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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Journal DOI :
Korean Institute of Intelligent Systems
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Volume & Issues
Volume 14, Issue 7 - Dec 2004
Volume 14, Issue 6 - Oct 2004
Volume 14, Issue 5 - Aug 2004
Volume 14, Issue 4 - Jul 2004
Volume 14, Issue 2 - Apr 2004
Volume 14, Issue 1 - Feb 2004
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Facial Image Analysis Algorithm for Emotion Recognition
Joo, Y.H. ; Jeong, K.H. ; Kim, M.H. ; Park, J.B. ; Lee, J. ; Cho, Y.J. ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 801~806
DOI : 10.5391/JKIIS.2004.14.7.801
Although the technology for emotion recognition is important one which demanded in various fields, it still remains as the unsolved problem. Especially, it needs to develop the algorithm based on human facial image. In this paper, we propose the facial image analysis algorithm for emotion recognition. The proposed algorithm is composed as the facial image extraction algorithm and the facial component extraction algorithm. In order to have robust performance under various illumination conditions, the fuzzy color filter is proposed in facial image extraction algorithm. In facial component extraction algorithm, the virtual face model is used to give information for high accuracy analysis. Finally, the simulations are given in order to check and evaluate the performance.
Stability Analysis and Proposal of the Simplified Form of a Fuzzy PID Controller with Fixed Parameters
Lee, Byung-Kyul ; Kim, In-Hwan ; Kim, Jong-Hwa ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 807~815
DOI : 10.5391/JKIIS.2004.14.7.807
This paper describes the design principle of a fuzzy PID controller with fixed parameters, proposes the simulified form of a fuzzy PID controller to increase the computational efficiency and analyzes stability of a proposed fuzzy PID controller. After a detailed stability analysis using ‘small gain theorem’, a simple and practical sufficient condition for the BIBO stability of the overall feedback control system is derived. The derived stability condition offers a calculation method to obtain parameters of a fuzzy PID controller from parameters of a stable PID controller. Finally several computer simulations are executed to confirm the effectiveness of the fuzzy PID controller with fixed parameters.
SVM based Clustering Technique for Processing High Dimensional Data
Kim, Man-Sun ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 816~820
DOI : 10.5391/JKIIS.2004.14.7.816
Clustering is a process of dividing similar data objects in data set into clusters and acquiring meaningful information in the data. The main issues related to clustering are the effective clustering of high dimensional data and optimization. This study proposed a method of measuring similarity based on SVM and a new method of calculating the number of clusters in an efficient way. The high dimensional data are mapped to Feature Space ones using kernel functions and then similarity between neighboring clusters is measured. As for created clusters, the desired number of clusters can be got using the value of similarity measured and the value of Δd. In order to verify the proposed methods, the author used data of six UCI Machine Learning Repositories and obtained the presented number of clusters as well as improved cohesiveness compared to the results of previous researches.
Robust Real-time Face Detection Scheme on Various illumination Conditions
Kim, Soo-Hyun ; Han, Young-Joon ; Cha, Hyung-Tai ; Hahn, Hern-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 821~829
DOI : 10.5391/JKIIS.2004.14.7.821
A face recognition has been used for verifying and authorizing valid users, but its applications have been restricted according to lighting conditions. In order to minimizing the restricted conditions, this paper proposes a new algorithm of detecting the face from the input image obtained under the irregular lighting condition. First, the proposed algorithm extracts an edge difference image from the input image where a skin color and a face contour are disappeared due to the background color or the lighting direction. In the next step, it extracts a face region using the histogram of the edge difference image and the intensity information. Using the intensity information, the face region is divided into the horizontal regions with feasible facial features. The each of horizontal regions is classified as three groups with the facial features(including eye, nose, and mouth) and the facial features are extracted using empirical properties of the facial features. Only when the facial features satisfy their topological rules, the face region is considered as a face. It has been proved by the experiments that the proposed algorithm can detect faces even when the large portion of face contour is lost due to the inadequate lighting condition or the image background color is similar to the skin color.
