• Asian Pacific Journal of Cancer Prevention
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• 제17권6호
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• pp.2871-2876
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• 2016

The Pap smear test is recommended for early diagnosis of cervical cancer. The aim of this study was to assess knowledge and behavior regarding the Pap smear test based on the Health Belief Model (HBM) in women referred to premarital counseling classes, Hamadan, Iran. This quasi-experimental study was conducted on 330 women, who were allocated randomly to two case and control groups (n=165). Two educational session classes were performed in the case group. Two stages in before and after intervention groups were evaluated. Analysis of data was performed by SPSS/16.0, using t-test, $x^2$, and McNemar's test. P-values <0.05 were regarded as significant. There was no significant difference between the mean scores of the various structures of this model in two groups before the intervention. However, after the intervention there were significant increase in mean score of knowledge and all variables of HBM in the intervention group(P<0.001). The findings of this study highlight the important role of education about cervical cancer on changing women's beliefs about cervical screening.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Asian Pacific Journal of Cancer Prevention
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• 제15권19호
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• pp.8371-8376
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• 2014

Background: The use of statistical methods has become an imperative tool in breast cancer survival data analysis. The purpose of this study was to develop the best statistical probability model using the Bayesian method to predict future survival times for the black non-Hispanic female breast cancer patients diagnosed during 1973-2009 in the U.S. Materials and Methods: We used a stratified random sample of black non-Hispanic female breast cancer patient data from the Surveillance Epidemiology and End Results (SEER) database. Survival analysis was performed using Kaplan-Meier and Cox proportional regression methods. Four advanced types of statistical models, Exponentiated Exponential (EE), Beta Generalized Exponential (BGE), Exponentiated Weibull (EW), and Beta Inverse Weibull (BIW) were utilized for data analysis. The statistical model building criteria, Akaike Information Criteria (AIC), Bayesian Information Criteria (BIC), and Deviance Information Criteria (DIC) were used to measure the goodness of fit tests. Furthermore, we used the Bayesian approach to obtain the predictive survival inferences from the best-fit data based on the exponentiated Weibull model. Results: We identified the highest number of black non-Hispanic female breast cancer patients in Michigan and the lowest in Hawaii. The mean (SD), of age at diagnosis (years) was 58.3 (14.43). The mean (SD), of survival time (months) for black non-Hispanic females was 66.8 (30.20). Non-Hispanic blacks had a significantly increased risk of death compared to Black Hispanics (Hazard ratio: 1.96, 95%CI: 1.51-2.54). Compared to other statistical probability models, we found that the exponentiated Weibull model better fits for the survival times. By making use of the Bayesian method predictive inferences for future survival times were obtained. Conclusions: These findings will be of great significance in determining appropriate treatment plans and health-care cost allocation. Furthermore, the same approach should contribute to build future predictive models for any health related diseases.

• 한국정보시스템학회지:정보시스템연구
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• 제27권1호
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• 디지털융복합연구
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• 제11권3호
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• pp.273-277
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• 2013

피싱 공격은 시간이 흐르면서 보다 더 지능적으로 실행되며, 기술적으로 고도화되고 있다. 해커는 지능화된 피싱 공격을 주요 기관의 내부 네트워크 침투를 위해 내부 사용자 컴퓨터를 점령하는 수단으로 이용하고 있다. 따라서, 본 연구에서는 고도화된 피싱 공격으로부터 내부 사용자와 중요 정보를 보호하기 위해 피싱공격 확산방지모델(PMPA : Prevention Model the spreading of Phishing Attack)을 기술하고자 한다. 내부 사용자들은 외부 웹메일 서비스와 내부 메일 서비스를 동시에 사용한다. 따라서 양 구간에서 발생하는 위협 요소를 동시에 식별하기 위해서는 각각의 패킷을 감시하고 저장하여 각각의 항목별로 구조화시켜야 한다. 이는 해커가 내부 사용자를 공격할 때 외부 웹메일 서비스와 내부 메일 서비스 중 어느 한 쪽을 이용하거나 또는 양쪽 모두를 이용할 수 있기 때문이다. 본 연구에서 제시된 모델은 기존에 연구된 메일 서버 중심의 보안구조 설계를 내부 사용자가 접속하는 내부 메일 서비스까지 보호할 수 있도록 확장한 것이며, 프록시 서버를 이용하여 직접 피싱 사이트 접속을 차단하는 것보다 메일 확인 시 해당 사이트를 목록화할 수 있기 때문에 별도의 요청/응답을 위한 대기 시간이 없다는 장점이 있다.

• 한국수자원학회논문집
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• 제45권11호
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• pp.1187-1199
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• 2012

본 연구에서는 Wavelet Transform과 Support Vector Machine (SVM)을 결합한 Hybrid 상수도 수요량 예측 모형을 개발하였다. Wavelet Transform 방법을 활용하여 다양한 스케일이 존재하는 상수도 수요량 시계열을 분해하여 단순한 형태의 시계열로 변환하는데 이용하였으며, 비선형 예측모형인 SVM은 이들 단순화된 시계열을 예측하는데 활용하여 예측성능을 극대화시키는 방안을 수립하였다. 본 연구에서는 상수도 수요량 자료에서 내재되어 있는 주기의 특성과 비선형 예측모형의 장점을 서로 연계한 해석이 가능하였으며 시각적인 검토 및 모든 통계지표에서 개선된 예측결과를 확인할 수 있었다. 특히, 기존 ARIMA 모형 계열에서 나타나는 자기예측문제를 상당부분 개선한 결과를 보여줌으로서 실질적인 수요량 예측모형으로서 활용이 가능할 것으로 판단된다.

