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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 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
Selecting the target year
Topic directed Web Spidering using Reinforcement Learning
Lim, Soo-Yeon ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 395~399
DOI : 10.5391/JKIIS.2005.15.4.395
In this paper, we presents HIGH-Q learning algorithm with reinforcement learning for more fast and exact topic-directed web spidering. The purpose of reinforcement learning is to maximize rewards from environment, an reinforcement learning agents learn by interacting with external environment through trial and error. We performed experiments that compared the proposed method using reinforcement learning with breath first search method for searching the web pages. In result, reinforcement learning method using future discounted rewards searched a small number of pages to find result pages.
A Face Recognition System using Eigenfaces: Performance Analysis
Kim, Young-Lae ; Wang, Bo-Hyeun ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 400~405
DOI : 10.5391/JKIIS.2005.15.4.400
This paper analyzes the performance of a face recognition algorithm using the eigenfaces method. In the absence of robust personal recognition schemes, a biometric recognition system has essentially researched to improve their shortcomings. A face recognition system in biometries is widely researched in the field of computer vision and pattern recognition, since it is possible to comprehend intuitively our faces. The proposed system projects facial images onto a feature space that effectively expresses the significant variations among known facial images. The significant features are known as `eigenfaces`, because they are the eigenvectors(principal components) of the set of faces. The projection operation characterizes an individual face by a weighted sum of the eigenface features, and to recognize a particular face it is necessary only to compare these weights to those of known individuals. In order to analyze the performance of the system, we develop a face recognition system by using Harvard database in Harvard Robotics Laboratory. We present the recognition rate according to variations on the lighting condition, numbers of the employed eigenfaces, and existence of a pre-processing step. Finally, we construct a rejection curve in order to investigate the practicability of the recognition method using the eigenfaces.
Area-Based Q-learning Algorithm to Search Target Object of Multiple Robots
Yoon, Han-Ul ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 406~411
DOI : 10.5391/JKIIS.2005.15.4.406
In this paper, we present the area-based Q-learning to search a target object using multiple robot. To search the target in Markovian space, the robots should recognize their surrounding at where they are located and generate some rules to act upon by themselves. Under area-based Q-learning, a robot, first of all, obtains 6-distances from itself to environment by infrared sensor which are hexagonally allocated around itself. Second, it calculates 6-areas with those distances then take an action, i.e., turn and move toward where the widest space will be guaranteed. After the action is taken, the value of Q will be updated by relative formula at the state. We set up an experimental environment with five small mobile robots, obstacles, and a target object, and tried to search for a target object while navigating in a unknown hallway where some obstacles were placed. In the end of this paper, we presents the results of three algorithms - a random search, area-based action making (ABAM), and hexagonal area-based Q-teaming.
Teleoperation of an Internet-Based Mobile Robot with Network Latency
Shin, Jik-Su ; Joo, Moon-Gab ; Kang, Geun-Taek ; Lee, Won-Chang ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 412~417
DOI : 10.5391/JKIIS.2005.15.4.412
The Internet has been widely applied to the remote control system. The network-based control system, however, has a random time delay and an inherent weak point of the network, when the data ate transmitted. The network delay may result in performance degradation or even system instability in teleoperation. In this paper a prediction model of network delay using TSK (Takagi-Sugeno-Kang) fuzzy model is presented. An adaptive scheme is developed to update the prediction model according to the current network status. The prediction model is applied to the control of an Internet-based mobile robot to show its usefulness. In the computer simulation the TSK Prediction model of network delay is proven superior to the conventional algorithms.
An Route Planning for the Navigation System of Autonomous vessel
Cho, Jae-Hee ; Ji, Min-Su ; Kim, Yong-Gi ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 418~424
DOI : 10.5391/JKIIS.2005.15.4.418
For the safety and cost reduction of the navigation in the sea, we need automatic and intelligent system for the ship. For the ship automation, we need a route planning based on GPS and the nautical chart. In this paper, we propose a route planning technique using point of contact of the obstacle and treecreation technique. The efficiency of the proposed technique is proved by comparing with A* search technique that is the most famous search technique for route planning from the optimal point of view.
