• Journal of the korean Society of Automotive Engineers
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• v.5 no.4
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• pp.1-9
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• 1983

최근 각종 분야에서 환경보전이 문제화되고 있으며 소음제어문제에 많은 관심을 불러일으키고 있다. 이러한 소음문제를 해결하기 위해서는 소음을 발생하는 기계 혹은 장치에 대책을 세우고, 소음을 억제하는 것이 무엇보다도 가장 이상적이라고 할 수 있다. 일반적으로 각종 플랜트, 선박, 차량기기 등은 많은 소음원을 가지고 있으며 소음문제는 먼저 문제가 되는 곳에 대책을 세워 발생원의 검출, 즉 각 발생원으로부터 기여량을 파악하는데 있다. 각 발생원의 기여량을 정확하게 파악할 수 있다면 적절하고 경제적인 대책을 수립하는데 도움이 된다. 장래에는 소음 발생원의 검출은 시행 착오적인 수법에 의해 행하여졌지만 최근 수년간에 있어서 전자계산기에 의한 시계열 데이터처리기술의 진보에 따라서 복잡한 소음예측정데이터에 포함되어 있는 정보를 추출하여 이용할 수 있도록 되었다. 본 해설에서는 복잡한 소음원해석에 다차원스펙트럼해석을 이용한 기여량추정법을 실제로 소음문제에 적용할 수 있는 기본적이고 구체적인 컴퓨터그포그 램작성요령에 대해서 시술하고자 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.224-226
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• 2012

IT 기술의 발전과 정보화 사회로 인해 컴퓨터 관련범죄뿐 아니라 일반 범죄에서도 증거 및 단서가 디지털정보 기기에 보관되는 경우가 발생하고 있다. 이러한 맥락에서 본 논문에서는 디지털 포렌식 기술의 하나로서 녹음 데이터로부터 녹음기기를 판별하는 효과적인 방법을 제안한다. 녹음된 데이터에서 노이즈를 추출하고, 이 노이즈의 차이점을 이용하면 효율적인 기기판별 방법이 가능해진다. 본 논문에서는 위너 필터를 통한 기기 Noise를 추출하고, MirToolBox를 이용하여 특징들을 추출한다. 추출된 특징들과 WEKA의 다중 신경망을 이용하여 학습 및 판별하였다. 판별 결과 평균 99.8%의 성능을 보였다.

• Korean Journal of Health Education and Promotion
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• v.18 no.2
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• pp.141-156
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• 2001

This study was performed to identify the occupational diseases in the dental technicians working in Korea, and to elucidate the main related affecting factors for the occurrence of the occupational diseases. The research was carried out using a mail questionnaire and data collection was done for two months from April 15, 2000. The questionnaires were delivered to 1000 dental technicians working at 250 dental laboratories which were chosen among the total 1330 dental laboratories in south Korea. And 763 questionnaires were collected, then 739 questionnaires were used for a logistic and a multiple regression analyses. The results obtained in this study are summarized as follows: 1. The occupational diseases in the dental technicians included pneumoconiosis, chronic bronchitis, asthma, pneumonia, hyposmia, allergic dermatitis, eczema, contagious dermatitis, central nervous disorder, dysfunction of finger, vertebral disorder, dysfunction of interphalangeal joint, ophthalmitis, auditory dysfunction, otitismedia, optic trauma, and bum. 2. The main related affecting factors for the occurrence of the occupational diseases in the dental technicians were elucidated as follows: On the ccurrence of chronic bronchitis, vibration of equipment and job career were affected positively. On the ccurrence of asthma, job career and career on current working part were affected positively, but exhaust ventilation, work hour were affected negatively. On the occurrence of eczema, career on current working part and vibration of equipment were affected positively, but personal protective equipment, local exhaust ventilation, isolation of gas source were affected negatively. And eczema was occurred more in methyl methacrylate work than in any other work part. On the occurrence of finger dysfunction, vibration of equipment and noise of work place were affected positively. But personal protective equipment, local exhaust ventilation, isolation of dust and gas source were affected negatively. But finger dysfunction was occurred more in metal polishing than in any other work part. On the occurrence of auditory dysfunction, noise of work place were affected negatively. The results obtained in this study can give a valuable information for a prevention of the occupational diseases in the dental technicians working in Korea, and for keeping them in healthy. This study also can be helpful for a researcher who is aiming at a identification of occupational diseases and a elucidation of related affecting factors in a similar occupation.

