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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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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 19, Issue 6 - Dec 2009
Volume 19, Issue 5 - Oct 2009
Volume 19, Issue 4 - Aug 2009
Volume 19, Issue 3 - Jun 2009
Volume 19, Issue 2 - Apr 2009
Volume 19, Issue 1 - Feb 2009
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Design of Fuzzy System with Hierarchical Classifying Structures and its Application to Time Series Prediction
Bang, Young-Keun ; Lee, Chul-Heui ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 595~602
DOI : 10.5391/JKIIS.2009.19.5.595
Fuzzy rules, which represent the behavior of their system, are sensitive to fuzzy clustering techniques. If the classification abilities of such clustering techniques are improved, their systems can work for the purpose more accurately because the capabilities of the fuzzy rules and parameters are enhanced by the clustering techniques. Thus, this paper proposes a new hierarchically structured clustering algorithm that can enhance the classification abilities. The proposed clustering technique consists of two clusters based on correlationship and statistical characteristics between data, which can perform classification more accurately. In addition, this paper uses difference data sets to reflect the patterns and regularities of the original data clearly, and constructs multiple fuzzy systems to consider various characteristics of the differences suitably. To verify effectiveness of the proposed techniques, this paper applies the constructed fuzzy systems to the field of time series prediction, and performs prediction for nonlinear time series examples.
Similarity Measure Between Interval-valued Vague Sets
Cho, Sang-Yeop ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 603~608
DOI : 10.5391/JKIIS.2009.19.5.603
In this paper, a similarity measure between interval-valued vague sets is proposed. In the interval-valued vague sets representation, the upper bound and the lower bound of a vague set are represented as intervals of interval-valued fuzzy set respectively. Proposed method combines the concept of geometric distance and the center-of-gravity point of interval-valued vague set to evaluate the degree of similarity between interval-valued vague sets. We also prove three properties of the proposed similarity measure. It provides a useful way to measure the degree of similarity between interval-valued vague sets.
Metal Object Detection System For Drive Inside Protection
Kim, Jin-Kyu ; Joo, Young-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 609~614
DOI : 10.5391/JKIIS.2009.19.5.609
The purpose of this paper is to design the metal object detection system for drive inside protection. To do this, we propose the algorithm for designing the color filter that can detect the metal object using fuzzy theory and the algorithm for detecting area of the driver`s face using fuzzy skin color filter. Also, by using the proposed algorithm, we propose the algorithm for detecting the metallic object candidate regions. And, the metallic object color filter is then applied to find the candidate regions. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.
TFT-LCD Defect Detection Using Multi-level Threshold and Probability Density Function
Kim, Se-Yun ; Jung, Chang-Do ; Yun, Byoung-Ju ; Joo, Young-Bok ; Choi, Byung-Jae ; Park, Kil-Houm ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 615~621
DOI : 10.5391/JKIIS.2009.19.5.615
TFT-LCD image consists of ununiform background, random noises and target defect signal components. Defects in TFT-LCD have some intensity variations compared to background region. It is sometimes difficult for human inspectors to figure out. In this paper, we propose multi-level threshold scheme for detection of the real defect using probability density function with Parzen Window. The experimental results show that the proposed algorithms produce promising results and can be applied to automated inspection systems for finding defects in the TFT-LCD image.
Analysis on Effective Walking Pattern for Multi-Legged Robots
Kim, Byoung-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 622~628
DOI : 10.5391/JKIIS.2009.19.5.622
A proper walking pattern is to be assigned for a walk of multi-legged robots. For the purpose of identifying a good walking pattern for multi-legged robots, this paper consider a simple model of quadruped robotic walking and analyze its walking balance based on the centroid of foot polygons formed in every step. A performance index to estimate the walking balance is also proposed. Simulation studies show that the centroid trajectory of foot polygons and the walking balance in a common quadruped walking are different according to the walking pattern employed. Based on the walking balance index and a bio-mimetic aspect, a useful walking pattern for quadruped robots is finally addressed.
Intelligent Feature Extraction and Scoring Algorithm for Classification of Passive Sonar Target
Kim, Hyun-Sik ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 629~634
DOI : 10.5391/JKIIS.2009.19.5.629
In real-time system application, the feature extraction and scoring algorithm for classification of the passive sonar target has the following problems: it requires an accurate and efficient feature extraction method because it is very difficult to distinguish the features of the propeller shaft rate (PSR) and the blade rate (BR) from the frequency spectrum in real-time, it requires a robust and effective feature scoring method because the classification database (DB) composed of extracted features is noised and incomplete, and further, it requires an easy design procedure in terms of structures and parameters. To solve these problems, an intelligent feature extraction and scoring algorithm using the evolution strategy (ES) and the fuzzy theory is proposed here. To verify the performance of the proposed algorithm, a passive sonar target classification is performed in real-time. Simulation results show that the proposed algorithm effectively solves sonar classification problems in real-time.
