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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 17, Issue 7 - Dec 2007
Volume 17, Issue 6 - Dec 2007
Volume 17, Issue 5 - Oct 2007
Volume 17, Issue 4 - Aug 2007
Volume 17, Issue 3 - Jun 2007
Volume 17, Issue 2 - Apr 2007
Volume 17, Issue 1 - Feb 2007
Selecting the target year
Multilevel Threshold Selection Method Based on Gaussian-Type Finite Mixture Distributions
Seo, Suk-T. ; Lee, In-K. ; Jeong, Hye-C. ; Kwon, Soon-H. ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 725~730
DOI : 10.5391/JKIIS.2007.17.6.725
Gray-level histogram-based threshold selection methods such as Otsu's method, Huang and Wang's method, and etc. have been widely used for the threshold selection in image processing. They are simple and effective, but take too much time to determine the optimal multilevel threshold values as the number of thresholds are increased. In this paper, we measure correlation between gray-levels by using the Gaussian function and define a Gaussian-type finite mixture distribution which is combination of the Gaussian distribution function with the gray-level histogram, and propose a fast and effective threshold selection method using it. We show the effectiveness of the proposed through experimental results applied it to three images and the efficiency though comparison of the computational complexity of the proposed with that of Otsu's method.
A Nutrition Status Analysis System Based on Hierarchical Fuzzy Inference Approach
Son, Chang-S. ; Jeong, Gu-Beom ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 731~737
DOI : 10.5391/JKIIS.2007.17.6.731
In this paper, we propose a system for analyzing nutrition status based on hierarchical fuzzy inference approach, where the hierarchical fuzzy approach used to analyze the transition process on the nutritional status from an obesity degree, the previous nutritional status, and the eating pattern with an individual. Moreover we discussed about the selection method of fuzzy membership intervals of the next layer to improve the reliability of inference results in hierarchical fuzzy system, where their intervals are modified by using statistical information of the defuzzified results obtained from the previous layer. To show the effectiveness of this system, we evaluated the nutritional status from the information of anthropometric measurement, biochemical test, and INQ on 113 people over the age of 65, and also analyzed their nutritional status.
Control of an Artificial Arm using Flex Sensor Signal
Yoo, Jae-Myung ; Kim, Young-Tark ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 738~743
DOI : 10.5391/JKIIS.2007.17.6.738
In this paper, a muscle motion sensing system and an artificial arm control system are studied. The artificial arm is for the people who lost one's forearm. The muscle motion sensing system detect the intention of motion from the upper arm's muscle. In sensing system we use flex sensors which is electrical resistance type sensor. The sensor is attached on the biceps brachii muscle and coracobrachialis muscle of the upper arm. We propose an algorithm to classify the one's intention of motions from the sensor signal. Using this algorithm, we extract the 4 motions which are flexion and extension of the forearm, pronation and supination of the arm. To verify the validity of the proposed algorithms we made experiments with two d.o.f. artificial arm. To reduce the control errors of the artificial arm we also proposed a fuzzy PID control algorithm which based on the errors and error rate.
Localization of Mobile Robot Using Multi IR Range Sensors
Ryoo, Young-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 744~748
DOI : 10.5391/JKIIS.2007.17.6.744
In this paper, a new localization method of indoor mobile robot using multi IR(infrared) range sensors is proposed. Each IR range sensor detects the edge of obstacles and wall using the acquired range data. The environment map is built by the merging process of the detected edge data of each sensor. The performance of proposed system is verified by the comparison of the real environment and the detected map in experiments.
On Lebesgue-type theorems for interval-valued Choquet integrals with respect to a monotone set function
Jang, Lee-Chae ; Kim, Tae-Kyun ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 749~753
DOI : 10.5391/JKIIS.2007.17.6.749
In this paper, we consider Lebesgue-type theorems in non-additive measure theory and then investigate interval valued Choquet integrals and interval-valued fuzzy integral with respect to a additive monotone set function. Furthermore, we discuss the equivalence among the Lebesgue's theorems, the monotone convergence theorems of interval-valued fuzzy integrals with respect to a monotone set function and find some sufficient condition that the monotone convergence theorem of interval-valued Choquet integrals with respect to a monotone set function holds.
