The Target Searching Method in the Chaotic Mobile Robot Embedding BVP Model

Bae, Young-Chul; Kim, Yi-Gon; Koo, Young-Duk

doi:10.5391/jkiis.2007.17.2.259

Cited by 5 publications

(3 citation statements)

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“…In the last two decades, chaotic dynamics has been used widely in real-world applications, such as biological systems [1], brain modeling [2], weather modeling [3], vibration modeling [4], mechanical and electrical engineering [5,6], control and synchronization [7][8][9][10][11], robotics [12,13], and others [14][15][16][17][18]. Currently, it is also being studied by many researchers in biology, physics, sociology, psychology, physiology, and engineering.…”

Section: Introductionmentioning

confidence: 99%

Synchronization of Dynamical Happiness Model

Bae

2014

International Journal of Fuzzy Logic and Intelligent Systems

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Chaotic dynamics is an active research area in fields such as biology, physics, sociology, psychology, physiology, and engineering. Interest in chaos is also expanding to the social sciences, such as politics, economics, and societal events prediction. Most people pursue happiness, both spiritual and physical in many cases. However, happiness is not easy to define, because people differ in how they perceive it. Happiness can exist in mind and body. Therefore, we need to be happy in both simultaneously to achieve optimal happiness. To do this, we need to synchronize mind and body. In this paper, we propose a chaotic synchronization method in a mathematical model of happiness organized by a second-order ordinary differential equation with external force. This proposed mathematical happiness equation is similar to Duffing's equation, because it is derived from that equation. We introduce synchronization method from our mathematical happiness model by using the derived Duffing equation. To achieve chaotic synchronization between the human mind and body, we apply an idea of mind/body unity originating in Oriental philosophy. Of many chaotic synchronization methods, we use only coupled synchronization, because this method is closest to representing mind/body unity. Typically, coupled synchronization can be applied only to non-autonomous systems, such as a modified Duffing system. We represent the result of synchronization using a differential time series mind/body model.

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Section: Introductionmentioning

confidence: 99%

Synchronization of Dynamical Happiness Model

Bae

2014

International Journal of Fuzzy Logic and Intelligent Systems

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“…In the last two decades, chaotic dynamics have been widely used in real-world applications such as biological systems [1], brain modeling [2], weather modeling [3], vibration modeling [4], mechanical and electrical engineering [5,6], control and synchronization [7,8,19], robotics [9,10], and more [12][13][14][15]20,21]. Currently, it is an active area of research by many in biology, physics, sociology, psychology, physiology, and engineering.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Dynamics in Tobacco's Addiction Model

Bae¹

2014

International Journal of Fuzzy Logic and Intelligent Systems

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Chaotic dynamics is an active area of research in biology, physics, sociology, psychology, physiology, and engineering. This interest in chaos is also expanding to the social scientific fields such as politics, economics, and argument of prediction of societal events. In this paper, we propose a dynamic model for addiction of tobacco. A proposed dynamical model originates from the dynamics of tobacco use, recovery, and relapse. In order to make an addiction model of tobacco, we try to modify and rescale the existing tobacco and Lorenz models. Using these models, we can derive a new tobacco addiction model. Finally, we obtain periodic motion, quasi-periodic motion, quasi-chaotic motion, and chaotic motion from the addiction model of tobacco that we established. We say that periodic motion and quasi-periodic motion are related to the pre-addiction or recovery stage, respectively. Quasi-chaotic and chaotic motion are related to the addiction stage and relapse stage, respectively.

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“…Nonlinear dynamics, including chaotic dynamics, have been widely used in real-world applications such as biological systems [1], brain modeling [2], weather modeling [3], vibration modeling [4], mechanical and electrical engineering [5,6], control and synchronization [7,8], robotics [9,10], and more [11][12][13][14][15]. Chaotic dynamics have also been studied by many researchers in the fields of biology, physics, and engineering.…”

Section: Introductionmentioning

confidence: 99%

Chaotic Phenomena in Addiction Model for Digital Leisure

Bae¹

2013

International Journal of Fuzzy Logic and Intelligent Systems

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Chaotic dynamics have been studied by many researchers in the fields of biology, physics, and engineering. Interest in chaos is also expanding to the social sciences such as politics, economics, and others, including the prediction of societal events. The concept of leisure has developed from a passive concept correlated with relaxation, entertainment, and ideology formation into a positive concept that assumes a more active role. As information and communications technology develops, digital leisure activity is expected to continue spreading. This expansion of digital leisure function correctly, as well as. Traditional leisure activity functions correctly more, whereas digital leisure activity is predicted to function incorrectly more often. In this paper, we propose a mathematical addiction model of digital leisure that deals with its dysfunctions such as addiction to digital leisure, including computer games, internet search, internet chatting, and social media. Herein, to solve addiction to digital leisure, we propose a model derived from a nicotine addiction.

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The Target Searching Method in the Chaotic Mobile Robot Embedding BVP Model

Cited by 5 publications

References 0 publications

Synchronization of Dynamical Happiness Model

Synchronization of Dynamical Happiness Model

Chaotic Dynamics in Tobacco's Addiction Model

Chaotic Phenomena in Addiction Model for Digital Leisure

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