A Distributed Path-Finding Algorithm for Distributed Metabolic Pathways
Lee, Sun-A ; Lee, Keon-Myung ; Lee, Seung-Joo ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 425~430
DOI : 10.5391/JKIIS.2005.15.4.425
Many problems can be formulated in terms nf graphs and thus solved by graph-theoretic algorithms. This paper is concerned with finding paths between nodes over the distributed and overlapped graphs. The proposed method allows multiple agents to cooperate to find paths without merging the distributed graphs. For each graph there is a designated agent which is charged of providing path-finding service for hot graph and initiating the path-finding tasks of which path starts from the graph. The proposed method earlier on constructs an abstract graph so-called viewgraph for the distributed overlapped graphs and thus enables to extract the information about how to guide the path finding over the graphs. The viewgraph is shared by all agents which determine how to coordinate other agents for the purpose of finding paths. Each agent maintains the shortest path information among the nodes which are placed in different overlapped subgraphs of her graph. Once an agent is asked to get a path from a node on her graph to another node on another`s graph, she directs other agents to provide the necessary information for finding paths.
Defect Analysis of the SBR Wastewater Treatment Plant for Unmanned Automation Based on Time-series Data Mining
Bae, Hyeon ; Choi, Dae-Won ; Cheon, Seong-Pyo ; Kim, Sung-Shin ; Kim, Ye-Jin ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 431~436
DOI : 10.5391/JKIIS.2005.15.4.431
This paper describes how to diagnose SBR plant equipment using time-series data mining. It shows the equipment diagnostics based upon vibration signals that are acquired front each device lot process control. Data transform techniques including two data preprocessing skills and data mining methods were employed in the data analysis. The proposed method is not only suitable for SBR equipment, but is also suitable for other Industrial devices. The experimental results performed on a lab-scale SBR plant show a good equip-ment-management performance.
Web-Based Forecasting System for Flood Runoff with Neural Network
Hang, Dong-Guk ; Jun, Kye-Won ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 437~442
DOI : 10.5391/JKIIS.2005.15.4.437
The forecasting of flood runoff in the river is essential for flood control. The purpose of this study is to test a development of system for flood runoff forecasting using neural network model. For the flood events the tested rainfall and runoff data were the input to the input layer and the flood runoff data were used in the output layer To choose the forecasting model which would make up of runoff forecasting system properly, real-time runoff in the river when flood periods were forecasted by using the neural network model and the state-space model. A comparison of the results obtained by the two forecasting models indicated the superiority and reliability of the neural network model over the state-space model. The neural network model was modified to work in the Web and developed to be the basic model of the forecasting system for the flood runoff.
Design & Evaluation of an Intelligent Model for Extracting the Web User` Preference
Kim, Kwang-Nam ; Yoon, Hee-Byung ; Kim, Hwa-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 443~450
DOI : 10.5391/JKIIS.2005.15.4.443
In this paper, we propose an intelligent model lot extraction of the web user`s preference and present the results of evaluation. For this purpose, we analyze shortcomings of current information retrieval engine being used and reflect preference weights on learner. As it doesn`t depend on frequency of each word but intelligently learns patterns of user behavior, the mechanism Provides the appropriate set of results about user`s questions. Then, we propose the concept of preference trend and its considerations and present an algorithm for extracting preference with examples. Also, we design an intelligent model for extraction of behavior patterns and propose HTML index and process of intelligent learning for preference decision. Finally, we validate the proposed model by comparing estimated results(after applying the Preference) of document ranking measurement.
