• Advances in nano research
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• 제16권4호
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• pp.365-374
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• 2024

This study delves into the significant impact of integrating nanomaterials, specifically carbon and graphene nanoparticles, into the polymer matrix of aluminum alloy 356, utilizing the vortex casting technique, with the aim of improving the mechanical properties of table tennis equipment. Athletes and their coaching teams have long been on a quest for high-performance sports gear, recognizing its pivotal role in unlocking the full potential of players. The dedication of engineers to craft designs, select materials with precision, and uphold stringent testing standards reflects the commitment to meeting the demands of the sporting world. Yet, to remain at the forefront, sports engineering must continually align with contemporary technologies, and nanotechnology has emerged as a transformative force in this regard. This study not only underscores the meticulous efforts in material integration but also highlights the remarkable strides made possible by nanotechnology. Aluminum nanocomposites, particularly, showcase a groundbreaking fusion of exceptional strength and reduced weight, marking a notable achievement in sports equipment innovation. The research outcomes are compelling, revealing a substantial enhancement in the mechanical performance of the sports structures under scrutiny. This promising development hints at a potential paradigm shift in the manufacturing of sports equipment, promising a new era of elevated athlete performance and enhanced safety during the rigors of physical education training. This study stands as a testament to the tangible impact of nanotechnology on the ever-evolving landscape of sports equipment.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.148-153
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• 2024

This article embarks on an exploration of how the burgeoning landscape of AI technology is reshaping and augmenting creative expression within the realm of 3D animation. As AI continues to evolve and mature, its integration into the process of 3D animation creation has become an increasingly focal point of investigation and analysis. The article undertakes a comprehensive examination of the myriad applications of AI within the domain of 3D animation, shedding light on its multifaceted contributions to various aspects of the creative process. Furthermore, it delves into the transformative impact that AI technology has on enhancing creative expression within 3D animation, particularly through increased productivity, personalized content creation, and the expansion of creative boundaries. By automating repetitive and time-consuming tasks inherent in traditional production methods, AI liberates artists and animators to unleash their creative ingenuity and push the boundaries of their craft. Through empirical research and case studies, the article elucidates how AI serves as a catalyst for innovation, fostering a conducive environment for the exploration of novel techniques and artistic styles.

• 한국IT서비스학회지
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• 제23권3호
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• pp.39-54
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• 2024

This study explores the barriers to using health and medical data in research and development (R&D) within the healthcare industry and suggests ways to enhance data utilization. As artificial intelligence technology drives transformative changes across industries, there is an increased demand for robust health and medical data, highlighting its critical economic value and utility in fostering innovation. Using qualitative analysis through Grounded Theory, the study involves ten R&D professionals from healthcare industry, including both medical centers and corporations, using surveys and in-depth interviews to gather diverse experiences and perspectives on the challenges and opportunities in health and medical data use. Key findings point to legislative, regulatory, and data quality and integration issues, as well as complexities in patient data access and usage. Technological limitations and inadequate data governance frameworks also emerge as significant obstacles. Recommendations focus on improving regulatory frameworks, enhancing data standardization and quality, and fostering stronger partnerships between data custodians and users. The study concludes that overcoming these obstacles requires a comprehensive strategy involving legislative changes, improved technological infrastructure, and increased stakeholder collaboration. Implementing these recommendations could greatly enhance health and medical data utilization in R&D, significantly advancing medical science and patient care services.

• Journal of Microbiology and Biotechnology
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• 제34권5호
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• pp.1003-1016
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• 2024

This study explores the potential of plant-based decellularization in regenerative medicine, a pivotal development in tissue engineering focusing on scaffold development, modification, and vascularization. Plant decellularization involves removing cellular components from plant structures, offering an eco-friendly and cost-effective alternative to traditional scaffold materials. The use of plant-derived polymers is critical, presenting both benefits and challenges, notably in mechanical properties. Integration of plant vascular networks represents a significant bioengineering breakthrough, aligning with natural design principles. The paper provides an in-depth analysis of development protocols, scaffold fabrication considerations, and illustrative case studies showcasing plant-based decellularization applications. This technique is transformative, offering sustainable scaffold design solutions with readily available plant materials capable of forming perfusable structures. Ongoing research aims to refine protocols, assess long-term implications, and adapt the process for clinical use, indicating a path toward widespread adoption. Plant-based decellularization holds promise for regenerative medicine, bridging biological sciences with engineering through eco-friendly approaches. Future perspectives include protocol optimization, understanding long-term impacts, clinical scalability, addressing mechanical limitations, fostering collaboration, exploring new research areas, and enhancing education. Collectively, these efforts envision a regenerative future where nature and scientific innovation converge to create sustainable solutions, offering hope for generations to come.

