• Industrial Engineering and Management Systems
• /
• v.8 no.3
• /
• pp.181-193
• /
• 2009

This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

• The Journal of Information Systems
• /
• v.32 no.1
• /
• pp.109-146
• /
• 2023

Purpose With Intelligent public service (IPS), it is possible to automate the quality of civil affairs, provide customized services for citizens, and provide timely public services. However, empirical studies on factors for the successful use of IPS are still insufficient. Hence, the purpose of this study is to empirically analyze the factors that affect the success of IPS with classification function. ISSM (Information System Success Model) is considered as the underlying research model, and how the algorithm quality, data quality, and environmental quality of the discrimination system affect the relationship between utilization intentions is analyzed. Design/methodology/approach In this study, a survey was conducted targeting users using IPS. After giving them a preliminary explanation of the intelligent public service centered on the discrimination system, they briefly experienced two types of IPS currently being used in the public sector. Structural model analysis was conducted using Smart-PLS 4.0 with a total of 415 valid samples. Findings First, it was confirmed that algorithm quality and data quality had a significant positive (+) effect on information quality and system quality. Second, it was confirmed that information quality, system quality, and environmental quality had a positive (+) effect on the use of IPS. Thirdly, it was confirmed that the use of IPS had a positive (+) effect on the net profit for the use of IPS. In addition, the moderating effect of the degree of knowledge on AI, the perceived accuracy of discriminative experience and IPS, and the user was analyzed. The results suggest that ISSM and TOE framework can expand the understanding of the success of IPS.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.9 no.3
• /
• pp.67-78
• /
• 2013

In this paper, We proposed an development method of application framework for using the precision time protocol(PTP) based on physical layer devices to synchronize clocks across a network with IEEE1588 capable devices. The algorithm was not designed as a complete solution across all conditions, but is intended to show the feasibility of such a for the PTP(Precision Time Protocol) based on time synchronization of heterogeneous network between devices that support in IEEE 1588 Standard application framework. With synchronization messages per second, the system was able to accurately synchronize across a single heavily loaded switch. we describes a method of synchronization that provides much more accurate synchronization in systems with larger networks. In this paper, using the IEEE 1588 PTP support for object-oriented modeling techniques through the 'application framework development Development(AFDM)' is proposed. The method described attempts to detect minimum delays, or precision packet probe and packet metrics. The method also takes advantage of the Tablet PC(Primary to Secondary) clock control mechanism to separately control clock rate and time corrections, minimizing overshoot or wild swings in the accuracy of the clock. We verifying the performance of PTP Systems through experiments that proposed method.

• The Journal of Korea Robotics Society
• /
• v.2 no.4
• /
• pp.297-303
• /
• 2007

In this paper, we discuss a service to give alarm in the case of emergency for the old and the weak by human behavior recognition in Intelligent Space. Our Intelligent Space consists of mobile robots, sensors and agents. And these components are connected to network framework. Agent analyzes data acquired from networked sensors and determines task of robots and a space to provide a service for humans. In our emergency alarm service, human behavior recognition service module analyzes accelerometer data obtained from body-attached human behavior sensing platform, and classifies into four basic human behavior such as walking, running, sitting and falling-down. For the old and the weak, falling-down behavior may bring about dangerous situations. On such an occasion, agent executes emergency alarm service immediately. And then a selected mobile robot approaches fallen person and sends images of the person to guardians. In this paper, we set up a scenario to verify the emergency alarm service in Intelligent Space, and show feasibility of the service from our simulation experiments.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2001.01a
• /
• pp.186-191
• /
• 2001

Mobile agent technologies are getting popular as means for accessing network resources efficiently. In order for mobile agents to be accepted as a reliable technology for applications such as e-commerce, a proper framework for mobile database should be established. In this paper, we first discuss weak points of current mobile computing systems that mostly result from the limitations of current mobile computing technology including frequent disconnection, limited battery capacity, low-bandwidth communication and reduced storage capacity. These weak points also have become the cause of transaction problem where mobile devices issue transactions. In order to eliminate this transaction problem in the mobile environment, we propose a mobile database framework, Proxyne, which is based on the proxy and SyncML.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 1999.03a
• /
• pp.125-133
• /
• 1999

The objective of knowledge discovery and data mining lies in the generation of useful insights from a store of data. This paper presents a framework for knowledge mining to provide a systematic approach to the selection and deployment of tools for automated learning. Every methodology has its strengths and limitations. Consequently, a multistrategy approach may be required to take advantage of the strengths of disparate technique while circumventing their individual limitations. For concreteness, the general framework for data mining in marketing is examined in the context of developing agents for optimizing a supply chain network.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.30 no.1
• /
• pp.75-94
• /
• 2005

Research in the decision sciences has continued to develop a variety of mathematical models as well as software tools supporting corporate decision-making. Yet. in spite of their potential usefulness, the models are little used in real-world decision making since the model solution processes are too complex for ordinary users to get accustomed. This paper proposes an intelligent and flexible model-solver integration framework that enables the user to solve decision problems using multiple models and solvers without having precise knowledge of the model-solution processes. Specifically, for intuitive model-solution, the framework enables a decision support system to suggest the compatible solvers of a model autonomously without direct user intervention and to solve the model by matching the model and solver parameters intelligently without any serious conflicts. Thus, the framework would improve the productivity of institutional model solving tasks by relieving the user from the burden of leaning model and solver semantics requiring considerable time and efforts.

• Proceedings of the Korean Information Science Society Conference
• /
• 2003.10b
• /
• pp.253-255
• /
• 2003

We address an integrated multimedia framework based on a software agent platform for context-aware multimedia computing. We adopt the FIPA (Foundation for Intelligent Physical Agents) platform which provides agent communications and management mechanisms. In order to express context information, we use MPEG-21 metadata for describing user characteristics and usage environment. We encapsulate such context information as a FIPA message to be delivered between agents. Based on context information, appropriate multimedia content delivery becomes possible. We present our system implementation with a use case scenario and show that our proposed framework is effective for context-aware multimedia computing so that personalization of multimedia consumption can be possible.

• Structural Engineering and Mechanics
• /
• v.88 no.6
• /
• pp.535-549
• /
• 2023

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

• 한국ITS학회:학술대회논문집
• /
• 2010.05a
• /
• pp.61-65
• /
• 2010