A Fault Diagnosis Based on Multilayer/ART2 Neural Networks
Lee, In-Soo ; Yu, Du-Hyoung ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 830~837
DOI : 10.5391/JKIIS.2004.14.7.830
Neural networks-based fault diagnosis algorithm to detect and isolate faults in the nonlinear systems is proposed. In the proposed method, the fault is detected when the errors between the system output and the multilayer neural network-based nominal model output cross a Predetermined threshold. Once a fault in the system is detected, the system outputs are transferred to the fault classifier by nultilayer/ART2 NN (adaptive resonance theory 2 neural network) for fault isolation. From the computer simulation results, it is verified that the proposed fault diagonal method can be performed successfully to detect and isolate faults in a nonlinear system.
A New Snake Model for Tracking a Moving Target Using a Mobile Robot
Han, Young-Joon ; Hahn, Hern-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 838~846
DOI : 10.5391/JKIIS.2004.14.7.838
In the case where both a camera and a target are moving at the same time, the image background is successively changed, and the overlap with other moving objects is apt to be generated. The snake algorithms have been variously used in tracking the object, but it is difficult to be applied in the excessive overlap with other objects and the large bias between the snake and the target. To solve this problem, this paper presents an extended snake model. It includes an additional energy function which considers the temporal variation rate of the snake's area and a SSD algorithm which generates the template adaptive to the snake detected in the previous frame. The new energy function prevents the snake from over-shrinking or stretching and the SSD algorithm with adaptively changing template allows the prediction of the target's position in the next frame. The experimental results have shown that the proposed algorithm successfully tracks the target even when the target is temporarily occluded by other objects.
Nonlinear Approximations Using Modified Mixture Density Networks
Cho, Won-Hee ; Park, Joo-Young ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 847~851
DOI : 10.5391/JKIIS.2004.14.7.847
In the original mixture density network(MDN), which was introduced by Bishop and Nabney, the parameters of the conditional probability density function are represented by the output vector of a single multi-layer perceptron. Among the recent modification of the MDNs, there is the so-called modified mixture density network, in which each of the priors, conditional means, and covariances is represented via an independent multi-layer perceptron. In this paper, we consider a further simplification of the modified MDN, in which the conditional means are linear with respect to the input variable together with the development of the MATLAB program for the simplification. In this paper, we first briefly review the original mixture density network, then we also review the modified mixture density network in which independent multi-layer perceptrons play an important role in the learning for the parameters of the conditional probability, and finally present a further modification so that the conditional means are linear in the input. The applicability of the presented method is shown via an illustrative simulation example.
Weak convergence for weighted sums of level-continuous fuzzy random variables
Kim, Yun-Kyong ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 852~856
DOI : 10.5391/JKIIS.2004.14.7.852
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.
Fuzzy Control of Elevator Speed Pattern
Ahn, Tae-Chon ; Kang, Jin-Hyun ; Kang, Doo-Young ; Yoon, Yang-Woong ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 857~864
DOI : 10.5391/JKIIS.2004.14.7.857
In this paper, a new speed pattern generation method is proposed to offer various speed patterns for the traffic changers, with the comfortable driving and the rapid transportation speed that are two important factors to determine elevator speed pattern. To reduce the speed shift impulse, acceleration and deceleration times are appropriately adjusted to the elevator system when start and stop. In order to improve transportation capability, the jerk is also adjusted to the traffic change. Using fuzzy inference system with 2 input variables and 1 output, the elevator system controls precisely, with the proposed speed pattern.
Tracking Methods of User Position for Privacy Problems in Location Based Service
Ra, Hyuk-Ju ; Choi, Woo-Kyung ; Jeon, Hong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 865~870
DOI : 10.5391/JKIIS.2004.14.7.865
Development of new information and traffic technology causes fast-growing in the field of information-based system. At recent, development of LBS(Location Based Service) makes a remarkable growth of industry as GPS(Global Positioning System) becomes wide-spread and location information becomes more important. However, there is a problem like infringement of privacy when location information is used improperly［1］. In this paper, LBS platform is proposed in order to prevent infringement of privacy. To implement, we classify user path as pattern in a zone of user life. Thereupon, location information is provided according to user' specific situation.
