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  1. AU="Hyunsoo Lee"
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  1. Artikel ; Online: Development of Sustainable Recycling Investment Framework Considering Uncertain Demand and Nonlinear Recycling Cost

    Hyunsoo Lee

    Sustainability, Vol 11, Iss 14, p

    2019  Band 3891

    Abstract: This paper presents a more active and efficient recycling investment strategy that considers the balances among the current production constraints, manufacturing profits, and recycling investments for a sustainable circular economy as compared to the ... ...

    Abstract This paper presents a more active and efficient recycling investment strategy that considers the balances among the current production constraints, manufacturing profits, and recycling investments for a sustainable circular economy as compared to the current methods. While existing production planning has numerous uncertainties and nonlinear characteristics, the circular economy-based production planning constitutes more complex uncertainties and nonlinear characteristics that result from an uncertain return rate, demand uncertainties, and nonlinear return on investment costs. This paper suggests a stochastic nonlinear programming model-based active recycling investment framework so as to generate a more effective process plan to handle these characteristics. In the proposed framework, recycling investment strategies are quantitatively analyzed when considering uncertain demand and unclear production conditions. In addition, the effective solving techniques for the circular economy based production framework are obtained while using Monte-Carlo based sample average approximation and memetic algorithm. To prove the effectiveness of the proposed framework, it is implemented for a given system and the numerical analyses that were conducted for the various sustainable manufacturing scenarios.
    Schlagwörter recycling investment strategy ; demand uncertainty ; Stochastic nonlinear Programming ; Monte-Carlo based sample average approximation method ; memetic algorithm ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Thema/Rubrik (Code) 338
    Sprache Englisch
    Erscheinungsdatum 2019-07-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System

    Hyunsoo Lee

    Processes, Vol 7, Iss 3, p

    2019  Band 172

    Abstract: Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the ...

    Abstract Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the embedded intelligence analytics. This research applied this trend to the control of a key supplier’s real-time production planning for solving joint production goals with downstream producers. As a key supplier has several downstream producers in general, several uncertainties are embedded on the supply chain network such as the quality issue in the supplier and the occurrence of unexpected orders from the downstream industries. While the control of a supply plan is difficult considering these dynamics in traditional frameworks, the proposed framework detects the dynamic changes accurately using the constructed cloud system. Moreover, the real-time control considering uncertain scenarios as well as the extracted knowledge is achieved using the provided Industrial Internet of Things (IIoT) and simulation-based control model using stochastic network. To show the effective of the suggested framework, real manufacturing cases and their numerical analyses are provided.
    Schlagwörter joint cooperation in upstream/downstream manufacturing ; Industrial Internet of Things (IIoT) ; cloud environment ; stochastic control ; simulation-based optimization ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
    Thema/Rubrik (Code) 629
    Sprache Englisch
    Erscheinungsdatum 2019-03-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Development of a prediction system for precipitation- and wind-causing typhoons affecting the Korean peninsula using observational data

    Minyeong Kim / Seonghee Won / Hyunsoo Lee

    Frontiers in Earth Science, Vol

    2024  Band 12

    Abstract: Introduction: When the forecasted typhoon track differs from the numerical model’s prediction, the estimated precipitation and wind from the model may not be reliable. Typically, forecasters receive numerical model forecasts with a delay of 4 h or more ... ...

