• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.76-84
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• 2010

Many pedestrian simulation models for micro-scale spaces as building indoor areas have been proposed for the last decade and two models - social force model and floor field model - are getting attention. Among these, CA-based floor field model is viewed more favourable for computer simulations than computationally complex social force model. However, Kirchner's floor field model has limitations in capturing the differences in dynamic values of different agents and this study proposes an enhanced algorithm. This study improved the floor field model in order for an agent to be able to exclude the influences of its own dynamic values by changing the data structure, and, also modified the initial dynamic value problem in order to fit more realistic environment. In the simulations, real 3D building data stored in a spatial DBMS were used considering future integration with indoor localization sensors and real time applications.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.242-244
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• 2003

The functional test of protection relays is divided into two kind of test types; the steady-state test and dynamic test. Because the steady-state test is comparatively easy, this test is used to test the characteristics of the relaying elements, operating values, resetting values and etc. using equipment such as Doble. But the dynamic test has to be performed on the test environment with RTDS(real time digital simulator) because of the dynamic characteristics of real protection relays. Therefore, it is not usually easy to perform dynamic test of relays using power system simulation tool based on PC(personal computer) such as PSCAD/EMTDC. This paper discusses how to develop and implement a test model and user-defined components that can be performed dynamic test using PSCAD/EMTDC.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.30-37
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• 2010

Many embedded real - lime systems have adopted processors supported with dynamic voltage scal-ing(DVS) recently. Power is one of the important metrics for Optimization in the design and operation of embedded real-time systems. We can save considerable energy by using slowdown of processor sup-ported with DVS. In this paper, we improved the previous algorithm at a point of view of time complexity to calculate task slowdown factors for an efficient energy consumption in embedded real-time systems with task synchronization. We grasped the properties of the previous algorithm having $O(n^{2})$ time complexity through mathematical analysis and s simulation. Using its properties we proposed the improved algorithms with O(nlogn) and O(n) time complexity which have the same performance as the previous algorithm has.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.10
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• pp.1518-1527
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• 1989

We proposed a technique to design a multimicrocomputer system for real-time parallel processing with an interconnection network which has good network latency time. In order to simplify the performance evaluation and the design procedure under the hard real-time constraints we defined network latency time which takes into account the queueing delays of the networks. We designed a dynamic interconnection network following the proposed technique, and the simulation results show that we can easily estimate the multimicrocomputer system's approximate performance using the defined network latency time before the actual design, so this definition can help the efficient design of the real-time parallel processing systems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.18-26
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• 2008

In this paper, dynamic GTS scheduling method based on IEEE 802.15.4 is proposed for wireless control system considering reliability and real-time property. The proposed methods can guarantee a transmission of real-time periodic and sporadic data within the limited time frame in factory environment. The superframe of IEEE 802.15.4 is used for the dynamic transmission method of real-time mixed traffic (periodic data, sporadic data, and non real-time message). By separating CFP and CAP properly, the periodic, sporadic, and non real-time messages are transmitted effectively and guarantee real-time transmission within a deadline. The simulation results show the improvement of real-time performance of periodic and sporadic data at the same time.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.925-926
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• 2006

In the multi-agent system for a single task, the action selection can be made for the real-time environment by using the global coordination space, global coordination graph and MAX-PLUS algorithm. However, there are some difficulties in multi-agent system for multi-tasking. In this paper, a real-time decision making method is suggested by using coordination space, coordination graph and dynamic coordinated state of multi-agent system including many agents and multiple tasks. Specifically, we propose locally dynamic coordinated state to effectively use MAX-PLUS algorithm for multiple tasks completion. Our technique is shown to be valid in the box pushing simulation of a multi-agent system.

• Proceedings of the Korea Society for Simulation Conference
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• 2000.11a
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• pp.165-173
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• 2000

Analytic models have been developed to solve integrated production-distribution problems in supply chain management (SCM). As one of major constraints in analytic models, capacity, which is the total operation time in this paper has mostly been known or disregarded assuming infinite capacity. Also, as major factors, machine processing time to fabricate or assemble a part or product at a certain machine center in production system and vehicle processing time to deliver a product to a customer by a certain vehicle in distribution system have been fixed and regarded as a static factor, But in the real systems significant differences exit between capacity and the required time to achieve the production-distribution plan and between processing time and consumed time to process a part or product. In this paper, capacity and processing times in the analytic model are considered as dynamic factors and adjusted by the results from independently developed simulation model, which includes general production-distribution characteristics. Through experiments, we obtain the more realistic solutions reflecting stochastic natures by performing the iterative analytic-simulation procedure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.5
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• pp.969-975
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• 2002

Visual effects are important cues for providing occupants with virtual reality in a vehicle simulator which imitates real driving. The viewpoint of an occupant is sensitively dependent upon the occupant's posture, therefore, the total human body motion must be considered in a graphic simulator. A real-time simulation is required for the dynamic analysis of complex human body motion. This study attempts to apply a neural network to the motion analysis in various driving situations. A full car of medium-sized vehicles was selected and modeled, and then analyzed using ADAMS in such driving conditions as bump-pass and lane-change for acquiring the accelerations of chassis of the vehicle model. A hybrid III 50%ile adult male dummy model was selected and modeled in an ellipsoid model. Multibody system analysis software, MADYMO, was used in the motion analysis of an occupant model in the seated position under the acceleration field of the vehicle model. Acceleration data of the head were collected as inputs to the viewpoint movement. Based on these data, a back-propagation neural network was composed to perform the real-time analysis of occupant motions under specified driving conditions and validated output of the composed neural network with MADYMO result in arbitrary driving scenario.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3361-3377
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• 2014

Synchronous computing models provided by real-time synchrony protocols, such as TTA [1] and PALS [2], greatly simplify the design, implementation, and verification of real-time distributed systems. However, their application to real systems has been limited since their assumptions on underlying systems are hard to satisfy. In particular, most previous real-time synchrony protocols hypothesize the existence of underlying fault tolerant real-time networks. This, however, might not be true in most soft real-time applications. In this paper, we propose a practical approach to a synchrony protocol, called Quality-Aware PALS (qPALS), which provides the benefits of a synchronous computing model in environments where no fault-tolerant real-time network is available. qPALS supports two flexible global synchronization protocols: one tailored for the performance and the other for the correctness of synchronization. Hence, applications can make a negotiation flexibly between performance and correctness. In qPALS, the Quality-of-Service (QoS) on synchronization and consistency is specified in a probabilistic manner, and the specified QoS is supported under dynamic and unpredictable network environments via a control-theoretic approach. Our simulation results show that qPALS supports highly reliable synchronization for critical events while still supporting the efficiency and performance even when the underlying network is not stable.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.759-763
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.