• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2272-2278
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• 2021

Background: Vibration stimulation has emerged as a treatment tool to help reduce spasticity during physical therapy. Spasticity includes problems of reduced range of motion (ROM) and stiffness. However, the benefits of vibration rolling (VR) on interventions for stroke patients are unclear. Objectives: This study aimed to investigate the effect of VR intervention on the ankle ROM and ankle stiffness in stroke patients. Design: A randomized crossover study. Methods: Seven stroke patients completed two test sessions (one VR and one non-VR [NVR]) in a randomized order, with 48 hours of rest between each session. Participants completed intervention and its measurements on the same day. The measurements included ankle dorsiflexion and plantarflexion ROM and stiffness of ankle muscles, including the tibialis anterior, medial, and lateral gastrocnemius muscle. Results: After VR, ankle dorsiflexion ROM, lateral gastrocnemius stiffness, and medial gastrocnemius stiffness improved significantly (all P<.05). After NVR, only the lateral gastrocnemius stiffness improved significantly (P<.05). Furthermore, in the cases of changed values for ankle dorsiflexion ROM and lateral gastrocnemius stiffness were compared within groups, VR showed a more significant difference than NVR (P<.05) Conclusion: VR improved ankle ROM and muscle stiffness. Therefore, we suggest that practitioners need to consider VR as an intervention to improve dorsiflexion ROM and gastrocnemius stiffness in stroke patients.

• Journal of Ocean Engineering and Technology
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• v.18 no.2
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• pp.77-82
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• 2004

The purpose of this study is to develop a nesting algorithm, using a genetic algorithm to optimize nesting order, and modified No Fit Polygon(NFP) methodology to place parts with the order generated from the previous genetic algorithm. Various genetic algorithm techniques, which have thus far been applied to the Travelling Salesman Problem, were tested. The partially mapped crossover method, the inversion method for mutation, the elitist strategy, and the linear scaling method of fitness value were selected to optimize the nesting order. A modified NFP methodology, with improved searching capability for non-convex polygon, was applied repeatedly to the placement of parts according to the order generated from previous genetic algorithm. Modified NFP, combined with the genetic algorithms that have been proven in TSP, were applied to the nesting problem. For two example cases, the combined nesting algorithm, proposed in this study, shows better results than that from previous studies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.111-118
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• 1995

This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.215-219
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• 2003

In this paper, we generate a trajectory minimized the energy gait of a biped robot for walking a staircase using genetic algorithms and apply to the computed torque controller for the stable dynamic biped locomotion. In the saggital plane, a 6 degree of freedom biped robot that model consists of seven links is used. In order to minimize the total energy efficiency, the Real-Coded Genetic Algorithm (RCGA) is used. Operators of genetic algorithms are composed of a reproduction, crossover and mutation. In order to approximate the walking gait, the each joint angle is defined as a 4-th order polynomial of which coefficients are chromosomes. Constraints are divided into equality and inequality. Firstly, equality constraints consist of position conditions at the end of stride period and each joint angle and angular velocity condition for periodic walking. On the other hand, inequality constraints include the knee joint conditions, the zero moment point conditions for the x-direction and the tip conditions of swing leg during the period of a stride for walking a staircase.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.157-160
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• 2001

This paper has been studied a Adaptive Mutation rate Genetic Algorithm Processor. Genetic Algorithm(GA) has some control parameters such as the probability of bit mutation or the probability of crossover. These value give a priori by the designer There exists a wide variety of values for for control parameters and it is difficult to find the best choice of these values in order to optimize the behavior of a particular GA. We proposed a Adaptive mutation rate GA within a steady-state genetic algorithm in order to provide a self-adapting mutation mechanism. In this paper, the proposed a adaptive mutation rate GAP is implemented on the FPGA board with a APEX EP20K600EBC652-3 devices. The proposed a adaptive mutation rate GAP increased the speed of finding optimal solution by about 10%, and increased probability of finding the optimal solution more than the conventional GAP

