• Analytical Science and Technology
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• v.20 no.1
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• pp.84-90
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• 2007

To determine levels of 11 sulfonamides for animals in food, simultaneously, a selective method of high performance liquid chromatography with UV detector has been applied. The targets were sulfachlorpyridazine (SCP), sulfadiazine (SDZ), sulfadimethoxine (SDM), sulfisoxazole (SSX), sulfamerazine (SMZ), sulfamethazine (SMT), sulfamethoxazole (SMX), sulfamethoxypyridazine (SMP), sulfamonomethoxine (SMM), sulfaquinoxaline (SQX) and sulfathiazole (STZ). Food samples were beef, pork, chicken, milk and whole egg that were collected at the main 6 cities in Korea as Seoul, Busan, Daejon, Incheon, Mokpo and Gangneung. After homogenizing food samples with sodium phosphate solution and acetonitrile, it was extracted with n-hexane. The mobile phase gradient was a mixture of 5 mM potassium phosphate (pH 3.25) and methanol with a gradient ratio from 100:0 to 30:70. The UV wavelength was 270 nm. The overall recoveries were ranged from 75% to 95% and the limit of detection was minimum 0.004 mg/kg for SMT, and 0.007 mg/kg for STZ at signal/noise > 3, respectively. As results, sulfonamide drugs were not detected in most of the selected food samples, however, sulfamonomethoxine was detected in meat. The determined level of sulfamonomethoxine were 0.03 and 0.06 mg/kg for beef that were below the MRLs.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.443-450
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• 2019

Vicia amoena has traditionally been used to treat disease of rheumatism, arthralgia, muscular paralysis, abscess and eczema, and it has anti-inflammatory properties. However, validity of the anti-inflammatory activity has not been scientifically in vestige acted so far. Therefore, the aim of this study was to investigate the anti-inflammatory potential of V. amoena using the ethanolic extract. To evaluate the anti-inflammatory effects, we examined the inflammatory mediators such as nitric oxide (NO) and prostaglandin E₂ (PGE₂) on RAW264.7 cells. Our results indicated that ethanolic extract of V. amoena significantly inhibited the LPS-induced NO and PGE₂ production in RAW264.7 cells. The ethanolic extract of V. amoena has inhibited the PGE₂ production by 88.0±0.8 % at the concentration of 40㎍/ml. This results showed that ethanol extract of V. amoena is expected to be a good candidate for development into source of inflammation inhibitor

• Journal of the Microelectronics and Packaging Society
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• v.30 no.2
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• pp.1-12
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• 2023

In the current era of the global mobile smart device revolution, electronic devices are required in all spaces that people interact with. The establishment of the internet of things (IoT) among smart devices has been recognized as a crucial objective to advance towards creating a comfortable and sustainable future society. In-mold electronic (IME) processes have gained significant industrial significance due to their ability to utilize conventional high-volume methods, which involve printing functional inks on 2D substrates, thermoforming them into 3D shapes, and injection-molded, manufacturing low-cost, lightweight, and functional components or devices. In this article, we provide an overview of IME and its latest advances in application. We review biomimetic nanomaterials for constructing self-supporting biosensor electronic materials on the body, energy storage devices, self-powered devices, and bio-monitoring technology from the perspective of in-mold electronic devices. We anticipate that IME device technology will play a critical role in establishing a human-machine interface (HMI) by converging with the rapidly growing flexible printed electronics technology, which is an integral component of the fourth industrial revolution.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.383-388
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• 2006

This Paper presents a novel approach to single channel microphone speech enhancement in noisy environments. Widely used noise reduction techniques based on the spectral subtraction are generally expressed as a spectral gam depending on the signal-to-noise ratio (SNR). The well-known decision-directed(DD) estimator of Ephraim and Malah efficiently reduces musical noise under the background noise conditions, but generates the delay of the a prioiri SNR because the DD weights the speech spectrum component of the Previous frame in the speech signal. Therefore, the noise suppression gain which is affected by the delay of the a priori SNR, which is estimated by the DD matches the previous frame rather than the current one, so after noise suppression. this degrades the noise reduction performance during speech transient periods. We propose a computationally simple but effective speech enhancement technique based on the sigmoid type function for the weight Parameter of the DD. The proposed approach solves the delay problem about the main parameter, the a priori SNR of the DD while maintaining the benefits of the DD. Performances of the proposed enhancement algorithm are evaluated by ITU-T p.862 Perceptual Evaluation of Speech duality (PESQ). the Mean Opinion Score (MOS) and the speech spectrogram under various noise environments and yields better results compared with the fixed weight parameter of the DD.

