• Journal of Animal Reproduction and Biotechnology
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• v.34 no.4
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• pp.318-321
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• 2019

Recent studies showed that tight junctions (TJs) integrity and assembly are required for blastocyst development in mouse and pig models. However, the biological functions of TJs associated with embryo implantation and maintenance of pregnancy were not investigated yet. To examine whether disrupted TJs affect further embryo development, we employed RNAi approach and inhibitor treatment. The embryos were injected with Cxadr (Coxsackievirus and adenovirus receptor) siRNA for knock down (KD) and treated with Adam10 (A Disintegrin and Metalloproteinase specific inhibitor 10; GI254023X; SI). We compared blastocyst development and paracellular sealing assay using FITC dextran uptake between control and KD or SI embryos. Finally, we transferred control and Cxadr KD or Adam 10 SI treated blastocyst to uteri of recipients. Cxadr KD and Adam 10 SI showed lower blastocyst development and more permeable to FITC-dextran. Moreover, we observed that half of KD and inhibited embryos failed to maintain pregnancies after the second trimester. Our findings suggested that TJs integrity is required for the maintenance of pregnancy and can be used as a selective marker for the successful application of assisted reproduction technologies.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.179-191
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• 2012

In 2003, the US Congress enacted the Code Adam Act of 2003. The Act was so-named in memory of six-year-old Adam Walsh, who was abducted from a Sears department store in Florida and was later found murdered in 1981. According to the Act, the designated authority for a public building must establish procedures for locating a child missing in a federal facility in the USA. In this context, the study basically aims to propose a legislative model for a missing children policy in Korean multi-use facilities, critically analyzing the US Code Adam Act. Unlike the Act, the proposed Korean bill requires all multi-use facilities beyond a certain size, including private buildings, to arrange a feasible missing child procedure on their own premises. The bill can impose an administrative fine on facilities which don't have the procedure in place, and further can make the list of the facilities known to the public. In order to encourage voluntary participation from the private sector, the bill finally suggests the Voluntary Certification Scheme through which participating business can take advantage of the certification logo commercially.

• Journal of IKEEE
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• v.24 no.3
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• pp.766-776
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• 2020

Recently, as interest in machine learning (ML) has increased and research using ML has become active, it is becoming more important to find an optimal hyperparameter combination for various ML models. In this paper, among various hyperparameters, we focused on ML optimizers, and measured and compared the performance of major optimizers using various datasets. In particular, we compared the performance of nine optimizers ranging from SGD, which is the most basic, to Momentum, NAG, AdaGrad, RMSProp, AdaDelta, Adam, AdaMax, and Nadam, using the MNIST, CIFAR-10, IRIS, TITANIC, and Boston Housing Price datasets. Experimental results showed that when Adam or Nadam was used, the loss of various ML models decreased most rapidly and their F1 score was also increased. Meanwhile, AdaMax showed a lot of instability during training and AdaDelta showed slower convergence speed and lower performance than other optimizers.

• The Korean Journal of Physiology and Pharmacology
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• v.17 no.3
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• pp.189-195
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• 2013

Amyloid-${\beta}$ peptide ($A{\beta}$), generated by proteolytic cleavage of the amyloid precursor protein (APP), plays a pivotal role in the pathogenesis of Alzheimer's disease (AD). The key step in the generation of $A{\beta}$ is cleavage of APP by beta-site APP-cleaving enzyme 1 (BACE1). Levels of BACE1 are increased in vulnerable regions of the AD brain, but the underlying mechanism is unknown. In the present study, we reported the effects of ferrous ions at subtoxic concentrations on the mRNA levels of BACE1 and a-disintegrin-and-metalloproteinase 10 (ADAM10) in PC12 cells and the cell responses to ferrous ions. The cell survival in PC12 cells significantly decreased with 0 to 0.3 mM $FeCl_2$, with 0.6 mM $FeCl_2$ treatment resulting in significant reductions by about 75%. 4,6-diamidino-2-phenylindole (DAPI) staining showed that the nuclei appeared fragmented in 0.2 and 0.3 mM $FeCl_2$. APP-${\alpha}$-carboxyl terminal fragment (APP-${\alpha}$-CTF) associations with ADAM10 and APP-${\beta}$-CTF with BACE1 were increased. Levels of ADAM10 and BACE1 mRNA increased in response to the concentrations of 0.25 mM, respectively. In addition, p-ERK and p-Bad (S112, S155) expressions were increased, suggesting that APP-CTF formation is related to ADAM10/ BACE1 expression. Levels of Bcl-2 protein were increased, but significant changes were not observed in the expression of Bax. These data suggest that ion-induced enhanced expression of AMDA10/BACE1 could be one of the causes for APP-${\alpha}/{\beta}$-CTF activation.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.389-396
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• 2022

