• Journal of Venture Innovation
• /
• v.6 no.1
• /
• pp.115-137
• /
• 2023

This study analyzed the relationship between organizational innovative capability and absorptive capacity, market and technology orientations, and their impact on business performance for IT-BPO companies that are required to absorb new technologies from a leading perspective in the digital transformation era. To achieve this, an online specialized research company and offline surveys were conducted on 291 domestic IT-BPO companies, and SPSS 23 was used for descriptive statistics and reliability analysis while AMOS 23 was used for hypothesis testing including validity and mediating effects. The main findings were as follows: First, in the relationship between innovation and absorptive capabilities and Market Orientation Strategic(MOS), learning capability and knowledge network capability were found to have a statistically significant positive (+) effect on MOS. In the relationship between innovation and absorptive capabilities and Technology Orientation Strategic(TOS), R&D capability, potential absorptive capacity, and realized absorptive capacity had a statistically significant positive (+) effect on TOS. Second, in the relationship between innovation and absorptive capabilities and BP, only R&D capability was found to have a significant effect on BP. Third, both market orientation and technology orientation were found to have a significant positive (+) effect on BP. These findings suggest that effective competency factors can be identified according to the market and technology orientations pursued by IT-BPO companies to increase their growth and value creation, and provide implications for developing differentiated competency enhancement strategies based on strategic objectives.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.6
• /
• pp.735-747
• /
• 2023

In recent times, the sharp increase in extreme flood damages due to climate change has posed a challenge to effectively address flood-related issues solely relying on conventional flood management infrastructure. In response to this problem, this study aims to consider the effectiveness of nature-based flood management approaches, specifically levee retreat and relocation. To achieve this, we utilized a 1D numerical model, HEC-RAS, to analyze the flood reduction effects concerning floodwater levels, flow velocities, and time-dependent responses to a 100-year frequency flood event. The analysis results revealed that the effect of creating a flood buffer zone of the nature-based solution extends from upstream to downstream, reducing flood water levels by up to 30 cm. The selection of the flow roughness coefficient in consideration of the nature-based flood buffer space creation characteristics should be based on precise criteria and scientific evidence because it is sensitive to the flood control effect analysis results. Notably, floodwater levels increased in some expanded floodplain sections, and the reduction in flow velocities varied depending on the ratio of the expanded cross-sectional area. In conclusion, levee retreat and floodplain expansion are viable nature-based alternatives for effective flood management. However, a comprehensive design approach is essential considering flood control effects, flow velocity reduction, and the timing of peak water levels. This study offers insights into addressing the challenges of climate-induced extreme flooding and advancing flood management strategies.

• Journal of Intelligence and Information Systems
• /
• v.29 no.4
• /
• pp.347-373
• /
• 2023

As the significance of ESG (Environmental, Social, and Governance) management amplifies in driving sustainable growth, this study delves into and compares ESG trends and interrelationships from both corporate and societal viewpoints. Employing a combination of Latent Dirichlet Allocation Topic Modeling (LDA) and Semantic Network Analysis, we analyzed sustainability reports alongside corresponding social media datasets. Additionally, an in-depth examination of social media content was conducted using Joint Sentiment Topic Modeling (JST), further enriched by Semantic Network Analysis (SNA). Complementing text mining analysis with the assistance of ChatGPT, this study identified 25 different ESG topics. It highlighted differences between companies aiming to avoid risks and build trust, and the general public's diverse concerns like investment options and working conditions. Key terms like 'greenwashing,' 'serious accidents,' and 'boycotts' show that many people doubt how companies handle ESG issues. The findings from this study set the foundation for a plan that serves key ESG groups, including businesses, government agencies, customers, and investors. This study also provide to guide the creation of more trustworthy and effective ESG strategies, helping to direct the discussion on ESG effectiveness.

• Journal of the Korea Institute of Building Construction
• /
• v.23 no.6
• /
• pp.785-796
• /
• 2023

The adoption of Environmental, Social, and Governance(ESG) practices in domestic construction firms is predominantly driven by major corporations. These companies not only publish reports on their ESG management but also engage in a meticulous process of identifying key issues and setting priorities. This process entails an in-depth evaluation of the severity of various issues and the gathering of insights from experts in the field. Interestingly, a comparative analysis of ESG assessments for construction companies, both domestically and internationally, reveals significant discrepancies in outcomes. These differences stem from the varied evaluation methodologies and criteria employed by different assessing bodies. Addressing this gap, our study proposes a suite of strategies aimed at bolstering ESG management within the construction sector. We advocate for enhanced policy support and financial backing, especially targeting small and medium-sized enterprises(SMEs) to facilitate their engagement in ESG practices. A critical step forward involves the standardization and transparent disclosure of ESG evaluation criteria, tailored to reflect the unique aspects of the construction industry. Moreover, the standardization and publication of ESG assessments for subcontractors are essential, equipping them with the necessary tools for effective ESG management and evaluation. Given the global nature of construction projects, particularly those commissioned by the European Union in regions like Africa and East Asia, adherence to ESG standards is imperative. Our long-term vision includes the development of a comprehensive database detailing ESG regulations and their impacts, segmented by region and country. This repository will serve as a valuable resource for companies venturing into international construction projects.

