• 전기전자학회논문지
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• 제12권3호
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• pp.158-166
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• 2008

의용 초음파 장비는 X-Ray, CT, MRI 등 다른 의료 장비보다 휴대성과 안전성면에서는 장점이 있지만 진단 시 해상도와 화질 저하를 유발하는 스펙클이 생기는 단점이 있다. 그러나 단순한 스펙클 잡음의 제거는 경계선 정보의 손실을 발생시킬 수도 있다. 이에 본 논문에서는 효과적인 스펙클 제거와 손실 없는 경계선 검출을 위해 뉴럴네트워크와 퍼지 클러스터링을 이용한 뉴로-퍼지 스펙클 제거 방법을 제안하였다. 제안된 방법은 입력된 의용 초음파 영상에 대해 먼저 퍼지 클러스터링을 적용하여 세 영역으로 나누고 이후 각 영역별로 별도의 뉴럴 네트워크를 적용하는 방법이다. 실제 실험 및 기존 방법들과의 정성적?정량적 비교 분석을 통해 제안 방법의 유용성을 검증하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.2356-2361
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• 2003

Proteome research in the medical field is expected to accelerate the understanding of disease mechanism, and to create new diagnostic concept. For protein profiling, this paper proposes a new methodology named CPDIB (Crude Protein Direct Blotting). In the CPDIB procedure, crude protein sample is directly immobilized on a membrane and the expression of protein molecules in the sample are analyzed quantitatively by using a special device called ImmobiChip, where the membrane is used as a field of the immune reaction. The over-all structure of the ImmobiChip is based on the conventional Slot blot device. Mechanical improvement in the air-tightness of the case holding the membrane realizes the direct blotting and results in high performance of stability in the immune reaction. In the measurement of multiple proteins, a dispensing robot is used for increasing the efficiency of handling of liquid. Cooperation of the dispensing robot with the ImmobiChip for immobilizing proteins realizes automated and stable performance of the CPDIB procedure. This paper shows the evaluation of the air-tightness of the ImmobiChip, the ability of analyzing proteins using the CPDIB procedure and the performance of the automated equipment.

• 대한의생명과학회지
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• 제23권2호
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• pp.57-63
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• 2017

A new body adiposity index (BAI) has been proposed that is expected to replace body mass index (BMI). We evaluated the correlations between metabolic syndrome risk factors and BAI, BMI, and other adiposity indices, such as waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR), by sex in the Korean population. We also evaluated whether BAI would be useful to diagnose metabolic syndrome. A total of 20,961 Korean adults who underwent health examinations were included in this study. The metabolic syndrome diagnostic criteria used in this study were those set by the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI). In men (12,719), BMI and WHtR were more strongly correlated to metabolic syndrome risk than BAI, and in women (8,242), WHtR showed the strongest association with metabolic syndrome risk. BAI (area under the curve [AUC] = 0.678) presented lower discriminatory capacity than that of BMI (AUC = 0.836) for diagnosing metabolic syndrome. Moreover, BAI underestimated fat levels in men and women when considering the ability to discriminate overweight and obese individuals. In conclusion, WHtR and BMI in men, and WHtR in women may be better candidates than BAI to evaluate metabolic risk factors in Korean adults.

• 정보교육학회논문지
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• 제6권1호
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• pp.1-12
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• 2002

본 논문은 초등학생의 수학과 학습능력을 진단하여서 결과에 따라 개별학습을 할 수 있는 LED 시스템 (LEarner Diagnosis system)을 설계 구현한 것이다. 수학과와 같이 위계적으로 학습이 이루어지는 교과는 선수학습을 제대로 성취하지 못하면 후속학습에 곤란을 겪는다. 이를 방지하기 위해 LED 시스템은 학습 전에 학습자의 선수 학습 능력을 진단한다. 진단 결과 학습 결손이 있을 때는 보충학습을 통해 결손을 보충하고 본 주제학습을 한다. 또한 매 학습이 완전학습이 되어 더 이상의 학습결손이 발생하지 않도록 학습 후에도 진단평가를 실시하여 완전학습이 이루어졌을때만 후속학습을 할 수 있도록 한다. LED 시스템을 이용하면 학습자는 학습결손을 방지할 수 있고 완전학습을 하기 때문에 궁극적으로 학습 목표에 도달 할 수 있게 된다.

• Clinics in Shoulder and Elbow
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• 제17권3호
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• pp.107-113
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• 2014

Background: Sonoelastography (SE) is a new technique that can assess differences in tissue stiffness, the purpose of this study was to evaluate the ability of SE to assess the long head of biceps tendon alteration. Methods: Forty shoulders of 36 consecutively registered patients with clinical symptoms and conventional ultrasonography findings of biceps tendinitis or tendinosis, and 40 asymptomatic shoulders of 20 healthy volunteers were assessed with SE. Transverse and longitudinal images of long head of biceps tendon were obtained using SE. SE images were performed by one orthopedic surgeon and evaluated by two orthopedic surgeons using an experimentally proven color grading system. Results: The transverse images of SE showed a sensitivity of 87.5%, a specificity of 95.0% and a accuracy of 91.3%, the longitudinal images of SE showed a sensitivity of 92.5%, a specificity of 90.0% and a accuracy of 91.3%. Inter-observer reliability of SE was in 'almost perfect agreement' with a weighted kappa coefficient of 0.83. Conclusions: SE is valuable in the detection of the intratendinous and peritendinous alterations of biceps tendon, and has excellent accuracy and excellent correlation with conventional ultrasound findings.

