• Proceedings of the KSME Conference
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• 2000.04a
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• pp.585-590
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• 2000

Problems involved in the numerical analysis on the forced oscillation of nonlinear oscillators such a microbubble oscillation under ultrasound and Duffing oscillator were discussed. One of the problems is proper choice of the time scale of the driving force. which is related to the numerical artifacts due to the mismatch between the natural frequency of an oscillator(or bubble) and the characteristic frequency of the applied force. Such problem may occur in a nonlinear oscillator whose behavior is crucially dependent on the frequency of the applied force. The artificial resonance problem during the numerical evaluation of such nonlinear systems was also discussed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.5 s.248
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• pp.520-527
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• 2006

The design of major industrial facilities for the prevention of fatigue failure is customarily done by defining a set of transients and performing a calculation of cumulative usage factor. However, sometimes, the inherent conservatism or lack of details as well as unanticipated transients in old plant may cause maintenance problems. Even though several famous on-line monitoring and diagnosis systems have been developed world-widely, in this paper, a new system fur fatigue monitoring and life evaluation of crane is proposed to reduce customizing effort and purchasing cost. With regard to the system, at first, comprehensive operating transient data has been acquired at critical locations of crane. The real-time data were classified, by using adaptive resonance theory that is one of typical artificial neural network, into representative stress groups. Then the each classified stress pattern was mapped to calculated cumulative usage factor in accordance with ASME procedure. Thereby, promising results were obtained fur the crane and it is believed that the developed system can be applicable to other major facilities extensively.

• Bulletin of the Korean Chemical Society
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• v.22 no.4
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• pp.367-371
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• 2001

Lithium inserted into artificial carbon has been synthesized as a function of the Li concentration. The characteristics of these prepared compounds were determined from the studies using X-ray diffraction(XRD), solid nuclear magnetic resonance (NM R) spectrophotometric and differential scanning calorimeter(DSC) analysis. X-ray diffraction showed that lower stage intercalation compounds were formed with increasing Li concentration. In the case of the AG3, most compounds formed were of the stage 1 structure. Pure stage 1 structural defects of artificial graphite were not observed. 7Li-NMR data showed that bands are shifted toward higher frequencies with increasing lithium concentration; this is because non-occupied electron shells of Li increased in charge carrier density. Line widths of the Li inserted carbon compounds decreased slowly because of nonhomogeneous local magnetic order and the random electron spin direction for located Li between graphene layers. The enthalpy and entropy changes of the compounds can be obtained from the differential scanning calorimetric analysis results. From these results, it was found that exothermic and endothermic reactions of lithium inserted into artificial carbon are related to the thermal stability of lithium between artificial carbon graphene layers.

• Journal of Biosystems Engineering
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• v.21 no.3
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• pp.336-342
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• 1996

A 4.1MHz$1^H$ Nuclear Magnetic Resonance(NMR) sensor was designed and manufactured to evaluate the internal quality of fruits. The magnet console having 963gauss magnetic field induction was used for the NMR sensor. To optimize and evaluate the NMR sensor, glycerol and sugar-water solutions were used. $^1$H(proton) resonance signals were used to estimate the sugar contents in fruits. Artificial neural network models were developed to predict sugar contents in fruits from the proton resonance signals. The standard errors of prediction(SEP) were 0.565(apple), 0.394(pear) and 0.415(kiwi), respectively. The result implied that it was possible to evaluate apple, pear and kiwi into 3 grades using the NMR sensor.

• Investigative Magnetic Resonance Imaging
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• v.24 no.2
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• pp.67-75
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• 2020

When a patient takes an MRI scan, the patient has a risk of unexpected injuries due to the intensive electromagnetic (EM) field. Among the injuries, the tissue heating by the time-varying EM field is one of the main issues. Since an implanted artificial structure with a conductive material aggravates the heating effect, lots of studies have been conducted to investigate the effect around the implants. In this review article, a mechanism of RF heating around the implants and related studies are comprehensively investigated.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.4
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• pp.22-31
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• 2005

The purpose of this study is to design a flexural structure that has a function of pan and tilt for an artificial eyeball. The artificial eyeball system has a function of image stabilization, which compensate panning and tilting vibration of the body on which the artificial eyeball is attached. The target closed loop control bandwidth is 50Hz, so the mechanical resonance frequency is required to be more than the control bandwidth, which is a tough design problem because of a big mass of camera and actuator. In this study, the design process including the selection of the principal parameters by numerical analysis with ANSYS will be described, as well as the design results and frequency response.