A Study on the Intelligent 3D Foot Scanning System
Kim, Young-Tak ; Park, Ju-Won ; Tack, Han-Ho ; Lee, Sang-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 871~877
DOI : 10.5391/JKIIS.2004.14.7.871
In this paper, for manufacturing a custom-made shoes, shape of foot acquired three-dimensional measurement device which makes shoe-last data for needing a custom-made shoes is founded on artificial intelligence technique and it shows method restoring to the original shape in optimized state. the developed system for this study is based on PC which uses existing three dimensional measurement method. And it gains shoe-last and data of foot shape going through 8 CCD(Charge Coupled Device) Which equipped top and bottom, right and left sides and 4 lasers which also equipped both sides and upper and lower sides. The acquired data are processed image processing algorithm using artificial intelligence technique. And result of data management is better quality of removing noise than other system not using artificial intelligence technique and it can simplify post-processing. So, this paper is constituted hardware and software system and it used neural network for determining threshold value, when input image on pre-processing step is being stage of image binarization and present that results.
Detection and Diagnosis of Induction Motor Using Conditional FCM and Radial Basis Function Network
Kim, Sung-Suk ; Lee, Dae-Jeong ; Park, Jang-Hwan ; Ryu, Jeong-Woong ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 878~882
DOI : 10.5391/JKIIS.2004.14.7.878
In this paper, we propose a hierarchical hybrid neural network for detecting faults of induction motor. Implementing the classifier based on the input and output data, we apply appropriate transform and classification method at each step. In the proposed method, after obtaining the current of state of motor for each period, we transform it by Principle Component Analysis(PCA) to reduce its dimension. Before the training process, we use the conditional Fuzzy C-means(FCM) for obtaining the initial parameters of neural network for more effective learning procedure. From the various simulations, we find that the proposed method shows better performance to detect and diagnosis of induction motor and compare than other methods.
Obstacle Avoidance Method in the Chaotic Unmanned Aerial Vehicle
Bae, Young-Chul ; Kim, Yi-Gon ; Kim, Chun-Suk ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 883~888
DOI : 10.5391/JKIIS.2004.14.7.883
In this paper, we propose a method to avoid obstacles that have unstable limit cycles in a chaos trajectory surface. We assume all obstacles in the chaos trajectory surface have a Van der Pol equation with an unstable limit cycle. When a chaos UAVs meet an obstacle in an Arnold equation, Chua's equation and hyper-chaos equation trajectory the obstacle reflects the UAV( Unmanned Aerial Vehicle).
A Kernel based Possibilistic Approach for Clustering and Image Segmentation
Choi, Kil-Soo ; Choi, Byung-In ; Rhee, Chung-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 889~894
DOI : 10.5391/JKIIS.2004.14.7.889
The fuzzy kernel c-means (FKCM) algorithm, which uses a kernel function, can obtain more desirable clustering results than fuzzy c-means (FCM) for not only spherical data but also non-spherical data. However, it can be sensitive to noise as in the FCM algorithm. In this paper, a kernel function is applied to the possibilistic c-means (PCM) algorithm and is shown to be robust for data with additive noise. Several experimental results show that the proposed kernel possibilistic c-means (KPCM) algorithm out performs the FKCM algorithm for general data with additive noise.
Intelligent Spam-mail Filtering Based on Textual Information and Hyperlinks
Kang, Sin-Jae ; Kim, Jong-Wan ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 895~901
DOI : 10.5391/JKIIS.2004.14.7.895
This paper describes a two-phase intelligent method for filtering spam mail based on textual information and hyperlinks. Scince the body of spam mail has little text information, it provides insufficient hints to distinguish spam mails from legitimate mails. To resolve this problem, we follows hyperlinks contained in the email body, fetches contents of a remote webpage, and extracts hints (i.e., features) from original email body and fetched webpages. We divided hints into two kinds of information: definite information (sender`s information and definite spam keyword lists) and less definite textual information (words or phrases, and particular features of email). In filtering spam mails, definite information is used first, and then less definite textual information is applied. In our experiment, the method of fetching web pages achieved an improvement of F-measure by 9.4% over the method of using on original email header and body only.
Local Separation Principle of Fuzzy Observer-Controller
Lee, Ho-Jae ; Park, Jin-Bae ; Joo, Young-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 902~906
DOI : 10.5391/JKIIS.2004.14.7.902
A separation principle of the Takagj-Sugeno (T-S) fuzzy-model-based observer-control is investigated. When the premise variables are able to be measured or directly computed from the outputs of the T-S fuzzy system and the fuzzy inference rules for the plant, control, and observer share the premise parts, the T-S fuzzy-model-based observer and the T-S fuzzy-model-based control can be separately designed such that the global stabilizability is guaranteed by the fuzzy observer-based output-feedback control. In this case, the global separation principle is well established. On the other hand, when the premise variables are unmeasurable or cannot be computed from the outputs, they should also be estimated. We examine the separation principle of this case. If the decay rates of the T-S fuzzy-model-based control and observer are sufficiently fast, the global separation is assured. Otherwise we show that the separation principle holds locally.
