• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.259-262
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• 2005

This paper addresses the problem of protecting security policies in security mechanisms, such as the detection policy of an Intrusion Detection System. Unauthorized disclosure of such information might reveal the fundamental principles and methods for the protection of the whole network. In order to avoid this risk, we suggest two schemes for protecting security policies in Snort using the symmetric cryptosystem, Triple-DES.

• Asian Pacific Journal of Cancer Prevention
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• 제16권2호
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• pp.559-564
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• 2015

Background: The participation of women in cervical cancer screening in Malaysia is low. Self-sampling might be able to overcome this problem. The aim of this study was to assess the reliability of self-sampling for cervical smear in our country. Materials and Methods: This cross-sectional study was conducted on 258 community dwelling women from urban and rural settings who participated in health campaigns. In order to reduce the sampling bias, half of the study population performed the self-sampling prior to the physician sampling while the other half performed the self-sampling after the physician sampling, randomly. Acquired samples were assessed for cytological changes as well as HPV DNA detection. Results: The mean age of the subjects was $40.4{\pm}11.3years$. The prevalence of abnormal cervical changes was 2.7%. High risk and low risk HPV genotypes were found in 4.0% and 2.7% of the subjects, respectively. A substantial agreement was observed between self-sampling and the physician obtained sampling in cytological diagnosis (k=0.62, 95%CI=0.50, 0.74), micro-organism detection (k=0.77, 95%CI=0.66, 0.88) and detection of hormonal status (k=0.75, 95%CI=0.65, 0.85) as well as detection of high risk (k=0.77, 95%CI=0.4, 0.98) and low risk (K=0.77, 95%CI=0.50, 0.92) HPV. Menopausal state was found to be related with 8.39 times more adequate cell specimens for cytology but 0.13 times less adequate cell specimens for virological assessment. Conclusions: This study revealed that self-sampling has a good agreement with physician sampling in detecting HPV genotypes. Self-sampling can serve as a tool in HPV screening while it may be useful in detecting cytological abnormalities in Malaysia.

• Journal of Applied Biological Chemistry
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• 제64권2호
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• pp.177-184
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• 2021

축산용 항생제는 투여된 양의 일부만이 체내에서 사용되며 나머지는 분뇨로 배출되며 이를 활용한 퇴비를 농경지에 살포함으로써 농업환경에 유입되어 2차 오염 등을 초래하고 있다. 따라서, 농업환경 중 항생제 관리기준 설정 등 사후 관리 기술이 필요하다. 본 연구는 국내 사용빈도가 높은 것으로 알려진 tetracycline 및 sulfonamide 계열 등의 항생제를 대상으로 매체별 잔류량을 비교하고 퇴비 시용 전·후 농경지 토양 중 잔류항생제의 위해성을 평가하기 위하여 수행되었다. Buffer 및 SPE를 사용한 전처리 방법은 ppb 수준에서 70% 이상의 회수율을 나타냈으며, 검출한계(LOD)의 범위는 퇴비와 토양에서 각각 0.13-0.46 ㎍/kg과 0.05-0.25 ㎍/kg이었다. 잔류 항생제 분석결과 퇴비 중 tetracycline 계열 항생제의 잔류 농도는 5.38-196.0 ㎍/kg, sulfonamide 계열은 below the detection of limit (BDL)-259.0 ㎍/kg 수준으로 검출되었다. 농경지 토양의 경우 각각 0.30-53.3 ㎍/kg, BDL-4.16 ㎍/kg의 잔류 수준을 나타냈으며 토양분배계수(Kd) 값이 높은 tetracycline 계열 항생제의 잔류 농도가 sulfonamide 계열보다 높았다. 퇴비 시용 전후의 농경지 토양의 항생제에 대한 인체위해도는 항생제 종류에 따른 차이가 있었으나, 전체 HQ가 1 이하에서 안전하다는 기준에 의하면 조사된 항생제 5종 모두 인체 위해성이 매우 낮았으며 시용 전·후의 영향이 전체 위해도에 미치는 비율을 고려하면, 퇴비시용이 토양의 항생제에 대한 인체위해성에 미치는 영향은 미비한 것으로 판단되었다.

