• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.616-625
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• 2002

In this paper, we drove the filtered-x least mean fourth (FXLMF) algorithm where the error raised to the power of four is minimized and analyzed its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. The application of the FXLMF adaptive filter to active noise control requires to estimate the transfer characteristics of the acoustic path between the output and the error signal of the adaptive controller. The results of the convergence analysis of the FXLMF algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that the convergence behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.1-8
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• 2005

Measurement of convergence was/is carried out manually throughout the world for tunnels under construction. However, manual method has certain limitations in terms of applicability for the tunnels in operation. This paper describes state of the art of convergence monitoring systems which are available for measuring displacement of existing tunnels. These technologies are analyzed as follows: 1 The Sofo system using the fiber optic sensors has been applied to the stress measurement of the tunnel lining. It has not yet been used for the monitoring of tunnel convergence because of its cost and reliability 2. A TPMS(Tunnel Profile Monitoring System) using tilt sensors and displacement sensors is used for the convergence monitoring of highway tunnels, subway tunnels and underground ducts. 3. A BCS(Bassett Convergence System) using a pair of tilt sensors can be used for the convergence monitoring of tunnels, however the accuracy of the measurement has to be improved because it uses AC input voltage during data acquisition. The system has to be validated before it can be applied to the tunnels in operation. Convergence monitoring systems using TPMS and/or BCS are recommended to be evaluated and improved by a series or tests in tunnels under construction in order to be applied to the main measuring section and the tunnels in operation.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.

• Journal of Multimedia Information System
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• v.8 no.1
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• pp.1-10
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• 2021

Heart Rate is a crucial physiological parameter that provides basic information about the state of the human body in the cardiovascular system, as well as in medical diagnostics and fitness assessments. At present day, it has been demonstrated that facial video-based photoplethysmographic signal captured using a low-cost RGB camera is possible to retrieve remote heart rate. Traditional heart rate measurement is mostly obtained by direct contact with the human body, therefore, it can result inconvenient for long-term measurement due to the discomfort that it causes to the subject. In this paper, we propose a non-contact-based remote heart rate measuring approach of the subject which depends on the color intensity variation of the subject's facial skin. The proposed method is applied in two regions of the subject's face, forehead and cheeks. For this, three different algorithms are used to measure the heart rate. i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The average accuracy for the three algorithms utilizing the proposed method was 89.25% in both regions. It is also noteworthy that the FastICA algorithm showed a higher average accuracy of more than 92% in both regions. The proposed method obtained 1.94% higher average accuracy than the traditional method based on average color value.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.4
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• pp.492-498
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• 2021

In this paper, the electromagnetic wave transmittance of the reinforced concrete structure wall was analyzed using the performance measurement system of electromagnetic wave shielding. Recently, electromagnetic wave shielding technologies on the reinforced concrete wall conditions have been studied, and the shielding effectiveness have been tested on unit cell size. However, the unit cell size tests have problems on that the measurement range for shielding performance is insufficient and it is difficult to reflect the real conditions of the concrete wall. Therefore, we constructed a shielding performance measurement system using a large sample of 2.2m × 2.2m like a real wall. To verify the measurement system, general reinforced concrete test samples were selected, and real shielding performance measurements and numerical analysis were proceeded. Test and numerical analysis results showed similar tendencies in the evaluation frequency range of 75MHz to 2GHz. Thus we validated the effectiveness of this shielding performance measurement system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.1506-1516
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• 1995

In this paper, we propose the filtered-x least mean fourth (FXLMF) algorithm where the error raised to the power of four is minimized and analyze its convergence behavior for a multiple sinusoidal acoustic noise and Gaussian measurement noise. Application of the FXLMF adaptive filter to active noise control requires to estimate the transfer characteristics of the acoustic path between the output and the error signal of the adaptive controller. The results of the convergence analysis of the FXLMF algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components : Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Also, we newly show that the convergence behavior can differ depending on the relative sizes of the Gaussian noise and the convergence constant.

• Journal of Advanced Navigation Technology
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• v.4 no.1
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• pp.45-49
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• 2000

A GPS measurement solution, in general, is obtained as a least squares solution since the measurement includes errors such as clock errors, ionospheric and tropospheric delays, multipath effect etc. Because of the nonlinearity of the measurement equation, we utilize the nonlinear Newton algorithm to obtain a least squares solution, or mostly, use its linearized algorithm which is more convenient and effective. In this study we developed a fixed point algorithm and proved its availability to replace the nonlinear Newton algorithm and the linearized algorithm. A nonlinear Newton algorithm and a linearized algorithm have the advantage of fast convergence, while their initial values have to be near the unknown solution. On the contrary, the fixed point algorithm provides more reliable but slower convergence even if the initial values are quite far from the solution. Therefore, two types of algorithms may be combined to achieve better performance.

• Fashion & Textile Research Journal
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• v.10 no.5
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• pp.676-682
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• 2008

In this study a guideline of the 3D-fit pattern for the ECG(electrocardiogram) measurement of elderly's u-healthcare clothes was proposed. In the screening test of the ECG measurement band, ECG peak band was observable at the band pressure of 0.20 kPa. By employing a 3D body image, tight-fit 3D patterns were made at two different reduction rates of 21%(pattern 1) and 33%(pattern 2), and corresponding pressure of both of the clothes were 0.25 kPa and 0.54 kPa, respectively. Typical waves of ECG were found in both stationary and moving position. In terms of the subjective evaluation of the u-healthcare clothes when worn, it was confirmed that reduction pattern 1(0.25 kPa) conveyed comfortable clothing pressure and pleasantness, which is very close to the result of screening test of ECG band experiment. As results, it is recommended that reduction rate should be adjusted, so that clothing pressure is about 0.2 kPa for the elderly's comfortable and efficient u-healthcare clothes.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.219-223
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• 2008

The dissolved oxygen (DO) sensors were fabricated by screen printing method, and potable dissolved oxygen measurement system was fabricated for low cost products. The fabricated sensors had high current change and fast response according to dissolved oxygen concentrations in the applied voltage of 0.7 V. The DO measurement system was consisted of MCV, amplifier, filter, power supply and display. DO concentrations were programed to display as digital percentages by converting the analog value. It is expected that the fabricated DO measurement system can replace the expensive commercial DO meter, because it reveals the high accuracy of ${\pm}0.5%$ to the standard solution and the response time of about 100 sec like the commercial DO meter.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.1
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• pp.51-56
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• 2019

This paper proposes an improved heartbeat signal extraction method for ballistocardiography(BCG)-based heart-rate measurement on mobile environment. First, from a mobile facial video, a handshake-free head motion signal is extracted by tracking facial features and background features at the same time. Then, a novel signal periodicity computation method is proposed to accurately separate out the heartbeat signal from the head motion signal. The proposed method could robustly extract heartbeat signals from mobile facial videos, and enabled more accurate heart rate measurement (measurement errors were reduced by 3-4 bpm) compared to the existing method.