• The Korean Journal of Cytopathology
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• v.15 no.1
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• pp.17-27
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• 2004

To investigate a population-based survey of the prevalence of human papillomavirus (HPV) infection in South Korea, we performed Papanicolaou smears and tests for HPV DNA and anti-HPV antibody detection in 909 sexually active general women (age range; 20-74 years, median 44 years) who were randomly selected residents from S district of Busan City. The presence of DNA of 36 different HPV types was detected by means of a GP 5+/6+ primer-mediated PCR enzyme immunoassay in cervical exfoliated cells, and IgG antibodies against L1 virus-like particles (anti-VLPs) of 5 HPV types 16, 18, 31, 33, and 58 were tested by means of enzyme linked immunoassay. The incidence of cytologic abnormality was 5.2% in Pap smear. The positive rate of HPV DNA was 10.4%, high in young women younger than 35 years old and proportionally increased according to the cytologic grades. The most often found HPV type was HPV 70, followed by HPV 16 and 33, and high-risk HPV types were more frequent in women younger than 35 years old. The most common HPV type in abnormal cytologic smears was HPV 16, followed by HPV 58 and 66. Anti-VLPs was positive in 19.7% and the frequent anti-VLPs type was against HPV 18, followed by HPV 31 and 16. The concordance between the markers for each specific HPV type was noted in 10 women and HPV 16 was the most frequent one. The incidence of multiple HPV infection was 18.9% and that of multiple anti-VLPs antibodies was 31%. Among 103 self-reported virgins, 4.9% had anti-VLP antibodies.

• Journal of Microbiology and Biotechnology
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• v.20 no.6
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• pp.959-967
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• 2010

Down syndrome (DS) is an abnormality of the 21st chromosome that commonly occurs in children born to older women. Thus, amniotic fluid (AF) is usually collected from such women for prenatal diagnosis. This study analyzed human AF supernatants (AFS) using a mass spectrometric (MS) approach to search for candidate biomarkers of a DS pregnancy. The AFS were collected from older pregnant women at weeks 16-18 of their gestation by amniocentesis for cytogenetic analysis. The AFS from the pregnancies carrying DS (n=4) or chromosomally normal (n=6) fetuses, as revealed by the cytogenetic analysis, were then subjected to global protein profiling based on liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Affinity chromatography was also applied prior to the LC-ESI-MS/MS to minimize the masking effect of highly abundant albumin and immunoglobulin and thereby increase the diversity of the identified proteins. As a result, at least 30 new AFS proteins were identified and 44 AFS proteins were found to be differentially expressed between the DS and normal cases, where 6 of the proteins were unique to the DS cases and 11 were unique to the chromosomally normal cases. In addition, in the DS cases, 19 AFS proteins were downregulated and 8 were upregulated to varying degrees. A Western blot analysis confirmed the LC-ESI-MS/MS data, indicating that the combined detection of apolipoprotein A-II (apoA-II) and alpha-fetoprotein (AFP) could be a potential tool for diagnosing DS cases.

• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.33-43
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• 2004

In this paper, a traffic trend analysis based SNMP algorithm is proposed for improving the problem of existing traffic analysis using SNMP. The existing traffic analysis method has a vulnerability that is taken much time In analyzing by using a threshold and not detected a harmful traffic at the point of transition. The method that is proposed in this paper can solve the problems that the existing method had, simultaneously using traffic trend analysis of the day, traffic trend analysis happening in each protocol and MIB object analysis responding to attacks instead of using the threshold. The algorithm proposed in this paper will analyze harmful traffic more quickly and more precisely; hence it can reduce the damage made by traffic flooding attacks. When traffic happens, it can detect the abnormality through the three analysis methods previously mentioned. After that, if abnormal traffic overlaps in at least two of the three methods, we can consider it as harmful traffic. The proposed algorithm will analyze harmful traffic more quickly and more precisely; hence it can reduce the damage made by traffic flooding attacks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.347-350
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• 2007

An ECG analysis with activity monitoring for the home care of elderly persons or patients, using wireless sensors technology was design and implemented. The changes in heart rate occur before, during, or following behavior such as posture changes, walking and running. Therefore, it is often very important to record heart rate along with posture and behavior, for continuously monitoring a patient's cardiovascular regulatory system during their daily life activity. The ECG and accelerometer data are continuously recorded with a built-in automatic alarm detection system, for giving early alarm signals even if the patient is unconscious or unaware of cardiac arrhythmias. The hardware allows data to be transmitted wirelessly from on-body sensors to a base station attached to server PC using IEEE802.15.4. If any abnormality un at server then the alarm condition sends to the doctor' PDA (Personal Digital Assistant).