    Abstract Introduction: When the forecasted typhoon track differs from the numerical model’s prediction, the estimated precipitation and wind from the model may not be reliable. Typically, forecasters receive numerical model forecasts with a delay of 4 h or more in calculation time. However, a more timely reference of precipitation and wind forecasts is required in an emergency with an approaching typhoon. Analyses of the observational data of typhoon-related characteristics, such as heavy rainfall and strong winds, from 1997 to 2021 revealed that their distribution areas are considerably affected by typhoon tracks. In this study, we developed a precipitation and wind prediction system based on the observational data of the typhoons that affected the Korean Peninsula.Methods: Typhoon tracks were categorized into west-coast landfalls, southeast landfalls, and those passing the Korea Strait. Each category affects the Korean Peninsula differently in terms of rainfall and wind. We devised a system that predicts these patterns based on incoming typhoon tracks. We can make forecasts by comparing the approaching typhoons to previous instances and analyzing their center, movement direction, and size. Observations from these past typhoons were averaged to produce a forecast grid for each new typhoon.Results: Our system, validated from 2019 to 2022, showed a wind speed root-mean-square error of 3.37 m/s and a precipitation accuracy index of 0.72. For comparison, traditional numerical models yielded 5.04 m/s and 0.75, respectively. This indicates that our system is comparably efficient and computationally less demanding.Discussion: Our system’s strength is its ability to offer real-time typhoon forecasts, often faster than numerical models. However, its dependence on historical data limits its predictive power for atypical weather scenarios. It is essential to consider integrating ensemble models with these observations for enhanced accuracy. Since 2022, this system has been operational at the Korea Meteorological Administration, ...
    Schlagwörter landfalling typhoon ; Korea meteorological administration ; precipitation forecast ; wind speed forecast ; automatic weather station ; Science ; Q
    Thema/Rubrik (Code) 910
    Sprache Englisch
    Erscheinungsdatum 2024-01-01T00:00:00Z
    Verlag Frontiers Media S.A.
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: Hybrid Metaheuristic-Based Spatial Modeling and Analysis of Logistics Distribution Center

    Maryam Khairunissa / Hyunsoo Lee

    ISPRS International Journal of Geo-Information, Vol 11, Iss 5, p

    2022  Band 5

    Abstract: The location analysis of logistics distribution centers is one of the most critical issues in large-scale supply chains. While a number of algorithms and applications have been provided for this end, comparatively fewer investigations have been made into ...

    Abstract The location analysis of logistics distribution centers is one of the most critical issues in large-scale supply chains. While a number of algorithms and applications have been provided for this end, comparatively fewer investigations have been made into the integration of geographical information. This study proposes logistic distribution center location analysis that considers current geographic and embedded information gathered from a geographic information system (GIS). After reviewing the GIS, the decision variables and parameters are estimated using spatial analysis. These variables and parameters are utilized during mathematical problem-based analysis stage. While a number of existing algorithms have been proposed, this study applies a hybrid metaheuristic algorithm integrating particle swarm optimization (PSO) and genetic algorithm (GA). Using the proposed method, a more realistic mathematical model is established and solved for accurate analysis of logistics performance. To demonstrate the effectiveness of the proposed method, Korea Post distribution centers were considered in South Korea. Through tests with several real-world scenarios, it is proven experimentally that the proposed solution is more effective than existing PSO variations.
    Schlagwörter logistics centers location ; spatial analysis ; geographic information system ; hybrid metaheuristics ; particle swarm optimization ; genetic algorithm ; Geography (General) ; G1-922
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2022-12-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: Lifestyle Experiences

    Yoojin Han / Hyunsoo Lee

    Sustainability, Vol 13, Iss 5, p

    Exploring Key Attributes of Lifestyle Hotels Using Instagram User-Created Contents in South Korea

    2021  Band 2591

    Abstract: This study aims to investigate the key attributes of a steadily growing hotel sector (lifestyle hotels), which has shown great success in the global competitive market, by analyzing user-created content on Instagram. The dataset used in this study were ... ...

    Abstract This study aims to investigate the key attributes of a steadily growing hotel sector (lifestyle hotels), which has shown great success in the global competitive market, by analyzing user-created content on Instagram. The dataset used in this study were prepared from a total of 20,999 lifestyle hotel posts and 24,262 boutique hotel posts created from 2013 to 2020 and retrieved using a Python web crawler. The locations, hashtags, and image data were analyzed based on frequency analysis using social network analysis methods and computer vision technology, after which they were visualized with a geographical information system and Gephi. The results demonstrated that lifestyle hotels share key attributes that differentiate them from others in terms of physical, geospatial, and experiential contexts. Design, location, and management type are the main attributes that comprise the distinct identity of each lifestyle hotel. Moreover, a lifestyle hotel is distinct from a boutique hotel in that staying in the former means consuming experiences with continuous changes. The information and knowledge gained from this research will contribute to bridging the gap between theoretical literature and the practical development of lifestyle hospitality.
    Schlagwörter user-created content ; big data ; social network analysis ; computer vision ; lifestyle hotel ; hospitality experience ; Environmental effects of industries and plants ; TD194-195 ; Renewable energy sources ; TJ807-830 ; Environmental sciences ; GE1-350
    Thema/Rubrik (Code) 910
    Sprache Englisch
    Erscheinungsdatum 2021-03-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Artikel ; Online: An analysis of the appearance characteristics of Korean ceramics per era through statistical analysis of metadata annotated with a visual element classification system of ceramics

    Ji Hyun Yi / Hyunsoo Lee / Songei Kim

    Heritage Science, Vol 10, Iss 1, Pp 1-

    2022  Band 21

    Abstract: Abstract This study is to create metadata with a ceramic visual element classification system, such as color, form, material, and pattern, and then to analyze the visual characteristics of Korean ceramics by era through this metadata statistical analysis. ...

