• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2452-2459
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• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.72-78
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• 2003

A new self-organizing neuro-fuzzy network based rate control algorithm for MPEG-4 video encoder is proposed in this paper. Contrary to the traditional methods that construct the rate-distorion (RD) model based on experimental equations, the proposed method effectively exploits the non-stationary property of the video date with neuro-fuzzy network that self-organizes the RD model online and adaptively updates the structure. The method needs not require off-line pre-training; hence it is geared toward real-time coding. The comparative results through the experiments suggest that our proposed rate control scheme encodes the video sequences with less frame skip, providing good temporal quality and higher PSNR, compared to VM18.0.

• Journal of Society of Preventive Korean Medicine
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• v.28 no.2
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• pp.1-18
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• 2024

Objectives : This study aimed to analyze the College of Korean Medicine's education related to vaccination to examine the feasibility of Korean medical doctors administering vaccines. Methods : We conducted a comprehensive review of the guidelines from the Korea Disease Control and Prevention Agency (KDCP) and the U.S. Advisory Committee on Immunization Practices (ACIP), along with the educational standards of Korean medical colleges. From these sources, key knowledge areas essential for vaccination were identified and distilled into 12 core items, creating a checklist used to evaluate the vaccination-related education. The curricula of Korean medical colleges and online continuing education courses for Korean medical doctors were analyzed using this checklist. Additionally, we reviewed the compulsory education course for vaccination providers for comparative purposes. Results : The analysis of common textbooks from colleges of Korean medicine revealed that while basic concepts of vaccination are widely covered, practical guidance on vaccine administration is less comprehensive. Continuing education for Korean medical doctors emphasizes basic epidemiological knowledge, vaccination contraindications and treating adverse reactions, but lacks details on patient education and the vaccination process. Compulsory education for vaccination providers covers extensive administrative content and comprehensively addresses essential vaccination knowledge, including patient education and practical vaccination procedures. Conclusion : The College of Korean Medicine's curriculum covers basic vaccination theories but lacks specific training in vaccine management. Additional training can improve Korean medical doctors' vaccination skills, enhancing the healthcare system's emergency response.

• Smart Structures and Systems
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• v.29 no.4
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• pp.625-640
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• 2022

Maglev rail joints are vital components serving as connections between the adjacent F-type rail sections in maglev guideway. Damage to maglev rail joints such as bolt looseness may result in rough suspension gap fluctuation, failure of suspension control, and even sudden clash between the electromagnets and F-type rail. The condition monitoring of maglev rail joints is therefore highly desirable to maintain safe operation of maglev. In this connection, an online damage detection approach based on three-dimensional (3D) convolutional neural network (CNN) and time-frequency characterization is developed for simultaneous detection of multiple damage of maglev rail joints in this paper. The training and testing data used for condition evaluation of maglev rail joints consist of two months of acceleration recordings, which were acquired in-situ from different rail joints by an integrated online monitoring system during a maglev train running on a test line. Short-time Fourier transform (STFT) method is applied to transform the raw monitoring data into time-frequency spectrograms (TFS). Three CNN architectures, i.e., small-sized CNN (S-CNN), middle-sized CNN (M-CNN), and large-sized CNN (L-CNN), are configured for trial calculation and the M-CNN model with excellent prediction accuracy and high computational efficiency is finally optioned for multiple damage detection of maglev rail joints. Results show that the rail joints in three different conditions (bolt-looseness-caused rail step, misalignment-caused lateral dislocation, and normal condition) are successfully identified by the proposed approach, even when using data collected from rail joints from which no data were used in the CNN training. The capability of the proposed method is further examined by using the data collected after the loosed bolts have been replaced. In addition, by comparison with the results of CNN using frequency spectrum and traditional neural network using TFS, the proposed TFS-CNN framework is proven more accurate and robust for multiple damage detection of maglev rail joints.

• Journal of Korean Library and Information Science Society
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• v.25
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• pp.529-567
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• 1996

This paper surveyed the theoretical backgrounds of digital library. Its definition and function and case studies, and basic skills for system construction of digital library were suggested. The differences between the traditional library and the digital library were compared. And the conditions that should be take into consideration of digital library construction were suggested. Suggestions are summarized as follows : 1. For the construction of digital library, library collection should be digitalized by using CD-ROM and commercial online services. 2. The digitalization of library collection should be planned by subject sharing between the libraries. For the control of this cooperation, the orgnization to propel the digitalization should be established. And it is necessary to enact the standards for the digital library. 3. The connection between MARC formatted bibliographic database and full-text should be studied. 4. All the types of information about texts, pictures, sounds and if films should be also digitalized. 5. To satisfy the needs of many users, we have to establish the various users's interface which is fitted for several kinds of users. 6. When a digital library was constructed, the copyright and resources sharing must be guranteed depending on the cost of database's usage. 7. Because the digitalization of library will be related to the various kinds of libraries, the interface for resources sharing will be constantly concerned. 8. The sharing of information resources between the libraries will be enacted on the Internet. And we must be interested in various internet tools such as telecommunication softwares, media convert programs, etc. 9. By training staffs continously, all libraries must be ready to come the library in the future.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.347-357
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• 2020