The Navigation Control for Intelligent Robot Using Genetic Algorithms
Joo, Young-Hoon ; Cho, Sang-Kyun ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 451~456
DOI : 10.5391/JKIIS.2005.15.4.451
In this paper, we propose the navigation control method for intelligent robot using messy genetic algorithm. The fuzzy controller design for navigation of the intelligent robot was dependant on expert`s knowledge. But, the parameters of the fuzzy logic controller obtained from expert`s control action may not be outimal. In this paper, to solve the above problem, we propose the identification method to automatically tune the number of fuzzy rule and parameters of memberships of fuzzy controller using mGA. Finally, to show and evaluate the generality and feasibility of the proposed method, we provides some simulations for wall following navigation of intelligent robot.
A Study on Wavelet Neural Network Based Generalized Predictive Control for Path Tracking of Mobile Robots
Song, Yong-Tae ; Oh, Joon-Seop ; Park, Jin-Bae ; Choi, Yoon-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 457~466
DOI : 10.5391/JKIIS.2005.15.4.457
In this paper, we propose a wavelet neural network(WNN) based predictive control method for path tracking of mobile robots with multi-input and multi-output. In our control method, we use a WNN as a state predictor which combines the capability of artificial neural networks in learning processes and the capability of wavelet decomposition. A WNN predictor is tuned to minimize errors between the WNN outputs and the states of mobile robot using the gradient descent rule. And control signals, linear velocity and angular velocity, are calculated to minimize the predefined cost function using errors between the reference states and the predicted states. Through a computer simulation for the tracking performance according to varied track, we demonstrate the efficiency and the feasibility of our predictive control system.
A Comparative Study on Image Enhancement Methods for Low Contrast Images
Kim, Yong-Soo ; Kim, Nam-Jin ; Lee, Se-Yul ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 467~472
DOI : 10.5391/JKIIS.2005.15.4.467
The principal objective of enhancement methods is to process an image so that the output image is more suitable than the original image lot a specific application. Images taken in the night can be low-contrast images because of poor environments. In this paper, we compared the performance of Image Contrast Enhancement Technique Using Clustering Algorithm(ICECA) with those of color adjustment methods such as Histogram Equalization(HE), Brightness Preserving Bi-Histogram Equalization(BBHE), and the Multi-Scale Refiner(MSR). We compared these methods by applying the image enhancement methods to a set of diverse images.
Analysis System of Endoscopic Image of Early Gastric Cancer
Kim, Kwang-Baek ; Lim, Eun-Kyung ; Kim, Gwang-Ha ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 473~478
DOI : 10.5391/JKIIS.2005.15.4.473
The gastric cancer takes the great part of the cancer occurrence and the mortality from cancer in Korea, and the early detection of gastric cancer is very important in the treatment and convalescence. This paper. for the early detection of gastric cancer, Proposes the analysis system of endoscopic image of the stomach that detects the abnormal region by using the change of color in the image and provides the surface tissue information to the detector. While the advanced inflammation and the cancer may be easily detected, the early inflammation and the cancer have a difficulty in detection and require the more attention lot detection. This paper, at first, converts the endoscopic image to the Image of IHb(Index of Hemoglobin) model and removes noises incurred by illumination, and next, automatically detects the regions suspected as cancer and provides the related information to the detector, or provides the surface tissue information for the regions appointed by the detector. This paper does not intend to provide the final diagnosis of the detected abnormal regions as gastric cancer, but provides the supplementary mean that reduces the load and mistaken diagnosis of the detector by automatically detecting the abnormal regions being not easily detected by human eyes and providing the additional information for the diagnosis. The experiments using practical endoscopic images for performance evaluation showed that the proposed system is effective in the analysis of endoscopic image of the stomach.
The Structure of 3-Tirer Context-awareness Processing Server/client based Intelligent Agents
Yun, Hyo-Gun ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 479~485
DOI : 10.5391/JKIIS.2005.15.4.479
Recently, computing technology requires intelligent system structures for context-awareness in ubiquitous computing environment. An intelligent system for context-awareness is based on agents, and need sensor information to recognize users and frames to support service. Therefore, this paper proposes the structure of 3-tier context-awareness processing server/client that can connect dynamically with each sensor and service, and support various context stably The structure of a proposal system is composed of a client class that recognizes uses` context information, a server class that processes realized context information by an application processing agent, and a management server that manages these two classes. Also, in this structure users information is composed of dynamic profile to support exquisite service.
