• Korean Journal of Radiology
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• v.23 no.4
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• pp.413-425
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• 2022

Objective: We compared appendiceal visualization on 2-mSv CT vs. conventional-dose CT (median 7 mSv) in adolescents and young adults and analyzed the undesirable clinical and diagnostic outcomes that followed appendiceal nonvisualization. Materials and Methods: A total of 3074 patients aged 15-44 years (mean ± standard deviation, 28 ± 9 years; 1672 female) from 20 hospitals were randomized to the 2-mSv CT or conventional-dose CT group (1535 vs. 1539) from December 2013 through August 2016. A total of 161 radiologists from 20 institutions prospectively rated appendiceal visualization (grade 0, not identified; grade 1, unsure or partly visualized; and grade 2, clearly and entirely visualized) and the presence of appendicitis in these patients. The final diagnosis was based on CT imaging and surgical, pathologic, and clinical findings. We analyzed undesirable clinical or diagnostic outcomes, such as negative appendectomy, perforated appendicitis, more extensive than simple appendectomy, delay in patient management, or incorrect CT diagnosis, which followed appendiceal nonvisualization (defined as grade 0 or 1) and compared the outcomes between the two groups. Results: In the 2-mSv CT and conventional-dose CT groups, appendiceal visualization was rated as grade 0 in 41 (2.7%) and 18 (1.2%) patients, respectively; grade 1 in 181 (11.8%) and 81 (5.3%) patients, respectively; and grade 2 in 1304 (85.0%) and 1421 (92.3%) patients, respectively (p < 0.001). Overall, undesirable outcomes were rare in both groups. Compared to the conventional-dose CT group, the 2-mSv CT group had slightly higher rates of perforated appendicitis (1.1% [17] vs. 0.5% [7], p = 0.06) and false-negative diagnoses (0.4% [6] vs. 0.0% [0], p = 0.01) following appendiceal nonvisualization. Otherwise, these two groups were comparable. Conclusion: The use of 2-mSv CT instead of conventional-dose CT impairs appendiceal visualization in more patients. However, appendiceal nonvisualization on 2-mSv CT rarely leads to undesirable clinical or diagnostic outcomes.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.267-272
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• 2024

Recently, major advanced countries are fostering megacities through policy for reasons such as solving population problems, political and economic issues, and strengthening national competitiveness. The trend of change is accelerating. In Korea, following Seoul and Gyeonggi, mega city policies are being promoted in Busan, Ulsan, Gyeongnam, Daegu and Gyeongbuk, Gwangju and Jeonnam, and Daejeon, Sejong, South Chungcheong and North Chungcheong areas. Due to this urbanization phenomenon, military experts predict that the future battlefield environment will be space or a large city (mega city). From this perspective, Korea will not be able to effectively respond to the threats facing megacities if it does not prepare in advance. Therefore, underground facility operation capabilities optimized for the huge scale of the mega city and the characteristics of the underground operational environment are required. Against this background, the characteristics of the underground operational environment of mega cities and cases of preparation for underground facility operations in advanced military countries such as the United States and Israel were analyzed. Based on this, the capabilities required for underground facility operations suitable for the underground operational environment within Korean megacities are developed from an idea perspective to military organization and combat system, securing special equipment and materials to ensure combatant survival, developing small unit combat techniques, and establishing a training system. It was presented with priority given to.

• Imaging Science in Dentistry
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• v.54 no.1
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• pp.81-91
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• 2024

Purpose: The objective of this study was to propose a deep-learning model for the detection of the mandibular canal on dental panoramic radiographs. Materials and Methods: A total of 2,100 panoramic radiographs (PANs) were collected from 3 different machines: RAYSCAN Alpha (n=700, PAN A), OP-100 (n=700, PAN B), and CS8100 (n=700, PAN C). Initially, an oral and maxillofacial radiologist coarsely annotated the mandibular canals. For deep learning analysis, convolutional neural networks (CNNs) utilizing U-Net architecture were employed for automated canal segmentation. Seven independent networks were trained using training sets representing all possible combinations of the 3 groups. These networks were then assessed using a hold-out test dataset. Results: Among the 7 networks evaluated, the network trained with all 3 available groups achieved an average precision of 90.6%, a recall of 87.4%, and a Dice similarity coefficient (DSC) of 88.9%. The 3 networks trained using each of the 3 possible 2-group combinations also demonstrated reliable performance for mandibular canal segmentation, as follows: 1) PAN A and B exhibited a mean DSC of 87.9%, 2) PAN A and C displayed a mean DSC of 87.8%, and 3) PAN B and C demonstrated a mean DSC of 88.4%. Conclusion: This multi-device study indicated that the examined CNN-based deep learning approach can achieve excellent canal segmentation performance, with a DSC exceeding 88%. Furthermore, the study highlighted the importance of considering the characteristics of panoramic radiographs when developing a robust deep-learning network, rather than depending solely on the size of the dataset.