Learning for User Profile Based on Negative Feedback and Reinforcement Learning
Son, Ki-Jun ; Lim, Soo-Yeon ; Lee, Sang-Jo ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 754~759
DOI : 10.5391/JKIIS.2007.17.6.754
The information recommendation system offers selected documents according to information needs of dynamic users. User's needs are expressed as profiles consisting of one or more words and may be changed into some specifics through relevance feedback made by users during the recommendation process. In previous research, users have entered relevance information by taking part in explicit relevance feedbacks and learned user profiles using the positive relevance feedbacks. In this paper, we learn user profiles using not only positive relevance feedback but negative relevance feedback and reinforcement learning. To compare the proposed with previous method, we performed experiments to evaluate recommendation performance of the same topic. As a result, the former shows the improved performance than the latter does.
Development of Fault Detection Algorithm Applicable to Sensor Network System
Youk, Eui-Su ; Yun, Seong-Ung ; Kim, Sung-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 760~765
DOI : 10.5391/JKIIS.2007.17.6.760
The sensor network system which has limited resources is deployed in a wide area and plays an important role of gethering information and monitoring. Generally, fault of sensor nodes which was caused by limited resources and poor environment happens. Futhermore, this fault poses many problems related with required quality of whole network. In this paper, new fault detection algorithm which utilizes both consensus algorithm and localized faulty sensor detection scheme is proposed. To verify the feasibility of the proposed scheme, some simulation and experiment are carried out.
Linear Path Query Processing using Backward Label Path on XML Documents
Park, Chung-Hee ; Koo, Heung-Seo ; Lee, Sang-Joon ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 766~772
DOI : 10.5391/JKIIS.2007.17.6.766
As XML is widely used, many researches on the XML storage and query processing have been done. But, previous works on path query processing have mainly focused on the storage and retrieval methods for a large XML document or XML documents had a same DTD. Those researches did not efficiently process partial match queries on the differently-structured document set. To resolve the problem, we suggested a new index structure using relational table. The method constructs the
-tree index using backward label paths instead of forward label paths used in previous researches for storing path information and allows for finding the label paths that match the partial match queries efficiently using it when process the queries.
The Design of Customized Board using the Web 2.0
Park, Sung-Shin ; Kim, Chang-Suk ; Kim, Dae-Su ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 773~779
DOI : 10.5391/JKIIS.2007.17.6.773
Internet bulletin boards have been used to exchange their idea and information among Internet users. But the existing Internet bulletin boards can not satisfy user's personal view. In this raper, Web 2.0 based customized Internet bulletin board is to design. The proposed Internet bulletin board provides each user with personalized information which are established by user beforehand. So user can retrieve his interested information fast. Moreover user can generate his own personalized bulletin board to collect one's interested information automatically. The personalized bulletin board is connected to several Internet bulletin boards with RSS feeds.
Decentralized Dynamic Output Feedback Controller for Discrete-time Nonlinear Interconnected Systems via T-S Fuzzy Models
Koo, Geun-Bum ; Kim, Jin-Kyu ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 780~785
DOI : 10.5391/JKIIS.2007.17.6.780
This paper proposes the decentralized dynamic output feedback controller for discrete-time nonlinear interconnected systems using Takagi-Sugeno (T-S) fuzzy model. Through T-S fuzzy model of each subsystem, the decentralized dynamic output feedback controller is designed. By the closed-loop subsystems with controller, it represents the linear matrix inequality (LMI) for stability of whole interconnected system. The value of control gain are obtained by LMI. An example is given to show the experimentally verification discussed throughout the paper.