• 한국가축번식학회지
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• 제11권2호
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• pp.132-138
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• 1987

This study was carried out to evaluate the ability of clinical application of pregnancy diagnosis based upon the determinatin of progesterone in milk, utilizing a chymosin inhibitor labelled with progesterone and monoclonal antibody to progesterone, and its compared with progesterone concentrations in the milk were assayed by radioimmunoassay. 1. The progesterone concentration of the pregnant cows (2.07$\pm$0.54ng/ml) were significantly higher than those of non-pregnant cows (1.04$\pm$0.19 ng/ml), and thereafter began to increase and maintained high levels. 2. During 20 to 22 days after artificial insemination, the accuracy of pregnancy diagnosis from monoclonal antigen of progesterone were 92.9% for non-pregnant cows, and 88.5% for pregnant cows. 3. During 20 to 22 days after artificial inseminatin, the accuracy of pregnancy diagnosis from milk progesterone concentrations were 92.9% for non-pregnant cows(<3.4ng/ml), and 92.3% for pregnant cows( 4.0ng/ml). The average overall accuracy of pregnancy prediction for pregnant and non-pregnant cows were 92.6%. 4. Accordingly, the pregnancy diagnosis from monoclonal antigen of progesterone is thought to be recommendable because this early diagnostic means are simple with accurate result.

• 대한정형외과 초음파학회지
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• 제2권2호
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• pp.99-106
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• 2009

상지의 말초신경 압박 병증의 진단은 환자의 병력 및 이학적 검사로 이환된 신경 및 부위를 임상적으로 짐작할 수 있지만 신경 압박 부위를 정확히 확인하기 위해서는 전기진단적 검사가 큰 도움이 된다. 대부분 증상의 초기에는 비 수술적 치료가 선행되지만 보존적 치료의 실패로 수술적 치료가 필요할 경우는 각 신경의 가능한 압박 부위 중 정확한 위치를 추정하는 것이 성공적인 수술의 시작이 된다. 또한 전기진단적 검사와 더불어 시행되는 근골격계 초음파 검사는 전기진단적 검사만으로는 진단이 어려운 공간 점유 병소(space occupying lesion; SOL)에 의한 말초신경 압박병증의 진단 및 신경의 해부학적 변화, 신경 내부 병변의 진단에 유용한 것으로 보고되고 있다. 성공적인 말초신경 압박병증의 치료를 위해서는 이러한 다양한 진단 방법을 동원하여 정확한 부위를 확인 후 효과적인 수술을 시행하는 것이 중요하다.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권5호
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• pp.175-181
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• 2002

In this paper, fault tolerant digital governor is designed to realize ceaseless controlling and to improve the reliability of control system. Designed digital governor huts duplex I/O module and triplex CPU module and also 2 out of 3 voting algorithm and self diagnostic ability. The Processor module of the system(SIDG-3000) is developed based on 32 Bit industrial microprocessor, which guaranteed high quality of the module and SRAM for data also SRAM for command are separated. The process module also includes inter process communication function and power back up function (SRAM for back-up). System reliability is estimated by using the model of Markov process. It is shown that the reliability of triplex system in mission time can be dramatically improved compared with a single control system Designed digital governor system is applied after modelling of the steam turbine generator system of Buk-Cheju Thermal Power Plant. Simulation is carried out to prove the effectiveness of the designed digital governor system

• 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.

• 한국과학교육학회지
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• 제32권8호
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• pp.1281-1294
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• 2012

This paper describes the types of models that biology majors use and how they go about making their models in learning key concepts in biology such as the cell membrane, cytoskeleton and cell structure. Initially, a total of 44 biology students from all year levels enrolled in the second semester of calendar year 2008-2009 were asked to make their respective models of the cell membrane, cytoskeleton and cell structure. They were also asked to answer an open-ended questionnaire. Of the 44, only 20 (five from each year level) were randomly selected for a one-on-one interview. Results showed that the student-generated models from all year levels were mostly analogies, some textbook definitions and occasional drawings. In making their model, students first read the text; second, outline similarities in structure and function or both; and third, make the model. Data suggest that models are good diagnostic tools for identifying critical thinking skills of students. In this case, students mostly demonstrate the ability to recognize similarities in structure and function between the concept and their model. Some senior students demonstrated integration and reflective thinking in making their models. Thus, more opportunities for student-generated models must be available if students were to develop integration and reflective thinking in their models.