Purpose: This study aimed to identify and evaluate interprofessional education (IPE) interventions for healthcare professional students in East Asian countries. Methods: The reporting of this study followed the Preferred Reporting Items of Systematic Reviews and Meta-Analysis guidelines. A literature search was conducted using seven electronic databases: PubMed, EMBASE, CINAHL, Scopus, Web of Science, ERIC, and ProQuest Dissertations & Theses Global. Joanna Briggs Institute Critical Appraisal Checklists were also used to appraise the quality of the included studies. The outcomes of IPE interventions were classified based on a modified Kirkpatrick model. Results: This review included 30 studies predominantly conducted in Singapore, South Korea, and Taiwan. The prevalent research design was a one-group pre-posttest design, and most IPE interventions occurred as single events. Approximately 70% of the studies involved students from two healthcare professions, mainly nursing and medicine. Simulations, group discussions, and lectures have emerged as the most common teaching methodologies, with almost half of the studies leveraging a combination of these techniques. The IPE content primarily focused on interprofessional teamwork, communication, and clinical patient care situations; these included the management of septic shock. The effectiveness of the IPE interventions was mainly evaluated through self-reported measures, indicating improvements in attitudes, perceptions, knowledge, and skills, aligning with Level 2 of the modified Kirkpatrick model. Nonetheless, the reviewed studies did not assess changes in the participants' behavior and patient results. Conclusion: IPE interventions promise to enhance interprofessional collaboration and communication skills among health professional students. Future studies should implement rigorous designs to assess the effectiveness of IPE interventions. Moreover, when designing IPE interventions, researchers and educators should consider the role of cultural characteristics in East Asian countries.
To grasp the structure of an industry and monitor its changes, it is essential to utilize relevant statistics. Various statistics are being compiled regarding the software (SW) industry, presenting diverse numerical values. However, without a precise understanding of the scope and measurement methods inherent to each statistic, gaining a rigorous understanding of the industry's structure and evolving trends becomes challenging. Moreover, significant discrepancies between similar statistics often lead to confusion among users. In the software (SW) industry, key statistics commonly used include SW production value and SW market size. As of 2022, the annual domestic SW production value is reported as 77.4 trillion KRW (based on ICT Survey), while the SW market size for the same year is stated as 38.5 trillion KRW (according to IDC data). Although production value and market size may seem conceptually similar, there is approximately a twofold difference between the figures provided. Without understanding the meanings of each statistic and the differences between them, there are limitations in utilizing these statistics effectively. While statistics are utilized for various purposes such as policy development or causal analysis of policy using statistical raw data, research that presents and analyzes the precise meanings and limitations of each SW-related statistic is virtually non-existent. Thus, this study aims to compare and analyze the methodologies and differences among key statistics used to represent the SW industry: SW production value, SW market size, and SW GDP statistics. Through this analysis, the goal is to contribute to a better understanding of the SW industry's structure and enable more accurate and rigorous utilization of relevant statistics.
International Journal of Naval Architecture and Ocean Engineering
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제13권1호
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pp.405-430
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2021
Production planning is a key part of production management of manufacturing enterprises. Since computerization began, modern production planning has been developed starting with Material Requirement Planning (MRP), and today Enterprise Resource Planning (ERP), Advanced Planning and Scheduling (APS), Supply Chain Management (SCM) has been spreading and advanced. However, in the shipbuilding field, rather than applying these general-purpose production planning methodologies, in most cases, each shipyard has developed its own production planning system. This is because the applications of general-purpose production planning methods are limited due to the order-taking industry such as shipbuilding with highly complicated construction process consisting of millions of parts per ship. This study introduces the design and development of the production planning system reflecting the production environment of heavy shipyards in Korea. Since Korean shipyards such as Hyundai, Daewoo and Samsung build more than 10 ships per year (50-70 ships in the case of large shipyards), a planning system for the mixed production with complex construction processes is required. This study draws requirements using PI/BPR (process innovation and business process reengineering) methodology to develop a production planning system for shipyards that simultaneously build several ships. Then, CBD software development methodology was applied for the design and implementation of planning system with drawn requirements. It is expected that the systematic development procedure as well as the requirements and functional elements for the development of the shipyard production planning system introduced in this study will be able to present important guidelines in the related research field of shipbuilding management.
