Journal of the Korea Institute of Building Construction
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v.24
no.1
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pp.109-120
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2024
For successful waterproofing construction, it is very important to secure construction quality as well as material performance of waterproofing materials used in construction. Due to the long-term cost reduction policy following the economic downturn in the construction market, most construction companies are using general low-priced waterproof materials rather than high-quality waterproof materials without clear quality control standards. Without clear education on construction, construction is being carried out with meaning only on construction activities. In addition, the waterproofing method applied in combination is a situation where water leakage occurs due to waterproofing failure due to insufficient construction quality because the construction method is complicated. Therefore, it is necessary to review the quality control measures(design, materials, construction) for successful waterproofing work and improve problems that are derived so that stable waterproofing work can be done. In order to expect the leakage prevention effect of a building, first, it is required to select appropriate materials for each part of the building and environment in the design stage, and the selected materials must satisfy all items of the Korean Industrial Standard(KS). Second, to secure the quality of waterproofing construction, sincere construction by workers is required. In this paper, we tried to describe "review of waterproof design", "constructor education", "site inspection", and "criticism(correction/supplementation)" as quality control measures after material selection.
Suiji Lee;Chong Hyun Suh;Sungyang Jo;Sun Ju Chung;Hwon Heo;Woo Hyun Shim;Jongho Lee;Ho Sung Kim;Sang Joon Kim;Eung Yeop Kim
Korean Journal of Radiology
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v.25
no.3
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pp.267-276
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2024
Objective: To evaluate the diagnostic performance of susceptibility map-weighted imaging (SMwI) taken in different acquisition planes for discriminating patients with neurodegenerative parkinsonism from those without. Materials and Methods: This retrospective, observational, single-institution study enrolled consecutive patients who visited movement disorder clinics and underwent brain MRI and 18F-FP-CIT PET between September 2021 and December 2021. SMwI images were acquired in both the oblique (perpendicular to the midbrain) and the anterior commissure-posterior commissure (AC-PC) planes. Hyperintensity in the substantia nigra was determined by two neuroradiologists. 18F-FP-CIT PET was used as the reference standard. Inter-rater agreement was assessed using Cohen;s kappa coefficient. The diagnostic performance of SMwI in the two planes was analyzed separately for the right and left substantia nigra. Multivariable logistic regression analysis with generalized estimating equations was applied to compare the diagnostic performance of the two planes. Results: In total, 194 patients were included, of whom 105 and 103 had positive results on 18F-FP-CIT PET in the left and right substantia nigra, respectively. Good inter-rater agreement in the oblique (κ = 0.772/0.658 for left/right) and AC-PC planes (0.730/0.741 for left/right) was confirmed. The pooled sensitivities for two readers were 86.4% (178/206, left) and 83.3% (175/210, right) in the oblique plane and 87.4% (180/206, left) and 87.6% (184/210, right) in the AC-PC plane. The pooled specificities for two readers were 83.5% (152/182, left) and 82.0% (146/178, right) in the oblique plane, and 83.5% (152/182, left) and 86.0% (153/178, right) in the AC-PC plane. There were no significant differences in the diagnostic performance between the two planes (P > 0.05). Conclusion: There are no significant difference in the diagnostic performance of SMwI performed in the oblique and AC-PC plane in discriminating patients with parkinsonism from those without. This finding affirms that each institution may choose the imaging plane for SMwI according to their clinical settings.
Sangjoon Park;Jong Chul Ye;Eun Sun Lee;Gyeongme Cho;Jin Woo Yoon;Joo Hyeok Choi;Ijin Joo;Yoon Jin Lee
Korean Journal of Radiology
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v.24
no.6
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pp.541-552
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2023
Objective: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using supine and erect abdominal radiography. Materials and Methods: A model that can utilize "pneumoperitoneum" and "non-pneumoperitoneum" classes was developed through knowledge distillation. To train the proposed model with limited training data and weak labels, it was trained using a recently proposed semi-supervised learning method called distillation for self-supervised and self-train learning (DISTL), which leverages the Vision Transformer. The proposed model was first pre-trained with chest radiographs to utilize common knowledge between modalities, fine-tuned, and self-trained on labeled and unlabeled abdominal radiographs. The proposed model was trained using data from supine and erect abdominal radiographs. In total, 191212 chest radiographs (CheXpert data) were used for pre-training, and 5518 labeled and 16671 unlabeled abdominal radiographs were used for fine-tuning and self-supervised learning, respectively. The proposed model was internally validated on 389 abdominal radiographs and externally validated on 475 and 798 abdominal radiographs from the two institutions. We evaluated the performance in diagnosing pneumoperitoneum using the area under the receiver operating characteristic curve (AUC) and compared it with that of radiologists. Results: In the internal validation, the proposed model had an AUC, sensitivity, and specificity of 0.881, 85.4%, and 73.3% and 0.968, 91.1, and 95.0 for supine and erect positions, respectively. In the external validation at the two institutions, the AUCs were 0.835 and 0.852 for the supine position and 0.909 and 0.944 for the erect position. In the reader study, the readers' performances improved with the assistance of the proposed model. Conclusion: The proposed model trained with the DISTL method can accurately detect pneumoperitoneum on abdominal radiography in both the supine and erect positions.
Younjung Choi;Sun Mi Kim;Mijung Jang;Bo La Yun;Eunyoung Kang;Eun-Kyu Kim;So Yeon Park;Bohyoung Kim;Nariya Cho;Woo Kyung Moon
Korean Journal of Radiology
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v.23
no.9
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pp.866-877
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2022
Objective: The optimal imaging approach for evaluating pathological nipple discharge remains unclear. We investigated the value of adding ductography to ultrasound (US) for evaluating pathologic nipple discharge in patients with negative mammography findings. Materials and Methods: From July 2003 to December 2018, 101 women (mean age, 46.3 ± 12.2 years; range, 23-75 years) with pathologic nipple discharge were evaluated using pre-ductography (initial) US, ductography, and post-ductography US. The imaging findings were reviewed retrospectively. The standard reference was surgery (70 patients) or > 2 years of follow-up with US (31 patients). The diagnostic performances of initial US, ductography, and post-ductography US for detecting malignancy were compared using the McNemar's test or a generalized estimating equation. Results: In total, 47 papillomas, 30 other benign lesions, seven high-risk lesions, and 17 malignant lesions were identified as underlying causes of pathologic nipple discharge. Only eight of the 17 malignancies were detected on the initial US, while the remaining nine malignancies were detected by ductography. Among the nine malignancies detected by ductography, eight were detected on post-ductography US and could be localized for US-guided intervention. The sensitivities of ductography (94.1% [16/17]) and post-ductography US (94.1% [16/17]) were significantly higher than those of initial US (47.1% [8/17]; p = 0.027 and 0.013, respectively). The negative predictive value of post-ductography US (96.9% [31/32]) was significantly higher than that of the initial US (83.3% [45/54]; p = 0.006). Specificity was significantly higher for initial US than for ductography and post-ductography US (p = 0.001 for all). Conclusion: The combined use of ductography and US has a high sensitivity for detecting malignancy in patients with pathologic nipple discharge and negative mammography. Ductography findings enable lesion localization on second-look post-ductography US, thus facilitating the selection of optimal treatment plans.
Dong Wook Kim;Hyemin Ahn;Kyung Won Kim;Seung Soo Lee;Hwa Jung Kim;Yousun Ko;Taeyong Park;Jeongjin Lee
Korean Journal of Radiology
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v.23
no.11
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pp.1055-1066
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2022
Objective: The clinical relevance of myosteatosis has not been well evaluated in patients with pancreatic ductal adenocarcinoma (PDAC), although sarcopenia has been extensively researched. Therefore, we evaluated the prognostic value of muscle quality, including myosteatosis, in patients with resectable PDAC treated surgically. Materials and Methods: We retrospectively evaluated 347 patients with resectable PDAC who underwent curative surgery (mean age ± standard deviation, 63.6 ± 9.6 years; 202 male). Automatic muscle segmentation was performed on preoperative computed tomography (CT) images using an artificial intelligence program. A single axial image of the portal phase at the inferior endplate level of the L3 vertebra was used for analysis in each patient. Sarcopenia was evaluated using the skeletal muscle index, calculated as the skeletal muscle area (SMA) divided by the height squared. The mean SMA attenuation was used to evaluate myosteatosis. Diagnostic cutoff values for sarcopenia and myosteatosis were devised using the Contal and O'Quigley methods, and patients were classified according to normal (nMT), sarcopenic (sMT), myosteatotic (mMT), or combined (cMT) muscle quality types. Multivariable Cox regression analyses were conducted to assess the effects of muscle type on the overall survival (OS) and recurrence-free survival (RFS) after surgery. Results: Eighty-four (24.2%), 73 (21.0%), 75 (21.6%), and 115 (33.1%) patients were classified as having nMT, sMT, mMT, and cMT, respectively. Compared to nMT, mMT and cMT were significantly associated with poorer OS, with hazard ratios (HRs) of 1.49 (95% confidence interval, 1.00-2.22) and 1.68 (1.16-2.43), respectively, while sMT was not (HR of 1.40 [0.94-2.10]). Only mMT was significantly associated with poorer RFS, with an HR of 1.59 (1.07-2.35), while sMT and cMT were not. Conclusion: Myosteatosis was associated with poor OS and RFS in patients with resectable PDAC who underwent curative surgery.
The social network service (SNS) is one of the important marketing channels, so many companies actively exploit SNSs by posting SNS messages with appropriate content and style for their customers. In this paper, we focused on the psychological distances embedded in the SNS messages and developed a method to measure the psychological distance in SNS message by mixing a traditional content analysis, natural language processing (NLP), and machine learning. Through a traditional content analysis by human coding, the psychological distance was extracted from the SNS message, and these coding results were used for input data for NLP and machine learning. With NLP, word embedding was executed and Bag of Word was created. The Support Vector Machine, one of machine learning techniques was performed to train and test the psychological distance in SNS message. As a result, sensitivity and precision of SVM prediction were significantly low because of the extreme skewness of dataset. We improved the performance of SVM by balancing the ratio of data by upsampling technique and using data coded with the same value in first content analysis. All performance index was more than 70%, which showed that psychological distance can be measured well.