• 지식경영연구
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• 제17권3호
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• pp.65-91
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• 2016

Although the success of industrial clusters largely depends on whether clustering firms can achieve economic performance, there has been less attention on investigating factors and conditions contributing to the performance enhancement for clustering small and medium-sized enterprises (SMEs). Along this vein, we adopt the theories of social capital and organizational learning as those success factors for clustering SMEs. This study thus aims at examining what effect social capital accrued in the relationships among actors within clusters has on firm performance of clustering SMEs and what role organizational learning plays in the linkage between social capital and firm performance. For the empirical analysis, we operationalized the variables and their measures to develop questionnaires through the theoretical reviews on literatures. As a sample of 227 clustering SMEs, our collected data was analyzed by hierarchical regression analysis. The results confirmed that a high level of social capital, represented by network, trust, and norm, has positive effect on firm performance of clustering SMEs. We also found that clustering firms presenting high organizational learning, represented by absorptive and transformative capability, achieve better performance than those placing less value on organizational learning. Furthermore the significant relationship between social capital and firm performance is mediated partially through organizational learning. These findings imply not only that the territorial agglomeration of industrial cluster does not guarantee the performance creation of clustering SMEs but that they need to develop social capital among various actors within clusters, facilitating their knowledge diffusion. In order to absorb and mobilize the shared knowledge and information into strategic resources, the firms should improve their capability associated with organizational learning. These expand our understanding on the importance of social capital and organizational learning for the performance enhancement of clustering firms. Differentiating from major studies addressing benefits and advantages of industrial cluster, this study based on the perspective of firm-internal business process contributes to the literature advancement. Strategic and policy implications of this study are discussed in detail.

• 산업진흥연구
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• 제2권2호
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• pp.45-52
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• 2017

본 연구는 현 품질명장들의 설문조사 분석과 독일의 마이스터제도, 일본 명공제도, 기능명장, 품질명장제도 고찰을 통하여 제도상 문제점을 도출하여, 품질명장제도 개선모형을 설정하였다. 첫째는 품질명장 선발분류 가이드 모형 설정하였으며, 둘째는 경험과 전문 기술이 이론과 접목을 위한 모형을 설정하였고, 셋째는 중소기업 경쟁력강화를 위한 품질명장 활용모형을 설정하였으며, 넷째는 향후 품질명장 되기 위한 기본적 모델을 제시하였다. 이러한 모델이 기대되는 효과로는 지식기반의 경제에서, 우수한 인재를 발굴과 육성 활용측면에서 품질명장은 각 분야에서 학문적 이론과 경험을 접목하여, 핵심적 전문기술과 지식, 최고의 기능 우수한 관리능력 및 참다운 인성보유자로 변혁적인 리더이자 전문가로써, 성과 창출로 기업경쟁력 향상과 후배 지도육성, 그리고 협력업체 지도로 혁신활동의 선봉장이 될 것이며, 중소기업 경쟁력강화를 위해서는 품질명장 정년퇴직 이후에도 제도적 보완으로 인재가 활용되어 중소기업의 기술축척과 배양이 가능 하리라 본다.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.17-25
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• 2023

The alarming global prevalence of Type 2 Diabetes Mellitus (T2DM) has catalyzed an urgent need for robust, early diagnostic methodologies. This study unveils a pioneering approach to predicting T2DM, employing the Extreme Gradient Boosting (XGBoost) algorithm, renowned for its predictive accuracy and computational efficiency. The investigation harnesses a meticulously curated dataset of 4303 samples, extracted from a comprehensive Chinese research study, scrupulously aligned with the World Health Organization's indicators and standards. The dataset encapsulates a multifaceted spectrum of clinical, demographic, and lifestyle attributes. Through an intricate process of hyperparameter optimization, the XGBoost model exhibited an unparalleled best score, elucidating a distinctive combination of parameters such as a learning rate of 0.1, max depth of 3, 150 estimators, and specific colsample strategies. The model's validation accuracy of 0.957, coupled with a sensitivity of 0.9898 and specificity of 0.8897, underlines its robustness in classifying T2DM. A detailed analysis of the confusion matrix further substantiated the model's diagnostic prowess, with an F1-score of 0.9308, illustrating its balanced performance in true positive and negative classifications. The precision and recall metrics provided nuanced insights into the model's ability to minimize false predictions, thereby enhancing its clinical applicability. The research findings not only underline the remarkable efficacy of XGBoost in T2DM prediction but also contribute to the burgeoning field of machine learning applications in personalized healthcare. By elucidating a novel paradigm that accentuates the synergistic integration of multifaceted clinical parameters, this study fosters a promising avenue for precise early detection, risk stratification, and patient-centric intervention in diabetes care. The research serves as a beacon, inspiring further exploration and innovation in leveraging advanced analytical techniques for transformative impacts on predictive diagnostics and chronic disease management.

• Journal of Smart Tourism
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• 제2권1호
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• pp.5-19
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• 2022

Smart tourism is seen as a revolution in the tourism industry, involving innovative and transformative theoretical-practical approaches for the sector. As a result of its application in the tourist context, benefits can be seen such as more sustainable practices, greater mobility and better accessibility in destinations, evolution of processes and experiences of tourists. Much of this is achieved through the support of technological solutions. However, despite the immense expectations, and the many researches carried out on it, a literature summary regarding the dimensions that can be observed in each application of this smart tourism has not yet been proposed. Therefore, supported by the PRISMA recommendation, this research proposed to carry out an integrative review of the literature on smart tourism (in its different levels of application, such as the city, the destination and the smart tourism region), with the objective of mapping the dimensions that underlie it. Thus, from an initial scope of 833 intellectual productions obtained, inputs were found for the dimensions in 363 of them after a thorough analysis. The compilation of data obtained from these productions supported the proposition of 14 operational dimensions of smart tourism, namely: collaboration, technology, sustainability, experience, accessibility, knowledge management, innovation management, human capital, marketing, customized services, transparency, safety, governance and mobility. With this set of dimensions, it is envisaged that the implementation of smart tourism projects can present more comprehensive and assertive results. In addition, shortcomings and opportunities for new research that support the evolution of the theory and practice of smart tourism are highlighted.