• International Commerce and Information Review
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• v.9 no.3
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• pp.305-320
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• 2007

With expanded use of B2B(between enterprises), B2G(between enterprises and government) and EDI(Electronic Data Interchange), and increased amount of available network information and information protection threat, as it was judged that security can not be perfectly assured only with security technology such as electronic signature/authorization and access control, Bayesian networks have been developed for protection of information. Therefore, this study speculates Bayesian networks system, centering on ERP(Enterprise Resource Planning). The Bayesian networks system is one of the methods to resolve uncertainty in electronic data interchange and is applied to overcome uncertainty of abnormal invasion detection in ERP. Bayesian networks are applied to construct profiling for system call and network data, and simulate against abnormal invasion detection. The host-based abnormal invasion detection system in electronic trade analyses system call, applies Bayesian probability values, and constructs normal behavior profile to detect abnormal behaviors. This study assumes before and after of delivery behavior of the electronic document through Bayesian probability value and expresses before and after of the delivery behavior or events based on Bayesian networks. Therefore, profiling process using Bayesian networks can be applied for abnormal invasion detection based on host and network. In respect to transmission and reception of electronic documents, we need further studies on standards that classify abnormal invasion of various patterns in ERP and evaluate them by Bayesian probability values, and on classification of B2B invasion pattern genealogy to effectively detect deformed abnormal invasion patterns.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.480-486
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• 2007

A gait diagnosis supporting system is necessary to evaluate the characteristics of abnormal gait of a patient in a systematic and efficient manner. The present study developed a gait diagnosis supporting system which compares abnormal gait of a patient with a reference gait data and presents abnormal gait characteristics in an organized form. Three types of diagnosis modules were developed for the spatio-temporal, kinematic and kinetic gait parameters, and a gait data for Korean normal adults was used for the reference data of the system. The system was applied to evaluate the gait pattern of three arthritis patients and the abnormal gait characteristics of them could be easily identified with a systematic and graphical presentation.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.7
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• pp.3147-3153
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• 2016

Background: Many strategies are required for cervical cancer reduction e.g. provision of education cautious sexual behavior, HPV vaccination, and early detection of pre-invasive cervical lesions and invasive cancer. Basic health data for cervical cytology/ HPV DNA and associated factors are important to make an appropriate policy to fight against cervical cancer. Aims: To assess the prevalence of abnormal cervical cytology and/or HPV DNA and associated factors, including sexual behavior, among Bangkok Metropolitan women. Materials and Methods: Thai women, aged 25-to-65 years old, had lived in Bangkok for ${\geq}5$ years were invited into the study. Liquid-based cervical cytology and HPV DNA tests were performed. Personal data were collected. Main Outcomes Measures: Rates of abnormal cytology and/ or high-risk HPV (HR-HPV) and factors associated with abnormal test (s) were studied. Results: Abnormal cytology and positive HR-HPV were found in 6.3% (279/4442 women) and 6.7% (295/4428), respectively. The most common abnormal cytology was ASC-US (3.5%) while the most common HR-HPV genotype was HPV 16 (1.4%) followed by HPV 52 (1.0%), HPV 58 (0.9%), and HPV 18 and HPV 51 at equal frequency (0.7%). Both tests were abnormal in 1.6% (71/4428 women). Rates of HR-HPV detection were directly associated with severity of abnormal cytology: 5.4% among normal cytology and 13.0%, 30.8%, 40.0%, 39.5%, 56.3% and 100.0% among ASC-US, ASC-H, AGC-NOS, LSIL, HSIL, and SCC, respectively. Some 5% of women who had no HR-HPV had abnormal cytology, in which 0.3% had ${\geq}$ HSIL. Factors associated with abnormal cytology or HR-HPV were: age ${\leq}40$ years, education lower than (for cytology) or higher than bachelor for HR-HPV), history of sexual intercourse, and sexual partners ${\geq}2$. Conclusions: Rates for abnormal cytology and HR-HPV detection were 6.3% and 6.7% HR-HPV detection was directly associated with severity of abnormal cytology. Significant associated factors were age ${\leq}40$ years, lower education, history of sexual intercourse, and sexual partners ${\geq}2$.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1161-1162
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• 2007

In year 2004 korea runs high speed train KTX for the 5th time in the world. And now the traction power system is quite stabilized. But still a lot of work to develop and abnormal voltage problem is one of them. In this paper, by actual measuring we have collected the abnormal data on the high speed train sub-staion for more than 15 days. The collected data has been evaluated. In the near future collected data will be used planing a countermeasure.

• Journal of Information Processing Systems
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• v.4 no.3
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• pp.113-120
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• 2008

Most enterprises have controlled claim data related to marketing, production, trade and delivery. They can extract the engineering information needed to the reliability of unit from the claim data, and also detect critical and latent reliability problems. Existing method which could detect abnormal quality unit lists in early stage from claim database has three problems: the exclusion of fallacy probability in claim, the false occurrence of claim fallacy alarm caused by not reflecting inventory information and too many excessive considerations of claim change factors. In this paper, we propose a process and methods extracting abnormal quality unit lists to solve three problems of existing method. Proposed one includes data extraction process for reliability measurement, the calculation method of claim fallacy alarm probability, the method for reflecting inventory time in calculating claim reliability and the method for identification of abnormal quality unit lists. This paper also shows that proposed mechanism could be effectively used after analyzing improved effects taken from automotive company's claim data adaptation for two years.

