• Steel and Composite Structures
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• v.39 no.1
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• pp.65-80
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• 2021

Irregularities of a building in plan and elevation, which results in the change in stiffness on different floors highly affect the seismic performance and resistance of a structure. This study motivated to investigate the seismic responses of high-rise steel-frame buildings of twelve stories with various stiffness irregularities. The building has five spans of 3200 mm distance in both X- and Z-directions in the plan. The design package SAP2000 was adopted for the design of beams and columns and resulted in the profile IPE500 for the beams of all floors and box sections for columns. The column cross-section dimensions vary concerning the number of the story; one to three: 0.50×0.50×0.05m, four to seven: 0.45×0.45×0.05 m, and eight to twelve: 0.40×0.40×0.05 m. Real recorded ground accelerations obtained from the Vrancea earthquake in Romania together with dead and live loads corresponding to each story were considered for the applied load. The model was validated by comparing the results of the current method and literature considering a three-bay steel moment-resisting frame of eight-story height subject to seismic load. To investigate the seismic performance of the buildings, the time-history analysis was performed using ABAQUS. Deformed shapes corresponding to negative and positive peaks were provided followed by the story drifts and fragility curves which were used to examine the probability of collapse of the building. From the results, it was concluded that regular buildings provided a seismic performance much better than irregular buildings. Furthermore, it was observed that building with torsional irregularity was more vulnerable to seismic failure.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.268-268
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• 2023

전 지구적 급격한 기후변화로 인해 수문기상인자들의 비선형적 변동성이 발생함과 동시에 가뭄, 홍수와 같은 수재해의 발생빈도 및 강도가 증가하고 있는 추세이다. 이에 따라, 세계의 유수기관 (NASA, ESA 등)에서는 대기모형과 해양 모형의 결합 및 수치해석적 접근법을 활용하여 계절내-계절 (Subseasonal to seasonal; S2S) 예측치를 생산하여 제공하고 있다. 이에 따라, 본 연구에서는 European Centre for Medium-Range Weather Forecast (ECMWF)에서 산정되는 수문기상인자 (강수량, 증발산량 및 유출량)에 대한 정확도를 평가하고자 한다. 연구지역으로는 다양한 기후대 및 토지 피복으로 구성되어 있으며, El-Nino-Southern Oscillation (ENSO), Indian Ocean Diapole (IOD)와 같은 기후 현상이 빈번히 발생하는 호주지역을 대상으로 연구를 수행하였다. ECMWF S2S 자료에 대한 통계적 검증은 1) 지점 기반 관측치와 더불어 2) 물수지 모델 기반 수문 추정치 (The Australian Water Resources Assessment Landscape Model; AWRA-L)와 비교하였다. 연구 결과 S2S 강우 및 증발산량 산정치의 경우 비교적 짧은 예측기간(약 2주)에서 상대적으로 높은 상관관계 (R=0.5~0.6)와 낮은 편차 (강수량 = 0.10 mm/day, 증발산량 = 0.21 mm/day)를 나타내었다. 유출량의 경우, 강우 및 증발산량에 비해 상대적으로 낮은 정확도를 나타내었으며, 예측 기간이 길어짐에 따라 불확실성이 상당히 높아지는 것으로 확인되었다. 이는, S2S 계산과정에서 강우 및 증발산량 뿐만아니라 지표 유출로 도달하기 전까지의 수문기상인자들의 불확실성이 모두 모여 유출량의 불확실성이 높아진 것으로 확인할 수 있었다. 계절적 검증에서는, 강우 및 증발산량 모두 여름철에 높은 상관관계를 나타내었지만 불확실성은 상대적으로 큰 값을 나타내었다. 자세한 분석을 위해, 공간적인 불확실성을 분석해본 결과 ECMWF S2S가 매우 습윤하거나 건조한 지역에서 수문기상인자를 예측하는데 있어 한계성이 나타난 것을 확인하였다. 본 연구를 토대로, 추후 S2S 예측치에 대한 보정과 더불어 미래의 수재해 발생 위험도에 대한 정보를 획득하는데 적용될 수 있을 것으로 판단된다.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.471-481
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• 2023

Digital twin is considered as a key technology of industry 4.0, thus being essential for the future of industrial production. Despite the significance, a systematic analysis of its technological landscape is lacking. This study aims to investigate the technological development trends and newly emerging technological convergence opportunities in the domain of digital twin by exploiting patent information derived from U SPTO. For this purpose, this study visualized and predicted the convergence dynamics among patent classification codes by adopting patent co-classification analysis and link prediction approach. The findings show that the number of digital twin-related patent applications has increased significantly since 2018. The CPC code G06F showed the highest eigenvector centrality, while G05B was characterized by highest betweenness centrality. According to the predictive model, 41 novel links were revealed, acting as potential technology convergence opportunities. These links were then categorized into 11 different domains. The most dominant category was "digital data processing and artificial intelligence", which could play a foundational role in the diffusion of digital twin technology. The presence of digital twin technology is dominant in manufacturing, but its applications are expected to expand, including "climate change", "healthcare" and "aerospace engineering". The derived insights can support R&D managers and policy makers in formulating R&D strategies and directing future R&D investment decisions.