Soundsource Localization and Tracking System of Intruder for Intelligent Surveillance System
Park, Jung-Hyun ; Yeom, Hong-Gi ; Jung, Bong-Gyu ; Jang, In-Hun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 786~791
DOI : 10.5391/JKIIS.2007.17.6.786
In the place that its security is crucial, the necessity of system which can tract and recognize random person is getting more important. In this paper, we'd like to develop the invader tracking system which consists of the sound source tracking-sensor and the pan-tilt camera for wide-area guard. After detecting the direction of any sound with the sound source tracking-sensor at first, our system make move the pan-tilt camera to that direction and extract reference image from that camera. This reference image is compared and updated by the next captured image after some interval time. By keeping on it over again, we can realize the guard system which can tract an invader using the difference image and the result of another image processing. By linking home network security system, the suggested system can provide some interfacing functions for the security service of the public facilities as well as that of home.
Statistical Information-Based Hierarchical Fuzzy-Rough Classification Approach
Son, Chang-S. ; Seo, Suk-T. ; Chung, Hwan-M. ; Kwon, Soon-H. ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 792~798
DOI : 10.5391/JKIIS.2007.17.6.792
In this paper, we propose a hierarchical fuzzy-rough classification method based on statistical information for maximizing the performance of pattern classification and reducing the number of rules without learning approaches such as neural network, genetic algorithm. In the proposed method, statistical information is used for extracting the partition intervals of antecedent fuzzy sets at each layer on hierarchical fuzzy-rough classification systems and rough sets are used for minimizing the number of fuzzy if-then rules which are associated with the partition intervals extracted by statistical information. To show the effectiveness of the proposed method, we compared the classification results(e.g. the classification accuracy and the number of rules) of the proposed with those of the conventional methods on the Fisher's IRIS data. From the experimental results, we can confirm the fact that the proposed method considers only statistical information of the given data is similar to the classification performance of the conventional methods.
On the Fuzzy Membership Function of Fuzzy Support Vector Machines for Pattern Classification of Time Series Data
Lee, Soo-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 799~803
DOI : 10.5391/JKIIS.2007.17.6.799
In this paper, we propose a new fuzzy membership function for FSVM(Fuzzy Support Vector Machines). We apply a fuzzy membership to each input point of SVM and reformulate SVM into fuzzy SVM (FSVM) such that different input points can make different contributions to the learning of decision surface. The proposed method enhances the SVM in reducing the effect of outliers and noises in data points. This paper compares classification and estimated performance of SVM, FSVM(1), and FSVM(2) model that are getting into the spotlight in time series prediction.
A note on T-sum of bell-shaped fuzzy intervals
Hong, Dug-Hun ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 804~806
DOI : 10.5391/JKIIS.2007.17.6.804
The usual arithmetic operations on real numbers can be extended to arithmetical operations on fuzzy intervals by means of Zadeh's extension principle based on a t-norm T. Dombi and Gyorbiro proved that addition is closed if the Dombi t-norm is used with two bell-shaped fuzzy intervals. Recently, Hong [Fuzzy Sets and Systems 158(2007) 739-746] defined a broader class of bell-shaped fuzzy intervals. Then he study t-norms which are consistent with these particular types of fuzzy intervals as applications of a result proved by Mesiar on a strict f-norm based shape preserving additions of LR-fuzzy intervals with unbounded support. In this note, we give a direct proof of the main results of Hong.
Parameter Optimization of Extreme Learning Machine Using Bacterial Foraging Algorithm
Cho, Jae-Hoon ; Lee, Dae-Jong ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 807~812
DOI : 10.5391/JKIIS.2007.17.6.807
Recently, Extreme learning machine(ELM), a novel learning algorithm which is much faster than conventional gradient-based learning algorithm, was proposed for single-hidden-layer feedforward neural networks. The initial input weights and hidden biases of ELM are usually randomly chosen, and the output weights are analytically determined by using Moore-Penrose(MP) generalized inverse. But it has the difficulties to choose initial input weights and hidden biases. In this paper, an advanced method using the bacterial foraging algorithm to adjust the input weights and hidden biases is proposed. Experiment at results show that this method can achieve better performance for problems having higher dimension than others.
