يعرض 1 - 10 نتائج من 1,240 نتيجة بحث عن '"Geon Kim"', وقت الاستعلام: 0.68s تنقيح النتائج
  1. 1
    دورية أكاديمية

    المصدر: Scientific Data, Vol 11, Iss 1, Pp 1-18 (2024)

    مصطلحات موضوعية: Science

    الوصف: Abstract As IoT technology advances, using machine learning to detect user activities emerges as a promising strategy for delivering a variety of smart services. It is essential to have access to high-quality data that also respects privacy concerns and data streams from ambient sensors in the surrounding environment meet this requirement. However, despite growing interest in research, there is a noticeable lack of datasets from ambient sensors designed for public spaces, as opposed to those for private settings. To bridge this gap, we design the DOO-RE dataset within an actual meeting room environment, equipped with three types of ambient sensors: those triggered by actuators, users, and the environment itself. This dataset is compiled from the activities of over twenty students throughout a period of four months. DOO-RE provides reliable and purpose-oriented activity data in a public setting, with activity labels verified by multiple annotators through a process of cross-validation to guarantee data integrity. DOO-RE categorizes nine different types of activities and facilitates the study of both single and group activities. We are optimistic that DOO-RE will play a significant role in advancing human activity recognition technologies, enhancing smart automation systems, and enabling the rapid setup of smart spaces through ambient sensors.

    وصف الملف: electronic resource

  2. 2
    دورية أكاديمية

    المصدر: Current Issues in Molecular Biology, Vol 45, Iss 8, Pp 6415-6431 (2023)

    الوصف: Type 2 diabetes (T2D) is a serious health issue with increasing incidences worldwide. However, current medications have limitations due to side effects such as decreased appetite, stomach pain, diarrhea, and extreme tiredness. Here, we report the effect of fermented ice plant (FMC) in the T2M mouse model of db/db mice. FMC showed a greater inhibition of lipid accumulation compared to unfermented ice plant extract. Two-week oral administration with FMC inhibited body weight gain, lowered fasting blood glucose, and improved glucose tolerance. Serum parameters related to T2D including insulin, glycosylated hemoglobin, adiponectin, and cholesterols were improved as well. Histological analysis confirmed the protective effect of FMC on pancreas and liver destruction. FMC treatment significantly increased the expression and phosphorylation of IRS-1, PI3K, and AKT. Additionally, AMP-activated protein kinase phosphorylation and nuclear factor erythroid 2–related factor 2 were also increased in the liver tissues of db/db mice treated with FMC. Overall, our results indicate the anti-diabetic effect of FMC; therefore, we suggest that FMC may be useful as a therapeutic agent for T2D.

    وصف الملف: electronic resource

  3. 3
    دورية أكاديمية

    المصدر: Scientific Data, Vol 11, Iss 1, Pp 1-1 (2024)

    مصطلحات موضوعية: Science

    وصف الملف: electronic resource

  4. 4
    دورية أكاديمية

    المصدر: Fertility & Reproduction, Vol 05, Iss 04, Pp 430-431 (2023)

    مصطلحات موضوعية: Reproduction, QH471-489

    الوصف: Background and Aims: Time-lapse technology is an emerging assisted reproductive technology (ART) that enables simultaneous culture and monitoring of embryos in vitro during their development. It provides extra information on key events during embryo development, which can assist embryologists in selecting embryos alongside traditional morphology evaluations. Various imaging technologies have been utilised to visualise and evaluate embryos such as brightfield microscopy, darkfield microscopy, and Hoffman modulation contrast microscopy. Although these imaging technologies allow for non-invasive imaging of human embryos in a clinical setting, 3D imaging of a whole embryo with subcellular resolution remains a challenge. Method: We demonstrate 3D time-lapse label-free imaging of live mouse embryos using the 3D refractive index (RI) imaging technique. The proposed method is a quantitative phase imaging technique that measures multiple-intensity images of transmitted light through the embryos via axial scanning to reconstruct the 3D RI map of the embryos. Results: Using the proposed method, live mouse embryos were monitored at different developmental stages, ranging from 2-cell embryos to expanded blastocysts. The measured 3D RI maps of the developing embryos reveal 3D landscape of subcellular features inside the embryos (Fig. 1). In the quantitative assessment of embryonic development, various morphokinematic parameters were extracted from the measured 3D RI maps of the embryos. Conclusion: Based on the results, we envision that our method has broad applications where non-invasive and quantitative assessment of embryonic development is required.

    وصف الملف: electronic resource

  5. 5
    دورية أكاديمية

    المصدر: Scientific Reports, Vol 13, Iss 1, Pp 1-10 (2023)

    مصطلحات موضوعية: Medicine, Science

    الوصف: Abstract Three-dimensional (3D) quantitative phase imaging (QPI) enables long-term label-free tomographic imaging and quantitative analysis of live individual bacteria. However, the Brownian motion or motility of bacteria in a liquid medium produces motion artifacts during 3D measurements and hinders precise cell imaging and analysis. Meanwhile, existing cell immobilization methods produce noisy backgrounds and even alter cellular physiology. Here, we introduce a protocol that utilizes hydrogels for high-quality 3D QPI of live bacteria maintaining bacterial physiology. We demonstrate long-term high-resolution quantitative imaging and analysis of individual bacteria, including measuring the biophysical parameters of bacteria and responses to antibiotic treatments.

