• 비파괴검사학회지
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• 제16권1호
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• pp.34-45
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• 1996

음향 방출 신호의 수집 및 처리, 특징값 추출 및 선택, 분류기 설계 및 검증 과정 등을 수행할 수 있는 신호 형상 인식 프로그램을 개발하고, 이를 오스테나이트계 STS304 용접부의 인공 결함 분류 연구에 적용하였다. 특히 분류기로는 선형 함수 분류기, 경험적 Bayesian 분류기, 신경 회로망 분류기를 사용하였고, 센서는 광대역 센서와 공진형 센서를 사용하여 분류기간의 비교와 센서간의 차이점을 검토하였다. 그 결과 신경 회로망 분류기가 다른 분류기에 비해 높은 인식률을 주었고, 공진형 센서보다는 광대역 센서를 통해 받은 신호가 더 높은 인식률을 주었다.

• Journal of Korean Neurosurgical Society
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• 제50권3호
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• pp.252-255
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• 2011

Authors report a case of a painless acute dissecting aneurysm of the descending aorta in a patient who presented with unexplained hypotension followed by simultaneous paraplegia and right arm monoparesis. To our knowledge, case like this has not been reported previously. Magnetic resonance imaging of the brain and spine revealed hemodynamic cerebral infarction and extensive cord ischemia, respectively. Computerized tomography angiography confirmed a dissecting aneurysm of the descending aorta. The cause of the brain infarction may not have been embolic, but hemodynamic one. Dissection-induced hypotension may have elicited cerebral perfusion insufficiency. The cause of cord ischemia may be embolic or hemodynamic. The dissected aorta was successfully replaced into an artificial patch graft. The arm monoparesis was improved, but the paraplegia was not improved. In rare cases of brain and/or spinal cord infarction caused by painless acute dissecting aneurysm of the aorta, accurate diagnosis is critical because careless thrombolytic therapy can result in life-threatening bleeding.

• International Journal of Korean Welding Society
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• 제1권1호
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• pp.23-30
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• 2001

Among the various welding conditions, the welding current that is inversely proportional to the tip-to-work-piece distance is an essential parameter as to monitor the GMAW process and to implement the welding automation. Considering the weld pool surface geometry including weld defects, it should modify the signal processing method for automatic seam tracking in horizontal fillet welding. To meet the above necessities, a mathematical model related with the weld pool geometry was proposed as in a conjunction with the two-dimensional heat flow analysis of the horizontal fillet welding. The signal processing method based on the artificial neural network (Adaptive Resonance Theory) was proposed for discriminating the sound weld pool surface from that with the weld defects. The reliability of the numerical model and the signal processing method proposed were evaluated through the experiments of which showed that they are effective for predicting the weld bead shape with or without the weld defects in a horizontal fillet welding.

• 대한후두음성언어의학회지
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• 제4권1호
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• pp.24-32
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• 1991

Cleft palate or velopharyngeal incompetence shows many disorders and disabilities affecting speech transmission. including distortion. substitution. and the nasalization of the vowels. The nasalized vowels are produced primarily by lowering of the velum. resulting in opening a side passage for the air flow through the nasal cavity. These abnormal movements give rise to complex modification of the physical property of the sound or in the sound spectrum. The authors employed Sonagraph$^{\circledR}$ as a sound analyzer in order to ascertain the features which characterize the nasalization of vowels. Twenty healthy Korean male adult voluteers were analyzed in artificial conditions of anterior and posterior nasal obstruction. and velo-pharyngeal incompetence. The results were as follows : 1) Fundamental frequency was not changed by nasal obstruction or velopharyngeal incompetence. 2) There was no significant difference of the formant intensity between normal and nasal vowels. 3) In VPI, a decrease of the frequency of $F_2$ was observed in /e/ and /i/ vowels(p<0.001). 4) In VPI, the $F_2$ was frequently missed in /o/ and /u/ vowels. 5) In the consonant spectra of VPI, the 'release burst' was usually not observed.

• 대한용접접합학회:학술대회논문집
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• 대한용접접합학회 1996년도 특별강연 및 추계학술발표 개요집
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• pp.139-141
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• 1996

Among various welding parameters, the welding current which is inversely proportional to the tip-to-workpiece distance in GMAW is an essential parameter to monitor the GMAW process of horizontal fillet joints. For the case of weld defect such as overlap in horizontal fillet welding, therefore, the signal processing for process monitoring or automatic seam tracking should be modified by considering the weld pool surface geometry including the corresponding weld defect. In other words, the adequate signal processing algorithm is indispensible to improve the performance of the arc sensor. However, arc sensor algorithm already developed usually focus on weld seam tracing but do not considering the weld qualities. In this paper, various experiments were carried out to investigate the tendencies of the weld defects when weaving motion is added, and the experimental method based on 2$^n$ factorial design was proposed for deriving the mathematical model between the leg length and the various welding conditions. Moreover, a signal processing method based on the artificial neural network(Adaptive Resonance Theory) was proposed far discriminating the current signal of sound weld beads from that of weld beads with overlap. Finally, the algorithm for weld seam tracking combined with the mathematical modeling and the signal processing method was carried out to track the weld line in conjunction with the improvement of the weld qualities. The reliability of the proposed algorithms were evaluated through various experiments, which showed that the proposed algorithms could be effectively used for arc welding automation.

