• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.31-36
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• 1998

This paper proposes a method to select essential elements in a human evaluation model using the Choquet integral based on fuzzy measures and applies the model to the evaluation of human interface. Three kinds of concepts, Increment Degree, average of Increment Degree, Necessity coefficient, are defined. The proposed method selects essential elements by the use of the Relative necessity coefficient. The proposed method is applied to the analysis of human interface. In the experiment, (1) a warning sound, (2)a color vision, (3) the size of working area, (4) a response of confirmation, are considered as human interface elements. subjects answer the questionnarie after the experiment. From the data of questionnaire, fuzzy measures are identified and are applied to the proposed model. effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnarie.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1187-1190
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• 1993

The problem of the optimization of fuzzy relational models for dealing with (non-fuzzy) numerical data is investigated. In this context, interfaces optimization assumes particular importance, becoming a determinant factor in what concerns the overall model performance. Considering this, several scenarios for building fuzzy relational models are presented. These are: (i) optimizing I/O interfaces in advance (independently from the linguistic part of the model); (ii) optimizing I/O interfaces in advance and allowing that their optimized parameters may change during the learning of the linguistic part of the model; (iii) build simultaneously both interfaces and the linguistic subsystem; and (iv) build simultaneously both linguistic subsystem and interfaces, now subject to semantic integrity constraints. As linguistic subsystems, both a basic type and an extended versions of fuzzy relation equations are exploited in each one of these scenarios. A comparative analysis of the differ nt approaches is summarized.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.873-876
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• 1993

A fuzzy controller designed by mini-max-gravity(MMG) method is essentially nonlinear with respect to the controller's input and output relationship, and stability analysis is thus needed to construct a stable control system. This paper deals with a design method of a position-type MMG fuzzy controller stable in a sense of Lyapunov when considered is a single-input-single-output linear, stable plant. We first introduce a method to construct a Laypunov function by using an eigen-value of A matrix of the linear, stable plant dynamics and then we derive an asymtotic stability condition in terms of scale factors for fuzzy state variables and controller gain. The stability condition is found reasonably practical through comparing the theoretical stability region with that obtained from simulations.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.55 no.2
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• pp.103-109
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• 2006

In this paper, the detection scheme of the spatial coordinates based on stereo camera for a intelligent path planning of an automatic mobile robot is proposed. In the proposed system, face area of a moving person is detected from a left image among the stereo image pairs by using the YCbCr color model and its center coordinates are computed by using the centroid method and then using these data, the stereo camera embedded on the mobile robot can be controlled for tracking the moving target in real-time. Moreover, using the disparity mad obtained from the left and right images captured by the tracking-controlled stereo camera system and the perspective transformation between a 3-D scene. and an image plane, depth information can be detected. Finally, based-on the analysis of these calculated coordinates, a mobile robot system is derived as a intelligent path planning and a estimation.

• Asia pacific journal of information systems
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• v.9 no.4
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• pp.41-67
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• 1999

ERP is now one of the prevailing applications for integrated information systems, So far, the conventional ERPs lack how to manage knowledge of making decisions, that is one of the important goal of ERP. This gives a motivation on adding decision support capabilities to the ERPs: active advice for business analysis, evaluation and control. In this paper, we proposed an agent-based intelligent ERP that is operated on the Internet. In special, knowledge of economic value added (EVA) is explicitly acquired as a set of data, models and methodologies, A new knowledge representation format, MIF, is suggested to show the communication mechanism between agents, The agent-based knowledge processing is adopted to deliver intelligence on the Internet.

• Journal of Platform Technology
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• v.6 no.4
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• pp.11-17
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• 2018

In the smart intelligence information society, there is a possibility that the social dysfunction such as the personal information protection issue and the risk to the electronic surveillance society may be highlighted. In this paper, we refer to various categories and classify electronic surveillance into audio surveillance, visual surveillance, location surveillance, biometric information surveillance, and data surveillance. In order to respond to new electronic surveillance in the intelligent information society, it requires a change of perception that is different from that of the past. This starts with the importance of digital privacy and results in the right to self-determination of personal information. Therefore, in order to preemptively respond to the dysfunctions that may arise in the intelligent information society, it is necessary to further raise the awareness of the civil society to protect information human rights.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.333-336
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• 2020

AI-powered robot news is drawing attention as artificial intelligence technology is fully spread in the news distribution field. Robot news still has many technical and ethical problems, but academic research on this is insufficient. This study analyzes the issue of robot writing in artificial intelligent based robot journalism industry using SWOT analysis. As a result, the advantages of big data processes, accurate information gathering, high efficiency and disadvantages such as lack of independent arguments and lack of evidence and opportunities for technical development, government support, academic development, and industrial applications, and threats such as uncritical acceptance and lack of talent have been found. This study suggests three future-oriented directions, such as human-machine collaboration, intelligent news, and chat-bot, through previous studies on the development direction of robot journalism-based article writing.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.360-365
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• 2014

There are many types of advanced devices for weather prediction process such as weather radar, satellite, radiosonde, and other weather observation devices. Among them, the weather radar is an essential device for weather forecasting because the radar has many advantages like wide observation area, high spatial and time resolution, and so on. In order to analyze the weather radar observation result, we should know the inside structure and data. Some non-precipitation echoes exist inside of the observed radar data. And these echoes affect decreased accuracy of weather forecasting. Therefore, this paper suggests a method that could remove line-shaped non-precipitation echo from raw radar data. The line-shaped echoes are distinguished from the raw radar data and extracted their own features. These extracted data pairs are used as learning data for naive bayesian classifier. After the learning process, the constructed naive bayesian classifier is applied to real case that includes not only line-shaped echo but also other precipitation echoes. From the experiments, we confirm that the conclusion that suggested naive bayesian classifier could distinguish line-shaped echo effectively.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.3
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• pp.226-230
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• 2009

Intelligent Tutoring System (ITS) is a procedure of analyzing collected data for teaming, making a strategy and performing adequate service for learners. To perform suitable service for learners, modeling is the first step to collect data from the process of their learning. The model, however, cannot be authentic if collected data can contain learners' inconsistent behaviors or unpredictable learning inclination. This study focused on how to sort normal and abnormal data by analyzing collected data from learners through visualization. A model has been set up to assort unusual data from collected learner's data by using DOLLS-HI which makes possible to diagnose learner's learning propensity based on housing interior learning contents in the experiment. The created model has been confirmed its improved reliability comparing to previous one.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.789-792
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• 2004

In various fields as web mining, bioinformatics, statistical data analysis, and so forth, very diversely missing values are found. These values make training data to be sparse. Largely, the missing values are replaced by predicted values using mean and mode. We can used the advanced missing value imputation methods as conditional mean, tree method, and Markov Chain Monte Carlo algorithm. But general imputation models have the property that their predictive accuracy is decreased according to increase the ratio of missing in training data. Moreover the number of available imputations is limited by increasing missing ratio. To settle this problem, we proposed statistical learning theory to preprocess for missing values. Our statistical learning theory is the support vector regression by Vapnik. The proposed method can be applied to sparsely training data. We verified the performance of our model using the data sets from UCI machine learning repository.