• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1638-1643
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• 2018

Multi-layer ceramic capacitors as decoupling capacitor were fabricated by dielectric composition with a high dielectric constant. The fabricated decoupling capacitors were embedded in the PCB of the 10G RF transceiver module and evaluated for the characteristics of electrical noise by the level of AC input voltage. In order to further improve the electrical properties of the $BaTiO_3$ based composite, glass frit, MgO, $Y_2O_3$, $Mn_3O$, $V_2O_5$, $BaCO_3$, $SiO_2$, and $Al_2O_3$ were used as additives. The electrical properties of the composites were determined by various amounts of additives and optimum sintering temperature. As a result of the optimized composite, it was possible to obtain a density of $5.77g/cm^3$, a dielectric constant of 1994, and an insulation resistance of $2.91{\times}10^{12}{\Omega}$ at an additive content of 5wt% and a sintering temperature of $1250^{\circ}C$. After forming a $2.5{\mu}m$ green sheet using the doctor blade method, a total of 77 layers were laminated and sintered at $1180^{\circ}C$. A decoupling capacitor with a size of $0.6mm(W){\times}0.3mm(L){\times}0.3mm(T)$ (width, length and thickness, respectively) and a capacitance of 100 nF was embedded using a PCB process for the 10G RF Transceiver modules. In the range of AC input voltage 400mmV @ 500kHz to 2200mV @ 900kHz, the embedded 10G RF Transceiver modules evaluated that it has better electrical performance than the non-embedded modules.

• 전자공학회논문지 IE
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• v.43 no.4
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• pp.28-36
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• 2006

In this paper, an algorithm to classify the 4 motions of arm and a control system to position control the prosthesis are studied. To classify the 4 motions, we use flex sensors which is electrical resistance type sensor that can measure warp of muscle. The flex sensors are attached to the biceps brchii muscle and coracobrachialis muscle and the sensor signals are passed the sensing system. 4 motion of the forearm - flexion and extension, the pronation and supination are classified from this. Also position of forearm is measured from the classified signals. Finally, A two D.O.F prosthesis arm with RC servo-motor is designed to verify the validity of the algorithm. At this time, fuzzy controller is used to reduce the position error by rotary inertia and noise. From the experiment, the position error had occurred within about 5 degree.

• Progress in Superconductivity
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• v.13 no.2
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• pp.105-110
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• 2011

SQUID sensor-based ultra low-field magnetic resonance apparatus with ${\mu}T$-level measurement field requires a strong prepolarization magnetic field ($B_p$) to magnetize its sample and obtain magnetic resonance signal with a high signal-to-noise ratio. This $B_p$ needs to be ramped down very quickly so that it does not interfere with signal acquisition which must take place before the sample magnetization relaxes off. A MOSFET switch-based $B_p$ coil driver has current ramp-down time ($t_{rd}$) that increases with $B_p$ current, which makes it unsuitable for driving high-field $B_p$ coil made of superconducting material. An energy cycling-type current driver has been developed for such a coil. This driver contains a storage capacitor inside a switch in IGBT-diode bridge configuration, which can manipulate how the capacitor is connected between the $B_p$ coil and its current source. The implemented circuit with 1.2 kV-tolerant devices was capable of driving 32 A current into a thick copper-wire solenoid $B_p$ coil with a 182 mm inner diameter, 0.23 H inductance, and 5.4 mT/A magnetic field-to-current ratio. The measured trd was 7.6 ms with a 160 ${\mu}F$ storage capacitor. trd was dependent only on the inductance of the coil and the capacitance of the driver capacitor. This driver is scalable to significantly higher current of superconducting $B_p$ coils without the $t_{rd}$ becoming unacceptably long with higher $B_p$ current.

