• Elastomers and Composites
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• v.55 no.2
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• pp.120-127
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• 2020

In this study, molding shrinkage of PPS resin was investigated. Two types of PPS resins with differing glass fiber and calcium carbonate content were used for this purpose. To observe mold shrinkage, molding conditions based on injection temperature, injection speed, and the position of the cushion were selected. Circular and rectangular specimens were used for the study model. Injection molding simulation was performed to predict the filling pattern and mold shrinkage, and the simulation results were compared with the experimental conclusions. It was observed that the mold shrinkage showed the highest shrinkage (distributed from 0.05% to 0.32%) dependence on the injection temperature, and the lowest shrinkage (distributed from 0.05% to 0.31%) dependence on the injection speed. The role of the position of the cushion in mold shrinkage was difficult to observe. The results of the simulation mostly agreed with the experimental results; however, for some molding conditions, the mold shrinkage in the simulation was overestimated as compared to that in the experiment.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.3-6
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• 2001

In common globular proteins, the native form is in its most stable state. However, the native form of inhibitory serpins (serine protease inhibitors) and some viral membrane fusion proteins is in a metastable state. Metastability in these Proteins is critical to their biological functions. Our previous studies revealed that unusual interactions, such as side-chain overpacking, buried polar groups, surface hydrophobic pockets, and internal cavities are the structural basis of the native metastability. To understand the mechanism by which these structural defects regulate protein functions, cavity-filling mutations of ${\alpha}$1-antitrypsin, a prototype serpin, were characterized. Increasing conformational stability is correlated with decreasing inhibitory activity. Moreover, the activity loss appears to correlate with the decrease in the rate of the conformational switch during complex formation with a target protease. We also increased the stability of ${\alpha}$1-antitrypsin greatly via combining various stabilizing single amino acid substitutions that were distributed throughout the molecule. The results showed that a substantial increase of stability, over 13 kcal/mol, affected the inhibitory activity with a correlation of 11% activity loss per kcal/mol. The results strongly suggest that the native metastability of proteins is indeed a structural design that regulates protein functions and that the native strain of e 1-antitrypsin distributed throughout the molecule regulates the inhibitory function in a concerted manner.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.173-182
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• 2005

In this paper, a target tracking algorithm for tracking maneuvering vehicles is presented. The overall algorithm belongs to the category of an interacting multiple-model (IMM) algorithm used to detect multiple targets using fused information from multiple sensors. First, two kinematic models are derived: a constant velocity model for linear motions, and a constant-speed turn model for curvilinear motions. Fpr the constant-speed turn model, a nonlinear information filter is used in place of the extended Kalman filter. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. The model-matched filter used in multi-sensor environments takes the form of a federated nonlinear information filter. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. In this paper, the structural features and information sharing principle of the federated information filter are discussed. The performance of the suggested algorithm using a Monte Carlo simulation under the two patterns is evaluated.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1916-1917
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• 2011

A development of a new moving obstacle avoidance algorithm using a delay-time Compensation for a network-based autonomous mobile robot is proposed in this paper. The moving obstacle avoidance algorithm is based on a Kalman filter through moving obstacle estimation and a Bezier curve for path generation. And, the network-based mobile robot, that is a unified system composed of distributed environmental sensors, mobile actuators, and controller, is compensated by a network delay compensation algorithm for degradation performance by network delay. The network delay compensation method by a sensor fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of readings of an odometry and the delay of reading of environmental sensors. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal point is shown here.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1898-1899
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• 2011

In this paper, we propose an obstacle avoidance algorithm for a network-based autonomous mobile robot. The obstacle avoidance algorithm is based on the VFH (Vector Field Histogram) algorithm and delay-compensative methods with the VFH algorithm are proposed for the network-based robot that is a unified system composed of distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the compensated readings of the sensors are used for building the polar histogram of the VFH algorithm. Secondly, a sensory fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of the readings of an odometry sensor and the delay of the readings of the environmental sensors. The performance enhancements of the proposed obstacle avoidance algorithm from the viewpoint of efficient path generation and accurate goal positioning are also shown in this paper through some simulation experiments by the Marilou Robotics Studio Simulator.

• Journal of Navigation and Port Research
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• v.28 no.7
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• pp.635-640
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• 2004

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) operating in container terminals is presented. The developed navigation algorithm takes the form of a federated information filter used to detect other AGVs and avoid obstacles using fused information from multiple sensors. Being equivalent to the Kalman filter (KF) algebraically, the information filter is extended to N-sensor distributed dynamic systems. In multi-sensor environments, the information-based filter is easier to decentralize, initialize, and fuse than a KF-based filter. It is proved that the information state and the information matrix of the suggested filter, which are weighted in terms of an information sharing factor, are equal to those of a centralized information filter under the regular conditions. Numerical examples using Monte Carlo simulation are provided to compare the centralized information filter and the proposed one.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.155-160
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• 2011

In distributed source localization where sensors transmit measurements to a fusion node, we address the sensor selection problem where the goal is to find the best set of sensors that maximizes localization accuracy when quantization of sensor measurements is taken into account. Since sensor selection depends heavily upon rate assigned to each sensor, joint optimization of rate allocation and sensor selection is required to achieve the best solution. We show that this task could be accomplished by solving the problem of allocating rates to each sensor so as to minimize the error in estimating the position of a source. Then we solve this rate allocation problem by using the generalized BFOS algorithm. Our experiments demonstrate that the best set of sensors obtained from the proposed sensor selection algorithm leads to significant improvements in localization performance with respect to the set of sensors determined from a sensor selection process based on unquantized measurements.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.53.2-53
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• 2002

NARO Space Center is being developed as a national project for the Korea Space Development Program. Among the major missions of the Space Center, the Range Control System is the focal point for all command and control operation of the Space Center. The acquired data from the Tracking Stations and the on-site facilities is processed and distributed in the Control Center. Data processing or data fusion is needed for the exact tracking of the Launch Vehicle from several tracking systems. The first phase, which is the best telemetry source is selected among data streams that are received from each telemetry stations using some pre-defined criterion. Trajectory data and major telemetry parameters...

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.2
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• pp.131-139
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• 1999

An easy and efficient method is proposed for a computation of reliability of preprocessing filters in the fire control system when the sensor data are frequently unreliable depending on the operation environment. It computes state transition probability matrix after modeling filter states as a Markov process, and computing false alarm and detection probability of each filter state under the given sensor failure probability. It shows that two important indices such as distributed state probability and error variance can be derived easily for a reliability assessment of the given sensor fusion system.

• Journal of Sensor Science and Technology
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• v.30 no.3
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• pp.131-138
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• 2021

The optimization of the specifications of vertical silicon on insulator (SOI) slot optical waveguides suitable for integrated-optical biochemical sensors was performed through computational analysis of the confinement factor of the guided mode distributed in the slot in addition to analytical examination of the TE mode. The optimized specifications were confirmed based on sensitivity in terms of the change in the refractive index of the biochemical analyte. When the slot width, rail width, and height were set to 120 nm, 200 nm, and 320 nm, respectively, the confinement factor was evaluated to be about 56% and the sensitivity was at least 0.9 [RIU/nm].