• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.214-216
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• 2012

BIT(Built-in Test)란 소프트웨어와 하드웨어의 기능 및 상태를 진단하고 오류에 대응하기 위한 방법론으로 빠른 오류 대처가 있어야 하는 다양한 분야에서 사용되고 있다. 현업에서의 BIT는 도메인의 특성에 따라 고려해야 하는 요소가 많으므로 각 도메인에 맞춰 구조화되지 않은 형태로 개발되고 있다. 따라서 기존 개발 방법론은 반복적인 작업이 수반되며 적용 환경 및 상활에 따라 변화하는 부분을 매번 새로 개발하기 위해 많은 인력과 시간이 필요하다는 문제점을 가진다. 이를 해결하기 위하여 본 논문에서는 개선된 BIT 개발 프로세스를 제안한다. 제안하는 프로세스는 BIT 처리 과정을 일반화하여 명세하고 이를 활용하여 BIT 처리 코트를 자동 생성한다. 그리고 BIT 코드를 검증할 수 있는 시뮬레이션 환경을 제공한다. 이를 통해 BIT 처리 구조 개발 과정의 편의성과 생산성을 향상하고 BIT 처리 구조의 유연성과 확장성 그리고 안정성을 높일 수 있다.

• Journal of KIISE:Software and Applications
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• v.28 no.1
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• pp.1-13
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• 2001

RMO(Region Monitor Object)는 결함전파나 객체군에 주어진 요구사항의 위반에 의해 발생하는 오류를 처리하는 실시간객체로써 여러 실시간객체의 상태를 감시 및 분석하여 오류를 감지하고, 증상을 진단한 후 알맞은 복구 및 재구성을 실행하다, 이를 위하여 RMO는 응용 실시간객체를 감시할 수 있는 권한을 갖는다. RMO의 권한을 지원해주는 구조는 결함허용 중개자를 이용한다. 결함허용 중개자(FTB 또는 Fault Tolerance Broker)는 RMO가 응용 실시간객체를 감시할 때에 응용의 설계와 응용의 위치에 투명하게 수행될 수 있게 중개자 역할을 한다. 제안하는 감시 구조에는 결함허용 중개자가 응용 실사간객체마다 스터브로 붙는 스터브 방식과 각 노드의 커널에 모듈로 존재하는 커널 모듈 방식이 있다. 본 논문은 스터브 방식에서 RMO가 응용 실시간객체를 감시하는 구조를 제시하고 구현한다. 결함허용 중개자 스터브는 응용 실시간객체와 같은 주소 공간에 존재하면서 응용 실시간객체에서 발생하는 메세지를 가로채고 소속자료에 접근한다. RMO는 결함허용 중개자 스터브가 제공하는 인터페이스를 통해서 응용 실시간객체에 대한 감시 정보를 얻는다. 제안한 감시 구조는 실시간객체 모델인 dRTO(dependable RTO) 모델에 기반하여 설계하였고 실시간 커널인 dKernel 상에서 구현 및 실험하였으나 다른 모델이나 커널에도 적용될 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1208-1210
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• 2012

BIT(Built-In Test)란 S/W 또는 H/W 의 기능 및 상태를 진단하고 오류에 대응하기 위한 방법론으로 기능에 대한 신뢰성 및 빠른 오류 복구를 보장하기 때문에 다양한 분야에서 BIT 처리를 통해 시스템의 안정성을 높이고 있다. 현업에서의 BIT 는 도메인 특성에 따라 처리해야 하는 작업의 변화가 크기 때문에 구조화 되지 않은 형태로 각각 개발되고 있다. 따라서 BIT 개발 시 반복적인 작업이 수반되며 처리 과정의 수정 또는 처리 범위의 확장을 위해서는 많은 시간 및 인력이 요구된다. 이에 본 논문에서는 BIT 처리를 구조화하기 위하여 처리과정에 필요한 정보들을 일반화된 형태로 기록할 수 있도록 하는 BIT 처리 병세 방안과 BIT 처리 명세를 기반으로 한 자동 코드 생성 체계를 제안한다. 이를 통해 개발 과정의 편의성과 생산성을 향상하고 BIT 처리의 유연성과 확장성을 높일 수 있다.

• The Journal of Korean Institute of Information Technology
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• v.17 no.5
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• pp.77-82
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• 2019

Diabetic retinopathy is a complicated form of diabetes due to circulatory disorder in the peripheral blood vessels of the retina. We segment the microvessel for diagnosing diabetic retinophathy. The conventional methods using filter and features can segment the thick blood vessels, but it has relatively weak for segmenting fine blood vessels. In pre-processing step, noise reduction filter and histogram equalization are applied to suppress the noise and enhance the image contrast. Then, deep learning technique is used for pixel-by-pixel segmentation. The accuracy of conventional methods is between 90% to 94%, while the proposed method has improved as 95% accuracy. There is a problem of segmentation error around the optic disc and exudate due to the network depth. However the accuracy can be improved by modifying the network architecture in the future.