This research aims to shed light on the technology adoption process and its drivers in the Vietnamese educational system. Research data was collected with an online questionnaire from more than 600 teachers in primary schools, secondary schools, high schools, colleges, and universities in Vietnam in 2020. Based on a holistic literature review, we develop a model of two extrinsic factors (global needs and school-infrastructure), and two intrinsic factors (teachers' technological literacy and their beliefs), which are correlated with the teachers' technological adoption. We measure the dependent variable by asking the teachers' ability and their efficacy to implement technology in teaching according to a Likert scale. With the support of SPSS_22 and STATA_2015, we find that over 70% of changes in technology adoption are explained by the changes in four independent variables and three control variables related to age, gender, and teaching-level of the teachers. Furthermore, these independent variables are significantly and positively associated with two dependent variables. However, a significant difference in technology integration ability can be seen among teachers' gender, age, and school-level. Specifically, male teachers seem to adopt technology at schools than female teachers better, and university teachers have the lowest level of technology adoption compared to other school-level teachers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.421-441
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• 2021

Fruit detection in orchards is one of the most crucial tasks for designing the visual system of an automated harvesting robot. It is the first and foremost tool employed for tasks such as sorting, grading, harvesting, disease control, and yield estimation, etc. Efficient visual systems are crucial for designing an automated robot. However, conventional fruit detection methods always a trade-off with accuracy, real-time response, and extensibility. Therefore, an improved method is proposed based on coarse-to-fine multitask cascaded convolutional networks (MTCNN) with three aspects to enable the practical application. First, the architecture of Fruit-MTCNN was improved to increase its power to discriminate between objects and their backgrounds. Then, with a few manual labels and operations, synthetic images and labels were generated to increase the diversity and the number of image samples. Further, through the online hard example mining (OHEM) strategy during training, the detector retrained hard examples. Finally, the improved detector was tested for its performance that proved superior in predicted accuracy and retaining good performances on portability with the low time cost. Based on performance, it was concluded that the detector could be applied practically in the actual orchard environment.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.965-976
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• 2017

The purpose of this study was to investigate how the Peer counseling program in on-offline would effect university students on their self-esteem and self-efficacy. In order to achieve this purpose, ten participants were in the experimental group and the other ten were in the control group. The subjects in the experimental group receive to the peer counseling program training for 120 minutes once a week for 10 weeks. The next day, practiced counseling online The data were analyzed by using t-test and ANCOVA. As the participants of the Peer counseling program reported that they experienced significant difference of improvement on their self-esteem(F=13.258, p<.01) and self-efficacy(F=15.565, p<.01) than those were in the control group. The Peer counseling program suggested that expected to positive effects it would help improve university freshmen students' self-esteem and self-efficacy.

• Safety and Health at Work
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• v.10 no.1
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• pp.3-20
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• 2019

This review aimed to identify risk factors for occupational accidents and illnesses among young workers in the Nordic countries and to attain knowledge on specific vulnerable groups within the young working force that may need special attention. We conducted a systematic review from 1994 to 2014 using five online databases. Of the 12,528 retrieved articles, 54 met the review criteria and were quality assessed, in which data were extracted focusing on identifying occupational safety, health risk factors, and vulnerable groups among the young workers. The review shows that mechanical factors such as heavy lifting, psychosocial factors such as low control over work pace, and organizational factors such as safety climate are all associated with increased injury risk for young Nordic workers. Results show that exposures to chemical substances were associated with skin reactions, e.g., hand eczema. Heavy lifting and awkward postures were risk factors for low back pain, and high job demands were risk factors for mental health outcomes. The review identified young unskilled workers including school drop-out workers as particularly vulnerable groups when it comes to occupational accidents. In addition, apprentices and young skilled workers were found to be vulnerable to work-related illnesses. It is essential to avoid stereotyping young Nordic workers into one group using only age as a factor, as young workers are a heterogeneous group and their vulnerabilities to occupational safety and health risks are contextual. Politicians, researchers, and practitioners should account for this complexity in the education, training and organization of work, and workplace health and safety culture.

• Journal of the Korean Society of School Health
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• v.34 no.1
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• pp.76-86
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• 2021

Purpose: This study was conducted to describe the experience of school health teachers in regard to the COVID-19 pandemic in South Korea. Methods: We conducted a qualitative study using content analysis. Ten school health teachers were recruited from 6 elementary schools, 2 middle schools and 2 high schools in Seoul, using purposive sampling. They participated in semi-structured in-depth interviews in person or using an online communication system from January to February, 2021. Interviews were transcribed verbatim and analysed using qualitative content analysis. Results: Three main categories and nine generic categories emerged from the analysis. Firstly, it was discovered that school health teachers had psychological and physical stress to cope with COVID-19 due to the 1) fear of the unexpected infectious disease, 2) burden of having to deal with it alone, 3) breakdown of personal life and physical exhaustion and 4) heavy duty as a health teacher caused by the lack of an organic cooperation system with institutions related to school infectious diseases. Secondly, school health teachers had an increased sense of empowerment in regard to infectious disease management as a result of 1) feeling rewarded and appreciated and 2) gaining confidence and trust in infectious disease management. Finally, school health teachers experienced the urgent need for an effective response strategy for infection control because of the 1) confusion over infectious disease response due to lack of practical manuals applicable to the field as well as training, 2) disappointing response system without an expert response team dedicated to managing infectious diseases in schools, and 3) growing awareness of the need for change. Conclusion: It is expected that school health teachers' experience of COVID-19 will be used as important data for building effective and advanced school infectious disease response systems.