• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.3-47
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• 2021

Recently a multilayer spectral inversion (MLSI) model has been proposed to infer the physical parameters of plasmas in the solar chromosphere. The inversion solves a three-layer radiative transfer model using the strong absorption line profiles, H alpha and Ca II 8542 Å, taken by the Fast Imaging Solar Spectrograph (FISS). The model successfully provides the physical plasma parameters, such as source functions, Doppler velocities, and Doppler widths in the layers of the photosphere to the chromosphere. However, it is quite expensive to apply the MLSI to a huge number of line profiles. For example, the calculating time is an hour to several hours depending on the size of the scan raster. We apply deep neural network (DNN) to the inversion code to reduce the cost of calculating the physical parameters. We train the models using pairs of absorption line profiles from FISS and their 13 physical parameters (source functions, Doppler velocities, Doppler widths in the chromosphere, and the pre-determined parameters for the photosphere) calculated from the spectral inversion code for 49 scan rasters (~2,000,000 dataset) including quiet and active regions. We use fully connected dense layers for training the model. In addition, we utilize a skip connection to avoid a problem of vanishing gradients. We evaluate the model by comparing the pairs of absorption line profiles and their inverted physical parameters from other quiet and active regions. Our result shows that the deep learning model successfully reproduces physical parameter maps of a scan raster observation per second within 15% of mean absolute percentage error and the mean squared error of 0.3 to 0.003 depending on the parameters. Taking this advantage of high performance of the deep learning model, we plan to provide the physical parameter maps from the FISS observations to understand the chromospheric plasma conditions in various solar features.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.55.3-55.3
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• 2019

We present a pipeline to estimate baryonic properties of a galaxy inside a dark matter (DM) halo in DM-only simulations using a machine trained on high-resolution hydrodynamic simulations. As an example, we use the IllustrisTNG hydrodynamic simulation of a (75 h^-1 Mpc)³ volume to train our machine to predict e.g., stellar mass and star formation rate in a galaxy-sized halo based purely on its DM content. An extremely randomized tree (ERT) algorithm is used together with multiple novel improvements we introduce here such as a refined error function in machine training and two-stage learning. Aided by these improvements, our model demonstrates a significantly increased accuracy in predicting baryonic properties compared to prior attempts --- in other words, the machine better mimics IllustrisTNG's galaxy-halo correlation. By applying our machine to the MultiDark-Planck DM-only simulation of a large (1 h^-1 Gpc)³ volume, we then validate the pipeline that rapidly generates a galaxy catalogue from a DM halo catalogue using the correlations the machine found in IllustrisTNG. We also compare our galaxy catalogue with the ones produced by popular semi-analytic models (SAMs). Our so-called machine-assisted semi-simulation model (MSSM) is shown to be largely compatible with SAMs, and may become a promising method to transplant the baryon physics of galaxy-scale hydrodynamic calculations onto a larger-volume DM-only run. We discuss the benefits that machine-based approaches like this entail, as well as suggestions to raise the scientific potential of such approaches.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.531-543
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• 2023

The existing concrete bridges are time-varying working systems, where the maintenance strategy should be planned according to the time-varying performance of the bridge. This work proposes a time-dependent residual capacity assessment procedure, which considers the non-stationary bridge load effects under growing traffic and non-stationary structural deterioration owing to material degradations. Lifetime bridge load effects under traffic growth are predicated by the non-stationary peaks-over-threshold (POT) method using time-dependent generalized Pareto distribution (GPD) models. The non-stationary structural resistance owing to material degradation is modeled by incorporating the Gamma deterioration process and field inspection data. A three-span continuous box-girder bridge is illustrated as an example to demonstrate the application of the proposed procedure, and the time-varying reliability indexes of the bridge girder are calculated. The accuracy of the proposed non-stationary POT method is verified through numerical examples, where the shape parameter of the time-varying GPD model is constant but the threshold and scale parameters are polynomial functions increasing with time. The case study illustrates that the residual flexural capacities show a degradation trend from a slow decrease to an accelerated decrease under traffic growth and material degradation. The reliability index for the mid-span cross-section reduces from 4.91 to 4.55 after being in service for 100 years, and the value is from 4.96 to 4.75 for the mid-support cross-section. The studied bridge shows no safety risk under traffic growth and structural deterioration owing to its high design safety reserve. However, applying the proposed numerical approach to analyze the degradation of residual bearing capacity for bridge structures with low safety reserves is of great significance for management and maintenance.

