• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.919-929
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• 2022

As a new type of healthy public space, greenway users carry out leisure activities, exercise, sightseeing and necessary transportation in greenway. However, at present, there is little research on greenway users' evaluation and perception of greenway, and there is no comprehensive exploration of Greenway environment from a humanistic perspective. Combined with the research and actual situation of the existing representative greenways in Chinese cities, this paper refers to a large number of documents, applies the semantic difference method and multiple regression analysis method, analyzes the current situation of the Dongfengqu greenway, explores the influencing factors and impact evaluation of the greenway environment from the perspective of greenway users' perception, and puts forward suggestions on the optimization of the greenway environment in Zhengzhou from multiple levels. The main conclusion of this paper comes from the data conclusion obtained by semantic difference method, which is feasible in the resident evaluation of greenway use. The feedback results of post use evaluation can provide a reliable reference for the planning and design of similar greenways in the future.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.216-230
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• 2023

Purpose: The purpose is to prevent accidents by predicting disasters through the analysis of near-miss. Method: In this study, a near-miss literature review and data were collected at construction sites, and a questionnaire survey was conducted to use logistic regression analysis and decision tree analysis to classify the possibility of near-miss connection. Result: As a result of analyzing the effects of near-miss types on mental, physical, and safety habits and behaviors, the factor with a high influence on the body is the need for near-miss management, the type of job is electricity·information communication, and health status in order, and the mental factor is the construction scale The influence was high, and the factors with the highest influence on the habit behavior factors were analyzed in the order of experience, number of serious injuries, and occupation in order of illusion, inappropriate work instructions, and body parts. Through decision tree analysis, factors and patterns that affect the possibility of a near-miss being a surprise accident were identified. Conclusion: Construction site officials consider the observation of near-miss and mentally and physically. Specific management of the relevance of physical aspects to near-miss should be implemented, and a work environment in which serious accidents are reduced is expected through personnel allocation, work plans, work procedures and methods, and feedback so that inappropriate work instructions do not lead to near-miss.

• Journal of Animal Science and Technology
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• v.65 no.1
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• pp.244-257
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• 2023

The study aimed to investigate the effect of low-frequency oscillations on the cow udder, milk parameters, and animal welfare during the automated milking process. The study's objective was to investigate the impact of low-frequency oscillations on the udder and teats' blood circulation by creating a mathematical model of mammary glands, using milkers and vibrators to analyze the theoretical dynamics of oscillations. The mechanical vibration device developed and tested in the study was mounted on a DeLaval automatic milking machine, which excited the udder with low-frequency oscillations, allowing the analysis of input parameters (temperature, oscillation amplitude) and using feedback data, changing the device parameters such as vibration frequency and duration. The experimental study was performed using an artificial cow's udder model with and without milk and a DeLaval milking machine, exciting the model with low-frequency harmonic oscillations (frequency range 15-60 Hz, vibration amplitude 2-5 mm). The investigation in vitro applying low-frequency of the vibration system's first-order frequencies in lateral (X) direction showed the low-frequency values of 23.5-26.5 Hz (effective frequency of the simulation analysis was 25.0 Hz). The tested values of the first-order frequency of the vibration system in the vertical (Y) direction were 37.5-41.5 Hz (effective frequency of the simulation analysis was 41.0 Hz), with higher amplitude and lower vibration damping. During in vivo experiments, while milking, the vibrator was inducing mechanical milking-similar vibrations in the udder. The vibrations were spreading to the entire udder and caused physiotherapeutic effects such as activated physiological processes and increased udder base temperature by 0.57℃ (p < 0.001), thus increasing blood flow in the udder. Used low-frequency vibrations did not significantly affect milk yield, milk composition, milk quality indicators, and animal welfare. The investigation results showed that applying low-frequency vibration on a cow udder during automatic milking is a non-invasive, efficient method to stimulate blood circulation in the udder and improve teat and udder health without changing milk quality and production. Further studies will be carried out in the following research phase on clinical and subclinical mastitis cows.

• Quality Improvement in Health Care
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• v.28 no.2
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• pp.30-38
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• 2022

Purpose: The Health Insurance Review and Assessment Service (HIRA) in South Korea initiated a quality assessment (QA) program for blood transfusion healthcare services in 2020 to ensure patient safety and appropriate blood use. This study examines the quality of blood transfusion services since the first national QA program for blood transfusion services in Korea. Methods: We analyzed HIRA claims and QA investigation data based on inpatient medical records from all tertiary, general, and primary hospitals between October 2020 and March 2021. The target population was patients aged 18 years and older who received either total knee arthroplasty or red blood cell transfusion. The QA indicators for transfusion healthcare service consisted of four quality indicators and four monitoring indicators. Results: We analyzed the results of QA indicators for transfusion service from the medical records of 189,668 patients from 1,171hospitals and expressed indicators as proportions. The average results for evaluation indicators were as follows: transfusion checklist presence, 64.8%; irregular antibody tests, 61.8%; transfusions in which the hemoglobin levels before transfusion met the transfusion guidelines for patients undergoing total knee arthroplasty, 20.6%, and transfusions in patients undergoing total knee arthroplasty, 59.3%. The average results for monitoring indicators were as follows: transfusion management implementation in medical institutions, 56.9%; preoperative anemia management in anemia patients undergoing total knee arthroplasty, 43.9%; one-unit transfusions, 82.5%; and the transfusion index. Conclusion: The quality of blood transfusion healthcare varied and the assessment revealed that there is scope for improvement. Hospitals require more effective blood transfusion management and this can be facilitated by providing feedback on the QA results about blood transfusion healthcare services to medical institutions, and by disclosing the results to the public.

