• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.179-186
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• 2006

A user interface that connects a user to intelligent robots needs to be designed for executing them efficiently. In this paper, it is analyzed how to organize a mobile terminal based user interface according to the function and level of autonomy of intelligent robots and the user interface of PDA (Personal Digital Assistant) and smart phone is developed for controlling intelligent robots remotely. In the image-based user interface, a user can see the motion of a robot directly and control the robot. In the map-based interface, the quantity of transmission information is reduced and therefore a user can control the robot with a small delay of transmission time.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.163-171
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• 2023

The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

• Journal of the Society of Disaster Information
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• v.10 no.1
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• pp.105-115
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• 2014

In this research, we developed video analytic algorithms to detect water-level automatically and a system for proactive alarming using intelligent CCTV cameras. We applied these algorithms and a system to test-beds and verified for practical use. We made camera-selection policies and operation plans to keep the detection accuracy high and to optimize the suitability for the ever-changing weather condition, while the environmental factors such as camera shaking and weather condition can affect to detection accuracy. The estimation result of algorithms showed 90% detection accuracy for all CCTV camera types. For water level detection, NIR camera performed great. NIR camera performed over 95% accuracy in day or night, suitable in natural weather condition such as shaking condition, fog, and low light, needs similar installment skills with common cameras, and spends only 15% high cost. As a result, we practically tested water level detection algorithms and operation system based on intelligent CCTV camera. Furthermore, we expect the positive evidences when it is applied for public use.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.05a
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• pp.415-417
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• 2005

In this paper, we propose a intelligent controller design method for the water level control of the power plant drum in the form of nonminimum phase system. The proposed method is based on T. Takagi and M. Sugeno's fuzzy model. And we illustrate the improved characteristics as the simulation results, comparing with the conventional the PID and LQ controller design method

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.199-202
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• 2006

We propose some properties of fuzzy p-value and fuzzy significance level to the test statistics for the fuzzy hypotheses testing. Appling the principle of agreement index, we suggest two method for fuzzy hypothesis testing by fuzzy rejection region and fuzzy p-value with fuzzy hypothesis $H_{f,0}$.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.385-388
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• 2004

The present paper establish the improved version of central limit theorem for sums of level-continuous fuzzy random variables as a generalization of central limit theorem for sums of independent and identically distributed random sets.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.852-856
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• 2004

The present paper establishes a necessary and sufficient condition for weak convergence for weighted sums of compactly uniformly integrable level-continuous fuzzy random variables as a generalization of weak laws of large numbers for sums of fuzzy random variables.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.52-55
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• 2001

퍼지 그래프는 그래프에 대한 정점들과 간선들의 소속정도를 표현할 수 있도록 일반 그래프를 확장한 그래프이다. 그러나 기준 퍼지 그래프는 명확한 정점들의 집합 위에서의 관계만을 표시할 수 있다. 본 논문에서는 퍼지 집합간의 관계를 표시할 수 있도록 확장된 레벨-2 퍼지 그래프를 제안한다. 본 논문에서는 레벨-2 퍼지 그래프를 정의하고 레벨-2 퍼지 그래프에서 수정되어야 하는 연산들과 레벨-2 퍼지 그래프의 특성에 대하여 소개한다. 제안된 레벨-2 퍼지 그래프는 퍼지 데이터 비교 및 퍼지 클러스터링 분야에 적용될 수 있다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.191-194
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• 2001

The ozone forecasting systems have many problems because the mechanism of the ozone concentration is highly complex, nonlinear, and nonstationary. Also, the results of prediction are not a good performance so far, especially in the high-level ozone concentration. This paper describes the modeling method of the ozone prediction system using neuro-fuzzy approaches and fuzzy clustering. The dynamic polynomial neural network (DPNN) based upon a typical algorithm of GMDH (group method of data handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system.