• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.398-403
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• 2009

The recent trend of logistics demands for improved monitoring system of the inside of containers including current temperature and other environmental conditions. This paper presents an information processing technique with fuzzy logic that recognizes the current situations inside the target container and can be implemented on intelligent container systems. The ZigBee modules are used to collect information such as temperature, humidity, and shock inside the container in ubiquitous environment. The information processing system using fuzzy logic and the InTouch, one of SCADA(Supervisory Control and Data Acquisition) systems, is implemented to monitor the inside of the container and predict the emergency state.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.479-485
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• 2005

Recently, computing technology requires intelligent system structures for context-awareness in ubiquitous computing environment. An intelligent system for context-awareness is based on agents, and need sensor information to recognize users and frames to support service. Therefore, this paper proposes the structure of 3-tier context-awareness processing server/client that can connect dynamically with each sensor and service, and support various context stably The structure of a proposal system is composed of a client class that recognizes uses' context information, a server class that processes realized context information by an application processing agent, and a management server that manages these two classes. Also, in this structure users information is composed of dynamic profile to support exquisite service.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.30-33
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• 2001

The number of hidden neurons of the feed-forward neural networks is generally decided on the basis of experience. The method usually results in the lack or redundancy of hidden neurons, and causes the shortage of capacity for storing information of learning overmuch. This research proposes a new method for optimizing the number of hidden neurons bases on information entropy, Firstly, an initial neural network with enough hidden neurons should be trained by a set of training samples. Second, the activation values of hidden neurons should be calculated by inputting the training samples that can be identified correctly by the trained neural network. Third, all kinds of partitions should be tried and its information gain should be calculated, and then a decision-tree correctly dividing the whole sample space can be constructed. Finally, the important and related hidden neurons that are included in the tree can be found by searching the whole tree, and other redundant hidden neurons can be deleted. Thus, the number of hidden neurons can be decided. In the case of building a neural network with the best number of hidden units for tea quality evaluation, the proposed method is applied. And the result shows that the method is effective

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.589-598
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• 2002

The color measuring/matching expert system is implemented with a new color measuring method that combines intelligent algorithms with image processing techniques. Color measuring part of the proposed system preprocesses the scanned original color input images to eliminate their distorted components by means of the image histogram technique of image pixels, and then extracts RGB(Red, Green, Blue)data among color information from preprocessed color input images. If the extracted RGB color data does not exist on the matching recipe databases, we can measure the colors for the user who want to implement the model that can search the rules for the color mixing information, using the intelligent modeling techniques such as fuzzy inference system and adaptive neuro-fuzzy inference system. Color matching part can easily choose images close to the original color for the user by comparing information of preprocessed color real input images with data-based measuring recipe information of the expert, from the viewpoint of the delta Eformula used in practical process.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.494-500
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• 2004

The purpose of this thesis is to know and understand the user requirements to provide with intelligent railway information service in response to the Ubiquitous environment. The railroad specially has a disadvantage of door-to-door service, however by using the information and communication techniques, we can provide the passengers who are using the intermodal transportation means with the realtime information, therefore we can overcome the above disadvantage. To deduce the passenger's needs for providing the future-type railway information service, we introduce the results of the questionnaire. In chapter 2, we studies on the concepts of intelligent railway information service, and in chapter 3, we investigate the cases of Japan and China, and in chapter 4, we study the passager's satisfaction by the questionnaire concerning the railway information service and suggest the needs for information offering.

• Annual Conference of KIPS
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• 2002.11a
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• pp.311-314
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• 2002

The dynamic nature of the World Wide Web challenges Information Retrieval System to find information relevant and recent. Intelligent agents can complement the power of search engines to deal with this challenge. In this paper, we explain in manner of building Information Retrieval System based on intelligent agent technology. We present a tool called Websearcher. It was performed in Java environment. The object-oriented nature of Java and built-in facilities for multi-thread decreased our implementation effort. A modular software design makes it easy to configure the system for various experiments.

• Journal of the Korean Society for information Management
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• v.9 no.1
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• pp.166-166
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• 1992

The purpose of this study is to review the c-oncept and background of intelligent information systemwhlch will be fixed on the next generation's information system and to describe the object orientationsystem. expert system, and hypermedia which are thc core technolclgies in the design of intelligentinformation system. Furthtmnort., intelligent information systems which are developed using thesetechnologies in the fields of library anti information science, and the future prospect on the intc~lligentinformation system are described In detail.

• Journal of IKEEE
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• v.28 no.3
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• pp.310-320
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• 2024

This article describes the 5G-NR-V2X system and its communication performance methodology. We present a system that can develop and verify the performance of self-driving services in a real road test environment using OBU and RSU for 5G-NR-V2X communication (level 4 or higher). This system ensures ultra-high speed (150Mbps or more), ultra-low latency (3ms or less), and high reliability (99.99 percent) in communication robustness, even under malicious conditions. The 5G-NR-V2X system and performance analysis method proposed in this paper are anticipated to aid in the development of V2X communication technologies that are ultrafast, ultralow-delay, and high-confidence. In addition, it is expected that the services validated by the suggested performance analysis technique will enhance technological competitiveness in the road, transportation, logistics, and commerce industries.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.1023-1026
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• 2005

In the ubiquitous computing environment, an intelligent vehicle is defined as a sensor node with a capability of intelligence and communication in a wire and wireless network space. To make it real, a lot of problems should be addressed in the aspect of vehicle mobility, in-vehicle communication, common service platform and the connection of heterogeneous networks to provide a driver with several intelligent information services beyond the time and space. In this paper, we present an intelligent information system for managing in-vehicle sensor network and a vehicle gateway for connecting the external networks. The in-vehicle sensor network connected with several sensor nodes is used to collect sensor data and control the vehicle based on CAN protocol. Each sensor node is equipped with a reusable modular node architecture, which contains a common CAN stack, a message manager and an event handler. The vehicle gateway makes vehicle control and diagnosis from a remote host possible by connecting the in-vehicle sensor network with an external network. Specifically, it gives an access to the external mobile communication network such as CDMA. Some experiments was made to find out how long it takes to communicate between a vehicle's intelligent information system and an external server in the various environment. The results show that the average response time amounts to 776ms at fixed place, 707ms at rural area and 910ms at urban area.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2038-2057
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• 2017

Gaussian learning is a new technology in the computational intelligence area. However, this technology weakens the learning ability of a particle swarm and achieves a lack of diversity. Thus, this paper proposes a vector Gaussian learning strategy and presents an effective approach, named particle swarm optimization based on vector Gaussian learning. The experiments show that the algorithm is more close to the optimal solution and the better search efficiency after we use vector Gaussian learning strategy. The strategy adopts vector Gaussian learning to generate the Gaussian solution of a swarm's optimal location, increases the learning ability of the swarm's optimal location, and maintains the diversity of the swarm. The method divides the states into normal and premature states by analyzing the state threshold of the swarm. If the swarm is in the premature category, the algorithm adopts an inertia weight strategy that decreases linearly in addition to vector Gaussian learning; otherwise, it uses a fixed inertia weight strategy. Experiments are conducted on eight well-known benchmark functions to verify the performance of the new approach. The results demonstrate promising performance of the new method in terms of convergence velocity and precision, with an improved ability to escape from a local optimum.