• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.916-919
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• 2004

In this paper, we proposed a new method of pre-operative planning for tibial deformity correction using double hexapod external fixator in pseudoacondroplasia. The 3-D computer graphic model of deformed tibia was reconstructed from 3 mm sliced CT data, and CAD model of double hexapod external fixator was developed. The fixator was composed of 170 mm diameter of three rings and 90 mm of twelve struts. The bone deformities and the osteotomy lines for double osteotomy were measured using X-rays, and the necessary joint values to correct the given deformities were obtained by inverse kinematics analysis. The computer graphic simulation was performed to visualize the deformity correction process and evaluate the analysis result. By examining the pre-op and post-op X-rays, the simulation result was in good agreement with the clinical outcomes.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.111-119
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• 1996

In this paper, we propose time-optimal trajectory planning algorithms for cooperative multi-robot manipulators system considering optimal load distribution. Internal forces essentially effect on time optimal trajectory planning and if they are comitted, the time optimal scheme is not no longer true. Therefore, we try to find the internal force factors of cooperative robot manipulators system in a time-optimal aspect. In this approach, a specific generalized inverse is used and is fuzzified for the purpose. In this optimal method, the fuzzy logic concept is used and selected for diminishing computation time, for finding the load distribution factors.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.579-588
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• 1996

The purpose of this paper is to develop a method of Collision-Free Path Planning (CFPP) for an articulated robot. First, the configuration of the robot is built by a set of robot joint angles derived from robot inverse kinematics. The joint space, that is made of the joint angle set, forms a Configuration space (Cspcce). Obstacles in the robot workcell are also transformed into the Cobstacles using slice projection method. Actually the Cobstacles means the configurations of the robot causing collision with obstacles. Secondly, a connected graph, a kind of roadmap, is constructed by the free configurations in the Cspace, where the free configurations are randomly sampled from a free Cspace immune from the collision. Thirdly, robot paths are optimally determinant in the connected graph. A path searching algorithm based on $A^*$ is employed in determining the paths. Finally, the whole procedures for the CFPP method are shown for a proper articulated robot as an illustrative example.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1960-1961
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• 2006

In this paper, The trajectory control of robot manipulator is proposed. It divides by trajectory planning and tracking control. A trajectory planning and tracking control of robot manipulator is used to the neural network and evolutionary algorithm. The trajectory planning provides not only the optimal trajectory for a given cost function through evolutionary algorithm but also the configurations of the robot manipulator along the trajectory by considering the robot dynamics. The computed torque method (C.T.M) using the model of the robot manipulators is an effective means for trajectory tracking control. However, the tracking performance of this method is severely affected by the uncertainties of robot manipulators. The Radial Basis Function Networks(RBFN) is used not to learn the inverse dynamic model but to compensate the uncertainties of robot manipulator. The computer simulations show the effectiveness of the proposed method.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.83-85
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• 2002

Yonsei Cancer Center introduced an IMRT System at the beginning of February, 2002. The system consists of CORVUS(NOMOS) inverse planning machine, LANTIS(SIEMENS), PRIMEVIEW and PRIMART Linac(SIEMENS). The optimization of CORVUS planning system with PRIMART is an important work to get an efficient treatment plan. So, we studied two Finite Size Pencil Beams, 1.0 x 1.0 cm$^2$ and 0.5 x 1.0 cm$^2$, and four leaf transmission sets, 5%, 10%, 20%, 33%. We compared the dose distribution of target volume and delivery efficiency of the plan results.

• Journal of radiological science and technology
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• v.47 no.4
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• pp.271-278
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• 2024

This study aimed to evaluate the impact of changes in beam arrangement and arc counts on dosimetric factors in volumetric modulated arc therapy (VMAT) inverse radiation therapy planning for hippocampal-avoidance whole brain radiation therapy (HA-WBRT) by using the Elekta Monaco radiation therapy planning system (RTPs). For coplanar VMAT, both the arc per beam (APB) method and the beam determined arc(BDA) method, which is determined by the number of beams, were applied. For non-coplanar VMAT, the BDA method was utilized, and a total of 9 treatment plans were established by varying the arc counts. All radiation therapy plans met the radiation oncology group (RTOG) 0933 protocol standards, and 14 dosimetric factors were compared and analyzed. The results showed that the BDA-NC VMAT method demonstrated superior performance in terms of planning target volume (PTV) coverage and protection of normal organs, while APB-VMAT was advantageous in terms of hippocampal protection, monitor unit and delivery time. This study is expected to contribute to the efficient establishment of HA-WBRT plans considering the changes in beam arrangement and rotation arc numbers in Monaco RTPs.