• 생약학회지
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• 제53권3호
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• pp.170-180
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• 2022

Polycyclic aromatic hydrocarbons(PAHs) contents were analyzed by measuring benz(a)anthracene(BaA), chrysene(Chr), benzo(b)fluoranthene(BbF) and benzo(a)pyrene(BaP), and the related risk characterization was conducted for 113 samples out of 14 different agricultural products used for food and medicine. Detection rate of PAHs was 90.3% as a whole, and the highest one was 80.5% for BaP. The detection rate of BaP exceeding the maximum permitted concentration of Rehmanniae Radix Preparata and Rehmanniae Radix, 5.0 ㎍/kg was 1.8%, and the detection rates of BaA, Chr and BbF were within the range of 2.7~10.6%. The highest average concentration of BaA was 3.41 ㎍/kg detected from Lycii Fructus, while those of Chr, BbF, BaP and PAH4(sum of detected BaA, Chr, BbF and BaP) were 5.00, 1.79, 2.36, 12.36 ㎍/kg, respectively, detected from Rehmanniae Radix Preparata. As for the risk characterization on PAHs, the overall MOE(Margin of Exposure) values were measured within the range of 10⁵~10⁷, which is unlikely to cause direct health concerns, but the worring values of MOE were measured 6.57×10⁴ for BaP and 6.10×10⁴ for PAH4 from Rehmanniae Radix Preparata, which may require an improvement plan to reduce BaP contents.

• 센서학회지
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• 제21권1호
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• pp.39-45
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• 2012

Recently the convergence of healthcare technology is used for daily life healthcare monitoring. Cardiac arrhythmia is presented by the state of the heart irregularity. Abnormal heart's electrical signal pathway or heart's tissue disorder could be the cause of cardiac arrhythmia. Fatal arrhythmia could put patient's life at risk. Therefore arrhythmia detection is very important. Previous studies on the detection of arrhythmia in various ECG analysis and classification methods had been carried out. In this paper, an ECG signal processing techniques to detect abnormal ECG based on DTW minimum accumulation distance through the template matching for normalized data and variable threshold method for ECG R-peak detection. Signal processing techniques able to determine the occurrence of normal ECG and abnormal ECG. Abnormal ECG detection algorithm using DTW minimum accumulation distance method is performed using MITBIH database for performance evaluation. Experiment result shows the average percentage accuracy of using the propose method for Rpeak detection is 99.63 % and abnormal detection is 99.60 %.

• Smart Structures and Systems
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• 제28권6호
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• pp.811-825
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• 2021

High-voltage isolating switches play a paramount role in ensuring the safety of power supply systems. However, their exposure to outdoor environmental conditions may cause serious physical defects, which may result in great risk to power supply systems and society. Image processing-based methods have been used for anomaly detection. However, their accuracy is affected by numerous uncertainties due to manually extracted features, which makes the anomaly detection of isolating switches still challenging. In this paper, a vision-based anomaly detection method for isolating switches, which uses the rotational angle of the switch system for more accurate and direct anomaly detection with the help of deep learning (DL) and image processing methods (Single Shot Multibox Detector (SSD), improved frame differencing method, and Hough transform), is proposed. The SSD is a deep learning method for object classification and localization. In addition, an improved frame differencing method is introduced for better feature extraction and a hough transform method is adopted for rotational angle calculation. A number of experiments are conducted for anomaly detection of single and multiple switches using video frames. The results of the experiments demonstrate that the SSD outperforms the You-Only-Look-Once network. The effectiveness and robustness of the proposed method have been proven under various conditions, such as different illumination and camera locations using 96 videos from the experiments.