Deep Learning is based on a perceptron, and is currently being used in various fields such as image recognition, voice recognition, object detection, and drug development. Accordingly, a variety of learning algorithms have been proposed, and the number of neurons constituting a neural network varies greatly among researchers. This study analyzed the learning characteristics according to the number of neurons of the currently used SGD, momentum methods, AdaGrad, RMSProp, and Adam methods. To this end, a neural network was constructed with one input layer, three hidden layers, and one output layer. ReLU was applied to the activation function, cross entropy error (CEE) was applied to the loss function, and MNIST was used for the experimental dataset. As a result, it was concluded that the number of neurons 100-300, the algorithm Adam, and the number of learning (iteraction) 200 would be the most efficient in deep learning learning. This study will provide implications for the algorithm to be developed and the reference value of the number of neurons given new learning data in the future.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.709-715
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• 2023

In this study, the performance evaluation of image quality for noise reduction was implemented using the U-net deep learning architecture in computed tomography (CT) images. In order to generate input data, the Gaussian noise was applied to ground truth (GT) data, and datasets were consisted of 8:1:1 ratio of train, validation, and test sets among 1300 CT images. The Adagrad, Adam, and AdamW were used as optimizer function, and 10, 50 and 100 times for number of epochs were applied. In addition, learning rates of 0.01, 0.001, and 0.0001 were applied using the U-net deep learning model to compare the output image quality. To analyze the quantitative values, the peak signal to noise ratio (PSNR) and coefficient of variation (COV) were calculated. Based on the results, deep learning model was useful for noise reduction. We suggested that optimized hyper parameters for noise reduction in CT images were AdamW optimizer function, 100 times number of epochs and 0.0001 learning rates.

• Journal of the Korean Society of Radiology
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• v.18 no.1
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• pp.21-26
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• 2024

The one of the famous deep learning models for object detection task is you only look once version 5 (YOLOv5) framework based on the one stage architecture. In addition, YOLOv5 model indicated high performance for accurate lesion detection using the bottleneck CSP layer and skip connection function. The purpose of this study was to evaluate the performance of YOLOv5 framework according to various hyperparameters in position emission tomogrpahy (PET) phantom images. The dataset was obtained from QIN PET segmentation challenge in 500 slices. We set the bounding box to generate ground truth dataset using labelImg software. The hyperparameters for network train were applied by changing optimization function (SDG, Adam, and AdamW), activation function (SiLU, LeakyRelu, Mish, and Hardwish), and YOLOv5 model size (nano, small, large, and xlarge). The intersection over union (IOU) method was used for performance evaluation. As a results, the condition of outstanding performance is to apply AdamW, Hardwish, and nano size for optimization function, activation function and model version, respectively. In conclusion, we confirmed the usefulness of YOLOv5 network for object detection performance in nuclear medicine images.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.2
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• pp.8-15
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• 2004

This paper presents a method of improvement of color mixing in an RGB LED white lamp. The deviation from white light after RGB color mixing results mainly from the difference in the ray direction among LEDs. The authors propose a method using tilted lenses covered over each LED to deflect the overall direction of the ray generated from far-sited LEDs toward the center axis of the lamp. The degree of improvement is evaulated using a color discrimination method based on McAdam ellipse.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.3
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• pp.241-249
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• 2014

This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.

• Mass Spectrometry Letters
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• v.10 no.4
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• pp.108-111
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• 2019

The hydrolysis of penicillin G, carbenicillin and ampicillin in pure water at room temperature was studied by high pressure liquid chromatography electrospray ionization mass spectrometry. Hydrolysis of ampicillin did not occur under these conditions; however, penicillin G and carbenicillin were completely hydrolyzed after seven days. A short interpretation of this difference is proposed. The mass spectrometric behaviour, namely ESI response and fragmentation pathway, of hydrolyzed penicillin G and hydrolyzed carbenicillin have been also discussed.