• Coupled systems mechanics
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• v.12 no.6
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• pp.531-537
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• 2023

Municipal solid waste landfills are unpredictable bioreactors which in cases of mishandling and bad supervision presents numerous risks. The key to municipal waste landfills is to approach them from the point of prevention of the possible consequences, which means using methods of organized waste disposal, and also utilizing landfill gas, as an unavoidable consequence with disposal of municipal solid waste with a high share of biodegradable organic matter. This paper presents an overview about problems of solid municipal waste management, type and composition of waste, and an overview of waste management condition. Further, the problem of landfill and landfill gasses is described with the calculation models of landfill production, as well as the use of the SWM GHG Calculator and LandGEM software on a specific example of gas production for the central zone at Sarajevo landfill "Smiljevici". Main focus of this thesis is the analysis of potentials of greenhouse gas emission reduction measures from the waste management. Overview of the best available techniques in waste management is presented as well as the methodology used for calculations. Scenarios of greenhouse gas emission reduction in waste management were defined so that emissions were calculated using the appropriate model. In the final section of the paper, its description of the problem of collection and utilization the landfill gas at the sanitary landfill "Smiljevici", and implementation of the system for landfill gas collection and solution suggestion for the gasification and exploitation of gas. Energy, environmental and economic benefits can be accomplished by utilizing municipal solid waste as fuel in industry and energy and moreover by utilizing energy generation from landfill gas, which this thesis emphasizes.

• Journal of The Korean Association For Science Education
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• v.28 no.5
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• pp.383-394
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• 2008

We analyzed the description of diffusion phenomena in a 7th-grade textbook, and investigated teachers' understanding and teaching methods on diffusion concepts. The data were collected from textbook analysis and questionnaires from 46 science teachers and interviews with 5 teachers. Based on texts' analysis by definition, example, and representation of the diffusion, we found that most of the representations were macroscopically explained by observing the movement of ink in water and smelling the fragrance of perfume in the air. The analysis of questionnaire and interviews also revealed that the definition and the explanation of the diffusion were too abstract for teachers to understand and teach the concept without further information about the microscopic concept of collision of the matter with the medium. Such examples and models lead science teachers to form indistinctive concepts such as dissolution, effusion, and evaporation. Furthermore, the analytical data showed that teachers' understanding of the diffusion concept has been heavily dependent upon the textbook and the level of the understanding was very similar with that of textual description.

• The Journal of Bigdata
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• v.8 no.2
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• pp.83-95
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• 2023

Big data analytics and AI play a critical role in the development of smart plants. This study presents a big data platform for plant data and an 'AutoML platform' for AI-based plant O&M(Operation and Maintenance). The big data platform collects, processes and stores large volumes of data generated in plants using Hadoop, Spark, and Kafka. The AutoML platform is a machine learning automation system aimed at constructing predictive models for equipment prognostics and process optimization in plants. The developed platforms configures a data pipeline considering compatibility with existing plant OISs(Operation Information Systems) and employs a web-based GUI to enhance both accessibility and convenience for users. Also, it has functions to load user-customizable modules into data processing and learning algorithms, which increases process flexibility. This paper demonstrates the operation of the platforms for a specific process of an oil company in Korea and presents an example of an effective data utilization platform for smart plants.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.7-21
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• 2024

