• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.315-323
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• 2023

Marine accidents due to loss of stability of small ships have continued to increase over the past decade. In particular, since sudden winds have been pointed out as main causes of most small ship accidents, safety measures have been established to prevent them. In this regard, to prevent accidents caused by sudden winds, a systematic analysis technique is required. The aim of the present study was to develop a probabilistic approach to estimate extreme value and evaluate effects of wind on motion characteristics of ships. The present study included studies of motion analysis, extraction of extreme values, and motion characteristics. A series analysis was conducted for three conditions: wave only, wave with uniform wind speed, and wave with the NPD wind model. Hysteresis filtering and Peak-Valley filtering techniques were applied to time-domain motion analysis results for extreme value extraction. Using extracted extreme values, the goodness of fit test was performed on four distribution functions to select the optimal distribution-function that best expressed extreme values. Motion characteristics of a fishing boat were evaluated for three periodic motion conditions (Heave, Roll, and Pitch) and results were compared. Numerical analysis was performed using a commercial solver, ANSYS-AQWA.

• Journal of Music and Human Behavior
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• v.21 no.1
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• pp.115-132
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• 2024

The purpose of this study was to explore the impact of music therapy on enhancing self-awareness and intrinsic motivation among patients with schizophrenia, particularly those experiencing motivational deficits. This study, primarily based on quantitative analyses supplemented by qualitative insights, included six adults (three males and three females) across 8 weekly sessions proactive music activities based on the exploration of musical emotion, each lasting 60 minutes, from October 5 to November 16, 2023. Data collection and analysis focused on the last five sessions, from the fourth to the eighth. Although no statistically significant changes were detected, likely due to the study's short duration, qualitative data from in-depth interviews indicate that music therapy contributed to enhanced motivation and improved self-perception in participants. They demonstrated better emotional articulation, self-awareness, and communication skills, which not only increased their intrinsic motivation but also led to an improved perception of their life quality. Individual variability was noted, however, indicating that these outcomes could differ among participants. These results highlight music therapy's potential as a valuable intervention for enhancing self-awareness and reigniting motivation in individuals with schizophrenia, suggesting a further research to corroborate these findings over longer periods.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.79-92
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• 2024

ChatGPT, as a representative chatbot leveraging generative artificial intelligence technology, is used valuable not only in scientific and technological domains but also across diverse sectors such as society, economy, industry, and culture. This study conducts an explorative analysis of user sentiments and needs for ChatGPT by examining global social media discourse on Reddit. We collected 10,796 comments on Reddit from December 2022 to August 2023 and then employed keyword analysis, sentiment analysis, and need-mining-based topic modeling to derive insights. The analysis reveals several key findings. The most frequently mentioned term in ChatGPT-related comments is "time," indicative of users' emphasis on prompt responses, time efficiency, and enhanced productivity. Users express sentiments of trust and anticipation in ChatGPT, yet simultaneously articulate concerns and frustrations regarding its societal impact, including fears and anger. In addition, the topic modeling analysis identifies 14 topics, shedding light on potential user needs. Notably, users exhibit a keen interest in the educational applications of ChatGPT and its societal implications. Moreover, our investigation uncovers various user-driven topics related to ChatGPT, encompassing language models, jobs, information retrieval, healthcare applications, services, gaming, regulations, energy, and ethical concerns. In conclusion, this analysis provides insights into user perspectives, emphasizing the significance of understanding and addressing user needs. The identified application directions offer valuable guidance for enhancing existing products and services or planning the development of new service platforms.