    Abstract Abstract This study is to create metadata with a ceramic visual element classification system, such as color, form, material, and pattern, and then to analyze the visual characteristics of Korean ceramics by era through this metadata statistical analysis. To achieve this, first, the visual element classification system for ceramics was established. Second, 7,346 ceramic photos were acquired and annotated using the visual element classification system to create metadata. Third, through statistical analysis of the metadata, the preferred visual elements in each era were organized, and their characteristics were analyzed. In particular, the differences in form implementation, color technology, and pattern representation, which vary depending on material properties, were identified. Through this study, the flow of visual elements of Korean ceramics and the reason for each type of appearance and production method could be comprehended more systematically.
    Schlagwörter Korean Ceramics ; Ceramic visual elements classification system ; Ceramic metadata ; Goryeo celadon ; Joseon buncheon ; Joseon white porcelain ; Fine Arts ; N ; Analytical chemistry ; QD71-142
    Thema/Rubrik (Code) 700
    Sprache Englisch
    Erscheinungsdatum 2022-04-01T00:00:00Z
    Verlag SpringerOpen
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Adaptive Human–Machine Evaluation Framework Using Stochastic Gradient Descent-Based Reinforcement Learning for Dynamic Competing Network

    Jinbae Kim / Hyunsoo Lee

    Applied Sciences, Vol 10, Iss 2558, p

    2020  Band 2558

    Abstract: Complex problems require considerable work, extensive computation, and the development of effective solution methods. Recently, physical hardware- and software-based technologies have been utilized to support problem solving with computers. However, ... ...

    Abstract Complex problems require considerable work, extensive computation, and the development of effective solution methods. Recently, physical hardware- and software-based technologies have been utilized to support problem solving with computers. However, problem solving often involves human expertise and guidance. In these cases, accurate human evaluations and diagnoses must be communicated to the system, which should be done using a series of real numbers. In previous studies, only binary numbers have been used for this purpose. Hence, to achieve this objective, this paper proposes a new method of learning complex network topologies that coexist and compete in the same environment and interfere with the learning objectives of the others. Considering the special problem of reinforcement learning in an environment in which multiple network topologies coexist, we propose a policy that properly computes and updates the rewards derived from quantitative human evaluation and computes together with the rewards of the system. The rewards derived from the quantitative human evaluation are designed to be updated quickly and easily in an adaptive manner. Our new framework was applied to a basketball game for validation and demonstrated greater effectiveness than the existing methods.
    Schlagwörter adaptive human evaluation ; dynamic competing network ; reinforcement learning ; stochastic gradient descent ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2020-04-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  8. Artikel ; Online: Dynamic Model for the Epidemiology of Diarrhea and Simulation Considering Multiple Disease Carriers

    Firda Rahmadani / Hyunsoo Lee

    International Journal of Environmental Research and Public Health, Vol 17, Iss 5692, p

    2020  Band 5692

    Abstract: Diarrhea is responsible for killing around 525,000 children every year, even though it is preventable and treatable. This research focuses on both houseflies’ roles and humans’ roles in carrying pathogens causing diarrhea as multiple disease carriers. ... ...

