• Physical Therapy Korea
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• v.28 no.1
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• pp.72-76
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• 2021

Background: A pressure ulcer is common in soft tissue over the greater trochanter (GT) in side-lying position, and sustained tissue deformation induced by the prolonged external force is a primary cause, which can be discussed with soft tissues' viscoelastic properties (i.e., stress relaxation, creep response). Objects: Using an automated hand-held indentation device, we measured the viscoelastic properties of soft tissue over the hip area, in order to examine how the properties are affected by site with respect to the GT. Methods: Twenty participants (15 males and 5 females) who aged from 21 to 32 were participated. An automated hand-held indentation device was used to measure the stress relaxation time and creep response. Trials were acquired for three different locations with respect to the GT (i.e., right over the GT, 6 cm anterior or posterior to the GT). For each location, five trials were acquired and averaged for data analyses. Results: Soft tissues' stress relaxation time and creep response were associated with site (F = 23.98, p < 0.005; F = 24.09, p < 0.005; respectively). The stress relaxation time was greatest at posterior gluteal region (19.22 ± 2.49 ms), and followed by anterior region (15.39 ± 2.47 ms) and right over the GT (14.40 ± 3.18 ms). Similarly, creep response was greatest at posterior gluteal region (1.16 ± 0.14), and followed by anterior region (0.95 ± 0.14) and right over the GT (0.89 ± 0.18). Conclusion: Our results showed that the stress relaxation and creep were greatest at the posterior gluteal region and least at right over the GT, indicating that the gluteal soft tissue is more protective to the prolonged external force, when compared to the trochanteric soft tissue. The results suggest that a risk of pressure ulcer over the GT may decrease with slightly posteriorly rotated side-lying position.

• The Korea Journal of Herbology
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• v.38 no.2
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• pp.35-41
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• 2023

Objectives : Washing face is the first step in skin beauty and health. I wanted to study the cleansing effect by using Placenta cp (cold process) soap. The skin condition is greatly influenced by the external environment such as lifestyle, drinking, smoking, and stress etc. I tried to measure the skin change state without environmental factors. Methods : In order to examine the effect before and after washing face under the same conditions, the same water and towel were used in the same place. The skin test was performed before and 10 minutes after washing. As a control group, a case of washing with water and foam cleanser. I compared and analyzed three cases: water washing, F/C (foam cleanser) washing, and Placenta cp soap washing. Results : In the case of water washing, it was significantly reduced in pores and increased in facial temperature. In the case of F/C washing, the facial temperature was significantly increased, but the decrease in moisture. In the case of washing with Placenta cp soap, significant reductions in T-zone and U-zone oil content, reduction in pore size, and increase in facial skin temperature were observed. Conclusion : In the case of Placenta cp soap, it is thought to be suitable for oily skin type, because of significant decrease in T-zone and U-zone oil content. It is thought to have the effect of increasing blood circulation in the facial skin and to reduce pores for oily skin types.

• Imaging Science in Dentistry
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• v.52 no.4
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• pp.351-357
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• 2022

Purpose: Convolutional neural networks (CNNs) have rapidly emerged as one of the most promising artificial intelligence methods in the field of medical and dental research. CNNs can provide an effective diagnostic methodology allowing for the detection of early-staged diseases. Therefore, this study aimed to evaluate the performance of a deep CNN algorithm for apical lesion segmentation from panoramic radiographs. Materials and Methods: A total of 1000 panoramic images showing apical lesions were separated into training (n=800, 80%), validation (n=100, 10%), and test (n=100, 10%) datasets. The performance of identifying apical lesions was evaluated by calculating the precision, recall, and F1-score. Results: In the test group of 180 apical lesions, 147 lesions were segmented from panoramic radiographs with an intersection over union (IoU) threshold of 0.3. The F1-score values, as a measure of performance, were 0.828, 0.815, and 0.742, respectively, with IoU thresholds of 0.3, 0.4, and 0.5. Conclusion: This study showed the potential utility of a deep learning-guided approach for the segmentation of apical lesions. The deep CNN algorithm using U-Net demonstrated considerably high performance in detecting apical lesions.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2349-2355
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• 2023

In the TRITIUM project, an on-site monitoring system is being developed to measure tritium (³H) levels in water near nuclear power plants. The quite low-energy betas emitted by ³H have a very short average path in water (5 ㎛ as shown by simulations for 18 keV electrons). This path would be further reduced by impurities present in the water, resulting in a significant reduction of the detection efficiency. Therefore, one of the essential requirements of the project is the elimination of these impurities through a filtration process and the removal of salts in solution. This paper describes a water treatment system developed for the project that meets the following requirements: the water produced should be of near-pure water quality according to ISO 3696 grade 3 standard (conductivity < 10 µS/cm); the system should operate autonomously and be remotely monitored.

