• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.330-335
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• 2000

This paper deals with sensing ability of smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the two type of smart sensors for experiment. The first type of smart sensor is H2 type. The second type of smart sensor is HH type. The smart sensor was developed for recognition of material. And then we developed estimation method of sensing ability of smart sensors. The first method(Sensing Ability Index) is developed for H2 smart sensor. The second method($R_{SAI}$ Index) is developed for HH smart sensor. We estimated sensing ability of smart sensor with new SAI and $R_{SAI}$ method. This paper describes our primary study for a new method of estimate sensing ability of smart sensor, which is need for precision work system. This is a study of dynamic characteristics of smart sensor according to frequency and displacement changing with new SAI and $R_{SAI}$ method. Experiment and analysis are executed for proper dynamic sensing condition. First, we developed advanced smart sensors. Second, we develop new SAI and $R_{SAI}$ methods that have a sensing ability of distinguish materials. Dynamic characteristics of smart sensor are evaluated through new SAI and $R_{SAI}$ method relatively. We can use the new SAI and $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object(auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.383-390
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• 2007

This paper describes the e-learning system for science and engineering mathematics using computer algebra system and Bayesian inference network. The best feature of this system is using one of the most recent mathematical dynamic web content authoring model which is called client independent dynamic web content authoring model and using the Bayesian inference network for diagnosing student's learning. The authoring module using computer algebra system provides teacher-user with easy way to make dynamic mathematical web contents. The diagnosis module using Bayesian inference network helps students know the weaker parts of their learning, in this way our system determines appropriate next learning sequences in order to provide supplementary learning feedback.

• Journal of the Korean Orthopaedic Association
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• v.55 no.1
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• pp.85-89
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• 2020

Bow hunter's syndrome is a rare disease that shows the symptoms of vertebrobasilar insufficiency resulting from a dynamic obstruction or stenosis of the vertebral arteries during neck movement. This paper reports a case of a 59-year-old male who visited the emergency room with diplopia, tinnitus, and gait disturbance. Magnetic resonance imaging and angiography revealed a multiple cerebellar infarct, total obstruction of the right vertebral artery, and dynamic obstruction of the left vertebral artery during neck extension. As the infarction worsened, a thrombectomy was done. Posterior decompression and fusion at C5-6 were performed for the left vertebral artery. The left vertebral arterial patency was confirmed by intraoperative and postoperative angiography. No recurrence of the symptoms was observed for six months after surgery. Physicians need to pay attention to the diagnosis of vertebrobasilar insufficiency caused by an obstruction of the vertebral arteries during neck extension in cervical instability patients.

• Clinics in Shoulder and Elbow
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• v.10 no.1
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• pp.99-105
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• 2007

Purpose: The morphological study and dynamic stability of the ulnar nerve around the elbow joint was investigated in asymptomatic normal population using ultrasonography. The purpose of this study is to provide fundamental data for ultrasonographic diagnosis of ulnar neuropathy in cubital tunnel syndrome. Materials and Methods: Fifty cases of 25 healthy male volunteers, aged between 20 to 30 years, included in this study. High resolution 7.5 MHz linear probe was used to examine the ulnar nerve in axial and longitudinal views. In a longitudinal view, the course, position and the thickness of nerve were monitored, the diameter of ulnar nerve and dynamic stability at elbow flexion and extension were measured in an axial view at four different points; 1cm proximal to medial epicondyle, behind the medial epicondyle, entrance to Osborne ligament, and 1cm distal to Osborne ligament. Results: The short diameters of ulnar nerve at elbow extension at four anatomic points were 2.66 mm, 2.97 mm, 2.64 mm, and 2.69 mm and the long diameters were 4.61 mm, 4.56 mm, 4.36 mm, and 4.37 mm, which showed no significant change at each point. However, at elbow flexion, the short diameters were changed to 2.72 mm, 2.34 mm, 2.65 mm, and 2.41 mm and the long diameters into 4.49 mm, 5.40 mm, 4.16 mm, and 4.66 mm. At elbow flexion, significant morphologic change was observed in the medial epicondyle area, and the diameter of the ulnar nerve was shortest at the entrance of Osborne ligament both at flexion and extension. In terms of dynamic stability, nine subluxations and seven dislocations were observed. Conclusion: This study shows dynamic instability and a morphological change of long and short diameters of ulnar nerve at flexion and extension in a normal person, which should be considered in the ultrasonographic diagnosis of ulnar neuropathy.

