KSCE Journal of Civil and Environmental Engineering Research
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v.43
no.6
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pp.735-747
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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.
KIPS Transactions on Computer and Communication Systems
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v.12
no.12
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pp.363-370
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2023
Object detection technology that accurately recognizes the road and surrounding conditions is a key technology in the field of autonomous driving. In the field of autonomous driving, object detection technology requires real-time performance as well as accuracy of inference services. Task offloading technology should be utilized to apply object detection technology for accuracy and real-time on resource-constrained devices rather than high-performance machines. In this paper, experiments such as performance comparison of task offloading, performance comparison according to input image resolution, and performance comparison according to camera object resolution were conducted and the results were analyzed in relation to the application of task offloading for real-time object detection of autonomous driving in resource-constrained devices. In this experiment, the low-resolution image could derive performance improvement through the application of the task offloading structure, which met the real-time requirements of autonomous driving. The high-resolution image did not meet the real-time requirements for autonomous driving due to the increase in communication time, although there was an improvement in performance. Through these experiments, it was confirmed that object recognition in autonomous driving affects various conditions such as input images and communication environments along with the object recognition model used.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.18
no.4
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pp.51-63
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2023
The purpose of this study is to develop and implement a secondary teacher training program based on the TPACK model to strengthen the capacity of teachers of youth entrepreneurship education in the context of the increasing importance of entrepreneurship as a future competency, and to provide theoretical and practical implications based on it. To this end, a teacher training program was developed through the process of analysis, design, development, implementation, and evaluation based on the ADDIE model, and 22 secondary school teachers in Gangwon Province were trained and the effectiveness and validity were analyzed. First, the results of the paired sample t-test of TPACK in entrepreneurship education conducted before and after the program showed statistically significant improvements in all sub-competencies. Second, the satisfaction survey of the training program showed that the overall satisfaction was high with M=4.83. Third, the validity of the program was reviewed by three experts, and it was found to be highly valid with a validity of M=5.0, usefulness of M=4.7, and universality of M=5.0. Based on the results, it is suggested that in order to expand entrepreneurship education, opportunities for teachers' holistic capacity building such as TPACK should be expanded, teachers' understanding and practice of backward design should be promoted, and access to various resources that can be utilized in entrepreneurship education should be improved.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.19
no.2
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pp.1-11
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2024
In the midst of the current turbulent global economy, traditional investment metrics are undergoing a metamorphosis, signaling the onset of what's often referred to as an "Investment cold season". Early-stage startups, despite their boundless potential, grapple with immediate revenue constraints, intensifying their pursuit of critical investments. While financial indicators once took center stage in investment evaluations, a notable paradigm shift is underway. Organizational culture, once relegated to the sidelines, has now emerged as a linchpin in forecasting a startup's resilience and enduring trajectory. Our comprehensive research, integrating insights from CVF and OCAI, unveils the intricate relationship between organizational culture and its magnetic appeal to investors. The results indicate that startups with a pronounced external focus, expertly balanced with flexibility and stability, hold particular allure for investment consideration. Furthermore, the study underscores the pivotal role of adhocracy and market-driven mindsets in shaping investment desirability. A significant observation emerges from the study: startups, whether they secured investment or failed to do so, consistently display strong clan culture, highlighting the widespread importance of nurturing a positive employee environment. Leadership deeply anchored in market culture, combined with an unwavering commitment to innovation and harmonious organizational practices, emerges as a potent recipe for attracting investor attention. Our model, with an impressive 88.3% predictive accuracy, serves as a guiding light for startups and astute investors, illuminating the intricate interplay of culture and investment success in today's economic landscape.
With the rapid development in network, graphic technology, and digital technology, content industry is emerging as an important industry for new cultural development and economic development. The development in digital content technology has remarkably expanded the generation and distribution of contents, thereby creating new value and extending into a large distribution market. However, the ease of distribution and duplication, which characterizes digital technology, has increased the circulation of illegal contents due to illegal copying, theft, and alteration. The damage caused by this illegal content is severe. Currently, a copyright protection system targeting online sites is available. By contrast, no system has been established for offline companies that sell offline genuine content, which compete with online companies. The demand for content of overseas tourists is increasing due to the Korean wave craze. Nevertheless, many offline content providers have lost competitiveness due to illegal content distribution with online companies. In this study, we analyzed the case and status of similar copyright certification systems in Korea and overseas through previous research and studied a system to certify the offline genuine contents business. In addition to the case analysis, we focused on interviews obtained through in-depth interviews with the copyright stakeholders. We also developed a certification framework by establishing the certification domain, certification direction, and incentive of the certification system for offline businesses with genuine content. Selected certification direction is ethical, open, inward, store, and rigid (post evaluation). This study aimed to increase awareness among consumers about the use of genuine content and establish a transparent trading order in a healthy content market.
