• The Journal of Korea CHUNA Manual Medicine
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• v.4 no.1
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• pp.1-16
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• 2003

Objectives : The purpose of this study is researching for possibility that Moire topography be applied in group school screening for scoliosis known school health problem, and find acceptable method of early detection and early treatment for scoliosis Methods : The authors practiced Moire topography for primary & middle school 1,895 students[male 976, female 919] in Jeonju, korea in 2001. After we distinguished students who had abnormal finding in Moire topography and then re-examined spinal X-ray analysis. The data was analysed and evaluated statistically Results : According to this research, the abnormal finding in Moire topography was 53.7% (1,018 students), and students needed X-ray re-examination were 11.2% (213 students). Students diagnosed scoliosis by X-ray re-examination were 1.8%. According to statistical analysis, interval between vertical base line of pelvis and vertical base line of neck, gap between left distance and right distance to the vertical base line of pelvis and difference of contour lines have strong correlations with deformity degree of the body surface examined by Moire. Conclusions : Following this research, throughout early detection for scoliosis by Moire topography could reduce exposure from scoliosis radiographs, and could detect trunk asymmetry that couldn't be found existing X-ray examination, so it made selecting students under observation who have bad posture possible.

• Tribology and Lubricants
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• v.27 no.3
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• pp.125-133
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• 2011

The purpose of this study is to develop an engine oil quality monitoring system to warn the abnormal condition of engine oil. To do this, first of all, it is needed a personal controller development to measure the capacitance of a pre-developed engine oil deterioration detection sensor integrated with an oil filter. To measure the capacitance of engine oil in the sensor, it is used the way measuring the electric charging time in a capacitor by impressing DC volt. This method has merits on cost and signal stability. The measured capacitance is compensated by comparing with the one measured by an impedance analyzer. Also, using the dielectric constant gained by an impedance analyzer, the calculating equation of the dielectric constant of engine oil related with the currently developed sensor is decided. Then, the deterioration degree of engine oil is estimated according to the change rate of dielectric constant between green oil and used oil. Finally, using this dielectric constant information together with engine oil temperature and pressure, the currently developed engine oil quality monitoring system is to tell the abnormal state of engine oil.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.368-372
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• 2009

The method to get the feature have been proposed to recognize the user activity by setting specific action for making the user independent result in previous research. However, it was only applied in specific environment and it was difficult to implement because it regarded only some specific feature as the recognized object. To improve this problem we detected the normality/abnormality of the activity based on the repetition and the continuity of the past activity pattern. We applied the unsupervised learning method, not supervised, and clustered the data which was collected within a certain period of time and we regarded it as the basis of the evaluation of the repetition. We demonstrated to be able to detect the abnormal activity based on wether the data was generated repeatedly.

• The Korean Journal of Cytopathology
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• v.14 no.2
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• pp.43-52
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• 2003

The incidence of cervical cancer has been gradually decreased since 1990, now it ranks the fourth most common carcinoma among Korean women in 2001. If squamous cell carcinomas in situ are included, the cervical cancer is still the most frequent tumor in Korean women. However, cervical cancer mortality in Korea has been decreased over the last 10 years in large part attributable to the introduction of the Papanicolaou test (Pap. test). The guidelines for the early detection of cervical cancer recommend women aged 30 and more to lake biennial screening with Pap. lest. According to the screening data of National Health Insurance Corporation (NHIC), 4,425 women (0.94%) showed an abnormal Pap among 473,395 cases tested in 2001; dysplasia was in 3,953 (0.84%) women, in situ carcinoma in 357 (0.075%) women, and invasive carcinoma in 115 (0.024%) women. The detection rates of abnormal Pap. were 4.21% in Korean Society for Cytopathology(KSC-2001), 1.37% (ASCUS : 0.26%, AGUS : 0.03%, LSIL : 0.45%, HSIL : 0.55%, Carcinoma 0.09%) in health check-up and 5.41% (ASCUS : 1.89%, AGUS . : 0.69%, LSIL : 1.39%, HSIL : 0.84%, Carcinoma : 0.64%) of patients in out-patient clinic without having history of cervical neoplasia at Hanyang University Hospital in 2002 Low rate of cervical cancer screening (34%) in Korea is mainly due to the lack of information for the Row income people regarding national cancer screening program. More adenuate budget by government and more man-power for precise screening, new guideline and system for management of the cervical cancer patients are required.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.95-101
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• 2019