Intelligent Obstacle Avoidance Algorithm for Autonomous Control of Underwater Flight Vehicle
Kim, Hyun-Sik ; Jin, Tae-Seok ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 635~640
DOI : 10.5391/JKIIS.2009.19.5.635
In real system application, the obstacle avoidance system for the autonomous control of the underwater flight vehicle (UFV) operates with the following problems: it has local information because the sonar can only offer the obstacle information in a local detection area, it requires a continuous control input because the system that has reduced acoustic noise and power consumption is necessary, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an intelligent obstacle avoidance algorithm using the evolution strategy (ES) and the fuzzy logic controller (FLC), is proposed. To verify the performance of the proposed algorithm, the obstacle avoidance of UFV is performed. Simulation results show that the proposed algorithm effectively solves the problems in the real system application.
Interacting Multiple Model Vehicle-Tracking System Based on Neural Network
Hwang, Jae-Pil ; Park, Seong-Keun ; Kim, Eun-Tai ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 641~647
DOI : 10.5391/JKIIS.2009.19.5.641
In this paper, a new filtering scheme for adaptive cruise control (ACC) system is presented. In the proposed scheme, the identification of the mode of the preceding vehicle is considered as a classification problem and it is done by a neural network classifier. The neural network classifier outputs a posterior probability of the mode of the preceding vehicle and the probability is directly used in the IMM framework. Finally, ten scenarios are made and the proposed NIMM is tested on them to show its validity.
Bilateral Diagonal 2DLDA Method for Human Face Recognition
Kim, Young-Gil ; Song, Young-Jun ; Kim, Dong-Woo ; Ahn, Jae-Hyeong ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 648~654
DOI : 10.5391/JKIIS.2009.19.5.648
In this paper, a method called bilateral diagonal 2DLDA is proposed for face recognition. Two methods called Dia2DPCA and Dia2DLDA were suggested to reserve the correlations between the variations in the rows and columns of diagonal images. However, these methods work in the row direction of these images. A row-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the column variation of alternative diagonal face images. In addition, column-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the row variation in diagonal images. A bilateral projection scheme was applied using left and right multiplying projection matrices. As a result, the dimension of the feature matrix and computation time can be reduced. Experiments carried out on an ORL face database show that the proposed method with three different distance measures, namely, Frobenius, Yang and AMD, is more accurate than some methods, such as 2DPCA, B2DPCA, 2DLDA, etc.
User Modeling based Time-Series Analysis for Context Prediction in Ubiquitous Computing Environment
Choi, Young-Hwan ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 655~660
DOI : 10.5391/JKIIS.2009.19.5.655
The context prediction algorithms are not suitable to provide real-time personalized service for users in context-awareness environment. The algorithms have problems like time delay in training data processing and the difficulties of implementation in real-time environment. In this paper, we propose a prediction algorithm with user modeling to shorten of processing time and to improve the prediction accuracy in the context prediction algorithm. The algorithm uses moving path of user contexts for context prediction and generates user model by time-series analysis of user`s moving path. And that predicts the user context with the user model by sequence matching method. We compared our algorithms with the prediction algorithms by processing time and prediction accuracy. As the result, the prediction accuracy of our algorithm is similar to the prediction algorithms, and processing time is reduced by 40% in real time service environment.
Generation of Locomotion for Snake-like Robot using Genetic Algorithm and Analysis for Selections of Partial Modules
Ahn, Ihn-Seok ; Jang, Jae-Young ; Seo, Ki-Sung ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 661~666
DOI : 10.5391/JKIIS.2009.19.5.661
Modular snake-like robots, which consist of series of modules, are robust for failure and have flexible locomotions for environment. However, they are difficult to control and few efficient and various locomotions are introduced yet. In this paper, GA based phase generation and trajectory generation approaches are implemented and compared for locomotion of snake-like robots and extended for analysis for selections of partial modules. In addition, modeling and simulation environments are implemented in Webots simulator and above GA based experiments for locomotion are executed for KMC snake-like robot.
