• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.12
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• pp.1338-1346
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• 2004

The positions of rotating sound sources have been localized by experiments with the Doppler effects removed. In order to de-Dopplerize the sound signals emitted from moving sources, two kinds of signal reconstruction methods were applied. One is the forward propagation method and the other is the backward propagation method. Forward propagation method analyze the source emission time based on the instantaneous distance between sensors and the assumed source position, then the signals are reconstructed with respect to the emission time. On the other hand, the backward method uses time delay to do-Dopplerize the acquired data for the received time of reference. In both techniques. the reconstructed signal data were processed using beamforming algorithm to produce power distributions at the frequencies of interest. Experiments have been carried out for varying frequencies, rotating speeds and the object distances. It is shown that the forward propagation method gives better performance in locating source position than the backward propagation method.

• Asian Journal of Atmospheric Environment
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• v.9 no.1
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• pp.86-90
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• 2015

Temperature was considered to estimate the minimum detectable absorption coefficient of aerosol particles from photothermal spectroscopy. Light energy absorbed by subsequent emission from the aerosol results in the heating of the aerosol sample and consequently causes a temperature change as well as changes in thermodynamic parameters of the sample. This thermal effect is the basis of photothermal spectroscopy. Photothermal spectroscopy has several types of techniques depending on how the photothermal effects are detected. Photothermal interferometry traces the photothermal effect, refractive index, using an interferometer. Photoacoustic spectroscopy detects the photothermal effect, sound wave, using a microphone. In this study, it is suggested that the detection limit for photothermal spectroscopy can be influenced by the introduction of a slip correction factor when the light absorption is determined in a high temperature environment. The minimum detectable absorption coefficient depends on the density, the specific heat and the temperature, which are thermodynamic properties. Without considering the slip correction, when the temperature of the environment is 400 K, the minimum detectable absorption coefficient for photothermal interferometry increases approximately 0.3% compared to the case of 300 K. The minimum detectable absorption coefficient for photoacoustic spectroscopy decreases only 0.2% compared to the case of 300 K. Photothermal interferometry differs only 0.5% point from photoacoustic spectroscopy. Thus, it is believed that photothermal interferometry is reliably comparable to photoacoustic spectroscopy under 400 K.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1656-1665
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• 1997

The intake noise, a major source of vehicle noises, has rapidly become a noticeable, and has been studied to reduce the level. Traditionally, the intake system has been developed through a experiment, namely, the trial and error process. This approach requires very high cost and long time consuming to develop the systm. Recently, FEM and BEM are becoming useful in analysis of the intake system, and the results of analysis are very valid. But because this techniques also require high cost and long analysis time, this technique is generally not practical tool at the early stage of the development. In this study, the software was developed to predict and analyze the acoustic characteristics of the intake system. It was based on the Transfer Matrix Method and operated to analyze a simplified intake system in a personal computer. It can be used early in the design stage of development of the intake system. This study presented a improvement to reduce the level of the intake noise, which modified the specification of the intake system. And the improvement were verified by NIT/SYSNOISE, FE analysis commercial software, and testing a prototype.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1648-1655
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• 1997

The intake noise, a major source of vehicle noises, has rapidly become a noticeable, and has been studied to reduce the level. Traditionally, the intake system has been developed through a experiment, namely, the trial and error process. This approach requires very high cost and long time consuming to develop the system. Recently, FEM and BEM are becoming useful in analysis of the intake system, and te results of analysis are very valid. But because these techniques also require high cost and long analysis time, these are generally not practical tool at the early stage of the development of an intake system. In this study, the software was developed to predict and analyze the acoustic characteristics of an intake system. It was based on the Transfer Matrix Method and operated to analyze a simplified intake system in a personal computer. It can be used early in the design stage of development of the intake system. This study presented an improvement to reduce the level of an intake noise. It was to select the optimum position of a resonator and verified by NIT/SYSNOISE, FE analysis commercial software, and testing a prototype.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.5
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• pp.3412-3420
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• 2015

Smartphone has become an essential element in our daily life and built-in sensors of the smartphone can be utilized in order to recognize of user's situation. However, it is lack of research for safety and accident prevention by dynamic situation recognition. In this paper, we propose a technique that can be recognized risk situation dynamically using accelerometer, microphone and GPS sensor of mobile device. We propose an architecture and process for sensing techniques of Dynamic Recognition Technique, and develop the mobile application for verifying the suitability of the architecture.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.3
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• pp.238-243
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• 2008

Several experimental techniques for identifying the noise sources distributed over a moving vehicle have been developed recently and are used to design a low noise vehicle. The beamforming method, which uses phase information between several microphones to localize the source position, is proved to be one of the promising techniques applicable even under complicated test environments. In this study a beamforming algorithm is developed and applied to measure the dominant noise sources on a passenger car passing by. Unlike the acoustic signals from a stationary noise source, the sound generated from a moving source is distorted due to the Doppler effects. The information about the speed and relative position of the vehicle are used to eliminate the Doppler effects from the measured acoustic signal by using a de-Dopplerization algorithm. The noise generated from a moving vehicle can be grouped in many ways, however, tire noise and the noise generated from the engine are distinguishable at the speeds being tested.

