• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.33-42
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• 2010

Travel speed is an important parameter in measurement of road traffic. UTIS(Urban Traffic Information System) was developed as a type of section detector. However, UTIS incur errors caused by irregular vehicle trajectories, wireless communication range and so on. This paper suggests a new model that use an error-filtering algorithm to improve the accuracy of travel speed measurements. In the field test, the variance of the percent errors measured by the new model was reduced. Therefore, it can be concluded that the proposed model significantly improves travel speed measuring accuracy.

• Women's Health Nursing
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• v.13 no.3
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• pp.211-218
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• 2007

Purpose: This study aimed to evaluate the accuracy and adequacy of research papers reporting statistical testings for mean differences. Methods: Original research articles utilized t-test, Chi-square test, and ANOVA were reviewed from Korean Journal of Women Health Nursing published from the year 2004 to 2006. Seventy-six papers were evaluated in accordance with formatted criteria in respect to an inclusiveness of research title, accuracy of statistical methods and presentation styles, and errors in reporting statistical outcomes. Results: Research titles were quite comprehensive, however overall accuracy of statistical values and basic formats reached only 60 to 80% by items. Details of the presentation in the reporting of outcomes were not complied with the guidelines, which need careful concerns of the writers. Errors of English in table presentation were found in more than 30% of the papers. Conclusion: The outcome would be reflected in the submission guidelines for future writers. To reach the level comparable with internationally recognized nursing journals, concrete knowledge to apply statistical methods should be ensured in the processes of submission, reviews, and editing.

• Journal of Home Health Care Nursing
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• v.28 no.3
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• pp.285-294
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• 2021

Purpose: The study examined the effects of knowledge, attitude, and confidence on the education needs of nursing students with respect to patient safety management. The participants were 119 students from nursing college. Data were analyzed using descriptive statistics, t-test, analysis of variance(ANOVA), Pearson's correlation coefficient, and multiple regression analysis with the SPSS program. Results: The student's educational needs with respect to patient safety management differed significantly by experience of patient safety accidents (p=.026) and experience of reporting medical errors (p<.001). Additionally, the educational needs with respect to patient safety management were found to have statistically significant positive relationships with both attitude (r=.39) and confidence (r=.37). Further, a total of 23% of the education needs with regard to patient safety management were explained by attitude and confidence. Conclusion: These results can be used to develop nursing students' education programs to enhance patient safety management competence be emphasizing the experience of patient safety accidents and reporting medical errors as well as improving the attitude and confidence of the students.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.73-81
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• 2015

The paper proposes a prototype selection method and evaluates the generalization performance of standard algorithms and prototype based classification learning. The proposed prototype classifier defines multidimensional spheres with variable radii within class areas and generates a small set of training data. The nearest-neighbor classifier uses the new training set for predicting the class of test data. By decomposing bias and variance of the mean expected error value, we compare the generalization errors of k-nearest neighbor, Bayesian classifier, prototype selection using fixed radius and the proposed prototype selection method. In experiments, the bias-variance changing trends of the proposed prototype classifier are similar to those of nearest neighbor classifiers with all training data and the prototype selection rates are under 27.0% on average.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.255-266
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• 2009

In this study, a robust aerospace system design process for the aerospace system is developed by considering the uncertainties of user requirements, manufacturing errors, and operational environment variation. User requirements are analyzed and quantified by decision making models and system engineering methods to select alternative concepts which satisfies the various requirements. Robust design and optimization method is applied to derive the robust solution of the selected system. First, a variance of objective function is calculated, and a mean value and a variance of target value are determined by the deterministic design optimization results of the system. A robust optimum design formulation is then needed to derive the robust solution that minimizes the variance of the response and moves the mean values to the target value. It is applied to Very Light Jet (VLJ) aircraft to which much attention is paid recently in civil aerospace market.

• Women's Health Nursing
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• v.17 no.4
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• pp.388-394
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• 2011

Purpose: This study was done to evaluate the accuracy and adequacy of research studies reporting statistical testing for mean differences in studies of the Korean Journal of Women Health. Methods: Among articles published in the journal from 2007 to 2009, 75 studies using t-test, $x^2$-test, and ANOVA were identified. The studies were evaluated using structured analysis format for adequacy of research title, accuracy of statistical methods and presentation styles, and errors in reported statistical outcomes. Results: In this study, the research titles generally reflected the purpose of research and study designs. Thus the research titles were quite comprehensive. Also, there was compatibility between the research purpose and research design. Most important though, many errors were identified in the tables of results of the statistical analysis in articles published from 2004 to 2006. Conclusion: Over six years, 2004 to 2009, accuracy and adequacy of research studies has improved in many aspects. In order to enhance the completeness of the published papers and to be an internationally recognized nursing journal, close attention of the researchers, reviewers and editors is necessary to avoid errors and present adequate and accurate research.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.84-93
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• 2018

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.19-24
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• 2002

The two-way balanced one-level rotation design has been discussed (Park, Kim and Choi, 2001), where the two-way balancing is done on interview time in monthly sample and rotation group. We extend it to three-way balanced multi-level design under the most general rotation system. The three-way balancing is accomplished on interview time not only in monthly sample and rotation group but also in recall time. We present the necessary condition and rotation algorithm which guarantee the three-way balancing. We propose multi-level composite estimators (MCE) from this design and derive their variances and mean squared errors (MSE), assuming the correlation from the measurements of the same sample unit and three types of biases in monthly sample.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.123-130
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• 2003

The estimation of key soil properties and subsequent quantitative assessment of the associated uncertainties has always been an important issue in geotechnical engineering. It is well recognized that soil properties vary spatially as a result of depositional and post-depositional processes. The stochastic nature of spatially varying soil properties can be treated as a random field. A practical statistical approach that can be used to systematically model various sources of uncertainty is presented in the context of reliability analysis of slope stability Newly developed expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. Reliability analyses of the probability of slope failure using the different statistical representations of soil properties show that the incorporation of spatial correlation and conditional simulation leads to significantly lower probability of failure than obtained using simple random variable approach.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.153-156
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• 1996

A new filtering algorithm for radar tracking is developed based on the fact that correct evaluation of the measurement error covariance can be made possible by doing it with respect to the Cartesian state vector. The new filter may be viewed as a modification of the extended Kalman filter where the variance of the range measurement errors is evaluated in an adaptive manner. The structure of the proposed filter allows sequential measurement processing scheme to be incorporated into the scheme, and this makes the resulting algorithm favorable in both estimation accuracy and computational efficiency.