• Title/Summary/Keyword: Comprehensive approach

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Korean Multinational Corporations' Global Expansion Strategies in Manufacturing Sector: Mother Factory Approach

  • Yong Ho Shin
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.1
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    • pp.269-279
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    • 2024
  • The study explores the evolving landscape of overseas expansion strategies by Korean corporations, focusing on recent geopolitical tensions, the COVID-19 pandemic, and disruptions in global supply chains. It emphasizes the challenges faced by industries producing high-value products and delves into the concept of "Friend-Shoring" policies in the United States, leading major Korean companies to invest in local semiconductor, battery, and automotive factories. Recognizing the potential fragmentation of Korea's manufacturing sector, the paper introduces the "Mother Factory" strategy as a policy initiative, inspired by Japan's model, to establish core production facilities domestically. The discussion unfolds by examining the cases of major companies in Japan and the United States, highlighting the need for Korea to adopt a mother factory strategy to mitigate risks associated with friend-shoring policies. Inspired by Intel's "Copy Exactly" approach, the paper proposes a Korean mother factory model integrating smart factory technology and digital twin systems. This strategic shift aims to enhance responsiveness to geopolitical challenges and fortify the competitiveness of Korean high-tech industries. Finally, the paper proposes a Korean Mother Factory based on smart factory concepts. The suggested model integrates smart factory technology and digital twin frameworks to enhance responsiveness and fortify competitiveness. In conclusion, the paper advocates for the adoption of a comprehensive Korean Mother Factory model to address contemporary challenges, foster advanced manufacturing, and ensure the sustainability and competitiveness of Korean high-tech industries in the global landscape. The proposed strategy aligns with the evolving dynamics of the manufacturing sector and emphasizes technological advancements, collaboration, and strategic realignment.

Multi-objective structural optimization of spatial steel frames with column orientation and bracing system as design variables

  • Claudio H. B. de Resende;Luiz F. Martha;Afonso C. C. Lemonge;Patricia H. Hallak;Jose P. G. Carvalho;Julia C. Motta
    • Advances in Computational Design
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    • v.8 no.4
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    • pp.327-351
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    • 2023
  • This article explores how multi-objective optimization techniques can be used to design cost-effective and structurally optimal spatial steel structures, highlighting that optimizing performance can be as important as minimizing costs in real-world engineering problems. The study includes the minimization of maximum horizontal displacement, the maximization of the first natural frequency of vibration, the maximization of the critical load factor concerning the first global buckling mode of the structure, and weight minimization as the objectives. Additionally, it outlines a systematic approach to selecting the best design by employing four different evolutionary algorithms based on differential evolution and a multi-criteria decision-making methodology. The paper's contribution lies in its comprehensive consideration of multiple conflicting objectives and its novel approach to simultaneous consideration of bracing system, column orientation, and commercial profiles as design variables.

Research on the educational management model for the interplay of structural damage in buildings and tunnels based on numerical solutions

  • Xiuzhi Wei;Zhen Ma;Jingtao Man;Seyyed Rohollah Taghaodi;H. Xiang
    • Geomechanics and Engineering
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    • v.37 no.1
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    • pp.21-29
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    • 2024
  • The effective management of damage in tunnels is crucial for ensuring their safety, longevity, and operational efficiency. In this paper, we propose an educational management model tailored specifically for addressing damage in tunnels, utilizing numerical solution techniques. By leveraging advanced computational methods, we aim to develop a comprehensive understanding of the factors contributing to tunnel damage and to establish proactive measures for mitigation and repair. The proposed model integrates principles of tunnel engineering, structural mechanics, and numerical analysis to facilitate a systematic approach to damage assessment, diagnosis, and management. Through the application of numerical solution techniques, such as finite element analysis, we demonstrate the efficacy of the proposed model in simulating various damage scenarios and predicting their impact on tunnel performance. Additionally, the educational component of the model provides valuable insights and training opportunities for tunnel management personnel, empowering them to make informed decisions and implement effective strategies for ensuring the structural integrity and safety of tunnel infrastructure. Overall, the proposed educational management model represents a significant advancement in tunnel management practices, offering a proactive and knowledge-driven approach to addressing damage and enhancing the resilience of tunnel systems.