• International Journal of Railway
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• 제3권3호
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• pp.83-89
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• 2010

This paper attempts to extract the fundamental dynamic properties, i.e. natural frequencies, damping ratios of the 48 m-long, $20^{\circ}$ skewed real bridge with PSC girders wrapped by a steel plate. The forced vibration test is achieved by mounting 12 Hz-capacity of artificial oscillator on the top of bridge deck. The acceleration histories at the 9 different locations of deck surface are recorded using accelerometors. From this full-scaled vibration test, the two possible resonance frequencies are detected at 2.38 Hz and 9.86 Hz of the skewed bridge deck by sweeping a beating frequency up to 12 Hz. The absolute acceleration/energy exhibits much higher in case of higher-order twist mode, 9.86 Hz due to the skewness of bridge deck which leads asymmetric situation of vibration. This implies the test bridge is under swinging vertically in fundamental flexure mode while the bridge is also flickered up and down laterally at 9.86 Hz. This is probably by asymmetric geometry of skewed deck. A detailed 3D beam-shell bridge models using finite elements are performed under a series of train loads for modal dynamic analyses. Thereby, the effect of skewness is examined to clarify the lateral flickering caused by asymmetrical geometry of bridge deck.

• Smart Structures and Systems
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• 제20권6호
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• pp.657-668
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• 2017

In this research, an active vibration suppression of a smart beam having piezoelectric sensor and actuators is investigated by designing separate controllers comprising a linear quadratic regulator and a neural network. Firstly, design of a smart beam which consists of a cantilever aluminum beam with surface bonded piezoelectric patches and a designed mechanism having a micro servomotor with a mass attached arm for obtaining variations in the frequency response function are presented. Secondly, the frequency response functions of the smart beam are investigated experimentally by using different piezoelectric patch combinations and the analytical models of the smart beam around its first resonance frequency region for various servomotor arm angle configurations are obtained. Then, a linear quadratic regulator controller is designed and used to simulate the suppression of free and forced vibrations which are performed both in time and frequency domain. In parallel to simulations, experiments are conducted to observe the closed loop behavior of the smart beam and the results are compared as well. Finally, active vibration suppression of the smart beam is investigated by using a linear controller with a neural network based adaptive element which is designed for the purpose of overcoming the undesired consequences due to variations in the real system.

• Applied Microscopy
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• 제46권4호
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• pp.184-187
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• 2016

Neuronal connectivity determines brain function. Therefore, understanding the full map of brain connectivity with functional annotations is one of the most desirable but challenging tasks in science. Current methods to achieve this goal are limited by the resolution of imaging tools and the field of view. Macroscale imaging tools (e.g., magnetic resonance imaging, diffusion tensor images, and positron emission tomography) are suitable for large-volume analysis, and the resolution of these methodologies is being improved by developing hardware and software systems. Microscale tools (e.g., serial electron microscopy and array tomography), on the other hand, are evolving to efficiently stack small volumes to expand the dimension of analysis. The advent of mesoscale tools (e.g., tissue clearing and single plane ilumination microscopy super-resolution imaging) has greatly contributed to filling in the gaps between macroscale and microscale data. To achieve anatomical maps with gene expression and neural connection tags as multimodal information hubs, much work on information analysis and processing is yet required. Once images are obtained, digitized, and cumulated, these large amounts of information should be analyzed with information processing tools. With this in mind, post-imaging processing with the aid of many advanced information processing tools (e.g., artificial intelligence-based image processing) is set to explode in the near future, and with that, anatomic problems will be transformed into informatics problems.

• 한국추진공학회지
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• 제17권2호
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• pp.1-8
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• 2013

모형 연소실에서 충돌형 분사기의 연소 안정성 평가를 위해 시간지연(time lag)과 간섭인자(interaction index)의 관계를 연구하였다. 산화제 분사 속도의 5%에 해당하는 섭동을 공진주파수로 인위적으로 가진하여 이에 대한 화염의 응답특성을 분석하였다. 연료와 산화제의 혼합지점인 충돌점들, 즉, 특성길이 위치에서 속도섭동과 열방출율 섭동간의 관계를 시간지연 모델을 이용하여 나타내었다. 시간지연을 정량화하는 개선된 방법으로서, 수치해석을 통해 얻은 결과로부터 분사기 출구면으로부터 충돌점까지 평균속도를 이용하는 방법을 제안하였다. 축방향의 평균속도가 증가할수록 시간지연이 짧아지는 경향성을 확인할 수 있었다.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.53-64
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• 2023

Early detection of endometrial carcinoma in uterus is essential for effective treatment. Endometrial carcinoma is the worst kind of endometrium cancer among the others since it is considerably more likely to affect the additional parts of the body if not detected and treated early. Non-invasive medical computer vision, also known as medical image processing, is becoming increasingly essential in the clinical diagnosis of various diseases. Such techniques provide a tool for automatic image processing, allowing for an accurate and timely assessment of the lesion. One of the most difficult aspects of developing an effective automatic categorization system is the absence of huge datasets. Using image processing and deep learning, this article presented an artificial endometrium cancer diagnosis system. The processes in this study include gathering a dermoscopy images from the database, preprocessing, segmentation using hybrid Fuzzy C-Means (FCM) and optimizing the weights using the Whale Optimization Algorithm (WOA). The characteristics of the damaged endometrium cells are retrieved using the feature extraction approach after the Magnetic Resonance pictures have been segmented. The collected characteristics are classified using a deep learning-based methodology called Long Short-Term Memory (LSTM) and Bi-directional LSTM classifiers. After using the publicly accessible data set, suggested classifiers obtain an accuracy of 97% and segmentation accuracy of 93%.