• Journal of Korean Neurosurgical Society
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• v.59 no.3
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• pp.314-318
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• 2016

Posterior fossa is a site next to the middle fossa where arachnoid cyst frequently occurs. Generally, most arachnoid cysts are asymptomatic and are found incidentally in most cases. Although arachnoid cysts are benign and asymptomatic lesions, patients with posterior fossa arachnoid cysts often complain of headaches, gait disturbance, and ataxia due to the local mass effects on the cerebellum. We observed a patient with a posterior fossa arachnoid cyst who had visual symptoms and a headache, but did not have gait disturbance and ataxia. We recommended an emergency operation for decompression, but the patient refused for personal reasons. After 7 days, the patient revisited our hospital in a state of near-blindness. We suspected that the arachnoid cyst induced the hydrocephalus and thereby the enlarged third ventricle directly compressed optic nerves. Compressed optic nerves were rapidly aggravated during the critical seven days; consequently, the patient's vision was damaged despite the operation. Considering the results of our case, it is important to keep in mind that the aggravation of symptoms cannot be predicted; therefore, symptomatic arachnoid cysts should be treated without undue delay.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.939-944
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• 2002

PD phenomena can be regarded as a deterministic dynamical process where PD should be occurred if the local electric field be reached to be sufficiently high. And thus, its mathematical model can be described by either difference equations or differential equations using several state variables obtained from the time sequential measured data of PD signals. These variables can provide rich and complex behavior of detectable time series, for which Chaos theory can be employed. In this respect, a new PD pattern recognition method is proposed and named as 'Chaotic Analysis of Partial Discharges (CAPD)' for this work. For this purpose, six types of specimen are designed and made as the models of the possible defects that may cause sudden failures of the underground power transmission cables under service, and partial discharge signals, generated from those samples, are detected and then analyzed by means of CAPD. Throughout the work, qualitative and quantitative properties related to the PD signals from different defects are analyzed by use of attractor in phase space, information dimensions ($D_0$ and D2), Lyapunov exponents and K-S entropy as well. Based on these results, it could be pointed out that the nature of defect seems to be identified more distinctively when the CAPD is combined with traditional statistical method such as PRPDA. Furthermore, the relationship between PD magnitude and the occurrence timing is investigated with a view to simulating PD phenomena.

• Journal of Adhesion and Interface
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• v.7 no.4
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• pp.10-12
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• 2006

The successful use of adhesively bonded parts depends on the defect-free bond of the components. Therefore it is necessary to detect relevant faults and defects in an early state of the production. A 100% test should be pursued, but especially at complicated structures the detection of defects is not easy. Possible testing methods, which show a high potential for the NDT of adhesively bonded parts, are thermography based NDT methods. At present mainly two different procedures of active thermography are being used: Pulse and Lock-In Thermography. With pulse thermography the examined material is warmed up with a short energy pulse (light, eddy current or ultrasonic pulse) and the heat response is recorded after a certain time. The result is an infrared image which indicates material defects in different depths. This paper presents a variety of images showing the capability of Lock-In Thermography to image subsurface defects. Several examples of adhesives joints qualify the ultrasonic Lock-In-Thermography for the in-process quality control for adhesive bonded components.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.63-68
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• 2015

A one-step fabrication of a photonic crystal (PC) with functional defects is demonstrated. Using multi-beam phase-controlled holographic lithography with a diffracting optical element, large area one dimensional (1D) and two dimensional (2D) PCs with periodic defects were fabricated. The uniform area is up to $2mm^2$, and tens of defect channels have been introduced in the 1D and 2D PC structure. This technique gives rise to substantial reduction in the fabrication complexity and significant improvement in the spatial accuracy of introducing functional defects in photonic crystals. This method can also be used to design and fabricate three dimensional (3D) PCs with periodic defects.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.481-486
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• 2012

This thesis examines the development and application of 'Health Monitoring System' which monitors periodically the state of a pipe of petrochemical plant by using magnetostrictive sensor technology. The existing guided-wave inspection methods cannot be applied to welding part inspection in pipe, and has a limit of precision when applied to general parts because of noise, reflected waves, and so on. This technology uses the information on displacement of a defect through periodic monitoring, which makes more precise inspection, and can be utilized very usefully in a petrochemical plant.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2580-2582
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• 2004

