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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 15, Issue 7 - Dec 2005
Volume 15, Issue 6 - Dec 2005
Volume 15, Issue 5 - Oct 2005
Volume 15, Issue 4 - Aug 2005
Volume 15, Issue 3 - Jun 2005
Volume 15, Issue 2 - Apr 2005
Volume 15, Issue 1 - Feb 2005
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Some properties of Choquet distance measures for interval-valued fuzzy numbers
Jang, Lee-Chae ; Kim, Won-Joo ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 789~793
DOI : 10.5391/JKIIS.2005.15.7.789
Interval-valued fuzzy sets were suggested for the first time by Gorzalczang(1983) and Turken(19a6). Based on this, Wang and Li offended their operations on interval-valued fuzzy numbers. Recently, Hong(2002) generalized results of Wang and Li and extended to interval-valued fuzzy sets with Riemann integral. In this paper, using Choquet integrals with respect to a fuzzy measure instead of Riemann integrals with respect to a classical measure, we define a Choquet distance measure for interval-valued fuzzy numbers and investigate its properties.
An XML-based Content Management System supporting Dynamic Content Caching
Koo Heung-Seo ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 794~799
DOI : 10.5391/JKIIS.2005.15.7.794
In this paper, We describe the XML-based Web content management system that supports the efficient dynamic content publishing environment. EasyCM is designed based on Cocoon2 that is the XML publishing framework. We propose the publishing mechanism to support the efficient dynamic content publishing environment to expand into the available dynamic content caching to Cocoon2. Publishing mechanism of EasyCM draws XML object from content repository, associates XML with XSLT, creates and caches content components preprocessing HTML transformation process, and publish web pages constructed into cached content component. For supporting more efficient caching, EasyCM supports also content component update, two update method that is immediately-update and delay-update for updated content component.
Fuzzy Neural Network Model Using Asymmetric Fuzzy Learning Rates
Kim Yong-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 800~804
DOI : 10.5391/JKIIS.2005.15.7.800
This paper presents a fuzzy learning rule which is the fuzzified version of LVQ(Learning Vector Quantization). This fuzzy learning rule 3 uses fuzzy learning rates. instead of the traditional learning rates. LVQ uses the same learning rate regardless of correctness of classification. But, the new fuzzy learning rule uses the different learning rates depending on whether classification is correct or not. The new fuzzy learning rule is integrated into the improved IAFC(Integrated Adaptive Fuzzy Clustering) neural network. The improved IAFC neural network is both stable and plastic. The iris data set is used to compare the performance of the supervised IAFC neural network 3 with the performance of backprogation neural network. The results show that the supervised IAFC neural network 3 is better than backpropagation neural network.
Fuzzy Inductive Learning System for Learning Preference of the User's Behavior Pattern
Lee Hyong-Euk ; Kim Yong-Hwi ; Park Kwang-Hyun ; Kim Yong-Su ; June Jin-Woo ; Cho Joonmyun ; Kim MinGyoung ; Bien Z. Zenn ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 805~812
DOI : 10.5391/JKIIS.2005.15.7.805
Smart home is one of the ubiquitous environment platforms with various complex sensor-and-control network. In this paper, a now learning methodology for learning user's behavior preference pattern is proposed in the sense of reductive user's cognitive load to access complex interfaces and providing personalized services. We propose a fuzzy inductive learning methodology based on life-long learning paradigm for knowledge discovery, which tries to construct efficient fuzzy partition for each input space and to extract fuzzy association rules from the numerical data pattern.
Human Ear Detection for Biometries
Kim Young-Baek ; Rhee Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 813~816
DOI : 10.5391/JKIIS.2005.15.7.813
Ear detection is an important part of an non-invasive ear recognition system. In this paper we propose human ear detection from side face images. The proposed method is made by imitating the human recognition process using feature information and color information. First, we search face candidate area in an input image by using 'skin-color model' and try to find an ear area based on edge information. Then, to verify whether it is the ear area or not, we use the SVM (Support Vector Machine) based on a statistical theory. The method shows high detection ratio in indoors environment with stable illumination.
Object Relationship Modeling based on Bayesian Network Integration for Improving Object Detection Performance of Service Robots
Song Youn-Suk ; Cho Sung-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 817~822
DOI : 10.5391/JKIIS.2005.15.7.817
Recently tile study that exploits visual information for tile services of robot in indoor environments is active. Conventional image processing approaches are based on the pre-defined geometric models, so their performances are likely to decrease when they are applied to the uncertain and dynamic environments. For this, diverse researches to manage the uncertainty based on the knowledge for improving image recognition performance have been doing. In this paper we propose a Bayesian network modeling method for predicting the existence of target objects when they are occluded by other ones for improving the object detection performance of the service robots. The proposed method makes object relationship, so that it allows to predict the target object through observed ones. For this, we define the design method for small size Bayesian networks (primitive Bayesian netqork), and allow to integrate them following to the situations. The experiments are performed for verifying the performance of constructed model, and they shows
of accuracy in 5 places.
