• Journal of Service Research and Studies
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• v.14 no.1
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• pp.44-62
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• 2024

The development of online funeral services and social issues of eco-friendly funeral culture have raised awareness of the new need for online funeral culture. There have been several attempts to revitalize online funeral services in domestic institutions and companies, but the effect is weak. The purpose of this study is to propose a design that can improve the accessibility and usability of online memorial services by analyzing the usability problem factors through a First Time User Experience analysis of the online memorial platform. Therefore, in this study, in order to identify the problem factors of the online memorial platform, a literature review on the UX, OOBE, and FTUE theories was conducted. The subject of the study was the app 'Memorial'. Before analyzing the First-Time User-Experience, IA was compared and analyzed with other similar services to understand the characteristics of the UX service of the app 'Memorial', which is the subject of the study. In addition, tasks corresponding to the Unpack-Setup/Configure-First Use stage were performed on 10 subjects who had no experience using the online memorial platform. The experimental process was expressed as the UX Curve to identify factors that caused negative experiences. As a result, the major problem factors included unnecessary UI elements, the need for sensitive personal information at the membership stage, and lack of immersion in the service. The improvements included strengthening community functions to facilitate the sharing of emotions and promote smooth communication between users. We proposed UI/UX service developments that enhanced the app by incorporating these insights. In order to verify the effectiveness, serviceability, and value of the developed prototype, an interview with a expert was conducted. The interviewes consisted of three service design experts. This study was conducted to contribute to the quality improvement and activation of the recently emerging online funeral services. The study is significant as it aims to understand the current status of these services and identify the factors necessary to improve service accessibility and usability. Subsequent studies require in-depth user verification of how much the proposed improvement plan affects the actual user experience.

• Journal of Service Research and Studies
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• v.14 no.1
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• pp.63-76
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• 2024

Multi-family housing plays a crucial role as a living and experiencing space, and its environment has a direct impact on the well-being and stability of its residents. Therefore, Crime Prevention Design (CPTED) for multi-family housing is of utmost importance. However, crime-related data in China is not disclosed to the public because of its specificity, making it difficult for researchers to conduct further in-depth studies based on accurate crime data. As a result, the establishment and application of CPTED theory in terms of crime prevention is limited and delayed. This study aims to explore three aspects of CPTED in multi-family housing as perceived by home-buying consumers. It investigated consumer perception of the CPTED, the importance of each element and ways to increase awareness of CPTED in multifamily housing in order to effectively improve multifamily crime prevention design principles and further enhance public safety. This study examined the current state and future trends of CPTED in China by analyzing relevant research reports and literature, aiming to gain insights into the crime prevention awareness of Chinese homeowners. In addition, a survey was conducted on Chinese consumers to unravel the importance of CPTED and increase awareness of its various elements in multifamily-family. This study used a Likert scale and SPSS reliability analysis to determine the cognitive status of multi-family CPTED, the importance of each element, and proposed an improvement plan based on the analysis results. As this study was limited by the difficulty of implementation and the lack of validation of its practical effectiveness, it is recommended that future research needs to validate the effectiveness of crime prevention designs and produce more practical results. Furthermore, it is crucial to utilize this study to inform the implementation of security solutions that are tailored to the unique characteristics of each district. Additionally, it is important to offer guidance on how to enhance community safety by increasing residents' awareness of security through education and information dissemination. The author hopes that the representative multi-family CPTED awareness, the importance of each element, and plans for improvement shall be summarized from this study, and provide foundational data for the future development of CPTED based on the Chinese region.

