• The Korean Journal of Archival Studies
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• no.77
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• pp.151-187
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• 2023

The cooperation between archives and libraries is necessary for the management of limited operational space and the improvement of work efficiency. "Larchive" is one of the model of cooperation between libraries and archives, so it can be an alternative plan for institutions that face difficulties in collaborating through "Larchiveum" - growing model of cooperation between libraries, archives, and museums. This study presents the recognition of Larchive to university archivists and librarians, and suggests a practical operation plan for cooperation between the archive and library. As a result, "Larchive" was relatively less aware of archivists and librarians, but in the practical point of view, respondents were fully aware of the need for cooperation between archives and libraries. In particular, Larchive was presented as a rational alternative model for both of the groups. And the need for material cooperation can be confirmed through the recognition survey, and the improvement plan for business cooperation can be confirmed through the FGI. Some prerequisites are proposed such as securing a collaborative workplace, assignment of budget and manpower. Through the results, this study presented practical operational plans for organizational cooperation in the form of Larchive, focusing on the perspectives of "teaching and learning support", "research support services", "curation services", "collection and management of school history data", "cooperation for evaluation", and drew discussion points.

• Korean Journal of Culture and Arts Education Studies
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• v.13 no.3
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• pp.81-109
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• 2018

This study aims to identify research trends in adaptation of young children from multicultural families in order to provide insights for researchers around research topics and cultural adaptation orientation of young children from multicultural families. Subjects of this study were 41 literatures with key words of'young children from multicultural families', 'adaptation', and'life'through paper search system. This study was analysed the research themes, methods, subjects, and perspectives of cultural adaptation in adaptation researches of young children from multicultural families, 2006-2017 from peer reviewed journals with analysis frameworks. The results showed that : (a) the most common research topic continues to be about adaptation conditions of young children from multicultural families; (b) among research methods, quantitative research has most frequently used in, followed by qualitative methods, mixed methods, and literature review; (c) cultural adaptation was focused on the perspective of social-cultural adaptation, developmental importance of adaptation in early childhood and problems-based research. It implicated that further researches are need to focused on psychological adaptation and formation of classroom community beyond personal and structural adaptation in preschools.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.331-337
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• 2023

In this paper, we propose a deep learning model to detect lumbar 3 (L3) CT images to determine the occurrence and degree of sarcopenia. In addition, we would like to propose an optimization technique that uses oversampling ratio and class weight as design parameters to address the problem of performance degradation due to data imbalance between L3 level and non-L3 level portions of CT data. In order to train and test the model, a total of 150 whole-body CT images of 104 prostate cancer patients and 46 bladder cancer patients who visited Gangneung Asan Medical Center were used. The deep learning model used ResNet50, and the design parameters of the optimization technique were selected as six types of model hyperparameters, data augmentation ratio, and class weight. It was confirmed that the proposed optimization-based L3 level extraction model reduced the median L3 error by about 1.0 slices compared to the control model (a model that optimized only 5 types of hyperparameters). Through the results of this study, accurate L3 slice detection was possible, and additionally, we were able to present the possibility of effectively solving the data imbalance problem through oversampling through data augmentation and class weight adjustment.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.185-198
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• 2023

In marine seismic surveys, the inevitable occurrence of trace gaps in the near offset resulting from geometrical differences between sources and receivers adversely affects subsequent seismic data processing and imaging. The absence of data in the near-offset region hinders accurate seismic imaging. Therefore, reconstructing the missing near-offset information is crucial for mitigating the influence of seismic multiples, particularly in the case of offshore surveys where the impact of multiple reflections is relatively more pronounced. Conventionally, various interpolation methods based on the Radon transform have been proposed to address the issue of the nearoffset data gap. However, these methods have several limitations, leading to the recent emergence of deep-learning (DL)-based approaches as alternatives. In this study, we conducted an in-depth analysis of two representative DL-based studies to scrutinize the challenges that future studies on near-offset interpolation must address. Furthermore, through field data experiments, we precisely analyze the limitations encountered when applying previous DL-based trace interpolation techniques to near-offset situations. Consequently, we suggest that near-offset data gaps must be approached by extrapolation rather than interpolation.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.536-543
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• 2023

Speaker diarization, which labels for "who spoken when?" in speech with multiple speakers, has been studied on a deep neural network-based end-to-end method for labeling on speech overlap and optimization of speaker diarization models. Most deep neural network-based end-to-end speaker diarization systems perform multi-label classification problem that predicts the labels of all speakers spoken in each frame of speech. However, the performance of the multi-label-based model varies greatly depending on what the threshold is set to. In this paper, it is studied a speaker diarization system using single-label classification so that speaker diarization can be performed without thresholds. The proposed model estimate labels from the output of the model by converting speaker labels into a single label. To consider speaker label permutations in the training, the proposed model is used a combination of Permutation Invariant Training (PIT) loss and cross-entropy loss. In addition, how to add the residual connection structures to model is studied for effective learning of speaker diarization models with deep structures. The experiment used the Librispech database to generate and use simulated noise data for two speakers. When compared with the proposed method and baseline model using the Diarization Error Rate (DER) performance the proposed method can be labeling without threshold, and it has improved performance by about 20.7 %.