Development of Reconfigurable and Evolvable Architecture for Intelligence Implement
Na Jin Hee ; Ahn Ho Seok ; Park Myoung Soo ; Choi Jin Young ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 823~827
DOI : 10.5391/JKIIS.2005.15.7.823
Many researches on intelligent system have been performed and various intelligent algorithms have been developed, which are effective under an assumed specific environment and purpose. But in an real environment, the Performance of these algorithms can be largely degraded. In this paper, we proposed an Evolvable and Reconfigurable(ERI) Architecture based on intelligent Macro Core(IMC) so that various and new algorithms can be easily added incrementally and construct the reconfigured intelligent system easily. We apply the proposed ERI Architecture to face detection and recognition system to show its usefulness.
Fuzzy Kernel K-Nearest Neighbor Algorithm for Image Segmentation
Choi Byung-In ; Rhee Chung-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 828~833
DOI : 10.5391/JKIIS.2005.15.7.828
Kernel methods have shown to improve the performance of conventional linear classification algorithms for complex distributed data sets, as mapping the data in input space into a higher dimensional feature space(7). In this paper, we propose a fuzzy kernel K-nearest neighbor(fuzzy kernel K-NN) algorithm, which applies the distance measure in feature space based on kernel functions to the fuzzy K-nearest neighbor(fuzzy K-NN) algorithm. In doing so, the proposed algorithm can enhance the Performance of the conventional algorithm, by choosing an appropriate kernel function. Results on several data sets and segmentation results for real images are given to show the validity of our proposed algorithm.
A mixed-initiative conversational agent for ubiquitous home environments
Song In-Jee ; Hong Jin-Hyuk ; Cho Sung-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 834~839
DOI : 10.5391/JKIIS.2005.15.7.834
When a great variety of services become available to user through the broadband convergence network in the ubiquitous home environment, an intelligent agent is required to deal with the complexity of services and perceive intension of a user. Different from the old-fashioned command-based user interface for selecting services, conversation enables flexible and rich interactions between human and agents, but diverse expressions of the user's background and context make conversation hard to implement by using either user-initiative or system-initiative methods. To deal with the ambiguity of diverse expressions between user and agents, we have to apply hierarchial bayesian networks for the mixed initiative conversation. Missing information from user's query is analyzed by hierarchial bayesian networks to inference the user's intension so that can be collected through the agent's query. We have implemented this approach in ubiquitous home environment by implementing simulation program.
An Intelligence P2P Mobile Agent System to learn Real-time Users' Tendency in Ubiquitous Environment
Yun Hyo-Gun ; Lee Sang-Yong ; Kim Chang-Suk ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 840~845
DOI : 10.5391/JKIIS.2005.15.7.840
Intelligent agents to learn users' tendency have learn uscrs' tendency by sufficient users information and training time. When the intelligent agents is used in ubiquitous environment, users must wait for intelligent agents to learn, so user may be can't get proper services. In this paper we proposed an intelligent P2P mobile agent system that can learn users' tendency in real-time by sharing users' resource. The system shared users contexts on four places and made feel groups which was composed of similar users. When users' service which had the highest correlation coefficient in the peer groups was suggested, users were satisfied over
A Study on GA-based Optimized Polynomial Neural Networks and Its Application to Nonlinear Process
Kim Wan-Su ; Lee In-Tae ; Oh Sung-Kwun ; Kim Hyun-Ki ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 846~851
DOI : 10.5391/JKIIS.2005.15.7.846
In this paper, we propose Genetic Algorithms(GAs)-based Optimized Polynomial Neural Networks(PNN). The proposed algorithm is based on Group Method of Data Handling(GMDH) method and its structure is similar to feedforward Neural Networks. But the structure of PNN is not fixed like in conventional neural networks and can be generated in a dynamic manner. As each node of PNN structure, we use several types of high-order polynomial such as linear, quadratic and modified quadratic, and it is connected as various kinds of multi-variable inputs. The conventional PNN depends on the experience of a designer that select the number of input variables, input variable and polynomial type. Therefore it is very difficult to organize optimized network. The proposed algorithm leads to identify and select the number of input variables, input variable and polynomial type by using Genetic Algorithms(GAs). The aggregate performance index with weighting factor is proposed as well. The study is illustrated with tile NOx omission process data of gas turbine power plant for application to nonlinear process. In the sequel the proposed model shows not only superb predictability but also high accuracy in comparison to the existing intelligent models.
Extraction of Human Body Using Hybrid Silhouette Extraction Method in Intelligent Robot System
Kim Moon Hwan ; Joo Young Hoon ; Park Jin Bae ; Cho Young Jo ; Chi Su Young ; Kim hye Jin ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 852~857
DOI : 10.5391/JKIIS.2005.15.7.852
This paper discusses a human body extraction method for intelligent robot system. The intelligent robot system requires more robust silhouette extraction method because it has internal vibration and low resolution. The new hybrid silhouette extraction method is proposed to overcome this constrained environment. The temporal and gradient information is combined as hybrid silhouette. The motion region model is used to adjust combining parameters in hybrid silhouette. Finally, the experimental results show the superiority of the proposed method.