Using Support Vector Machine to Predict Political Affiliations on Twitter: Machine Learning approach

  • Muhammad Javed;Kiran Hanif;Arslan Ali Raza;Syeda Maryum Batool;Syed Muhammad Ali Haider
    • International Journal of Computer Science & Network Security
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    • v.24 no.5
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    • pp.217-223
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    • 2024
  • The current study aimed to evaluate the effectiveness of using Support Vector Machine (SVM) for political affiliation classification. The system was designed to analyze the political tweets collected from Twitter and classify them as positive, negative, and neutral. The performance analysis of the SVM classifier was based on the calculation of metrics such as accuracy, precision, recall, and f1-score. The results showed that the classifier had high accuracy and f1-score, indicating its effectiveness in classifying the political tweets. The implementation of SVM in this study is based on the principle of Structural Risk Minimization (SRM), which endeavors to identify the maximum margin hyperplane between two classes of data. The results indicate that SVM can be a reliable classification approach for the analysis of political affiliations, possessing the capability to accurately categorize both linear and non-linear information using linear, polynomial or radial basis kernels. This paper provides a comprehensive overview of using SVM for political affiliation analysis and highlights the importance of using accurate classification methods in the field of political analysis.

Developing an Integrated Acupuncture Protocol for Treating Medial Tibial Stress Syndrome: A Delphi Consensus Study

  • Pradeep M.K. Nair;Gita Sharma;Deepika Singh;Mamta Jagwani;Anu Alias;Hassan Kodandarama Gurudatta;Radhakrishnan Shubha;Sreedhar Pulipatti;Nagaraja Nagajyothi;Anjali Sharma;Janak Bahadur Basnet;Kalpana Devi;Karuppaiah Muthukrishnan;Kajal Gupta
    • Journal of Acupuncture Research
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    • v.41
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    • pp.160-167
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    • 2024
  • The present study employs the Delphi method to devise a consensus-based protocol for utilizing integrated acupuncture in treating medial tibial stress syndrome (MTSS). Twenty acupuncture experts contributed opinions across six key themes, including diagnosis, acupuncture points, additional Traditional Oriental Medicine modalities, treatment rationale, treatment duration/frequency, and integration of yoga/naturopathic therapies. Consensus, defined as a 70% agreement or higher, was reached on all themes, reflecting a collective acknowledgment of the necessity for a holistic approach to MTSS management. The final protocol includes six diagnostic criteria, six acupuncture points, one additional modality, two Traditional Oriental Medicine therapies, four treatment rationales, and six yoga/naturopathic therapies. The present comprehensive protocol offers valuable guidance for healthcare professionals seeking an integrated approach to MTSS management.

Ultrasound Imaging in Active Surveillance of Small, Low-Risk Papillary Thyroid Cancer

  • Sangeet Ghai;David P Goldstein;Anna M Sawka
    • Korean Journal of Radiology
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    • v.25 no.8
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    • pp.749-755
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    • 2024
  • The recent surge in the incidence of small papillary thyroid cancers (PTCs) has been linked to the widespread use of ultrasonography, thereby prompting concerns regarding overdiagnosis. Active surveillance (AS) has emerged as a less invasive alternative management strategy for low-risk PTCs, especially for PTCs measuring ≤1 cm in maximal diameter. Recent studies report low disease progression rates of low-risk PTCs ≤1 cm under AS. Ongoing research is currently exploring the feasibility of AS for larger PTCs (<20 mm). AS protocols include meticulous ultrasound assessment, emphasis on standardized techniques, and a multidisciplinary approach; they involve monitoring the nodules for size, growth, potential extrathyroidal extension, proximity to the trachea and recurrent laryngeal nerve, and potential cervical nodal metastases. The criteria for progression, often defined as an increase in the maximum diameter of the PTC, warrant a review of precision and ongoing examinations. Challenges exist regarding the reliability of volume measurements for defining PTC disease progression. Although ultrasonography plays a pivotal role, challenges in assessing progression and minor extrathyroidal extension underscore the importance of a multidisciplinary approach in disease management. This comprehensive overview highlights the evolving landscape of AS for PTCs, emphasizing the need for standardized protocols, meticulous assessments, and ongoing research to inform decision-making.

Evidence-based Approach for Prevention of Surgical Site Infection

  • Mehmet Kursat Yilmaz;Nursanem Celik;Saad Tarabichi;Ahmad Abbaszadeh;Javad Parvizi
    • Hip & pelvis
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    • v.36 no.3
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    • pp.161-167
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    • 2024
  • Periprosthetic joint infection (PJI) is regarded as a critical factor contributing to the failure of primary and revision total joint arthroplasty (TJA). With the increasing prevalence of TJA, a significant increase in the incidence of PJI is expected. The escalating number of cases, along with the significant economic strain imposed on healthcare systems, place emphasis on the pressing need for development of effective strategies for prevention. PJI not only affects patient outcomes but also increases mortality rates, thus its prevention is a matter of vital importance. The longer-term survival rates for PJI after total hip and knee arthroplasty correspond with or are lower than those for prevalent cancers in older adults while exceeding those for other types of cancers. Because of the multifaceted nature of infection risk, a collaborative effort among healthcare professionals is essential to implementing diverse strategies for prevention. Rigorous validation of the efficacy of emerging novel preventive techniques will be required. The combined application of these strategies can minimize the risk of infection, thus their comprehensive adoption is important. Collectively, the risk of PJI could be substantially minimized by application of a multifaceted approach implementing these strategies, leading to improvement of patient outcomes and a reduced economic burden.