Home Automation System using Intelligent Mobile Robot
Ahn, Ho-Seok ; Choi, Jin-Young ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 486~491
DOI : 10.5391/JKIIS.2005.15.4.486
This paper proposes the system model that is more efficient and active than formal home automation system and it can conquer the limits of formal one using intelligent mobile robot. This system uses specialized intelligent mobile robot for home environment and the robot moves around home instead of human. We call the system model to HAuPIRS (Home Automation system using PDA based Intelligent Robot System). HAuPIRS control architecture is composed three parts and each part is User Level, Cognitive Level, Executive Level. It is easy to use system and possible to extend the home apparatus from new technology. We made the PBMoRo System (PDA Based Mobile Robot System) based on HAuPIRS architecture and verified the efficiency of the system model.
PCA-based Feature Extraction using Class Information
Park, Myoung-Soo ; Na, Jin-Hee ; Choi, Jin-Young ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 492~497
DOI : 10.5391/JKIIS.2005.15.4.492
Feature extraction is important to classify data with large dimension such as image data. The representative feature extraction methods lot feature extraction ate PCA, ICA, LDA and MLP, etc. These algorithms can be classified in two groups: unsupervised algorithms such as PCA, LDA, and supervised algorithms such as LDA, MLP. Among these two groups, supervised algorithms are more suitable to extract the features for classification because of the class information of input data. In this paper we suggest a new feature extraction algorithm PCA-FX which uses class information with PCA to extract ieatures for classification. We test our algorithm using Yale face database and compare the performance of proposed algorithm with those of other algorithms.
A New Path Control Algorithm for Underwater Robots Using Fuzzy Logic
Kwon, Kyoung-Youb ; Joung, Tae-Whee ; Jo, Joong-Seon ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 498~504
DOI : 10.5391/JKIIS.2005.15.4.498
A fuzzy logic for collision avoidance of underwater robots is proposed in this paper. The VFF(Virtual Force Field) method, which is widely used in the field of mobile robots, is modified for application to the autonomous navigation of underwater robots. This Modified Virtual Force Field(MVFF) method using the fuzzy logic can be used in either track keeping or obstacle avoidance. Fuzzy logics are devised to handle various situations which can be faced during autonomous navigation of underwater robots. The obstacle avoidance algorithm has the ability to handle multiple static obstacles. Results of simulation show that the proposed method can be efficiently applied to obstacle avoidance of the underwater robots.
Robot Control via RPO-based Reinforcement Learning Algorithm
Kim, Jong-Ho ; Kang, Dae-Sung ; Park, Joo-Young ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 505~510
DOI : 10.5391/JKIIS.2005.15.4.505
The RPO(randomized policy optimizer) algorithm, which utilizes probabilistic policy for the action selection, is a recently developed tool in the area of reinforcement learning, and has been shown to be very successful in several application problems. In this paper, we propose a modified RPO algorithm, whose critic network is adapted via RLS(Recursive Least Square) algorithm. In order to illustrate the applicability of the modified RPO method, we applied the modified algorithm to Kimura`s robot and observed very good performance. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms on the acceleration or the robot movement were observed.
The fuzzy linear maps
Kim, Chang-Bum ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 511~513
DOI : 10.5391/JKIIS.2005.15.4.511
We investigate some situations in connection with two exact sequences of fuzzy linear maps.
T-upper approximation spaces
Kim, Yong-Chan ; Ko, Jung-Mi ;
Journal of Korean Institute of Intelligent Systems, volume 15, issue 4, 2005, Pages 514~519
DOI : 10.5391/JKIIS.2005.15.4.514
We define extensional spaces. Moreover, we investigate the relations among T-upper-approximation spaces, T-quasi -equivalence relations and extensional spaces.