• 한국임상수의학회지
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• 제36권1호
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• pp.15-22
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• 2019

Highly pathogenic avian influenza (HPAI) is among the top infectious disease priorities in Korea and the leading cause of economic loss in relevant poultry industry. An understanding of the spatial epidemiology of HPAI outbreak is essential in assessing and managing the risk of the infection. Though previous studies have reported the majority of outbreaks occurred clustered in what are preferred to as densely populated poultry regions, especially in southwest coast of Korea, little is known about the spatial distribution of risk areas vulnerable to HPAI occurrence based on geographic information system (GIS). The main aim of the present study was to develop a GIS-based risk index model for defining potential high-risk areas of HPAI outbreaks and to explore spatial distribution in relative risk index for each 252 Si-Gun-Gu (administrative unit) in Korea. The risk index was derived incorporating seven GIS database associated with risk factors of HPAI in a standardized five-score scale. Scale 1 and 5 for each database represent the lowest and the highest risk of HPAI respectively. Our model showed that Jeollabuk-do, Chungcheongnam-do, Jeollanam-do and Chungcheongbuk-do regions will have the highest relative risk from HPAI. Areas with risk index value over 4.0 were Naju, Jeongeup, Anseong, Cheonan, Kochang, Iksan, Kyeongju and Kimje, indicating that Korea is at risk of HPAI introduction. Management and control of HPAI becomes difficult once the virus are established in domestic poultry populations; therefore, early detection and development of nationwide monitoring system through targeted surveillance of high-risk spots are priorities for preventing the future outbreaks.

• 한국컴퓨터정보학회논문지
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• 제9권1호
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• pp.37-43
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• 2004

컴퓨터 네트워크의 확대 및 인터넷 이용의 급속한 증가에 따라 컴퓨터 보안문제가 중요하게 되었다 따라서 침입자들로부터 위험을 줄이기 위해 침입탐지 시스템에 관한 연구가 진행되고 있다. 본 논문에서는 네트워크 기반의 이상 침입 탐지를 위하여 뉴로-퍼지 기법을 적용하고자 한다 불확실성을 처리하는 퍼지 이론을 이상 침입 탐지영역에 도입하여 적용함으로써 오용 탐지의 한계성을 극복하여 알려지지 않은 침입탐지를 하고자 한다.

• 한국시뮬레이션학회논문지
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• 제8권3호
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• pp.105-121
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• 1999

Computer security is considered important due to the side effect generated from the expansion of computer network and rapid increase of the use of computers. Intrusion Detection System(IDS) has been an active research area to reduce the risk from intruders. We propose a new IDS model, which consists of several computers with IDS, based on the immune system model and describe the design of the IDS model and the prototype implementation of it for feasibility testing and evaluate the performance of the IDS in the aspect of detection time, detection accuracy, diversity which is feature of immune system, and system overhead. The IDSs are distributed and if any of distributed IDSs detect anomaly system call among system call sequences generated by a privilege process, the anomaly system call can be dynamically shared with other IDSs. This makes the IDSs improve the ability of immunity for new intruders.

• 스마트미디어저널
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• 제7권4호
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• pp.79-89
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• 2018

In recent years, falls among elderly people have gained serious attention as a major cause of injuries. Falls often lead to fatal consequences due to lack of prompt response and rescue. Therefore, a more accurate fall detection system and an effective feature extraction technique are required to prevent and reduce the risk of such incidents. In this paper, we proposed an efficient feature extraction technique based on multiple sliding windows and validated it through a series of experiments using supervised learning algorithms. The experiments were conducted using the public datasets obtained from tri-axial accelerometers. The results depicted that extraction of the feature from adjacent sliding windows led to high accuracy in supervised machine learning-based fall detection. Also, the experiments conducted in this study suggested that the best accuracy can be achieved by keeping the window size as small as 2 seconds. With the kNN classifier and dataset from wearable sensors, the experiments achieved accuracy rates of 94%.