• Journal of Korea Water Resources Association
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• v.57 no.2
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• pp.73-85
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• 2024

Predicting water quality of rivers and reservoirs is necessary for the management of water resources. Artificial Neural Networks (ANNs) have been used in many studies to predict water quality with high accuracy. Previous studies have used Gradient Descent (GD)-based optimizers as an optimizer, an operator of ANN that searches parameters. However, GD-based optimizers have the disadvantages of the possibility of local optimal convergence and absence of a solution storage and comparison structure. This study developed improved optimizers to overcome the disadvantages of GD-based optimizers. Proposed optimizers are optimizers that combine adaptive moments (Adam) and Nesterov-accelerated adaptive moments (Nadam), which have low learning errors among GD-based optimizers, with Harmony Search (HS) or Novel Self-adaptive Harmony Search (NSHS). To evaluate the performance of Long Short-Term Memory (LSTM) using improved optimizers, the water quality data from the Dasan water quality monitoring station were used for training and prediction. Comparing the learning results, Mean Squared Error (MSE) of LSTM using Nadam combined with NSHS (NadamNSHS) was the lowest at 0.002921. In addition, the prediction rankings according to MSE and R² for the four water quality indices for each optimizer were compared. Comparing the average of ranking for each optimizer, it was confirmed that LSTM using NadamNSHS was the highest at 2.25.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.19-23
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• 2024

Patients with amputations of both hands need prosthetic hands that serve both cosmetic and functional purposes, and research on prosthetic hands using electromyography of remaining muscles is active, but there is still the problem of high cost. In this study, an artificial prosthetic hand was manufactured and its performance was evaluated using low-cost parts and software such as a surface electromyography sensor, machine learning software Edge Impulse, Arduino Nano 33 BLE, and 3D printing. Using signals acquired with surface electromyography sensors and subjected to digital signal processing through Edge Impulse, the flexing movement signals of each finger were transmitted to the fingers of the prosthetic hand model through training to determine the type of finger movement using machine learning. When the digital signal processing conditions were set to a notch filter of 60 Hz, a bandpass filter of 10-300 Hz, and a sampling frequency of 1,000 Hz, the accuracy of machine learning was the highest at 82.1%. The possibility of being confused between each finger flexion movement was highest for the ring finger, with a 44.7% chance of being confused with the movement of the index finger. More research is needed to successfully develop a low-cost prosthetic hand.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.51-60
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• 2024

The purpose of this study is to explore the meaning of the 2018 'Comprehensive Plan for the Vitalization of Democratic Citizenship Education' centered on the '2022 Revised Curriculum General Discussion'. Research Results First, in the case of strengthening democratic citizenship education in schools, one of the main tasks in the general discussion of the 2022 revised curriculum emphasizes democratic citizenship education to cultivate citizenship. are doing Second, in the case of teacher professionalism enhancement and support for educational activities, development of teaching and learning materials and reinforcement of teacher training are promoted in the 2022 revised curriculum summary. Third, in the case of creating a democratic school culture, the 2022 revised curriculum outline guarantees student safety and learning rights through remodeling or remodeling old schools to restructure learning spaces and realize a digital-based learning environment. Fourth, in the case of revitalization of student autonomy, in the general discussion of the 2022 revised curriculum, the autonomy of the school curriculum considering the needs of students and school conditions is expanded, and classes centered on participatory experiences and self-government activities are strengthened. Fifth, in the case of establishing a democratic citizenship education support system, the 2022 revised curriculum outline establishes a mutual cooperation system that respects the roles and expertise of various educational subjects and a mutual cooperation system between the local community and the educational community.