PURPOSES : The current practice in car headlight visibility performance evaluation is based on the luminous intensity and illuminance of headlight. Such practice can be inappropriate from a visibility point of view where visibility indicates abilities to perceive an object ahead on the road. This study aimed at evaluating the appropriateness of current headlight evaluation method. METHODS : This study measured the luminance of object and road surface at unlit roadways. The variables were measured by vehicle type and by headlight lamp type. Based on the measurements, the distance where drivers can perceive an object ahead was calculated and then compared against such distance obtained by conventional visibility performance evaluation. RESULTS : The evaluation method based on illuminance of headlight is not appropriate when viewed from the visibility concept that is based on object-perceivable distance. Further, the results indicated a shorter object-perceiving distance even when road surface luminance is higher, thereby suggesting that illuminance of headlight and luminance of road surface are not the representative indices of nighttime visibility. CONCLUSIONS : Considering that this study utilized limited vehicle types and that road surface (background) luminance can vary depending on the characteristics of the given road surface, it would likely go too far to argue that this study's visibility performance evaluation results can get generalized to other conditions. Regardless, there is little doubt that the current performance evaluation criterion which is based on illuminance, is unreasonable. There should be future endeavors on the current subject which will need to explore study conditions further, under which more experiments should be conducted and effective methodologies developed for evaluating automotive headlight visibility performance. Needs are recognized particularly in the development of headlight visibility performance evaluation methodology which will take into account road surface (background) luminance and luminance contrast from various perspectives as the former indicates the driver's perception of the front road alignment and the latter being indicative of object perception performance.
Lee, Mi Hye;Choi, Won Jung;Seo, Seok-Jun;Kim, Bum Sung
Journal of Powder Materials
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제23권4호
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pp.325-330
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2016
Owing to increasing demand of rare metals present in ICT products, it is necessary to promote the rare metal recycling industry from an environmental viewpoint and to prevent climate change. Despite the fact that information for toxic substances is partly indicated, a legal basis and an international standard indicating usage of rare metals is insufficient. In order to address this issue, a newly created study group of environment and climate change at the ITU (International Telecommunication Union) is doing research to develop methodologies for recycling rare metals from ICT products in an eco-friendly way. Under this group, the Republic of Korea has established two international standards related to rare metals present in ICT products. The first is 'Release of rare metal information for ICT products (ITU-T L.1100)' and the other is 'Quantitative and qualitative analysis methods for rare metals (ITU-T L.1101)'. A new proposal for recommending the provision of rare metal information through a label by manufacturers and consumer/recycling businesses has been approved recently and is supposed to be published later in 2016. Moreover, these recommendations are also being extended to IEC, ISO and other standardization organizations and a strategy to reinforce the ability for domestic standardization is being established in accordance with industrial requirements. This will promote efficient recycling of rare metals from ICT products and will help improve the domestic supply of rare metals.
Deep learning applications are increasingly being leveraged for disease detection tasks in medical imaging modalities such as X-ray, Computed Tomography (CT), and Magnetic Resonance Imaging (MRI). Most data-centric deep learning challenges necessitate the use of supervised learning methodologies to attain high accuracy and to facilitate performance evaluation through comparison with the ground truth. Supervised learning mandates a substantial amount of image and label sets, however, procuring an adequate volume of medical imaging data for training is a formidable task. Various data augmentation strategies can mitigate the underfitting issue inherent in supervised learning-based models that are trained on limited medical image and label sets. This research investigates the enhancement of a deep learning-based rib fracture segmentation model and the efficacy of data augmentation techniques such as left-right flipping, rotation, and scaling. Augmented dataset with L/R flipping and rotations(30°, 60°) increased model performance, however, dataset with rotation(90°) and ⨯0.5 rescaling decreased model performance. This indicates the usage of appropriate data augmentation methods depending on datasets and tasks.