An Efficient Facial Expression Recognition by Measuring Histogram Distance Based on Preprocessing
Cho, Yong-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 667~673
DOI : 10.5391/JKIIS.2009.19.5.667
This paper presents an efficient facial expression recognition method by measuring the histogram distance based on preprocessing. The preprocessing that uses both centroid shift and histogram equalization is applied to improve the recognition performance, The distance measurement is also applied to estimate the similarity between the facial expressions. The centroid shift based on the first moment balance technique is applied not only to obtain the robust recognition with respect to position or size variations but also to reduce the distance measurement load by excluding the background in the recognition. Histogram equalization is used for robustly recognizing the poor contrast of the images due to light intensity. The proposed method has been applied for recognizing 72 facial expression images(4 persons * 18 scenes) of 320*243 pixels. Three distances such as city-block, Euclidean, and ordinal are used as a similarity measure between histograms. The experimental results show that the proposed method has superior recognition performances compared with the method without preprocessing. The ordinal distance shows superior recognition performances over city-block and Euclidean distances, respectively.
Design of a Chain-Type Modular Robot
Lee, Bo-Hee ; Lee, Sang-Kyung ; Kong, Jung-Shik ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 674~682
DOI : 10.5391/JKIIS.2009.19.5.674
The modular robot is one which was developed to get over limit of the space movement for the mobile robot. The chain type robot in particular is connected by series each other and this form expression method is simple and easy to really make a docking method efficiently. However, the related studies were focused on the movement that used to be combination, and the movement of a cell independent mainly does not consist and have a problem to dock only in a direction, not to be connected with all directions. Therefore, we suggested a modular structure for quick, independent movement to solve such a problem and had own autonomy. In addition, we are intended to get some effectiveness for connection mechanism using one locking motor. In this paper, we dealt with the design for the mechanical and electrical points and docking algorithm including communication method. All of the structure is verified with real action experiment through the shape expressions of various application platform.
3D Image Process by Template Matching and B-Spline Interpolations
Joo, Young-Hoon ; Yang, Han-Jin ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 683~688
DOI : 10.5391/JKIIS.2009.19.5.683
The purposes of this paper is to propose new techniques to reconstruct measured optical images by using the template matching and B-Spline interpolation method based on image processing technology. To do this, we detect the matching template and non-matching template from each optical image. And then, we match the overlaped images from base level by correcting roll, pitch, and yaw error of images. At last, the matching image is interpolated by B-Spline interpolation. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.
Time Series Stock Prices Prediction Based On Fuzzy Model
Hwang, Hee-Soo ; Oh, Jin-Sung ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 689~694
DOI : 10.5391/JKIIS.2009.19.5.689
In this paper an approach to building fuzzy models for predicting daily and weekly stock prices is presented. Predicting stock prices with traditional time series analysis has proven to be difficult. Fuzzy logic based models have advantage of expressing the input-output relation linguistically, which facilitates the understanding of the system behavior. In building a stock prediction model we bear a burden of selecting most effective indicators for the stock prediction. In this paper information used in traditional candle stick-chart analysis is considered as input variables of our fuzzy models. The fuzzy rules have the premises and the consequents composed of trapezoidal membership functions and nonlinear equations, respectively. DE(Differential Evolution) identifies optimal fuzzy rules through an evolutionary process. The fuzzy models to predict daily and weekly open, high, low, and close prices of KOSPI(KOrea composite Stock Price Index) are built, and their performances are demonstrated.
Fuzzy r-Generalized Open Sets and Fuzzy r-Generalized Continuity
Min, Won-Keun ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 695~698
DOI : 10.5391/JKIIS.2009.19.5.695
In this paper, we introduce the concept of fuzzy r-generalized open sets which are generalizations of fuzzy r-open sets defined by Lee and Lee  and obtain some basic properties of their structures. Also we introduce and study the concepts of fuzzy r-generalized continuous mapping, fuzzy r-generalized open mapping and fuzzy r-generalized closed mapping.
Fuzzy and Proportional Controls for Driving Control of Forklift AGV
Kim, Jung-Min ; Park, Jung-Je ; Jeon, Tae-Ryong ; Kim, Sung-Shin ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 699~705
DOI : 10.5391/JKIIS.2009.19.5.699
This paper is represented to research of driving control for the forklift AGV. The related works that were studied about AGV as heavy equipment used two methods which are magnet-gyro and wire guidance for localization. However, they have weaknesses that are high cost, difficult maintenance according to change of environment. In this paper, we develop localization system through sensor fusion with laser navigation system and encoder, gyro for robustness. Also we design driving controller using fuzzy and proportional control. It considers distance and angle difference between forklift AGV and pallet for engaging work. To analyze performance of the proposed control system, we experiment in same working condition over 10 times. In the results, the average error was presented with 54.16mm between simulation of control navigation and real control navigation. Consequently, experimental result shows that the performance of proposed control system is effective.
