• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.99-107
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• 2023

Recently, the rate of death and safety accidents at construction sites is the highest among all kinds of industries. In order to apply artificial intelligence technology to construction sites, it is essential to secure a dataset which can be used as a basic training data. In this paper, a number of image data were collected through actual construction site, for which major construction equipment objects mainly operated in civil engineering sites were defined. The optimal training dataset construction was completed by annotation process of about 90,000 image dataset. Reliability of the dataset was verified with the mAP of over 90 % in use of YOLO, a representative model in the field of object detection. The construction equipment training dataset built in this study has been released which is currently available on the public data portal of the Ministry of Public Administration and Security. This dataset is expected to be freely used for any application of object detection technology on construction sites especially in the field of construction safety in the future.

• Korean Educational Research Journal
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• v.43 no.1
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• pp.29-57
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• 2022

This study was conducted to determine the effects of adolescents' media literacy, self-esteem, and cognitive related to on critical media understanding ability using data from the Korea Media Panel Survey 2020. As a result of the study, PC literacy and smart device literacy influenced adolescents' critical media literacy. The mediating effect of cognitive needs between Internet literacy and critical media understanding ability using PCs and smart devices was significant, and the mediating effect of self-esteem between email literacy using PCs and smart devices and critical media understanding ability was significant. Therefore, to improve adolescents' critical media understanding ability, it is necessary to educate them to use PCs and smart devices as tools for interaction. To this end, it is desirable for information and technology subjects to focus on media literacy to increase cognitive needs, and for other subjects, cooperative learning using media is desirable.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.885-890
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• 2023

As satellite technology progresses, a growing number of satellites-like CubeSat and radar satellites-are available with a higher spectral and spatial resolutions than previous. National initiatives used to be the main force behind satellite development, but current trendsindicate that private enterprises are also actively exploring and developing new satellite technologies. This special issue examines the recent research results and advanced technology in remote sensing approaches for Earth environment analysis. These results provide important information for the development of satellite sensors in the future and are of great interest to researchers working with artificial intelligence in thisfield. The special issue introduces the latest advances in remote sensing technology and highlights studies that make use of data to monitor and forecast Earth's environment. The objective is to provide direction for the future of remote sensing research.

• Smart Media Journal
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• v.12 no.9
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• pp.28-37
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• 2023

The main factor affecting the decline in rice yield is damage caused by localized heavy rains or typhoons. The method of analyzing the rice lodging area is difficult to obtain objective results based on visual inspection and judgment based on field surveys visiting the affected area. it requires a lot of time and money. In this paper, we propose the method of estimation and diagnosis for rice lodging areas using a Vision Transformer-based Segformer for RGB images, which are captured by unmanned aerial vehicles. The proposed method estimates the lodging, normal, and background area using the Segformer model, and the lodging rate is diagnosed through the rice field inspection criteria in the seed industry Act. The diagnosis result can be used to find the distribution of the rice lodging areas, to show the trend of lodging, and to use the quality management of certified seed in government. The proposed method of rice lodging area estimation shows 98.33% of mean accuracy and 96.79% of mIoU.

• Journal of Practical Engineering Education
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• v.16 no.1_spc
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• pp.33-39
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• 2024

This study examines the changes in learners' positive/negative perceptions of classroom experience and actual utilisation of AI chatbots in response to the recent changes in education trends caused by generative AI. AI chatbots were utilised in web programming classes for six classes of engineering students over two semesters. The learners' experience and usage were analysed from the beginning of the semester through surveys until the submission of midterm and final examination reports. The study's results indicate that the chatbot enhanced learning by providing Q/A feedback and solving practical problems. Additionally, the perception of the chatbot improved from midterm to the end of the course. The study also drew meaningful conclusions about the issue of community disconnection (personalisation) in the classroom and how to use it as educational software. This research is significant for the development of generative AI-based software.

• Journal of Korean Neurosurgical Society
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• v.67 no.5
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• pp.493-509
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• 2024

In neurointensive care units (NICUs), particularly in cases involving traumatic brain injury (TBI), swift and accurate decision-making is critical because of rapidly changing patient conditions and the risk of secondary brain injury. The use of artificial intelligence (AI) in NICU can enhance clinical decision support and provide valuable assistance in these complex scenarios. This article aims to provide a comprehensive review of the current status and future prospects of AI utilization in the NICU, along with the challenges that must be overcome to realize this. Presently, the primary application of AI in NICU is outcome prediction through the analysis of preadmission and high-resolution data during admission. Recent applications include augmented neuromonitoring via signal quality control and real-time event prediction. In addition, AI can integrate data gathered from various measures and support minimally invasive neuromonitoring to increase patient safety. However, despite the recent surge in AI adoption within the NICU, the majority of AI applications have been limited to simple classification tasks, thus leaving the true potential of AI largely untapped. Emerging AI technologies, such as generalist medical AI and digital twins, harbor immense potential for enhancing advanced neurocritical care through broader AI applications. If challenges such as acquiring high-quality data and ethical issues are overcome, these new AI technologies can be clinically utilized in the actual NICU environment. Emphasizing the need for continuous research and development to maximize the potential of AI in the NICU, we anticipate that this will further enhance the efficiency and accuracy of TBI treatment within the NICU.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.3
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• pp.35-64
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• 2024

