• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1297-1300
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• 1993

Machine learning in an uncertain or unknown environment is of vital interest to those working with intelligent systems. The ability to garner new information, process it, and increase the understanding/ capability of the machine is crucial to the performance of autonomous systems. The field of artificial intelligence provides two major approaches to the problem of knowledge engineering-expert systems and neural networks. Harnessing the power of these two techniques in a hybrid, cooperating system holds great promise.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.3
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• pp.304-309
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• 2014

In this paper, we design a hybrid wheeled and legged mobile robot with a waist joint. The proposed hybrid mobile robot is designed to have a hybrid structure with leg and wheel for the efficient movement in flat and uneven surfaces. The proposed robot have a waist joint that is used to stably transform from wheeled driving to legged walking of the robot and to overcome non-flat surface. In order to recognize various environments we use LRF sensor, PSD sensor, CCD camera. Also, a motion planning method for hybrid mobile robot with a waist joint is proposed to select wheeled driving motion and legged walking motion of the robot based the environment types. We verify the efficient mobility of the developed hybrid mobile robot through navigation experiments using the proposed motion planning method in various environments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1118-1120
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• 1993

Fuzzy logic places a considerable burden on an inference engine for applications such as control or approximate reasoning. Various neural network architectures have been proposed to deal with the computational task, and yet, maintain flexibility in the desired traits of the final system. Recently, we introduced a trainable network architecture whose nodes implement weighted Yager additive hybrid operators for fuzzy logic inference in an approximate reasoning setting. In this paper we examine the utility of such networks for control situations. We show that they are capable of learning control functions which are piece-wise monotonic in each of the variables. The learning ability is demonstrated through an example.

• Journal of Microbiology and Biotechnology
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• v.32 no.4
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• pp.531-540
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• 2022

Due to the high incidence of malignant melanoma, the establishment of in vitro models that recapitulate the tumor microenvironment is of great biological and clinical importance for tumor treatment and drug research. In this study, 3D printing technology was used to prepare GelMA/PEGDA composite scaffolds that mimic the microenvironment of human malignant melanoma cell (A375) growth and construct in vitro melanoma micro-models. The GelMA/PEGDA hybrid scaffold was tested by the mechanical property, cell live/dead assay, cell proliferation assay, cytoskeleton staining and drug loading assay. The growth of tumor cells in two- and three-dimensional culture systems and the anti-cancer effect of luteolin were evaluated using the live/dead staining method and the Cell Counting Kit-8 (CCK-8) method. The results showed a high aggregation of tumor cells on the 3D scaffold, which was suitable for long-term culture. Cytoskeleton staining and immunofluorescent protein staining were used to evaluate the degree of differentiation of tumor cells under 2D and 3D culture systems. The results indicated that 3D bioprinted scaffolds were more suitable for tumor cell expansion and differentiation, and the tumor cells were more aggressive. In addition, luteolin was time- and dose-dependent on tumor cells, and tumor cells in the 3D culture system were more resistant to the drug.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.554-561
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• 2014

Hybrid wind Diesel stand-alone power systems are considered economically viable and effective to create balance between production and load demand in remote areas where the wind speed is considerable for electric generation, and also, electric energy is not easily available from the grid. In Wind diesel hybrid system, the wind energy system is the main constitute and diesel system forms the back up. This type of hybrid power system saves fuel cost, improves power capacity to meet the increasing demand and maintains the continuity of supply in the system. Problem we face in this system is that even after producing enough power through wind turbine system, considerable portion of this power needs to be dumped due to short term oversupply of power and to maintain the frequency within close tolerances. As a result remaining portion of total energy supplied comes from the diesel generator to overcome the temporal energy shortage. This scenario decreases the overall efficiency of hybrid power system. In this study, efficient Simulink modeling for wind-diesel hybrid system is proposed and some simulations study is carried out to verify the feasibility of the proposed scheme.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.692-697
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• 2011

There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid mobile robot that can dock with the other robot and transforms between wheeled robot and legged robot is proposed. The hybrid mobile robot platform has docking device with a peg and a cup module. In addition, the robot is possible to walk and drive according to condition of the road. A navigation algorithm of the hybrid mobile robot is proposed to improve the mobility of robots using docking algorithm based on image processing on the broken road and uneven terrain. The proposed method recognizes road condition through PSD sensor attached in front and bottom of the robot and selects an appropriate navigation method according to terrain surface. The proposed docking and navigation methods are verified through experiments using hybrid mobile robots.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.126-134
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• 2008

As many systems depend on electronics, concern for fault tolerance is growing rapidly. For example, a car with its steering controlled by electronics and no mechanical linkage from steering wheel to front tires (steer-by-wire) should be fault tolerant because a failure can come without any warning and its effect is devastating. In order to make system fault tolerant, there has been a body of research mainly from aerospace field. This paper presents the structure of predictive hybrid redundancy that can remove most erroneous values. In addition, several numerical simulation results are given where the predictive hybrid redundancy outperforms wellknown average and median voters.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.3
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• pp.337-345
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• 2009

The dependence of numerous systems on electronic devices is causing rapidly increasing concern over fault tolerance because of safety issues of safety critical system. As an example, a vehicle with electronics-controlled system such as x-by-wire systems, which are replacing rigid mechanical components with dynamically configurable electronic elements, should be fault￢tolerant because a devastating failure could arise without warning. Fault-tolerant systems have been studied in detail, mainly in the field of aeronautics. As an alternative to solve these problems, this paper presents the fuzzy hybrid redundancy system that can remove most erroneous faults with fuzzy fault detection algorithm. In addition, several numerical simulation results are given where the fuzzy hybrid redundancy outperforms with general voting method.

• International Journal of Automotive Technology
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• v.4 no.2
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• pp.57-64
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• 2003

The Intelligent Power Unit (IPU) utilized in Honda's Civic Hybrid Integrated Motor Assist (IMA) system was developed with the aim of making every component lighter, more compact and more efficient than those in the former model. To reduce energy loss, inverter efficiency was increased by fine patterning of the Insulated Gate Bipolar Transistor (IGBT) chips, 12V DC-DC converter efficiency was increased by utilizing soft-switching, and the internal resistance of the IMA battery was lowered by modifying the electrodes and the current collecting structure. These improvements reduced the amount of heat generated by the unit components and made it possible to combine the previously separated Power Control Unit (PCU) and battery cooling systems into a single system. Consolidation of these two cooling circuits into one has reduced the volume of the newly developed IPU by 42% compared to the former model.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.321-326
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. There exists a variety of combinations of d and q-axis current which provide a specific motor torque. The objective of the efficiency optimization controller is to seek a combination of d and q-axis current components, which provides minimum losses at a certain operating point in steady state. It is shown that the current components which directly govern the torque production have been very well regulated by the efficiency optimization control scheme. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm.