• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.6
• /
• pp.120-129
• /
• 2023

To evaluate the vertical loads on railway bridges, conventional load tests are typically conducted. However, these tests often entail significant costs and procedural challenges. Railway conditions involve nearly identical load profiles due to standardized rail systems, which may appear straightforward in terms of load conditions. Nevertheless, this study aims to validate load tests conducted under operational train conditions by comparing the results with those obtained from conventional load tests. Additionally, static and dynamic structural behaviors are extracted from the measurement data for evaluation. To ensure the reliability of load testing, this research demonstrates feasibility through comparisons of existing measurement data with sensor attachment locations, train speeds, responses between different rail lines, tendency analysis, selection of impact coefficients, and analysis of natural frequencies. This study applies to the Dongho Railway Bridge and verifies the applicability of the proposed method. Ten operational trains and 44 sensors were deployed on the bridge to measure deformations and deflections during load test intervals, which were then compared with theoretical values. The analysis results indicate good symmetry and overlap of loads, as well as a favorable comparison between static and dynamic load test results. The maximum measured impact coefficient (0.092) was found to be lower than the theoretical impact coefficient (0.327), and the impact influence from live loads was deemed acceptable. The measured natural frequencies approximated the theoretical values, with an average of 2.393Hz compared to the calculated value of 2.415Hz. Based on these results, this paper demonstrates that for evaluating vertical loads, it is possible to measure deformations and deflections of truss railway bridges through load tests under operational train conditions without traffic control, enabling the calculation of response factors for stress adjustments.

• Journal of Venture Innovation
• /
• v.4 no.2
• /
• pp.29-42
• /
• 2021

The stress on finding a job is also increasing in a situation where the difficulty in finding a job is aggravating due to the COVID-19 pandemic. In this study, the major satisfaction of college students was subdivided into subject satisfaction and relationship satisfaction, and the relationship between these and job-seeking stress was investigated. In addition, We tried to find out whether there is a difference in the influence relationship between these majors according to their current major, that is, whether they majored in a science, engineering major or a social science major. The population for the study was the students currently enrolled in the 4th grade, and the research sample was obtained from students of H and N universities in the metropolitan area. A total of 220 people were analyzed, 110 people from science and engineering and 110 from social sciences. For analysis, SPSS 24.0 and Process Macro 5.0 were used. The empirical analysis results are as follows. First, subject satisfaction had a negative (-) effect on job-seeking stress. Second, relationship satisfaction also had a significant negative (-) effect on job-seeking stress. Third, there was a significant difference between science, engineering students and social science students in the effect of subject satisfaction on job-seking stress. Fourth, in the effect of relationship satisfaction on job-seeking stress, there was also a significant difference between science, engineering students and social science students. Therefore, the higher the satisfaction with the major you are majoring in, the lower the job-seeking stress, and the extent of this decrease is social science students were larger than science, engineering students. It is necessary to be cautious in generalizing the results of this study, which was made in the context of the COVID-19 pandemic. Based on the empirical analysis results, the academic and practical implications of this study are presented.

• Journal of Venture Innovation
• /
• v.6 no.4
• /
• pp.99-111
• /
• 2023

This study aims to confirm that consumers' satisfaction with online shopping websites has changed to a phenomenon different from the past. In other words, in a situation where the use of e-commerce is expanding worldwide after the pandemic and various types of commerce such as mobile commerce and social commerce are formed, the consumer's information processing and decision-making process are meaningful in examining the behavior that has been changed based on the perceived motivation level of consumers by the new environment according to the consumption value and personal characteristics perceived by the consumer. In other words, the purpose of this study was to investigate the effect of consumption value and need for cognition on the satisfaction toward online websites as a mediating role in the trust of the website. As a result of testing Hypothesis 1, not only the hedonic value of the consumer for the website but also the utilitarian value had a positive influence on the satisfaction toward the website, and in particular, the utilitarian value showed a relatively greater influence than the hedonic value. However, the negative relationship between the need for cognition and satisfaction was found to be at a significant level under one-sided verification. In Hypothesis 2, only the utilitarian value among the consumption values of 2-1 showed a positive effect on satisfaction through a mediating role of trust. It was confirmed that the utilitarian value among the consumption values was an important factor in the satisfaction toward the website. The significance of this study is that, unlike previous research results, not only consumption value based on senses and emotions but also utilitarian value has a greater influence. Therefore, utilitarian value and need for cognition have a stronger influence on satisfaction if they play a mediating role based on the trust of the website used by consumers. These findings reflect the current market trend of online consumption, and they are helpful in the management and strategy of online websites based on consumer behavior understanding and major factors.

• Journal of Venture Innovation
• /
• v.6 no.4
• /
• pp.23-40
• /
• 2023

This study examines the customer value factors affecting the intention to continue using the mobile app of department stores, which are traditional offline retailers, in the retail industry that is rapidly digitalizing and becoming mobile. This study clarifies multidimensional customer value in three dimensions; functional, convenience, and social. Functional value refers to the integrated channel, and consistent customer experience provided between channels in the omnichannel retail environment, while convenience value is the convenience of saving time and effort save while customers use a mobile app. Social value refers to the improvement of social approval or social self-concept occurring due to the use of products or services related to green marketing within the mobile app of the department store. The influence of each on the dependent variable, the mobile app's continuous use intention, was analyzed by using the three dimensions of customer value as independent variables. Data was collected from customers who have a history of using the mobile app of Shinsegae Department Store in Korea, and a confirmatory analysis was conducted using Smart PLS 4.0. The analysis results showed that all three dimensions of customer value; functional value, convenience value, and social value, had a positive (+) influence on customers' intention to continue using the mobile app, and the influence of functional value had the greatest impact. As functional value appears to be the most important influencing factor due to the omnichannel retail trend by advancement of technology, it suggests that it is important for department stores, and offline retailers, to provide integrated channels. This provides insights into the direction of customer-centered strategy formulation for activating department store mobile apps and suggests basic analytical data for customized services and marketing activities that department stores can effectively meet the changing expectations and demands of customers through new mobile channels rather than existing offline channels.

• Journal of Venture Innovation
• /
• v.6 no.4
• /
• pp.63-81
• /
• 2023

The purpose of this study was to utilize the Photovoice qualitative research method targeting university students. Through this method, we aimed to understand the perceptions of environmental issues, environmental barriers, and eco-friendly behaviors among university students. By employing the Photovoice methodology, we sought to share the perspectives of university students on eco-friendly behaviors, explore the motivations and manifestations of these behaviors, and reflect on their significance. The ultimate goal was to provide practical suggestions for fostering eco-friendly behaviors through an in-depth examination of the visual narratives and reflections of university students. Under the overarching theme of the environment, participants were given the opportunity to individually select and explore three specific sub-themes: 'My Concept of the Environment,' 'Environmental Barriers in My Life,' and 'My Eco-friendly Behaviors.' Participants engaged in the process of capturing photographs from their daily lives related to each theme, expressing their thoughts and perspectives through the selected images. Subsequently, they shared and discussed their insights, actively listening to the opinions of others in the group. The results of this study revealed several key findings. Firstly, participants assigned meaning to the photographs they selected by directly capturing aspects related to the environment, such as 'waste,' 'discomfort,' 'fine dust=environmental pollution,' and 'indifference.' Secondly, participants attributed meaning to the selected photographs related to environmental barriers, associating them with concepts like 'invisibility,' 'apathy,' 'social stigma,' 'inefficiency,' and 'compulsion.' Lastly, participants ascribed significance to photographs selected in the context of eco-friendly behaviors, with themes like 'recycling,' 'energy conservation,' 'reuse,' and 'reducing the use of disposable items.' Based on these research findings, the confirmation of the V-A-B (Values-Attitudes-Behavior) model was established. It was observed that consumers structure a hierarchical relationship between their personal values, attitudes, and behaviors. The study also identified clear impediments in consumers' daily lives hindering the practice of eco-friendly behaviors. In light of this, the research highlighted the need for strategies to address the discomfort or inconvenience associated with implementing environmentally friendly consumer behaviors. The implications of the study suggest that interventions or solutions are necessary to alleviate barriers and promote a more seamless integration of eco-friendly practices into consumers' daily routines.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.6
• /
• pp.53-62
• /
• 2023

This paper has suggested the necessity of introducing training contents using XR(Extended reality) technology as a way to lower the high rate of nursing accidents among unskilled technical personnel in domestic shipbuilding industry, focusing on cable pulling using winch. The occurrence rate of nursing accidents in the domestic shipbuilding industry was almost double(197.4%) (2017~2020) when compared with other manufacturing industries. In particular, it is worth noting that more than 31.8% of nursing accidents in the shipbuilding industry occurred among workers whose job experience is no more than 6 months. Most of new workers are seen to have hard time due to several factors such as lack of work information, inexperience, and unfamiliarity with the working environments. This indicates that it is essential to incorporate more effective training method that could help new workers become familiar with technical skills as well as working environments in a short period of time. Currently, education/training at the domestic shipyard is biased toward technical skills such as welding, painting, machine installation, and electrical installation. Contrary, even more important training required to get new workers used to the working environment has remained at a superficial level such as explaining ship building processes using 2D drawings. This may be the reason why it is inevitable to repeat similar training at OJT (On-the-Job Training) even at the leading domestic companies. Domestic shipbuilding industries have been attracting a lot of new workers thanks to recent economic recovery, which is very likely to increase the occurrence of disasters. In this paper, the introduction of training using XR technology was proposed, and as a specific example, the process of pulling cables using winches on ships was implemented as XR-based training content by using Unity. Using the developed content, it demonstrated that new workers can experience the actual work process in advance through simulation in a virtual space, thereby becoming more effective training content that can help new workers become familiar with the work environment.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_3
• /
• pp.979-995
• /
• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.

• Journal of Life Science
• /
• v.33 no.10
• /
• pp.828-834
• /
• 2023

The cDNA that encodes transmembrane protein 258 (Tmem258) was cloned from Gryllus bimaculatus and named GbTmem258. This protein comprises 80 amino acids, has no N-glycosylation site, and contains five potential phosphorylation sites at two serines, two threonines, and one tyrosine. The predicted molecular mass of GbTmem258 is 9.06 kDa, and its theoretical isoelectric point is 5.5. The tertiary structure of GbTmem258 was predicted using the available secondary structure information, which suggests the presence of alpha helices (52.5%), random coils (22.5%), extended strands (16.25%), and beta turns (8.75%). Homology analysis revealed that GbTmem258 exhibits high similarity at the amino-acid level to Tmem258 found in other species. The effect of starvation and refeeding on GbTmem258 mRNA expression was also examined in this study. It was found that GbTmem258 mRNA expression in the hindgut progressively increased throughout the starvation period, peaking at almost 1.5 times the control level after six days of starvation. However, refeeding for one to two days after the six-day starvation period restored GbTmem258 mRNA expression to the control level. In fat body, GbTmem258 mRNA expression was almost 3-fold higher during starvation compared to the control level. Refeeding for one to two days after the six-day fast resulted in a decline in the expression to about a 2.5-fold increase over the control level. Throughout the starving and refeeding periods, no other tissues showed any discernible alterations in GbTmem258 mRNA expression.

• Journal of Life Science
• /
• v.33 no.10
• /
• pp.808-819
• /
• 2023

This study was conducted to develop a selection marker for the identification of the Bacillus licheniformis K12 strain in microbial communities. The strain not only demonstrates good growth at moderate temperatures but also contains enzymes that catalyze the decomposition of various polymer materials, such as proteases, amylases, cellulases, lipases, and xylanases. To identify molecular markers appropriate for use in a microbial community, a search was conducted to identify variable gene regions that show considerable genetic mutations, such as recombinase, integration, and transposase sites, as well as phase-related genes. As a result, five areas were identified that have potential as selection markers. The candidate markers were two recombinase sites (BLK1 and BLK2), two integration sites (BLK3 and BLK4), and one phase-related site (BLK5). A PCR analysis performed with different Bacillus species (e.g., B. licheniformis, Bacillus velezensis, Bacillus subtilis, and Bacillus cereus) confirmed that PCR products appeared at specific locations in B. licheniformis: BLK1 in recombinase, BLK2 in recombinase family protein, and BLK3 and BLK4 as site-specific integrations. In addition, BLK1 and BLK3 were identified as good candidate markers via a PCR analysis performed on subspecies of standard B. licheniformis strains. Therefore, the findings suggest that BLK1 can be used as a selection marker for B. licheniformis species and subspecies in the microbiome.