• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.776-781
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• 2023

K-UAM will be commercialized through maturity after 2035. Since the Urban Air Mobility (UAM) corridor will be used vertically separating the existing helicopter corridor, the corridor usage is expected to increase. Therefore, a system for monitoring corridors is also needed. In recent years, object detection algorithms have developed significantly. Object detection algorithms are largely divided into one-stage model and two-stage model. In real-time detection, the two-stage model is not suitable for being too slow. One-stage models also had problems with accuracy, but they have improved performance through version upgrades. Among them, YOLO-V5 improved small image object detection performance through Mosaic. Therefore, YOLO-V5 is the most suitable algorithm for systems that require real-time monitoring of wide corridors. Therefore, this paper trains YOLO-V5 and analyzes whether it is ultimately suitable for corridor monitoring.K-uam will be commercialized through maturity after 2035.

• Tuberculosis and Respiratory Diseases
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• v.87 no.1
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• pp.80-90
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• 2024

Background: There are many methods of evaluating diaphragmatic function, including trans-diaphragmatic pressure measurements, which are considered the key rule of diagnosis. We studied the clinical usefulness of chest ultrasonography in evaluating stable chronic obstructive pulmonary disease (COPD) patients and those in exacerbation, focusing on diaphragmatic measurements and their correlation with spirometry and other clinical parameters. Methods: In a prospective case-control study, we enrolled 100 COPD patients divided into 40 stable COPD patients and 60 patients with exacerbation. The analysis included 20 age-matched controls. In addition to the clinical assessment of the study population, radiological evaluation included chest radiographs and chest computed tomography. Transthoracic ultrasonography (TUS) was performed for all included subjects. Results: Multiple A lines (more than 3) were more frequent in COPD exacerbation than in stable patients, as was the case for B-lines. TUS significantly showed high specificity, negative predictive value, positive predictive value, and accuracy in detecting pleural effusion, consolidation, pneumothorax, and lung mass. Diaphragmatic measurements were significantly lower among stable COPD subjects than healthy controls. Diaphragmatic thickness and excursion displayed a significant negative correlation with body mass index and the dyspnea scale, and a positive correlation with spirometry measures. Patients in Global Initiative for Chronic Obstructive Lung Disease (GOLD) group D showed lower diaphragmatic measurements (thickness and excursion). Conclusion: The TUS of COPD patients both in stable and exacerbated conditions and the assessment of diaphragm excursion and thickness by TUS in COPD patients and their correlations to disease-related factors proved informative and paved the way for the better management of COPD patients.

• Imaging Science in Dentistry
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• v.54 no.2
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• pp.171-180
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• 2024

Purpose: This study was conducted to identify the typical sites and patterns of peri-implant bone defects on cone-beam computed tomography (CBCT) images, as well as to evaluate the detectability of the identified bone defects on panoramic images. Materials and Methods: The study population included 114 patients with a total of 367 implant fixtures. CBCT images were used to assess the presence or absence of bone defects around each implant fixture at the mesial, distal, buccal, and lingual sites. Based on the number of defect sites, the presentations of the peri-implant bone defects were categorized into 3 patterns: 1 site, 2 or 3 sites, and circumferential bone defects. Two observers independently evaluated the presence or absence of bone defects on panoramic images. The bone defect detection rate on these images was evaluated using receiver operating characteristic analysis. Results: Of the 367 implants studied, 167 (45.5%) had at least 1 site with a confirmed bone defect. The most common type of defect was circumferential, affecting 107 of the 167 implants(64.1%). Implants were most frequently placed in the mandibular molar region. The prevalence of bone defects was greatest in the maxillary premolar and mandibular molar regions. The highest kappa value was associated with the mandibular premolar region. Conclusion: The typical bone defect pattern observed was a circumferential defect surrounding the implant. The detection rate was generally higher in the molar region than in the anterior region. However, the capacity to detect partial bone defects using panoramic imaging was determined to be poor.

