• Title/Summary/Keyword: signal field

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Corrosion Behaviors of Dental Implant Alloy after Micro-sized Surface Modification in Electrolytes Containing Mn Ion

  • Kang, Jung-In;Son, Mee-Kyoung;Choe, Han-Cheol
    • Journal of Korean Dental Science
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    • v.11 no.2
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    • pp.71-81
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    • 2018
  • Purpose: The purpose of this study was to investigate the corrosion behaviors of dental implant alloy after microsized surface modification in electrolytes containing Mn ion. Materials and Methods: $Mn-TiO_2$ coatings were prepared on the Ti-6Al-4V alloy for dental implants using a plasma electrolytic oxidation (PEO) method carried out in electrolytes containing different concentrations of Mn, namely, 0%, 5%, and 20%. Potentiodynamic method was employed to examine the corrosion behaviors, and the alternatingcurrent (AC) impedance behaviors were examined in 0.9% NaCl solution at $36.5^{\circ}C{\pm}1.0^{\circ}C$ using a potentiostat and an electrochemical impedance spectroscope. The potentiodynamic test was performed with a scanning rate of $1.667mV\;s^{-1}$ from -1,500 to 2,000 mV. A frequency range of $10^{-1}$ to $10^5Hz$ was used for the electrochemical impedance spectroscopy (EIS) measurements. The amplitude of the AC signal was 10 mV, and 5 points per decade were used. The morphology and structure of the samples were examined using field-emission scanning electron microscopy and thin-film X-ray diffraction. The elemental analysis was performed using energy-dispersive X-ray spectroscopy. Result: The PEO-treated surface exhibited an irregular pore shape, and the pore size and number of the pores increased with an increase in the Mn concentration. For the PEO-treated surface, a higher corrosion current density ($I_{corr}$) and a lower corrosion potential ($E_{corr}$) was obtained as compared to that of the bulk surface. However, the current density in the passive regions ($I_{pass}$) was found to be more stable for the PEO-treated surface than that of the bulk surface. As the Mn concentration increased, the capacitance values of the outer porous layer and the barrier layer decreased, and the polarization resistance of the barrier layers increased. In the case of the Mn/Ca-P coatings, the corroded surface was found to be covered with corrosion products. Conclusion: It is confirmed that corrosion resistance and polarization resistance of PEO-treated alloy increased as Mn content increased, and PEO-treated surface showed lower current density in the passive region.

Effects of a Blindfold in Improving Concentration (착용형 시야 가리개가 집중력 향상에 미치는 영향)

  • Chung, Soon-Cheol;Choi, Mi-Hyun;Kim, Hyung-Sik
    • Science of Emotion and Sensibility
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    • v.24 no.1
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    • pp.37-44
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    • 2021
  • A study was conducted on the effects of improving concentration by obscuring the peripheral vision using a blindfold that only covers the left and right sides of the field of view. The blindfold was trapezoidal in shape (5 × 4.8 cm in length and width) and was fixed to the left and right sides of the glasses with fixing clips. The material was a black-colored polypropylene (PP) and weighed 2.3 g including the clip. Qualitative and quantitative evaluations were performed on 50 healthy college students during the 15 days of using a blindfold. The qualitative analysis was performed utilizing a questionnaire regarding the improvement of concentration and the structure of the blindfold. EEG was measured while watching a learning video that required attention for quantitative analysis, and signal power and ERD/S analyses were performed for the mid β band (15-20 Hz) at the F4 position, which was the frontal lobe. The results showed that 40 of the 50 people reported improved concentration when they wore a vision shield, and 80% of the total subjects found it to be effective. From the quantitative evaluation, the ERS peak (p = 0.023) and the ERD + ERS peak value showed a significant difference (p = 0.017). In conclusion, concentration still improved even if only the left and right visual fields were used. Thus, it is expected that blindfolding could be used in various environments that require concentration.

Effects of Dose and Image Quality according to Center Location in Lumbar Spine Lateral Radiography Using AEC Mode (자동노출제어장치를 이용한 요추 측면 방사선검사 시 환자 중심 위치 변화가 선량과 화질에 미치는 영향)