• The Journal of the Acoustical Society of Korea
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• v.15 no.5
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• pp.99-106
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• 1996

The noise of a compressor is a major contributor to overall noise radiated from the refrigerator. The major source of the noise is radiated by the vibration of the compressor shell. In this study, to identify the dynamic characteristics of compressor shell, a compressor shell is divided into several components and these are analyzed with a commercial FEM(Finite Element Method) package such as MSC/NASTRAN. Using substructure synthesis method, the dynamic characteristics of the total system is identified. The coherence of each component to the total system is computed by using strain and kinetic energy. To increase the frequency of the first resonance mode which is most effective mode to the noise of the compressor shell, the improving strategy of dynamic characteristics is suggested by changing mass and stiffness of the coherence component to the first mode.

• Journal of Sensor Science and Technology
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• v.9 no.4
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• pp.316-326
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• 2000

A new signal processing algorithm for white light interferometry has been proposed and investigated theoretically. The goal of the algorithm is to determine the absolute optical path length of an interferometer with very high precision (<< one optical wavelength). The algorithm features cross-correlation of interferometer fringe scans and hypothesis testing. The hypothesis test looks for a zero order fringe peak candidate about which the cross-correlation is symmetric minimizing the uncertainty of misidentification. The shot noise limited performance of the proposed signal processing algorithm has been analyzed using computer simulations. Simulation results were extrapolated to predict the misidentification rate at Signal to-Shot noise ratio (SNR) higher than 31 dB. Root-mean-square phase error between the computer-generated zero order fringe peak and the estimated zero order fringe peak has been calculated for the changes of three different parameters (SNR, fringe scan sampling rate, coherence length of light source). Results of computer simulations showed the ability of the proposed signal processing algorithm to identify the zero order fringe peak correctly. The proposed signal processing algorithm uses a software approach, which is potentially inexpensive, simple and fast.

• Journal of the Korean Geotechnical Society
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• v.37 no.9
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• pp.13-24
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• 2021

Recently, attempts have been made to detect fouling patterns in the ground using Ground Penetrating Radar (GPR) during the maintenance of gravel ballast railway tracks. However, dealing with GPR signal data obtained with a large amount of noise in a site where complex ground conditions are mixed, often depends on the experience of experts, and there are many difficulties in precise analysis. Therefore, in this study, a numerical modeling technique that can quantitatively simulate the GPR signal characteristics according to the degree of fouling of the gravel ballast material was proposed using python-based open-source code gprMax and RSA (Random sequential Absorption) algorithm. To confirm the accuracy of the simulation model, model tests were manufactured and the results were compared to each other. In addition, the identification of the fouling layer in the model test and analysis by various test conditions was evaluated and the results were analyzed.

• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.274-284
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• 2021

Customized services to a sleep induction for better sleepcare are more effective because of different satisfaction levels to users. The EOG data measured at the frontal lobe when a person blinks his eyes can be used as biometric data because it has different values for each person. The accuracy of measurement is degraded by a noise source, such as toss and turn. Therefore, it is necessary to analyze the noisy data and remove them from normal EOG by filtering. There are low-pass filtering and high-pass filtering as filtering using a frequency band. However, since filtering within a frequency band range is also required for more effective performance, we propose a machine learning model for the filtering of EOG data in this paper as the second filtering method. In addition, optimal values of parameters such as the depth of the hidden layer, the number of nodes of the hidden layer, the activation function, and the dropout were found through experiments, to improve the performance of the machine learning filtering model, and the filtering performance of 95.7% was obtained. Eventually, it is expected that it can be used for effective user identification services by using filtering model for EOG data.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.370-376
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• 2023

