• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.295-302
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• 2022

This study intends to apply the concept of reputation as a tool to positively build an evaluation of the CEO, the CEO of a company. It aims to develop tools to manage the reputation of the CEO and empirically explore the value of the tools use. As a result of the study, reliability, customer management, strategic vision, employee management, and social responsibility were derived as the constituent factors of CEO reputation, and it was confirmed that the relationship between CEO reputation and organizational favorability was statistically causal. Furthermore, the relationship between CEO reputation and product purchase intention was also statistically significant. It was confirmed that if the CEO's reputation was positively managed, it could help the stakeholders to evaluate the company to which the CEO belongs, as well as to purchase the products provided by the company. One of the ways to be well-received by various stakeholders in a corporate environment where uncertainty is intensifying is a reputation management system for CEOs, and CEOs themselves should recognize that their reputation can affect the organization and pay attention to reputation management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.3
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• pp.42-52
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• 2022

Bus Information System (BIS) services are expanding nationwide to small and medium-sized cities, including large cities, and user satisfaction is continuously improving. In addition, technology development related to improving reliability of bus arrival time and improvement research to minimize errors continue, and above all, the importance of information accuracy is emerging. In this study, accuracy performance was evaluated using LSTM, a machine learning method, and compared with existing methodologies such as Kalman filter and neural network. As a result of analyzing the standard error for the actual travel time and predicted values, it was analyzed that the LSTM machine learning method has about 1% higher accuracy and the standard error is about 10 seconds lower than the existing algorithm. On the other hand, 109 out of 162 sections (67.3%) were analyzed to be excellent, indicating that the LSTM method was not entirely excellent. It is judged that further improved accuracy prediction will be possible when algorithms are fused through section characteristic analysis.

• Journal of Wetlands Research
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• v.24 no.2
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• pp.102-114
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• 2022

Global climate change can be solved only through international cooperation. Climate change can be caused by natural and anthropogenic causes. An important policy responding on the climate change is to reduce the emission of climate change-affecting substances caused by anthropogenic causes. This research was conducted to suggest the direction of Korea's LULUCF(Land Use-Land Use Change and Forestry) policy by comparing Germany's LULUCF policy, which is considered as a good case for establishing the EU's greenhouse gas reduction response policy. Germany's LULUCF policy concerns with various sectors for synergy effects, while Korea's LULUCF policy is biased towards the forest sector. Although Korea's LULUCF policy focuses on forests, basic research is still insufficient and the linkage with existing environmental policies is low. Therefore, Korea's LULUCF policy needs more expansion into many different sectors such as agricultural, environmental, and other fields.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.495-499
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• 2024

This article summarizes the importance, definition, key strategies and future directions of sustainable packaging design.In modern society, sustainable packaging design is not only concerned with environmental protection and resource conservation, but also involves economic, social and cultural sustainable development.This paper explores strategies to reduce environmental burden and promote ecological balance by using environmentally friendly materials, optimizing packaging design, improving packaging recyclability and reuse. In addition, the article emphasizes the importance of design innovation, such as adopting a simplified design concept and modular system, as well as increasing the versatility of packaging.It also explores the application of life cycle assessment in packaging design to ensure that every step from design to disposal minimizes environmental impact. Finally, despite the environmental and social benefits that sustainable packaging design brings, it still faces technical, economic and regulatory challenges in practice.Future design will require interdisciplinary collaboration, integration of advanced technologies, consumer education and engagement, and enhanced policy and standard-setting to promote widespread adoption and practice of sustainable packaging.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.4
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• pp.303-314
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• 2024

Recently, the consecutive shield tunnel boring machine (TBM) has gained attention for its potential to enhance TBM penetration rates. However, its development requires a thorough risk assessment due to the unconventional nature of its equipment and hydraulic systems, coupled with the absence of design or construction precedents. This study investigated the causal relationships between four accidents and eight relevant sources associated with the consecutive shield TBM. Subsequently, risk levels were determined based on expert surveys and a risk matrix technique. The findings highlighted significant impacts associated with collapses or surface settlements and the likelihood of causal combinations leading to misalignment. Specifically, this study emphasized the importance of proactive mitigation measures to address collapses or surface settlements caused by inadequate continuous tail void backfill or damaged thrust jacks. Furthermore, it is recommended to develop advanced non-destructive testing technology capable of comprehensive range detection across helical segments, to design a sequential thrust jack propulsion system, and to determine an optimal pedestal angle.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.167-179
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• 2016

The safety of SOC facilities is constantly under threat by the globally increasing abnormal climate. Responding to disasters requires prompt decision-making such as suggesting evacuation paths. For doing so, spatio-temporal information with convergence of disaster information and SOC facility information must be utilized. Such information is being collected separately by the government or related organizations, but not collectively. The collective control of the separately collected disaster information and the generation of SOC facility safety and damage information are required for prompt disaster response. Also, as disaster information requires spatio-temporal convergence in its nature, the construction of an inventory that integrates related information and assists disaster response decision-making is required. A plan to construct a facility importance, risk, and damage estimation inventory for assisting prompt disaster response decision-making is suggested in this study. Through this study, the disaster and SOC facility-related data, which are being managed separately, can be collected and standardized. The integrated information required for the estimation of facility importance, risk, and damage can be provided. The suggested system is expected to be used as a decision-making tool for proactive disaster response.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.446-460
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• 2022

In this paper, we propose an algorithm to improve target detection rate degradation due to direct blast in a bi-static sonar systems with high duty cycle using an adaptive filters. It is very important to suppress the direct blast in the aforementioned sonar systems because it has a fatal effect on the actual system operation. In this paper, the performance was evaluated by applying the Normalized Least Mean Square (NLMS) and Recursive Least Square (RLS) algorithms to the simulation and sea experimental data. The beam signals of the target and direct blast bearings were used as the input and desired signals, respectively. By optimizing the difference between the two signals, the direct blast is removed and only the target signal is remained. As a result of evaluating the results of the matched filter in the simulation, it was confirmed that the direct blast was removed to the noise level in both Linear Frequency Modultated (LFM) and Generalized Sinusoidal Frequency Modulated (GSFM), and in the case of GSFM, the target sidelobe decreased by more than 20 dB, thereby improving performance. In the sea experiment, it was confirmed that the LFM reduced the level of the transmitted direct wave by 10 dB, the GSFM reduced the level of the transmitted direct wave by about 4 dB, and the side lobe of the target decreased by about 4 dB, thereby improving the performance.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.39-59
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• 2022

We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.159-181
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• 2022

Today, people in cities use differentthe types of transportation that rangepeople use in cities have diversified from existing public transportation, cars, taxis to shared bicycles and shared electric kickboards. In addition, with the development of mobile platform -based search, order, and payment services, and transportation services have also begun to change into platform-based integrated services. In particular, MaaS, which has emerged as an integrated mobile service and, is currently being studied and operated worldwide., However, MaaS but remains at the level of the integrated provision of the existing public transportation. As a result of Specifically, the results of a literature review on this issue reveal that, the First/Last Mile problem raised at the current level of MaaS is likely to be solved by establishing an improved policy incorporating new means of transportation. Therefore, this study aims to establish a First/Last Mile transportation supply plan for successful MaaS provision. This establishment is realized by analyzing the traffic patterns of urban populations usingbased on the ABATA system,, an activity-based traffic analysis model withevaluated as having higher analysis power on people's traffic.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.