• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.5 no.1
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• pp.13-24
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• 2006

This paper proposes a wireless management system for a pet dog using wireless sensor network. The developed intelligent wireless management system is compose of a central control system, auto-feeder, miniguidance robot, and wireless sensing devices. The developed system uses three types of sensed data such as light, temperature, md sounds from a pet dog and surrounded environment respectively. The presented design method using these data provides an efficient way to controlling and monitoring the pet dog. The implemented system can be used as a design framework of portable device for the pet management.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.7 no.1
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• pp.1-13
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• 2007

This paper proposes a wireless management system for a pet dog using wireless sensor network. The developed intelligent wireless management system is compose of a central control system, auto-feeder, mini-guidance robot, and wireless sensing devices. The developed system uses three types of sensed data such as light, temperature, and sounds from a pet dog and surrounded environment respectively. The presented design method using these data provides an efficient way to controlling and monitoring the pet dog. The implemented system can be used as a design framework of portable device for the pet management.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.421-430
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• 2018

Many voice recognition systems use methods such as MFCC, HMM to acknowledge human voice. This recognition method is designed to analyze only a targeted sound which normally appears between a human and a device one. However, the recognition capability is limited when there is a group sound formed with diversity in wider frequency range such as dog barking and indoor sounds. The frequency of overlapped sound resides in a wide range, up to 20KHz, which is higher than a voice. This paper proposes the new recognition method which provides wider frequency range by conjugating the Wideband Sound Spectrogram and the Keras Sequential Model based on DNN. The wideband sound spectrogram is adopted to analyze and verify diverse sounds from wide frequency range as it is designed to extract features and also classify as explained. The KSM is employed for the pattern recognition using extracted features from the WSS to improve sound recognition quality. The experiment verified that the proposed WSS and KSM excellently classified the targeted sound among noisy environment; overlapped sounds such as dog barking and indoor sounds. Furthermore, the paper shows a stage by stage analyzation and comparison of the factors' influences on the recognition and its characteristics according to various levels of noise.

• Fashion & Textile Research Journal
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• v.15 no.4
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• pp.620-629
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• 2013

This study examines the rustling sound characteristics of electrospun nanofiber web laminates according to layer structures. This study assesses mechanical properties and frictional sounds (such as SPL); in addition, Zwicker's psychoacoustic parameters (such as Loudness (Z), Sharpness (Z), Roughness (Z), and Fluctuation strength (Z)) were calculated using the Sound Quality Program (ver.3.2, B&K, Denmark). The result determined how to control these characteristics and minimize rustling sounds. A total of 3 specimens' frictional sound (generated at 0.63 m/s) was recorded using a Simulator for Frictional Sound of Fabrics (Korea Patent No. 10-2008-0105524) and SPLs were analyzed with a Fast Fourier Transformation (FFT). The mechanical properties of fabrics were measured with a KES-FB system. The SPL value of the sound spectrum showed 6.84~58.47dB at 0~17,500Hz. The SPL value was 61.2dB for the 2-layer PU nanofiber web laminates layered on densely woven PET(C1) and was the highest at 65.1dB for the 3-layer PU nanofiber web laminates (C3). Based on SPSS 18.0, it was shown that there is a correlation between mechanical properties and psychoacoustic characteristics. Tensile properties (LT), weight (T), and bending properties (2HB) showed a high correlation with psychoacoustic characteristics. Tensile linearity (LT) with Loudness (Z) showed a negative correlation coefficient; however, weight (T) with Sharpness (Z) and Roughness (Z), and bending hysteresis (2HB) with Roughness (Z) indicated positive correlation coefficients, respectively.

• Journal of Biomedical Engineering Research
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• v.37 no.1
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• pp.7-14
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• 2016

Radiopharmaceutical agents for positron emission tomography (PET), such as $^{18}F$-FDG and $^{68}Ga$, have been used not only for whole-body PET imaging but also for intraoperative radionuclide-guided surgery due to their quantitative and sensitive imaging characteristics. Current intraoperative probes detect gamma or beta particles, but not both of them. Gamma probes have low sensitivities since a collimator has to be used to reduce backgrounds. Positron probes have a high tumor-to-background ratio, but they have a 1-2 mm depth limitation from the body surface. Most of current intraoperative probes produce only audible sounds proportional to count rates without providing tumor images. This research aims to detect both positrons and annihilation photons from $^{18}F$ using plastic scintillators and a GAGG scintillation crystal attached to silicon photomultiplier (SiPM). The depth-of-interaction (DOI) along the plastic scintillator can be used to obtain the 2-D images of tumors near the body surface. The front and rear part of the intraoperative probe consists of $4{\times}1$ plastic scintillators ($2.9{\times}2.0{\times}12.0mm^3$) for positron detection and a Ce:GAGG scintillation crystal ($12.0{\times}12.0{\times}9.0mm^3$) for annihilation photon detection, respectively. The DOI resolution of $4.4{\pm}1.6mm$ along the plastic scintillator was obtained by using the 3M enhanced specular reflector (ESR) with rectangular holes between the plastic scintillators, which showed the feasibility of a 2-D image pixel size of $2.9{\times}4.4mm^2$ (X-direction ${\times}$ Y-direction).