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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 13, Issue 6 - Dec 2003
Volume 13, Issue 5 - Oct 2003
Volume 13, Issue 4 - Aug 2003
Volume 13, Issue 3 - Jun 2003
Volume 13, Issue 2 - Apr 2003
Volume 13, Issue 1 - Feb 2003
Selecting the target year
A Reduction Method of Search Space for Polyhedral Object Recognition
Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 381~385
DOI : 10.5391/JKIIS.2003.13.4.381
We suggest a method which reduces the search space of a model-base on multiple-view approach for polyhedral object recognition using the ART-1 neural network. In this approach, the model-base is consisted of extracted features from two-dimensional projections observed at the predetermined viewpoints of a viewing sphere enclosing the object.
A Study on the Node Split in Decision Tree with Multivariate Target Variables
Kim, Seong-Jun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 386~390
DOI : 10.5391/JKIIS.2003.13.4.386
Data mining is a process of discovering useful patterns for decision making from an amount of data. It has recently received much attention in a wide range of business and engineering fields. Classifying a group into subgroups is one of the most important subjects in data mining. Tree-based methods, known as decision trees, provide an efficient way to finding the classification model. The primary concern in tree learning is to minimize a node impurity, which is evaluated using a target variable in the data set. However, there are situations where multiple target variable should be taken into account, for example, such as manufacturing process monitoring, marketing science, and clinical and health analysis. The purpose of this article is to present some methods for measuring the node impurity, which are applicable to data sets with multivariate target variables. For illustration, a numerical cxample is given with discussion.
Discretization of Continuous-Valued Attributes considering Data Distribution
Lee, Sang-Hoon ; Park, Jung-Eun ; Oh, Kyung-Whan ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 391~396
DOI : 10.5391/JKIIS.2003.13.4.391
This paper proposes a new approach that converts continuous-valued attributes to categorical-valued ones considering the distribution of target attributes(classes). In this approach, It can be possible to get optimal interval boundaries by considering the distribution of data itself without any requirements of parameters. For each attributes, the distribution of target attributes is projected to one-dimensional space. And this space is clustered according to the criteria like as the density value of each target attributes and the amount of overlapped areas among each density values of target attributes. Clusters which are made in this ways are based on the probabilities that can predict a target attribute of instances. Therefore it has an interval boundaries that minimize a loss of information of original data. An improved performance of proposed discretization method can be validated using C4.5 algorithm and UCI Machine Learning Data Repository data sets.
Development of Digital PWM Attitude Controller for Artificial Satellites Using Digital Redesign
Joo, Young-Hoon ; Lee, Yeon-Woo ; Lee, Ho-Jae ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 397~402
DOI : 10.5391/JKIIS.2003.13.4.397
This paper concerns a pulse-width-modulation (PWM) controller design technique using digital redesign. Digital redesign is to convert a well-designed analog controller into an equivalent pulse-amplitude-modulation (PAM) controller maintaining the original analog control system in the sense of state-matching. In similar line of conversion concept, the redesigned PAM controller is converted into a PWM controller using the equivalent area principle. To convincingly visualize the proposed technique, an computer simulation example-attitude control of artificial satellite system is included.
Caricaturing using Local Warping and Edge Detection
Choi, Sung-Jin ; Bae, Hyeon ; Kim, Sung-Shin ; Woo, Kwang-Bang ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 403~408
DOI : 10.5391/JKIIS.2003.13.4.403
A general meaning of caricaturing is that a representation, especially pictorial or literary, in which the subject`s distinctive features or peculiarities are deliberately exaggerated to produce a comic or grotesque effect. In other words, a caricature is defined as a rough sketch(dessin) which is made by detecting features from human face and exaggerating or warping those. There have been developed many methods which can make a caricature image from human face using computer. In this paper, we propose a new caricaturing system. The system uses a real-time image or supplied image as an input image and deals with it on four processing steps and then creates a caricatured image finally. The four Processing steps are like that. The first step is detecting a face from input image. The second step is extracting special coordinate values as facial geometric information. The third step is deforming the face image using local warping method and the coordinate values acquired in the second step. In fourth step, the system transforms the deformed image into the better improved edge image using a fuzzy Sobel method and then creates a caricatured image finally. In this paper , we can realize a caricaturing system which is simpler than any other exiting systems in ways that create a caricatured image and does not need complex algorithms using many image processing methods like image recognition, transformation and edge detection.
Character Recognition of Vehicle Number Plate using Modular Neural Network
Park, Chang-Seok ; Kim, Byeong-Man ; Seo, Byung-Hoon ; Lee, Kwang-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 409~415
DOI : 10.5391/JKIIS.2003.13.4.409
Recently, the modular learning are very popular and receive much attention for pattern classification. The modular learning method based on the "divide and conquer" strategy can not only solve the complex problems, but also reach a better result than a single classifier′s on the learning quality and speed. In the neural network area, some researches that take the modular learning approach also have been made to improve classification performance. In this paper, we propose a simple modular neural network for characters recognition of vehicle number plate and evaluate its performance on the clustering methods of feature vectors used in constructing subnetworks. We implement two clustering method, one is grouping similar feature vectors by K-means clustering algorithm, the other grouping unsimilar feature vectors by our proposed algorithm. The experiment result shows that our algorithm achieves much better performance.
