• Spatial Information Research
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• v.18 no.5
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• pp.13-26
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• 2010

In this paper, a dynamic variable window-based topographical classification method is proposed which has the changeable classification units depending on topographical properties. In the proposed scheme, to im prove the classification efficiency, the unit of topographical classification can be changeable dynamically according to the topographical properties and repeated patterns. Also, in this paper, the classification efficiency and accuracy of the proposed method are analyzed in order to find an optimal maximum decision window-size through the experiment. According to the experiment results, the proposed dynamic variable window-based topographical classification method maintains similar accuracy but remarkably reduce computing time than that of a fixed window-size based one, respectively.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.330-340
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• 2007

IEEE 802.11 wireless LANs employ the backoff algorithm to avoid contentions among STAs when two or more STAs attempt to transmit their data frames simultaneously. The MAC efficiency can be improved if the CW values are adaptively changed according to the channel state of IEEE 802.11 wireless LANs. In this paper, we propose a dynamic contention window control algorithm using the genetic algorithm to improve the MAC throughput of IEEE 802.11 wireless LANs.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.689-694
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• 2011

Objective: The aim of this study is to evaluate the fluctuation of signal amplitude during repetitive dynamic contraction based on surface electromyography(EMG). Background: The most previous studies were considered isometric muscle contraction and they were difference to smoothing window length by moving average filter. In practical, the human movement is dynamic state. Dynamic EMG signal which indicated as the nonstationary pattern should be analyzed differently compared with the static EMG signal. Method: Ten male subjects participated in this experiment, and EMG signal was recorded by biceps brachii, anterior/posterior deltoid, and upper/lower trapezius muscles. The subject was performed to repetitive right horizontal lifting task during ten cycles. This study was considered three independent variables(muscle, amplitude processing technique, and smoothing window length) as the within-subject experimental design. This study was estimated muscular activation by means of the linear envelope technique(LE). The dependent variable was set coefficient of variation(CV) of LE for each cycle. Results: The ANOVA results showed that the main and interaction effects between the amplitude processing technique and smoothing window length were significant difference. The CV value of peak LE was higher than mean LE. According to increase the smoothing window length, this study shows that the CV trend of peak LE was decreased. However, the CV of mean LE was analyzed constant fluctuation trend regardless of the smoothing window length. Conclusion: Based on these results, we expected that using the mean LE and 300ms window length increased reproducibility and signal noise ratio during repetitive dynamic muscle contraction. Application: These results can be used to provide fundamental information for repetitive dynamic EMG signal processing.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.91-99
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• 2013

An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.389-397
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• 2011

The global dynamic window approach (DWA) is widely used to generate the shortest path of mobile robots considering obstacles and kinematic constraints. However, the dynamic constraints of robots should be considered to generate the minimum-time path. We propose a modified global DWA considering the dynamic constraints of robots. The reference path is generated using A* algorithm and smoothed by cardinal spline function. The trajectory is then generated to follows the reference path in the minimum time considering the robot dynamics. Finally, the local path is generated using the dynamic window which includes additional terms of speed and orientation. Simulation and experimental results are presented to verify the performance of the proposed method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.5
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• pp.681-687
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• 2003

Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces fur realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and the T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in a successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. The dynamic T-search, which is proposed in this paper, combines conventional T-search and the concept of the dynmaic-window search which uses reduced searching windows or sets of triangular surface polygons at each frame by taking advantage of the information regarding dynamic charactereistics of a simulated vehicle. Numerical tests show improvement of searching speeds by about 5% for randomly distributed triangles. For continuous search following a vehicle path, which occurs in actual vehicle simulation, the searching speed becomes 4 times faster.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.3
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• pp.593-603
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• 1997

Connection admission decision in ATM networks requires decision made in real time using fast algorithm. It is difficult to construct a model of the multiplexed traffic and thus, approximation of the traffic load is necessary. In this paper, we propose a measurement-based dynamic CAC(Connection admission Control) in ATM(Asynchronous Transfer Mode) networks, which observes current traffic by the moving window and set the window size to the value which is computed from the measured cell loss amount. It is based on the measurements of the traffic load over an admission period that is load enough to reflect the current traffic behavior instead of analytic modeling. And, the dynamic reallocation of bandwidth for each class leads to effective bandwidth utilization. The performance of proposed method is analyzed through computer simulation. The performance of proposed method is analyzed by using SIMAN simulation package and FORTRAN language. As can be seen in the simulation result, cell loss performance and bandwidth utilization have been increased.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.10-19
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• 2009

Wireless LAN systems have been widely implemented for supporting the wireless internet services especially in the hotspot areas such as hospitals, homes, conference rooms, and so on. Compared with wired LAN systems, wireless LAN systems have the advantages of the users' mobility support and low implementation and maintenance costs. IEEE 802.11 wireless LAN systems employ the backoff algorithm to avoid contentions among STAs when two or more STAs attempt to transmit their data frames simultaneously. The MAC efficiency can be improved if the CW values are adaptively changed according to the channel state of IEEE 802.11 wireless LANs. In this paper, a dynamic contention window control algorithm is proposed using the genetic algorithm to improve the MAC throughput of IEEE 802.11 wireless LANs.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.61-69
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• 2021

Recently, autonomous navigation technology is actively being developed due to the increasing demand of an unmanned surface vehicle(USV). Local planning is essential for the USV to safely reach its destination along paths. the dynamic window approach(DWA) algorithm is a well-known navigation scheme as a local path planning. However, the existing DWA algorithm does not consider path line tracking, and the fixed weight coefficient of the evaluation function, which is a core part, cannot provide flexible path planning for all situations. Therefore, in this paper, we propose a new DWA algorithm that can follow path lines in all situations. Fixed weight coefficients were trained using reinforcement learning(RL) which has been actively studied recently. We implemented the simulation and compared the existing DWA algorithm with the DWA algorithm proposed in this paper. As a result, we confirmed the effectiveness of the proposed algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.94-96
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• 2021

In this paper, we develop a new navigation algorithm for industrial mobile robots to arrive at the destination in unknown environment. To achieve this, we suggest a navigation algorithm that combines Dynamic Window Approach (DWA) and Dijkstra path planning algorithm. We compare Local Dynamic Window Approach (LDWA), Global Dynamic Window Approach(GDWA), Rapidly-exploring Random Tree (RRT) Algorithm. The navigation algorithm using Dijkstra algorithm combined with LDWA and GDWA makes mobile robots to reach the destination. and obstacles faced during the path planning process of LDWA and GDWA. Then, we compare on time taken to arrive at the destination, obstacle avoidance and computation complexity of each algorithm. To overcome the limitation, we seek ways to use the optimized navigation algorithm for industrial use.