• Research in Plant Disease
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• v.30 no.2
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• pp.148-156
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• 2024

Ralstonia pseudosolanacearum, a plant pathogenic bacterium that can survive for a long time in soil and water, causes lethal wilt in the Solanaceae family. Sigma S is a part of the RNA polymerase complex, which regulates gene expression during bacterial stress response or stationary phase. In this study, we investigated the role of sigma S in R. pseudosolanacearum under stress conditions using a rpoS-defective mutant strain of R. pseudosolanacearum and its wild-type strain. The phenotypes of rpoS-defective mutant were complemented by introducing the original rpoS gene. There were no differences observed in bacterial growth rate and exopolysaccharide production between the wild-type strain and the rpoS mutant. However, the wild-type strain responded more sensitively to nutrient deficiency compared to the mutant strain. Under the nutrient deficiency, the rpoS mutant maintained a high bacterial viability for a longer period, while the viability of the wild-type strain declined rapidly. Furthermore, a significant difference in pH was observed between the culture supernatant of the wild-type strain and the mutant strain. The pH of the culture supernatant for the wild-type strain decreased rapidly during bacterial growth, leading to medium acidification. The rapid decline in the wild-type strain's viability may be associated with medium acidification and bacterial sensitivity to acidity during transition to the stationary phase. Interestingly, the rpoS mutant strain cannot utilize acetic acid, D-alanine, D-trehalose, and L-histidine. These results suggest that sigma S of R. pseudosolanacearum regulates the production or utilization of organic acids and controls cell death during stationary phase under nutrient deficiency.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.205-216
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• 2024

Recently, seismic Probabilistic Safety Assessment (PSA) methods have been developed for process plants, such as gas plants, oil refineries, and chemical plants. The framework originated from the PSA of nuclear power plants, which aims to assess the risk of reactor core damage. The original PSA method was modified to adopt the characteristics of a process plant whose purpose is continuous operation without shutdown. Therefore, a fault tree, whose top event is shut down, was constructed and transformed into a Bayesian Network (BN), a probabilistic graph model, for efficient risk-informed decision-making. In this research, the fault tree-based BN from the previous research is further developed to consider the multi-hazard of earthquake-induced fire and explosion (EQ-induced F&E). For this purpose, an event tree describing the occurrence of fire and explosion from a release is first constructed and transformed into a BN. And then, this BN is connected to the previous BN model developed for seismic PSA. A virtual plot plan of a gas plant is introduced as a basis for the construction of the specific EQ-induced F&E BN to test the proposed BN framework. The paper demonstrates the method through two examples of risk-informed decision-making. In particular, the second example verifies how the proposed method can establish a repair and retrofit strategy when a shutdown occurs in a process plant.

• Bangmulgwan gwa yeongu (The National Museum of Korea Journal)
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• v.1
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• pp.74-95
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• 2024

A vast body of inscribed bricks has been found connected to the mid-fourth-century Tomb of Jang Mui in Bongsan-gun, Hwanghae-do Province. After several inspections of the bricks conducted at the National Museum of Korea in 2023, these inscribed bricks were grouped into ten types. This paper interprets in detail the phrases written on these bricks from the Tomb of Jang Mui in an attempt to understand their characteristics and intentions. This detailed interpretation facilitates a rough understanding of how each phrase relates to the others and in what order the phrases would make full sentences. In terms of their contents, these inscribed bricks are presumed to have been produced to convey information about the construction of the tomb to viewers on the outside. In particular, they relate that a narrator referred to as a Jubu official named Jo was involved in the construction of the Tomb of Jang Mui. They can be compared to the inscribed bricks created in China during the Western Jin and Eastern Jin Dynasties that were produced not by family members of the tomb occupants, but by figures who participated in the construction of the tombs based on political and social connections to their occupants. During the mid-fourth century, funeral practices in the former lands of the Nangnang and Daebang Commanderies followed Chinese traditions with the permission of Goguryeo Kingdom. Many of the artifacts found inside these Chinese-style tombs and introduced to the public, including the murals, ink inscriptions, and inscribed bricks, are related to the desire of the family members of the tomb occupants to strengthen their bonds and to share emotions and goals with settler groups. The contents of the inscribed bricks discovered from the Tomb of Jang Mui can be observed in this context.

