Journal of Korean Society of Industrial and Systems Engineering
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v.33
no.1
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pp.17-23
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2010
The corporate R&D(Research and Development) has a primary role of new product development and its potential is the most crucial factor to estimate corporate future value. However, its systemic inadequacies and inefficiencies, the shorten product life-cycle to satisfy customer needs, the global operations by outsourcing strategy, and the reduction of product cost, are starting to expose to R&D business processes. The three-phased execution strategy for R&D innovation is introduced to establish master plan for new R&D model. From information technology point of view, PLM(Product Life-cycle Management) is one of the business total solutions in product development area. It is not a system, but the strategic business approach that collaboratively manage the product from beginning stage to end of life in all business areas PLM functions and capabilities are usually used as references to re-design new R&D process. BPA(Business Process Assessment) and 5DP(Design Parameters) in PI6sigma developed by Samsung SDS Consulting division are introduced to establish R&D master plan and re-design process respectively. This research provides a case study for R&D process innovation. How process assessment and PMM(Process Maturity Model) can be applied in business processes, and also it explains process re-design by 5DP method.
Kim, Soo-Young;Lee, Sae-Won;You, Sung Yong;Rha, Sun Young;Kim, Kyu-Won
Genomics & Informatics
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v.2
no.1
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pp.36-44
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2004
Astrocytes play supportive roles for neurons in the brain. Recently, they have been accepted to have various functions in the vascular system as well as in the nervous system. We investigated the differential gene expression in rat astrocytes according to the oxygen tension, which is a crucial factor for angiogenesis. A cDNA microarray was performed to find the genes whose expression was sensitive to oxygen tension. We found 26 genes in the astrocyte were found and classified into 4 groups. In order to show the genes' relevancy to angiogenesis, seven of the 26 genes were investigated to see whether they have capabilities of interaction with angiogenesisrelated factors in AngioDB. Through this investigation, we found interactions of three proteins with angiogenesis-related factors. These genes were further investigated with a new focus on the vascular endothelial growth factor (VEGF) expression in an astrocyte based on our hypothesis that astrocytes can have effects on endothelial angiogenesis via the release of VEGF. Collectively, we identified several genes whose expressions were dependent on the oxygen concentration of the astrocyte. Furthermore, the relevancy of astrocytes to angiogenesis was investigated using preexisting information of AngioDB, and suggested a possible signaling pathway for VEGF expression in the aspects of brain endothelial angiogenesis by astrocytes.
Journal of the Korean Society for Aviation and Aeronautics
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v.28
no.4
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pp.176-181
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2020
In the face of the unprecedented crisis of coronavirus disease (COVID-19), the aviation and tourism industry fell without help. The bigger problem is that a crisis like COVID-19 can always come back. A new variant of the virus that is more powerful than COVID-19 may emerge, and another crisis such as a massive war may come. In addition, there may be an unexpected large-scale crisis that could shake the survival of the aviation and tourism industry in place. At that time, the aviation and tourism industry should not be pushed into a survival crisis defenselessly. Taking the experience of the crisis caused by COVID-19 as a crucial lesson, sufficient protection measures should be prepared in advance, and within the protection measures, the overall capabilities of the aviation and tourism industry should be preserved, and preparation should be made for the aftermath of the crisis. There is a need to establish a support system in which financial resources that can be used in crisis situation can be secured in advance, and various support measures can be implemented as effectively as possible by using the secured financial resources. Regarding the preparation for financial resources, various fundraising, insurance, and compensation for losses by the state or local government may be considered as a priority, and in addition, there is a need to continuously consider ways to prepare additional financial resources. On the other hand, in terms of system construction, establishment of the system inside the aviation and tourism industry may need to be considered first, but the improvement of related laws and systems needs to be more actively discussed and related legislation needs to be actively promoted.