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.54-59
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• 2005

The cylindrical object are widely used as mechanical parts in the manufacturing process. In order to handling those objects using a robot or an automated machine automatically, the pose of the object must be known. The pose can be described by two rotation angles; one angle about the x axis and the other about the y axis. In the many previous researches these angles were obtained by the computationally intensive algorithm, that is, fitting the data as a polynomial and doing pseudo inverse. So that, this method required high performance microprocessor. In this paper in order to avoid complex computation, a new method based on a genetic algorithm is proposed and analyzed through a series of simulations. This algorithm utilized the geometry of the cylindrical shape. The simulation results show that this method find the pose angles very well In most cases, but the computation time is randomly changed because the genetic algorithm is basically one of the random search method.

• International Journal of Control, Automation, and Systems
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• v.5 no.1
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• pp.79-85
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• 2007

In this paper, a real-coded genetic algorithm is proposed for identification of time delay systems from step responses. FOPDT(First-Order Plus Dead-Time) and SOPDT(Second-Order Plus Dead-Time) systems, which are the most useful processes in this field, but are difficult for system identification because of a long dead-time problem and a model mismatch problem. Genetic algorithms have been successfully applied to a variety of complex optimization problems where other techniques have often failed. Thus, the modified crossover operator of a real-code genetic algorithm is proposed to effectively search the system parameters. The proposed method, using a real-coding genetic algorithm, shows better performance characteristics when compared to the usual area-based identification method and the directed identification method that uses step responses.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.56-64
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• 1997

In distributed autonomous robotic systems, each robot must behaves by itself according to the its states and environements, and if necessary, must cooperates with other orbots in order to carray out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new learning and evolution method based on reinforement learning having delayed reward ability and distributed genectic algorithms is proposed for behavior learning and evolution of collective autonomous mobile robots. Reinforement learning having delayed reward is still useful even though when there is no immediate reward. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability. Specially, in order to improve the perfodrmance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper, we verify the effectiveness of the proposed method by applying it to cooperative search problem.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.6
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• pp.514-528
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• 2004

An emotion-based video scene retrieval algorithm is proposed in this paper. First, abrupt/gradual shot boundaries are detected in the video clip representing a specific story Then, five video features such as 'average color histogram' 'average brightness', 'average edge histogram', 'average shot duration', and 'gradual change rate' are extracted from each of the videos and mapping between these features and the emotional space that user has in mind is achieved by an interactive genetic algorithm. Once the proposed algorithm has selected videos that contain the corresponding emotion from initial population of videos, feature vectors from the selected videos are regarded as chromosomes and a genetic crossover is applied over them. Next, new chromosomes after crossover and feature vectors in the database videos are compared based on the similarity function to obtain the most similar videos as solutions of the next generation. By iterating above procedures, new population of videos that user has in mind are retrieved. In order to show the validity of the proposed method, six example categories such as 'action', 'excitement', 'suspense', 'quietness', 'relaxation', 'happiness' are used as emotions for experiments. Over 300 commercial videos, retrieval results show 70% effectiveness in average.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.296-301
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• 2017

Recently, there are many efforts focused on development of more economical non-fluorinated membranes for PEMFCs (Proton Exchange Membrane Fuel Cells). In this study, sulfonated poly (ether ether ketone) (sPEEK) membrane reinforced with poly imide was made to enhance of membrane durability. In order to test durability of single (un-reinforced) membrane and reinforced membrane MEA (Membrane and Electrode Assembly), degradation accelerated stress test was used. Before and after degradation, I-V polarization curve, hydrogen crossover current, electrochemical surface area, membrane resistance and charge transfer resistance were measured. As a result of experiments, hydrogen crossover current of reinforced MEA was lower than that of single MEA, therefor durability of reinforced MEA was higher than that of single MEA. There was not especially short phenomena in reinforced MEA after degradation accelerated stress test.