• Clinical Endoscopy
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• v.56 no.3
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• pp.353-366
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• 2023

Background/Aims: This study aimed to clarify the efficacy and safety of pancreatic duct lavage cytology combined with a cell-block method (PLC-CB) for possible pancreatic ductal adenocarcinomas (PDACs). Methods: This study included 41 patients with suspected PDACs who underwent PLC-CB mainly because they were unfit for undergoing endoscopic ultrasonography-guided fine needle aspiration. A 6-Fr double lumen catheter was mainly used to perform PLC-CB. Final diagnoses were obtained from the findings of resected specimens or clinical outcomes during surveillance after PLC-CB. Results: Histocytological evaluations using PLC-CB were performed in 87.8% (36/41) of the patients. For 31 of the 36 patients, final diagnoses (invasive PDAC, 12; pancreatic carcinoma in situ, 5; benignancy, 14) were made, and the remaining five patients were excluded due to lack of surveillance periods after PLC-CB. For 31 patients, the sensitivity, specificity, and accuracy of PLC-CB for detecting malignancy were 94.1%, 100%, and 96.8%, respectively. In addition, they were 87.5%, 100%, and 94.1%, respectively, in 17 patients without pancreatic masses detectable using endoscopic ultrasonography. Four patients developed postprocedural pancreatitis, which improved with conservative therapy. Conclusions: PLC-CB has an excellent ability to detect malignancies in patients with possible PDACs, including pancreatic carcinoma in situ.

• Journal of Sensor Science and Technology
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• v.33 no.2
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• pp.112-116
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• 2024

Gas-sensor technology for volatile organic compounds (VOC) biomarker detection offers significant advantages for noninvasive diagnostics, including rapid response time and low operational costs, exhibiting promising potential for disease diagnosis. Colorimetric gas sensors, which enable intuitive analysis of gas concentrations through changes in color, present additional benefits for the development of personal diagnostic kits. However, the traditional method of visually monitoring these sensors can limit quantitative analysis and consistency in detection threshold evaluation, potentially affecting diagnostic accuracy. To address this, we developed a machine vision platform based on metal-organic framework (MOF) for colorimetric gas sensor arrays, designed to accurately detect disease-related VOC biomarkers. This platform integrates a CMOS camera module, gas chamber, and colorimetric MOF sensor jig to quantitatively assess color changes. A specialized machine vision algorithm accurately identifies the color-change Region of Interest (ROI) from the captured images and monitors the color trends. Performance evaluation was conducted through experiments using a platform with four types of low-concentration standard gases. A limit-of-detection (LoD) at 100 ppb level was observed. This approach significantly enhances the potential for non-invasive and accurate disease diagnosis by detecting low-concentration VOC biomarkers and offers a novel diagnostic tool.

• Food Science of Animal Resources
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• v.44 no.4
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• pp.873-884
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• 2024

Flunixin is a veterinary nonsteroidal anti-inflammatory agent whose residues have been investigated in their original form within tissues such as muscle and liver. However, flunixin remains in milk as a metabolite, and 5-hydroxy flunixin has been used as the primary marker for its surveillance. This study aimed to develop a quantitative method for detecting flunixin and 5-hydroxy flunixin in milk and to strengthen the monitoring system by applying to other livestock and fishery products. Two different methods were compared, and the target compounds were extracted from milk using an organic solvent, purified with C₁₈, concentrated, and reconstituted using a methanol-based solvent. Following filtering, the final sample was analyzed using liquid chromatography-tandem mass spectrometry. Method 1 is environmentally friendly due to the low use of reagents and is based on a multi-residue, multi-class analysis method approved by the Ministry of Food and Drug Safety. The accuracy and precision of both methods were 84.6%-115% and 0.7%-9.3%, respectively. Owing to the low matrix effect in milk and its convenience, Method 1 was evaluated for other matrices (beef, chicken, egg, flatfish, and shrimp) and its recovery and coefficient of variation are sufficient according to the Codex criteria (CAC/GL 71-2009). The limits of detection and quantification were 2-8 and 5-27 ㎍/kg for flunixin and 2-10 and 6-33 ㎍/kg for 5-hydroxy flunixin, respectively. This study can be used as a monitoring method for a positive list system that regulates veterinary drug residues for all livestock and fisheries products.

• Smart Structures and Systems
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• v.33 no.2
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• pp.93-103
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• 2024

Despite the rapid development of sensors, structural health monitoring (SHM) still faces challenges in monitoring due to the degradation of devices and harsh environmental loads. These challenges can lead to measurement errors, missing data, or outliers, which can affect the accuracy and reliability of SHM systems. To address this problem, this study proposes a classification method that detects anomaly patterns in sensor data. The proposed classification method involves several steps. First, data scaling is conducted to adjust the scale of the raw data, which may have different magnitudes and ranges. This step ensures that the data is on the same scale, facilitating the comparison of data across different sensors. Next, informative features in the time and frequency domains are extracted and used as input for a deep neural network model. The model can effectively detect the most probable anomaly pattern, allowing for the timely identification of potential issues. To demonstrate the effectiveness of the proposed method, it was applied to actual data obtained from a long-span cable-stayed bridge in China. The results of the study have successfully verified the proposed method's applicability to practical SHM systems for civil infrastructures. The method has the potential to significantly enhance the safety and reliability of civil infrastructures by detecting potential issues and anomalies at an early stage.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.2
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• pp.79-87
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• 2024