In this study, a new recentering friction device (RFD) to retrofit steel moment frame structures is introduced. The device provides both self-centering and energy dissipation capabilities for the retrofitted structure. A hybrid performance-based seismic design procedure considering multiple limit states is proposed for designing the device and the retrofitted structure. The design of the RFD is achieved by modifying the conventional performance-based seismic design (PBSD) procedure using computational intelligence techniques, namely, genetic algorithm (GA) and artificial neural network (ANN). Numerous nonlinear time-history response analyses (NLTHAs) are conducted on multi-degree of freedom (MDOF) and single-degree of freedom (SDOF) systems to train and validate the ANN to achieve high prediction accuracy. The proposed procedure and the new RFD are assessed using 2D and 3D models globally and locally. Globally, the effectiveness of the proposed device is assessed by conducting NLTHAs to check the maximum inter-story drift ratio (MIDR). Seismic fragilities of the retrofitted models are investigated by constructing fragility curves of the models for different limit states. After that, seismic life cycle cost (LCC) is estimated for the models with and without the retrofit. Locally, the stress concentration at the contact point of the RFD and the existing steel frame is checked being within acceptable limits using finite element modeling (FEM). The RFD showed its effectiveness in minimizing MIDR and eliminating residual drift for low to mid-rise steel frames models tested. GA and ANN proved to be crucial integrated parts in the modified PBSD to achieve the required seismic performance at different limit states with reasonable computational cost. ANN showed a very high prediction accuracy for transformation between MDOF and SDOF systems. Also, the proposed retrofit showed its efficiency in enhancing the seismic fragility and reducing the LCC significantly compared to the un-retrofitted models.
P Mary Rajaitha;Runia Jana;Sugato Hajra;Swati Panda;Hoe Joon Kim
Journal of Sensor Science and Technology
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v.32
no.3
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pp.131-139
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2023
Ascorbic acid plays a crucial role in the regulation of neurotransmitters and enzymes in the central nervous system. Maintaining an optimal level of ascorbic acid, which is between 0.6-2 mg/dL, is vital for preventing oxidative stress and associated health conditions, such as cancer, diabetes, and liver disease. Therefore, the detection of ascorbic acid is of the utmost importance. Electrochemical sensing has gained significant attention among the various detection methods, owing to its simplicity, speed, affordability, high selectivity, and real-time analysis capabilities. However, conventional electrodes have poor signal response, which has led to the development of modified electrodes with better signal response and selectivity. Carbon nanotubes (CNTs) and their composites have emerged as promising materials for the electrochemical detection of ascorbic acid. CNTs possess unique mechanical, electrical, and chemical properties that depend on their structure, and their large surface area and excellent electron transport properties make them ideal candidates for electrochemical sensing. Recently, various CNT composites with different materials and nanoparticles have been studied to enhance the electrochemical detection of ascorbic acid. Therefore, this review aims to highlight the significance of CNTs and their composites for improving the sensitivity and selectivity of ascorbic acid detection. Specifically, it focuses on the use of CNTs and their composites in electrochemical sensing to revolutionize the detection of ascorbic acid and contribute to the prevention of oxidative stress-related health conditions. The potential benefits of this technology make it a promising area for future research and development.
The Journal of the Convergence on Culture Technology
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v.9
no.3
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pp.159-166
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2023
Humanities are as crucial as the technology itself in the intelligent information society. Human-centered convergence information technology (IT), which reflects emotional and human nature, can be considered a unique technology with an optimistic outlook in the unpredictable future. Based on this research background, this paper proposed an education model that can improve the IT humanities capabilities of various learners, including elementary and secondary students, prospective teachers, incumbent teachers, school managers, and the general public, through analysis of previous studies on convergence education models. Furthermore, the practical aspects of the proposed model were closely examined so that the proposed education model could be stably incorporated and utilized in the educational field. There are seven strategies for implementing the education model proposed in this paper, including research on textbooks, teaching and learning materials, activation of research results, maker space creation, global joint research, online education operation, developing living lab governance, and diversification of self-sustaining platforms for sustainable and practical education. In the future, validity verification through expert Delphi is required as a follow-up study.