  • Jeong, Woon-Chan;Joo, Young-Cheol
    • Journal of radiological science and technology
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    • v.44 no.2
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    • pp.85-90
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    • 2021
  • The purpose of this study is to consider usefulness of using AEC mode and importance of patient center location in L-spine lateral radiography by comparing dose and image quality according to the change of patient center location with using AEC mode or not. In this study, guide wire is attached to the human body phantom's lumbar spine and the lead ruler is attached to the bottom of the wall detector to find out center location in detector. ESD, mAs, and EI were selected as dose factors, and image quality was compared through SNR. With the lumbar spine located center of the detector, dose factors and image quality were compared according to using AEC mode or not. Afterwards, phantom moved 4 cm and 8 cm back and forth and compared dose factors and image quality. The exposure parameters were 85 kVp, 320 mA, x-ray field size 10×17 inch, and the distance between the center X-ray and the detector was fixed at 100 cm. The center X-ray was perpendicular to the fourth lumbar spine and the only bottom AEC chamber was used. All data were analyzed by independent t-test and ANOVA. As a result of this study, with AEC when the center is matched, ESD was 1.31±0.01 mGy, without AEC was 2.12±0.01 mGy. SNR was shown to be 22.81±1.83, and 23.44±1.87 respectively. When the phantom's center moves 4 cm, 8 cm forward, and 4 cm, 8 cm backward, ESD were 1.09±0.004 mGy, 0.32±0.003 mGy, 1.19±0.017 mGy, 1.11±0.006 mGy respectively, SNR were 18.29±0.60 dB, 11.11±0.22 dB, 18.98±0.80 dB, 17.71±0.82 dB. Using AEC in L-spine lateral radiography reduced ESD by 38%, EI by 35%, and mAs by 38%, without any difference in SNR(p<0.05). When the phantom's center moves 4 cm, 8 cm forward, and 4 cm, 8 cm backward, ESD was decreasing each 16%, 75%, 9%, 15%, EI was decreasing each 14%, 77%, 15%, 20%, mAs was decreasing each 15% 75% 9%, 15%. SNR was decreasing each 19%, 51%, 17%, 22%.

Analysis of Propagation Environment for Selecting R-Mode Reference and Integrity Station (R-Mode 보정국과 감시국 선정을 위한 전파환경 분석에 관한 연구)

  • Jeon, Joong-Sung;Jeong, Hae-Sang;Gug, Seung-Gi
    • Journal of Navigation and Port Research
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    • v.45 no.1
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    • pp.26-32
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    • 2021
  • In ocean field, the spread of the Fourth Industrial Revolution based on information and communication technology requires high precision and stable PNT&D (Position, Navigation, Timing and Data). As the IMO (International Maritime Organization) and IALA (The International Association of Marine Aids to Navigation and Lighthouse Authorities) are requiring backup systems due to mitigate vulnerabilities and the increase of dependency on GNSS (Global Navigation Satellite System), Korea is conducting a research & development of R-Mode. An DGPS (Differentiate Global Positioning System) reference station that uses MF, an existing maritime infrastructure, and AIS (Automatic Identification System) base stations that use 34 integrity station and VHF will be utilized in this study to avoid redundant investment. Because there are radio shadow areas that display low signal levels in the west sea, the establishment of new R-Mode reference and integrity station will be intended to resolve problems regrading the radio shadow area. Because the frequency has a characteristic in that radio wave transmits well along the ground (water surface) in low frequency band, simulation and measurement were conducted therefore this paper to propose candidate sites for R-Mode reference and integrity station resulted through p wave's propagation characteristics analysis. Using this paper, R-Mode reference and integrity station can be established at appropriate locations to resolve radio shadow areas in other regions.

A Study on the Analysis of R&D Trends and the Development Plan of Electronic Attack System (전자공격체계 연구개발 동향 분석과 발전방안에 대한 연구)

  • Sim, Jaeseong;Park, Byoung-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.6
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    • pp.469-476
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    • 2021
  • An electronic attack (EA) system is an essential weapon system for performing electronic warfare missions that contain signal tracking and jamming against multiple threats using electromagnetic waves, such as air defense radars, wireless command and communication networks, and guided missiles. The combat effectiveness can be maximized, and the survivability of militarily protecting combat power can be enhanced through EA mission operations, such as disabling the functions of multiple threats. The EA system can be used as a radio frequency jamming system to respond to drone attacks on the core infrastructure, such as airports, power plants, and communication broadcasting systems, in the civilian field. This study examined the criteria for classification according to the electronic attack missions of foreign EA systems based on an aviation platform. The foreign R&D trends by those criteria were investigated. Moreover, by analyzing the R&D trends of domestic EA systems and future battlefields in the domestic security environments, this paper proposes technological development plans of EA systems suitable for the future battlefield environments compared to the foreign R&D trends.

Estimation of Significant Wave Heights from X-Band Radar Using Artificial Neural Network (인공신경망을 이용한 X-Band 레이다 유의파고 추정)

  • Park, Jaeseong;Ahn, Kyungmo;Oh, Chanyeong;Chang, Yeon S.
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.32 no.6
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    • pp.561-568
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    • 2020
  • Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

DOI Detector Design using Different Sized Scintillators in Each Layer (각 층의 서로 다른 크기의 섬광체를 사용한 반응 깊이 측정 검출기 설계)