In the underwater image, it is not clear to distinguish the shape of the target due to underwater noise and low resolution. In addition, as an input of deep learning, underwater images require pre-processing and segmentation must be preceded. Even after pre-processing, the target is not clear, and the performance of detection and identification by deep learning may not be high. Therefore, it is necessary to distinguish and clarify the target. In this study, the importance of target shadows is confirmed in underwater images, object detection and target area acquisition by shadows, and data containing only the shape of targets and shadows without underwater background are generated. We present the process of converting the shadow image into a 3-mode image in which the target is white, the shadow is black, and the background is gray. Through this, it is possible to provide an image that is clearly pre-processed and easily discriminated as an input of deep learning. In addition, if the image processing code using Open Source Computer Vision (OpenCV)Library was used for processing, the processing speed was also suitable for real-time processing.

• Analytical Science and Technology
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• v.35 no.2
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• pp.69-81
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• 2022

The method of measuring and classifying the energy category of neutrons directly using raw data acquired through a CZT detector is not satisfactory, in terms of accuracy and efficiency, because of its poor energy resolution and low measurement efficiency. Moreover, this method of measuring and analyzing the characteristics of low-energy or low-activity gamma-ray sources might be not accurate and efficient in the case of neutrons because of various factors, such as the noise of the CZT detector itself and the influence of environmental radiation. We have therefore developed an efficient method of analyzing radiation characteristics using a neutron and gamma-ray analysis algorithm for the rapid and clear identification of the type, energy, and radioactivity of gamma-ray sources as well as the detection and classification of the energy category (fast or thermal neutrons) of neutron sources, employing raw data acquired through a CZT detector. The neutron analysis algorithm is based on the fact that in the energy-spectrum channel of 558.6 keV emitted in the nuclear reaction ¹¹³Cd + ¹n → ¹¹⁴Cd + in the CZT detector, there is a notable difference in detection information between a CZT detector without a PE modulator and a CZT detector with a PE modulator, but there is no significant difference between the two detectors in other energy-spectrum channels. In addition, the gamma-ray analysis algorithm uses the difference in the detection information of the CZT detector between the unique characteristic energy-spectrum channel of a gamma-ray source and other channels. This efficient method of analyzing radiation characteristics is expected to be useful for the rapid radiation detection and accurate information collection on radiation sources, which are required to minimize radiation damage and manage accidents in national disaster situations, such as large-scale radioactivity leak accidents at nuclear power plants or nuclear material handling facilities.

• Ocean Systems Engineering
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• v.13 no.2
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• pp.173-193
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• 2023

Reliable prediction of the motion of FOWT (floating offshore wind turbine) and associated mooring line tension is important in both design and operation/monitoring processes. In the present study, a 5MW OC4 semisubmersible wind turbine is numerically modeled, simulated, and analyzed by the open-source numerical tool, OpenFAST and in-house numerical tool, Charm3D-FAST. Another commercial-level program FASTv8-OrcaFlex is also introduced for comparison for selected cases. The three simulation programs solve the same turbine-floater-mooring coupled dynamics in time domain while there exist minor differences in the details of the program. Both the motions and mooring-line tensions are calculated and compared with the DeepCWind 1/50 scale model-testing results. The system identification between the numerical and physical models is checked through the static-offset test and free-decay test. Then the system motions and mooring tensions are systematically compared among the simulated results and measured values. Reasonably good agreements between the simulation and measurement are demonstrated for (i) white-noise random waves, (ii) typical random waves, and (iii) typical random waves with steady wind. Based on the comparison between numerical results and experimental data, the relative importance and role of the differences in the numerical methodologies of those three programs can be observed and interpreted. These comparative-study results may provide a certain confidence level and some insight of potential variability in motion and tension predictions for future FOWT designs and applications.