• 한국의류학회지
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• 제5권1호
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• pp.23-26
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• 1981

In this paper, the extraction mechanism of free formaldehyde in the urea formaldehyde resin finished cotton fabric is discussed. An empirical equation for formaldehyde release has been formulated. $$F=3.7\times10^{-3}\;H\;T^{2.2326}+440$$ in which, F: the amount of free formaldehyde extracted ($\mu$g/g) H: extraction time (min) T: extraction temperature ($^{\circ}C$)

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.245-265
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• 2022

In response to problems such as insufficient extraction information, low detection accuracy, and frequent misdetection in the field of Thangka image defects, this paper proposes a YOLOv5 prediction algorithm fused with the attention mechanism. Firstly, the Backbone network is used for feature extraction, and the attention mechanism is fused to represent different features, so that the network can fully extract the texture and semantic features of the defect area. The extracted features are then weighted and fused, so as to reduce the loss of information. Next, the weighted fused features are transferred to the Neck network, the semantic features and texture features of different layers are fused by FPN, and the defect target is located more accurately by PAN. In the detection network, the CIOU loss function is used to replace the GIOU loss function to locate the image defect area quickly and accurately, generate the bounding box, and predict the defect category. The results show that compared with the original network, YOLOv5-SE and YOLOv5-CBAM achieve an improvement of 8.95% and 12.87% in detection accuracy respectively. The improved networks can identify the location and category of defects more accurately, and greatly improve the accuracy of defect detection of Thangka images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.980-997
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• 2024

To improve the brightness of images and reveal hidden information in dark areas is the main objective of low-light image enhancement (LLIE). LLIE methods based on deep learning show good performance. However, there are some limitations to these methods, such as the complex network model requires highly configurable environments, and deficient enhancement of edge details leads to blurring of the target content. Single-scale feature extraction results in the insufficient recovery of the hidden content of the enhanced images. This paper proposed an edge detection-based multi-scale feature enhancement network for LLIE (EDMFEN). To reduce the loss of edge details in the enhanced images, an edge extraction module consisting of a Sobel operator is introduced to obtain edge information by computing gradients of images. In addition, a multi-scale feature enhancement module (MSFEM) consisting of multi-scale feature extraction block (MSFEB) and a spatial attention mechanism is proposed to thoroughly recover the hidden content of the enhanced images and obtain richer features. Since the fused features may contain some useless information, the MSFEB is introduced so as to obtain the image features with different perceptual fields. To use the multi-scale features more effectively, a spatial attention mechanism module is used to retain the key features and improve the model performance after fusing multi-scale features. Experimental results on two datasets and five baseline datasets show that EDMFEN has good performance when compared with the stateof-the-art LLIE methods.

• 한국멀티미디어학회논문지
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• 제15권4호
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• pp.540-551
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• 2012

최근, W3C에서는 웹을 통해 다양한 웹 응용을 제공할 수 있는 기능을 포함하는 HTML5의 표준화가 추진 중이다. 광대역 무선 네트워크의 등장 및 스마트 TV, 태블릿 PC, 스마트 폰과 같은 스마트 단말이 웹 브라우저를 탑재함에 따라 스마트 단말을 통해 언제 어디서나 웹 서비스를 이용하는 것이 가능해졌다. 또한 사용자가 다수의 단말을 보유함에 따라 상황에 맞는 단말을 사용하여 웹 응용을 이용하는 멀티스크린 서비스의 요구가 증가하고 있다. 본 논문에서는 HTML5 기반의 웹 플랫폼에서 웹 객체를 그룹화하는 방안, 이동할 웹 객체의 정보를 추출하는 방안 및 다른 단말로부터 전달받은 웹 객체 정보를 기반으로 새로운 객체를 생성하는 방안을 제안한다. 또한 HTML5 기반 개방형 웹 플랫폼에서 단말 간 웹 응용을 이동하는 웹 서비스 이동 구조를 제안하였으며 이를 구현하여 테스트용 웹 문서와 일반 웹 문서에 대해 크롬 확장기능을 이용하여 검증하였다. 마지막으로 node.js와 웹 소켓을 이용하여 단말 간 객체 정보를 전달하는 메커니즘을 구현하고 제안한 방안을 검증하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• Bulletin of the Korean Chemical Society
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• 제29권1호
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• pp.94-98
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• 2008

A fundamental study was developed concerning the novel solvent extraction of the tetravalent metal ions; zirconium(IV), hafnium(IV) and thorium(IV). Their extraction behavior in toluene was investigated with a recently synthesized naphthol-derivative Schiff base, 1-({[4-(4-{[(E)-1-(2-hydroxy-1-naphthyl)methyliden]amino}phenoxy) phenyl]imino}methyl)-2-naphthol (HAPMN). The spectrophotometrical examination of the complex formation between HAPMN and the Zr(IV), Hf(IV) and Th(IV) ions in acetonitrile revealed the formation of stable 1:1 complexes in the solution. After the thorium extraction in toluene, it was found that [Th(OH)3HA] was the respective deriving substance. While, in the case of zirconium and hafnium extraction, the extracted adduct was found to be [M4(OH)8(H2O)16Cl62HA]. The stoichiometric coefficients of these extracted species were determined by the slope analysis method. The extraction reaction followed a cation exchange mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권3호
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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.

• Applied Science and Convergence Technology
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• 제27권3호
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• pp.47-51
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• 2018

We fabricated an anode-type ion beam source and studied its driving characteristics of the initial extraction of ions using two driving mechanisms: a diffusion phenomenon and a charge repulsion phenomenon. For specimen exposed to the ion beam in two methods, the surface impurity element was investigated by using X-ray photoelectron spectroscopy. Upon Ar gas injection for plasma generation the ion beam source was operated for 48 hours. We found a Fe 2p peak 5.4 at. % in the initial ions by the diffusion mechanism while no indication of Fe in the ions released in the charge repulsion mechanism. As for a long operation of 200 min, the temperature of ion beam sources was measured to increase at the rate of ${\sim}0.1^{\circ}C/min$ and kept at the initial value of $27^{\circ}C$ for driving by diffusion and charge repulsion mechanism, respectively. In this study, we confirmed that the ion beam source driven by the charge repulsion mechanism was very efficient for a long operation as proved by little electrode damage and thermal stability.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 추계학술대회 논문집 학회본부
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• pp.395-397
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• 1995

To investigate the effects of solvent extraction on electrical properties of LDPE, charge distribution, electrical conduction, and FT-IR experiments are carried out for three kinds of LDPE which are same for melt index (MI) and density. The effects of short chains for the charge distribution are quite different. For the electrical conduction, the electrical conduction mechanism remains unchanged, as the solvent extraction temperature is increased.

• Korean Chemical Engineering Research
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• 제57권3호
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• pp.313-320
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• 2019

Extraction/separation of cobalt by supported liquid membrane has been reviewed. The review discusses various directions associated with the supported liquid membrane process, such as the kind of supported liquid membrane, the principle of supported liquid membrane, transport mechanism involved, and the advantages and disadvantages of the supported liquid. Finally, extraction and separation of cobalt from other metals using extractant through supported liquid membrane have been reviewed. Separation of cobalt using various reagents and cobalt recovery from scrap using commercial extractant can be a potential perspective from the application of supported liquid membrane application.