• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.338-345
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• 2024

Magnetic anomaly signals from the ferromagnetic targets such as ships in the sea are measured by drone-based magnetic anomaly detection. A quantum magnetometer is suspended from the drone by 4 strings. Flight altitude and speed of drone are 100 m and 5 m/s, respectively. We obtain magnetic anomaly signals of few nT from the ships clearly. We analyze the signal characteristics by the ferromagnetic target through simulation using COMSOL multiphysics.

• Journal of the Korea Institute of Military Science and Technology
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• v.26 no.4
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• pp.335-343
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• 2023

Drone based Magnetic Anomaly Detection measure a magnetic anomaly signal from the ferromagnetic target on the ground. We conduct a magnetic anomaly detection with 9 ferromagnetic targets on the ground. By removing the magnetic field measured in the absence of ferromagnetic targets from the experimental value, the magnetic anomaly signal is clearly measured at an altitude of 100 m. We analyze the signal characteristics by the ferromagnetic target through simulation using COMSOL multiphysics. The simulation results are within the GPS error range of the experimental results.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1501-1512
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• 2024

Plasma disruption in tokamak experiments is a challenging issue that causes damage to the device. Reliable prediction methods are needed, but the lack of full understanding of plasma disruption limits the effectiveness of physics-driven methods. Data-driven methods based on supervised learning are commonly used, and they rely on labelled training data. However, manual labelling of disruption precursors is a time-consuming and challenging task, as some precursors are difficult to accurately identify. The mainstream labelling methods assume that the precursor onset occurs at a fixed time before disruption, which leads to mislabeled samples and suboptimal prediction performance. In this paper, we present disruption prediction methods based on anomaly detection to address these issues, demonstrating good prediction performance on J-TEXT and EAST. By evaluating precursor onset times using different anomaly detection algorithms, it is found that labelling methods can be improved since the onset times of different shots are not necessarily the same. The study optimizes precursor labelling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels.

• Geophysics and Geophysical Exploration
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• v.16 no.1
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• pp.36-44
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• 2013

We conducted the airborne magnetic and radiometric survey for the characterization of the black shale related and pyrometamorphic uranium deposits distributed in Geumsan area. For the successful characterization of the uranium deposits, the general geological and structural geological features were investigated based on the lithological and linear feature analysis to individual magnetic and radiometric data as the first step. Lithological analysis from the magnetic reduction to the pole and downward continuation map revealed that prominent positive anomalies caused by black and dark gray slate member were clearly recognized as magnetic sources. These results indicate that magnetic survey, even though it is not a direct method for the detection of uranium, can be a useful tool in uranium detection. By the linear feature analysis based on 2nd vertical derivative and curvature map, two linearments corresponded the gray hornfels and black slate member were extracted and in succession, the additional uranium potential zone was inferred. Final discrimination whether uranium-rich or not was confirmed by radiometric and uranium anomaly map. From these analysis, we finally concluded that uranium deposit originated by pyrometamorphic process was confined near the intrusive area only. On the contrary, it was found that black shale related uranium deposit is distributed and extended through out the entire survey area with south-west to north-east direction. In addition, from the linear feature analysis based on radiometric total anomaly map, the typical discontinuous characteristics were recognized in areas where uranium-contained linearments cross the faults. From the above discussion, we concluded that airborne magnetic and radiometric survey are complementary to each other. So it is preferable to carry out simultaneously for the efficient data processing and fruitful interpretation.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.193-196
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• 2021

Congenital absence of the bilateral internal carotid arteries (ICA) is a very rare occurrence. Recognition of this rare anomaly is important, when considering intracranial endovascular interventions in the event of thromboembolic events with revascularization, transsphenoidal surgery, and the surveillance and detection of associated cerebral aneurysms. We report a case of a 25-year-old man who presented with headache since 2 years ago, and was incidentally discovered to have a congenital bilateral absence of ICAs.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.979-987
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• 2021

Multiple Sclerosis (MS) can be early diagnosed by detecting lesions in brain magnetic resonance images (MRI). Unsupervised anomaly detection methods based on autoencoder have been recently proposed for automated detection of MS lesions. However, these autoencoder-based methods were developed only for 2D images (e.g. 2D cross-sectional slices) of MRI, so do not utilize the full 3D information of MRI. In this paper, therefore, we propose a novel 3D autoencoder-based framework for detection of the lesion volume of MS in MRI. We first define a 3D convolutional neural network (CNN) for full MRI volumes, and build each encoder and decoder layer of the 3D autoencoder based on 3D CNN. We also add a skip connection between the encoder and decoder layer for effective data reconstruction. In the experimental results, we compare the 3D autoencoder-based method with the 2D autoencoder models using the training datasets of 80 healthy subjects from the Human Connectome Project (HCP) and the testing datasets of 25 MS patients from the Longitudinal multiple sclerosis lesion segmentation challenge, and show that the proposed method achieves superior performance in prediction of MS lesion by up to 15%.

