• 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.

• Korean Journal of Radiology
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• v.23 no.3
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• pp.322-332
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• 2022

Objective: CT plays a central role in determining the resectability of pancreatic cancer, which directs the use of neoadjuvant therapy. This study aimed to assess the diagnostic accuracy of CT in predicting circumferential resection margin (CRM) involvement in patients with resectable or borderline resectable pancreatic head cancer. Materials and Methods: Seventy-seven patients who were scheduled for upfront surgery for resectable or borderline resectable pancreatic head cancer were prospectively enrolled, and 75 patients (38 male and 37 female; mean age ± standard deviation, 68 ± 11 years) were finally analyzed. The CRM status was evaluated separately for the superior mesenteric artery (SMA) and posterior and superior mesenteric vein/portal vein (SMV/PV) margins. Three independent radiologists reviewed the preoperative CT images and evaluated the resection margin status. The reference standard for CRM status was pathologic examination of pancreaticoduodenectomy specimens in an axial plane perpendicular to the axis of the second portion of the duodenum. The diagnostic accuracy of CT was assessed for overall CRM involvement, defined as involvement of the SMA or posterior margins (per-patient analysis), and involvement of each of the three resection margins (per-margin analysis). The data were pooled using a crossed random effects model. Results: Forty patients had pathologically confirmed overall CRM involvement in pancreatic cancer, while CRM involvement was not seen in 35 patients. For overall CRM involvement, the pooled sensitivity and specificity were 15% (95% confidence interval: 7%-49%) and 99% (96%-100%), respectively. For each of the resection margins, the pooled sensitivity and specificity were 14% (9%-54%) and 99% (38%-100%) for the SMA margin, 12% (8%-46%) and 99% (97%-100%) for the posterior margin; and 37% (29%-53%) and 96% (31%-100%) for the SMV/PV margin, respectively. Conclusion: CT showed very high specificity but low sensitivity in predicting pathological CRM involvement in pancreatic cancer.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.63-72
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• 2024

The size of the home interior market is growing rapidly as interest in interiors and self-interiors has increased due to the recent rapid increase in single-person households. Most of the Bathroom remodeling is done by requesting an offline interior contractor and then visually checking it in the final completion stage, so it is not easy to re-construct even if the customer is dissatisfied. Therefore, this study developed an immersive virtual reality-based Bathroom self-remodeling system that can visually check space and design from the design stage to the final stage by incorporating VR technology to feel realistic in virtual reality. The bathroom structure may select the basic structure of the predefined bathroom space or freely set the size of the bathroom space. For furniture items, you can choose the washbasin, toilet, bathtub, shower booth that are essential elements of the bathroom and others(mounting rack, trash bin, handle). The tile texture may change the texture of the selected tile at a desired wall position by selecting various textures. In particular,, the texture of the wall tile can be varied by selecting horizontal, vertical and inclined directions at the desired angle according to the needs of the user and the contractor. As a future research project, this system will enable indoor sharing between users who are physically far away in real-time, allowing direct experience in virtual spaces, connection to purchases, and request estimates.

• Information Systems Review
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• v.20 no.2
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• pp.21-37
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• 2018

Under ubiquitous work environment, innovative changes occur in work process with ICT. The work process for collaboration through mobile devices and network should be investigated. The research model consists of two major antecedents: autonomy and interdependence as a task characteristic and job satisfaction as ultimate consequence followed by work design theory. To elaborate work design theory, smartwork application (app) use, communication extent, and work-life balance were reviewed from the literature. Data were collected from three ICT firms, which adopted certain smartwork app, and a partial least squares analysis was made on 175 data points. The analysis results show that task interdependence exerts a statistically significant effect on the level of smartwork app usage. Communication extent directly affects job satisfaction and work-life balance. The remarkable point is that smartwork app usage does not affect employees' work-life balance; the former can only affect the latter indirectly by increasing communication extent. This study attempts to explain the organizational impact by considering smartwork app and the effects simultaneously. We proposed and empirically tested the extended work design theory including information technology and its environment. Based on the results, other theoretical and practical contributions are discussed at the end with limitations and further studies.

• Informatization Policy
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• v.31 no.2
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• pp.82-104
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• 2024

Smart home services are growing rapidly as the development of the Internet of Things (IoT) opens the era of the so-called "Connected Living." Although personal information leaks through smart home cameras are increasing, however, users-while concerned-tend to take passive measures to protect their personal information. This study theoretically explained and verified how to design effective software update notification messages for smart home cameras to ensure that users comply with the recommended security behavior (i.e., update installation). In a survey experiment participated in by 120 actual users, the effectiveness of both emotional appeals (i.e., security breach warning images for fear appeals) and rational appeals (i.e., loss-framed messages emphasizing the negative consequences of not installing the updates) were confirmed. The results of this study provide theoretical interpretations and practical guidelines on the message design features that are effective for threat appraisals (i.e., severity, vulnerability) of smart home camera users and their protection motivation.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.4
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• pp.41-49
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• 2023