• Communications of Mathematical Education
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• v.37 no.3
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• pp.329-348
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• 2023

This study is necessary for the stable settlement of the 2022 revised mathematics curriculum 'data and possibility' area. This study was conducted centering on literature analysis. The purpose of this study is to realize statistics education in line with the 2022 revised mathematics curriculum. This purpose was achieved by examining the statistics learning contents of the 2022 revised curriculum, analyzing Chinese mathematics curriculum, and analyzing Chinese mathematics textbooks. In this study, the following studies were conducted. First, five elements were extracted through the analysis of the 'statistics and probability' area of the Chinese mathematics curriculum. The extracted elements are the 4th grade goals, synthesis and practice content areas, achievement standards for statistics and probability (6), (9), and (11). Second, examples presented in Chinese mathematics textbooks and Chinese curriculum appendices related to the extracted elements were analyzed. Regarding the 4th grade goal, the statistical problem-solving process of the 7th grade 2nd semester mathematics textbook was analyzed. Regarding the synthesis and practice content area, the data analysis unit of the 8th grade 2nd semester mathematics textbook was analyzed. In relation to the achievement standard (6), Example 85 of the curriculum appendix was analyzed, in relation to the achievement standard (9), Example 86 was analyzed, and in relation to the achievement standard (11), Example 87 was analyzed. Third, based on the analysis results, implications for the development of new curriculum and 'textbook development, teaching and learning methods' according to the 2022 revised middle school mathematics curriculum were derived. Through the results of this study, we expect the successful realization of the 2022 revised middle school mathematics and curriculum statistics education.

• Journal of Digital Policy
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• v.2 no.4
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• pp.1-10
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• 2023

This study conducted preliminary study to identify effective ways to use ChatGPT in traffic policing by analyzing ChatGPT's responses to the driver's license test and the road traffic accident appraiser test. I collected ChatGPT responses for the driver's license test item pool and the road traffic accident appraiser test using the OpenAI API with Python code for 30 iterative experiments, and analyzed the percentage of correct answers by test, year, section, and consistency. First, the average correct answer rate for the driver's license test and the for road traffic accident appraisers test was 44.60% and 35.45%, respectively, which was lower than the pass criteria, and the correct answer rate after 2022 was lower than the average correct answer rate. Second, the percentage of correct answers by section ranged from 29.69% to 56.80%, showing a significant difference. Third, it consistently produced the same response more than 95% of the time when the answer was correct. To effectively utilize ChatGPT, it is necessary to have user expertise, evaluation data and analysis methods, design a quality traffic law corpus and periodic learning.

• Journal of Cadastre & Land InformatiX
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• v.53 no.2
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• pp.53-66
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• 2023

Recently, there has been a significant interest in the development of autonomous driving simulation environment based on digital twin. In the development of such digital twin-based simulation environment, many researches has been conducted not only performance and functionality validation of autonomous driving, but also generation of virtual training data for deep learning. However, such digital twin-based autonomous driving simulation system has the problem of requiring a significant amount of time and cost for the system development and the data construction. Therefore, in this research, we aim to propose a method for rapidly designing and implementing a digital twin-based autonomous driving simulation system, using only the existing 3D models and high-definition map. Specifically, we propose a method for integrating 3D model of FBX and NGII HD Map for the Busan EDC area into CARLA, and a method for adding and modifying CARLA functions. The results of this research show that it is possible to rapidly design and implement the simulation system at a low cost by using the existing 3D models and NGII HD map. Also, the results show that our system can support various functions such as simulation scenario configuration, user-defined driving, and real-time simulation of traffic light states. We expect that usability of the system will be significantly improved when it is applied to broader geographical area in the future.

• Journal of The Korean Association For Science Education
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• v.26 no.1
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• pp.58-67
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• 2006

Student understanding of the nature of science is necessary not only because it is helpful for solving everyday problems with growing science literacy, but also because it influences students' science learning. Therefore, it was necessary to investigate student views on the nature of science under the 7th national curriculum and compare with those before the 7th national curriculum in order to probe the elements which contribute to changes in student views on the nature of science. A significant number of differences were found between subdimensions of views on the nature of science through the comparison. High school students under the 7th national curriculum had more relativistic, instrumental, and deductive but less process-oriented views than high school students before the 7th national curriculum. The differences between mean values which showed high school student views on the nature of science under and before the 7th national curriculum were significant, except for the subdimension of instrumentanlism/realism. In particular, high school students under the 7th national curriculum possessed a contextual view, whereas those before the 7th national curriculum possessed a decontextual view. Although other factors might be the cause for differences found in this study, we argued by discussion that differences among textbook contents seemed to be the major factor.

• Journal of The Korean Association For Science Education
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• v.28 no.4
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• pp.282-290
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• 2008

The Research and Education (R&E) program was a year-long, apprenticeship and research-based program that was guided by mentors who are scientists or science teachers. The objective of the R&E program was to help scientifically gifted students in Korea Science Academy (KSA) and Science High Schools (SHS) to enhance abilities in creative thinking, scientific inquiry, problem solving, positive attitude towards scientists, and promoting cooperative research and interests in science and technology. In this study, the impact of the R&E program on the goals of 182 gifted college students in KAIST was evaluated using Likert-type items and multiple-choice method approach that provided a more comprehensive evaluation of the program's impact on science attitudes, creative thinking, scientific inquiry, and interests in science and technology. The results indicated a positive impact on cooperative research, gaining knowledge on the research topic, attitude towards scientists, interest in science and technology, scientific inquiry, and creative thinking in that order. There were rather remarkable and meaningful differences in science inquiry (p<.05), and scientific knowledge (p<.01), between the two groups of KAIST freshmen who came from SHS and KSA in 2006. Implications for science apprenticeship or a research-based mentorship program and their respective evaluations are also discussed.