• Journal of Environmental Impact Assessment
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• v.33 no.3
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• pp.131-141
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• 2024

The environmental impact assessment have been played important role for sustainable development of the country. Meantime, various studies have been conducted for scientific and effective environmental impact assessment. Howeverthe quantitative data such as regional distribution status and development characteristics according to the type of development project, environmental changes due to development projects, and spatial-temporal changes are insufficient, currently. In this study, we investigated the eco-friendliness of major development projects (industrial complex, urban development, tourist complexes, and waste disposal equipments) by integrating the EA-INDEX of each development projects which were reported by prior researches. As a result, we found that the eco-friendliness of development projects tended to gradually increase overtime due to the increase in eco-friendliness in the protection of living environment sector. The protection of living environment sector was a major factor in the the eco-friendliness of industrial complexes and urban development projects. In the case ofroad construction, landfill and tourist complex development projects, the natural environment conservation sector was a major factor in the eco-friendliness of the project. As a result of analyzing the eco-friendliness of development projects by local government, the eco-friendliness of development projects promoted and implemented in Ulsan, Jeonnam, and Gwangju was higher compared to other regions, and it was relatively low in Daejeon, Gyeongnam, and Daegu. This study is considered to be significant in that it conducted a quantitative analysis of the eco-friendliness of development projects carried out over a relatively long period of time throughout South Korea by dividing them by year and local government.

• The Journal of the Acoustical Society of Korea
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• v.43 no.1
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• pp.9-18
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• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.57-75
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• 2024

This study aimed to investigate the current state and educational needs of risk education related to science and technology as perceived by secondary science teachers. A survey was conducted with a total of 366 secondary science teachers. The results are as follows. First, There were more teachers who had not provided education on risks arising from science and technology in terms of risk perception, risk assessment, and risk management than those who had not. Global warming was the most common risk taught by teachers, followed by earthquakes, artificial intelligence, and traffic accidents. Second, teachers recognized that they lacked understanding that the achievement standards of the 2022 revised science curriculum include risks that may occur due to science and technology, but they thought they were prepared to teach. Third, teachers recognized that their understanding of risk perception was higher than that of risk management and risk assessment. Fourth, the experience of teachers in training on risk was very limited, with fewer having training in risk assessment and risk management compared to risk perception. The most common training experienced was in laboratory safety. Fifth, teachers recognized that their capabilities for the 10 goals of risk education were not high. Middle school teachers or teachers majoring in integrated science education evaluated their capabilities relatively highly. Sixth, many teachers thought it was important to address risks in school science education. They prioritized 'information use', 'decision-making skills', and 'influence of mass media', in that order, for importance and called for urgent education in 'action skills', 'information use', and 'influence of risk perception'. Seventh, as a result of deriving the priorities of education needs for each of the 10 goals of risk education, 'action skills', 'influence of risk perception', and 'evaluate risk assessment' were ranked 1st, 2nd, and 3rd, respectively.

• Journal of Food Hygiene and Safety
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• v.39 no.1
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• pp.26-34
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• 2024

In this study, the food service management levels of cafeterias in childcare facilities were investigated based on the number of meal recipients and the working status of the kitchen staff. The study included 199 childcare facilities nationwide that received food supplies from the food ingredients distribution company, Pulmuone Foodmerce, from 2021 to 2022. The assessment was conducted using 61 inspection items. The analysis revealed that, as the number of meal recipients and kitchen staff members decreased, the documentation of inspection results was less likely to be conducted (P<0.05). Facilities with fewer meal recipients showed less adequate health status checks for kitchen staff, and those with fewer kitchen staff showed insufficient compliance with hygienic clothing (P<0.05). Additionally, facilities with fewer meal recipients showed a higher frequency of lapses in checking the expiration dates of stored ingredients (P<0.05), requiring increased management attention. They also exhibited the absence of internal temperature measurement records during heating processes (P<0.05). Furthermore, facilities with fewer meal recipients demonstrated inadequate maintenance of kitchen facilities (P<0.05). Significantly higher adenosine triphosphate (ATP) levels were detected on the hands and cutting boards of the kitchen staff in facilities with fewer meal recipients and fewer kitchen staff (P>0.05). Overall, facilities with fewer meal recipients exhibited insufficient infrastructure management for kitchen operations and inadequate hygiene management. These results are expected to provide foundational data for the selection of national support programs for childcare facilities in the future.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.49-95
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• 2024

