• Journal of The Korean Society of Integrative Medicine
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• v.10 no.1
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• pp.27-38
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• 2022

Purpose : This study is aimed to develop and validate the clinical practice education program and clinical competence scale of occupational therapy student. Methods : The development of the clinical practice education program used the delphi technique method, which had a total of five steps. Based on the occupational therapist's job analysis, the first stage assessed the importance of 21 experts, and the second stage examined the importance of 19 new specialists to derive constitutive factors. In the third stage, in-depth interviews were conducted with three experts based on the derived factors, and in the fourth stage, the final clinical practice education program was derived. In the final stage, the details of the clinical training program were drawn up based on the themes and were reviewed by two experts. Structured and unstructured interviews were conducted with 43 job experts. Results : The expert survey through the delphi technique was conducted three times, and content analysis and descriptive statistics were conducted to examine the distribution of responses. The final 11 educational program topics and contents were derived. Topics are confirmation of client information, evaluation and intervention, cognitive therapy, spinal cord injury, brain injury, musculoskeletal disorders, pediatric occupational therapy, interventions in activities of daily living, driving rehabilitation, vocational rehabilitation, occupational therapy assessment tool, safety training and management. Conclusion : The clinical practice education program reduce the difference between school education and clinical education of occupational therapy student. Occupational therapy helps college student understand occupational therapy practices and improve the quality of clinical education. Through more research and supplementation of clinical practice education programs in the future, it is suggested that clinical practice education be successfully operated in various practice institutions and used as basic data for designing and evaluating useful educational models.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.51-58
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• 2023

Blockchains have recently struggled to design for the ideal distributed trust networks by solving scalability trilemma. However, local conflicts between some countries lead to imbalance on energy distribution. Besides, blockchain networks (e.g., Bitcoin) currently consume enormous energy for transaction and mining. The existing data volume based trust model evaluated an increasing blockchain size better than Lubin's trust model in scalability trilemma. In this paper, we propose a scalability based energy model to evaluate sustainability for blockchain networks, considering energy consumption for transaction, time duration, and the blockchain size of growing blockchain networks. Through the rigorous numerical analysis, we compare the proposed scalability based energy model with the existing model for the satisfaction and optimal blockchain size. Thus, the scalability based energy model will provide an assessment tool to choose the proper blockchain networks to solve scalability trilemma problem and prove sustainability.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3732-3753
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• 2023

The Real-time Analysis for Particle-transport and In-situ Detection (RAPID) Code System, developed based on the Multi-stage Response-function Transport (MRT) methodology, enables real-time simulation of nuclear systems such as reactor cores, spent nuclear fuel pools and casks, and sub-critical facilities. This paper presents the application of a novel fission matrix-based burnup methodology to the well-characterized JSI TRIGA Mark II research reactor. This methodology allows for calculation of nuclear fuel depletion by combination and interpolation of RAPID's burnup dependent fission matrix (FM) coefficients to take into account core changes due to burnup. The methodology is compared to experimentally validated Serpent-2 Monte Carlo depletion calculations. The results show that the burnup methodology for RAPID (bRAPID) implemented into RAPID is capable of accurately calculating the k_eff burnup changes of the reactor core as the average discrepancies throughout the whole burnup interval are 37 pcm. Furthermore, capability of accurately describing 3D fission source distribution changes with burnup is demonstrated by having less than 1% relative discrepancies compared to Serpent-2. Good agreement is observed for axially and pin-wise dependent fuel burnup and nuclear fuel nuclide composition as a function of burnup. It is demonstrated that bRAPID accurately describes burnup in areas with high gradients of neutron flux (e.g. vicinity of control rods). Observed discrepancies for some isotopes are explained by analyzing the neutron spectrum. This paper presents a powerful depletion calculation tool that is capable of characterization of spent nuclear fuel on the fly while the reactor is in operation.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.95-100
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• 2024

Vitiligo is a condition characterized by the destruction or dysfunction of melanin-producing cells in the skin, resulting in a loss of skin pigmentation. Facial vitiligo, specifically affecting the face, significantly impacts patients' appearance, thereby diminishing their quality of life. Evaluating the efficacy of facial vitiligo treatment typically relies on subjective assessments, such as the Facial Vitiligo Area Scoring Index (F-VASI), which can be time-consuming and subjective due to its reliance on clinical observations like lesion shape and distribution. Various machine learning and deep learning methods have been proposed for segmenting vitiligo areas in facial images, showing promising results. However, these methods often struggle to accurately segment vitiligo lesions irregularly distributed across the face. Therefore, our study introduces a framework aimed at improving the segmentation of vitiligo lesions on the face and providing an evaluation of vitiligo lesions. Our framework for facial vitiligo segmentation and lesion evaluation consists of three main steps. Firstly, we perform face detection to minimize background areas and identify the face area of interest using high-quality ultraviolet photographs. Secondly, we extract facial area masks and vitiligo lesion masks using a semantic segmentation network-based approach with the generated dataset. Thirdly, we automatically calculate the vitiligo area relative to the facial area. We evaluated the performance of facial and vitiligo lesion segmentation using an independent test dataset that was not included in the training and validation, showing excellent results. The framework proposed in this study can serve as a useful tool for evaluating the diagnosis and treatment efficacy of vitiligo.

