• The Journal of Engineering Geology
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• v.5 no.3
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• pp.277-288
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• 1995

Fracture detection has always been very attractive to the log, because it is important in many of our prospecting activities, e.g. in understanding the underground rock formation and also the fluid flow as a high permeability path. This paper demonstrates the use of high resolution borehole acoustic scanner for the detection of fractures. The tool, known as Televiewer, is the first acoustic borehole imaging system to use a focussed beam. The acoustic beams generated by a single transducer are sent toward the borehole wall, scanning the wall in a tight helix as the tool moves along the borehole. The amplitudes and travel times of the reflected signals are then measured, which produces the corresponding images. The highly resolved amplitude image allows to recognize various size of fractures and in addition to derive the rock strength from the image. Meanwhile, the travel time image itself can be directly converted to a precise caliper image, providing detailed information of deviations of the borehole shape. It also allows correction of and explanations for amplitude variations. Field measurements were carried Out at the Cheongyang study sites in Korea to illustrate the efficiency of the televiewer log.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.891-899
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• 2020

Objective: To assess the diagnostic performance of a deep learning-based algorithm for automated detection of acute and chronic rib fractures on whole-body trauma CT. Materials and Methods: We retrospectively identified all whole-body trauma CT scans referred from the emergency department of our hospital from January to December 2018 (n = 511). Scans were categorized as positive (n = 159) or negative (n = 352) for rib fractures according to the clinically approved written CT reports, which served as the index test. The bone kernel series (1.5-mm slice thickness) served as an input for a detection prototype algorithm trained to detect both acute and chronic rib fractures based on a deep convolutional neural network. It had previously been trained on an independent sample from eight other institutions (n = 11455). Results: All CTs except one were successfully processed (510/511). The algorithm achieved a sensitivity of 87.4% and specificity of 91.5% on a per-examination level [per CT scan: rib fracture(s): yes/no]. There were 0.16 false-positives per examination (= 81/510). On a per-finding level, there were 587 true-positive findings (sensitivity: 65.7%) and 307 false-negatives. Furthermore, 97 true rib fractures were detected that were not mentioned in the written CT reports. A major factor associated with correct detection was displacement. Conclusion: We found good performance of a deep learning-based prototype algorithm detecting rib fractures on trauma CT on a per-examination level at a low rate of false-positives per case. A potential area for clinical application is its use as a screening tool to avoid false-negative radiology reports.

• Imaging Science in Dentistry
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• v.54 no.2
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• pp.139-145
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• 2024

Purpose: This study examined the influence of a metal artifact reduction (MAR) tool, sharpening filters, and their combination on the diagnosis of vertical root fracture (VRF) in teeth with metallic posts using cone-beam computed tomography (CBCT). Materials and Methods: Twenty single-rooted human premolars - 9 with VRF and 11 without - were individually placed in a human mandible. A metallic post composed of a cobalt-chromium alloy was inserted into the root canal of each tooth. CBCT scans were then acquired under the following parameters: 8 mA, a 5×5 cm field of view, a voxel size of 0.085 mm, 90 kVp, and with MAR either enabled or disabled. Five oral and maxillofacial radiologists independently evaluated the CBCT exams under each MAR mode and across 3 sharpening filter conditions: no filter, Sharpen 1×, and Sharpen 2×. The diagnostic performance was quantified by the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. These metrics were compared using 2-way analysis of variance with a significance level of α=5%. Intra- and inter-examiner agreement were assessed using the weighted kappa test. Results: Neither MAR nor the application of sharpening filters significantly impacted AUC or specificity (P>0.05). However, sensitivity increased when MAR was combined with Sharpen 1× and Sharpen 2× (P=0.015). The intra-examiner agreement ranged from fair to substantial (0.34-0.66), while the inter-examiner agreement ranged from fair to moderate (0.27-0.41). Conclusion: MAR in conjunction with sharpening filters improved VRF detection; therefore, their combined use is recommended in cases of suspected VRF.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.6
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• pp.988-994
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• 1997

The demands for robotic and automatic system are continually increasing in manufacturing fields. There have been many studies to monitor and predict the system, but they have mainly focused upon measuring cutting force, and current of motor spindle, and upon using acoustic sensor, etc. In this study, digital image of time series sequence was acquired by taking advantage of optical technique. Mean square error was obtained from it and was available for useful observation data. The parameter was estimated using PAA(parameter adaptation algorithm) from observation data. AR(auto regressive) model was selected for system model and fifth order was decided according to parameter estimation. Uncorrelation test was also carried out to verify convergence of parameter. Through the proceedings, it was found that there was a system stability.

• Journal of the Korean Society for Nondestructive Testing
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• v.22 no.6
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• pp.609-620
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• 2002

It is well known that during tensile testing, a part of the mechanical work done on the specimen is transformed into heat energy. However, the ultimate temperature rise and the rate of temperature rise is related to the nature of the material, conditions of the test and also to the deformation behaviour of the material during loading. The recent advances in infrared sensors and image/data processing techniques enable observation and quantitative analysis of the heat energy dissipated during such tensile tests. In this study, infrared imaging technique has been used to characterise the tensile deformation in AISI type 316 nuclear grade stainless steel. Apart from identifying the different stages during tensile deformation, the technique provided an accurate full-field temperature image by which the point and time of strain localization could be identified. The technique makes it possible to visualise the region of deformation and failure and also predict the exact region of fracture in advance. The effect of thermal gradients on plastic flow in the case of interrupted straining revealed that the interruption of strain and restraining at a lower strain rate not only delays the growth of the temperature gradient, but the temperature rise per unit strain decreases. The technique is a potential NDE tool that can be used for on-line detection of thermal gradients developed during extrusion and metal forming process which can be used for ensuring uniform distribution of plastic strain.

• Geomechanics and Engineering
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• v.25 no.4
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• pp.295-302
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• 2021

Cross-borehole electrical resistivity tomography (ERT) is an effective groundwater detection tool in geophysical investigations. In this paper, an artificial water injection test was conducted on a small clay sample, where the high-resolution cross-borehole ERT was used to investigate the moisture migration law over time. The moisture migration path can be two-dimensionally imaged based on the relationship between resistivity and saturation. The hydraulic conductivity was estimated, and the magnitude ranged from 10^-11 m/s to 10^-9 m/s according to the comparison between the simulation flow and the saturation distribution inferred from ERT. The results indicate that cross-borehole ERT could help determine the resistivity distribution of small size clay samples. Finally, the cross-borehole ERT technique has been applied to investigate the self-sealing characteristics of clay.