• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.191-214
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• 2014

The goal of this study is an exploratory statistical analysis of the university and college library statistics in the Academic Information Statistics System(rinfo.kr) governed of Korean Education and Research Information Service(KERIS) with performance measures based on sustainability. For the goal, we adopt a preprocessing method to develop change-rate variables by considering preceding predictive elements and succeeding performance elements, and to control external factors, such as size and socioeconomic factors. Then we execute a series of factor analyses and multiple linear regression analyses. 13 factors are extracted by the factor analyses and some sets of significant variables affecting the performance measures are identified through the regression analyses. Based on the results, we discuss the problem of out-lier and low correlation between variables. A suggestion for developing new variables is also discussed based on low effect sizes of the developed regression models. We hope that this study contributes to diffuse discussions on statistics system, evaluation, and further library management based on sustainability.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.457-465
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• 2011

Sample entropy (Vasicek, 1976) has poor performance, and several nonparametric entropy estimators have been proposed as alternatives. In this paper, we consider a piecewise uniform density function based on quantiles, which enables us to evaluate entropy in each interval, and study the poor performance of the sample entropy in terms of the poor estimation of lower and upper quantiles. Then we propose some improved entropy estimators by simply modifying the quantile estimators, and compare their performances with some existing estimators.

• The Journal of the Acoustical Society of Korea
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• v.16 no.6
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• pp.25-35
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• 1997

Most of speech analysis methods developed up to date are based on second order statistics, and one of the biggest drawback of these methods is that they show dramatical performance degradation in noisy environments. On the contrary, the methods using higher order statistics(HOS), which has the property of suppressing Gaussian noise, enable robust feature extraction in noisy environments. In this paper we propose a text-independent speaker identification system using higher order statistics and compare its performance with that using the conventional second-order-statistics-based method in both white and colored noise environments. The proposed speaker identification system is based on the vector quantization approach, and employs HOS-based voiced/unvoiced detector in order to extract feature parameters for voiced speech only, which has non-Gaussian distribution and is known to contain most of speaker-specific characteristics. Experimental results using 50 speaker's database show that higher-order-statistics-based method gives a better identificaiton performance than the conventional second-order-statistics-based method in noisy environments.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.119-123
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• 2009

Recently, a MEMS gyroscope has been broadly fabricated and used due to development of a micromachining. However, there is a difference between the modeling design and the actual product and this difference can lead to the performance variation of a MEMS gyroscope. A classical design method does not exactly estimate the performance of a MEMS gyroscope. Therefore a design process considering the design variable uncertainty has to be employed to design MEMS gyroscope model. In this paper, the equation of motion of a MEMS gyroscope model is obtained to analyze the performance of a MEMS gyroscope and the effects of the design variables on the MEMS gyroscope performance are investigated. Finally the performance of MEMS gyroscope is estimated through a statistical analysis based on sample statistics.

• Journal of the Korean Institute of Plant Engineering
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• v.23 no.4
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• pp.57-64
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• 2018

User-based collaborative filtering is a method of recommending an item to a user based on the preference of the neighbor users who have similar purchasing history to the target user. User-based collaborative filtering is based on the fact that users are strongly influenced by the opinions of other users with similar interests. Item-based collaborative filtering is a method of recommending an item by comparing the similarity of the user's previously preferred items. In this study, we create a recommendation model using user-based collaborative filtering and item-based collaborative filtering with consumer's consumption data. Collaborative filtering is performed by using RFM (recency, frequency, and monetary) technique with purchasing data to recommend items with high purchase potential. We compared the performance of the recommendation system with the purchase amount and the performance when applying the RFM method. The performance of recommendation system using RFM technique is better.

• ETRI Journal
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• v.28 no.6
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• pp.815-818
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• 2006

In the global Internet, a constraint-based routing algorithm performs the function of selecting a routing path while satisfying some given constraints rather than selecting the shortest path based on physical topology. It is necessary for constraint-based routing to disseminate and update link state information. The triggering policy of link state updates significantly affects the volume of update traffic and the quality of services (QoS). In this letter, we propose an adaptive triggering policy based on link-usage statistics in order to reduce the volume of link state update traffic without deterioration of QoS. Also, we evaluate the performance of the proposed policy via simulations.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.269-284
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• 2020

This study compares two teaching methods in an introductory statistics course at a large state university. The first method is the traditional lecture-based approach. The second method implements a flipped classroom that incorporates the recommendations of the American Statistical Association's Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. We compare these two methods, based on student performance, illustrate the procedures of the flipped pedagogy, and discuss the impact of aligning our course to current guidelines for teaching statistics at the college level. Results show that students in the flipped class performed better than students in traditional delivery. Student questionnaire responses also indicate that students in flipped delivery aligned with the GAISE recommendations have built a productive mindset in statistics.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.19 no.1
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• pp.61-87
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• 2008

There is a close relationship between indicators of statistics and performance measurement in international standards, working sections and the data items similarity in academic libraries. However, this co-relationship between statistics and measuring performance in the Korean academic library is not related to each other in terms of designing or usage. In order to prove this, the co-relationship between indicators of statistics and performance measurement has been researched based on applications of international standards and data. The international result shows 45% of overlapping in statistical and measuring performance indicators. However, there is only 14 to 26% of the co-relationship in existing statistics and performance measurement in Korea. A considerable improvement of the co-relationship between the indicators has newly been found. Therefore, in developing online system of academic library statistics, it is essential to provideinclusive information between indications of statistics and performance measurements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.849-853
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• 2005

Signal detectors often utilize nonlinear statistics of observations rather than the observation as they are. The sign statistic, a typical example of the nonlinear statistics, for example, relies oかy on the sign information of observations. In this letter, a qualitative analysis is presented that the correlation coefficients between the statistics and original observations can be used to predict the asymptotic performance of a detection schemes utilizing the nonlinear statistics.

• The Korean Journal of Applied Statistics
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• v.25 no.2
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• pp.321-330
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• 2012

In this paper we study some basic statistics in quantile regression. In particular, we investigate the residual, goodness-of-fit statistic and the effect of one or few observations on estimates of regression coefficients. In addition, we compare the proposed goodness-of-fit statistic with the statistic considered by Koenker and Machado (1999). An illustrative example based on real data sets is given to see the numerical performance of the proposed basic statistics.