The Impact of Importance of Online Platform Food Delivery Selection Attributes on Satisfaction and Repurchase Intention

  • Bo-Kyung SEO;Seunghyeon LEE;Seong Soo CHA
    • The Korean Journal of Food & Health Convergence
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    • v.10 no.4
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    • pp.9-19
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    • 2024
  • This qualitative study explores the impact of online food delivery platform attributes on customer satisfaction and repurchase intentions. Employing a phenomenological approach, we conducted in-depth interviews and focus group discussions with 15 participants to gain rich insights into user experiences. Thematic analysis revealed key factors influencing satisfaction and loyalty: service quality dimensions (efficiency, reliability, fulfillment, privacy), expectation disconfirmation, perceived usefulness and ease of use, multi-level customer value, relationship quality, electronic word-of-mouth, value co-creation, and phased loyalty formation. Our findings extend customer behavior theory in digital platforms, offering a comprehensive framework for understanding the complex mechanisms underlying user satisfaction and repurchase decisions. The study provides valuable implications for platform operators, highlighting the importance of exceeding customer expectations, enhancing user experience, building trust, leveraging user-generated content, and fostering co-creation processes. Methodologically, we demonstrate the efficacy of qualitative approaches in uncovering nuanced insights in digital service contexts. While acknowledging limitations in generalizability, this research establishes a solid foundation for future investigations into the rapidly evolving domain of online food delivery services. The integrated theoretical approach offers a robust model for analyzing customer behavior in emerging digital service environments, contributing significantly to both academic understanding and practical application in the field of digital service provision and platform management.

Extended cognitive reliability and error analysis method for advanced control rooms of nuclear power plants

  • Xiaodan Zhang;Shengyuan Yan;Xin Liu
    • Nuclear Engineering and Technology
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    • v.56 no.9
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    • pp.3472-3482
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    • 2024
  • This study proposes a modified extended cognitive reliability and error analysis method (CREAM) for achieving a more accurate human error probability (HEP) in advanced control rooms. The traditional approach lacks failure data and does not consider the common performance condition (CPC) weights in different cognitive functions. The modified extended CREAM decomposes tasks using a method that combines structured information analysis (SIA) and the extended CREAM. The modified extended CREAM performs the weight analysis of CPCs in different cognitive functions, and the weights include cognitive, correlative, and important weights. We used the extended CREAM to obtain the cognitive weight. We determined the correlative weights of the CPCs for different cognitive functions using the triangular fuzzy decision-making trial and evaluation laboratory (TF-DEMATEL), and evaluated the importance weight of CPCs based on the interval 2-tuple linguistic approach and ensured the value of the importance weight using the entropy method in the different cognitive functions. Finally, we obtained the comprehensive weights of the different cognitive functions and calculated the HEPs. The accuracy and sensitivity of the modified extended CREAM were compared with those of the basic CREAM. The results demonstrate that the modified extended CREAM calculates the HEP more effectively in advanced control rooms.

Reactor core design with practical gadolinia burnable absorbers for soluble boron-free operation in the innovative SMR

  • Jin Sun Kim;Tae Sik Jung;Jooil Yoon
    • Nuclear Engineering and Technology
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    • v.56 no.8
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    • pp.3144-3154
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    • 2024
  • The development of soluble boron-free (SBF) operation in the innovative Small Modular Reactor (i-SMR) requires effective strategies for managing excess reactivity over extended operational cycles. This paper introduces a practical approach to reactor core design for SBF operation in i-SMR, emphasizing the use of gadolinia burnable absorbers (BA). The study investigates the feasibility of Highly Intensive and Discrete Gadolinia/Alumina Burnable Absorber (HIGA) rods for controlling excess reactivity sustainably. Through comprehensive analysis and simulations, the reactivity behavior with varying quantities of HIGA rods is examined, leading to the development of optimized fuel assembly designs. Furthermore, the integration of HIGA rods with integral gadolinia BA rods is discussed to enhance reactivity control and operational flexibility further. This approach utilizes the spatial self-shielding effect of gadolinia for extended reactivity management, crucial for stable and efficient reactor performance. The paper thoroughly addresses core design considerations, including fuel assembly configurations and control rod patterns, to ensure safety and performance in initial and reload cycles. This research advances the development of SBF operation in i-SMR by offering practical reactivity management solutions.