Reading postmodern texts certainly situates readers in roles different from the ones we have been used to. Recently, postmodern metafiction forms a significant body of children's literature that is intended to challenge and transform the conventions of books in the digital age. While many studies have been done as to how child readers have capabilities to appreciate and interpret postmodern metafiction picture books, few studies on teachers and preservice teachers' reactions are not readily available. The role of teachers and preservice teachers are crucial for child readers to have access to affluent reading resources. This study discusses how preservice teachers read and respond to postmodern metafiction picture books using a deconstructive approach by means of binary opposites. Data was collected with 14 preservice teachers as to their likes/dislikes, reading levels, and reading paths about postmodern metafiction picture books. Expected pedagogical implications for literacy and language education were requested to address in their reading diaries and response papers. With their likes/ dislikes, since binary opposites always imply the hierarchy of power and value, the likes is apparently more valued and appreciated over their dislikes. This differentiated values are discussed in more detail with three recurring themes-Education, Morals and Behavior, and Tradition. With reading levels, there seems to be a gap existing between the authors' implied reader and literary critics' and the preservice teachers' ideal readers for the postmodern metafiction picture books. Although many studies have already revealed young readers' capability of appreciating postmodern metafiction, it depends a lot more on the teachers and preservice teachers whether children's right to have access to affluent literacy resources is respected or not. Preservice teachers' awareness of the potential of postmodern metafiction will work as an initial step to bring and realize the new reading path and new literacies in classrooms. By challenging metanarratives of children's literature, preservice teachers' readings of postmodern picture books reveals potentials to raise different reading paths and develop new literacies and other educational implications.
Hassan, Fahad ul;Le, Tuyen;Le, Chau;Shrestha, K. Joseph
International conference on construction engineering and project management
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2022.06a
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pp.304-311
/
2022
Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.
Ayman Abu Ghazal;Rawand Alakash;Zainab Aljumaili;Ahmed El-Sayed;Hamza Abdel-Rahman
Journal of Radiation Protection and Research
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v.48
no.4
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pp.184-196
/
2023
Background: Radiation protection is crucial in various fields due to the harmful effects of radiation. Shielding is used to reduce radiation exposure, but gamma radiation poses challenges due to its high energy and penetration capabilities. Materials and Methods: This work investigates the radiation shielding properties of polyvinylidene fluoride (PVDF) samples containing different weight fraction of tungsten carbide (WC), tungsten trioxide (WO3), and tungsten disulfide (WS2). Parameters such as the mass attenuation coefficient (MAC), half-value layer (HVL), mean free path (MFP), effective atomic number (Zeff), and macroscopic effective removal cross-section for fast neutrons (ΣR) were calculated using the Phy-X/PSD software. EpiXS simulations were conducted for MAC validation. Results and Discussion: Increasing the weight fraction of the additives resulted in higher MAC values, indicating improved radiation shielding. PVDF-xWC showed the highest percentage increase in MAC values. MFP results indicated that PVDF-0.20WC has the lowest values, suggesting superior shielding properties compared to PVDF-0.20WO3 and PVDF-0.20WS2. PVDF-0.20WC also exhibited the highest Zeff values, while PVDF-0.20WS2 showed a slightly higher increase in Zeff at energies of 0.662 and 1.333 MeV. PVDF-0.20WC has demonstrated the highest ΣR value, indicating effective shielding against fast neutrons, while PVDF-0.20WS2 had the lowest ΣR value. The Monte Carlo N-Particle Transport version 5 (MCNP5) simulations showed that PVDF-xWC attenuates gamma radiation more than pure PVDF, significantly decreasing the dose equivalent rate. Conclusion: Overall, this research provides insights into the radiation shielding properties of PVDF mixtures, with PVDF-xWC showing the most promising results.
Heavy metals, widely present in the environment, have become significant pollutants due to their excessive use in industries and technology. Their non-degradable nature poses a persistent environmental problem, leading to potential acute or chronic poisoning from prolonged exposure. Recent research has focused on separating heavy metals, particularly from industrial and mining sources. Industries such as metal plating, mining operations, tanning, wood and chipboard production, industrial paint and textile manufacturing, as well as oil refining, are major contributors of heavy metals in water sources. Therefore, removing heavy metals from water is crucial, especially for safe water supply in swimming and water sports. Iron oxide nanoparticles have proven to be highly effective adsorbents for water contaminants, and efforts have been made to enhance their efficiency and absorption capabilities through surface modifications. Nanoparticles synthesized using plant extracts can effectively bind with heavy metal ions by modifying the nanoparticle surface with plant components, thereby increasing the efficiency of heavy metal removal. This study focuses on removing lead from industrial wastewater using environmentally friendly, cost-effective iron nanoparticles synthesized with Genovese basil extract. The synthesis of nanoparticles is confirmed through analysis using Transmission Electron Microscope (TEM) and X-ray diffraction, validating their spherical shape and nanometer-scale dimensions. The method used in this study has a low detection limit of 0.031 ppm for measuring lead concentration, making it suitable for ensuring water safety in swimming and water sports.
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