Improved Expectation and Maximization via a New Method for Initial Values
Kim, Sung-Soo ; Kang, Jee-Hye ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 416~426
DOI : 10.5391/JKIIS.2003.13.4.416
In this paper we propose a new method for choosing the initial values of Expectation-Maximization(EM) algorithm that has been used in various applications for clustering. Conventionally, the initial values were chosen randomly, which sometimes yields undesired local convergence. Later, K-means clustering method was employed to choose better initial values, which is currently widely used. However the method using K-means still has the same problem of converging to local points. In order to resolve this problem, a new method of initializing values for the EM process. The proposed method not only strengthens the characteristics of EM such that the number of iteration is reduced in great amount but also removes the possibility of falling into local convergence.
Direction control using signals originating from facial muscle constructions
Yang, Eun-Joo ; Kim, Eung-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 427~432
DOI : 10.5391/JKIIS.2003.13.4.427
EEG is an electrical signal, which occurs during information processing in the brain. These EEG signals have been used clinically, but nowadays we ate mainly studying Brain-Computer Interface (BCI) such as interfacing with a computer through the EEG, controlling the machine through the EEG. The ultimate purpose of BCI study is specifying the EEG at various mental states so as to control the computer and machine. This research makes the controlling system of directions with the artifact that are generated from the subject s will, for the purpose of controlling the machine correctly and reliably We made the system like this. First, we select the particular artifact among the EEG mixed with artifact, then, recognize and classify the signals pattern, then, change the signals to general signals that can be used by the controlling system of directions.
Dynamic Recommendation System of Web Information Using Ensemble Support Vector Machine and Hybrid SOM
Yoon, Kyung-Bae ; Choi, Jun-Hyeog ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 433~438
DOI : 10.5391/JKIIS.2003.13.4.433
Recently, some studies of a web-based information recommendation technique which provides users with the most necessary information through websites like a web-based shopping mall have been conducted vigorously. In most cases of web information recommendation techniques which rely on a user profile and a specific feedback from users, they require accurate and diverse profile information of users. However, in reality, it is quite difficult to acquire this related information. This paper is aimed to suggest an information prediction technique for a web information service without depending on the users`specific feedback and profile. To achieve this goal, this study is to design and implement a Dynamic Web Information Prediction System which can recommend the most useful and necessary information to users from a large volume of web data by designing and embodying Ensemble Support Vector Machine and hybrid SOM algorithm and eliminating the scarcity problem of web log data.
Proportional-Integral-Derivative Evaluation for Enhancing Performance of Genetic Algorithms
Jung, Sung-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 439~447
DOI : 10.5391/JKIIS.2003.13.4.439
This paper proposes a proportional-integral-derivative (PID) evaluation method for enhancing performance of genetic algorithms. In PID evaluation, the fitness of individuals is evaluated by not only the fitness derived from an evaluation function, but also the parents fitness of each individual and the minimum and maximum fitness from initial generation to previous generation. This evaluation decreases the probability that the genetic algorithms fall into a premature convergence phenomenon and results in enhancing the performance of genetic algorithms. We experimented our evaluation method with typical numerical function optimization problems. It was found from extensive experiments that out evaluation method can increase the performance of genetic algorithms greatly. This evaluation method can be easily applied to the other types of genetic algorithms for improving their performance.
Implementation of Virtual Laboratory Based on the Internet
Joo, Young-Hoon ; Kim, Moon-Hwan ; Lee, Ho-Jae ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 448~454
DOI : 10.5391/JKIIS.2003.13.4.448
This paper concerns the establishment of the Internet-based virtual laboratory (VL). In control engineering, it is required to evaluate the feasibility of a newly developed controller design technique by applying to a physical system. However, it is inefficient to make or build such a experimental apparatus in all research activities. A possible remedy is to share such a apparatus spatially via the Internet. We set up techniques for the remote -control of various experimental apparatuses based on the Internet. The proposed VL forms a server-client structure and is implemented in multi-control interfaces.
A Cluster Validity Index Using Overlap and Separation Measures Between Fuzzy Clusters
Kim, Dae-Won ; Lee, Kwang-H. ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 455~460
DOI : 10.5391/JKIIS.2003.13.4.455
A new cluster validity index is proposed that determines the optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy c-means algorithm. The proposed validity index exploits an overlap measure and a separation measure between clusters. The overlap measure is obtained by computing an inter-cluster overlap. The separation measure is obtained by computing a distance between fuzzy clusters. A good fuzzy partition is expected to have a low degree of overlap and a larger separation distance. Testing of the proposed index and nine previously formulated indexes on well-known data sets showed the superior effectiveness and reliability of the proposed index in comparison to other indexes.