• Journal of Biomedical Engineering Research
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• v.44 no.2
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• pp.147-156
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• 2023

Efforts to employ smart home sensors to monitor the indoor activities of elderly single residents have been made to assess the feasibility of a safe and healthy lifestyle. However, the bathroom remains an area of blind spot. In this study, we have developed and evaluated a new edge computer device that can automatically detect water usage activities in the bathroom and record the activity log on a cloud server. Three kinds of sound as flushing, showering, and washing using wash basin generated during water usage were recorded and cut into 1-second scenes. These sound clips were then converted into a 2-dimensional image using MEL-spectrogram. Sound data augmentation techniques were adopted to obtain better learning effect from smaller number of data sets. These techniques, some of which are applied in time domain and others in frequency domain, increased the number of training data set by 30 times. A deep learning model, called CRNN, combining Convolutional Neural Network and Recurrent Neural Network was employed. The edge device was implemented using Raspberry Pi 4 and was equipped with a condenser microphone and amplifier to run the pre-trained model in real-time. The detected activities were recorded as text-based activity logs on a Firebase server. Performance was evaluated in two bathrooms for the three water usage activities, resulting in an accuracy of 96.1% and 88.2%, and F1 Score of 96.1% and 87.8%, respectively. Most of the classification errors were observed in the water sound from washing. In conclusion, this system demonstrates the potential for use in recording the activities as a lifelog of elderly single residents to a cloud server over the long-term.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.108-114
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• 2018

Due to the development of nondestructive testing techniques, methods of inspecting cracks in mechanical parts have drawn attentions. Among various non-destructive testing methods the acoustic resonance method which analyzes the natural frequencies has been developed into a technique suitable for the prompt judgements of the existence of the defects in the mechanical parts. In this study, we investigated the crack inspection technique to examine the cracks in the yoke tubes by using the acoustic resonance method and realized the system to quickly detect the cracks. A 24bit ADC circuit and an MCU were installed for the smooth data collection, and a TCP / IP communication interface was configured for the data communication with PC. We used a microphone as a sensor measuring the vibrations. We constructed an analysis software to obtain the frequency spectra of the vibrations, to find the existence of the cracks, and to feedback to the user. Tests were conducted using the yoke tubes manufactured in the real industrial field. The tests were successfully conducted to distinguish the good products from the defective (cracked) products and confirmed that they can be employed in the actual industrial field.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.239-244
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• 1998

Piezoelectric pressure sensors and pyroelectric infrared detectors based on ZnO thin film have been integrated with GaAs metal-semiconductor field effect transistor (MESFET) amplifiers. Surface micromachining techniques have been applied in a GaAs MESFET process to form both microsensors and electronic circuits. The on-chip integration of microsensors such as pressure sensors and infrared detectors with GaAs integrated circuits is attractive because of the higher operating temperature up to 200 oC for GaAs devices compared to 125 oC for silicon devices and radiation hardness for infrared imaging applications. The microsensors incorporate a 1${\mu}$m-thick sputtered ZnO capacitor supported by a 2${\mu}$m-thick aluminum membrane formed on a semi-insulating GaAs substrate. The piezoelectric pressure sensor of an area 80${\times}$80 ${\mu}$m2 designed for use as a miniature microphone exhibits 2.99${\mu}$V/${\mu}$ bar sensitivity at 400Hz. The voltage responsivity and the detectivity of a single infrared detector of an area 80${\times}$80 $\mu\textrm{m}$2 is 700 V/W and 6${\times}$108cm$.$ Hz/W at 10Hz respectively, and the time constant of the sensor with the amplifying circuit is 53 ms. Circuits using 4${\mu}$m-gate GaAs MESFETs are fabricated in planar, direct ion-implanted process. The measured transconductance of a 4${\mu}$m-gate GaAs MESFET is 25.6 mS/mm and 12.4 mS/mm at 27 oC and 200oC, respectively. A differential amplifier whose voltage gain in 33.7 dB using 4${\mu}$m gate GaAs MESFETs is fabricated for high selectivity to the physical variable being sensed.

• Korean Journal of Audiology
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• v.18 no.3
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• pp.105-111
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• 2014

Assistive listening devices (ALDs) refer to various types of amplification equipment designed to improve the communication of individuals with hard of hearing to enhance the accessibility to speech signal when individual hearing instruments are not sufficient. There are many types of ALDs to overcome a triangle of speech to noise ratio (SNR) problems, noise, distance, and reverberation. ALDs vary in their internal electronic mechanisms ranging from simple hard-wire microphone-amplifier units to more sophisticated broadcasting systems. They usually use microphones to capture an audio source and broadcast it wirelessly over a frequency modulation (FM), infra-red, induction loop, or other transmission techniques. The seven types of ALDs are introduced including hardwire devices, FM sound system, infra-red sound system, induction loop system, telephone listening devices, television, and alert/alarm system. Further development of digital wireless technology in hearing instruments will make possible direct communication with ALDs without any accessories in the near future. There are two technology solutions for digital wireless hearing instruments improving SNR and convenience. One is near-field magnetic induction combined with Bluetooth radio frequency (RF) transmission or proprietary RF transmission and the other is proprietary RF transmission alone. Recently launched digital wireless hearing aid applying this new technology can communicate from the hearing instrument to personal computer, phones, Wi-Fi, alert systems, and ALDs via iPhone, iPad, and iPod. However, it comes with its own iOS application offering a range of features but there is no option for Android users as of this moment.