• Asian Pacific Journal of Cancer Prevention
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• 제17권12호
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• pp.5107-5111
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• 2016

Background: Epidemiological studies have indicated an increasing incidence of radiation induced secondary cancer (SC) in breast cancer patients after radiotherapy (RT), most commonly in the contra-lateral breast (CLB). The present study was conducted to estimate the SC risk in the CLB following 3D conformal radiotherapy techniques (3DCRT) including wedge field and forward intensity modulated radiotherapy (fIMRT) based on the organ equivalent dose (OED). Material and Methods: RT plans treating the chest wall with conformal wedge field and fIMRT plans were created for 30 breast cancer patients. The risks of radiation induced cancer were estimated for the CLB using dose-response models: a linear model, a linear-plateau model and a bell-shaped model with full dose response accounting for fractionated RT on the basis of OED. Results: The plans were found to be ranked quite differently according to the choice of model; calculations based on a linear dose response model fIMRT predict statistically significant lower risk compared to the enhanced dynamic wedge (EDW) technique (p-0.0089) and a non-significant difference between fIMRT and physical wedge (PW) techniques (p-0.054). The widely used plateau dose response model based estimation showed significantly lower SC risk associated with fIMRT technique compared to both wedge field techniques (fIMRT vs EDW p-0.013, fIMRT vs PW p-0.04). The full dose response model showed a non-significant difference between all three techniques in the view of second CLB cancer. Finally the bell shaped model predicted interestingly that PW is associated with significantly higher risk compared to both fIMRT and EDW techniques (fIMRT vs PW p-0.0003, EDW vs PW p-0.0032). Conclusion: In conclusion, the SC risk estimations of the CLB revealed that there is a clear relation between risk associated with wedge field and fIMRT technique depending on the choice of model selected for risk comparison.

• 한국전기전자재료학회논문지
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• 제37권3호
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• pp.261-273
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• 2024

This paper is an experimental study on the improvement of smoke and flame detection from different materials with YOLO. For the study, images of fires occurring in various materials were collected through an open dataset, and experiments were conducted by changing the main factors affecting the performance of the fire object detection model, such as the bounding box, polygon, and data augmentation of the collected image open dataset during data preprocessing. To evaluate the model performance, we calculated the values of precision, recall, F1Score, mAP, and FPS for each condition, and compared the performance of each model based on these values. We also analyzed the changes in model performance due to the data preprocessing method to derive the conditions that have the greatest impact on improving the performance of the fire object detection model. The experimental results showed that for the fire object detection model using the YOLOv5s6.0 model, data augmentation that can change the color of the flame, such as saturation, brightness, and exposure, is most effective in improving the performance of the fire object detection model. The real-time fire object detection model developed in this study can be applied to equipment such as existing CCTV, and it is believed that it can contribute to minimizing fire damage by enabling early detection of fires occurring in various materials.

• Journal of Community Nutrition
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• 제6권3호
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• pp.125-130
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• 2004

The purpose of this study is to investigate the relative influence of diet and physical activity on obesity. The subjects were 155 adults aged 35-52 years from 24 neighborhood committees in 4 urban districts of Beijing (male : 78, female : 77). They were divided into normal weight, overweight and obese groups according to their BMI. The general information of the subjects was collected by interview-administered questionnaire. Dietary intake was obtained by three-day(two weekdays and one weekend day) food weighted method, physical activity was assessed by a validated combination of data obtained from activity monitors, bicycling information and activity records. There were no significant differences of age, gender, height, educational, family economic level, smoking and drinking between different groups. The proportion of flour intake was higher in obese group compared to normal weight and overweight groups, and that of vegetables is lower in obese group. The physical activity (PAL) was not significantly different between two groups of the normal, overweight and obese groups. After the adjustment for confounding factors using logistic regression model, we found that the proportion of flour intake was positively associated with obesity, while the proportion of vegetable intake was inversely associated with obesity. It is concluded that dietary patterns were associated with obesity and diets composed of more vegetables and less staple combined with physical activities could contribute to obesity prevention.

• Perspectives in Nursing Science
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• 제8권2호
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• pp.97-104
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• 2011

Purpose: This study seeks to assess the educational needs pertaining to staff competency for alcohol prevention services in the workplace. Methods: The subjects were staff in charge of alcohol prevention services in four organizations. A questionnaire was modified pursuant to the IC & RC (International Certification & Reciprocity Consortium) Certified Prevention Specialist role delineation. The questionnaire consisted of five domains with 27 items. Data were collected via the self-administered questionnaire from October to November of 2009. 400 questionnaires were mailed and 144(36.0%) were returned. The collected data were analyzed using the Borich's needs assessment model and with SPSS/WIN 15.0. Results: Overall mean scores for the importance levels of competency ratings were 3.79, while the performance levels of the competency were 2.13 and Borich's need results were 6.32. Public Health and Mental Health Center showed the highest degree of educational needs in terms of education & program development (p=.022). Conclusion: The perceived importance levels pertaining to staff competency for alcohol prevention services in the workplace were higher than those of the current performance levels. Staff working for alcohol prevention services in the workplace showed a different level of educational need as regards these competency levels according to service providers. To promote the effectiveness of alcohol prevention services in the workplace, the development of an educational program to meet the needs of the service providers is necessary.