• Computers and Concrete
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• v.31 no.3
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• pp.267-276
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• 2023

The main purpose of the current research is to develop an efficient two variables trigonometric shear deformation beam theory to investigate the buckling behavior of symmetric and non-symmetric functionally graded carbon nanotubes reinforced composite (FG-CNTRC) beam resting on an elastic foundation with various boundary conditions. The proposed theory obviates the use to shear correction factors as it satisfies the parabolic variation of through-thickness shear stress distribution. The composite beam is made of a polymeric matrix reinforced by aligned and distributed single-walled carbon nanotubes (SWCNTs) with different patterns of reinforcement. The material properties of the FG-CNTRC beam are estimated by using the rule of mixture. The governing equilibrium equations are solved by using new analytical solutions based on the Galerkin method. The robustness and accuracy of the proposed analytical model are demonstrated by comparing its results with those available by other researchers in the existing literature. Moreover, a comprehensive parametric study is presented and discussed in detail to show the effects of CNTs volume fraction, distribution patterns of CNTs, boundary conditions, length-to-thickness ratio, and spring constant factors on the buckling response of FG-CNTRC beam. Some new referential results are reported for the first time, which will serve as a benchmark for future research.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.93-114
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• 2023

Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.61-69
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• 2023

Recently, as the fishery resources are depleted, expectations for productivity improvement by 'rearing fishery' in land farms are greatly rising. In the case of land farms, unlike ocean environments, it is easy to control and manage environmental and breeding factors, and has the advantage of being able to adjust production according to the production plan. On the other hand, unlike in the natural environment, there is a disadvantage in that operation costs may significantly increase due to the artificial management for fish growth. Therefore, profit maximization can be pursued by efficiently operating the farm in accordance with the planned target shipment. In order to operate such an efficient farm and nurture fish, an accurate growth prediction model according to the target fish species is absolutely required. Most of the growth prediction models are mainly numerical results based on statistical analysis using farm data. In this paper, we present a growth prediction model from a stochastic point of view to overcome the difficulties in securing data and the difficulty in providing quantitative expected values for inaccuracies that existing growth prediction models from a statistical point of view may have. For a stochastic approach, modeling is performed by introducing a Gaussian process regression method based on water temperature, which is the most important factor in positive growth. From the corresponding results, it is expected that it will be able to provide reference values for more efficient farm operation by simultaneously providing the average value of the predicted growth value at a specific point in time and the confidence interval for that value.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.89-100
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• 2020

The smart factory is an important axis of the 4th industrial revolution. Smart factory is a system that induces the maximum efficiency and effectiveness of production using the IoT and intelligent sensing systems. The product lifecycle management technique is a method that can actively reflect the consumer's requirements in the smart factory and manage the entire process from the consumer to the post management. There have been many studies on product lifecycle management, but studies on how to organize product lifecycle management knowledge domains in preparation for the era of the 4th industrial revolution were insufficient. This study analyzed the opinions of a group of experts preparing for the 4th industrial revolution in terms of product lifecycle management. The impact of the 4th industrial revolution on the detailed knowledge areas of product lifecycle management was investigated. The changes in product lifecycle management were summarized using a qualitative data analysis technique for a group of experts. Based on the opinions of experts, the product lifecycle management, which consists of a total of 30 detailed knowledge areas, was prepared to supplement or prepare for the 4th industrial revolution. This study investigates changes in product lifecycle management in preparation for the 4th industrial revolution in the knowledge domain of the existing defined product life cycle management. In future research, it is necessary to redefine the knowledge domain of product life cycle management suitable for the era of the 4th industrial revolution and investigate the perception of experts. Considering the social culture and technological change factors of the 4th industrial revolution, the scope and scope of product life cycle management can be newly defined.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.883-890
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• 2022

Purpose: Currently, in the case of domestic fire fighting facility design, it is difficult to secure highquality manpower due to low design costs and overheated competition between companies, so there is a limit to improving the fire safety performance of buildings. Accordingly, AI-based firefighting design solutions were studied to solve these problems and secure leading fire engineering technologies. Method: Through AutoCAD, which is widely used in existing fire fighting design, the procedures required for basic design and implementation design were processed, and AI technology was utilized through the YOLO v4 object recognition deep learning model. Result: Through the design process for fire fighting facilities, the facility was determined and the drawing design automation was carried out. In addition, by learning images of doors and pillars, artificial intelligence recognized the part and implemented the function of selecting boundary areas and installing piping and fire fighting facilities. Conclusion: Based on artificial intelligence technology, it was confirmed that human and material resources could be reduced when creating basic and implementation design drawings for building fire protection facilities, and technology was secured in artificial intelligence-based fire fighting design through prior technology development.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.19-25
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• 2022

