• Composites Research
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• v.34 no.3
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• pp.192-198
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• 2021

Due to enormous market growing of electric vehicles without combustion engine, reducing unwanted BSR (buzz, squeak, and rattle) noise is highly demanded for vehicle quality and performance. Particularly, innerbelt weatherstrips which not only block wind noise, rain, and dust from outside, but also reduce noise and vibration of door glass and vehicle are required to exhibit high damping properties for improved BSR performance of the vehicle. Thermoplastic elastomers (TPEs), which can be recycled and have lighter weight than thermoset elastomers, are receiving much attention for weatherstrip material, but TPEs exhibit low material damping and compression set causing frictional noise and vibration between the door glass and the weatherstrip. In this study, high damping EPDM (ethylene-propylene-diene monomer)/PP (polypropylene) thermoplastic vulcanizates (TPV) were investigated by varying EPDM/PP ratio and ENB (ethylidene norbornene) fraction in EPDM. Viscoelastic properties of TPV materials were characterized by assuming that the material damping is directly related to the viscoelasticity. The optimum material damping factor (tanδ peak 0.611) was achieved with low PP ratio (14 wt%) and high ENB fraction (8.9 wt%), which was increased by 140% compared to the reference (tanδ 0.254). The improved damping is believed due to high fraction of flexible EPDM chains and higher interfacial slippage area of EPDM particles generated by increasing ENB fraction in EPDM. The stick-slip test was conducted to characterize frictional noise and vibration of the TPV weatherstrip. With improved TPV material damping, the acceleration peak of frictional vibration decreased by about 57.9%. This finding can not only improve BSR performance of electric vehicles by designing material damping of weatherstrips but also contribute to various structural applications such as urban air mobility or aircrafts, which require lightweight and high damping properties.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.234-241
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• 2022

Wheat (Triticum aestivum L.) is a major staple foods and is in increasing demand in the world. The elevated temperature caused by changes in climate and environmental conditions is a major factor affecting wheat development and grain quality. The optimal temperature range for winter wheat is between 15 and 25℃, and it is necessary to study the physiological characteristic of wheat according to elevated temperatures. This study presents the effect of elevated temperature on the yield and quality of two Korean bread wheat (Baekkang and Jokyoung) in temperature gradient tunnels (TGT). Two bread wheat cultivars were grown in TGT at four different temperature conditions: T0 (control, near ambient temperature), T1 (T0+1℃), T2 (T0+2℃), (T0+2℃), T3 (T0+3℃). The period from sowing to heading stage accelerated and the number of grains per spike and grain yield reduced under T3 condition compared with those under T0 condition. Grain filling rate and grain maturity also accelerated with elevated temperature (T3). The increase in temperature led to the increase in protein contents, whereas decreased the total starch contents. These results are consistent with the decreased expression of starch synthesis genes and increased gliadin synthesis or gluten metabolism genes during the late grain filling stage. Taken together, our results suggest that the increase in temperature (T3) led to the decrease in grain yield by regulating the number of grains/spike, whereas increased the protein content by regulating the expression of starch and gliadin-related genes or gluten metabolism process genes expression. In addition, our results provide a useful physiological information on the response of wheat to heat stress.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.287-316
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• 2023

As global energy crisis and the COVID-19 pandemic have emerged as social issues, there is a growing demand for companies to move away from profit-centric business models and embrace sustainable management that balances environmental, social, and governance (ESG) factors. ESG activities of companies vary across industries, and industry-specific weights are applied in ESG evaluations. Therefore, it is important to develop strategic management approaches that reflect the characteristics of each industry and the importance of each ESG factor. Additionally, with the stance of strengthened focus on ESG disclosures, specific guidelines are needed to identify and report on sustainable management activities of domestic companies. To understand corporate sustainability strategies, analyzing ESG reports and news articles by industry can help identify strategic characteristics in specific industries. However, each company has its own unique strategies and report structures, making it difficult to grasp detailed trends or action items. In our study, we analyzed ESG reports (2019-2021) and news articles (2019-2022) of six companies in the 'Finance,' 'Manufacturing,' and 'IT' sectors to examine the sustainability strategies of leading domestic ESG companies. Text mining techniques such as keyword frequency analysis and topic modeling were applied to identify industry-specific, ESG element-specific management strategies and issues. The analysis revealed that in the 'Finance' sector, customer-centric management strategies and efforts to promote an inclusive culture within and outside the company were prominent. Strategies addressing climate change, such as carbon neutrality and expanding green finance, were also emphasized. In the 'Manufacturing' sector, the focus was on creating sustainable communities through occupational health and safety issues, sustainable supply chain management, low-carbon technology development, and eco-friendly investments to achieve carbon neutrality. In the 'IT' sector, there was a tendency to focus on technological innovation and digital responsibility to enhance social value through technology. Furthermore, the key issues identified in the ESG factors were as follows: under the 'Environmental' element, issues such as greenhouse gas and carbon emission management, industry-specific eco-friendly activities, and green partnerships were identified. Under the 'Social' element, key issues included social contribution activities through stakeholder engagement, supporting the growth and coexistence of members and partner companies, and enhancing customer value through stable service provision. Under the 'Governance' element, key issues were identified as strengthening board independence through the appointment of outside directors, risk management and communication for sustainable growth, and establishing transparent governance structures. The exploration of the relationship between ESG disclosures in reports and ESG issues in news articles revealed that the sustainability strategies disclosed in reports were aligned with the issues related to ESG disclosed in news articles. However, there was a tendency to strengthen ESG activities for prevention and improvement after negative media coverage that could have a negative impact on corporate image. Additionally, environmental issues were mentioned more frequently in news articles compared to ESG reports, with environmental-related keywords being emphasized in the 'Finance' sector in the reports. Thus, ESG reports and news articles shared some similarities in content due to the sharing of information sources. However, the impact of media coverage influenced the emphasis on specific sustainability strategies, and the extent of mentioning environmental issues varied across documents. Based on our study, the following contributions were derived. From a practical perspective, companies need to consider their characteristics and establish sustainability strategies that align with their capabilities and situations. From an academic perspective, unlike previous studies on ESG strategies, we present a subdivided methodology through analysis considering the industry-specific characteristics of companies.

• Journal of Wetlands Research
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• v.25 no.3
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• pp.205-212
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• 2023

This study was attempted to find out how the ecological niche and interspecies relationship of Quercus aliena and Q. serrata, which are the main constituents of potential natural vegetation along the riverside of mountains in Korea, under climate change conditions. To this end, soil moisture and soil nutrients were treated with 4 grad ients under climate change conditions with elevated CO₂ and temperature, plants we re harvested at the end of the growing season, growth responses of traits were measured, ecological niche breadth and overlap were calculated, and it was compared with that of the control group(ambient condition). In addition, the relationship between the two species was analyzed by principal component analysis using trait values. As a result, the ecological niche breadth of Q. aliena was wider than that of Q. serrata under the moisture environment conditions under climate change. Under nutrient conditions, the ecological niche of the two species were similar. In addition, the ecological overlap for soil moisture of Q. aliena and Q. serrata was wider than the soil nutrient gradient under climate change. The species with traits in which the increase in ecological niche breadth due to climate change occurred more than the decrease was Q. aliena in both water and nutrient gradients. And in the responses of the population level, due to climate change, the adaptability of Q. aliena was higher than that of Q. serrata under the soil moisture condition, but the two species were similar under the nutrient condition. These results mean that the competition between the two species occurs more severely in the water environment under climate change conditions, and at that time, Q. aliena has higher adaptability than Q. serrata.

• Korea Science and Art Forum
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• v.34
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• pp.327-337
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• 2018

Korea is rapidly becoming an aging society as much as it takes the first place among OECD countries, and as the life expectancy of Korea gradually increases, the proportion of the elders in society increases. Accordingly, the happiness of the elders is contributed to the overall social atmosphere and happiness, however, the lower quality of life of the elders due to physical, psychological and social changes can be developed into social problems such as depression and rising suicide rate. As a result, there is a social interest in improving the quality of life and satisfaction of the elders, and the senior citizen center is receiving renewed attention as a form of welfare facility that can play a pivotal role in the social activities of the elders. In recent years, efforts to improve the environment of the senior citizen center have been made due to the growing role of it, however, there is a controversy over whether the quality of the indoor environment is user-friendly or not due to the limitations of material resources and human resources. It is considered that the quality of the color environment should be improved in the senior citizen center in the way that the color environment is not only an indoor environmental factor which gives high psychological and mental effects to users but also a way to improve the environmental satisfaction at the lowest cost. Previous studies on the facilities related to the elders have been actively carried out, but they were very sporadic and there was very little information about the color environment in the related laws or in the guideline presented by cities. It is necessary to integrate guidelines that are scattered within a comprehensive range without any specific target in order to grasp the current status of the color environment and to properly evaluate it. In addition, considering that the senior citizen center is an important leisure facility for the elders that functions in a residential area with a nationwide network, the results of this study are expected to contribute to the environmental improvement of existing senior citizen center which will be activated in the future by enabling the improvement of psychological satisfaction of the elders.

• Korean Journal of Social Welfare Studies
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• v.41 no.4
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• pp.189-224
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• 2010

Nowadays Korean society has a fast growing population of North Korean immigrant youth. Especially, North Korean immigrant youth, who are discontinuing formal education, experience difficulties in social exclusion and adaptation. Therefore, the purpose of this study was to understand the experiences of adaptation and social support of North Korean immigrant youth discontinuing formal education, and to seek affirmative supporting plans and solutions for their adaptation. The methodology utilized for this study was a case study research. On the basis of the results and categorization, 'a network between overall categories and of early adaptation' was derived. The major findings of this study are summarized as follows. First, the participants of this study experienced major difficulties during 'economical adaptation', and their economical adaptation was strongly interrelated with their 'educational adaptation'. The discontinuing of their education resulting from their fleeing period caused 'academic differential and age disparity.' Thus they could not enroll in the formal education system, and their insufficient educational background resulted in low wages and overwork due to manual labor jobs. Second, participants recognized 'interpersonal relations' as the most essential factor in adaptation, and 'social support' from the interpersonal relations played an important role in adaptation to and comfort in Korean society. 'Interactions with South Koreans' was recognized as a significant resource for gaining informational and appraisal support, but was not activated satisfactorily. On the other hand, interaction with North Korean immigrants was avoided by the reason that 'there's nothing to learn', however emotional support from North Korean immigrants of close relationship played an important role in participants' adaptation, especially in all aspects of psychological adaptation. Third, participants experienced a lot of difficulties and stresses in their 'physical health and psychological adaptation'. Their chronic diseases worsened by remaining untreated, and female perceived symptoms were observed more often than in male. Meanwhile, excessive 'stresses' from the unfamiliar environment of South Korea negatively affected their psychological adaptation. However, they were satisfied with sense of liberty and security from living in a democratic society.

• Korean Chemical Engineering Research
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• v.61 no.4
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• pp.523-541
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• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Korean Journal of Poultry Science
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• v.50 no.4
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• pp.213-229
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• 2023

This study aimed to investigate the effects of beak trimming and crossbreeding-combinations on the productive performance and stress response levels of Korean native chickens. The study divided 248 individuals from six crossbreeding-combinations into two groups: one underwent beak trimming, and the other did not. The survival rate, body weight, egg production rate, egg quality, feather damage score, HSP-70 gene expression level, H/L ratio, and intracellular DNA damage rate were measured and analyzed. The results showed that the beak-trimmed group had significantly higher survival rates and hen-housed egg production compared to the non-beak-trimmed group (P<0.05). Feather damage and DNA damage rates were significantly lower in the beak-trimmed group (P<0.05). On the other hand, there were no significant differences between the two groups in adult body weight, hen-day egg production, egg quality, HSP-70 gene expression level, and H/L ratio. Among the crossbreeding-combinations, there were significant differences in survival rate, body weight, feather damage score, egg quality, and DNA damage rate (P<0.05), while egg production rate, HSP-70 gene expression level, and H/L ratio showed no significant differences. There was an interaction between beak trimming and crossbreeding-combinations in some traits. In conclusion, beak trimming in Korean native chickens has a positive impact on productive performance, and in terms of stress response, beak trimming may not act as a stress factor or may even reduce stress after the growing period. Furthermore, there were differences in productive performance and stress response levels among crossbreeding-combinations, but the effects of beak trimming were similar across these combinations.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.45-59
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• 2023

The global focus on mitigating climate change has traditionally centered on carbon dioxide, but recent attention has shifted towards methane as a crucial factor in climate change adaptation. Natural settings, particularly aquatic environments such as wetlands, reservoirs, and lakes, play a significant role as sources of greenhouse gases. The accumulation of organic contaminants on the lake and reservoir beds can lead to the microbial decomposition of sedimentary material, generating greenhouse gases, notably methane, under anaerobic conditions. The escalation of methane emissions in freshwater is attributed to the growing impact of non-point sources, alterations in water bodies for diverse purposes, and the introduction of structures such as river crossings that disrupt natural flow patterns. Furthermore, the effects of climate change, including rising water temperatures and ensuing hydrological and water quality challenges, contribute to an acceleration in methane emissions into the atmosphere. Methane emissions occur through various pathways, with ebullition fluxes-where methane bubbles are formed and released from bed sediments-recognized as a major mechanism. This study employs Biochemical Methane Potential (BMP) tests to analyze and quantify the factors influencing methane gas emissions. Methane production rates are measured under diverse conditions, including temperature, substrate type (glucose), shear velocity, and sediment properties. Additionally, numerical simulations are conducted to analyze the relationship between fluid shear stress on the sand bed and methane ebullition rates. The findings reveal that biochemical factors significantly influence methane production, whereas shear velocity primarily affects methane ebullition. Sediment properties are identified as influential factors impacting both methane production and ebullition. Overall, this study establishes empirical relationships between bubble dynamics, the Weber number, and methane emissions, presenting a formula to estimate methane ebullition flux. Future research, incorporating specific conditions such as water depth, effective shear stress beneath the sediment's tensile strength, and organic matter, is expected to contribute to the development of biogeochemical and hydro-environmental impact assessment methods suitable for in-situ applications.