• Steel and Composite Structures
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• v.51 no.4
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• pp.351-361
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• 2024

Accurate measurement of K_IC values for gas pipeline steels is important for assessing pipe safety using failure assessment diagrams. As direct measurement of K_IC was impossible for the API X70 pipeline steel, multi-specimen fracture tests were conducted to measure J_IC using three-point bend geometry. The J values were calculated from load-displacement (F-δ) plots, and the associated crack extensions were measured from the fracture surface of test specimens. Valid data points were found for the constructed J-Δa plot resulting in J_IC=356kN/m. More data points were added analytically to the J-Δa plot to increase the number of data points without performing additional experiments for different J-Δa zones where test data was unavailable. Consequently, displacement (δ) and crack-growth (Δa) from multi-specimen tests (with small displacements) were used simultaneously, resulting in the variation of Δa-δ (crack growth law) and δ-Δa obtained for this steel. For new Δa values, corresponding δ values were first calculated from δ-Δa. Then, corresponding J values for the obtained δ values were calculated from the area under the F-δ record of a full-fractured specimen (with large displacement). Given Δa and J values for new data points, the developed J-Δa plot with extra data points yielded a satisfactory estimation of J_IC=345kN/m with only a -3.1% error. This is promising and showed that the developed technique could ease the estimation of J_IC significantly and reduce the time and cost of expensive extra fracture toughness tests.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1986-2009
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• 2024

The integration of blockchain technology with the rapid growth of Internet of Things (IoT) devices has enabled secure and decentralised data exchange. However, security vulnerabilities and performance limitations remain significant challenges in IoT blockchain networks. This work proposes a novel approach that combines transaction representation and machine learning techniques to address these challenges. Various clustering techniques, including k-means, DBSCAN, Gaussian Mixture Models (GMM), and Hierarchical clustering, were employed to effectively group unlabelled transaction data based on their intrinsic characteristics. Anomaly transaction prediction models based on classifiers were then developed using the labelled data. Performance metrics such as accuracy, precision, recall, and F1-measure were used to identify the minority class representing specious transactions or security threats. The classifiers were also evaluated on their performance using balanced and unbalanced data. Compared to unbalanced data, balanced data resulted in an overall average improvement of approximately 15.85% in accuracy, 88.76% in precision, 60% in recall, and 74.36% in F1-score. This demonstrates the effectiveness of each classifier as a robust classifier with consistently better predictive performance across various evaluation metrics. Moreover, the k-means and GMM clustering techniques outperformed other techniques in identifying security threats, underscoring the importance of appropriate feature selection and clustering methods. The findings have practical implications for reinforcing security and efficiency in real-world IoT blockchain networks, paving the way for future investigations and advancements.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.1
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• pp.94-97
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• 2014

Purpose: Standardized uptake value (SUV) is a simple semi-quantitative method that can measure the ratio of the tissue radioactivity between the tumor and normal. SUV is commonly used in PET/CT, however, SUV is affected by various factor. The purpose of this study was to evaluate the impact of the residual activity on SUV depending on the location of catheter insertion device post injection. Materials and Methods: NEMA IEC Body Phantom was imaged using a Discovery 600 PET scanner. In 22 mm diameter sphere, the different activity of $^{18}F-FDG$ (7.4, 14.8, 22.2, 29.6, 37, 55.5 MBq) was filled and background was filled with $^{18}F-FDG$ (5.7 kBq/mL). We scaned the phantom on the assumption that the radioactivity in sphere was residual activity in insertion device. Simulation of PET was divided into three groups based on the location of sphere in Scan FOV (SFOV); inclusion, 1/2 inclusion and exclusion group. Results: Among three groups, the group of excluded sphere showed the highest SUV regardless of the amount of $^{18}F-FDG$ activity. In case of 7.4 MBq, average SUV of inclusion group, 1/2 inclusion and exclusion group was 0.780, 0.840 and 0.896 respectively. However, average SUV of 55.5 MBq showed 0.372, 0.460 and 0.508 with same order. Depend on residual radioactivity in the sphere and position of sphere, the SUV was different minimum of 10.4%, maximum of 62.8%. Conclusion: This study showed that SUV is underestimated as the residual radio-activity is increased. In addition, SUV was a changed according to the position of residual radio-activity. And among the position, exclusion group showed the difference of SUV was lowest. If we measure the residual radio-activity of inserting devices and radio-activity from extra-vasation in the patients, it seems to be more useful in clinical field.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.122-126
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• 2010