In the development of existing games, it is judged that virtual world production was done by arranging game elements one by one. What is noteworthy here is the question of whether quality virtual worlds were efficiently produced in preparation for investment. In this study, we propose a methodology that can build an efficient virtual world based on the concept of modularization in an unreal engine. First, precedents were analyzed and five reference elements for modularization were extracted. In addition, the concept of an instance production pipeline was proposed by dividing it into four stages, and the minimum-unit instance modules for urban virtual world production were compressed into four. Finally, an urban virtual world constructed based on the minimum unit module and reference elements was implemented and presented. In conclusion, research on the production method centered on this efficiency is thought to be able to focus the time that designers or artists had to spend on production only on ideas and creativity. The limitations of the research are that the basic minimum module is limited to the city, and the derived reference elements and production pipelines have not been verified when implementing them with an unreal engine. Therefore, it is expected that various virtual world creation plans will be derived through more advanced modular research.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.2
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• pp.37-42
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• 2022

Purpose Since 1985, the Korean society of nuclear medicine technology (KSNMT) has been engaged in academic activities related to nuclear medicine imaging. From 2017 to 2021, the papers published in the journal were classified by the specific fields to examine the trends in the research and the direction of nuclear medicine in comparison with the papers submitted to the Korean Society of Nuclear Medicine (KSNM) during the same period. Materials and Methods From 2017 to 2021, papers submitted to KSNMT and KSNM were classified and databaseization using the Excel program by submission type, examination equipment, and examination field. Through this data, the number of papers published in journals by year, the number of papers submitted by detailed fields, and key words by era were analyzed and compared. Results The papers included by journal was 57 KSNMT and 280 KSNM. The major large classification of equipment, PET, Planar and SPECT was 26.3%, 21.1%, 19.3% in the KSNMT, KSNM was 49.6%, 6.4%, and 9.3%, with 66.7% and 65.3%, respectively. the major medium classification of equipment, industrial safety, urogenital system, nervous system, and quality control accounted for 54.4% of the total papers of the total ratio in the KSNMT, while the medium classification of oncology, endocrine system, urogenital system, therapy, and nervous system accounted for 61.1% of KSNM. In the major small classification of image acquisition, improvement effect, and exposure management accounted for 70.2% in KSNMT, while the items of image acquisition, report, and improvement effect accounted for 60.7% in KSNM. The major keywords except for equipment-related keywords such as PET/CT, PET/MR, and SPECT were SUV, Planar Image, and Respiration Gating Method in KSNMT and Ga68, Thyroid, and Lymphoma in the KSNM. Conclusion When checking the last 5 years of submissions, we can see that KSNMT is mainly concerned with image acquisition using existing radiotracers, while KSNM has focused on new radiotracers such as ⁶⁸Ga, ¹⁷⁷Lu, etc., and new medical technologies of theranostic. It has been confirmed that more PET-related papers than other examination equipment will account for a greater number of papers, and it is believed that future submissions will also account for a higher proportion of PET-related papers than other equipment.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.6
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• pp.325-334
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• 2022

It has been more than 30 years since the term climate change began to become popular, but recently, rapid accelerated phenomena are appearing in the form of extreme weather all over the world. It is showing a distinctly different phenomenon from previous years, with heavy rain falling in the Death Valley desert in the U.S., and temperatures rising more than 40 degrees in Europe. In the Korean Peninsula, super typhoons with very strong wind speeds have become a major disaster risk for many years, and the supply of more energy due to the rise in sea temperature increases the possibility of super typhoons, requiring a proactive response. Unlike the method using numerical analysis, this study analyzed past typhoon data to study changes in typhoon characteristics for coastal disaster prevention. Existing studies have targeted all typhoons that have occurred, but in this study, a specific area was set up in the southern ocean of the Korean Peninsula and then a study was conducted. The subjects of the study were typhoons that occurred over the past 40 years from 1980 to the present, and it was confirmed that the maximum wind speed of typhoons affecting the Korean Peninsula increased slightly. The wind speed of typhoons in the specific area is about 80% of the maximum wind speed in their lifetime, and a correlation with ENSO could not be confirmed.

• Journal of the Korean Society of Earth Science Education
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• v.16 no.1
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• pp.72-86
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• 2023

The purpose of this study is to examine what epistemological beliefs pre-service teachers have about science depending on the situation, and to explore in-depth changes in epistemological beliefs through disciplinary reading. For this purpose, 77 essays written by pre-service elementary school teachers after reading Feynman's 'the meaning of it all' were analyzed using an inductive analysis method. As a result of the study, the epistemological beliefs of pre-service teachers were divided into two situations: 'science in subject learning' and 'science in daily life', and the epistemological beliefs formed in the 'science handled by scientists' situation were analyzed after reading the book. Each situation was divided into sub-categories of 'Impression of Knowledge', 'Source of Knowledge', 'Justification of Knowledge', 'Variability of Knowledge', 'Structure of Knowledge', and 'Value of Knowledge Acquisition' to reveal differences in sophisticated beliefs and naive belief levels. As a result, it was derived that Feynman's science lecture influenced pre-service teachers in terms of establishing new perspectives and recontextualizing existing epistemological beliefs. This study is meaningful in that pre-service teachers' scientific epistemological beliefs may vary depending on the situation, and that the scope and depth of epistemological beliefs may be expanded to include scientists' beliefs in science through disciplinary reading.