Journal of the Korean Society of Earth Science Education
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v.17
no.1
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pp.34-48
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2024
With the global rise in interest in competency-based education, the Ministry of Education of the Republic of Korea outlined six core competencies in the 2015 revised curriculum, essential for future society's 'creative and convergent talent'. This study introduces an HTE-STEAM constellation education program designed to develop the core competencies outlined in the 2015 revised curriculum and address the limitations of hands-on astronomy education. The program's effectiveness was assessed through a pilot test. The program was implemented at G Library, an out-of-school education site in Cheongju-si, Chungcheongbuk-do, targeting students from 3rd to 6th grade. The study's results include: First, the HTE-STEAM program significantly impacted all aspects of the STEAM attitude test except for 'self-concept', particularly influencing 'science and engineering career choice', 'consideration', and 'communication'. Thus, it has led to positive outcomes in the cultivation of future society's core competencies, including 'creative thinking skills', 'communication skills', and 'community skills'. Secondly, the HTE-STEAM constellation education program, despite covering the challenging concept of spacetime, was deemed easy by many students. Observations of students applying the spatial concepts they learned by using teaching aids suggest that the program was effective in enhancing students' understanding of the spatial structure of the sky and the universe. Additionally, this program aligns with the 2022 curriculum's updated standards for understanding the sky's spatial structure. Consequently, the HTE-STEAM constellation education program positively cultivates future society's core competencies and serves as a valuable complement to night observation practices in schools.
Jae-young Park;Jung Hwan Lee;Mo-Yeol Kang;Tae-Won Jang;Hyoung-Ryoul Kim;Se-Yeong Kim;Jongin Lee
Annals of Occupational and Environmental Medicine
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v.35
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pp.24.1-24.15
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2023
Background: The construction workers are vulnerable to fatigue due to high physical workload. This study aimed to investigate the relationship between overwork and heart rate in construction workers and propose a scheme to prevent overwork in advance. Methods: We measured the heart rates of construction workers at a construction site of a residential and commercial complex in Seoul from August to October 2021 and develop an index that monitors overwork in real-time. A total of 66 Korean workers participated in the study, wearing real-time heart rate monitoring equipment. The relative heart rate (RHR) was calculated using the minimum and maximum heart rates, and the maximum acceptable working time (MAWT) was estimated using RHR to calculate the workload. The overwork index (OI) was defined as the cumulative workload evaluated with the MAWT. An appropriate scenario line (PSL) was set as an index that can be compared to the OI to evaluate the degree of overwork in real-time. The excess overwork index (EOI) was evaluated in real-time during work performance using the difference between the OI and the PSL. The EOI value was used to perform receiver operating characteristic (ROC) curve analysis to find the optimal cut-off value for classification of overwork state. Results: Of the 60 participants analyzed, 28 (46.7%) were classified as the overwork group based on their RHR. ROC curve analysis showed that the EOI was a good predictor of overwork, with an area under the curve of 0.824. The optimal cut-off values ranged from 21.8% to 24.0% depending on the method used to determine the cut-off point. Conclusion: The EOI showed promising results as a predictive tool to assess overwork in real-time using heart rate monitoring and calculation through MAWT. Further research is needed to assess physical workload accurately and determine cut-off values across industries.
Han Kyu Chae;Nayoung Suh;Myong Jin Jang;Yu Seon Kim;Bo Hyun Kim;Joomin Aum;Ha Chul Shin;Dalsan You;Bumsik Hong;Hyung Keun Park;Choung-Soo Kim
International Journal of Stem Cells
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v.16
no.1
/
pp.66-77
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2023
Background and Objectives: We compared the efficacy and safety of human bone marrow-derived mesenchymal stem cells (hBMSC), delivered at different doses and via different injection routes in an animal model of chronic kidney disease. Methods and Results: A total of ninety 12-week-old rats underwent 5/6 nephrectomy and randomized among nine groups: sham, renal artery control (RA-C), tail vein control (TV-C), renal artery low dose (RA-LD) (0.5×106 cells), renal artery moderate dose (RA-MD) (1.0×106 cells), renal artery high dose (RA-HD) (2.0×106 cells), tail vein low dose (TV-LD) (0.5×106 cells), tail vein moderate dose (TV-MD) (1.0×106 cells), and tail vein high dose (TV-HD) (2.0×106 cells). Renal function and mortality of rats were evaluated after hBMSC injection. Serum blood urea nitrogen was significantly lower in the TV-HD group at 2 weeks (p<0.01), 16 weeks (p<0.05), and 24 weeks (p<0.01) than in the TV-C group, as determined by one-way ANOVA. Serum creatinine was significantly lower in the TV-HD group at 24 weeks (p<0.05). At 8 weeks, creatinine clearance was significantly higher in the TV-MD and TV-HD groups (p<0.01, p<0.05) than in the TV-C group. In the safety evaluation, we observed no significant difference among the groups. Conclusions: Our findings confirm the efficacy and safety of high dose (2×106 cells) injection of hBMSC via the tail vein.
Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.
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