• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.1
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• pp.80-91
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• 2022

This study is to provide an prediction model of setting time of super retarding mortar based on equivalent age method under various super retarding agent contents, curing temperature, and water-binder ratio (W/B). An equation for predicting setting time using maturity was proposed. Test results indicated that the setting time can be predicted by determining the curing temperature, W/B, and super retarding agent contents and substituting it into the equation proposed in this study. The coefficient of determination of the equation is 0.9 or more, and the reliability was confirmed through the F-test. Finally, using the equation proposed in this paper, reasonable quality control is possible regarding the setting of super retarding concrete in practice.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.113-118
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• 2005

Softswitch is the core BcN equipment which voice and multimedia switching based on the IP Technologies. It is designed to replace the Class 5(local Exchange) and Class 4(Toll Exchange) switch based on the circuit wired and wireless switching network technologies. Softswitch gets its name because typically it is a software based solution implemented on general purpose computers/servers. While the traditional PSTN switches are rely on dedicated facilities for T and S inter-connection and are designed primarily for voice communications. Packet based Softswitch is divided the control of call and bearer, very different from Public telephone network. Sometimes Call Agent or Media Gateway Controller, a key component in the VoIP solution, is also called Softswitch. This paper will suggest the software architecture of softswitch for performance in call processing part, also suggest the session management model to cover call setup latency.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.200-209
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• 2006

Load building is an important step to make the delivery supply chain efficient. We present a family of load makeup algorithms using market based control strategy, named LoadMarket, in order to build efficient loads where each load consists of a certain number of finished products having destinations. LoadMarket adopts Clark-Wright algorithm for generating initial endowment for Load Traders who cooperate to minimize either total travel distance or the variance with respect to the travel distances of loads by means of the spot market or double-sided auction market mechanism. The efficiency of the LoadMarket algorithms is illustrated using simulation based experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.174-174
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• 2000

Q-learning, based on discrete state and action space, is a most widely used reinforcement Learning. However, this requires a lot of memory and much time for learning all actions of each state when it is applied to a real mobile robot navigation using continuous state and action space Region-based Q-learning is a reinforcement learning method that estimates action values of real state by using triangular-type action distribution model and relationship with its neighboring state which was defined and learned before. This paper proposes a new Region-based Q-learning which uses a reward assigned only when the agent reached the target, and get out of the Local optimal path with adjustment of random action rate. If this is applied to mobile robot navigation, less memory can be used and robot can move smoothly, and optimal solution can be learned fast. To show the validity of our method, computer simulations are illusrated.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.226-234
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• 2022

With advances in autonomous vehicles and networked control, there is a growing interest in the consensus control of a multi-agents system to control multi-agents with distributed control beyond the control of a single agent. Since consensus control is a distributed control, it is bound to have delay in a practical system. In addition, it is often difficult to have a very accurate mathematical model for a system. Even though a reinforcement learning (RL) method was developed to deal with these issues, it often experiences slow convergence in the presence of large uncertainties. Thus, we propose a slide RL which combines the sliding mode control with RL to be robust to the uncertainties. The structure of a sliding mode control is introduced to the action in RL while an auxiliary sliding variable is included in the state information. Numerical simulation results show that the slide RL provides comparable performance to the model-based consensus control in the presence of unknown time-varying delay and disturbance while outperforming existing state-of-the-art RL-based consensus algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7B
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• pp.619-631
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• 2006

With the advent of ubiquitous computing environments, it has become increasingly important for applications to take full advantage of context information, such as the user's location, to offer greater services to the user without any explicit request. In this paper, we propose context-aware active services on the basis of CAMUS (Context-Aware Middleware for URC Systems). CAMUS is a middleware for providing context-aware applications with development and execution methodology. Accordingly, the applications developed by CAMUS respond in a timely fashion to contexts. To evaluate, we apply proposed active services to TV application domain. Therefore, we implement and experiment the TV contents recommendation service agent, control service agent and TV task based on CAMUS. The context-aware TV task is to recommend programs and control of TV according to user preference, location and voice commands.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1663-1669
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• 2021

This paper considers the cooperative control problem for multiple leaders and a single follower with interactions. The leaders are controllable, and the follower has interactions with all leaders and is controlled by the interactions. Then, we study the cooperative control problem that achieves the consensus by controlling the leaders. The leaders and the follower are modeled by the single-integrator and the double-integrator, respectively, and it is assumed that the interactions have the nonlinearities. The leaders can estimate the interaction between the follower and exchange the estimated information with neighbors. Then, this paper proposes the consensus-based cooperative control algorithm using the information exchange of the estimated interactions and the virtual velocity variables to achieve the velocity consensus. We analyze the convergence of the agents to the common state based on the Lasalle's Invaraince Principle. Finally, we provide the numerical example to validate the theoretical results.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.5
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• pp.34-45
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• 2000

In this paper, a multiagent fault-tolerant supervisory control methodology is proposed for serial production systems under partial observation. To this end, the idea of multiagent control is incorporated with the fault-tolerant supervisory control of discrete event systems. Especially, the concept of mutual fault-tolerance between cascaded processes is established and the unobservable fault identification utilizing the difference information of the controlled results is investigated. Then the synthesis of agent supervisors is formulated based on the proposed concept. A case study of the fault-propagation control of polypropylene prepolymerization and polymerization processes is provided to illustrate the proposed control policy.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2033-2038
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• 2003

This paper describes an integrated navigation strategy for the autonomous service robot PSR. The PSR is under development at the KIST for service tasks in indoor public environments. The PSR is a multi-functional mobile-manipulator typed agent, which works in daily life. Major advantages of proposed navigation are as follows: 1) Structured control architecture for a systematic integration of various software modules. A Petri net based configuration design enables stable control flow of a robot. 2) A range sensor based generalized scheme of navigation. Any range sensor can be selectively applied using the proposed navigation scheme. 3) No need for modification of environments. (No use of artificial landmarks.) 4) Hybrid approaches combining reactive behavior as well as deliberative planner, and local grid maps as well as global topological maps. A presented experimental result shows that the proposed navigation scheme is useful for mobile service robot in practical applications.