In this paper, a Neural Network(NN) based approach for classification of two dimensions images. The proposed algorithm is able to apply in the actual industry. The described diagnostic algorithm is presented to defect surface failures on tiles. A way to get data for a digital image process is several kinds of it. The tiles are scanned and the digital images are preprocessed and classified using neural networks. It is important to reduce the amount of input data with problem specific preprocessing. The auto-associative neural network is used for feature generation and selection while the probabilistic neural network is used for classification. The proposed algorithm is evaluated experimentally using one hundred of the real tile images. Sample image data to preprocess have histogram. The histogram is used as input value of probabilistic neural network. Auto-associative neural network compress input data and compressed data is classified using probabilistic neural network. Classified sample images are determined by human state. So it is intervened human subjectivity. But digital image processing and neural network are better than human classification ability. Therefore it is very useful of quality control improvement.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.25 no.6
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• pp.776-785
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• 2001

Hot-wire measurements are performed in boundary layers developing on a NACA0012 airfoil over which wakes pass periodically. The Reynolds number based on chord length of the airfoil is 2$\times$10(sup)5 and the wakes are generated by circular cylinders rotating clockwise and counterclockwise around the airfoil. This paper and its companion Part II describe the phenomena of wake-induced transition of the boundary layers on the airfoil using measured data; phase-and time-averaged streamwise mean velocities, turbulent fluctuations, integral parameters and wall skin frictions. This paper describes the background and facility together with results of time-averaged quantities. Due to the passing wake with mean velocity defects and high turbulence intensities, the laminar boundary layer is periodically disturbed at the upstream station and becomes steady-state transitional boundary layer at the downstream station. The velocity defect in the passing wake changes the local pressure at the leading of the airfoil, significantly affects the time-mean pressure distribution on the airfoil and eventually, has influence on the transition process of the boundary layer.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.79-85
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• 2003

One of unique characteristics of guided waves is a dispersive behavior that guided wave velocity changes with an excitation frequency and mode. In practical applications of guided wave techniques, it is very important to identify propagating modes in a time-domain waveform for determination of defect location and size. Mode identification can be done by measurement of group velocity in a time-domain waveform. Thus, it is preferred to generate a single or less dispersive mode But in many cases, it is difficult to distinguish a mode clearly in a time-domain waveform because of superposition of multi modes and mode conversion phenomena. Time-frequency analysis is used as efficient methods to identify modes by presenting wave energy distribution in a time-frequency. In this study, experimental guided wave mode identification is carried out in a steel plate using time-frequency analysis methods such as wavelet transform. The results are compared with theoretically calculated group velocity dispersion curves. The results are in good agreement with analytical predictions and show the effectiveness of using the wavelet transform method to identify and measure the amplitudes of individual guided wave modes.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.1093-1101
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• 2015

Partial Discharge (PD) is a physical phenomenon, which causes defects and damages to the insulation. This phenomenon is regarded as the most important source of fault and defect in power transformers. Therefore, methods of high speed and precision are considered of special importance for the maintenance of transformers in localization of the origin of partial discharge. In this paper, the transformer winding is first modeled in a transient state by using RLC ladder network and multiconductor transmission line (MTL) models. The parameters of the two models were calculated by Ansoft Maxwell software, and the simulations were performed by Matlab software. Then, the PD pulses were applied to the models with different widths of pulses. With regard to the fact that the signals received after the application of PD had a variable frequency nature over time, and based on the wavelet transform and signal energy, a new method was presented for the localization of PD. Ultimately; the mentioned method was implemented on a 20 kV winding distribution transformer. Then, the performances of the models used in this paper, including RLC and MTL models, were compared in different frequency bands for the correct distinction of partial discharge location.

• Journal of Chest Surgery
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• v.37 no.1
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• pp.72-75
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• 2004

The Fontan operation is commonly practiced for the physiologic correction of univentricular heart diseases. However, for the patients who have risk factors against this operation, it is recommended to take the initial palliative operation rather than going to the Fontan operation at once. The proper timing to the Fontan operation after palliation is decided by assessing several factors such as patient's age and other risks of maintaining palliative state, etc. Usually, the Fontan operation is done relatively early after palliation stage. Here, we report a 36 years old-adult-female with univentricular heart disease who underwent the successful Fontan operation at 17 years after unidirectional Glenn procedure.