    وصف الملف: electronic resource

  6. 6
    دورية أكاديمية

    المصدر: Nuclear Engineering and Technology, Vol 54, Iss 8, Pp 2783-2791 (2022)

    الوصف: Molecular dynamics simulations were performed to predict the behavior of graphite atoms under neutron irradiation using large-scale atomic/molecular massively parallel simulator (LAMMPS) package with adaptive intermolecular reactive empirical bond order (AIREBOM) potential. Defect structures of graphite were compared with results from previous studies by means of density functional theory (DFT) calculations. The quantitative relation between primary knock-on atom (PKA) energy and irradiation damage on graphite was calculated.and the effect of PKA direction on the amount of defects is estimated by counting displaced atoms. Defects are classified into four groups: structural defects, energy defects, vacancies, and near-defect structures, where a structural defect is further subdivided into six types by decision tree method which is one of the supervised machine learning techniques.

    وصف الملف: electronic resource

  7. 7
    دورية أكاديمية

    المصدر: Light: Science & Applications, Vol 11, Iss 1, Pp 1-12 (2022)

    مصطلحات موضوعية: Applied optics. Photonics, TA1501-1820, Optics. Light, QC350-467

    الوصف: Label-free rapid deep-learning-based identification of bacterial species that classifies 3D refractive index tomograms into the species.

    وصف الملف: electronic resource

  8. 8
    دورية أكاديمية

    المصدر: IEEE Access, Vol 10, Pp 39789-39799 (2022)

    الوصف: Numerous problems have emerged with the development of HVDC transmission technology. One of them is the fault current that occurs when there is an issue in the line. In particular, in the case of a PTP (pole-to-pole) fault, a DCCB design suitable for the direction is required because the fault current flows through the positive and negative poles. In the case of PTP fault, a fault current of the same value occurs in the opposite direction, and in the case of DCCB, the breaking efficiency may be reduced or even impossible to break due to a mistake in the emission direction or a wrong design. In particular, when designing using several unidirectional DCCBs, it is cheaper and consumes less area than typical DCCBs, so it is economical, but this problem may be more prominent. To solve this problem, this paper proposes a 4- pole Hybrid HVDC circuit breaker to solve this problem. This circuit optimizes the DCCB internal components through quantitative analysis of the fault current to reduce the influence of the residual fault current as well as the previously most important parameter, Zero-Cross Time (ZCT). We also verified the circuit’s energy dissipation process to increase reliability. The circuit in this paper is simulated based on the VSC-based HVDC transmission link. Physically analyze the derived results and described the circuit mechanism.

    وصف الملف: electronic resource

  9. 9
    دورية أكاديمية

    المصدر: IEEE Access, Vol 9, Pp 111567-111575 (2021)

    الوصف: In this paper, we compare conventional saddle type FinFETs to partial isolation type saddle FinFETs (Pi-FinFETs) using 3D TCAD simulations to examine the effect of single charge traps for proper prediction of leakage current. We simulated single charge traps at various locations in the drain region, and analyzed how the traps affect leakage current. Our results show that Pi-FinFETs enhanced the leakage current characteristics given the presence of a single charge trap. Also, it was found that Pi-FinFETs exhibit half the $\text{F}_{\mathrm {TAT}}$ of S-FinFETs. Based on the results from our analysis method, where we use $\text{I}_{\mathrm {off}}$ fluctuation, the $\text{F}_{\mathrm {TAT}}$ , the $\sigma _{\mathrm {F}}$ and the $\text{P}_{\mathrm {F}}$ parameters to accurately compare performance, and present device design guidelines aimed at improving DRAM refresh characteristics.

    وصف الملف: electronic resource

  10. 10
    دورية أكاديمية

    المصدر: Scientific Reports, Vol 9, Iss 1, Pp 1-9 (2019)

    مصطلحات موضوعية: Medicine, Science

    الوصف: Abstract In tomographic reconstruction, the image quality of the reconstructed images can be significantly degraded by defects in the measured two-dimensional (2D) raw image data. Despite the importance of screening defective 2D images for robust tomographic reconstruction, manual inspection and rule-based automation suffer from low-throughput and insufficient accuracy, respectively. Here, we present deep learning-enabled quality control for holographic data to produce robust and high-throughput optical diffraction tomography (ODT). The key idea is to distil the knowledge of an expert into a deep convolutional neural network. We built an extensive database of optical field images with clean/noisy annotations, and then trained a binary-classification network based upon the data. The trained network outperformed visual inspection by non-expert users and a widely used rule-based algorithm, with >90% test accuracy. Subsequently, we confirmed that the superior screening performance significantly improved the tomogram quality. To further confirm the trained model’s performance and generalisability, we evaluated it on unseen biological cell data obtained with a setup that was not used to generate the training dataset. Lastly, we interpreted the trained model using various visualisation techniques that provided the saliency map underlying each model inference. We envision the proposed network would a powerful lightweight module in the tomographic reconstruction pipeline.

    وصف الملف: electronic resource