There are various machine learning techniques such as Reinforcement Learning, Deep Learning, Neural Network Learning, and so on. In recent, Large Language Models (LLMs) are popularly used for Generative AI based on Reinforcement Learning. It makes decisions with the most optimal rewards through the fine tuning process in a particular situation. Unfortunately, LLMs can not provide any explanation for how they reach the goal because the training is based on learning of black-box AI. Reinforcement Learning as black-box AI is based on graph-evolving structure for deriving enhanced solution through adjustment by human feedback or reinforced data. In this research, for mutually exclusive decision-making, Mutually Exclusive Learning (MEL) is proposed to provide explanations of the chosen goals that are achieved by a decision on both ends with specified conditions. In MEL, decision-making process is based on the tree-based structure that can provide processes of pruning branches that are used as explanations of how to achieve the goals. The goal can be reached by trade-off among mutually exclusive alternatives according to the specific contextual conditions. Therefore, the tree-based structure is adopted to provide feasible solutions with the explanations based on the pruning branches. The sequence of pruning processes can be used to provide the explanations of the inferences and ways to reach the goals, as Explainable AI (XAI). The learning process is based on the pruning branches according to the multi-dimensional contextual conditions. To deep-dive the search, they are composed of time window to determine the temporal perspective, depth of phases for lookahead and decision criteria to prune branches. The goal depends on the policy of the pruning branches, which can be dynamically changed by configured situation with the specific multi-dimensional contextual conditions at a particular moment. The explanation is represented by the chosen episode among the decision alternatives according to configured situations. In this research, MEL adopts the tree-based learning model to provide explanation for the goal derived with specific conditions. Therefore, as an example of mutually exclusive problems, employment process is proposed to demonstrate the decision-making process of how to reach the goal and explanation by the pruning branches. Finally, further study is discussed to verify the effectiveness of MEL with experiments.

• The Korean Journal of Air & Space Law and Policy
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• v.21 no.1
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• pp.135-167
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• 2006

Air service agreements between EU Member States and third countries concluded by Sweden, Finland, Belgium, Luxembourg, Austria, the Netherlands, Denmark and the United Kingdom after the Second World War infringe EU law. They authorize the third countries to withdraw, suspend or limit the traffic rights of air carriers designated by the signatory States. According to the Court of Justice of the European Communities (CJEC), these agreements infringe EU law in two respects. On the one hand, the presence of nationality clauses infringes the right of European airlines to non-discriminatory market access to routes between all Member States and third countries. On the other hand, only the EU has the authority to sign up to this type of commitment where agreements affect the exercise of EU competence, i.e. involve an area covered by EU legislation. The Court held that since the third countries have the right to refuse a carrier, these agreements therefore constitute an obstacle to the freedom of establishment and freedom to provide services, as the opening of European skies to third countries' companies is not reciprocal for all EU airlines. In the conclusion, in order to reconstruct these public international air law, The new negotiations between EU member states and third countries, especially the US, must be designed to ensure an adequate set of principles, so that Member States, in their bilateral relations with third countries in the area of air service, should consider following three models. The 1st, to develop a new model of public international air law such as a new Bermuda III. The 2nd, to reconstruct new freedoms of the air, for example, the 7th, 8th, and 9th freedoms. The 3rd, to explore new approaching models, such as complex system theory explored in the recent social sciences, to make access world-wide global problems instead of bilateral problems between EU member states and United States. The example will show any lessons to air talks between European Union and ROK.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.195-221
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• 2009