• Journal of the Korean Geophysical Society
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• v.3 no.3
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• pp.175-184
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• 2000

A nondestructive experimental feasibility study was conducted using magnetometer to find buried cultural objects at pottery and steel matters in low-relief mountaineous area of Doojeong-dong, Cheonan, Chungnam Province from May 23 to July 18, 1998. Magnetic survey was carried out with $20cm{\times}20cm$ grid in a site of $20m{\times}40m$ before excavation, and the distribution of magnetic anomalies was compared with the results of excavation. Magnetic sensor was located on the surface of ground during the magnetic survey on the basis of an experimental result. Positive magnetic anomalies of maximum 130 nT are found over a pair of potteries. Magnetic anomaly map reveals several anomalous points in the 1st and 4th quadrants of the survey site, from where potteries and their fragments were confirmed. Six points out of seven points cprrelated with magnetic anomaly are found contain earthwares, whereas a magnetically uncorrelated location produced earthware made of unbaked clay. Steel waste such as cans and wires hidden in soil and bushes also influenced magnetic anomalies. Therefore, it is better to remove such steel wastes prior to magnetic survey if possible. Some magnetically anomalous points produced no archaeological object on excavation. This may be explained by shallower level of excavation than burial depth.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.97-103
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• 2005

Recent development of marine magnetic gradient systems, using arrays of sensors, has made it possible to survey large contaminated areas very quickly. However, underwater Unexploded Ordnances (UXO) can be moved by water currents. Because of this mobility, the cleanup process in such situations becomes dynamic rather than static. This implies that detection should occur in near real-time for successful remediation. Therefore, there is a need for a fast interpretation method to rapidly detect signatures of underwater objects in marine magnetic data. In this paper, we present a fast method for location and characterization of underwater UXOs. The approach utilises gradient interpretation techniques (analytic signal and Euler methods) to locate the objects precisely. Then, using an iterative linear least-squares technique, we obtain the magnetization characteristics of the sources. The approach was applied to a theoretical marine magnetic anomaly, with random errors, over a known source. We demonstrate the practical utility of the method using marine magnetic gradient data from Japan.

• Investigative Magnetic Resonance Imaging
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• v.18 no.3
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• pp.200-207
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• 2014

Purpose : We evaluated the diagnostic value of susceptibility-weighted imaging (SWI) for the detection of developmental venous anomaly (DVA). Materials and Methods: Retrospective review of 1068 brain MR examinations found 28 DVAs in 28 patients (2.6%) on contrast-enhanced T1-weighted images. SWI, T2, and FLAIR images of 28 patients with DVA and 28 sex- and age-matched control patients without DVA were analyzed by blinded readers on each type of sequences. All images were independently reviewed by two radiologists who were blinded to other MR imaging finding. In cases of discrepancy, two reviewers reached a consensus later. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each MR sequence for the detection of DVA were determined. Statistical analysis was performed by using the Mcnemar test. The significance level was p < 0.05. Results: The sensitivity, specificity, PPV, and NPV of SWI for the detection of DVA were 85.7%, 92.9%, 92.3%, and 86.7%, respectively. T2 and FLAIR images showed sensitivity of 35.7% and 35.7%, specificity of 92.9% and 96.4%, PPV of 83.3% and 90.9%, and NPV of 59.1% and 60.0%, respectively. On SWI, the sensitivity and NPV for the detection of DVAs were significantly higher than those of T2 and FLAIR images (p < 0.05). Conclusion: SWI was sensitive and specific for the detection of DVA.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.219-224
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• 2007

We conducted geophysical surveys to detect antitank mine at Namji-eup, Gyeongsangnam-do which had been installed during Korean war. The surveys consisted of 2 stages, at the first stage we divided the survey area into 7 block and carried out magnetic gradient survey and GEM-3 EM survey sequentially for each block. Hence we verified anomaly areas using an excavator and a metal detector. Most of anomalies were found to be garbages such as trash cans, metallic wastes, and so on. And also, the concrete pipe was found at depth of 1 m, which had not referred in any report of that area. At the second stage, after trenching the covered soil down to 75 cm the same surveys were conducted. We could not find the strong signal to be inferred from a antitank mine, but we pointed out some anomalies to need careful handling because demining is very dangerous work even though there is few possibility that is mine.