    Abstract Diarrhea is responsible for killing around 525,000 children every year, even though it is preventable and treatable. This research focuses on both houseflies’ roles and humans’ roles in carrying pathogens causing diarrhea as multiple disease carriers. Both human and fly compartmental models are simulated with five diseases control strategies in order to identify the epidemic dynamics. The framework considers the life cycle of flies modeled into eggs, larvae, pupae, susceptible flies, and carrier flies, while the human system follows a compartment model as susceptible, infected, recovered, and back to susceptible again (SIRS). The relationships are modeled into an ordinary differential equation-based compartmental system. Then, the control parameters of the compartmental framework are analyzed. In order to propose effective control methods, five control strategies are considered: (1) elimination of flies’ breeding site, (2) sanitation, (3) installation of UV light trap, (4) good personal and food hygiene, and (5) water purification. Then, overall, ten control scenarios using the five control strategies are analyzed. Among them, effective control solutions considering various dynamic epidemiology are provided with the simulations and analyses. The proposed framework contributes to an effective control strategy in reducing the number of both flies and infected humans, since it minimizes the spread of the disease and considers cost-effectiveness.
    Schlagwörter dynamic epidemiology ; multiple disease carriers ; diarrhea ; infection process-based dynamic control ; Pontryagin’s maximum principle ; Medicine ; R
    Thema/Rubrik (Code) 629
    Sprache Englisch
    Erscheinungsdatum 2020-08-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Artikel ; Online: Hybrid Deep Learning-Based Epidemic Prediction Framework of COVID-19

    Firda Rahmadani / Hyunsoo Lee

    Applied Sciences, Vol 10, Iss 8539, p

    South Korea Case

    2020  Band 8539

    Abstract: The emergence of COVID-19 and the pandemic have changed and devastated every aspect of our lives. Before effective vaccines are widely used, it is important to predict the epidemic patterns of COVID-19. As SARS-CoV-2 is transferred primarily by droplets ... ...

    Abstract The emergence of COVID-19 and the pandemic have changed and devastated every aspect of our lives. Before effective vaccines are widely used, it is important to predict the epidemic patterns of COVID-19. As SARS-CoV-2 is transferred primarily by droplets of infected people, the incorporation of human mobility is crucial in epidemic dynamics models. This study expands the susceptible–exposed–infected–recovered compartment model by considering human mobility among a number of regions. Although the expanded meta-population epidemic model exhibits better performance than general compartment models, it requires a more accurate estimation of the extended modeling parameters. To estimate the parameters of these epidemic models, the meta-population model is incorporated with deep learning models. The combined deep learning model generates more accurate modeling parameters, which are used for epidemic meta-population modeling. In order to demonstrate the effectiveness of the proposed hybrid deep learning framework, COVID-19 data in South Korea were tested, and the forecast of the epidemic patterns was compared with other estimation methods.
    Schlagwörter COVID-19 ; epidemic modeling ; hybrid deep learning ; meta-population model ; human mobility ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Thema/Rubrik (Code) 612
    Sprache Englisch
    Erscheinungsdatum 2020-11-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  10. Artikel ; Online: Cooperative Multi-Agent Interaction and Evaluation Framework Considering Competitive Networks with Dynamic Topology Changes

    Jinbae Kim / Hyunsoo Lee

    Applied Sciences, Vol 10, Iss 5828, p

    2020  Band 5828

    Abstract: In recent years, the problem of reinforcement learning has become increasingly complex, and the computational demands with respect to such processes have increased. Accordingly, various methods for effective learning have been proposed. With the help of ... ...

    Abstract In recent years, the problem of reinforcement learning has become increasingly complex, and the computational demands with respect to such processes have increased. Accordingly, various methods for effective learning have been proposed. With the help of humans, the learning object can learn more accurately and quickly to maximize the reward. However, the rewards calculated by the system and via human intervention (that make up the learning environment) differ and must be used accordingly. In this paper, we propose a framework for learning the problems of competitive network topologies, wherein the environment dynamically changes agent, by computing the rewards via the system and via human evaluation. The proposed method is adaptively updated with the rewards calculated via human evaluation, making it more stable and reducing the penalty incurred while learning. It also ensures learning accuracy, including rewards generated from complex network topology consisting of multiple agents. The proposed framework contributes to fast training process using multi-agent cooperation. By implementing these methods as software programs, this study performs numerical analysis to demonstrate the effectiveness of the adaptive evaluation framework applied to the competitive network problem depicting the dynamic environmental topology changes proposed herein. As per the numerical experiments, the greater is the human intervention, the better is the learning performance with the proposed framework.
    Schlagwörter adaptive algorithm ; competitive network agent ; dynamically changes networks ; human–machine–agent interaction ; reinforcement learning ; Technology ; T ; Engineering (General). Civil engineering (General) ; TA1-2040 ; Biology (General) ; QH301-705.5 ; Physics ; QC1-999 ; Chemistry ; QD1-999
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2020-08-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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