• Journal of the Semiconductor & Display Technology
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• v.18 no.1
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• pp.1-4
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• 2019

Reactive sputtering is widely used because of its high deposition rate and high step coverage. The deposition layer is often affected by target poisoning because the target conditions are changed, as well, by reactive gases during the initial stage of sputtering process. The reactive gas affects the deposition rate and process stability (target poisoning), and it also leads unintended oxide interlayer formation. Although the target poisoning mechanism has been well known, little attention has been paid on understanding the interlayer formation during the reactive sputtering. In this research, we studied the interlayer formation during the reactive sputtering. A DC magnetron sputtering process is carried out to deposit an aluminum oxide film on a silicon wafer. From the real-time process monitoring and material analysis, the target poisoning phenomena changes the reactive gas balance at the initial stage, and affects the interlayer formation during the reactive sputtering process.

• The Journal of Information Systems
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• v.30 no.3
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• pp.201-216
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• 2021

Purpose The purpose of this study is to analyze the trend of patent technology in textile materials using text mining methodology based on Dynamic Embedded Topic Model and Structural Topic Model. It is expected that this study will have positive impact on revitalizing and developing textile materials industry as finding out technology trends. Design/methodology/approach The data used in this study is 866 domestic patent text data in textile material from 1974 to 2020. In order to analyze technology trends from various aspect, Dynamic Embedded Topic Model and Structural Topic Model mechanism were used. The word embedding technique used in DETM is the GloVe technique. For Stable learning of topic modeling, amortized variational inference was performed based on the Recurrent Neural Network. Findings As a result of this analysis, it was found that 'manufacture' topics had the largest share among the six topics. Keyword trend analysis found the fact that natural and nanotechnology have recently been attracting attention. The metadata analysis results showed that manufacture technologies could have a high probability of patent registration in entire time series, but the analysis results in recent years showed that the trend of elasticity and safety technology is increasing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2321-2338
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• 2021

Compared with vehicle trajectories, pedestrian trajectories have stronger degrees of freedom and complexity, which poses a higher challenge to trajectory prediction tasks. This paper designs a mode to divide the trajectory of pedestrians at a traffic intersection, which converts the trajectory regression problem into a trajectory classification problem. This paper builds a deep model for pedestrian trajectory prediction at intersections for the task of pedestrian short-term trajectory prediction. The model calculates the spatial correlation and temporal dependence of the trajectory. More importantly, it captures the interactive features among pedestrians through the Attention mechanism. In order to improve the training speed, the model is composed of pure convolutional networks. This design overcomes the single-step calculation mode of the traditional recurrent neural network. The experiment uses Vulnerable Road Users trajectory dataset for related modeling and evaluation work. Compared with the existing models of pedestrian trajectory prediction, the model proposed in this paper has advantages in terms of evaluation indicators, training speed and the number of model parameters.

• Korean Journal of Metals and Materials
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• v.46 no.5
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• pp.296-303
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• 2008

Hydrogen permeation through dense palladium-based membranes has attracted the attention of many scientists largely due to their unmatched potential as hydrogen-selective membranes for membrane reactor applications. Although it is well known that the permeation mechanism of hydrogen through Pd involves various processes such as dissociative adsorption, transitions to and from the bulk Pd, diffusion within Pd, and recombinative desorption, it is still unclear which process mainly limits hydrogen permeation at a given temperature and hydrogen partial pressure. In this study, we report an all-electron density-functional theory study of hydrogen permeation through Pd membrane (using VASP code). Especially, we focus on the variation of the energy barrier of the penetration process from the surface to the bulk with hydrogen coverage, which means the large reduction of the fracture stress in the brittle crack propagation considering Griffith's criterion. It is also found that the penetration energy barrier from the surface to the bulk largely decreases so that it almost vanishes at the coverage 1.25, which means that the penetration process cannot be the rate determining process.

• Journal of Ginseng Research
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• v.46 no.2
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• pp.214-224
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• 2022

Red ginseng oil (RGO), rather than the conventional aqueous extract of red ginseng, has been receiving much attention due to accumulating evidence of its functional and pharmacological potential. In this review, we describe the key extraction technologies, chemical composition, potential health benefits, and safety of RGO. This review emphasizes the proposed molecular mechanisms by which RGO is involved in various bioactivities. RGO is mainly produced using organic solvents or supercritical fluid extraction, with the choice of method greatly affecting the yield and quality of the end products. RGO contains a high unsaturated fatty acid levels along with considerable amounts of lipophilic components such as phytosterols, tocopherols, and polyacetylenes. The beneficial health properties of RGO include cellular defense, antioxidation, anti-inflammation, anti-apoptosis, chemoprevention, hair growth promotion, and skin health improvement. We propose several molecular mechanisms and signaling pathways that underlie the bioactivity of RGO. In addition, RGO is regarded as safe and nontoxic. Further studies on RGO must focus on a deeper understanding of the underlying molecular mechanisms, composition-functionality relationship, and verification of the bioactivities of RGO in clinical models. This review may provide useful information in the development of RGO-based products in nutraceuticals, functional foods, and functional cosmetics.