Diagnostic system development for state monitoring of induction motor and oil level in press process system
Lee, In-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 706~712
DOI : 10.5391/JKIIS.2009.19.5.706
In this paper, a fault diagnosis method is proposed to detect and classifies faults that occur in press process line. An oil level automatic monitoring method is also presented to detect oil level. The FFT(fast fourier transform) frequency analysis and ART2 NN(adaptive resonance theory 2 neural network) with uneven vigilance parameters are used to achieve fault diagnosis in proposing method, and GUI(graphical user interface) program for fault diagnosis and oil level automatic monitoring using LabVIEW is produced and fault diagnosis was done. The experiment results demonstrate the effectiveness of the proposed fault diagnosis method of induction motors and oil level automatic monitor system.
Short-Term Water Demand Forecasting Algorithm Using AR Model and MLP
Choi, Gee-Seon ; Yu, Chool ; Jin, Ryuk-Min ; Yu, Seong-Keun ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 713~719
DOI : 10.5391/JKIIS.2009.19.5.713
In this paper, we develope a water demand forecasting algorithm using AR(Auto-regressive) and MLP(Multi-layer perceptron). To show effectiveness of the proposed method, we analyzed characteristics of time-series data collected in "A" purification plant at Jeon-Buk province during 2007-2008, and then performed the proposed method with various input factors selected through various analyses. As noted in experimental results, the performance of three types model such as multi-regressive, AR(Auto-regressive), and AR+MLP(Auto-regressive + Multi-layer perceptron) show 5.1%, 3.8%, and 3.6% with respect to MAPE(Mean Absolute Percentage Error), respectively. Thus, it is noted that the proposed method can be used to predict short-term water demand for the efficient operation of a water purification plant.
A Consciousness Structure Analysis for the Success Factors of Company Projects Using FSM
Lee, Young-Joo ; Hwang, Seung-Gook ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 720~724
DOI : 10.5391/JKIIS.2009.19.5.720
This thesis analyze structure of consciousness of success factors of company project by applying FSM(Fuzzy Structural Modeling). FSM is a theory that implied fuzzy theory to ISM(Interpretive Structural Modeling) and is known to be more valid in recognizing a complex pluralistic value system and it is also designed to choose structure model that fits reality with when it is changed by parameter p and
. It is desirable to conduct conformity assessment to complement even though selected structure model is considered as conformed because structure model is chosen without objective evaluation for conformity. Therefore, this paper present more objective structure model through conformity evaluation using structural equation modeling on success factors to achieve company project obtained by FSM and analyze the consciousness structure according to that structure.
On Intuitionistic Fuzzy Generalized Topological Spaces
Min, Won-Keun ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 725~729
DOI : 10.5391/JKIIS.2009.19.5.725
In this paper, we introduce the concepts of intuitionistic fuzzy generalized topological spaces and intuitionistic gradation of generalized openness. We also introduce the concepts of IFG-mapping, weak IFG-mapping and IFG-open mapping, and obtain some characterizations for such mappings.
Feature Selection and Classification of Protein CDS Using n-Block substring weighted Linear Model
Choi, Seong-Yong ; Kim, Jin-Su ; Han, Seung-Jin ; Choi, Jun-Hyeog ; Rim, Kee-Wook ; Lee, Jung-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 730~736
DOI : 10.5391/JKIIS.2009.19.5.730
It is more important to analysis of huge gemonics data in Bioinformatics. Here we present a novel datamining approach to predict structure and function using protein`s primnary structure only. We propose not also to develope n-Block substring search algorithm in reducing enormous search space effectively in relation to feature selection, but to formulate weighted linear algorithm in a prediction of structure and function of a protein using primary structure. And we show efficient in protein domain characterization and classification by calculation weight value in determining domain association in each selected substring, and also reveal that more efficient results are acquired through claculated model score result in an inference about degree of association with each CDS(coding sequence) in domain.
Study on Path Planning for Autonomous Mobile Robot using Potential Field
Jung, Kwang-Min ; Lee, Hea-Jae ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 19, issue 5, 2009, Pages 737~742
DOI : 10.5391/JKIIS.2009.19.5.737
The popularity of autonomous mobile robots have been rapidly increasing due to their new emerging application area, from room cleaning, tourist guidance to space explorations. However, the development of a satisfactory control algorithm that will enable the autonomous mobile robots to navigate safely especially in dynamic environments is still an open research problem. In this paper, a newly proposed potential field based control method is implemented, analyzed, and improvements are suggest based on experimental results obtain from computer simulations. The experimental results are presented to show the effectiveness of the behavior-based control using the proposed potential field generation technique.