• Journal of Aerospace System Engineering
• /
• v.18 no.1
• /
• pp.11-20
• /
• 2024

In the recent era of NewSpace, unlike high-reliability satellites of the past, low-reliability satellites are being developed and mass-produced at a lower cost to launch constellations satellites. To achieve cost-effective cluster satellite development, satellite users and developers need to assess the feasibility of maintaining mission performance over the expected lifespan when cluster satellites are launched. Plans for replacements due to random failures should also be established to maintain performance. This study proposed a method for assessing system reliability and availability to maintain mission performance and establish replacement strategies for Earth observation constellation satellites. In this study, a constellation reliability and availability model considering mission performance required for a satellite constellation, situations of satellite backup, and additional ground backups was established. The reliability model was structured based on the concept of a k-out-of-n system and the availability model used a Markov chain model. Based on the proposed reliability model, the minimum number of satellites required to meet mission requirements was defined and satellites needed in orbit during the required mission period to satisfy mission reliability were calculated. This research also analyzed the number of spare satellites in orbit and on the ground required to meet the desired availability during required service period through availability analysis.

• Journal of Industrial Convergence
• /
• v.22 no.2
• /
• pp.153-159
• /
• 2024

This study is a descriptive research study to determine the relationship between middle-aged women's social support, resilience and quality of life, and to identify factors that affect quality of life. The participants were 162 middle-aged women in G City. Data was collected from May 10 to June 10, 2023. Data were analyzed through descriptive statistics, t-test, one-way ANOVA, Pearson's correlation coefficient, and multiple regression using SPSS 25.0 program. The social support was 3.36±0.38, resilience was 3.39±0.42, and quality of life was 3.18±0.50. Quality of life was positively correlated with social support(r=.502, p<.001), resilience(r=.530, p<.001). Factors that have a significant impact on quality of life include resilience(β=.422, p<.001), social support(β=.412, p<.001) and health status(β=.212, p=.001). The total explanatory power of these variables on quality of life was 39.2%. Therefore, it is necessary to develop effective programs and strategies to improve the quality of life of middle-aged women by improving their resilience, social support, and health status.

• Information Systems Review
• /
• v.24 no.1
• /
• pp.21-37
• /
• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• Information Systems Review
• /
• v.24 no.2
• /
• pp.41-66
• /
• 2022

With the development of IT, mobile apps and the expansion of contactless services due to COVID-19, "smart orders" have recently been activated in the food and beverage service. Even in recent years, when sales have declined, the number of orders made by smart orders has been steadily increasing, and this ordering method can accumulate customer data, enabling effective customized services in the future. In the present study, satisfaction with smart orders and continuous use intention were studied based on the technology acceptance model (TAM). And it focused on whether there is a difference in personality when using smart orders. For this purpose, a survey was conducted on 317 smart order users, and the hypothesis was verified by structural equation model analysis. Perceived benefits had a significant effect on satisfaction; also, satisfaction had a significant effect on continuous use intention. There is a significant disparity between introvert and extrovert type. As a consequence, the introverted type has a greater intention to perceive usefulness of smart orders and continuously use them. These results suggest that the customer's personality type should be considered in future customer customization strategies.

• Journal of The Korean Association For Science Education
• /
• v.27 no.5
• /
• pp.379-393
• /
• 2007

The purpose of this article is to analyze the conceptual change of nine 11th graders after implementing the model-based instruction of blood circulation by multidimensional framework, and to find some implications about teaching strategies for improving conceptual understanding. The model-based instruction consisted of 4 periods: (1) introduction for inducing students' interests using an episode in the science history of blood circulation, (2) vivisectional experiment on rats, (3) visual-linguistic model instruction using the videotape of heartbeat, and (4) modeling activity on the path of blood flow. Based on the data from pre-test, post-test and interviews, we classified students' models on the path of blood flow, and investigated their ontological features and the conceptual status of blood circulation. Most students could describe the path of blood flow and the changes of substances in blood precisely after the instructions. However, the modeling activity were not sufficient to improve students' understanding of the mechanisms of the blood distribution throughout various organs and the material exchanges between blood and tissues. From the interview of 9 students, we acquired informative results about conceptual status elements that were helpful to, preventing from, or not used for students' understanding. It was also found that conceptual status of students depended on the ontological categories into which students' conceptions of blood circulation fell. The results of this study can help design the effective teaching strategy for the understanding of concept of the equilibrium category.

• Journal of Life Science
• /
• v.34 no.6
• /
• pp.434-441
• /
• 2024

Mammary gland tumors are the most common tumors detected in non-spayed female dogs and pose a significant clinical challenge. Due to the strong similarity between canine mammary tumors (CMT) and human breast cancer (HBC), biomarkers identified in HBC can also be detected in CMT. These biomarkers have been shown to offer valuable insights into early diagnosis, prognosis, and treatment strategies. The purpose of this article is to provide a concise overview of CMT biomarkers based on the current literature. Traditional treatments for CMT in dogs typically begin with surgery, followed by chemotherapy, radiotherapy, or hormonal therapy. However, these treatments alone are not always fully effective. A diagnostic biomarker can detect the presence of a disease or the characteristics of a disease and classify an individual's status. Prognostic biomarkers focus on predicting the expected progression, recurrence, or survival of the disease in patients. By utilizing advances in understanding the mechanism of canine-specific mammary gland tumors, the estimation of biomarkers offers hope for improved outcomes in cancer patients. Novel technologies, such as single-cell RNA sequencing analysis, could provide a valuable resource for deciphering intra- and inter-tumoral heterogeneity. This review paper explores current research on CMT biomarkers and suggests directions for their development.