Polygraph examination, statement validity analysis and P300-based concealed information test are major three examination tools, which are use to determine a person's truthfulness and credibility in criminal procedure. Although polygraph examination is most common in criminal procedure, but it has little admissibility of evidence due to the weakness of scientific basis. In 1990s to support the weakness of scientific basis about polygraph, Farwell and Donchin proposed the P300-based concealed information test technique. The P300-based concealed information test has two strong points. First, the P300-based concealed information test is easy to conduct with polygraph. Second, the P300-based concealed information test has plentiful scientific basis. Nevertheless, the utilization of P300-based concealed information test is infrequent, because of the quantity of probe stimulus. The probe stimulus contains closed information that is relevant to the crime or other investigated situation. In tradition P300-based concealed information test protocol, three or more probe stimuli are necessarily needed. But it is hard to acquire three or more probe stimuli, because most of the crime relevant information is opened in investigative situation. In addition, P300-based concealed information test uses oddball paradigm, and oddball paradigm makes imbalance between the number of probe and irrelevant stimulus. Thus, there is a possibility that the unbalanced number of probe and irrelevant stimulus caused systematic underestimation of P300 amplitude of irrelevant stimuli. To overcome the these two limitation of P300-based concealed information test, one-probe P300-based concealed information test protocol is explored with various machine learning algorithms. According to this study, parameters of the modified one-probe protocol are as follows. In the condition of female and male face stimuli, the duration of stimuli are encouraged 400ms, the repetition of stimuli are encouraged 60 times, the analysis method of P300 amplitude is encouraged peak to peak method, the cut-off of guilty condition is encouraged 90% and the cut-off of innocent condition is encouraged 30%. In the condition of two-syllable word stimulus, the duration of stimulus is encouraged 300ms, the repetition of stimulus is encouraged 60 times, the analysis method of P300 amplitude is encouraged peak to peak method, the cut-off of guilty condition is encouraged 90% and the cut-off of innocent condition is encouraged 30%. It was also conformed that the logistic regression (LR), linear discriminant analysis (LDA), K Neighbors (KNN) algorithms were probable methods for analysis of P300 amplitude. The one-probe P300-based concealed information test with machine learning protocol is helpful to increase utilization of P300-based concealed information test, and supports to determine a person's truthfulness and credibility with the polygraph examination in criminal procedure.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.177-198
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• 2024

Article 22(1) of the Library Act, which was completely revised in December 2006, stipulated that regional representative libraries are statutory organizations, and Article 25(1) of the Library Act, which was revised again in late 2021, renamed them as metropolitan representative libraries and expanded their duties. The reason why cities and provinces are required to specify or establish and operate metropolitan representative libraries is that in addition to their role as public libraries for public information use, cultural activities, and lifelong learning as stipulated in Article 23 of the Act, they are also responsible for the legal works of metropolitan representative libraries as stipulated in Article 26, and lead the development of libraries and knowledge culture by serving as policy libraries, comprehensive knowledge information centers, support and cooperation centers, research centers, and joint preservation libraries for all public libraries in the city or province. Therefore, it is necessary to analyze and diagnose whether the metropolitan representative library has been faithfully fulfilling its legal works for the past 15 years(2009-2023), and whether it is properly providing the results of its statutory planning and implementation on its website to meet the digital and mobile era. Therefore, this study investigated and analyzed the performance of the metropolitan representative library for the last two years based on the current statutory tasks and evaluated the extent to which it provides them through its website, and suggested complementary measures to strengthen its web services. As a result, it was analyzed that the web services for legal works that the metropolitan representative library should perform are quite insufficient and inadequate, so it suggested complementary measures such as building a website for legal works on the homepage, enhancing accessibility and visibility through providing an independent website, providing various policy information and web services (portal search, inter-library loan, one-to-one consultation, joint DB construction, data transfer and preservation, etc.), and ensuring digital accessibility of knowledge information for the vulnerable.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.