• The Journal of Korean Society for Radiation Therapy
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• v.15 no.1
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• pp.41-52
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• 2003

I. Purpose The dose distribution in normal tissues and target lesions is very important in the treatment planning. To make the uniform dose distribution in target lesions, many methods has been used. Especially in the head and neck, the dose inhomogeneity at the skin surface should be corrected. Conventional methods have a limitation in delivering the enough doses to the planning target volume (PTV) with minimized dose to the parotid gland and spinal cord. In this study, we investigated the feasibility and the practical QA methods of the forward IMRT. II. Material and Methods The treatment plan of the forward IMRT with the partial block technique using the dynamic multi-leaf collimator (dMLC) for the patients with the nasopharyngeal cancer was verified using the dose volume histogram (DVH). The films and pinpoint chamber were used for the accurate dose verification. III. Results As a result of verifying the DVH for the 2-D treatment plan with the forward IMRT, the dose to the both parotid gland and spinal cord were reduced. So the forward IMRT could save the normal tissues and optimize the treatment. Forward IMRT can use the 3-D treatment planning system and easily assure the quality, so it is easily accessible comparing with inverse IMRT IV. Conclusion The forward IMRT could make the uniform dose in the PTV while maintaining under the tolerance dose in the normal tissues comparing with the 2-D treatment.

• Smart Structures and Systems
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• v.21 no.6
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• pp.741-749
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• 2018

Structural health monitoring (SHM) systems are necessary to achieve smart predictive maintenance and repair planning as well as they lead to a safe operation of mechanical structures. In the context of vibration-based SHM the measured structural responses are employed to draw conclusions about the structural integrity. This usually leads to a mathematically illposed inverse problem which needs regularization. The restriction of the solution set of this inverse problem by using prior information about the damage properties is advisable to obtain meaningful solutions. Compared to the undamaged state typically only a few local stiffness changes occur while the other areas remain unchanged. This change can be described by a sparse damage parameter vector. Such a sparse vector can be identified by employing $L_1$-regularization techniques. This paper presents a novel framework for damage parameter identification by combining sparse solution techniques with an Extended Kalman Filter. In order to ensure sparsity of the damage parameter vector the measurement equation is expanded by an additional nonlinear $L_1$-minimizing observation. This fictive measurement equation accomplishes stability of the Extended Kalman Filter and leads to a sparse estimation. For verification, a proof-of-concept example on a quadratic aluminum plate is presented.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.139-145
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• 2015

This paper proposed a method of cooperative control of three mobile robots for carrying an object placed on a floor together. Each robot moves to the object independently from its location to a pre-designated location for grasping the object stably. After grasping the common object, the coordination among the robots has been achieved by a master-slave mode. That is, a trajectory planning has been done for the master robot and the distances form the master robot to the two slave robots have been kept constant during the carrying operation. The localization for mobile robots has been implemented using the encoder data and inverse kinematics since the whole system does not have the slippage as much as a single mobile robot. Before the carrying operation, the lifting operations are implemented using the manipulators attached on the top of the mobile robots cooperatively. The real cooperative lifting and carrying operations are implanted to show the feasibility of the master-slave mode control based on the kinematics using the mobile manipulators developed for this research.

• KIISE Transactions on Computing Practices
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• v.23 no.10
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• pp.599-604
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• 2017

A useful application of smart assistants is to predict and suggest users' daily behaviors the way real assistants do. Conventional methods to predict behavior have mainly used explicit schedule information logged by a user or extracted from e-mail or SNS data. However, gathering explicit information for smart assistants has limitations, and much of a user's routine behavior is not logged in the first place. In this paper, we suggest a novel approach that combines explicit schedule information with patterns of routine behavior. We propose using inference based on a Markov decision process and learning with a reward function based on inverse reinforcement learning. The results of our experiment shows that the proposed method outperforms comparable models on a life-log dataset collected over six weeks.