• Journal of Ecology and Environment
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• v.44 no.3
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• pp.162-177
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• 2020

Background: Ecologists have achieved much progress in the study of mechanisms that maintain species coexistence and diversity. In this paper, we reviewed a wide range of past research related to these topics, focusing on five theoretical bodies: (1) coexistence by niche differentiation, (2) coexistence without niche differentiation, (3) coexistence along environmental stress gradients, (4) coexistence under non-equilibrium versus equilibrium conditions, and (5) modern perspectives. Results: From the review, we identified that there are few models that can be generally and confidently applicable to different ecological systems. This problem arises mainly because most theories have not been substantiated by enough empirical research based on field data to test various coexistence hypotheses at different spatial scales. We also found that little is still known about the mechanisms of species coexistence under harsh environmental conditions. This is because most previous models treat disturbance as a key factor shaping community structure, but they do not explicitly deal with stressful systems with non-lethal conditions. We evaluated the mainstream ideas of niche differentiation and stochasticity for the coexistence of plant species across salt marsh creeks in southwestern Denmark. The results showed that diversity indices, such as Shannon-Wiener diversity, richness, and evenness, decreased with increasing surface elevation and increased with increasing niche overlap and niche breadth. The two niche parameters linearly decreased with increasing elevation. These findings imply a substantial influence of an equalizing mechanism that reduces differences in relative fitness among species in the highly stressful environments of the marsh. We propose that species evenness increases under very harsh conditions if the associated stress is not lethal. Finally, we present a conceptual model of patterns related to the level of environmental stress and niche characteristics along a microhabitat gradient (i.e., surface elevation). Conclusions: The ecology of stressful systems with non-lethal conditions will be increasingly important as ongoing global-scale climate change extends the period of chronic stresses that are not necessarily fatal to inhabiting plants. We recommend that more ecologists continue this line of research.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.7
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• pp.918-924
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• 2013

In a conventional power system, the frequency is recovered to the nominal value by the inertial, primary, and secondary responses of the synchronous generators (SGs) after a large disturbance such as a generator tripping. For a power system with high wind penetration, the system inertia is significantly reduced due to the maximum power point tracking control based operation of the variable speed wind generators (WGs). This paper proposes a virtual inertial control for a wind power plant (WPP) based on the maximum rate of change of frequency to release more kinetic energy stored in the WGs. The performance of the proposed algorithm is investigated in a model system, which consists of a doubly fed induction generator-based WPP and SGs using an EMTP-RV simulator. The results indicate that the proposed algorithm can improve the frequency nadir after a generator tripping. In addition, the algorithm can lead the instant of a frequency rebound and help frequency recovery after the frequency rebound.

• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.541-548
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• 2004

In the maritime container terminal. LMCTS (Linear Motor-based Container Transfer System) is horizontal transfer system for the yard automation, which In., been proposed to take the place of AGV (Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc. LMCTS is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the softcomputing method of a multi-step prediction control for LMCTS using DR- FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi step prediction Consequently, the system has an ability to adapt for external disturbance, detent force, force ripple, and sudden changes by loading and unloading the container.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.11
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• pp.65-73
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• 2005

The compressible flow of reactive fluid is investigated by using the transonic small-disturbance (TSD) model and the one-step first-order Arrhenuis chemical reaction. The fluid flow is restricted to dilute premixed reactions with small heat release. The effects of channel shape and Mach number on transonic combustion are studied by numerical analysis. The results show that the channel divergence increases the chemical reaction within the given channel length whereas the channel convergence inhibits the chemical reaction near the outlet and that increasing the inlet flow Mach number at a fixed reaction rate causes the flow acceleration in a diverging channel and the appearance of weak shock waves which do not show in the inert flow case. It also helps to increase the pressure and temperature near the diverging channel outlet and to consume the reactant within the given channel length.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.284-293
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• 2020

The rapid progress of AI technology gives us the expectation to solutions to various problems in our society, and at the same time, it gives us anxiety about the side effects that can occur if AI develops beyond human control. This study was conducted in the early 20s with less objection to advanced devices. We attempted to provide clues to understand thoughts and attitudes of the targets about the future environment that will be brought by AI through the process of finding intent the acceptance of strong AI technology. For this, we applied the Theory of Planned Behavior, and further expanded this research model to identify factors affecting the attitude toward AI. As a result, the attitude toward AI and perceived behavioral control had a significant effect on the intention to use to strong AI. In addition, we found that the expectation of the benefit of improving task performance and the anxiety on the threat of relationship disturbance had a significant effect on the attitude toward AI. This study suggests implications for AI-related companies establishing the direction of technology development and for government setting a policy direction for AI adoption.

• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.574-579
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• 2016

Unlike general unmanned aerial vehicles, the quad-rotor is attracting the attention of many people because of simple structure and very useful value. However, as the interest in drones increases, the safety and location of vehicles are becoming more important provide against aviation safety accidents or lost accidents. Therefore, in this paper, we propose a tracking system that stabilizes the model with a simple controller by linearized modeling and grasp tilt angle data from various sensor through the filter. The developed tracking system transmits the position of the quad-rotor in flight to the computer and shows it through the route, so it can check the flight path and various information such as flight speed and altitude at the same time. Then the sensor used in the actual quad-rotor can not measure exact sensor data for disturbance and vibration. So we use sensor fusion of Kalman filter and Complementary filter to overcome this problem and the stability of the quad-rotor hovering is realized by PID control. Through simulation, various information such as the speed, position, and altitude of the quad-rotor were confirmed in real time.

• Journal of Astronomy and Space Sciences
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• v.20 no.3
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• pp.205-216
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• 2003

The attitude motion of a spin-stabilized, upper-stage spacecraft is investigated based on a two-body model, consisting of a symmetric body, representing the spacecraft, and a spherical pendulum, representing the liquid slag pool entrapped in the aft section of the rocket motor. Exact time-varying nonlinear equations are derived and used to eliminate the drawbacks of conventional linear models. To study the stability of the spacecraft's attitude motion, both the spacecraft and pendulum are assumed to be in states of steady spin about the symmetry axis of the spacecraft and the coupled time-varying nonlinear equation of the pendulum is simplified. A quasi-stationary solution to that equation and approximate resonance conditions are determined in terms of the system parameters. The analysis shows that the pendulum is subject to a combination of parametric and external-type excitation by the main body and that energy from the excited pendulum is fed into the main body to develop the coning instability. In this paper, numerical examples are presented to explain the mechanism of the coning angle growth and how angular momenta and disturbance moments are generated.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.28-35
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• 2012

This paper presents the method for $H_{\infty}$ fuzzy controller design of discrete-time fuzzy Markovian jump systems with state and input time delays. The Takagi and Sugeno fuzzy model is employed to represent a delayed nonlinear system that possesses Markovian jump parameters. A stochastic mode dependent Lyapunov function is employed to analyze the stability and $H_{\infty}$ disturbance attenuation performance of the fuzzy Markovian jump systems with state and input time delays. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller is given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficiency of the proposed design method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.1
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• pp.8-17
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• 2002

This paper suggests that the immune algorithm can effectively be used in tuning of a PID controller. The artificial immune network always has a new parallel decentralized processing mechanism for various situations, since antibodies communicate to each other among different species of antibodies/B-cells through the stimulation and suppression chains among antibodies that form a large-scaled network. In addition to that, the structure of the network is not fixed, but varies continuously. That is, the artificial immune network flexibly self-organizes according to dynamic changes of external environment (meta-dynamics function). However, up to the present time, models based on the conventional crisp approach have been used to describe dynamic model relationship between antibody and antigen. Therefore, there are some problems with a less flexible result to the external behavior. On the other hand, a number of tuning technologies have been considered for the tuning of a PID controller. As a less common method, the fuzzy and neural network or its combined techniques are applied. However, in the case of the latter, yet, it is not applied in the practical field, in the former, a higher experience and technology is required during tuning procedure. In addition to that, tuning performance cannot be guaranteed with regards to a plant with non-linear characteristics or many kinds of disturbances. Along with these, this paper used immune algorithm in order that a PID controller can be more adaptable controlled against the external condition, including moise or disturbance of plant. Parameters P, I, D encoded in antibody randomly are allocated during selection processes to obtain an optimal gain required for plant. The result of study shows the artificial immune can effectively be used to tune, since it can more fit modes or parameters of the PID controller than that of the conventional tuning methods.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.431-439
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• 2015

One of common challenges in designing modern production machines is realizing high speed motion without sacrificing accuracy. To address this challenge it is necessary to maximize the stiffness of the mechanical structure and the control system with consideration on the main disturbance input, cutting forces. This paper presents analysis technologies for realizing high stiffness in production machines. First, CAE analysis techniques to evaluate the dynamic stiffness of a machine structure and a new method to construct the physical machine model for servo controller simulations are demonstrated. Second, cutting forces generated in milling processes are analyzed to evaluate their effects on the mechatronics system. In the effort to investigate the interaction among the structure, controller, and process, a flexible multi-body dynamics simulation method is implemented on a magnetic bearing stage as an example. The presented technologies can provide better understandings on the mechatronics system and help realizing high stiffness production machines.