• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.283-301
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• 2020

In Korean society, words related to misogyny are being created and spread out in the Internet communities and the Internet news posts comments. This study was conducted to investigate if exposure to misogynistic words affects misogynistic attitudes toward women. Study 1 examined the relationship between exposure of misogynistic words (the number of misogynistic words known and the level of Internet comments viewed) and explicit misogynistic attitudes. As a result, the greater the exposure of misogynistic words, the less explicit misogynistic attitudes were found among men. The result can be explained as a desensitization of stimuli caused by repetitive exposure to media. In Study 2, experiments were conducted to manipulate the exposure of misogynistic words and to identify the relationship between implicit misogynistic attitudes through implicit association tests. Results of analysis show that implicit misogyny attitude is stronger as male participants are exposed to misogynistic words. The finding of this study suggests that explicit and implicit attitudes toward misogyny can diverge. It also implies that the exposure to misogynistic words can affect men's and women's attitudes in a different manner.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.175-183
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• 2022

With the expansion of the automobile market, the demand for Nd as an essential rare earth material for automobile motors is rapidly increasing. Research on the calcio-thermic reduction process between Nd₂O₃ and calcium-based alloys has been extensively studied in order to manufacture Nd. In this study, Ca-Cu, as a reducing for Nd₂O₃, was prepared by electrolysis in CaCl₂ molten salt. Cu wire and graphite were employed as a working electrode and a counter electrode for electrolysis reaction, respectively. The reference electrode was manufactured by putting Ag wire in a mixture of AgCl and CaCl₂ at a ratio of 1:99 mol%. The cyclic voltammetry results showed that the deposition of Ca²⁺ on the surface of working electrode was observed from a potential of -1.8 V, and the reduction potential of Ca²⁺ decreased as the reaction temperature increased. The diffusion coefficient of Ca²⁺ calculated by the chronoamperometry experiment was found to be 5.4(±6.8)×10^-6 cm²/s. In addition, Ca-Cu liquid alloy was prepared by applying a constant potential to Cu electrodes. The element ratio of Ca-Cu alloy formed by applying a potential of -2.0 V was found to Ca:Cu=1:4.

• Journal of Plant Biotechnology
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• v.49 no.3
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• pp.163-170
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• 2022

There is a continuous rise in the commercialization of living modified (LM) organisms worldwide. While LM plants have not yet been cultivated in South Korea, research, development, import of products, and registration of related research facilities are progressing. LM plants should be tested in greenhouses and fields during development. Furthermore, environmental risk assessment and safety management should be performed before their release into the environment. Research on LM plant development is conducted in laboratories as well as confined greenhouses and fields. Safety management regulations are provided as combination standards for the LMO Act in each research district. The accidental release of the LM petunia in Japan was a significant incident related to LM plant research. It implies that normal plants within the distance of crossing should be regarded as LM plants. In the United States, LM creeping bentgrass was released into the environment, thus necessitating the establishment of stringent measures to prevent the scattering of LM plant seeds by wind or other mediums. In South Korea, LM Zoysia and LM cotton were released through rainwater. Therefore, safety measures that prevent LM seed mixing and plant vegetative propagules escaping into the environment via rainwater must be established. Preventing the dispersal of unapproved LM plants requires significant time, expenditure, and effort. Researchers should first identify the impact of LM plants on the ecosystem, and steps to avert their environmental release must be implemented.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.941-948
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• 2022

Disaster response robots are deployed to disaster sites where human access is difficult and dangerous. The disaster response robots explore the disaster sites prevent a structural collapse and perform lifesaving to minimize damage. It is difficult to operate robots in the disaster sites due to rough terrains where various obstacles are scattered, communication failures and invisible environments. In this paper, we developed a series connectable wheeled robot module. The series connectable wheeled robot module was developed into two types: an active driven robot module and a passive driven robot module. A wheeled robot was built by connecting the two active type robot modules and one passive type robot module. Two robot modules were connected by one DoF rotating joint, allowing the wheeled robot to avoid obstructions in a vertical direction. The wheeled robot performed driving and obstacle avoidance using only pressure sensors, which allows the wheeled robot operate in the invisible environment. An obstacle avoidance experiment was conducted to evaluate the performance of the wheeled robot consisting of two active driven wheeled robot modules and one passive driven wheeled robot module. The wheeled robot successfully avoided step-shaped obstacles with a maximum height of 80 mm in a time of 24.5 seconds using only a pressure sensors, which confirms that the wheeled robot possible to perform the driving and the obstacle avoidance in invisible environment.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.185-200
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• 2022