• Journal of Distribution Science
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• v.13 no.9
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• pp.5-11
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• 2015

Purpose - The purpose of this research is to provide insights that can be used for deliberate decision making around challenging big data investments by measuring the economic value of such big data implementations. Research design, data, and methodology - We perform empirical research through an event study. To this end, we measure actual abnormal returns of companies that are triggered by their investment announcements in big data, or firm size information, during the three-year research period. The research period targets a timeframe after the introduction of big data at Korean firms listed on the Korea stock markets. Results - Our empirical findings discover that on the event day and the day after, the abnormal returns are significantly positive. In addition, our further examination of firm size impacts on the abnormal returns does not show any evidence of an effect. Conclusions - Our research suggests that an event study can be useful as an alternative means to measure the return on investment (ROI) for big data in order to lessen the difficulties or decision making around big data investments.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.355-364
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• 2022

In this study a tendency of abnormal sea surface temperature (SST) occurrence in the seas around South Korea is analyzed from daily SST data from satellite and 14 buoys from August 2020 to July 2021. As thresholds 28℃ and 4℃ are used to determine marine heatwaves(MHWs) and abnormal low water temperature (ALWT), respectively, because those values are adopted by the National Institute of Fisheries Science for the breaking news of abnormal temperature. In order to calculate frequency of abnormal SST occurrence spatially by using satellite SST, research area was divided into six areas of coast and three open seas. ALWT dominantly appeared over a wide area (7,745 km²) in Gyeonggi Bay for total 94 days and it was also confirmed from buoy temperature showing an occurrence number of 47 days. MHWs tended to be high in frequency in the coastal areas of Chungcheongdo and Jeollabukdo and the south coastal areas while in case of buoy temperature Jupo was the place of high frequency (32 days). This difference was supposed to be due to the low accuracy of satellite SST at the coasts. MHWs are also dominant in offshore waters around Korean Peninsula. Although detecting abnormal SST by using satellite SST has advantage of understanding occurrence from a spatial point of view, we also need to perform detection using buoys to increase detection accuracy along the coast.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.243-260
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• 2008

To prevent low yields in the semiconductor industry is crucial to the success of that industry. However, to prevent low yields is difficult because of too many factors to affect yield variation and their complex relation in the semiconductor manufacturing process. This study presents a new efficient detection methodology for detecting abnormal yields including high and low yields, which can forecast the yield level of a production unit (namely a lot) based on yield-related feature variables' behaviors. In the methodology, we use C5.0 to identify the yield-related feature variables that are the combination of correlated process variables associated with yield, use SOM (Self-Organizing Map) neural networks to extract and classify significant patterns of past abnormal yield lots and finally use C5.0 to generate classification rules for detecting abnormal yield lot. We illustrate the effectiveness of our methodology using a semiconductor manufacturing company's field data.

• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.25-31
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• 2005

We know that the Hurst Exponent (HE) is a real number in [0, 1] which denotes randomness of time series. in this research, we suggest non-linear analysis of human biological signals through HE. The feasibility of human biological signals using inductive incitement provides Some diagnosis for active treatment. In our experiment, we measured the heartbeat through the MCG, 29 healthy and 34 abnormal subjects ostensibly. The raw data of acupuncture incitement are supported by opinions of gross examination and pathological diagnosis. The mean values of HE are 0.345, 0.755 and 0.805 for the periods of before, during and after acupuncture treatment, respectively in case of abnormal subjects. On the other hand, the mean values, 0.808, 0.797 and 0.785 are for normal cases, correspondingly. From this data, we show that HE is very significant in abnormal controls according to an acupuncture incitement, and the incitement effect is evidently extracted in abnormal subjects. But, in normal subjects, the incitement effect is meaningless.

• Journal of Biomedical Engineering Research
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• v.12 no.2
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• pp.89-98
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• 1991

This study is concerned on the automation for cell diagnosis which has better objectivity and speed of test than human beings. Diagnosis is on the basis of shape change of abnormal Cells. Used parameters are nucleus area, nucleus perimeter, nucleus shape, cytoplasm area, nucleus/cytoplsm ratio, which was obtained using image processing technics. A new mode method is proposed on the automatic threshold selection for superior process time compared with Otsu's. Contour of the cytoplasm of abnormal cell is obtained using me- dian filter and sorel operator. The mask to get only original shape of abnormal cells is formed uslng the contour filling algorithm. In the result the normal cells are separated from the abnormal cells and the abnormal cells can be distinguished through screwing of abnormal cell's image with reference data to judge abnormal cells. Owing to this study the number of inspections which the pathologists should examine will be decreased and the time for inspection will be shortened.