• The Journal of Korean Obstetrics and Gynecology
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• v.19 no.3
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• pp.191-201
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• 2006

Purpose : Skin Resistance Variability(SRV) is a kind of biofunctional signal, and it can show the function of autonomic nervous system, especially in the sympathetic nerve. The objective of this study is to find out the differences of SRV of reproductive women with aging. Method : We measured SRV(by CP-6000A) of 151 women who visited Gynecologic Clinic. And the results were classified according to age, by five groups. After detection of SRV, we performed correlation analysis and ANOVA by SPSS 12.0. Results : 1. The SRV was measured twice. It resulted in seven areas. In 1, 2, 3 areas, the second results were higher than first results in every groups. In 4, 5, 6, 7 areas, the first results were higher than second results in every groups. 2. The SRV of lower part (4, 5, 6, 7 area) on the body was higher than that of higher part (1, 2, 3 area). 3. The SRV in the youngest group was higher than the oldest group in 1, 2, 3 area of second trial. Conclusion : With relations to the standardization and objectification of oriental medicine, we expect that these results contribute to gynecologic clinic in the department of diagnosis of functional abnormality of hypothalamus-hypophysis-ovarian axis (H-P-O axis).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.45-51
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• 2011

In this paper, we propose an unsupervised learning method for modeling motion trajectory patterns effectively. In our approach, observations of an object on a trajectory are treated as words in a document for latent dirichlet allocation algorithm which is used for clustering words on the topic in natural language process. This allows clustering topics (e.g. go straight, turn left, turn right) effectively in complex scenes, such as crossroads. After this procedure, we learn patterns of word sequences in each cluster using Baum-Welch algorithm used to find the unknown parameters in a hidden markov model. Evaluation of abnormality can be done using forward algorithm by comparing learned sequence and input sequence. Results of experiments show that modeling of semantic region is robust against noise in various scene.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.5
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• pp.2069-2074
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• 2014

Purpose: To appraise the frequency of cervical cytological abnormalities in a population at normal risk via analysing the archive records of cytology for the period of approximately 9,5 years, comparing them with patient demographic charecteristics, and discuss the results for women under age of 35. Materials and Methods: A total of 32,578 cases of Pap smears were retrieved and analysed from our archive included the Pap tests performed between January 2001 and April 2010 at the Early Cancer Screening, Diagnosing and Education Center by the consent of three pathologists via utilizing the Bethesda System Criteria 2001 and the results were compared with some demographical characteristics. Results: Our rate of the cervical cytological abnormality was 1.83%, with ASCUS in 1.18%, LSIL in 0.39, HSIL in 0.16%, AGUS in 0.07%, squamous cell carcinoma in 0.02%, and adenoarcinoma in 0.006%. Cytological abnormalities were detected mostly in those with higher age, lower parity, and premenopausal period whereas the smoking status was without influence. Bacterial vaginosis (5.6%) was the most frequent infectious finding (Candida albicans 2.7%; Actinomyces sp. 1.3%; and Trichomonas vaginalis 0.2%) detected on the smears. The rate of abnormal cervical cytology was 9.5% among the women aged between 30-34. Conclusions: Early detection of the cervical abnormalities by means of the regular cervical cancer screening programmes is useful to attenuate the incidence, mortality, and morbidity of cervical cancer. Our prevalence of the cytological abnormalities was much lower than the one in Western populations in general but very similar to those reported from other Islamic countries that may be explained by the conservative lifestyle and the lower prevalence of HPV in Turkey. A remarkable rate of abnormal cervical cytology of women aged 30-34 was pointed out in the present study.

• Progress in Superconductivity
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• v.8 no.1
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• pp.46-53
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• 2006

Magnetocardiography(MCG) has been proposed as a novel and non-invasive diagnostic tool for the detection of cardiac electrical abnormality associated with myocardial ischemia. In our previous study, we have proposed a new classification method of MCG parameters, based on the different populations of the parameters between coronary artery disease(CAD) patients, symptomatic patients and healthy volunteers. We used four parameters, representing the directional changes of the electrical activity in the period of an R-ST-T interval. In patients with chest pain and without ST-segment elevation, who were selected consecutively from all patients admitted to the hospital in 2004, the patients with CAD could be classified with a higher sensitivity than conventional methods, showing that the proposed method can be useful for the diagnosis of CAD with MCG. In this study, we examined the validity of the algorithm with the prior probability distribution in diagnosis of new patients admitted to the hospital in 2005. In the results, presence of CAD could be found with sensitivity and specificity of 81.3% and 71.4%, respectively, in patients with chest pain and non-diagnostic ECG findings.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.313-316
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• 2009

A novel approach for electrocardiogram (ECG) analysis within a functional sensor node has been developed and evaluated. The main aim is to reduce data collision, traffic over loads and power consumption in healthcare applications of wireless sensor networks (WSN). The sensor node attached on the patient's bodysurface around the heart can perform ECG analysis based on a QRS detection algorithm to detect abnormal condition of the patient. Data transfer is activated only after detected abnormality in the ECG. This system can reduce packet loss during transmission by reducing traffic overload. In addition, it saves power supply energy leading to more reliable, cheap and user-friendly operation in the WSN based ubiquitous health monitoring.

• Journal of the Korean Institute of Gas
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• v.23 no.4
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• pp.19-27
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• 2019

The consumption of liquefied natural gas (LNG) has increased annually due to the strengthening of international environmental regulations. In order to produce stable and efficient LNG, it is essential to divide the global (overall) operating condition and construct a quick and accurate monitoring system for each operation condition. In this study, multi-mode monitoring system is proposed to the LNG plant fractionation process. First, global normal operation data is divided to local (subdivide) normal operation data using global principal component analysis (PCA) and k-means clustering method. And then, the data to be analyzed were matched with the local normal mode. Finally, it is determined the state of process abnormality through the local PCA. The proposed method is applied to 45 fault case and it proved to be more than 5~10% efficient compared to the global PCA and univariate monitoring.