Purpose: Recently, the prevalence of eosinophilic gastrointestinal disease (EGID) has shown an increasing trend worldwide. As the diagnosis of EGID requires invasive endoscopy with biopsy, noninvasive markers for detecting EGID in suspected patients, particularly children, are urgently needed. Therefore, this study aimed to evaluate the diagnostic accuracy of serum eosinophil cationic protein (ECP) beyond peripheral eosinophil counts in pediatric patients with EGID. Methods: Overall, 156 children diagnosed with EGID were enrolled and 150 children with functional abdominal pain disorder (FAPD) were recruited as controls. All participants underwent endoscopic biopsy in each segment of the gastrointestinal (GI) tract and serum ECP measurement, as well as peripheral eosinophil percent and absolute eosinophil count. Results: Comparing EGID (n=156) with FAPD (n=150) patients, serum ECP levels were significantly higher in pediatric patients with EGID than in those with FAPD (25.8±28.6 ㎍/L vs. 19.5±21.0 ㎍/L, p=0.007), while there was no significant difference in peripheral eosinophil percent and absolute eosinophil counts between the two groups. Serum ECP levels were correlated with peripheral eosinophil percent (r=0.593, p<0.001) and the absolute eosinophil count (r=0.660, p<0.001). The optimal cutoff value of serum ECP for pediatric EGID was 10.5 ㎍/mL, with a sensitivity of 69.9% and a specificity of 43.4% with an area under the receiver operating characteristic curve of 0.562. Conclusion: The combination of serum ECP levels and peripheral eosinophil counts, when employed with appropriated thresholds, could serve as a valuable noninvasive biomarker to distinguish between EGID and FAPD in pediatric patients manifesting GI symptoms.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.36-44
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• 2024

This paper presents the application of Convolutional Neural Networks (CNNs) and Region of Interest (ROI) techniques for concrete crack analysis. Surfaces of concrete structures, such as beams, etc., are exposed to fatigue stress and cyclic loads, typically resulting in the initiation of cracks at a microscopic level on the structure's surface. Early detection enables preventative measures to mitigate potential damage and failures. Conventional manual inspections often yield subpar results, especially for large-scale infrastructure where access is challenging and detecting cracks can be difficult. This paper presents data collection, edge segmentation and ROI techniques application, and analysis of concrete cracks using Convolutional Neural Networks. This paper aims to achieve the following objectives: Firstly, achieving improved accuracy in crack detection using image-based technology compared to traditional manual inspection methods. Secondly, developing an algorithm that utilizes enhanced Sobel edge segmentation and ROI techniques. The algorithm provides automated crack detection capabilities for non-destructive testing.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.589-599
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• 2024

This study presents the usability of the high-rate single-frequency Precise Point Positioning (SF-PPP) technique based on 20 Hz Global Positioning Systems (GPS)-only observations in detecting dynamic motions. SF-PPP solutions were obtained from post-mission and real-time GNSS corrections. These include the International GNSS Service (IGS)-Final, IGS real-time (RT), real-time MADOCA (Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis), and real-time products from the Australian/New Zealand satellite-based augmentation systems (SBAS, known as SouthPAN). SF-PPP results were compared with LVDT (Linear Variable Differential Transformer) sensor and single-frequency relative positioning (SF-RP) solutions. The findings show that the SF-PPP technique successfully detects the harmonic motions, and the real-time products-based PPP solutions were as accurate as the final post-mission products. In the frequency domain, all GNSS-based methods evaluated in this contribution correctly detect the dominant frequency of short-term harmonic oscillations, while the differences in the amplitude values corresponding to the peak frequency do not exceed 1.1 mm. However, evaluations in the time domain show that SF-PPP needs high-pass filtering to detect accurate displacement since SF-PPP solutions include trends and low-frequency fluctuations, mainly due to atmospheric effects. Findings obtained in the time domain indicate that final, real-time, and MADOCA-based PPP results capture short-term dynamic behaviors with an accuracy ranging from 3.4 mm to 8.5 mm, and SBAS-based PPP solutions have several times higher RMSE values compared to other methods. However, after high-pass filtering, the accuracies obtained from PPP methods decreased to a few mm. The outcomes demonstrate the potential of the high-rate SF-PPP method to reliably monitor structural and earthquake-induced ground motions and vibration frequencies of structures.