Entering the era of the 4^th Industrial Revolution and the Internet of Things, various services are growing rapidly, and various researches are actively underway. Among them, research on abnormal behaviors on various devices that are being used in the IoT is being conducted. In a hyper-connected society, the damage caused by one wrong device can have a serious impact on the various connected systems. In this paper, We propose a technique to cope with the problem that the threats caused by various abnormal behaviors such as anti-debugging scheme, anomalous process detection method and back door detection method on how to increase the safety of the device and how to use the device and service safely in such IoT environment.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.293-299
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• 2004

This paper is about the extraction of basis function for ECG signal processing. In the first step, it is assumed that ECG signal consists of linearly mixed independent source signals. 12 channel ECG signals, which were sampled at 600sps, were used and the basis function, which can separate and detect source signals - QRS complex, P and T waves, - was found by applying the fast fixed point algorithm, which is one of learning algorithms in independent component analysis(ICA). The possibilities of significant point detection and classification of normal and abnormal ECG, using the basis function, were suggested. Finally, the proposed method showed that it could overcome the difficulty in separating specific frequency in ECG signal processing by wavelet transform. And, it was found that independent component analysis(ICA) could be applied to ECG signal processing for detection of significant points and classification of abnormal beats.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.27-37
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• 1997

Internal combustion engine is the main source of environmental pollutants and therefore better technology is required to reduce harmful elements from the exhaust gases all over the world. Especially, harmful elements from the exhaust gases are caused by incomplete combustion of mixture inside the engine cylinder and this abnormal combustion like misfire or partial burning is the direct cause of the air pollution and engine performance degradation. the object of this research is to detect abnormal combustion like misfire and to keep the engine performance in the optimal operating state. Development of a new system therefore could be applied to a real car. To realize this, the spark-plug in a conventional ignition system is used as a misfire detection sensor and breakdown voltage is analyzed. In this research, bias voltage(about 3kV) was applied to the electrodes of spark-plug and breakdown voltage signal is obtained. This breakdown voltage signal is analyzed and found that a combustion phenomena in engine cylinder has close relationship with harmonic coefficient K which was introduced in this research. Newly developed combustion diagnostic method( breakdown voltage signal analysis) from this research can be used for the combustion diagnostic and combustion control system in an real car.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.515-520
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• 2018

A large number of lithium-ion batteries are arranged in series and parallel in battery packs, such as those in electric vehicles or energy storage systems. As battery packs age, their output power and energy density drop because of voltage deviation, constant and non-uniform exposure to abnormal environments, and increased contact resistance between batteries; this reduces application system efficiency. Despite the balancing circuit and logic of the battery management system, the output of the battery pack is concentrated in the most severely aged unit cell and the output is frequently limited by power derating. In this study, we implemented a cell imbalance detection algorithm and selected parameters to detect a sudden decrease in battery pack output. In addition, we propose a method to increase efficiency by applying the measured testing values considering the operating conditions and abnormal conditions of the battery pack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.632-657
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• 2022

Detecting web attacks is a major challenge, and it is observed that the use of simple models leads to low sensitivity or high false positive problems. In this study, we aim to develop a robust two-stage deep learning based stacked ensemble web application firewall. Normal and abnormal classification is carried out in the first stage of the proposed WAF model. The classification process of the types of abnormal traffics is postponed to the second stage and carried out using an integrated stacked ensemble model. By this way, clients' requests can be served without time delay, and attack types can be detected with high sensitivity. In addition to the high accuracy of the proposed model, by using the statistical similarity and diversity analyses in the study, high generalization for the ensemble model is achieved. Within the study, a comprehensive, up-to-date, and robust multi-class web anomaly dataset named GAZI-HTTP is created in accordance with the real-world situations. The performance of the proposed WAF model is compared to state-of-the-art deep learning models and previous studies using the benchmark dataset. The proposed two-stage model achieved multi-class detection rates of 97.43% and 94.77% for GAZI-HTTP and ECML-PKDD, respectively.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.89-92
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• 2021

In a manufacturing fields, an abnormality or breakdown of equipment is a factor that causes product defects. Recently, with the spread of smart factory services, a lot of research to predict and prevent machine's failures is actively ongoing. However, there is a big difficulty in developing a classification model because the number of abnormal or failure data of the machine is severely smaller than normal data. In this paper, we present an algorithm for detecting abnormalities in an MCT at manufacturing work site depending on the differences between inputs and outputs of Autoencoder model and analyze its performance. The algorithm detects abnormalities using only features of normal data from manufacturing data of the MCT in which abnormal data does not exist.