm allows servers to ensure definite traffic distribution, unless incoming data loads differ much. Although error levels are high in some cases, they were eventually alleviated by repeated tests for a long period of time. The study uses two software packages (Packet Capture and Round Robin Test Package) to check packet volume from Virtual Network Structure (data generator, virtual server, Server 1, 2, 3), and finds out traffic distribution toward Server 1, 2, and 3. The functions of implemented Round Robin Load Balancing Monitoring System include round robin testing, system monitoring, and graphical indication of data transmission and packet volume.

• Progress in Medical Physics
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• v.32 no.2
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• pp.40-49
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• 2021

Purpose: This study aimed to develop a surface-guided radiosurgery system customized for a neurosurgery clinic that could be used as an auxiliary system for improving the accuracy, monitoring the movements of patients while performing hypofractionated radiosurgery, and minimizing the geometric misses. Methods: RGB-D cameras were installed in the treatment room and a monitoring system was constructed to perform a three-dimensional (3D) scan of the body surface of the patient and to express it as a point cloud. This could be used to confirm the exact position of the body of the patient and monitor their movements during radiosurgery. The image from the system was matched with the computed tomography (CT) image, and the positional accuracy was compared and analyzed in relation to the existing system to evaluate the accuracy of the setup. Results: The user interface was configured to register the patient and display the setup image to position the setup location by matching the 3D points on the body of the patient with the CT image. The error rate for the position difference was within 1-mm distance (min, -0.21 mm; max, 0.63 mm). Compared with the existing system, the differences were found to be as follows: x=0.08 mm, y=0.13 mm, and z=0.26 mm. Conclusions: We developed a surface-guided repositioning and monitoring system that can be customized and applied in a radiation surgery environment with an existing linear accelerator. It was confirmed that this system could be easily applied for accurate patient repositioning and inter-treatment motion monitoring.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.227-236
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• 2005

We study, in terms of VoIP user assessment of voice quality, the synchronization of measurement system is important. Commonly the synchronization system uses NTP(Network Time Protocol) or GPS(Global Positioning System), these synchronization method has time error of distance, system overhead of data processing, and system specialized clock error. we propose and implement the synchronization method to correct time error between two measurement system in the internet. So the time synchronization of systems can get time error, then user assessment of voice quality become reliable.

• Journal of Biosystems Engineering
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• v.18 no.1
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• pp.37-47
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• 1993

This study was conducted to develop the on-line monitoring system for plant growth responses. The system consisted of two parts. One system was the measuring system and the other was its controlling system. The established measuring systems were the ultrasonic wave sensor driver for height of plant, the potentiometer for diameter of plant stem, and the weighing system with strain gage application for plant weight. Also, computer program for measurement and controlling was developed, and the whole system was tested by the fabricated plant, and the actual plant growth responses were monitored by the system. When monitoring the actual plant growth responses, even the small amount of plant growth resposes could be measured by the system within tolerable error ranges.

• Journal of Korean Society of Rural Planning
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• v.21 no.4
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• pp.177-186
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• 2015

The main objective of this study was to assess the applicability of IoT (Internet of Things)-based flood management under climate change by developing intelligent water level monitoring platform based on IoT. In this study, Arduino Uno was selected as the development board, which is an open-source electronic platform. Arduino Uno was designed to connect the ultrasonic sensor, temperature sensor, and data logger shield for implementing IoT. Arduino IDE (Integrated Development Environment) was selected as the Arduino software and used to develop the intelligent algorithm to measure and calibrate the real-time water level automatically. The intelligent water level monitoring platform consists of water level measurement, temperature calibration, data calibration, stage-discharge relationship, and data logger algorithms. Water level measurement and temperature calibration algorithm corrected the bias inherent in the ultrasonic sensor. Data calibration algorithm analyzed and corrected the outliers during the measurement process. The verification of the intelligent water level measurement algorithm was performed by comparing water levels using the tape and ultrasonic sensor, which was generated by measuring water levels at regular intervals up to the maximum level. The statistics of the slope of the regression line and $R^2$ were 1.00 and 0.99, respectively which were considered acceptable. The error was 0.0575 cm. The verification of data calibration algorithm was performed by analyzing water levels containing all error codes in a time series graph. The intelligent platform developed in this study may contribute to the public IoT service, which is applicable to intelligent flood management under climate change.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.99-109
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• 2012

This study aimed to develop a Structural Health Monitoring System for steel beams in the manner of suggesting and verifying a theoretical formula for displacement estimation using strain gauges, and estimating the loading points and magnitude. According to the results of this study, it was found that when a load of 160kN (56% of the yield load) was applied, the error rate of the deflection obtained with a strain gauge at the point of maximum deflection compared to the deflection measured with a displacement meter was within 2%, and that the estimates of the magnitude and points of load application also showed the error rate of not more than 1%. This suggests that the displacement and load of steel beams can be measured with strain gauges and further, it will enable more cost-effective sensor designing without displacement meter or load cell. The Structural Health Monitoring System program implemented in Lab VIEW gave graded warnings whenever the measured data exceeds the specified range (strength limit state, serviceability limit state, yield strain), and both the serviceability limit state and strength limit state could be simultaneously monitored with strain gauge alone.

• Journal of Drive and Control
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• v.21 no.2
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• pp.36-43
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• 2024

The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.133-142
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• 2007

The Electric Power Research Institute (EPRI) demonstrated a method for monitoring the performance of instrument channels in Topical Report (TR) 104965, 'On-Line Monitoring of Instrument Channel Performance.' This paper presents the results of several models originally developed by EPRI to monitor three nuclear plant sensor sets: Pressurizer Level, Reactor Protection System (RPS) Loop A, and Reactor Coolant System (RCS) Loop A Steam Generator (SG) Level. The sensor sets investigated include one redundant sensor model and two non-redundant sensor models. Each model employs an Auto-Associative Kernel Regression (AAKR) model architecture to predict correct sensor behavior. Performance of each of the developed models is evaluated using four metrics: accuracy, auto-sensitivity, cross-sensitivity, and newly developed Error Uncertainty Limit Monitoring (EULM) detectability. The uncertainty estimate for each model is also calculated through two methods: analytic formulas and Monte Carlo estimation. The uncertainty estimates are verified by calculating confidence interval coverages to assure that 95% of the measured data fall within the confidence intervals. The model performance evaluation identified the Pressurizer Level model as acceptable for on-line monitoring (OLM) implementation. The other two models, RPS Loop A and RCS Loop A SG Level, highlight two common problems that occur in model development and evaluation, namely faulty data and poor signal selection

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.1
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• pp.11-17
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• 2008

Typical wireless sensor networks used in structural monitoring are continuous types wherein data transmission is progressive at all time that may include irrelevant and insignificant data and information. Continuous types of wireless monitoring systems often pose problems of handling large-sized data that may deteriorate the performance of the system. The proposed method is to suggest an event-triggered monitoring system that captures and transmits relevant data only. An error signal generated by the Principal Components Analysis (PCA) is utilized as an index for event detection and selective data transmission. With this new monitoring scheme, the remote server is relieved of unwanted data by receiving only relevant information from the wireless sensor networks. The performance of the proposed scheme was verified with simulation studies.