• Journal of Science Education
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• v.47 no.1
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• pp.1-10
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• 2023

In this study, we investigated the perception of STEAM (science, technology, engineering, arts, and mathematics) education consultants (SEC) about the requirements to achieve actual results and the improvements for STEAM education consulting. Data were collected from teachers who have had previous SEC experience or have extensive experience in STEAM education. First, an open-ended questionnaire was used to conduct a survey on the requirements and improvements for the STEAM education consulting, and items were composed by analyzing the contents of these free responses, and then statistical analysis was performed by asking them to respond on the Likert scale to how much they agreed to each item. As a result of the analysis, the SEC recognized that "formation of consensus between consultants and teachers", "consultant feedback on reflection of previous consulting results" and "encouragement and support for teachers" are appeared to be the most required for STEAM education consulting to achieve actual results. As the improvements of STEAM education consulting, "sharing cases and opinions among consultants", "selection and sharing of consulting best practices", and "development of various consulting types such as open classes" received the highest agreement. Based on these results, a support plan to increase the effectiveness of STEAM consulting was proposed.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.9
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• pp.429-442
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• 2017

This study was performed to investigate and analyze users' needs for m-health based prevention and intervention programs that are intended to improve the awareness of metabolic syndrome and promote health behaviors of college students. A questionnaire survey was conducted to 200 college students of 2 university in D city. Data were analyzed using descriptive statistics, t-tests, chi-square test with the SPSS Version 20.0. The result showed that users wanted customization of prescriptions and accurate measurement of health applications, and provided a positive feedback on information exchange between those who manage their health. The most preferred content was proper exercise methods, and the preferred gamification factors were goal-setting, compensation, and competition. The optimal price for wearable devices was between 10,000 to 50,000 won, and calorie consumption function was also preferred. Although users with experiences of wearable devices and health apps had a higher knowledge score pertaining to metabolic syndrome, there was no significant difference in the overall score. Concerning the health behaviors associated with lifestyles, individuals without the experiences of wearable devices and health apps showed a remarkably lower score. The research has a significance that it investigated and analyzed the contents needed for the development of effective moblie health based prevention and intervention programs targeting the population in their early adulthood. Therefore, based on the findings, we propose a rich and concrete follow-up study on the needs and characteristics of different user types by collecting a population with experiences of wearable devices, and a development of differentiated mobile health based prevention and intervention programs.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.2
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• pp.1-25
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• 2023

This study aims to propose implications for the development of archival content of archives management institutions in Korea by analyzing cases of the archival content on Instagram of the national archives in the Anglosphere. The basic information of the research target's Instagram account, including the creation date, content, and the number of followers, was investigated, and the posts' contents and interaction types with high user responses were analyzed. As a result, to spread the records information service using Instagram, producing images and short-form content that can be intuitively checked through mobile screens and creating content that will attract the attention of primary users are required. Moreover, it is necessary to develop content for informative communications that can be shared with other users. There is also a need to enhance the exposure and searchability of the institution's Instagram account by strengthening connections with the institution's existing online resources and enabling communications, such as using hashtags, following related institutional accounts, and providing feedback on the contents' comments with followers. This study is meaningful in that it examined cases of archival content for Instagram and suggested their applications, and it can be used as basic data to help plan archival contents to spread the archival culture.

• Journal of The Korean Association For Science Education
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• v.27 no.4
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• pp.346-353
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• 2007

In order to be efficient in teaching, a teacher should understand the current learner's level through diagnostic evaluation. This study has examined the major issues arising from the noble diagnostic assessment tool based on the theory of knowledge space. The knowledge state analysis method is actualizing the theory of knowledge space for practical use. The knowledge state analysis method is very advantageous when a certain group or individual student's knowledge structure is analyzed especially for strong hierarchical subjects such as mathematics, physics, chemistry, etc. Students' knowledge state helps design an efficient teaching plan by referring their hierarchical knowledge structure. The knowledge state analysis method can be enhanced by computer due to fast data processing. In addition, each student's knowledge can be improved effectively through individualistic feedback depending on individualized knowledge structure. In this study, we have developed a diagnostic assessment test for measuring student's learning outcome which is unattainable from the conventional examination. The diagnostic assessment test was administered to middle school students and analyzed by the knowledge state analysis method. The analyzed results show that students' knowledge structure after learning found to be more structured and well-defined than the knowledge structure before the learning.