• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• Korean Journal of Culture and Social Issue
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• v.15 no.4
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• pp.487-505
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• 2009

We focused on the missing confirmation domain of the hasteful behavior. We tried to identify the variety of hasteful behavior and the effects of missing confirmation behavior domain of the hasteful behavior on driving behaviors. 388 drivers responded to Hasteful Behavior Questionnaire, Driver Behavior Questionnaire(DBQ), and Driving Experience Questions. Data which have missing values among them were removed, 374 data were analyzed. As a result of factor analysis, hasteful behavior consist of time pressure, uncomfortableness, isolation, boring condition, and expecting rewards, and the DBQ consist of violation, error, and lapse. The components of hasteful behavior was divided into the missing confirmation behavior and the need for achievement domain by the second factor analysis and difference verification of coefficient of correlation. The missing confirmation behavior domain of hasteful behavior had significant influence on error and lapse. The isolation of the missing confirmation behavior domain had a negative effect, and the uncomfortableness of the missing confirmation domain had a positive effect on violation. The time pressure had a negative effect, and the isolation and the uncomfortableness had a positive effect on error and lapse.

• Korean Journal of Health Education and Promotion
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• v.18 no.3
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• pp.11-36
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• 2001

The purpose of this study is to analyze health behavior by comparing the difference between self-perceived health status and health examination results. The study subjects consist of 7,702 people aged over 20, surveyed by Health Interview survey, Health Examination survey, Dietary Life survey, Health Consciousness and Behavior survey. Data used in the study are drawn from raw data from a 1998 National Health and Nutrition survey. General characteristics variables are sex, age, education level, residential area, marital status, occupation, and living standard while dichotomous variables, ‘not healthy’ and ‘healthy’ are used to measure self-perceived health status. Variables for health examination results are high blood pressure, high cholesterol, diabetes, liver diseases, liver inflammation, kidney diseases, normal weight, regular diet, optimum sleeping time(7-8 hours), regular health examination and health behavior practice group. Major findings of the study are as follows: 1) Analysis of self-perceived health status and health behavior by disease: Variables significantly correlated with high self-perceived health status have strong associations with high health behavior practice, which supports the hypothesis that as one has high self-perceived health status, one is more likely to practice health promoting behavior. The results of analysis of health behavior differences by dividing subjects into two categories, ‘cases of illness’ and ‘cases of no illness’ indicate that drinking, sleeping time, health examination are significant variables (p〈0.001, 0.05) whereas smoking, weight control, regular exercise, regular diet are not significant. 2) Analysis of disparity patterns between self-perceived health status and health examination: The hypothesis that health behaviors would be different according to the disparity pattern between self-perceived health status and health examination is supported as a result of χ2 test. Among Type I : Self-perceived health status is high and actual health status is good (no disease) Type II: Self-perceived health status is high and actual health status is poor(have disease) Type III: Self-perceived health status is low and actual health status is good(no disease) Type IN: Self-perceived health status is low and actual health status is poor(have disease) Type I and Type IV show no disparity, Type I shows the highest health promoting behavior whereas Type IV shows the lowest health promoting behavior. Type II, and III, compared to Type I, practise lower health promoting behavior. Multi-logistics regression analysis was conducted to find out the degree of impact on health behavior. Independent variables are general characteristics, self-perceived health status and health examination result and presence of illness, while the dependent variable is health promoting behavior. The analysis of the impact of self-perceived health status on the health promoting behavior shows that smoking, drinking, weight control, regular exercise, health examination practice, and/or regular diet are significantly correlated to self-perceived health status. High self-perceived health status is inversely related to high health promoting behavior. This finding supports the hypothesis that the higher one perceives one's health, the more likely one is to practice health promoting behavior. On the contrary, the presence of illness has little impact on health promoting behavior. 3) Multiple logistics analysis on how disparity patterns between self-perceived health status and health examination affect health behavior: The results of multiple logistics analysis made on health behavior variables compared to the standard variable are as follows: When analyzed on the standard of Type I, smoking is a significant risk factor for the Type IV. In case of drinking, all the patterns show a high probability of relative risk ratio. With regard to weight control, it is a risk factor for Type II while all the patterns show high probability of not practising when analyzed on the standard of type IV. Type III and IV show high probability of not doing regular exercise while Type IV, shows a high probability of not taking appropriate sleeping time. When analyzed on the standard of type IV, all the patterns show a high probability of not taking health examinations. Type III and IV show a high probability of not having regular meals. As for overall health promoting behavior, Type III and IV show a high relative risk ratio. These two groups have low self-perceived health status. It implies that self-perceived health status has significant impact on health promoting behavior. This is also supported by the fact that Type I with high self-perceived health status and no illness shows a high practice rate of health promoting behavior. Types II and III the groups with high disparity between self-perceived health status and health examination results, show a low practice rate of health promoting behavior when compared to Type I. Type IV, that is the group with low self-perceived health status and actual illness, shows the lowest practice of health promoting behavior. It is highly probable that this type proves to be the poorest health group.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.262-269
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• 2016