Climate change is already impacting sustainable water resource management. The influence of climate change on water supply from reservoirs has been generally assessed using climate change scenarios generated based on global climate models. However, inherent uncertainties exist due to the limitations of estimating climate change by assuming IPCC carbon emission scenarios. The decision scaling approach was applied to mitigate these issues in this study focusing on four reservoir watersheds: Chungju, Yongdam, Hapcheon, and Seomjingang reservoirs. The reservoir water supply reliablity was analyzed by combining the rainfall-runoff model (IHACRES) and the reservoir operation model based on HEC-ResSim. Water supply reliability analysis was aimed at ensuring the stable operation of dams, and its results ccould be utilized to develop either structural or non-structural water supply plans. Therefore, in this study, we aimed to assess potential risks that might arise during the operation of reserviors under various climate conditions. Using observed precipitation and temperature from 1995 to 2014, 49 climate stress scenarios were developed (7 precipitation scenarios based on quantiles and 7 temperature scenarios ranging from 0℃ to 6℃ at 1℃ intervals). Our study demonstrated that despite an increase in flood season precipitation leading to an increase in reservoir discharge, it had a greater impact on sustainable water management compared to the increase in non-flood season precipitation. Furthermore, in scenarios combining rainfall and temperature, the reliability of reservoir water supply showed greater variations than the sum of individual reliability changes in rainfall and temperature scenarios. This difference was attributed to the opposing effects of decreased and increased precipitation, each causing limitations in water and energy-limited evapotranspiration. These results were expected to enhance the efficiency of reservoir operation.
The Journal of the Convergence on Culture Technology
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v.10
no.1
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pp.403-409
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2024
In this paper, the guidelines for the design of an Artificial Intelligence(AI) based Integrated Process Safety Management(PSM) system to enhance workplace safety using data from process safety reports submitted by hazardous and risky facility operators in accordance with the Occupational Safety and Health Act is proposed. The system composed of the proposed guidelines is to be implemented separately by individual facility operators and specialized process safety management agencies for single or multiple workplaces. It is structured with key components and stages, including data collection and preprocessing, expansion and segmentation, labeling, and the construction of training datasets. It enables the collection of process operation data and change approval data from various processes, allowing potential fault prediction and maintenance planning through the analysis of all data generated in workplace operations, thereby supporting decision-making during process operation. Moreover, it offers utility and effectiveness in time and cost savings, detection and prediction of various risk factors, including human errors, and continuous model improvement through the use of accurate and reliable training data and specialized datasets. Through this approach, it becomes possible to enhance workplace safety and prevent accidents.
Journal of Korean Library and Information Science Society
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v.55
no.2
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pp.267-291
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2024
Since the introduction of the OA transformative agreement as a new way of licensing electronic resources, the number of OA transformative agreements has continued to grow. Despite the wide range of content that should be included in the agreement due to the nature of the OA transformative agreement, there is a lack of research on OA transformative agreements. As a basis for developing a standard for OA transformative agreements, this study examines the current status of OA transformative agreements and analyzes the differences between two types of OA transformative agreements and the subscription contract. It was found that the number of OA transformative agreements has increased significantly worldwide, but the disclosure of OA transformative agreements has not been universalized. The overall structure of two different types of OA transformative agreements and a subscription contract is similar, but there are differences in the detailed clauses. In the OA transformative agreement, the detailed clauses related to the characteristic of the transformative agreement were newly created, or the details of the transformative agreement were added to the existing clauses of the subscription agreement. There were also some differences between the two types of agreements, identifying clauses that differed in content regardless of the OA transformative agreement. The study concluded that it is important to standardize the OA transformative agreement, as the number of different clauses between agreement types may increase the burden on librarians. This study is significant in that it provides a basis for the development of standardized agreements by examining the overall status of OA transformative agreements and analyzing actual agreements.
Journal of the Korean Society of Marine Environment & Safety
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v.30
no.2
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pp.200-208
/
2024
The occurrence a fire on a training ship with a large number of people on board can lead to severe casualties. Hence the Seafarers' Act and Safety Life At Sea(SOLAS) emphasizes the importance of the abandon ship drill. Therefore, in this study, the training ship of Mokpo National Maritime University, Segero, which has a large number of people on board, was selected as the target ship and the likelihood and severity of fire accidents on each deck were predicted through the preliminary hazard analysis(PHA) qualitative risk assessment. Additionally, assuming a fire in a high-risk area, a simulation of evacuation time and population density was performed to quantitatively predict the risk. The the total evacuation time was predicted to be the longest at 501s in the meal time scenario, in which the population distribution was concentrated in one area. Depending on the scenario, some decks had relatively high population densities of over 1.4pers/m2, preventing stagnation in the number of evacuees. The results of this study are expected to be used as basic data to develop training scenarios for training ships by quantifying evacuation time and population density according to various evacuation scenarios, and the research can be expanded in the future through comparison of mathematical models and experimental values.
Korean Journal of Construction Engineering and Management
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v.25
no.4
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pp.45-52
/
2024
Estimating the sales price of a residential building development project is difficult because of it has many complex variables such as location, environment, and economic conditions. Many previous studies related to influence factors of the sales price is to identify by survey of experts and it is few studies by comparing with actual sales price. Accordingly, the purpose of this study is to identify the factors influenced on the projects by using correlation analysis from collected actual data in this study. For the purpose, first, the factors such as economy, location, housing, financial environmental factors were identified from previous studies. Second, data were collected on actual sale prices and selected factors. Finally, the actual sales price and factors were compared and analyzed by using correlation analysis. As a result, the R2 values of economy, location, housing and financial environmental factors were over 0.5 respectively. Therefore, it was confirmed that these factors were significantly correlated with actual sales price. The results of this study are expected to be utilized as basic data for research and development of a new sale prices prediction model.
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