• Smart Media Journal
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• v.3 no.3
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• pp.26-35
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• 2014

The statistical graphics is a design field focusing on the user perception aspects for the correct information delivery and the effective understanding, with the use of the quantitative data through the information analysis, extraction, visualization process. The statistical graphics with the big data composition factor is termed as the statistical big data graphics. In the statistical graphics the visual factors are used to reduce the errors in the perception part and to successfully deliver the information. However, in the statistical big data graphics the visual factors of the enormous data are causing the cognitive discouragements. The purpose of this study is to extract the cognitive discouragement factors from the big data statistical graphics, categorizing the types of the statistical big data graphics as 'network type', 'segment type', and 'mixed type', based on their compositional shapes, and explored the characteristics according to them. Especially, based on the visual main factors in the statistical big data graphics, We extracted the cognitive discouragement factors that appear in the high visualization as the four categories: 'multi-dimensional cases', 'various color', 'information overlap', and 'legibility of the writing'.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.4
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• pp.615-625
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• 2011

This study presents a descriptive statistical analysis on grade characteristics and employment rates of three ocean-related departments at a university. The ocean-related departments belong to the same college along with the other six departments. To obtain the correlation between the grade characteristics and employment rates, we carried out the followings. Firstly, four-year employment rates and six-semester GPAs (grade point averages) were obtained from the nine departments. Secondly, the box-and-whisker plots were constructed for each data set to capture the grade characteristics (mean, the first quartile, median, third quartile, whisker+, and Q3 box). Finally, the grade characteristics and employment rates were correlated. It is shown from the correlation analysis that the employment rate has a positive linear relation with the mean or third quartile, while the rate has a negative linear relation with the whisker+ or Q3 box, for the ocean-related departments possibly because these departments have higher regular employment rates than those of the other six departments.

• Journal of Power System Engineering
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• v.13 no.2
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• pp.63-70
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• 2009

This paper discusses the influence on long-tenn predictions of the ship response in ocean by using the Global Wave Statistics data, GWS, and wave information from the remote sensing satellites. GWS's standard scatter diagrams of significant wave height and zero-crossing wave period are suggested to be corrected to a round number of 0.01/1000 fitted with a statistical analytic model of the conditional lognormal distribution for zero-crossing wave period. The GEOSAT satellite data are utilized which presented by I. R. Young and G. J. Holland (1996, named as GEOSAT data). At first, qualities of this data are investigated, and statistical characteristic trends are studied by means of applying known probability distribution functions. The wave height data of GEOSAT are compared to the data observed onboard merchant ships, the data observed by measure instrument installed on the ocean-going container ship and so on. To execute a long-tenn prediction of ship response, joint probability functions between wave height and wave period are introduced, therefore long-term statistical predictions are executed by using the functions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.875-879
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• 2007

The effects of the statistical properties of the Coulomb friction coefficients on the dynamic responses of a galloping quadruped robot are investigated in this paper. In general, the Coulomb friction coefficients are assumed to be deterministic for a controller design to achieve required motion characteristics. However, the friction coefficients between the ground and the robot legs are not constant in reality. Therefore, statistical characteristics of the friction coefficients need to be considered for a multi-body modeling of the robot galloping on the ground. The effects of the statistical properties on the dynamic responses of the quadruped robots are investigated.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.3
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• pp.116-126
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• 2003

In this study, we research about the relationships of human longevity and environments, inducted the significant factors of longevity from the statistical analysis, and represented spatial distribution of longevity using geographic information system. The factors confining human longevity can be categorized by geography/geology, climate/weather, economy, and social welfare. After analyzing statistical data, dependent variable which means the longevity index is defined by the ratio of population more than 85 years old among population more than 65 years old. The results of analysis show that longevity are related with waterworks ratio, temperature, local tax ratio, and latitude. In this study we discussed about the spatial characteristics which are represented by variance of the longevity index and described a spatial relationship between the longevity index and significant factors which are chosen by statistical analysis. In the further study, in order to sustain the longevity of a region, it is necessary for the effective rural planning to propagate a longevity of rural areas.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.241-262
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• 2012

An understanding of quality attributes is relevant for the software organization to deliver high software reliability. An empirical assessment of metrics to predict the quality attributes is essential in order to gain insight about the quality of software in the early phases of software development and to ensure corrective actions. In this paper, we predict a model to estimate fault proneness using Object Oriented CK metrics and QMOOD metrics. We apply one statistical method and six machine learning methods to predict the models. The proposed models are validated using dataset collected from Open Source software. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the model predicted using the random forest and bagging methods outperformed all the other models. Hence, based on these results it is reasonable to claim that quality models have a significant relevance with Object Oriented metrics and that machine learning methods have a comparable performance with statistical methods.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1231-1234
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• 2006

In this study, we detected electromagnetic waves generated in an enclosed switchgear and applied various statistical methods for detecting signals. We calculated the various statistical factors via the appropriate statistical methods. Further, we used these statistics to recognize the characteristics for each pattern by identifying the partial discharge in each case for normal, proceeding and abnormal states. The characteristics of electromagnetic wave patterns occurred in various states at electric power facilities and were used as an output variable for more efficient diagnosis. In this paper, we confirmed that the pattern of partial discharge signal can be used as one of the factors used to analyze the insulation state and to consider while estimating diagnosis of insulation states by recognizing the signal pattern to intelligence. We will utilize the proposed diagnosis method to determine insulation degradation states.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.2
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• pp.149-154
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• 2014

Detection performance of fire detection in the outdoor depends on weather conditions, the shadow by the movement of the sun, or illumination changes. In this paper, a smoke detection in conjunction with a robust background estimate algorithm to environment change in the outdoor in daytime is proposed. Gaussian Mixture Model (GMM) is applied as background estimation, and also, statistical characteristics of smoke is applied to detect the smoke for separated candidate region. Through the experiments with input videos obtained from a various weather conditions, the proposed algorithms were useful to detect smoke in the outdoor.

• Journal of Aerospace System Engineering
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• v.10 no.1
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• pp.103-110
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• 2016

This study shows the statistical properties of the domestic composite material prepregs test result. During the last three years(2012.5~2015.6) the prepreg specimen tests have been performed by referring to NCAMP developed test procedure which was approved by FAA. The database of (1) Carbon Tape, (2) Glass Fabric, and (3) Carbon Fabric composite material prepregs' characteristics have been established for certified aircraft structures. This qualified materials can be used for aircraft structural design through proper material equivalency procedures.

• Communications for Statistical Applications and Methods
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• v.28 no.6
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• pp.583-594
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• 2021

In this paper, we propose wavelet-based procedures to identify the difference between images, including portraits and handwriting. The proposed methods are based on a novel combination of multiscale methods with a regularization technique. The multiscale method extracts the local characteristics of an image, and the distinct features are obtained through the regularized regression of the local characteristics. The regularized regression approach copes with the high-dimensional problem to build the relation between the local characteristics. Lytle and Yang (2006) introduced the detection method of forged handwriting via wavelets and summary statistics. We expand the scope of their method to the general image and significantly improve the results. We demonstrate the promising empirical evidence of the proposed method through various experiments.