• Journal of Korean Neurosurgical Society
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• 제59권3호
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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.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 하계학술대회 논문집 Vol.3 No.2
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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.

• 접착 및 계면
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• 제7권4호
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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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• 제19권1호
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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.

• 한국지능시스템학회논문지
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• 제22권4호
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• pp.481-486
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• 2012

본 논문은 석유화학 플랜트 등의 결함을 자기자왜센서기술을 활용하여 주기적으로 검사하는 오프라인 모니터링이 가능한 'Health Monitoring System'의 개발과 그 활용성에 대해 확인하였다. 기존의 유도파 검사 방식은 용접부위 검사에는 적용할 수 없고, 일반적인 부위에서도 노이즈 및 반사파 등으로 검사의 정밀도에 한계를 갖고 있다. 본 기술은 주기적인 모니터링을 통해 결함의 진전에 따른 변위정보를 활용할 수 있음으로서, 더 정밀한 검사가 가능하기 때문에 석유화학 플랜트에서 매우 유용하게 활용될 수 있을 것으로 사료된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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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.

• 대한기계학회논문집B
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• 제25권6호
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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.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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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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• 제10권3호
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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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• 제37권1호
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• pp.72-75
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• 2004

단심실성 심장기형의 교정방법으로 Fontan 수술이 행해지지만 이 수술의 위험요소를 가진 대상군에서는 고식적 수술을 시행한 후 단계적으로 Fontan 수술을 시행하는 것이 보편적이다. Fontan 수술의 시기는 고식적 수술 후 감소한 수술 위험요소와 고식적 수슬상태의 지속에 의하여 증가하는 위험 요소를 재평가한 후 결정되며, 고식술 후 비교적 조기에 시행되는 것이 보통이다. 국립의료원에서는 36세 성인 단심실증 환자에서 과거에 단방향성 Glenn 수술을 시행하고 17년 후에 완전 Fontan 수술로 전환한 증례가 있어 보고하고자 한다.