Moving Path following and High Speed Precision Control of Autonomous Mobile Robot Using Fuzzy
Lee, Won-Ho ; Lee, Hyung-Woo ; Kim, Sang-Heon ; Jung, Jae-Young ; Roh, Tae-Jung ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 907~913
DOI : 10.5391/JKIIS.2004.14.7.907
The major interest of general mobile robot is making a route and following a maked route. But, In the case of robot that is in need of movement of partial high speed, the condition of dynamic limitation is exist, and in these conditions, it demands controlling against movements we want. In this paper, in respect of the following a route at the situation that don't have the environmental map, that is, unknown environments, to prevent the slide of moving robot or the overturn that can happen for it moves fast, we organize the dynamic condition of limitation using the fuzzy logic, and we obtain more safe and fast route tracing ability by changing the standard velocity. Especially, by modeling the line tracing mobile robot, we design the tracing controller against a realtime changing target, and using the fuzzy optimized velocity limitation controller, we confirm that our robot shows its stable tracing ability by limiting its velocity intelligently against the continuously changing line.
Development of the Power Monitoring System for the Planetary Geared Motor using Hall Effect Sensor
Jang, In-Hun ; Sim, Kwee-Bo ; Oh, Se-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 914~919
DOI : 10.5391/JKIIS.2004.14.7.914
When the motor is rotating, the torque and rpm are varying as the loads or the driving status connecting through reduction units are changing. On the contrary, one can monitor the changes of the loads or the driving status in the manner of measuring motor torque and rpm. There is a torque measuring method using the strain gauge and bridge circuit. But, because this is the contact method, it has the life time which is dependent on rotating velocity and used time. So this system demands on replacement of some Parts or whole system itself for maintenance. And this system is also relatively big and expensive, requiring preceding annoying process. In this paper, we are going to suppose non-contact method to measure torque and rpm using the Hall effects sensor For this we have made the planetary geared reduction motor with Hall sensors and with the monitoring system. The monitoring system displays the sensing data(torque, rpm) and calculated data( power) and also has the network capability with Bluetooth protocol. Our solution is much more inexpensive ;md simple method to measure torque and rpm than before.
Memory Management Model Using Combined ART and Fuzzy Logic
Kim, Joo-Hoon ; Kim, Seong-Joo ; Choi, Woo-Kyung ; Kim, Jong-Soo ; Jeon, Hong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 920~926
DOI : 10.5391/JKIIS.2004.14.7.920
The human being receives a new information from outside and the information shows gradual oblivion with time. But the information remains in memory and isn't forgotten for a long time if the information is read several times over. For example, we assume that we memorize a telephone number when we listen and never remind we may forget it soon, but we commit to memory long time by repeating. If the human being received new information with strong stimulus, it could remain in memory without recalling repeatedly. The moments of almost losing one's life in an accident or getting a stroke of luck are rarely forgiven. The human being can keep memory for a long time in spite of the limit of memory for the mechanism mentioned above. In this paper, we propose a model to explain the mechanism mentioned above using a neural network and fuzzy.
Indirect Adaptive Fuzzy Observer Design
Yang, Jong-Kun ; Hyun, Chang-Ho ; Kim, Jae-Hun ; Kim, Eun-Tai ; Park, Mignon ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 927~933
DOI : 10.5391/JKIIS.2004.14.7.927
This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.
THE SEMINORMED FUZZY CO-INTEGRAL
Im, Sung-Mo ; Kim, Mi-Hye ;
Journal of Korean Institute of Intelligent Systems, volume 14, issue 7, 2004, Pages 934~938
DOI : 10.5391/JKIIS.2004.14.7.934
In this paper, we introduce the seminormed fuzzy co-integral as a complementary concept of seminormed fuzzy integral, and investigate its properties. Furthermore we propose an application of this new integral for decision making problems.