• 한국대기환경학회지
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• 제20권1호
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• pp.119-128
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• 2004

The nitrate concentrations in PM$_{2.5}$ and TSP measured at Gosan, Jeju Island, Korea, between March 1998 and February 2002, are discussed. Especially, the characteristics of high nitrate concentration days were analyzed. High nitrate concentration cases in PM$_{2.5}$ were highly correlated with anthropogenic species such as NH$_4$$^{[-10]}$ , and high nitrate concentration cases in TSP were highly correlated with crustal species such as nss-Ca$^{2+}$ and nss -Mg$^{2+}$ Backward trajectory analysis results show the cases of high correlation between nitrate and anthropogenic species occurred when the air parcels moved from China, and the cases of high correlation between nitrate and crustal species occurred when the air parcels moved from Mongolia. Also, high nitrate concentration cases occurred most often in spring (65%) when the air parcels moved from Mongolia and China.ina.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.241-246
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• 2004

This paper proposed trajectory tracking control of mobile robot. Trajectory tracking control scheme are real coding genetic-algorithm and back-propergation algorithm. Control scheme ability experience proposed simulation. Stable tracking control problem of mobile robots have been studied in recent years. These studios have guaranteed stability of controller, but the performance of transient state has not been guaranteed. In some situations, constant gain controller shows overshoots and oscillations. So we introduce better control scheme using Real coding Genetic Algorithm(RCGA) and neural network. Using RCGA, we can find proper gains in several situations and these gains are generalized by neural network. The generalization power of neural network will give proper gain in untrained situation. Performance of proposed controller will verify numerical simulations and the results show better performance than constant gain controller.

• 한국공작기계학회논문집
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• 제11권4호
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• pp.62-67
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized loaming architecture. It is Proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tucking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 한국정밀공학회지
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• 제20권7호
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• pp.155-162
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• 2003

We propose a new technique far real-tine controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Caussian function as a unit function in the fuzzy neural network. and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-foray. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1697-1700
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• 2003

We propose a new technique for real-time controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and a back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.312-318
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• 2003

We propose a new technique for the cruise control system design of a mobile robot with three drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized teaming architecture. It is proposed a learning controller consisting of too neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by three independent wheels.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.207-212
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• 2004

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.179-181
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• 2007

This paper presents the desired position control of the mobile inverted pendulum system(MIP). The MIP is required to track the circular trajectory in the xy plane through the kinematic Jacobian relationship between the xy plane and the joint space. The reference compensation technique of the radial basis function(RBF) network is used as a neural network control method. The back-propagation teaming algorithm of the RBF network is derived and embedded on a DSP board. Experimental studies of tracking the circular trajectory are conducted.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2002년도 추계학술대회 논문집
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 대한정형도수물리치료학회지
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• 제19권1호
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• pp.49-54
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• 2013

Background: The purposed of this study is to examine the static and dynamic plantar foot pressure in chronic low back pain patients and normal adults. Methods: The subjects were divided into a group of 30 patients with chronic low back pain and a control group of 30 healthy persons. While static posture and dynamic posture at comfortable walking speeds, the low back pain group and the control group measured their plantar foot pressure and the trajectory of their center of pressure (COP) using the Matscan(R) system. Independent t-tests were measured to compare differences in plantar foot pressure characteristics between the left side and right side of the low back pain group and the control group. Results: In the comparison of differences in plantar foot pressure characteristics between the left side and right side of the low back pain group and the control group, the anteroposterior (AP) displacement of COP showed significant differences (p<.05). Although the low back pain group and the control group did not show any significant differences in leg length, weight distribution, mediolateral (ML) displacement of COP, static contract area, dynamic contract areas (p>.05), increases in the contract area values were shown in the hind foot in general. Conclusion: In this study, it was shown that patients with chronic low back pain were walking with short AP displacement of the COP as a compensatory action to avoid pain.