• The Journal of Economics, Marketing and Management
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• v.5 no.2
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• pp.10-32
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• 2017

The landscape of corporate reporting is changing quickly. The concepts, elements and principles that characterize the way organizations plan, manage and report their annual performances are currently being questioned, debated, and redesigned throughout the world. However, widening the scope of corporate performance and reporting is a major issue. Research needs to bridge the gap between social and financial performance by considering corporate performance in a wider perspective. At base, IR is a relatively new but powerful idea: enhancing the way organizations think, plan and report the story of their business. Organizations are using IR to communicate a clear, concise, integrated story that explains how all of their resources are creating value. This paper examines the rise of what has been widely claimed to represent a new and striking future for corporate reporting, namely the notion of "Integrated Reporting" (IR). Unfortunately, there is poor empirical research work undertaken which has focused on published integrated reports. This research study provides initial analysis of the content and structure of the corporate integrated reports published in 2013 and available on the International Integrated Reporting Council (IIRC) Emerging Examples Database. As part of this study, Integrated Reports were analyzed for company information, report information and report content. Moreover, they were also evaluated as to the extent these adhered to the integrated reporting (IR) Guiding Principles, Content Elements, and the multiple capitals model. Findings of this study indicate that "early integrated reports were mostly lengthy, fail to adhere to all the guiding principles, and covered four of the six capitals suggested." At present, no universally accepted global framework for IR exists and it is still largely a voluntary practice. We believe that IR of both financial and non-financial performance should be made mandatory, and it should become a universal practice for all the global listed companies within the next 5-10 years.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.439-441
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• 2023

National park is one of the important types of protected area management systems established by IUCN and a management model for effective conservation and sustainable use of natural and cultural heritage in countries around the world, and it assumes important roles in conservation, scientific research, education, recreation and driving community development. This study takes Liaohe National Park in China, a typical representative of global coastal wetlands, as a case study, and uses python technology to collect travelogues and reviews of visitors from Mafengwo.com, Ctrip.com, Go.com, Meituan.com and Dianping.com as a source, and the text spans from 2015 to 2022. The results show that wildlife resources, natural landscape with river and sea, wetland ecology and fishing and hunting culture of northern China are fully reflected in the perceptions of visitors to Liaohe National Park. However, there is still much room for improvement in terms of supporting services and facilities, public education and tourists' experience and participation in Liaohe National Park. In this paper, we use python data visualization technology to study the public perception of wetland wildlife as the theme, and grasp the satisfaction, spatial distribution, activity content and emotional tendency of the public in the process of wetland wildlife as the theme, so as to better promote the Liaohe National Park to better carry out the public experience while strictly adhering to ecological protection, and to provide the Liaohe National Park with a better opportunity to This will provide scientific basis for the Liaohe National Park to play a better role in ecological civilization construction and education of ecological civilization awareness.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.259-277
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• 2023

This study aims to identify the academic landscape of the field of Library and Information Science by analyzing the research areas of the four major domestic journals using structural topic modeling and network analysis. The results show that each journal focuses on different research areas. The Journal of the Korean Society for Library and Information Science covers the most comprehensive range of research areas in the field, while the Journal of the Korean Biblia Society for Library and Information Science shows a similar research trend but with a higher preference for research areas related to library management and library programs. The Journal of Korean Library and Information Science Society deals more with topics related to school libraries and reading education and the Journal of the Korean Society for Information Management focuses more on information technology and information science. This study is able to provide valuable foundational data for researchers in submitting their papers and for the topical specialization and diversification of the journals in the field of Library and Information Science.

• Korean Journal of Radiology
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• v.25 no.3
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• pp.224-242
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• 2024

The emergence of Chat Generative Pre-trained Transformer (ChatGPT), a chatbot developed by OpenAI, has garnered interest in the application of generative artificial intelligence (AI) models in the medical field. This review summarizes different generative AI models and their potential applications in the field of medicine and explores the evolving landscape of Generative Adversarial Networks and diffusion models since the introduction of generative AI models. These models have made valuable contributions to the field of radiology. Furthermore, this review also explores the significance of synthetic data in addressing privacy concerns and augmenting data diversity and quality within the medical domain, in addition to emphasizing the role of inversion in the investigation of generative models and outlining an approach to replicate this process. We provide an overview of Large Language Models, such as GPTs and bidirectional encoder representations (BERTs), that focus on prominent representatives and discuss recent initiatives involving language-vision models in radiology, including innovative large language and vision assistant for biomedicine (LLaVa-Med), to illustrate their practical application. This comprehensive review offers insights into the wide-ranging applications of generative AI models in clinical research and emphasizes their transformative potential.

• Journal of Integrative Natural Science
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• v.17 no.3
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• pp.93-103
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• 2024

Mongolia's diverse geographical landscape and harsh climate make it particularly susceptible to various natural disasters, including forest fires, heavy rains, dust storms, and heavy snow. This study aims to explore the relationships between key climatic variables and the frequency of these disasters. We collected monthly data from January 2022 to April 2024, encompassing average temperature, temperature variability (absolute temperature difference), average humidity, and precipitation across the capitals of Mongolia's 21 provinces and the capital city Ulaanbaatar. The data were analyzed using multiple statistical models: Linear Regression, Poisson Regression, and Negative Binomial Regression. Descriptive statistics provided initial insights into the variability and distribution of the climatic variables and disaster occurrences. The models aimed to identify significant predictors and quantify their impact on disaster frequencies. Our approach involved standardizing the predictor variables to ensure comparability and interpretability of the regression coefficients. Our findings indicate that climatic variables significantly affect the frequency of natural disasters. The Negative Binomial Regression model was particularly suitable for our data, which exhibited overdispersion common characteristic in count data such as disaster occurrences. Understanding these relationships is crucial for developing targeted disaster management strategies and policies to mitigate the adverse effects of climate change on Mongolian communities. This research provides valuable insights into how climatic changes impact disaster occurrences, offering a foundation for informed decision-making and policy development to enhance community resilience.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1315-1315
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• 2024

In recent years, the building industry has seen a fundamental transition due to Digitalization Transformation (DX), with the aim of improving efficiency, productivity, sustainability, and cost-effectiveness. In particular, literature has significantly emphasized Smart Buildings (SBs), which are expected to grow in the global marketplace in the coming years. The most noticeable benefits include energy efficiency, increased occupant comfort and productivity, and a reduction in the building's impact on the environment. Most importantly, the shift to SBs has resulted in major changes to how traditional business practices are carried out. The Facility Asset Management (FAM) domain is one key area undergoing considerable changes to meet the needs of managing functional SBs. Despite this shifting landscape, the changes and prospective extensions to the business areas of FAM in the context of SBs remain largely unexplored. Thus, to address this limitation, this paper aims to investigate the potential changes (i.e., either the addition of a new function or the expansion of an existing function) of the FAM domain from the context of SBs. To achieve this objective, • First, based on a generic model of FAM proposed by Jin et al. (2024), a three-level hierarchical classification of FAM business functions for a conventional building is proposed. • Second, the concept of SBs is thoroughly discussed, including its drivers, features, enablers, and improvement areas. • Finally, a new FAM business function for SB is proposed, aligning with the distinct characteristics of SBs. As there are no established functional taxonomies of FAM, the comprehensive breakdown of FAM business functions presented in this study can be used as a standardized functional breakdown of the FAM domain. Moreover, it can also be used to facilitate robust and integrated information management practices throughout the whole lifecycle of SB facilities.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.146-157
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• 2019

One of the most distinctive features of the South Korean rural environment is that the variation of weather or climate is large even within a small area due to complex terrains. The Geospatial Schemes based on Topo-Climatology (GSTP) was developed to simulate such variations effectively. In the present study, we reviewed the progress of the geospatial schemes for production of farm-scale agricultural weather data. Efforts have been made to improve the GSTP since 2000s. The schemes were used to provide climate information based on the current normal year and future climate scenarios at a landscape scale. The digital climate maps for the normal year include the maps of the monthly minimum temperature, maximum temperature, precipitation, and solar radiation in the past 30 years at 30 m or 270 m spatial resolution. Based on these digital climate maps, future climate change scenario maps were also produced at the high spatial resolution. These maps have been used for climate change impact assessment at the field scale by reprocessing them and transforming them into various forms. In the 2010s, the GSTP model was used to produce information for farm-specific weather conditions and weather forecast data on a landscape scale. The microclimate models of which the GSTP model consists have been improved to provide detailed weather condition data based on daily weather observation data in recent development. Using such daily data, the Early warning service for agrometeorological hazard has been developed to provide weather forecasts in real-time by processing a digital forecast and mid-term weather forecast data (KMA) at 30 m spatial resolution. Currently, daily minimum temperature, maximum temperature, precipitation, solar radiation quantity, and the duration of sunshine are forecasted as detailed weather conditions and forecast information. Moreover, based on farm-specific past-current-future weather information, growth information for various crops and agrometeorological disaster forecasts have been produced.