• The Journal of Korean Academy of Sensory Integration
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• v.22 no.1
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• pp.54-68
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• 2024

Purpose : This study aimed to explore the clinical experiences of occupational therapists who have transitioned from adult to child occupational therapy to provide a basis for developing programs to facilitate rapid clinical adjustment for transitioning occupational therapists. Method : Telephone interviews and Colaizzi's phenomenological research method were employed. The interviewees were six occupational therapists with at least three years of clinical experience who had transitioned from hospital-based adult occupational therapy to sensory integration-focused children's occupational therapy. The interviews were recorded, transcribed, and analyzed with the participants' consent. Results : The analysis of the interview transcripts yielded 3 categories, 7 themes, and 17 meanings. The three categories were the challenges facing transitioning occupational therapists in clinical practice, the strengths gained from their post-transition clinical experiences, and the facilitators needed before the transition to ensure quick clinical adjustment. Conclusion : Training and institutional arrangements must be in place to ensure that adult occupational therapists transitioning to sensory integration-focused child occupational therapy can quickly adapt clinically and professionally to their new environments.

• Journal of Korean Home Economics Education Association
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• v.35 no.3
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• pp.135-149
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• 2023

The purpose of this study is to develop and implement an integrated course model that centers around the subject of Home Economics Education Curriculum and Teaching Methods and its pedagogical approaches, as well as the subject of Chinese Language and Literature Curriculum and Teaching Methods and its pedagogical methods. This study aims to provide a framework to prepare pre-service teachers to effectively address a variety of educational issues in future educational settings. To achieve these objectives, the study utilizes Fogarty's connected model as a guiding framework to explore the impact of the integrated curriculum on fostering collaborative and divergent thinking among students. The findings of this research confirm that this model not only cultivates interdisciplinary competencies among course participants but also goes beyond the mere transmission of knowledge to build the capacities needed for forming an educational community, thereby increasing course satisfaction. Additionally, the study substantiates the importance of learner-centered strategies, cooperative learning, and diverse evaluation mechanisms. Such an integrated course model has the potential to revolutionize not only pre-service teacher education but also to be applicable in in-service teacher training, thus contributing to solving a broader range of educational issues.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.125-132
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• 2024

Recently, with immersive virtual reality(IVR) technologies, various services such as education, training, entertainment, industry, healthcare and remote collaboration have been applied. In particular, researches are actively being studied to visualize and interact with virtual humans, research on virtual pets in IVR is also emerging. For interaction with the virtual pet, similar to real-world interaction scenarios, the most important thing is to provide physical contact such as haptic and non-verbal interaction(e.g., gesture). This paper investigates the effects on factors (e.g., shape and texture) of passive haptic feedbacks using mapping physical props corresponding to the virtual pet. Experimental results show significant differences in terms of immersion, co-presence, realism, and friendliness depending on the levels of texture elements when interacting with virtual pets by passive haptic feedback. Additionally, as the main findings of this study by statistical interaction between two variables, we found that there was Uncanny valley effect in terms of friendliness. With our results, we will expect to be able to provide guidelines for creating interactive contents with the virtual pet in immersive VR environments.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.171-178
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• 2024

Exercises using a Balance Board (BB) are effective in developing balance, strengthening core muscles, and improving physical fitness and concentration. In particular, the Smart Balance Board (SBB), which integrates with various digital content, provides appropriate feedback compared to traditional balance boards, maximizing the effectiveness of the exercise. However, most systems only offer visual and auditory feedback, failing to evaluate the impact on user engagement, interest, and the accuracy of exercise postures. This study proposes an Immersive Smart Balance Board (I-SBB) that utilizes multiple sensors to enable training with various feedback mechanisms and precise postures. The proposed system, based on Arduino, consists of a gyro sensor for measuring the board's posture, a communication module for wired/wireless communication, an infrared sensor to guide the user's foot placement, and a vibration motor for tactile feedback. The board's posture measurements are smoothly corrected using a Kalman Filter, and the multi-sensor data is processed in real-time using FreeRTOS. The proposed I-SBB is shown to be effective in enhancing user concentration and engagement, as well as generating interest, by integrating with diverse content.