  • Seung-Jae, Lee
    • Journal of the Korean Society of Radiology
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    • v.17 no.1
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    • pp.11-16
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    • 2023
  • In preclinical positron emisson tomography(PET), spatial resolution degradation occurs outside the field of view(FOV). To solve this problem, a depth of interaction(DOI) detector was developed that measures the position where gamma rays and the scintillator interact. There are a method in which a scintillation pixel array is composed of multiple layers, a method in which photosensors are arranged at both ends of a single layer, a method in which a scintillation pixel array is constituted in several layers and a photosensor is arranged in each layer. In this study, a new type of DOI detector was designed by analyzing the characteristics of the previously developed detectors. In the two-layer detector, different sizes of scintillation pixels were used for each layer, and the array size was configured differently. When configured in this form, the positions of the scintillation pixels for each layer are arranged to be shifted from each other, so that they are imaged at different positions in a flood image. DETECT2000 simulation was performed to confirm the possibility of measuring the depth of interaction of the designed detector. A flood image was reconstructed from a light signal acquired by a gamma-ray event generated at the center of each scintillation pixel. As a result, it was confirmed that all scintillation pixels for each layer were separated from the reconstructed flood image and imaged to measure the interaction depth. When this detector is applied to preclinical PET, it is considered that excellent images can be obtained by improving spatial resolution.

Ginsenoside Rg1 treatment protects against cognitive dysfunction via inhibiting PLC-CN-NFAT1 signaling in T2DM mice

  • Xianan Dong ;Liangliang Kong ;Lei Huang ;Yong Su ;Xuewang Li;Liu Yang;Pengmin Ji ;Weiping Li ;Weizu Li
    • Journal of Ginseng Research
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    • v.47 no.3
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    • pp.458-468
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    • 2023
  • Background: As a complication of Type II Diabetes Mellitus (T2DM), the etiology, pathogenesis, and treatment of cognitive dysfunction are still undefined. Recent studies demonstrated that Ginsenoside Rg1 (Rg1) has promising neuroprotective properties, but the effect and mechanism in diabetes-associated cognitive dysfunction (DACD) deserve further investigation. Methods: After establishing the T2DM model with a high-fat diet and STZ intraperitoneal injection, Rg1 was given for 8 weeks. The behavior alterations and neuronal lesions were judged using the open field test (OFT) and Morris water maze (MWM), as well as HE and Nissl staining. The protein or mRNA changes of NOX2, p-PLC, TRPC6, CN, NFAT1, APP, BACE1, NCSTN, and Ab1-42 were investigated by immunoblot, immunofluorescence or qPCR. Commercial kits were used to evaluate the levels of IP3, DAG, and calcium ion (Ca2+) in brain tissues. Results: Rg1 therapy improved memory impairment and neuronal injury, decreased ROS, IP3, and DAG levels to revert Ca2+ overload, downregulated the expressions of p-PLC, TRPC6, CN, and NFAT1 nuclear translocation, and alleviated Aβ deposition in T2DM mice. In addition, Rg1 therapy elevated the expression of PSD95 and SYN in T2DM mice, which in turn improved synaptic dysfunction. Conclusions: Rg1 therapy may improve neuronal injury and DACD via mediating PLC-CN-NFAT1 signal pathway to reduce Aβ generation in T2DM mice.

Machine Learning-based Phase Picking Algorithm of P and S Waves for Distributed Acoustic Sensing Data (분포형 광섬유 센서 자료 적용을 위한 기계학습 기반 P, S파 위상 발췌 알고리즘 개발)

  • Yonggyu, Choi;Youngseok, Song;Soon Jee, Seol;Joongmoo, Byun
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.177-188
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    • 2022
  • Recently, the application of distributed acoustic sensors (DAS), which can replace geophones and seismometers, has significantly increased along with interest in micro-seismic monitoring technique, which is one of the CO2 storage monitoring techniques. A significant amount of temporally and spatially continuous data is recorded in a DAS monitoring system, thereby necessitating fast and accurate data processing techniques. Because event detection and seismic phase picking are the most basic data processing techniques, they should be performed on all data. In this study, a machine learning-based P, S wave phase picking algorithm was developed to compensate for the limitations of conventional phase picking algorithms, and it was modified using a transfer learning technique for the application of DAS data consisting of a single component with a low signal-to-noise ratio. Our model was constructed by modifying the convolution-based EQTransformer, which performs well in phase picking, to the ResUNet structure. Not only the global earthquake dataset, STEAD but also the augmented dataset was used as training datasets to enhance the prediction performance on the unseen characteristics of the target dataset. The performance of the developed algorithm was verified using K-net and KiK-net data with characteristics different from the training data. Additionally, after modifying the trained model to suit DAS data using the transfer learning technique, the performance was verified by applying it to the DAS field data measured in the Pohang Janggi basin.

A Study on Efficient AI Model Drift Detection Methods for MLOps (MLOps를 위한 효율적인 AI 모델 드리프트 탐지방안 연구)

  • Ye-eun Lee;Tae-jin Lee
    • Journal of Internet Computing and Services
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    • v.24 no.5
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    • pp.17-27
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    • 2023
  • Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.