The purpose of this study is to develop educational strategies and models by applying future-oriented elements of libraries, which are transitioning into integrated spaces through collaboration with archives and museums, into school library education. This study focuses on the changes where libraries expand their spaces and roles in response to the trends of a pluralistic society. The term 'Larchiveum' was established to represent a knowledge and culture complex space. The concepts and functions of this term were identified, and the characteristics of materials collected and managed by archives, museums, and art galleries, as well as domestic and international educational information services, were analyzed to explore ways to integrate them into school library education. Based on the ASSURE instructional design model, which emphasizes the effective selection and use of teaching and learning media, this study developed Larchiveum strategies, including 'Inquiry-based Information Utilization,' 'Curriculum Integration and Convergence,' 'Collaboration, Sharing, and Dissemination,' and 'Digital Archive,' and structured the educational content accordingly. The procedures and steps were refined through the evaluation and feedback of field experts, leading to the development of a collaborative educational model that incorporates Larchiveum strategies, resources, and inquiry-based instruction.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.167-178
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• 2024

In this study, we investigated the perceptions of science-related careers and career education among middle school science teachers. Sixty-four science teachers experienced in teaching unit 7 in the first year of middle school participated. The results of the study revealed that not only careers in science but also careers with science were found to be quite high when teachers were asked to provide examples of science-related careers. Jobs related to research/engineering, which are careers in science, comprised the highest proportion of teachers' answers, followed by jobs related to education/law/social welfare/police/firefighting/military, and health/medical, which are careers with science. However, the proportion of jobs mentioned related to installation/maintenance/production was extremely low. The skills required for science-related careers were mainly perceived to consist of tools for working and ways of working. The number of skills classified under living in the world was perceived to be extremely low across most careers, irrespective of career type. Most teachers only taught unit 7 for two to four sessions and devoted little time to science-related career education, even in general science classes. In the free semester system, a significant number of teachers responded that they provide science-related career education for more than 8 hours. Teachers mainly utilize lecture, discussion/debate, and self-study activities. Meanwhile, in the free semester system, the resource-based learning method was utilized at a high proportion compared to other class situations. Teachers generally made much use of media materials, with the use of textbooks and teacher guides found to be lower than expected. There were also cases of using materials supported by science museums or the Ministry of Education. Teachers preferred to implementing student-centered classes and utilizing various teaching and learning methods. Based on the above research results, discussions were proposed to improve teachers' perceptions of science-related careers and career education.

• The KIPS Transactions:PartC
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• v.15C no.5
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• pp.351-358
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• 2008

Recently, as network flooding attacks such as DoS/DDoS and Internet Worm have posed devastating threats to network services, rapid detection and proper response mechanisms are the major concern for secure and reliable network services. However, most of the current Intrusion Detection Systems(IDSs) focus on detail analysis of packet data, which results in late detection and a high system burden to cope with high-speed network environment. In this paper we propose a lightweight and fast detection mechanism for traffic flooding attacks. Firstly, we use SNMP MIB statistical data gathered from SNMP agents, instead of raw packet data from network links. Secondly, we use a machine learning approach based on a Support Vector Machine(SVM) for attack classification. Using MIB and SVM, we achieved fast detection with high accuracy, the minimization of the system burden, and extendibility for system deployment. The proposed mechanism is constructed in a hierarchical structure, which first distinguishes attack traffic from normal traffic and then determines the type of attacks in detail. Using MIB data sets collected from real experiments involving a DDoS attack, we validate the possibility of our approaches. It is shown that network attacks are detected with high efficiency, and classified with low false alarms.

• Journal of The Korean Association For Science Education
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• v.34 no.7
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• pp.635-645
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• 2014

The purpose of this study is to identify elementary school teachers' perceptions, practices, and background factors related to introducing students' everyday experience in science teaching process. The participants of this study were four elementary school teachers who have different features such as major, teaching period, gender, growth area, and age. The data was collected through semi-constructed and in-depth interviews. The results of the research are as follows: Teachers mostly used students' everyday experience during the introduction phase of science lessons for the purpose of motivation. They hold a positive view of using students' everyday experience during science lessons and thought that science teaching needs to actively use more of students' everyday experience, while in actual practice they disregarded or only passively introduced students' everyday experience. The various background factors found to affect teachers' practice are as follows: positive memory on their science class; educational experience of their own children; their own childhood environment; their learning style; their insufficient knowledge or enthusiasm; perceived educational value of everyday life in science education; teacher's duties; importance of students' achievement; difficulty in guiding experiment; reaction of students on introducing everyday experience; characteristics of science textbook and teacher's guidebook; lack of lesson time; realization of national common basic education; characteristics of their students; demands from parents or students; effect of introducing everyday experience. In addition, we found that the teachers behave not in accordance with what they thought due to external factors related to their profession and that, for a more active use of students' everyday experience in their teaching, teachers need support from textbooks and teachers' guidebooks.