This review paper investigates the use of shockwave attenuating materials within composite structures to enhance personnel protection against blast-induced traumatic brain injury (bTBI). This paper also introduces experimental methodologies exploited in the generation and measurement of shockwaves to evaluate the performance of the shock dissipating composites. The generation of shockwaves is elucidated through diverse approaches such as high-energy explosives, shock tubes, lasers, and laser-flyer techniques. Evaluation of shockwave propagation and attenuation involves the utilization of cutting-edge techniques, including piezoelectric, interferometer, electromagnetic induction, and streak camera methods. This paper investigates phase-separated materials, including polyurea and ionic liquids, and provides insight into composite structures in the quest for shockwave pressure attenuation. By synthesizing and analyzing the findings from these experimental approaches, this review aims to contribute valuable insights to the advancement of protective measures against blast-induced traumatic brain injuries.
Since a government design department office was set up in 2007, active design projects have been implemented. With this opportunity, each local self-governing organization has improved its administration and institutions, and are planning intensive research on public design for efficient execution of public design projects. However, recent public design projects have caused many problems due to unspecialized design processes, a lack of cooperation with relevant organizations, and unsatisfactory management systems after projects. Therefore, to overcome such problems in the execution of public design projects, a procedure-centered model should be developed. This study aims to analyse the process structures for the strategic execution of public design projects, and the methods and content of the execution process. For this purpose, this study looked into the process structures of public design projects based on design management strategies in order to draw suggestions needed for the execution process through advanced cases. The study is summed up as follows: First, when the process of public design projects was examined in terms of management strategies and design management strategies, it included two dimensions: the management structure of general projects and the design of development projects. Secondly, through the analysis of public design cases, this study discovered useful methodologies and the main programs used and drew suggestions needed for each step in public design projects. It is expected that the results of this study will be helpful for the development of a process model appropriate for national public design projects based on the current status of the project execution and to make a contribution to systematic development in national public design.
Research on how to develop information systems efficiently and effectively since early 1960s has resulted in many techniques, methods and methodologies. Only a few of them, however, have been successfully practiced in the field. Model-Driven Development(MDD) is an innovative approach emphasizing the central role of model for development activities, attracting many practitioners' attention as well as researchers'. As MDD matures, many researchers have been trying to establish the evidence of its effectiveness. But many of them only suggest lessons learned or report limited evidence of effectiveness based on isolated case studies. This paper reports the state of the art of Model-Driven Engineering(MDE) and its major issues. We reviewed a number of papers and collected the conceptual definitions of MDE effectiveness from the technological and organizational perspectives. A case study in which MDD technology was adopted has been performed in order to measure the effectiveness of MDD quantitatively and qualitatively. This paper also analyzes and summarizes key considerations and lessons learned for IT organizations to adopt MDE successfully from the case study.
Objectives: Improving public capability to obtain, understand, and use health information is important for decision-making and communication. This study attempts to measure adults' literacy of the information provided by a public health institution. Factors affecting different health literacy level are also investigated. The relation between public risk perception and health literacy is examined as well. Methods: A total of 800 korean adults were surveyed. To provide the participants health literacy questions, health messages of heavy metals released by KFDA as well as literacy questions developed by NIKL were used. A total of eight questions were developed to measure health literacy. The dimensions of risk perception proposed by Brewer et al.(2008) were modified to measure risk perception. Results: The average percentage of correct answer for all literacy questions was only 65.57%. Individuals at the older age, and with lower education/ income level were more likely to be low literate. In addition, health literacy was strongly associated with risk perception. Conclusions: Public literacy of health information is influenced by socio demographic factors. This study suggested a possibility that low health literacy may affect unrealistically high risk perception. Further studies with sophisticated methodologies to measure health literacy need to be developed.
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