Development of Directed Diffusion Algorithm with Enhanced Performance
Kim Sung-Ho ; Kim Si-Hwan ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 858~863
DOI : 10.5391/JKIIS.2005.15.7.858
Sensor network is subject to novel problems and constraints because it is composed of thousands of tiny devices with very limited resources. The large number of motes in a sensor network means that there will be some failing nodes owing to the lack of battery in sensor nodes. Therefore, it is imperative to save the energy as much as possible. In this work, we propose energy efficient routing algorithm which is based on directed diffusion scheme. In the proposed scheme, some overloads required for reinforcing the gradient path can be effectively eliminated. Furthermore, in order to verify the usefulness of the proposed algorithm, several simulations are executed.
Implementation of Negotiation based Personalized Digital Library System
Cho, Young-Im ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 864~869
DOI : 10.5391/JKIIS.2005.15.7.864
Design and Theoretic Analysis of 3D Tactile Sensor
Sim Kwee-Bo ; Hwang Han-Kun ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 870~874
DOI : 10.5391/JKIIS.2005.15.7.870
This paper presents capacitive tactile sensor that can detect normal and shear forces. This tactile sensor consists of index plate, sensing plate, and elastic dielectric layer. The calculated sensing character is based on the changes of space between two horizontal plate. Larger overlap areas and narrow space between top and bottom plate guarantees higher sensitivity. Tactile sense information can be calculated from the changes of phase of output signal. The symmetric arrangement of sensing plates makes the manufacturing process easier and guarantees the stability of the structure. In this paper, the sensor structure is designed, the mechanism of the Proposed sensor is theoretically explained, and the simulated result is presented.
Integration of OWL and SWRL Inference using Jess
Lee Ki-Chul ; Lee Jee-Hyong ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 875~880
DOI : 10.5391/JKIIS.2005.15.7.875
OWL(Web Ontology Language) is the Ontology Standard Language and the a lot of Ontologies are being constructed in OWL. But the research on the extension of OWL is also progressing because of the limit of representation power of in OWL language. The W3C suggests the SWRL(Semantic Web Rule Language) based on the combination of OWL and RuleML(Rule Markup Language), which is improved in the representation of rule. Thus, both OWL and SWRL are used for developing ontologies. However, research on inference of ontologies written in both languages is just begun. These day, for the inference of ontologies written in both languages, ontologies and divided in to two parts. The part written in OWL and written in SWRL. For the inference of the part written in OWL, Racer, a DL based inference engine, is used and for the other part Jess, a rule-based engine, is used. In this paper, we will propose three methods for integrated inference of the OWL part and the SWRL part of ontologies using Jess and some tools for ontology inference : OWLJessKB and SWRL Factory
Intelligent Digital Redesign for Uncertain Nonlinear Systems Using Power Series
Sung Hwa Chang ; Park Jin Bae ; Go Sung Hyun ; Joo Young Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 881~886
DOI : 10.5391/JKIIS.2005.15.7.881
This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.
A Real-time Service Recommendation System using Context Information in Pure P2P Environment
Lee Se-Il ; Lee Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 887~892
DOI : 10.5391/JKIIS.2005.15.7.887
Under pure P2P environments, collaborative filtering must be provided with only a few service items by real time information without accumulated data. However, in case of collaborative filtering with only a few service items collected locally, quality of recommended service becomes low. Therefore, it is necessary to research a method to improve quality of recommended service by users' context information. But because a great volume of users' context information can be recognized in a moment, there can be a scalability problem and there are limitations in supporting differentiated services according to fields and items. In this paper, we solved the scalability problem by clustering context information Per each service field and classifying il per each user, using SOM. In addition, we could recommend proper services for users by measuring the context information of the users belonging to the similar classification to the service requester among classified data and then using collaborative filtering.
Robot Locomotion via RLS-based Actor-Critic Learning
Kim, Jong-Ho ; Kang, Dae-Sung ; Park, Joo-Young ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 7, 2005, Pages 893~898
DOI : 10.5391/JKIIS.2005.15.7.893
Due to the merits that only a small amount of computation is needed for solutions and stochastic policies can be handled explicitly, the actor-critic algorithm, which is a class of reinforcement learning methods, has recently attracted a lot of interests in the area of artificial intelligence. The actor-critic network composes of tile actor network for selecting control inputs and the critic network for estimating value functions, and in its training stage, the actor and critic networks take the strategy, of changing their parameters adaptively in order to select excellent control inputs and yield accurate approximation for value functions as fast as possible. In this paper, we consider a new actor-critic algorithm employing an RLS(Recursive Least Square) method for critic learning, and policy gradients for actor learning. The applicability of the considered algorithm is illustrated with experiments on the two linked robot arm.