• Smart Media Journal
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• v.13 no.6
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• pp.80-89
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• 2024

This study aims not only to address environmental issues caused by indiscriminate fashion consumption, specifically in the context of Fast Fashion but also to find an alternative and a sustainable solution that is 'Upcycling' using the 3D clothing simulation program Z-weave. Upcycling products have limitations in that it is difficult to produce samples since finished products must be produced directly with limited materials and resources like waste clothes. To overcome these limitations, a 3D clothing simulation program is introduced to effectively utilize the limited resources of waste clothing. The purpose of this study is to confirm the similarity between a virtual fabric created through Z-weave and a real fabric, through this, to evaluate the possibility of application in the actual fashion industry. As a research method, surveys and interviews were conducted with related majors on virtual clothing created as similar as possible to actual clothing by adjusting the physical properties within the Z-weave program. This study attempted to describe the impact of digital technology on the fashion industry and how 3D clothing simulation programs can be used in sustainable fashion production.

• Journal of the Korea Society of Computer and Information
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• v.29 no.7
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• pp.41-51
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• 2024

In this paper, we explore the enhancement of target detection accuracy in the guided weapon using deep learning object detection on infrared (IR) images. Due to the characteristics of IR images being influenced by factors such as time and temperature, it's crucial to ensure a consistent representation of object features in various environments when training the model. A simple way to address this is by emphasizing the features of target objects and reducing noise within the infrared images through appropriate pre-processing techniques. However, in previous studies, there has not been sufficient discussion on pre-processing methods in learning deep learning models based on infrared images. In this paper, we aim to investigate the impact of image pre-processing techniques on infrared image-based training for object detection. To achieve this, we analyze the pre-processing results on infrared images that utilized global or local information from the video and the image. In addition, in order to confirm the impact of images converted by each pre-processing technique on object detector training, we learn the YOLOX target detector for images processed by various pre-processing methods and analyze them. In particular, the results of the experiments using the CLAHE (Contrast Limited Adaptive Histogram Equalization) shows the highest detection accuracy with a mean average precision (mAP) of 81.9%.

• Food Science and Preservation
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• v.30 no.2
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• pp.262-271
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• 2023

The objective of this study is to compare and assess the effectiveness of real-time polymerase chain reaction (RT-PCR), loop-mediated isothermal amplification (LAMP), and the selective agar plate method for the detection of Salmonella spp. and Listeria monocytogenes in ready-to-eat (RTE) foods. In RTE foods, the detection performance of the three methods (RT-PCR [SureTect^TM kit and PowerChek^TM kit], LAMP [3M MDS], selective agar) were similar at 0-10, 10-50, 50-100, and 100- CFU/mL of Salmonella spp. and L. monocytogenes. We found that with RT-PCR, the Ct value of salad was significantly higher (p<0.05) than other RTE foods, indicating that fiber plays a critical role as an obstacle to the rapid detection of Salmonella spp. However, the Ct value displayed a mixed pattern according to the inoculation level of L. monocytogenes. The use of rapid detection kits and machines mostly depends on the user's choice, with accuracy, ease of use, and economy being the primary considerations. As an RT-PCR kit, SureTect^TM and PowerChek^TM showed high accuracy in detecting Salmonella spp. and L. monocytogenes in RTE foods, showing that they can replace the existing RT-PCR kits available. Additionally, LAMP also showed excellent detection performance, suggesting that it has the potential to be used as a food safety management tool.

• Information Systems Review
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• v.21 no.3
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• pp.63-86
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• 2019

As the use of ICT became a part of daily social life, online community has emerged as a new type of social organization. Online community is a virtual space which enables many people to participate and contribute together to collective knowledge. Anonymity in online communities can encourage active social participation by people with various social constraints, however, anonymity can also lead to serious social pathology. As a result, it is necessary to study on what is fundamentally influencing human behavior and how people's behavior is controlled in anonymous online community. This study focuses on human identity and investigate the factors affecting human behavior control in anonymous online environment by examining various aspects of identity in online discussion community. This study empirically verifies the causal relationship between factors, including social & technical anonymities, various identity dimensions, intrinsic motivation to participate in the community, group norm conformity, and quality of discussion. It also analyzes the difference between groups by the level of anonymity, gender, age, community usage period, and discussion topic. Based on the findings, this research provides theoretical and practical implications for online community management strategies and a better culture on Internet discussion.