According to an industry report, a large number of organizations have invested in Organizational Information System(OIS) in the past few years. Several research results indicate that successful investments in OIS lead to productivity enhancement, while failed ones result in undesirable consequences such as financial losses and dissatisfaction among employees. In spite of huge investments, however, many organizations have failed in achieving the hoped-for returns from OIS. Thus, understanding user acceptance, adoption, and usage of new IS(Information Systems) is an important issue for IS practitioners. Indeed, study of the user acceptance of new information system has been one of the most important research topics in the contemporary IS literature. Several theoretical models are tested to examine 'user acceptance' and 'usage behavior' in IS context. While many research models incorporate 'ease of use' or 'usefulness' as important factors in explaining user acceptance, Technology Acceptance Model(TAM) has been one of the most widely applied models in user acceptance and usage behavior. Even in recent IS studies that employ theories of innovation diffusion in the area of IS implementation, a major focus has been on the user's perception of information technologies. In this research, we study 'voluntariness' as an important factor in IS acceptance by users. Voluntariness is defined as "the degree to which the use of the innovation is perceived as being voluntary, or of free will" When examining the diffusion of accepting OIS, a thoughtful consideration should be given to 'perceived voluntariness.' Current article has following research questions: 1) What models are appropriate to explain the success of OIS? and 2) How does the 'voluntariness' affect the success of OIS? In order to answer these questions, a research model is proposed to describe the detailed nature of association among three independent variables (IT usage level, task interdependency, and organizational support), a mediating variable (IS usage), a dependent variable (perceived performance), and a moderating variable(perceived voluntariness). The central claim of this article is that organizations hardly realize expected returns from OIS investments unless perceived voluntariness is effectively managed after operating OIS. As an example of OIS in this study we have selected the Intranet of Republic of Korea Air Force (ROKAF). ROKAF has implemented the Intranet in an attempt to improve communication and coordination within the organization. To test our research model and hypotheses, survey questionnaires were first sent out to 400 Intranet users. With the assistance of ROKAF, Intranet users were initially identified among its members, and subjects were randomly drawn from the pool. 377 survey responses were finally returned. The unit of measurement and analysis in this research is a personal level. Path analysis based on structural equation modeling was used to test research hypotheses. Construct validity represents accordance between the theoretical base concept of constructs and its measurement items. Tests for the reliability and discriminant validity are accepted, thus verifying our survey instrument. In this research, we have proposed a conceptual framework to highlight the importance of perceived voluntariness after organization deploys OIS. The results of our analysis present several key finding. First, all three independent variables (IT usage level, task interdependency, and organizational support) have significant effects on IS usage, which will eventually improve performance. Thus, IS usage plays a mediating role between antecedent variables (IT usage level. task interdependency, and organizational support) and performance improvement. Second, the effect of the task dependency was the highest for IS usage among the three antecedent variables. This is highly plausible since one of the Intranet's major capabilities is to facilitate communication among members within an organization. Accordingly, we conclude that the higher the task dependency, the higher Intranet usage. The effect of user's IT usage level was the second, while the effect of the organizational support was the third. Finally, the perceived voluntariness plays a pivotal role in enhancing perceived performance in personal level after launching the Intranet. Relationships among investigated variables were significantly different between groups with a high level and a low level of voluntariness. The impact of the Intranet usage on the performance was greater in the higher level voluntariness group than in the lower one. For the lower level voluntariness group, the user's IT usage had the highest effect on the Intranet usage among the three antecedent variables. In short, our study suggests that the higher the perceived voluntariness is the more IS usage will be. Perceived voluntariness was found to have a moderating effect on the relationships among user IT usage level, task interdependency, IS usage, and perceived performance, supporting all the hypotheses on the moderating effect. Most of all, user IT usage level has the strongest influence on IS usage, indicating that users with superior IT usage are more likely to enjoy a high level of perceived performance.

• Journal of Life Science
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• v.34 no.5
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• pp.339-355
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• 2024

The pulmonary system is a highly complex system that can only be understood by integrating its functional and structural aspects. Hence, in vivo animal models are generally used for pathological studies of pulmonary diseases and the evaluation of inhalation toxicity. However, to reduce the number of animals used in experimentation and with the consideration of animal welfare, alternative methods have been extensively developed. Notably, the Organization for Economic Co-operation and Development (OECD) and the United States Environmental Protection Agency (USEPA) have agreed to prohibit animal testing after 2030. Therefore, the latest advances in biotechnology are revolutionizing the approach to developing in vitro inhalation models. For example, lung organ-on-a-chip (OoC) and organoid models have been intensively studied alongside advancements in three-dimensional (3D) bioprinting and microfluidic systems. These modeling systems can more precisely imitate the complex biological environment compared to traditional in vivo animal experiments. This review paper addresses multiple aspects of the recent in vitro modeling systems of lung OoC and organoids. It includes discussions on the use of endothelial cells, epithelial cells, and fibroblasts composed of lung alveoli generated from pluripotent stem cells or cancer cells. Moreover, it covers lung air-liquid interface (ALI) systems, transwell membrane materials, and in silico models using artificial intelligence (AI) for the establishment and evaluation of in vitro pulmonary systems.