• Journal of the Korean Society of Visualization
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• v.19 no.3
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• pp.130-135
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• 2021

Water vapor has received worldwide large attention due to its broad technological implications ranged from resource production and environmental remediation. Especially, one of the typical areas where the water vapor is important is the removal of PM (particulate matter) which causes a critical hazard to human health. However, most vapor-based PM removal methods are limited in removing PM2.5 by using relatively large water droplets and consume large energy. Here, we propose a superhydrophilic thermally-insulated macroporous membrane to generate steam flow. The water vapor directly captures PM with steam flow and hygroscopic characteristic of PM. The steam, the cluster of water vapor, from the membrane gives rise to high removal efficiencies compared to those of the control case without light illumination. To reveal PM removal mechanism, the steam flow and PM were quantitatively analyzed using PIV measurement. The proposed steam generator could be utilized as an economical and ecofriendly platform for effective PM removal at a fairly low cost in a sustainable, energy-free, and harmless-to-human manner.

• Journal of Korea Game Society
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• v.21 no.6
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• pp.111-124
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• 2021

Starting with painting, it is the frame that plays the main role in movies, cartoons, and games as well as the act of attracting the audience's attention. Knowing about a frame is to be able to read and use the frame. Therefore, this paper deals with frames of digital games, especially multiple frames that complement the limited configuration of primary frames. In this paper, frame within frames are classified into structural frames, which are the basic components of the game, temporal frames, which reflect player behavior, and surface frames representing the characteristics of existing visual media. Through this, we examine the aspects of frame within a frame as digital game design equipment. This paper is meaningful in that it derives the possibility of using frame within a frame of games in the future and provides a mechanism for frame within a frame analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.771-791
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• 2022

Protein-protein interaction (PPI) extraction from original text is important for revealing the molecular mechanism of biological processes. With the rapid growth of biomedical literature, manually extracting PPI has become more time-consuming and laborious. Therefore, the automatic PPI extraction from the raw literature through natural language processing technology has attracted the attention of the majority of researchers. We propose a PPI extraction model based on the large pre-trained language model and adversarial training. It enhances the learning of semantic and syntactic features using BioBERT pre-trained weights, which are built on large-scale domain corpora, and adversarial perturbations are applied to the embedding layer to improve the robustness of the model. Experimental results showed that the proposed model achieved the highest F1 scores (83.93% and 90.31%) on two corpora with large sample sizes, namely, AIMed and BioInfer, respectively, compared with the previous method. It also achieved comparable performance on three corpora with small sample sizes, namely, HPRD50, IEPA, and LLL.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.3
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• pp.877-893
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• 2022

With the development of deep learning, face inpainting has been significantly enhanced in the past few years. Although image inpainting framework integrated with generative adversarial network or attention mechanism enhanced the semantic understanding among facial components, the issues of reconstruction on corrupted regions are still worthy to explore, such as blurred edge structure, excessive smoothness, unreasonable semantic understanding and visual artifacts, etc. To address these issues, we propose a Learnable Structure Knowledge of Fusion Network (LSK-FNet), which learns a prior knowledge by edge generation network for image inpainting. The architecture involves two steps: Firstly, structure information obtained by edge generation network is used as the prior knowledge for face inpainting network. Secondly, both the generated prior knowledge and the incomplete image are fed into the face inpainting network together to get the fusion information. To improve the accuracy of inpainting, both of gated convolution and region normalization are applied in our proposed model. We evaluate our LSK-FNet qualitatively and quantitatively on the CelebA-HQ dataset. The experimental results demonstrate that the edge structure and details of facial images can be improved by using LSK-FNet. Our model surpasses the compared models on L1, PSNR and SSIM metrics. When the masked region is less than 20%, L1 loss reduce by more than 4.3%.

• Composites Research
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• v.35 no.3
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• pp.121-126
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• 2022

Owing to advantages of polymeric materials for hydrogen tank liner like light-weight property and high specific strength, polymer based composites have gained much attention. Despite of many benefits, polymeric materials for fuel cell tank cause problems which is critical to applications as low gas barrier property, and poor processability when adding fillers. For these reasons, improving gas barrier property of polymer composites is required to study for expanding application fields. This work presents impermeable polymer nanocomposites by introducing thin barrier coating using layer by layer (LBL) deposition method. Also, bi-layered and quad-layered nanocomposites were fabricated and compared for identifying relationship between deposition step and gas barrier property. Reduction in gas permeability was observed without interrupting mechanical property and processability. It is discussed that proper coating conditions were suggested when different coating materials and deposition steps were applied. We investigated morphology, gas barrier property and mechanical properties of fabricated nanocomposites by FE-SEM, Oxygen permeation analyzer, UTM, respectively. In addition, we revealed the mechanism of barrier performance of LBL coating using materials which have high aspect ratio.