• Speech Sciences
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• v.14 no.2
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• pp.43-53
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• 2007

The purpose of this study was to observe the effect of eating a raw egg by professional or nonprofessional voice users on their voice quality and the duration of the effect. 20 professional voice users and 20 nonprofessional voice users participated in the experiment and they had gone through stroboscopy to have no vocal or laryngeal diseases. The voice exam was performed three times: before eating a raw egg (1st period), right after eating it (2nd period), and 10 minutes later (3rd period). By using Multi-dimensional Voice Program which is a software of Computerized Speech Lab 4500 as a voice analysis instrument, the authors checked the F0, Jitter, Shimmer, Noise to harmonic ratio (NHR), and Voice Range Profile (VRP). Results showed as follows: Firstly, vocal hygiene was good in 57.5% of the total subjects and was poor in 42.5%. 40% of professional voice users and 75% of nonprofessional voice users hand good quality. 77.5% of the total subjects had the vocal fatigue while 22.5% of the subjects did not. 95% of the professional voice users and 60% of nonprofessional voice users complained the vocal fatigue. 60% of the total subjects reported a subjective vocal symptom. 65.0% professional voice users and 70.0% of nonprofessional voice users reported a voice symptom. From the results above, we suggest that eating a raw egg may lead to imporve voice quality of the professional voice users.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.57-65
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• 2007

In the fast block matching algorithm. search patterns of different shapes or sizes and the distribution of motion vectors have a large impact on both the searching speed and the image qualify. In this paper, we propose a new fast block matching algorithm using the flat-hexagon search pattern that ate solved disadvantages of the diamond pattern search algorithm(DS) and the hexagon-based search algorithm(HEXBS). Our proposed algorithm finds mainly the motion vectors that not close to the center of search window using the flat-hexagon search pattern. Through experiments, compared with the DS and HEXBS, the proposed f)at-hexagon search algorithm(FHS) improves about $0.4{\sim}21.3%$ in terms of average number of search point per motion vector estimation and improves about $0.009{\sim}0.531dB$ in terms of PSNR(Peak Signal to Noise Ratio).

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.3
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• pp.69-76
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• 2008

This work proposes a 12b 1kS/s 65uA 0.35um CMOS algorithmic ADC for sensor interface applications such as accelerometers and gyro sensors requiring high resolution, ultra-low power, and small size simultaneously. The proposed ADC is based on an algorithmic architecture with recycling techniques to optimize sampling rate, resolution, chip area, and power consumption. Two versions of ADCs are fabricated with a conventional open-loop sampling scheme and a closed-loop sampling scheme to investigate the effects of offset and 1/f noise during dynamic operation. Switched bias power-reduction techniques and bias circuit sharing reduce the power consumption of amplifiers in the SHA and MDAC. The current and voltage references are implemented on chip with optional of-chip voltage references for low-power SoC applications. The prototype ADC in a 0.35um 2P4M CMOS technology demonstrates a measured DNL and INL within 0.78LSB and 2.24LSB, and shows a maximum SNDR and SFDR of 60dB and 70dB in versionl, and 63dB and 75dB in version2 at 1kS/s. The versionl and version2 ADCs with an active die area of $0.78mm^2$ and $0.81mm^2$ consume 0.163mW and 0.176mW at 1kS/s and 2.5V, respectively.

• Korean Journal of Optics and Photonics
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• v.15 no.3
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• pp.193-199
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• 2004

We present the double resonance optical pumping(DROP) spectra in the transition 5P$_{3}$2/-4D$_{3}$2/ and 5P$_{3}$2/-4D$_{5}$ 2/ of ($^{87}$ Rb) and the frequency stabilization in the $1.5mutextrm{m}$ region using those spectra. Those spectra have high signal-to-noise ratio and narrow spectral linewidth, which is about 10 MHz. We could account fur the relative intensities of the hyperfine states of those spectra by the spontaneous emission into the other state. When the frequency of the $1.5mutextrm{m}$ laser diode was stabilized to the DROP spectrum, the frequency fluctuation was about 0.2 MHz fDr sampling time of 0.1 s and the Allan deviation(or the square root of the Allan variance) was about 1${\times}$10$^{-11}$ for averaging time of l00s.