• Structural Engineering and Mechanics
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• v.71 no.4
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• pp.377-390
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• 2019

A method for estimating the floor response spectra (FRS) of elastic structures under earthquake excitations is proposed. The method is established based on a previously proposed direct estimation method for single degree of freedom systems, which generally overestimates the FRS of a structure, particularly in the resonance period range. A modification factor is introduced to modify the original method; the modification factor is expressed as a function of the period ratio and is determined through regression analysis on time history analysis results. Both real and artificial ground motions are considered in the analysis, and it is found that the modification factors obtained from the real and artificial ground motions are significantly different. This suggests that the effect of ground motion should be considered in the estimation of FRS. The modified FRS estimation method is further applied to a 10-story building structure, and it is verified that the proposed method can lead to a good estimation of FRS of multi-story buildings.

• Magazine of the Korea Concrete Institute
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• v.11 no.1
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• pp.161-171
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• 1999

Impact resonance testing was carried out on small and large concrete blocks containing several types of artificial flaws respectively. Quantitative analysis of the observed peak frequencies in the impact resonance tests identifies the possible normal modes of concrete blocks containing flaws. and enables to determine the depth and size of the flaws in concrete blocks. In this study, concrete can be treated as a homogeneous and isotropic material. The flaw size and location at each section of artificial flaw series in small and large concrete blocks, determined through two-dimensional scanning of impact point and real-time fast Fourier transform, are in good agreement with real size location, respectively. Consequently, quantitative analysis method of vibration modes in the impact resonance tests, which can be applied for homogeneous and isotropic material, can be useful for the detection of flaws in any case of small and large concrete blocks in this study.

• ETRI Journal
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• v.46 no.2
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• pp.263-276
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• 2024

Different diseases occur in the brain. For instance, hereditary and progressive diseases affect and degenerate the white matter. Although addressing, diagnosing, and treating complex abnormalities in the brain is challenging, different strategies have been presented with significant advances in medical research. With state-of-art developments in artificial intelligence, new techniques are being applied to brain magnetic resonance images. Deep learning has been recently used for the segmentation and classification of brain images. In this study, we classified normal and pathological brain images using pretrained deep models through transfer learning. The EfficientNet-B5 model reached the highest accuracy of 98.39% on real data, 91.96% on augmented data, and 100% on pathological data. To verify the reliability of the model, fivefold cross-validation and a two-tier cross-test were applied. The results suggest that the proposed method performs reasonably on the classification of brain magnetic resonance images.

• Journal of the Korean Society of Radiology
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• v.12 no.6
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• pp.793-799
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• 2018

As interest in artificial intelligence has increased, artificial intelligence has been actively studied in the medical field. In Korea, artificial intelligence has been applied to medical imaging devices such as X-ray imaging, Computer Tomography and Magnetic Resonance Imaging and artificial intelligence capable of acquiring radiation images of patients without radiologists in the future Medical devices are expected to be invented. This study was an initial study on the automation of patient positioning in X - ray imaging. We used x-ray equipment and human phantoms to evaluate the positioning. The program used Visual Studio 2010 MFC and the image was in the size $1450{\times}1814$. The pixel values were converted to contrasts with values of 0 to 255 that can be visually recognized and output to the monitor. We developed a procedure algorithm program that predicts the angle of the output image through three pixel coordinate values and induces the patient to perform correct positioning according to the voice guidance according to the angle. In the next study, we will study the artificial intelligence to grasp the structure itself and calculate the angle, rather than conveying the reference of coordinates to artificial intelligence. In the future, it is expected that it will be helpful in the study of artificial intelligence from shooting to positioning through the automation of positioning.