Purpose: F-18-FPCIT that shows strong familiarity with DAT located at a neural terminal site offers diagnostic information about DAT density state in the region of the striatum especially Parkinson's disease. In this study, we altered the iteration and subset and measured SUV${\pm}$SD and Contrasts from phantom images which set up to specific iteration and subset. So, we are going to suggest the appropriate range of the iteration and subset. Materials and Methods: This study has been performed with 10 normal volunteers who don't have any history of Parkinson's disease or cerebral disease and Flangeless Esser PET Phantom from Data Spectrum Corporation. $5.3{\pm}0.2$ mCi of F-18-FPCIT was injected to the normal group and PET Phantom was assembled by ACR PET Phantom Instructions and it's actual ratio between hot spheres and background was 2.35 to 1. Brain and Phantom images were acquired after 3 hours from the time of the injection and images were acquired for ten minutes. Basically, SIEMENS Bio graph 40 True-point was used and True-X method was applied for image reconstruction method. The iteration and Subset were set to 2 iterations, 8 subsets, 3 iterations, 16 subsets, 6 iterations, 16 subsets, 8 iterations, 16 subsets and 8 iterations, 21 subsets respectively. To measure SUVs on the brain images, ROIs were drawn on the right Putamen. Also, Coefficient of variance (CV) was calculated to indicate the uniformity at each iteration and subset combinations. On the phantom study, we measured the actual ratio between hot spheres and back ground at each combinations. Same size's ROIs were drawn on the same slide and location. Results: Mean SUVs were 10.60, 12.83, 13.87, 13.98 and 13.5 at each combination. The range of fluctuation by sets were 22.36%, 10.34%, 1.1%, and 4.8% respectively. The range of fluctuation of mean SUV was lowest between 6 iterations 16 subsets and 8 iterations 16 subsets. CV showed 9.07%, 11.46%, 13.56%, 14.91% and 19.47% respectively. This means that the numerical value of the iteration and subset gets higher the image's uniformity gets worse. The range of fluctuation of CV by sets were 2.39, 2.1, 1.35, and 4.56. The range of fluctuation of uniformity was lowest between 6 iterations, 16 subsets and 8 iterations, 16 subsets. In the contrast test, it showed 1.92:1, 2.12:1, 2.10:1, 2.13:1 and 2.11:1 at each iteration and subset combinations. A Setting of 8 iterations and 16 subsets reappeared most close ratio between hot spheres and background. Conclusion: Findings on this study, SUVs and uniformity might be calculated differently caused by variable reconstruction parameters like filter or FWHM. Mean SUV and uniformity showed the lowest range of fluctuation at 6 iterations 16 subsets and 8 iterations 16 subsets. Also, 8 iterations 16 subsets showed the nearest hot sphere to background ratio compared with others. But it can not be concluded that only 6 iterations 16 subsets and 8 iterations 16 subsets can make right images for the clinical diagnosis. There might be more factors that can make better images. For more exact clinical diagnosis through the quantitative analysis of DAT density in the region of striatum we need to secure healthy people's quantitative values.

• Horticultural Science & Technology
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• v.34 no.3
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• pp.442-452
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• 2016

Clubroot caused by Plasmodiophra brassicae Woron. is one of the most important diseases in Brassica crops worldwide. To investigate resistance of cabbage to disease caused by P. brassicae isolates, we evaluated development of clubroot on commercial clubroot resistant (CR) and non-CR cultivars, a CR line, and $F_3$ lines from a cross between a CR line and a non-CR line using several isolates of P. brassicae. Four P. brassicae isolates (DJ, HN1, GN1, and YC) were used to measure development of clubroot on 16 non-CR cabbage cultivars that have been commercialized in Korea. Although four P. brassicae isolates induced similar disease severity on non-CR Chinese cabbage, these isolates exhibited different virulence on the cabbage cultivars. The YC isolate was the most virulent, followed by the GN1, HN1, and DJ isolates. Despite differences in virulence of the isolates on the cabbage cultivars, a CR cabbage line 'YCR478' and two CR cabbage cultivars showed high resistance to 12 P. brassicae isolates including DJ, HN1, GN1, and YC. When three isolates (YC, GN1, and DJ) were inoculated onto 107 $F_3$ lines that were derived from a cross between 'YCR478' and a susceptible cabbage line 'C1176', our results showed that 89, 33, and 6 of $F_3$ lines were susceptible to YC, GN1, and DJ isolates, respectively. In aspects of resistance, 6, 36, and 67 of $F_3$ lines exhibited resistant responses to YC, GN1, and DJ isolates, respectively. Taken together, these results suggest that resistance of cabbage to clubroot is likely affected by the virulence of P. brassicae isolates.

• Journal of Dental Rehabilitation and Applied Science
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• v.39 no.4
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• pp.187-194
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• 2023

Purpose: A mismatched size in the post and post space is a common problem during post-fixation. Since this discordance affects the bonding strength of the fiber-reinforced composite resin post (FRC Post), a corresponding luting agent is required. The aim of this study was to evaluate the bonding strength of the FRC post according to the fitness of the fiber post and the type of luting agent. Materials and Methods: Thirty mandibular premolar were endodontic-treated and assigned to two groups according to their prepared post space: Fitting (F) and Mismatching (M). These groups were further classified into three subgroups according to their luting agent: RelyX Unicem (ReX), Luxacore dual (Lux), and Duolink (Duo). A push-out test was performed to measure the push-out bond strengths. The fractured surfaces of each cross-section were then examined, and the fracture modes were classified. Results: In the ReX and Duo subgroups, the F group had a higher mean bond strength; however, the Lux subgroup had no significant difference between the F and M groups. In the analysis of the failure modes, the ReX subgroup had only adhesive failures between the cement and dentin. Conclusion: The result of this study showed that the bond strength of an FRC post was influenced by the type of luting agent and the mismatch between the diameter of the prepared post space and that of the post.