• 한국인공지능학회지
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• 제8권1호
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• pp.7-9
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• 2020

In this paper, a study was conducted to find a self-diagnosis method to prevent the spread of COVID-19 based on machine learning. COVID-19 is an infectious disease caused by a newly discovered coronavirus. According to WHO(World Health Organization)'s situation report published on May 18th, 2020, COVID-19 has already affected 4,600,000 cases and 310,000 deaths globally and still increasing. The most severe problem of COVID-19 virus is that it spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, which occurs in everyday life. And also, at this time, there are no specific vaccines or treatments for COVID-19. Because of the secure diffusion method and the absence of a vaccine, it is essential to self-diagnose or do a self-diagnosis questionnaire whenever possible. But self-diagnosing has too many questions, and ambiguous standards also take time. Therefore, in this study, using SVM(Support Vector Machine), Decision Tree and correlation analysis found two vital factors to predict the infection of the COVID-19 virus with an accuracy of 80%. Applying the result proposed in this paper, people can self-diagnose quickly to prevent COVID-19 and further prevent the spread of COVID-19.

• 인지과학
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• 제13권1호
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• pp.53-59
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• 2002

본 논문은 퍼지 인지 맵과 퍼지 연상 메모리를 사용하여 열과 온도에 관한 학생들의 과학개념 이해에서 발생되는 오인을 진단할 수 있는 오인 진단 모델을 제시한다. 오인 진단 모델에서 퍼지 인지 맵은 과학현상에 대한 학생들이 가지는 선입개념들과 오인들을 인과관계로 표현할 수 있다. 또한 개념간의 인과관계를 기억할 수 있는 퍼지 연상 메모리를 통하여 오인의 원인들을 진단한다. 본 연구는 기존의 학습 오인을 진단하는 규칙기반 전문가 시스템의 한계성을 극복할 수 있는 새로운 방법을 제공하며, 교육분야의 다양한 영역에서 학습자들의 학습 진단을 위한 지능형 개인교수 시스템으로 적용될 수 있을 것이다.

• Journal of Korean Neurosurgical Society
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• 제48권1호
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• pp.88-90
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• 2010

Retroperitoneal hematoma (RH) due to radiologic intervention for an intracranial lesion is relatively rare, difficult to diagnose, and can be lifethreatening. We report a case of RH that developed in a patient on anticoagulant therapy following endovascular coiling of a ruptured anterior communicating artery (AcoA) aneurysm. An 82-year-old man presented with a 12-day history of headache. Computed tomography (CT) on admission demonstrated slight subarachnoid hemorrhage, and left carotid angiography revealed an AcoA aneurysm. The next day, the aneurysm was occluded with coils via the femoral approach under general anesthesia. The patient received a bolus of 5,000 units of heparin immediately following the procedure, and an infusion rate of 10,000 units/day was initiated. The patient gradually became hypotensive 25 hours after coiling. Abdominal CT showed a huge, high-density soft-tissue mass filling the right side of the retroperitoneum space. The patient eventually died of multiple organ failure five days after coiling. RH after interventional radiology for neurological disease is relatively rare and can be difficult to diagnose if consciousness is disturbed. This case demonstrates the importance of performing routine physical examinations, sequentially measuring the hematocrit and closely monitoring systemic blood pressures following interventional radiologic procedures in patients with abnormal mental status.

• 산업경영시스템학회지
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• 제42권4호
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• pp.126-134
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• 2019

Nowadays, since there are so many big data available everywhere, those big data can be used to find useful information to improve design and operation by using various analysis methods such as data mining. Especially if we have event log data that has execution history data of an organization such as case_id, event_time, event (activity), performer, etc., then we can apply process mining to discover the main process model in the organization. Once we can find the main process from process mining, we can utilize it to improve current working environment. In this paper we developed a new method to find a final diagnosis of a patient, who needs several procedures (medical test and examination) to diagnose disease of the patient by using process mining approach. Some patients can be diagnosed by only one procedure, but there are certainly some patients who are very difficult to diagnose and need to take several procedures to find exact disease name. We used 2 million procedure log data and there are 397 thousands patients who took 2 and more procedures to find a final disease. These multi-procedure patients are not frequent case, but it is very critical to prevent wrong diagnosis. From those multi-procedure taken patients, 4 procedures were discovered to be a main process model in the hospital. Using this main process model, we can understand the sequence of procedures in the hospital and furthermore the relationship between diagnosis and corresponding procedures.