• The Journal of the Acoustical Society of Korea
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• v.26 no.4
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• pp.173-181
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• 2007

In this paper, we propose a moving target localization algorithm using acoustic spectrograms. A time-versus-frequency spectrogram provide a information of trajectory of the moving target in underwater. For a source at sufficiently long range from a receiver, broadband striation patterns seen in spectrogram represents the mutual interference between modes which reflected by surface and bottom. The slope of the maximum intensity striation is influenced by waveguide invariant parameter ${\beta}$ and distance between target and sensor. When more than two sensors are applied to measure the moving ship-radited noise, the slope and frequency of the maximum intensity striation are depend on distance between target and receiver. We assumed two sensors to fixed point then form a circle of apollonios which set of all points whose distances from two fixed points are in a constant ratio. In case of three sensors are applied, two circle form an intersection point so coordinates of this point can be estimated as a position of target. To evaluates a performance of the proposed localization algorithm, simulation is performed using acoustic propagation program.

• Journal of the Korean Society of Radiology
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• v.18 no.2
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• pp.65-71
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• 2024

To achieve high resolution and sensitivity of positron emission tomography (PET) for small animals, the detector is constructed using very thin and long scintillation pixels. Due to the structure of these scintillation pixels, spatial resolution deterioration occurs outside the system's field of view. To solve this problem, we designed a detector that could improve spatial resolution by measuring the interaction depth and improve sensitivity by using a quasi-block scintillator. A quasi-block scintillator size of 12.6 mm x 12.6 mm x 3 mm was arranged in four layers, and optical sensors were placed on all sides to collect light generated by the interaction between gamma rays and the scintillator. DETECT2000 simulation was performed to evaluate the performance of the designed detector. Flood images were acquired by generating gamma-ray events at 1 mm intervals from 1.3 mm to 11.3 mm within the scintillator of each layer. The spatial resolution and peak-to-peak distance for each location were measured in an 11 x 11 array of flood images. The average measured spatial resolution was 0.25 mm, and the average distance between peaks was 1.0 mm. Through this, it was confirmed that all locations were separated from each other. In addition, because the light signals of all layers were measured separately from each other, the layer of the scintillator that interacted with the gamma rays could be completely separated. When the designed detector is used as a detector in a PET system for small animals, it is considered that excellent spatial resolution and sensitivity can be achieved and image quality can be improved.

• Journal of IKEEE
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• v.28 no.2
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• pp.221-227
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• 2024

This paper presents a smartphone-attachable vascular compliance monitoring module. The proposed sensor module measures photoplethysmogram (PPG) and reconstructs an accelerated PPG waveform. The feature points are extracted from the accelerated PPG waves, and vascular compliance is estimated using these extracted features. The module is powered via the smartphone's USB terminal and transmits the acquired waveforms along with vascular compliance values through Bluetooth. The transmitted waveforms and vascular compliance value are displayed through the smartphone application. This work proposes an assessment method for consistency of PPG instrumentation, and it was implemented in a processor of sensor module. The proposed sensor module can be easily attached to smartphone that does not support PPG instrumentation, providing simple measurment and numerical analysis of vascular compliance. To verify the performance of the implemented sensor module, we acquired vascular compliance and pulse pressure data from 29 subjects. Pulse pressure, which serves as a representative indicator of vascular compliance, was obtained using a commercial blood pressure monitor. The analysis results showed that the Pearson coefficient between vascular compliance and pulse pressure was 0.778, confirming a relatively high correlation between two metrics.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1268-1277
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• 2023

In this study, to evaluate the possibility of utilizing Chamaecyparis obtusa (Siebold & Zucc.) Endl. (C. obtusa) leaf fractions as anti-inflammatory functional materials, C. obtusa extract extracted with 99% ethanol (CO99EL) was fractionated with hexane (CO99EL-H), chloroform (CO99EL-C), ethyl acetate (CO99EL-E), butanol (CO99EL-B) and distilled water (CO99EL-W). The anti-inflammatory effects of each fraction was performed using lipopolysaccharide (LPS)-induced RAW264.7 mouse macrophages. Cytotoxicity was highest in CO99EL-H and CO99EL-C and lowest in CO99EL-W. Interestingly, LPS-induced iNOS expression and NO production were significantly reduced by CO99EL-H and CO99EL-E, and COX-2 expression was significantly reduced by CO99EL-B and CO99EL-W. In addition, interleukin (IL)-1𝛽, an inflammatory cytokine increased by LPS, was significantly reduced by CO99EL-C, CO99EL-E, CO99EL-B and CO99EL-W, and IL-6 was significantly reduced by CO99EL-B and CO99EL-W. Therefore, the janus kinase (JAK)/signaling transducer and activator of transcription (STAT) signaling pathway activated by LPS was significantly reduced by CO99EL-H and CO99EL-C, and the mitogen-activated protein kinase (MAPK) signaling pathway was slightly reduced by CO99EL-H and CO99EL-C. However, nuclear factor (NF)-𝜅B activity was not reduced by any fractions. Based on the results of this study, it was confirmed that CO99EL fractions have different anti-inflammatory mechanisms depending on the solvent used for fractionation.