• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.389-400
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• 2019

Level meters are non-invasively capable of measuring the level of the medium, and a growing variety of level meters are being used in the industry in connection with safety and maintenance. The level meter can be measured according to various kinds of medium such as solid medium such as coal, flour, rice and liquid medium such as water and petroleum. In order to reduce the error depending on the medium, the measurement using the Doppler Effect can compensate the measurement error, However, the number of signal processing steps is increased, the operation speed is further increased, the hardware complexity increases, and a high cost structure is required. In this paper, we propose a method to improve the signal processing operation structure of the remote measurement level meter to reduce the amount of computation and the resource usage of the required FPGA.

• Journal of Sensor Science and Technology
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• v.33 no.5
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• pp.373-377
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• 2024

To increase the sensitivity of film-type level sensors for water-level measurements, a Wheatstone bridge comprising a half-bridge circuit with a new film-type level sensor design containing four resistors and two electrodes was employed. The proposed film-type level sensor included a temperature compensation feature and demonstrated improved sensitivity owing to a two-fold increase in the voltage output. Furthermore, a repetition error of less than 1.0% was observed for water levels. As the change in resistance varied linearly with the water level, a linear function was derived to represent their relation. Using this derived formula, water level measurements that were twice as precise as those yielded by commercial products were achieved.

• Journal of The Geomorphological Association of Korea
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• v.20 no.4
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• pp.85-99
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• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.1
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• pp.12-18
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• 2008

In this research, we proposed a method for high precision measurement than laser displacement measurement. The proposed method finds the causes of error due to change in reflected laser signal level reflected from an object and compensation, and we designed this by applying laser displacement meter.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.1
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• pp.76-83
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• 2000

A measurement technique of a sea height of burst is introduced for a proximate test using the image recognition of video cameras. In the burst of fuse on the ocean, the burst center of fuse, the sea surface level and the height of calibration poles are measured by the process of image obtained from cameras. Finally, the height of burst of fuse can be computed by Hough transform algorithm. The error compensation algorithms are proposed to eliminate the errors caused by camera level and environmental parameters. As a result of experiment, it has been proved that the proposed measurement system shows the recognition of the center point of the burst image with ${\pm}$0.5m error.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.333-340
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• 2017

In this paper, we describe HW/SW co-optimizations for reconfigurable application specific instruction-set processors (ASIPs). Based on our previous very long instruction word (VLIW) ASIP, the proposed framework realizes various forward error-correction (FEC) algorithms for wireless communication systems. In order to enhance the energy efficiency, we newly introduce several design methodologies including high-radix algorithms, task-level out-of-order executions, and intensive resource allocations with loop-level rescheduling. The case study on the radix-4 turbo decoding shows that the proposed techniques improve the energy efficiency by 3.7 times compared to the previous architecture.

• ETRI Journal
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• v.32 no.5
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• pp.774-783
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• 2010

Many chaos-based encryption methods have been presented and discussed in the last two decades, but very few of them are suitable to secure transmission on noisy channels or respect the standard of the National Institute of Standards and Technology (NIST). This paper tackles the problem and presents a novel chaos-based cryptosystem for secure transmitted images. The proposed cryptosystem overcomes the drawbacks of existing chaotic algorithms such as the Socek, Xiang, Yang, and Wong methods. It takes advantage of the increasingly complex behavior of perturbed chaotic signals. The perturbing orbit technique improves the dynamic statistical properties of generated chaotic sequences, permits the proposed algorithm reaching higher performance, and avoids the problem of error propagation. Finally, many standard tools, such as NIST tests, are used to quantify the security level of the proposed cryptosystem, and experimental results prove that the suggested cryptosystem has a high security level, lower correlation coefficients, and improved entropy.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.213-222
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• 2002

The 3-hour-interval prediction of ground-level temperature up to +45 hours in Seoul area is performed using dynamic linear models(DLM). Numerical outputs and observations we used as input values of DLM. According to compare DLM forecasts to RDAPS forecasts using RMSE, DLM improve the accuracy of prediction and systematic error of numerical model outputs are eliminated by DLM.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.141-146
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• 2002

In this article we consider the problem of constructing confidence intervals for a linear regression model with nested error structure. A popular approach is the likelihood-based method employed by PROC MIXED of SAS. In this paper, we examine the ability of MIXED to produce confidence intervals that maintain the stated confidence coefficient. Our results suggest the intervals for the regression coefficients work well, but the intervals for the variance component associated with the primary level cannot be recommended. Accordingly, we propose alternative methods for constructing confidence intervals on the primary level variance component. Computer simulation is used to compare the proposed methods. A numerical example and SAS code are provided to demonstrate the methods.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.146-151
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• 1994

An empirical comparison of static fuzzy relational models which are identified with different fuzzy implication operators and inferred by different composition operators is made in case that all the information is represented by the fuzzy discretization. Four performance measures (integral of mean squared error, maximal error, fuzzy equality index and mean lack of sharpness) are adopted to evaluate and compare the quality of the fuzzy relational models both at the numerical level and logical level. As the results, the fuzzy implication operators useful in various fuzzy modeling problems are discussed and it is empirically shown that the selection of data pairs is another important factor for identifying the fuzzy model with high quality.