• 제어로봇시스템학회논문지
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• 제15권4호
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• pp.406-412
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• 2009

ECG is used on purpose to keep good health or monitor cardiac function of aged person as well as on purpose to diagnose the disease of heart patients. The ambulatory ECG monitoring system under guarantee of safety and accuracy is very efficient to prevent the progress of heart disease and sudden death. These systems can detect the temporary change of ECG that is very significant to diagnose heart disease such as myocardial ischemia, arrhyamia and cardiac infarction. In this paper, we describe the ECG signal analysis algorithm and measurement device for ECG monitoring. The authors designed a small-size portable ECG device that consisted of instrumentation amplifier, micro-controller, filter and RF module. The device measures ECG with four electrodes on the body and detects QRS complex and ST level change in realtime. Also it transmits the measured signals to the personal computer. The developed software for ECG analysis in personal computer has the function to detect the feature points and ST level changes.

• Journal of Forest and Environmental Science
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• 제34권1호
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• pp.95-100
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• 2018

Rabies causes the highest mortality of all viral diseases in the world unless the victim has been protected either by active immunization or post-exposure immunoprophylaxis. Infected stray dogs, raccoons, skunks, foxes and bats are the demonstrated carriers of most cases of rabies. It is difficult to diagnose a rabid animal in the field unless characteristic clinical signs are evident. However, this study used a commercial fast check kit comprised of immunochromatographic test (ICT) strips (ICTS) to diagnose rabies infection in clinically suspected samples obtained from a wildebeest. A 10-year old male wildebeest (approximate weight, 150 kg) died at Bangabandhu Sheikh Mujib Safari (BSMS) Park, Cox's Bazar, Bangladesh with a clinical history of severe excitation and abundant oral secretions. A gross pathological examination revealed no specific lesions indicating any fatal diseases. The entire brain was collected within 6 hours of death, and the brain sample was tested using the ICT strips following the manufacturer's directions. The rabies viral antibody was detected within the brain stem and medulla of the brain tissue of the dead wildebeest.

• 품질경영학회지
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• 제44권2호
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• pp.277-296
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• 2016

Purpose: Propose model to diagnose and assess National Defense Industry and quality management by investigating and analyzing established standard model. Methods: Research on established internal model including MB, EQA and JQA model and make standard index for quality index extraction and quantitative index to test objectively for internal state. Results: Extract advantage and disadvantage by performance of National Defense Industry level diagnose and build foundation for quality management policy and road map. Conclusion: Due to result of diagnostic assesment of quality management of national defense industry, dependability, SCQM and safety part shows vulnerability and require improvement and support.

• Journal of Information Technology Applications and Management
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• 제21권1호
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• pp.53-67
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• 2014

In recent years, more data is being generated for the activation of the SNS, the spread of Smartphones and the development of IT technology. Therefore, it is to collect large amounts of data, analyze and ensure meaningful information has become important. The use of these data are formed on the global trend. Big data so-called, has attracted attention as a source of new business. Big Data can then give us the opportunity to be able to create a new customer and diversify the business. So, many companies have investment and effort for big data utilization. However, technology, infrastructure, human resources is different for each of the companies. Therefore, it is necessary to diagnose the level of big data utilization companies. In this study, through a literature review of existing, we derived the success factors for the big data utilization. And developed a diagnostic indicator that allows success factors derived, can be used to determine levels of big data utilization of the company. In addition, as a development of diagnostic indicators, were carried out case studies to diagnose company. Through this study, it will be an opportunity to be able to be reflected in the strategy of big data utilization company.

• 한국수학교육학회지시리즈A:수학교육
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• 제50권1호
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• pp.89-102
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• 2011

The purpose of this study is to diagnose the problems of mathematics education in Korea by conducting an in-depth analysis of international comparative studies, a Delphi method, and a survey. Further analysis of TIMSS and PISA results also reveals several negative aspects of mathematics education practice in Korea. The mathematics education experts' opinions collected by Delphi method were classified into 12 categories: private education and test-driven education, curriculum and textbooks, lessons, evaluation, teacher, learner, teaching aid and facilities. affective aspects of mathematics, discrepancy between a theory and a practice, preservice/inservice teacher education and teacher employment test, education policy, and overall. Another survey was conducted to focus more on the development of curriculum which is a pending issue. Considering the fact that mathematics education should contribute to improve practical aspect as well as elaborate theoretical aspect, this study lays a foundation of improvement of mathematics education in Korea.

• 한국정밀공학회지
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• 제30권7호
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• pp.687-693
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• 2013

The service conditions of railway cars have become more difficult in recent years due to increased speed. Faulty components in the railcars may result in service interruption, or in extreme cases, derailment. Thus, it is important to diagnose and monitor the main components of railcars. Temperature monitoring is one of the basic methods used to diagnose abnormal conditions in the main components of railway cars, such as in bearings, reduction gears, and traction motors. In this study, we developed a monitoring system for the main components, using an infrared thermography technique. This technique has the advantage of infrared thermal camera imaging of temperature contours in the components. Various hardware and software components of the monitoring system are used to acquire the sensor data, to identify potential problems in railcar operation.