• 대기
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• 제19권2호
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• pp.199-211
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• 2009

In this paper, we examine the multiple change-point and change pattern in the 54 years (1954-2007) time series of the annual and the heavy precipitation characteristics (amount, days and intensity) averaged over South Korea. A Bayesian approach is used for detecting of mean and/or variance changes in a sequence of independent univariate normal observations. Using non-informative priors for the parameters, the Bayesian model selection is performed by the posterior probability through the intrinsic Bayes factor of Berger and Pericchi (1996). To investigate the significance of the changes in the precipitation characteristics between before and after the change-point, the posterior probability and 90% highest posterior density credible intervals are examined. The results showed that no significant changes have occurred in the annual precipitation characteristics (amount, days and intensity) and the heavy precipitation intensity. On the other hand, a statistically significant single change has occurred around 1996 or 1997 in the heavy precipitation days and amount. The heavy precipitation amount and days have increased after the change-point but no changes in the variances.

• Environmental Engineering Research
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• 제22권2호
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• pp.162-168
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• 2017

Rainfall is one of the most important phenomena of the natural system. In Bangladesh, agriculture largely depends on the intensity and variability of rainfall. Therefore, an early indication of possible rainfall can help to solve several problems related to agriculture, climate change and natural hazards like flood and drought. Rainfall forecasting could play a significant role in the planning and management of water resource systems also. In this study, univariate Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used to forecast monthly rainfall for twelve months lead-time for thirty rainfall stations of Bangladesh. The best SARIMA model was chosen based on the RMSE and normalized BIC criteria. A validation check for each station was performed on residual series. Residuals were found white noise at almost all stations. Besides, lack of fit test and normalized BIC confirms all the models were fitted satisfactorily. The predicted results from the selected models were compared with the observed data to determine prediction precision. We found that selected models predicted monthly rainfall with a reasonable accuracy. Therefore, year-long rainfall can be forecasted using these models.

• 기본간호학회지
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• 제12권3호
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• pp.395-403
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• 2005

Purpose: Methicillin-resistant Staphylococcus aureus (MRSA) is a major nosocomial pathogen in the intensive care units (ICUS). The purpose of this case-control study is to identify risk factors for acquisition of MRSA during ICU stays in patients with and without MRSA. Method: The study was conducted in a 16 beds-neurosurgical intensive care unit of a 2200-bed tertiary care university hospital in Seoul, Korea. Medical record and Critical Classification Scoring System were reviewed retrospectively in patients who were admitted more than 3 days from August 1, 2003 to May 30, 2004. Cases and controls were matched for age and gender. The obtained specimens were nasal swab and sputum. Result: There were 950 patients' admissions during the period. Among them, MRSA was isolated from twenty-three patients who were considered as hospital acquired. Artificial airway (p=.045), frequency of suction (p=.002), nasogastric tube (p=.004), wound drain (p=.045), and vancomycin (p=.019) were risk factors for MRSA acquisition in univariate analysis. Frequency of suction (p=.012, OR 3.5) was revealed as the only risk factor in multivariate conditional logistic regression. Conclusion: Our findings give support to recent studies that suggest that frequent physical contact maγ increase the nosocomial acquisition of MRSA in a neurosurgical ICU.

• 대한간호학회지
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• 제34권1호
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• pp.141-149
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• 2004

Purpose: To identify the status of regular cervical cancer screening practices among middle-aged women, the associations between regular practice and research factors, and the predictive model and factors effecting such behavior was studied. Method: Two hundred women, aged 40 to 60, were selected by convenience in one urban area of Seoul. They were asked about their regular attendance for screening, knowledge of cancer and screening, health belief, health self-determination index and certain personal factors. Result: Approximately 54.5% of the women had periodic screening tests every 6 months to 2 years. Their knowledge of cervical cancer and health belief were at the medium level of each scale, but their health self-determination scores (HSDI) were low. Some influencing factors, and their cancer odds ratio were identified through univariate regression analysis. These variables were included in a predictive model, and this model proved to have enough fit and classification power (83.5%). In this model, the financial state, self-belief and self-determination scores were found to be significant. Conclusion: Middle-age women's intrinsic motivation for healthy behavior was found to be low in those who felt to be in a poor financial state, had higher perceived barriers, lower perceived benefits and a lower prevalence of undergoing regular screening test.