The innovative development of museum cultural products is an important way for museums to play the function of cultural communication with their collections. In the context of consumer upgrading, traditional cultural product design and sales methods gradually fail to meet the diverse needs of consumers. This study aims to propose the construction of a customized interactive experience platform for museum cultural products, promote the development of museum cultural products, and facilitate the inheritance and preservation of museum culture. The research methodology analyzes the model and characteristics of existing cultural product customization platforms by collating existing literature studies, and distributes 159 questionnaires to investigate the needs of cultural product consumers, and finally combines the customization experience with existing e-tailing platform systems according to user needs, proposes a theoretical framework and conducts design practice and usability testing using the Shenyang Palace Museum as an example. The findings show that users have a high acceptance of the customized platform for cultural products and that the design of the customized platform can be used to promote the dissemination of the cultural connotations of museums, optimize the personalized user experience of cultural products, and provide new ideas for the development, design, and retailing of museum cultural products. Based on the above findings, this paper suggests that museums' cultural product development can utilize the design model of customized platforms to further enhance consumers' personalized service experience.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.230-237
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• 2022

It is essential that service life of reinforced concrete structures in economic and safety aspects should be secured. It is well-known that chloride attack is a typical deterioration mechanism in field concrete structures. To prevent serious accidents like collapse, many studies have been conducted to increase resistance of chloride ingress using concrete mixed with GGBS. The usage of GGBS concrete is nowadays mandatory. Since most concretes in the field are unsaturated, study regarding chloride absorption is necessary, but many studies have focused on the chloride diffusion phenomenon. Methods for evaluating chloride absorption are cost and improper in the field. It is necessary to develop a simple method for evaluating chloride absorption in practice. This study evaluated resistance of chloride ingress in GGBS concretes with impedance measurement and absorption test. From the results, it was confirmed that the contents of absorbed chloride were linearly correlated with the measured electrical resistivities (or conductivities) in the concrete. At the end of the test, the electrical conductivities were 250.8 S/m (w/b=0.4) and 303.1 S/m (w/b=0.6) for PC concretes, and 2.6 S/m (w/b=0.4) and 64.4 S/m (w/b=0.6) for GGBS concretes, respectively. Considering influencing factors for chloride absorption and impedance measurement, chloride ingress into concrete is mainly affected by pore structures due to replacement of GGBS. Especially, formations of pore structure are different with binder, thereby binders should be considered in building reinforced concrete structures exposed to chloride environments.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• Journal of the Korean GEO-environmental Society
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• v.24 no.1
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• pp.15-23
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• 2023

The grouting method is a method of construction for the purpose of waterproofing and reinforcing soft ground. When grout is injected into the ground, there are various types of penetration and diffusion of grout depending on the shape of the ground, the size of soil, the porosity, and the presence or absence of groundwater. the current situation. Therefore, in this study, to investigate the penetration performance of the grouting to conductive material, laboratory tests were performed on the addition of the conductive material. In the injection test, 0%, 3%, and 5% of the mixed water were added as conductive materials to the grout, and the original ground condition was composed of various types of ground composed of gravel and silica sand. Conductive grout is injected by pressure into the model ground using a dedicated injection device, and the injection time (t), pressure (p), flow rate (v) and injection amount (q) are measured, and the hardened body injected in the model ground is collected. Penetration performance was evaluated. In the results of the grout injection experiment, the amount of conductive material used and the grout injection rate showed an inverse relationship, and it was confirmed that the penetration pattern was changed according to the size of the soil particles in the model ground. The grout containing the conductive material has relatively good penetration into the ground and excellent strength and durability of the hardened body, so it was judged that it could be used as an additive for measuring the penetration range of the grout.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.