• Journal of radiological science and technology
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• v.27 no.4
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• pp.17-21
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• 2004

With advancement of the medical imaging technology, the dynamic pelvic MRI (magnetic resonance imaging) has been introduced and used for dynamic MR defecography to improved diagnosis of the patients. At the early stage of its use, it was mostly used to diagnose enterocele or cystocele, then its use was extended to diagnose the organ prolapse and other dysfunctional pelvis organs. There now have been many reports of other diseases such as the functional constipation and others. This paper introduces the pelvis MRI and the dynamic MR defecography and reports the future trend in their clinical applications. Until recently, the studies with pelvic MRI were mostly focused on observing the movement of the pelvis in the supine position. Yang and 26 others reported good result in observing the patients with the pelvic organ prolapse by using the pubococcygeal line as the anatomical index. Using the fast gradient recalled acquisition (fast GRASS), they compared cystocoele, genitourinary prolapse, enterocoele and rectocoele with the control group. Kruyt et al. observed the posterior compartment and reported that MRI was more helpful than the fluoroscopy. Healy et al. applied the dynamic MRI test on the patients with constipation or incontinence as well as the control group without those symptoms. Since then, MRI technology has further advance by Lienemann, who was able to attain the more detailed images using the fast T2 weighted turbo spin echo technology, and others. If its limitation in diagnosing intussusception and the like, since the observation can be made only from the supine position, can be overcome with open MR or others, it is envisages that the method can eventually replace the radiological defecography.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1525-1530
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• 2003

In this paper, a model of adaptive individual life support system is proposed from the viewpoint of cybernetics. This model is derived based on the relation between human behavior and human action, static and dynamic in processing speed, and abstract/concrete. In applications, task and information of human which includes in this system analyzed by paying attention to cybernetics. This paper shows a few actual example of modeling by fundamental adaptive individual life support model such as medical diagnosis, health care and education support. Finally as an example, design and implementation are concretely carried out for health care support system. This is also a method to design a information support system which is involved in human.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.626-641
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• 2015

Conventional case-based reasoning (CBR) does not perform efficiently for high-volume datasets because of case retrieval time. To overcome this problem, previous research suggested clustering a case base into several small groups and retrieving neighbors within a corresponding group to a target case. However, this approach generally produces less accurate predictive performance than the conventional CBR. This paper proposes a new case-based reasoning method called the clustering-merging CBR (CM-CBR). The CM-CBR method dynamically indexes a search pool to retrieve neighbors considering the distance between a target case and the centroid of a corresponding cluster. This method is applied to three real-life medical datasets. Results show that the proposed CM-CBR method produces similar or better predictive performance than the conventional CBR and clustering-CBR methods in numerous cases with significantly less computational cost.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1463-1467
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• 2005

This paper proposes an analytical redundancy technique for fault diagnostics of the sensor in steer-by-wire system. We use incorporating vehicle dynamics modeling into the design of a diagnostic system for steer-by-wire system. The use of a model of vehicle dynamics improves the speed and accuracy of the diagnoses. The proposed fault diagnostics algorithm is based on parity-space methods to generate residuals. To reduce the effects of modeling uncertainty and dynamic transients, the residuals are subject to filtering. We construct diagnostic system consisting residual threshold for detection and isolator with using the directional residual vector.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.241-243
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• 2003

일반적으로 사용되는 반도체 공정에 대한 진단 기법은 한 공정을 진행하기 전에 테스트 공정을 수행하여 공정의 진행 여부를 결정하고, 한 공정의 진행을 완료한 후에 다시 테스트 공정을 수행하여 공정의 결과를 진단하는 방법이다. 본 논문에서 제안하는 실시간 자동 진단 시스템은 기존 방법의 문제점인 자원의 낭비를 막고, 실시간으로 진단함으로써 시간의 낭비를 막는 진단 시스템을 제안한다. 실시간 자동 진단 시스템은 크게 시스템 초기화 단계, 학습 단계 그리고 예측 단계로 나누어진다. 초기화 단계는 진단할 공정에 대한 사전 입력값을 받아 시스템을 초기화하는 과정으로 공정장비 파라미터별 중요도 자동 설정 과정과 초기화 클러스터링으로 이루어진다. 학습 단계는 실시간으로 저장된 공정장치별 데이터와 계측기로부터 획득된 데이터를 이용하여 최적의 유사 클래스를 결정하는 단계와 결정된 유사 클래스를 이용하여 가중치를 학습하는 단계로 나누어진다. 예측 단계는 공정 진행 중 획득된 실시간 데이터를 학습 단계에서 결정된 파라미터별 가중치를 사용하여 공정에 대한 진단을 한다. 본 시스템에서 사용하는 클러스터링 알고리즘은 DTW(Dynamic Time Warping)를 이용하여 파라미터 데이터에 대한 특징을 추출하고 LBG(Linde, Buzo and Gray) 알고리즘을 사용하여 데이터를 군집화 한다.

• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.81-84
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• 1994

A clinically oriented EEG and EP mapping system was developed with user-friendly interface and easy interactive operations. The system was based on the graphical user interface developed with C/C++ and Software Development Kit (SDK) operated under Microsoft Windows 3.1. Continuous acquisition for the EEG signal and burst mode acquisition for EEG signal syncronized to the external stimuli arc implemented with real time display. A neural network based automatic artifact discrimation is developed and implemented with which examination time can be reduced by a factor of 3 or more. Several bands of spectral maps and spectrums arc displayed for EEG diagnosis. Amplitude maps of EP signal at specified times by operator are displayed together with cine mode of EP maps for dynamic study. Source localization and other statistical signal processing are also included.