This study examined the effect of input substrate concentration on hydrogen production of microbial electrolysis cells. To compare the performance of MEC according to the input substrate concentration, six laboratory-scale MEC reactors were operated by sequentially increasing the input substrate concentration from 2 g/L of sodium acetate, to 4 g/L, and 6 g/L. The current density, hydrogen production, and SCOD removal rate were analyzed, and energy efficiency and cathodic hydrogen recovery were calculated to compare the performance of MEC. The maximum volumetric current density was obtained at 4 g/L condition (76.3 A/m³) and it decreased to 19.0 A/m³, when the input concentration was increased to 6 g/L, which was a 75% decrease compared to the 4 g/L input condition. Maximum hydrogen production was obtained also at 4 g/L condition (47.3 ± 16.8 mL), but maximum hydrogen yield was obtained at 2 g/L input condition (1.1 L H₂/g COD_in). Energy efficiencies were also highest in 2 g/L condition; the lowest result was observed at 6 g/L condition. Maximum electrical energy efficiency was 76.4%, and the maximum overall energy efficiency was 39.7% at 2 g/L condition. However, when the substrate concentration increased to 6 g/L, the performance was drastically decreased. Cathodic hydrogen recovery also showed a similar tendency with energy efficiency, with the lowest concentration condition showing the best performance. It can be concluded that operating at low input substrate concentration might be better when considering not only hydrogen yield but also energy efficiency.

• Journal of the Korean Recycled Construction Resources Institute
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• v.12 no.1
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• pp.63-71
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• 2024

Through the development of construction technology, various construction projects such as redevelopment projects, undergrounding of roads, expansion of subways, and metro railways are being carried out. However, this has led to an increase in the number of construction projects in existing urban centers and neighborhoods, resulting in an increase in the number of damages and disputes between neighboring buildings and residents, as well as an increase in safety accidents due to the aging of existing buildings. In this study, digital data was applied to a graphics program to objectify the progress of cracks by comparing the creation of cracks and the increase in length and width through photographic images and presenting the degree of cracks numerically. Through the application of the program, the error caused by the subjective judgment of crack change, which was mentioned as a shortcoming of the existing field survey, was solved. It is expected that the program can be used universally in the building diagnosis process by improving its reliability if supplemented and improved in the process of use. As a follow-up study, it is necessary to apply the extraction algorithm of the digital graphic data program to calculate the length and width of the crack by itself without human intervention in the preprocessing work and to check the overall change of the building.

• Korean Journal of Radiology
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• v.21 no.10
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• pp.1165-1177
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• 2020

Objective: To assess the feasibility of applying a deep learning-based denoising technique to coronary CT angiography (CCTA) along with iterative reconstruction for additional noise reduction. Materials and Methods: We retrospectively enrolled 82 consecutive patients (male:female = 60:22; mean age, 67.0 ± 10.8 years) who had undergone both CCTA and invasive coronary artery angiography from March 2017 to June 2018. All included patients underwent CCTA with iterative reconstruction (ADMIRE level 3, Siemens Healthineers). We developed a deep learning based denoising technique (ClariCT.AI, ClariPI), which was based on a modified U-net type convolutional neural net model designed to predict the possible occurrence of low-dose noise in the originals. Denoised images were obtained by subtracting the predicted noise from the originals. Image noise, CT attenuation, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were objectively calculated. The edge rise distance (ERD) was measured as an indicator of image sharpness. Two blinded readers subjectively graded the image quality using a 5-point scale. Diagnostic performance of the CCTA was evaluated based on the presence or absence of significant stenosis (≥ 50% lumen reduction). Results: Objective image qualities (original vs. denoised: image noise, 67.22 ± 25.74 vs. 52.64 ± 27.40; SNR [left main], 21.91 ± 6.38 vs. 30.35 ± 10.46; CNR [left main], 23.24 ± 6.52 vs. 31.93 ± 10.72; all p < 0.001) and subjective image quality (2.45 ± 0.62 vs. 3.65 ± 0.60, p < 0.001) improved significantly in the denoised images. The average ERDs of the denoised images were significantly smaller than those of originals (0.98 ± 0.08 vs. 0.09 ± 0.08, p < 0.001). With regard to diagnostic accuracy, no significant differences were observed among paired comparisons. Conclusion: Application of the deep learning technique along with iterative reconstruction can enhance the noise reduction performance with a significant improvement in objective and subjective image qualities of CCTA images.

• 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 the Society of Disaster Information
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• v.20 no.1
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• pp.232-243
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• 2024

Purpose: Recently, large-scale forest fires caused by climate change, natural disasters, and human factors have been increasing every year in the East Coast and Taebaek Mountains region. Although forest fire extinguishing using helicopters is currently increasing, the need to introduce air force transport aircraft has continued to be raised due to the importance of early fire extinguishment to respond to large forest fires and the difficulty of extinguishing forest fires between sheep. This study seeks to present a plan for developing a post-fire management system for several aspects - achieving operational objectives, overcoming the operating environment, selecting a staging area, and efficient operation measures - to efficiently perform forest fire extinguishing missions using Air Force transport aircraft. Method: Based on literature research on forest fire extinguishing, forest fire extinguishing experiments using fixed-wing aircraft, and the operation status and operation method of forest fire extinguishing helicopters, the pros and cons of helicopter operation and the effects of large forest fire extinguishing using a large transport aircraft (C-130) Analyze the effectiveness of operation through analysis. Results: When extinguishing a large forest fire, an effective CM (Consequence Management) application plan was derived, including effective operation, control, command system, dispatch request, and forest fire extinguishment when integrating helicopter and fixed-wing aircraft (C-130). Conclusion: The application of the concept of CM (Consequence Management) is partially applied to some areas of chemical, biological, and radiological (CBRNE) protection in Korea, but efficient operation, control, and command systems are established when integrated operation of helicopters and large aircraft (C-130) in forest fire extinguishment. the concept of CM (Consequence Management), which is operated in advanced countries, was applied for safety management, dispatch requests, and forest fire extinguishing, thereby contributing to the establishment of a more advanced disaster and post-disaster management system.