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

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.1
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• pp.22-40
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• 2009

Detailed bathymetry and magnetic survey data for NW Rota-1 and Esmeralda Bank obtained by R/V Onnuri of Korea Ocean Research & Development Institute in September 2007 were analyzed to investigate bathymetry and magnetic characteristics of the study area and to estimate the locations of possible hydrothermal vents. The shape of NW Rota-1 is corn type, and the depth of the summit is about 500 meter b.s.l. NW Rota-1 shows irregular topographic expression in the southeastern part. The shape of Esmeralda Bank is caldera type opened in the western part. The summit is very shallow, about 50 meter b.s.l. The western part of Esmeralda Bank is more steeper and topographic irregular than the eastern part, and have the valley made by erosion or collapse. The magnetic anomaly patterns of NW Rota-1 and Esmeralda Bank show low anomalies over the north and high anomalies over the south. The magnetic anomalies are steep over the summits and gently smooth over the deep bottom. The low magnetization zone occurs over the summit of NW Rota-1 and is surrounded by the high zones correlated with its crater. Two low magnetization zones are located in the summit and westside of Esmeralda Bank. The low magnetization zones of the summits of NW Rota-1 and Esmeralda Bank suggest the possible existence of hydrothermal vent.

• Journal of The Korean Association For Science Education
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• v.28 no.8
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• pp.955-963
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• 2008

This study was conducted to assess any change in students' views on the nature of science (NOS) after lessons through the activities of model construction and pattern identification. The instrument used to examine NOS views was the Views of Nature of Science questionnaire (VNOS). Four students' responses on VNOS before and after instruction were analyzed. The two levels of their views, novice and expert, were judged by the authors based on criteria set by several science educators. The instruction consisted of six hours of the so-called black box and cube activities developed for model construction and pattern identification, respectively. Students' views were at the novice level in definition of scientific theory, tentativeness of scientific knowledge, difference of hypotheses, theories and laws, model construction, and creativity and imagination in experiments and investigations. Students' views on NOS knowledge such as model and theory have improved for two students after instruction. The improvement seemed to be due to an explicit approach using the activities of model construction and pattern identification. The factors of changes and no-changes of views on NOS were identified and discussed in terms of improvement of the views.

• Journal of The Korean Association For Science Education
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• v.27 no.7
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• pp.663-675
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• 2007

Chemical reactions in cells are so complicated and abstract that students have difficulty in understanding them. In this study, classes with the application of systematic analogies used at the interpretation of experimental results were taught to 10th-grade students in order to help them to understand the concept of enzymes, which play an important role in chemical reactions in cells. Effects of the classes on their understanding of the concept of enzymes and the role of systematic analogies were analyzed. The gap of understanding between the test group and the control group was significant at 0.05, indicating that systematic analogies are effective for students' understanding of the concept of enzymes. Looking into the concept of enzymes by individual element, the effect of systematic analogies was shown to be large for equilibrium-like processes, such as the enzyme structure change caused by temperature and pH; and the continuous and random actions of enzymes, which students have difficulty in understanding. For these processes, systematic analogies played a positive role in improving their conceptual status. The visualizations and familiarity of analogs increased their intelligibility regarding the concept of enzyme. Also, the systematic analogies increases their plausibility by helping to connect phenomena, taking place in the enzyme reaction experiments, with scientific concepts as scaffold. Accordingly, it was possible to explain experimental results as scientific concepts in a consistent manner. In addition, analogies familiar to students played a positive role from the affective perspective by promoting students' interest and helping them to approach hard scientific concepts.

• Information Systems Review
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• v.22 no.3
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• pp.99-118
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• 2020

At present, our society is developing into the intelligent information society in the wave of the 4th industrial revolution, and this change will have the positive effect of innovating all industry fields. However, due to the duality of technology, there will be positive and negative effects. With intelligence, threats to cyber dysfunction such as hacking, terrorism, privacy infringement, and illegal content distribution will become more serious. Until now, the security system of the Internet has been a proactive security system, but in recent years, a proposal for a trust network, a preventive security system, has been introduced. Therefore, this study aims to analyze the possibility of resolving cyber dysfunction of intelligent information society about Bright Internet, one of trust network technologies. This study defines the cyber dysfunction of the intelligent information society and analyzes the perceptions of changes in the cyber dysfunction of the intelligent information society on the introduction of the five principles of the Bright Internet. The change of cyber dysfunction severity of the intelligent information society due to the introduction of the trust network is analyzed to reflect the technical and social demands. This work will guide the structure of the trust network and the direction of practical technological introduction and its influence.

• Knowledge Management Research
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• v.25 no.2
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• pp.115-134
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• 2024

In an age where consumers can easily search and pass on their opinions of products and purchasing decisions through the internet, Electronic-word-of-mouth(Ewom) plays an important role in decision making of other potential customers. In this study, we empirically analyze the impact EWOM on consumer purchase decisions, when contradictory Ewom is presented from varying sources of information, such as experts and general consumers. First, we find that when there is a consensus among different information sources there exists a positive relationship between Ewom sentiment and purchase intent, confirming the results of previous literature. However, when expert opinion and consumer opinion do not match we find that consumer opinion is more impactful on purchasing decisions compared to the expert opinion, regardless of product types. The findings of this study add insight to the current literature by examining the effect of contradictory Ewom on purchase decisions, and also to industry marketers by presenting a more efficient strategy in promoting positive Ewom for different product types.

• KIPS Transactions on Computer and Communication Systems
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• v.13 no.1
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• pp.21-30
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• 2024

As the self-driving car market continues to grow, the need for charging infrastructure is growing. However, in the case of a wireless charging system, stability issues are being raised because it requires a large amount of power compared with conventional wired charging. SAE J2954 is a standard for building autonomous vehicle wireless charging infrastructure, and the standard defines a communication method between a vehicle and a power transmission system. SAE J2954 recommends using physical media such as Wi-Fi, Bluetooth, and UWB as a wireless charging communication method for autonomous vehicles to enable communication between the vehicle and the charging pad. In particular, UWB is a suitable solution for indoor and outdoor charging environments because it exhibits robust communication capabilities in indoor environments and is not sensitive to interference. In this standard, the process for building a wireless power transmission system is divided into several stages from the start to the completion of charging. In this study, UWB technology is used as a means of fine alignment, a process in the wireless power transmission system. To determine the applicability to an actual autonomous vehicle wireless power transmission system, experiments were conducted based on distance, and the distance information was collected from UWB. To improve the accuracy of the distance data obtained from UWB, we propose a Single Model and Multi Model that apply machine learning and deep learning techniques to the collected data through a three-step preprocessing process.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.67-74
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• 2024

In this paper, we present a study aimed at analyzing how different rainfall measurement methods affect the performance of reservoir water level predictions. This work is particularly timely given the increasing emphasis on climate change and the sustainable management of water resources. To this end, we have employed rainfall data from ASOS, AWS, and Thiessen Network-based measures provided by the KMA Weather Data Service to train our neural network models for reservoir yield predictions. Our analysis, which encompasses 34 reservoirs in Jeollabuk-do Province, examines how each method contributes to enhancing prediction accuracy. The results reveal that models using rainfall data based on the Thiessen Network's area rainfall ratio yield the highest accuracy. This can be attributed to the method's accounting for precise distances between observation stations, offering a more accurate reflection of the actual rainfall across different regions. These findings underscore the importance of precise regional rainfall data in predicting reservoir yields. Additionally, the paper underscores the significance of meticulous rainfall measurement and data analysis, and discusses the prediction model's potential applications in agriculture, urban planning, and flood management.

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.493-498
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• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.