• Investigative Magnetic Resonance Imaging
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• v.15 no.1
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• pp.22-31
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• 2011

Purpose : To compare free-breathing and respiratory-triggered diffusion-weighted imaging on 1.5-T MR system in the detection of hepatic lesions. Materials and Methods: This single-institution study was approved by our institutional review board. Forty-seven patients (mean 57.9 year; M:F = 25:22) underwent hepatic MR imaging on 1.5-T MR system using both free-breathing and respiratory-triggered diffusion-weighted imaging (DWI) at a single examination. Two radiologists retrospectively reviewed respiratory-triggered and free-breathing sets (B50, B400, B800 diffusion weighted images and ADC map) in random order with a time interval of 2 weeks. Liver SNR and lesion-to-liver CNR of DWI were calculated measuring ROI. Results : Total of 62 lesions (53 benign, 9 malignant) that included 32 cysts, 13 hemangiomas, 7 hepatocellular carcinomas (HCCs), 5 eosinophilic infiltration, 2 metastases, 1 eosinophilic abscess, focal nodular hyperplasia, and pseudolipoma of Glisson's capsule were reviewed by two reviewers. Though not reaching statistical significance, the overall lesion sensitivities were increased in respiratory-triggered DWI [reviewer1: reviewer2, 47/62(75.81%):45/62(72.58%)] than free-breathing DWI [44/62(70.97%):41/62(66.13%)]. Especially for smaller than 1 cm hepatic lesions, sensitivity of respiratory-triggered DWI [24/30(80%):21/30(70%)] was superior to free-breathing DWI [17/30(56.7%):15/30(50%)]. The diagnostic accuracy measuring the area under the ROC curve (Az value) of free-breathing and respiratory-triggered DWI was not statistically different. Liver SNR and lesion-to-liver CNR of respiratory-triggered DWI ($87.6{\pm}41.4$, $41.2{\pm}62.5$) were higher than free-breathing DWI ($38.8:{\pm}13.6$, $24.8{\pm}36.8$) (p value < 0.001, respectively). Conclusion: Respiratory-triggered diffusion-weighted MR imaging seemed to be better than free-breathing diffusion-weighted MR imaging on 1.5-T MR system for the detection of smaller than 1 cm lesions by providing high SNR and CNR.

• Journal of the Korean Society of Radiology
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• v.14 no.1
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• pp.23-29
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• 2020

The standard uptake values (SUVs) strongly depend on positron emission tomographs (PETs) and image reconstruction methods. Various image reconstruction algorithms in GE Discovery MIDR (DMIDR) and Discovery Ste (DSte) installed at Department of Nuclear Medicine, Seoul Samsung Medical Center were applied to measure the SUVs in an anthropomorphic torso phantom. The measured SUVs in the heart, liver, and background were compared to the actual SUVs. Applied image reconstruction algorithms were VPFX-S (TOF+PSF), QCFX-S-350 (Q.Clear+TOF+PSF), QCFX-S-50, VPHD-S (OSEM+PSF) for DMIDR, and VUE Point (OSEM) and FORE-FBP for DSte. To reduce the radiation exposure to radiation technologists, only the small amount of radiation source ¹⁸F-FDG was mixed with the distilled water: 2.28 MBq in the 52.5 ml heart, 20.3 MBq in the 1,290 ml liver and 45.7 MBq for the 9,590 ml in the background region. SUV values in the heart with the algorithms of VPFX-S, QCFX-S-350, QCFX-S-50, VPHD-S, VUE Point, and FOR-FBP were 27.1, 28.0, 27.1, 26.5, 8.0, and 7.4 with the expected SUV of 5.9, and in the background 4.2, 4.1, 4.2, 4.1, 1.1, and 1.2 with the expected SUV of 0.8, respectively. Although the SUVs in each region were different for the six reconstruction algorithms in two PET/CTs, the SUV ratios between heart and background were found to be relatively consistent; 6.5, 6.8, 6.5, 6.5, 7.3, and 6.2 for the six reconstruction algorithms with the expected ratio of 7.8, respectively. Mean SNRs (Signal to Noise Ratios) in the heart were 8.3, 12.8, 8.3, 8.4, 17.2, and 16.6, respectively. In conclusion, the performance of PETs may be checked by using with the SUV ratios between two regions and a relatively small amount of radioactivity.