• Journal of Service Research and Studies
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• v.3 no.2
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• pp.33-44
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• 2013

As the Internet and mobile services increase, the use of wired/wireless web contents services increase and the demand for various contents explosively grows. To survive in competitive market, and to minimize the errors and warnings for web accessibility and standardization, and then to maximize the web usability, the periodical evaluation for web site should be performed with the events of web marketing and campaign. Through the web evaluation, the errors for technical programming language and contents offering can be found and diagnosed. In this paper, the quantitative and qualitative evaluation method for web site providing web contents are presented, and the analytic results for the 138 home pages in domestic are evaluated to validate the quantitative methodology. The accessibility, standardization, and usability factor are adopted for the evaluation in which accessibility is evaluated for perceivable, operable, understandable, and robust discipline with K-WAH(Korea-Web Accessibility Helper) tool, the standardization are measured for the number of errors and warnings in technical language with the W3C validator, and finally the usability factor is analyzed for the number of visits, average visit duration, and bounce rate with Google Analytics. In addition to, the quantitative analysis is also performed with the consideration of cost for construction and operation of web site. From the results, in the case of total score of 100 in conversion with relative weight, the average and standard deviation are evaluated to be 55 and 14, respectively. The correlation analysis indicates that the coefficient is estimated as 0.058, and then correlation between the quantitative results and cost is evaluated to be a little positive.

• Journal of the Korean Society of Radiology
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• v.84 no.6
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• pp.1324-1336
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• 2023

Purpose This study aimed to compare the diagnostic performance of cardiac CT and transthoracic echocardiogram (TTE) depending on the degree of valvular calcification and bicuspid aortic valve (BAV) subtype. Materials and Methods This retrospective study included 266 consecutive patients (106 with BAV and 160 with tricuspid aortic valve) who underwent cardiac CT and TTE before aortic valve replacement. Cardiac CT was used to evaluate the morphology of the aortic valve, and a calcium scoring scan was used to quantify valve calcium. The aortic valves were classified into fused and two-sinus types. The diagnostic accuracy of cardiac CT and TTE was calculated using a reference standard for intraoperative inspection. Results CT demonstrated significantly higher sensitivity, negative predictive value, and accuracy than TTE in detecting BAV (p < 0.001, p < 0.001, and p = 0.003, respectively). The TTE sensitivity tended to decrease as valvular calcification increased. The error rate of TTE for CT was 10.9% for the twosinus type of BAV and 28.3% for the fused type (p = 0.044). Conclusion Cardiac CT had a higher diagnostic performance in detecting BAV than TTE and may help diagnose BAV, particularly in patients with severe valvular calcification.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.23 no.1
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• pp.77-81
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• 2001

Necrotizing fasciitis is defined as infectious disease showing extensive necrosis of the superficial fascia with widespread involvement of the surrounding tissues and concurrent systemic toxicity. It is found commonly in the extremities, the trunk and the perineum, but shows extremely rare occurrence in the well vascularized area such as head and neck area. Occurred in the head and neck area, it is called "cervicofacial necrotizing fasciitis" (CFNF). It is a fatal disease which carries a mortality rate up to 60%. Early diagnosis, aggressive surgical debridement of necrotic tissues and massive antibiotics therapy are essential for achieving a favorable outcome. We present a case of cervicofacial necrotizing fasciitis in 35-year-old male patient with literature review.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.5
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• pp.50-57
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• 2016

The present study proposed three inspection reliability indices which compared inspection results evaluated at in-depth(routine) inspection and in-depth safety inspection; Nominal inspection reliability index, Real inspection reliability index, and DS nominal inspection reliability index. The methods to improve the inspection reliability were also proposed. Since bridge inspection process is critical to ensuring the safety of bridges and identifying repair and maintenance needs, the quality of the inspection data produced from the inspection process is very important. Consequently, the inspection reliability indices were suggested to evaluate quality of current inspection practices. Specifically, approximately 85% of inspection errors evaluated by the DS nominal inspection reliability index are within 1 rating grade(equal to or less than damage score ${\pm}0.1$). In order to improve the inspection reliability, transportation agency should implement QC(Quality Control) practices and develop professional expertises of inspectors by higher requirements for inspectors, on-off line inspection training and etc.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.938-946
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• 2001

A web support open environment in which flexibility that allows it to be applied in the education field has gradually evolved but the WBI(Web Based Instruction) which compose it have many limitations and problems, as far as learning efficiency is concerned. In particular, existing web-based estimation systems just give information on whether learner's replies are 'correct' or 'incorrect' and offer the learners evaluations of results in terms of scores. Therefore it is difficult for the learners to get more detailed information about their shortcomings and errors. What is needed for the learners is that web based instruction systems diagnose learner's comprehension status, providing c causes: Why did the learners make the errors\ulcorner In this paper, we propose the development of a web-based instruction system that learners can access with their browsers at any time and no matter where they are. Our system has a facility that analyses learner's weak points and diagnoses error cause, giving advice to learners and more detailed error information than existing systems. By accumulating user behaviors, relevant individualized information on the learners can be given.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.45-52
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• 2008

As the recent development of the IT services, there is a urgent need of effective diagnosis system to present appropriate solution for the complicated problems of breakdown control, a cause analysis of breakdown and others. So we propose an intelligent diagnosis system that integrates the case-based reasoning and the artificial neural network to improve the system performance and to achieve optimal diagnosis. The case-based reasoning is a reasoning method that resolves the problems presented in current time through the past cases (experience). And it enables to make efficient reasoning by means of less complicated knowledge acquisition process, especially in the domain where it is difficult to extract formal rules. However, reasoning by using the case-based reasoning alone in diagnosis problem domain causes a problem of suggesting multiple causes on a given symptom. Since the suggested multiple causes of given symptom has the same weight, the unnecessary causes are also examined as well. In order to resolve such problems, the back-propagation learning algorithm of the artificial neural network is used to train the pairs of the causes and associated symptoms and find out the cause with the highest weight for occurrence to make more clarified and reliable diagnosis.