Definition Sentences Recognition Based on Definition Centroid
Kim, Kweon-Yang ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 813~818
DOI : 10.5391/JKIIS.2007.17.6.813
This paper is concerned with the problem of recognizing definition sentences. Given a definition question like "Who is the person X?", we are to retrieve the definition sentences which capture descriptive information correspond variously to a person's age, occupation, of some role a person played in an event from the collection of news articles. In order to retrieve as many relevant sentences for the definition question as possible, we adopt a centroid based statistical approach which has been applied in summarization of multiple documents. To improve the precision and recall performance, the weight measure of centroid words is supplemented by using external knowledge resource such as Wikipedia and redundant candidate sentences are removed from candidate definitions. We see some improvements obtained by our approach over the baseline for 20 IT persons who have high document frequency.
Fault Diagnosis of Induction Motors by DFT and Wavelet
Kwon, Mann-Jun ; Lee, Dae-Jong ; Park, Sung-Moo ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 819~825
DOI : 10.5391/JKIIS.2007.17.6.819
In this paper, we propose a fault diagnosis algorithm of induction motors by DFT and wavelet. We extract a feature vector using a fault pattern extraction method by DFT in frequency domain and wavelet transform in time-frequency domain. And then we deal with a fusion algorithm for the feature vectors extracted from DFT and wavelet to classify the faults of induction motors. Finally, we provide an experimental results that the proposed algorithm can be successfully applied to classify the several fault signals acquired from induction motors.
A study on Development of Soft-Motor Controller using EtherCAT
Moon, Yong-Seon ; Lee, Young-Pil ; Seo, Dong-Jin ; Lee, Sung-Ho ; Bae, Young-Chul ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 826~831
DOI : 10.5391/JKIIS.2007.17.6.826
In this paper, we proposed new method of soft-motor control which is control method allowing motor control within control stage by using EtherCAT which is real time motion control network of high speed. We also evaluated performance of the system and verified possibility and effectiveness of application into real system through experiments.
Brain-wave Analysis using fMRI, TRS and EEG for Human Emotion Recognition
Kim, Ho-Duck ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 832~837
DOI : 10.5391/JKIIS.2007.17.6.832
Many researchers are studying brain activity to using functional Magnetic Resonance Imaging (fMRI), Time Resolved Spectroscopy(TRS), Electroencephalography(EEG), and etc. They are used detection of seizures or epilepsy and deception detection in the main. In this paper, we focus on emotion recognition by recording brain waves. We specially use fMRI, TRS, and EEG for measuring brain activity Researchers are experimenting brain waves to get only a measuring apparatus or to use both fMRI and EEG. This paper is measured that we take images of fMRI and TRS about brain activity as human emotions and then we take data of EEG signals. Especially, we focus on EEG signals analysis. We analyze not only original features in brain waves but also transferred features to classify into five sections as frequency. And we eliminate low frequency from 0.2 to 4Hz for EEG artifacts elimination.
Fuzzy Convergence Approach Spaces
Lee, Hyei-Kyung ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 838~842
DOI : 10.5391/JKIIS.2007.17.6.838
In this paper, we define that a fuzzy convergence approach limit and a fuzzy approach Chuchy structure on X. And we investigate the relations between the category CAP and the category FCAP. And we show that the categories
Generation of Falling Motion for Humanoid Robot Using GA
An, Kwang-Chul ; Cho, Young-Wan ; Seo, Ki-Sung ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 843~848
DOI : 10.5391/JKIIS.2007.17.6.843
This paper introduced an automatic generation method of falling motions for humanoid robots to minimize a damage. The proposed approach used a GA based optimization technique to find a set of joint trajectories which minimize a damage of the falling over and down. A couple of fitness functions are provided to generate various falling motions. To verify the proposed method, experiments for falling motions were executed for Sony QRIO robot in Webots simulation environments.
A Method of Efficient Web Crawling Using URL Pattern Scripts
Chang, Moon-Soo ; Jung, June-Young ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 6, 2007, Pages 849~854
DOI : 10.5391/JKIIS.2007.17.6.849
It is difficult that we collect only target documents from the Innumerable Web documents. One of solution to the problem is that we select target documents on the Web site which services many documents of target domain. In this paper, we will propose an intelligent crawling method collecting needed documents based on URL pattern script defined by XML. Proposed crawling method will efficiently apply to the sites which service structuralized information of a piece with database. In this paper, we collected 50 thousand Web documents using our crawling method.