• The Journal of Internal Korean Medicine
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• v.45 no.1
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• pp.1-10
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• 2024

Objectives: This study investigated the pattern identification (PI) and clinical index of Parkinson's disease (PD) for personalized diagnosis and treatment. Methods: This prospective observational multi-center study recruited 100 patients diagnosed with PD from two Korean medicine hospitals. To cluster new subtypes of PD, items on a PI questionnaire (heat and cold, deficiency and excess, visceral PI) were evaluated along with pulse and tongue analysis. Gait analysis was performed and blood and feces molecular signature changes were assessed to explore biomarkers for new subtypes. In addition, unified PD rating scale II and III scores and the European quality of life 5-dimension questionnaire were assessed. Results: The clinical index obtained in this study analyzed the frequency statistics and hierarchical clustering analysis to classify new subtypes based on PI. Moreover, the biomarkers and current status of herbal medicine treatment were analyzed using the new subtypes. The results provide comprehensive data to investigate new subtypes and subtype-based biomarkers for the personalized diagnosis and treatment of PD patients. Ethical approval was obtained from the medical ethics committees of the two Korean medicine hospitals. All amendments to the research protocol were submitted and approved. Conclusions: An objective and standardized diagnostic tool is needed for the personalized treatment of PD by traditional Korean medicine. Therefore, we developed a clinical index as the basis for the PI clinical evaluation of PD. Trial Registration: This trial is registered with the Clinical Research Information Service (CRIS) (KCT0008677)

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.4
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• pp.27-39
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• 2024

Soil texture is determined by the proportions of sand, silt, and clay within the soil, which influence characteristics such as porosity, water retention capacity, electrical conductivity (EC), and pH. Traditional classification of soil texture requires significant sample preparation including oven drying to remove organic matter and moisture, a process that is both time-consuming and costly. This study aims to explore an alternative method by developing an AI model capable of predicting soil texture from images of pre-sorted soil samples using computer vision and deep learning technologies. Soil samples collected from agricultural fields were pre-processed using sieve analysis and the images of each sample were acquired in a controlled studio environment using a smartphone camera. Color distribution ratios based on RGB values of the images were analyzed using the OpenCV library in Python. A convolutional neural network (CNN) model, built on PyTorch, was enhanced using Digital Image Processing (DIP) techniques and then trained across nine distinct conditions to evaluate its robustness and accuracy. The model has achieved an accuracy of over 80% in classifying the images of pre-sorted soil samples, as validated by the components of the confusion matrix and measurements of the F1 score, demonstrating its potential to replace traditional experimental methods for soil texture classification. By utilizing an easily accessible tool, significant time and cost savings can be expected compared to traditional methods.

• Journal of the Korean Society of Radiology
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• v.82 no.1
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• pp.2-11
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• 2021

More than 4 million women undergo breast cancer (BC) screening with mammography each year in Korea. Digital mammography (DM) was introduced in 2000, and it has been reported to have a higher diagnostic accuracy than screen-film mammography (SFM) or computed radiography (CR) in women with dense breasts. According to a study using data from the National Cancer Screening Program for BC, the diagnostic accuracy of DM was higher than those of SFM and CR, regardless of age, breast density, and screening round. Currently, despite high supply rate among OECD countries, the distribution of DM equipment is approximately 35% in Korea. For quick replacement with DM, it will be necessary to improve its fee for the National Health Insurance and support an educational program for radiologists. In addition, efforts should be made to increase the accessibility of DM.

• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.233-252
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• 2024

This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam's directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures.

• Structural Engineering and Mechanics
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• v.90 no.3
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• pp.253-261
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• 2024

This research explores a new finite element model for the free vibration analysis of bi-directional functionally graded (BDFG) beams. The model is based on an efficient higher-order shear deformation beam theory that incorporates a trigonometric warping function for both transverse shear deformation and stress to guarantee traction-free boundary conditions without the necessity of shear correction factors. The proposed two-node beam element has three degrees of freedom per node, and the inter-element continuity is retained using both C1 and C0 continuities for kinematics variables. In addition, the mechanical properties of the (BDFG) beam vary gradually and smoothly in both the in-plane and out-of-plane beam's directions according to an exponential power-law distribution. The highly elevated performance of the developed model is shown by comparing it to conceptual frameworks and solution procedures. Detailed numerical investigations are also conducted to examine the impact of boundary conditions, the bi-directional gradient indices, and the slenderness ratio on the free vibration response of BDFG beams. The suggested finite element beam model is an excellent potential tool for the design and the mechanical behavior estimation of BDFG structures.