• 산업경영시스템학회지
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• 제30권4호
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• pp.182-189
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• 2007

Process Capability indices(PCIs) have been widely used in manufacturing industries to provide a quantitative measure of process performance. PCIs have been developed to represent process capability more exactly. The traditional process capability indices Cp, Cpk, Cpm, $Cpm^+$ have been used to characterize process performance on the basis of univariate quality characteristics. Cp, Cpk consider the process variation, Cpm considers both the process variation and the process deviation from target and $Cpm^+$ considers economic loss for the process deviation from target In the previous studies, only one designated location on each part is measured. System process capability index even though in single process, multiple measurement locations on each part are required to calculate the reliable process capability. In manufacturing industry, there is growing interest in quantitative measures of process variation under multivariate quality characteristics. The multivariate process capability index incorporates both the process variation and the process deviation from target or considers expected loss caused by the process deviation from target. In this paper, we compare various process capability indices and propose the application method of PCIs.

• Journal of Gastric Cancer
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• 제10권2호
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• pp.55-62
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• 2010

Purpose: We evaluated the clinicopathological charicterics and prognostic impacts of lymphatic vessel invasion in gastric cancer without lymph node involvement. Materials and Methods: Among 1,795 patients who underwent gastric surgery with gastric cancer at the department of surgery, Hanyang university college of medicine from June 1992 to March 2009, we retrospectively evaluated 890 patients with lymph node negative gastric cancer. Results: The lymphatic vessel invasion correlated significantly with tumor stage, age, tumor size, perineural invasion and operation method. The survival rates were only significantly different between the patients with and without lymphatic vessel invasion in patients with stage Ia (P=0.036). Univariate and multivariate analysis demonstrated that blood vessel invasion and preoperative serum CEA level were significant factor influencing the survival rate in lymph node negative gastric cancer patients with lymphatic invasion. Conclusions: In patients with lymph node negative gastric cancer, the survival rate is significantly lower in those with lymphatic vessel invasion than in those without. Especially, in patients with stage Ia gastric cancer, the survival rates is significantly different between those with and those without lymphatic vessel invasion. Blood vessel invasion and preoperative serum CEA level is an adverse prognostic indicator in patients with stage Ia gastric cancer with lymphatic invasion. Thus we should consider further adjuvant therapies in case of need and need to show more concern to identify gastric cancer patients early at risk for recurrence.

• ETRI Journal
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• 제41권5호
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• pp.626-636
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• 2019

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game-based revenue maximization in a downlink non-orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5-dB signal-to-noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user-rates, fairness index, and outage probability, approach near-optimal values at moderate to high SNRs.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.53-59
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• 2021

This research aims to examine the model of investor herding behavior in making investment decisions in the Indonesian capital market, which is influenced by social and information impacting on the value of the Book Value Per Share (BVPS). The latest stock market conditions show that most investors make the same error pattern in making investment decisions that result in losses. The experiment involves two independent variables, namely, information about BVPS and social influence. This study used a 2×2 factorial design laboratory experimental method. Data collection was carried out through treatment of a sample of 100 individual investors listed on the Indonesia Stock Exchange. Univariate Two-Way Analysis of Variance (ANOVA) statistical tool was used to test the independent variable on the dependent variable. Research results showed that the social influence originating from expert investors is more influential than the Book Value Per Share (BVPS) information on the behavior of herding investors in making investment decisions. These findings suggest that investors know their psychological factors, thereby increasing self-control and investment analysis skills. Further research can use psychological bias and other indicators of accounting relevant information such as Earning Per Share (EPS) to test herding behavior in investment decision making in the capital market.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• 한국융합학회논문지
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• 제7권4호
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• pp.1-7
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• 2016

구조적 MRI 영상은 여러 단 변량과 다변량 방법을 위해 그레이 메터 (GM), 화이트 메터 (WM), 뇌척수액 (CSF) 세션화 과정을 하고 난후 형태계측학적 특징을 추출하기 위해 사용한다. 새로운 접근 방법은 매우 가벼운 알츠하이머 병에서 가벼운 알츠하이머병의 진단을 위해 적용된다. 간이정신상태검사에 따른 형태계측학적 특징과 가우시안 복합 모델 파라미터를 결합하여 정상인으로부터 알츠하이머 병 환자로 분류하는 방법을 제안한다. 결합한 특징은 주성분 분석 기법을 이용한 고차원의 저주를 제거한 후 다중 커널 SVM 분류기에 공급한다. 제안한 진단 방법의 실험적 결과는 90%이상의 특성도와 고민감도에 따라 다중 커널 SVM을 가진 층화 정확도가 96%까지 최대 산출한다.