• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

• Nuclear Engineering and Technology
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• v.41 no.4
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• pp.391-402
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• 2009

This paper introduces the development of safety assessment technology in Korea, focusing on the activities of the Korea Atomic Energy Research Institute in the areas of system thermal hydraulics, severe accidents and probabilistic safety assessment. In the 1970s and 1980s, safety analysis codes and methodologies were introduced from the United States, France, Canada and other developed countries along with technology related to the construction and operation of nuclear power plants. The main focus was on understanding and utilizing computer codes that were sourced from abroad up to the early 1990s, when efforts to develop domestic safety analysis codes and methodologies became active. Remarkable achievements have been made over the last 15 years in the development and application of safety analysis technologies. In addition, significant experimental work has been performed to verify the safety characteristics of reactors and fuels as well as to support the development and validation of analysis methods.

• Journal of the Korea Convergence Society
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• v.5 no.3
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• pp.45-51
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• 2014

Computer science and computing technologies are applied into mathematical, science, medical, engineering and educational applications. The models are used to solve the issues in all the domains. Educational systems are used top down, bottom up, Gap Analysis model in the educational learning system. Educational learning process integrated with Lerner, content and the methodology. The Learners and content are same in the educational system or similar courses but the teaching methodologies are differing one with another. The determinations of teaching methodologies are based on the factors related to that particular model or subject. The learning model influencing determinations are made by the surveys, analysis and observation of data to maximize the learning outcome. This paper attempted to evaluate the SNE learners cognitive using NASA Scaling.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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• pp.83-89
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• 2017

This study aims to investigate the compatibility between 'quality' and 'R&D' and to ascertain what methodology can be applied. To consider the compatibility, this study discussed whether quality management can expand into R&D area in future and whether the quality management principles in ISO9000 can work well in R&D environment. Our conclusion is that the application of the quality management in R&D is valid and can serve as a new paradigm for improving R&D performance. In addition, this study divided the quality concept in R&D into several types from the viewpoints of quality definition and suggested quality methodologies for each type.

• Electronics and Telecommunications Trends
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• v.36 no.4
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• pp.145-153
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• 2021

Data imputation is a crucial issue in data analysis because quality data are highly correlated with the performance of AI models. Particularly, it is difficult to collect quality time-series data for uncertain situations (for example, electricity blackout, delays for network conditions). Thus, it is necessary to research effective methods of time-series data imputation. Many studies on time-series data imputation can be divided into 5 parts, including statistical based, matrix-based, regression-based, deep learning (RNN and GAN) based methodologies. This study reviews and organizes these methodologies. Recently, deep learning-based imputation methods are developed and show excellent performance. However, it is associated to some computational problems that make it difficult to use in real-time system. Thus, the direction of future work is to develop low computational but high-performance imputation methods for application in the real field.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.307-313
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• 2024

This study explores the integration of Explainable Artificial Intelligence (XAI) and network science in healthcare, focusing on enhancing healthcare data interpretation and improving diagnostic and treatment methods. Key methodologies like Graph Neural Networks, Community Detection, Overlapping Network Models, and Time-Series Network Analysis are examined in depth for their potential in patient health management. The research highlights the transformative role of XAI in making complex AI models transparent and interpretable, essential for accurate, data-driven decision-making in healthcare. Case studies demonstrate the practical application of these methodologies in predicting diseases, understanding drug interactions, and tracking patient health over time. The study concludes with the immense promise of these advancements in healthcare, despite existing challenges, and underscores the need for ongoing research to fully realize the potential of AI in this field.

• International Journal of Stem Cells
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• v.17 no.2
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• pp.130-140
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• 2024

Cardiac organoids have emerged as invaluable tools for assessing the impact of diverse substances on heart function. This report introduces guidelines for general requirements for manufacturing cardiac organoids and conducting cardiac organoid-based assays, encompassing protocols, analytical methodologies, and ethical considerations. In the quest to employ recently developed three-dimensional cardiac organoid models as substitutes for animal testing, it becomes imperative to establish robust criteria for evaluating organoid quality and conducting toxicity assessments. This guideline addresses this need, catering to regulatory requirements, and describes common standards for organoid quality and toxicity assessment methodologies, commensurate with current technological capabilities. While acknowledging the dynamic nature of technological progress and the potential for future comparative studies, this guideline serves as a foundational framework. It offers a comprehensive approach to standardized cardiac organoid testing, ensuring scientific rigor, reproducibility, and ethical integrity in investigations of cardiotoxicity, particularly through the utilization of human pluripotent stem cell-derived cardiac organoids.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.57-66
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• 2022

Claims and disputes are major causes of cost and schedule overruns in the construction business. In order to manage claims and disputes effectively, it is necessary to analyze various types of contract documents punctually and accurately. Since volume of such documents is so vast, analyzing them in a timely manner is practically very challenging. Recently developed approaches such as artificial intelligence (AI), machine learning algorithms, and natural language processing (NLP) have been applied to various topics in the field of construction contract and claim management. Based on the systematic literature review, this paper analyzed the goals, methodologies, and application results of such approaches. AI methods applied to construction contract management are classified into several categories. This study identified possibilities and limitations of the application of such approaches. This study contributes to providing the directions for how such approaches should be applied to contract management for future studies, which will eventually lead to more effective management of claims and disputes.

• Journal of Environmental Policy
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• v.5 no.2
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• pp.69-93
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• 2006

This paper considers major three steps to arrive at accurate baseline emissions against which actual emission reductions attributable to CDM projects are accounted for. The first step is to select most likely baseline scenario among plausible alternatives. Then, the additionality of the project in question would be assessed by demonstrating that the project is not included in the baseline scenario selected. Finally, baseline emissions are calculated under the baseline scenario. In this paper, these three steps are integrated into a single flow chart in order to help understand the procedures for application of a baseline methodology better. Following the flow chart, a landfill gas-to-electricity project in Korea is analyzed as a case study. In consequence, this paper concludes that landfill gas-to-electricity projects in Korea have great potential for CDM projects, and it could also be concluded that data availability and reliability are a prerequisite for successful application of baseline methodologies for landfill gas projects to Korean specific situations.

• Quality Improvement in Health Care
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• v.21 no.1
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• pp.80-95
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• 2015

Objectives : A safety culture is the bedrock for all patient safety improvement initiatives; thus, many resources have been invested in measuring hospital culture. However, many of these endeavors have failed to yield meaningful results. This article proposes a practical checklist to ensure successful administration of a safety culture survey and describes current methodologies for analyzing survey results to develop safety improvement programs. Methods : We reviewed currently used safety culture surveys and summarized their strengths and weaknesses. We also reviewed studies using safety culture surveys and found several pitfalls leading to failure in survey administration. With this information, we developed a checklist that covers critical items in the survey process. We also reviewed newly developed methodologies for survey results analysis and application and described them using the Korean version of the Safety Attitudes Questionnaire as an example. Results : The checklist consists of three steps: survey preparation, administration, and analysis and application. Each step contains clear action items. The content even describes how to get buy-in from hospital executives and manage communication channels with them. Also, common misunderstandings regarding survey scores are described and possible solutions are suggested. In the analysis section, we demonstrate new methods for obtaining more accurate survey results and how to utilize these methods to develop and implement hospital-wide safety improvement programs. Conclusion : A successful safety culture survey is the foundation of all future safety improvement projects. This review is intended to guide hospitals in enhancing safety.