Block Based Face Detection Scheme Using Face Color and Motion Information
Kim, Soo-Hyun ; Lim, Sung-Hyun ; Cha, Hyung-Tai ; Hahn, Hern-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 461~468
DOI : 10.5391/JKIIS.2003.13.4.461
In a sequence of images obtained by surveillance cameras, facial regions appear very small and their colors change abruptly by lighting condition. This paper proposes a new face detection scheme, robust on complex background, small size, and lighting conditions. The proposed method is consisted of three processes. In the first step, the candidates for the face regions are selected using face color distribution and motion information. In the second stage, the non-face regions are removed using face color ratio, boundary ratio, and average of column-wise intensity variation in the candidates. The face regions containing eyes and mouth are segmented and classified, and then they are scored using their topological relations in the last step. To speed up and improve a performance the above process, a block based image segmentation technique is used. The experiments have shown that the proposed algorithm detects faced regions with more than 91% of accuracy and less than 4.3% of false alarm rate
On fuzzy semi-topogenous orders
Kim, Young-Sun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 469~473
DOI : 10.5391/JKIIS.2003.13.4.469
We investigate the properties of fuzzy semi-topogenous orders. We study the relationship among fuzzy supra topologies, fuzzy supra interior operators and fuzzy semi-topogenous orders. We give examples of them.
Recognition of English Calling Cards by Using Projection Method and Enhanced RBE Network
Kim, Kwang-Baek ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 474~479
DOI : 10.5391/JKIIS.2003.13.4.474
In this paper, we proposed the novel method for the recognition of English calling cards by using the projection method and the enhanced RBF (Radial Basis Function) network. The recognition of calling cards consists of the extraction phase of character areas and the recognition phase of extracted characters. In the extraction phase, first of all, noises are removed from the images of calling cards, and the feature areas including character strings are separated from the calling card images by using the horizontal smearing method and the 8-directional contour tracking method. And using the image projection method, the feature areas are split into the areas of individual characters. We also proposed the enhanced RBF network that organizes the middle layer effectively by using the enhanced ART1 neural network adjusting the vigilance threshold dynamically according to the homogeneity between patterns. In the recognition phase, the proposed neural network is applied to recognize individual characters. Our experiment result showed that the proposed recognition algorithm has higher success rate of recognition and faster learning time than the existing neural network based recognition.
A Clustering Algorithm for Path Planning of SMT Inspection Machines
Kim, Hwa-Jung ; Park, Tae-Hyoung ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 480~485
DOI : 10.5391/JKIIS.2003.13.4.480
We Propose a Path planning method to reduce the Inspection time of AOI (automatic optical inspection) machines in SMT (surface mount technology) in-line system. Inspection windows of board should be clustered to consider the FOV (field-of-view) of camera. The number of clusters is desirable to be minimized in order to reduce the overall inspection time. We newly propose a genetic algorithm to minimize the number of clusters for a given board. Comparative simulation results are presented to verify the usefulness of proposed algorithm.
Software Reliability Assessment with Fuzzy Least Squares Support Vector Machine Regression
Hwang, Chang-Ha ; Hong, Dug-Hun ; Kim, Jang-Han ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 486~490
DOI : 10.5391/JKIIS.2003.13.4.486
Software qualify models can predict the risk of faults in the software early enough for cost-effective prevention of problems. This paper introduces a least squares support vector machine (LS-SVM) as a fuzzy regression method for predicting fault ranges in the software under development. This LS-SVM deals with the fuzzy data with crisp inputs and fuzzy output. Predicting the exact number of bugs in software is often not necessary. This LS-SVM can predict the interval that the number of faults of the program at each session falls into with a certain possibility. A case study on software reliability problem is used to illustrate the usefulness of this LS -SVM.
A Probe Prevention Model for Detection of Denial of Service Attack on TCP Protocol
Lee, Se-Yul ; Kim, Yong-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 491~498
DOI : 10.5391/JKIIS.2003.13.4.491
The advanced computer network technology enables connectivity of computers through an open network environment. There has been growing numbers of security threat to the networks. Therefore, it requires intrusion detection and prevention technologies. In this paper, we propose a network based intrusion detection model using FCM(Fuzzy Cognitive Maps) that can detect intrusion by the DoS attack detection method adopting the packet analyses. A DoS attack appears in the form of the Probe and Syn Flooding attack which is a typical example. The SPuF(Syn flooding Preventer using Fussy cognitive maps) model captures and analyzes the packet informations to detect Syn flooding attack. Using the result of analysis of decision module, which utilized FCM, the decision module measures the degree of danger of the DoS and trains the response module to deal with attacks. For the performance comparison, the "KDD′99 Competition Data Set" made by MIT Lincoln Labs was used. The result of simulating the "KDD′99 Competition Data Set" in the SPuF model shows that the probe detection rates were over 97 percentages.
The exact controllability for the nonlinear fuzzy control system in E
Kwun, Young-Chel ; Park, Jong-Seo ; Kang, Jum-Ran ; Jeong, Doo-Hwan ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 4, 2003, Pages 499~503
DOI : 10.5391/JKIIS.2003.13.4.499
This paper we study the exact controllability for the nonlinear fuzzy control system in
by using the concept of fuzzy number of dimension n whose values are normal, convex, upper semicontinuous and compactly supported surface in