In this paper, we propose a novel dynamical love model of Romeo and Juliet, which has an external force with a fuzzy membership function. The external force used in the model has the characteristics of a Gaussian function. The chaotic behavior in the model is demonstrated using time series and phase portraits.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.579-582
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• 1999

This paper represents the results of experiments designed to investigate the time-dependent response of concrete and steel tube in circular concrete-filled steel tubes, as are deployed extensively in high-rise building construction. The experiments were performed for creep of concrete and CFT column specimens with three loading cases. The creep coefficient and specific creep(unit creep) obtained from the test results were used for estimating and comparing the time-dependent response of each case. From these analyses, it is show that CFT-column has many merits for long-term behavior.

• East Asian mathematical journal
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• v.32 no.3
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• pp.377-385
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• 2016

Global attractor is a basic concept to study the long-time behavior of solutions of the various equations. This paper is investigated with the existence of a global attractor for the beam equation $$u_{tt}+{\Delta}^2u-{\nabla}{\cdot}\{{\sigma}({\mid}{\nabla}u{\mid}^2){\nabla}u\}+f(u)+a(x)g(u_t)=h,$$ using multipliers technique and Nakao's Lemma.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.497-506
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• 2007

Coverage-based NHPP SRGMs have been introduced in order to incorporate the coverage growth behavior into the NHPP SRGMs. The coverage growth function representing the coverage growth behavior during testing is thus an essential factor of the coverage-based NHPP SRGMs. This paper proposes a class of discrete time coverage growth functions and illustrates its application to real data sets.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.534-538
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• 1987

State-space techniques are employed to derive an equivalent nonlinear recurrent time-domain model that describes the series resonant converter behavior exactly. This model is employed effectively to analyze large signal behavior by propagating the recurrent equation and matching boundary conditions through digital computation. The model is verified with a laboratory converter for a steady-state operation.

• Communications of the Korean Mathematical Society
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• v.28 no.4
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• pp.751-766
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• 2013

We study the existence and long-time behavior of solutions to the following semilinear degenerate parabolic equation on $\mathbb{R}^N$: $$\frac{{\partial}u}{{\partial}t}-div({\sigma}(x){\nabla}u+{\lambda}u+f(u)=g(x)$$, under a new condition concerning a variable non-negative diffusivity ${\sigma}({\cdot})$. Some essential difficulty caused by the lack of compactness of Sobolev embeddings is overcome here by exploiting the tail-estimates method.

• Journal of Ginseng Research
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• v.18 no.1
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• pp.39-43
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• 1994

This study was performed to investigate the effect of ginseng saponin from Korean red ginseng on the learning and memory. Total (50, 100 mg/kg, bw) and panaxadiol saponin (15, 30 mg/kg, bw) treated groups did not show the difference of the time score and the number of error in comparison with control group. Panaxatriol saponin (15, 30 mg/kg, bw) significantly decreased both the time score and the number of error in water maze test. These results indicate that panaxatriol saponin from Korean red ginseng may improve the learning ability of rat in water multiple T-maze.