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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 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
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A Method of Supervised Word Sense Disambiguation Using Decision Lists Based on Syntactic Clues
Kim, Kweon-Yang ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 125~130
DOI : 10.5391/JKIIS.2003.13.2.125
This paper presents a simple method of supervised word sense disambiguation using decision lists based on syntactic clues. This approach focuses on the syntactic relations between the given ambiguous word and surrounding words in context for resolving a given sense ambiguity. By identifying and utilizing only the single best disambiguation evidence in a given context instead of combining a set of clues, the algorithm decides the correct sense. Experiments with 10 Korean verbs show that adding syntactic clues to a basic set of surrounding context words improves 33% higher performance than baseline accuracy. In addition, our method using decision lists is 3% higher than a method using integration of all disambiguation evidences.
A DNA Coding-Based Intelligent Kalman Filter for Tracking a Maneuvering Target
Lee, Bum-Jik ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 131~136
DOI : 10.5391/JKIIS.2003.13.2.131
The problem of maneuvering target tracking has been studied in the field of the state estimation over decades. The Kalman filter has been widely used to estimate the states of the target, but in the presence of a maneuver, its performance may be seriously degraded. In this paper, to solve this problem and track a maneuvering target effectively, DNA coding-based intelligent Kalman filter (DNA coding-based IKF) is proposed. The proposed method can overcome the mathematical limits of conventional methods and can effectively track a maneuvering target with only one filter by using the fuzzy logic based on DNA coding method. The tracking performance of the proposed method is compared with those of the adaptive interacting multiple model (AIMM) method and the GA-based IKF in computer simulations.
Fuzzy Control and Implementation of a 3-Dimensional Inverted Pendulum System
Shin, Ho-Sun ; Chu, Jun-Uk ; Lee, Seung-Ha ; Lee, Yun-Jung ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 137~147
DOI : 10.5391/JKIIS.2003.13.2.137
The fuzzy control and implementation of a new three-dimensional(3-D) inverted pendulum system are addressed. In comparison with conventional 1-D and 2-D systems, the 3-D inverted pendulum system is a proper benchmark system to simulate human's control action which includes the up and down motion to stabilize an inverted pendulum. To investigate the characteristics of the 3-D inverted pendulum system and to design of a fuzzy controller, we derive dynamic equations of the mechanism including a 3-axis cartesian robot and an inverted pendulum. We propose a design method of a fuzzy controller of the yaw and pitch angles of an inverted pendulum. In the design, the redundant degree-of-freedom(DOF) of the robot and the constrained workspace are taken into account. The performance of the proposed system is proved by experimental results using a developed PC-based Multi-Motion Control(MMC) board.
A Study on Network based Intelligent Intrusion Prevention model by using Fuzzy Cognitive Maps on Denial of Service Attack
Lee, Se-Yul ; Kim, Yong-Soo ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 148~153
DOI : 10.5391/JKIIS.2003.13.2.148
A DoS(Denial of Service) attack appears in the form of the intrusion attempt and Syn Flooding attack is a typical example. The Syn Flooding attack takes advantage of the weak point of 3-way handshake between the end-points of TCP which is the connection-oriented transmission service and has the reliability This paper proposes a NIIP(Network based Intelligent Intrusion Prevention) model. This model captures and analyzes the packet informations for the detection of Syn Flooding attack. Using the result of analysis of decision module, the decision module, which utilizes FCM(Fuzzy Cognitive Maps), measures the degree of danger of the DoS and trains the response module to deal with attacks. This model is a network based intelligent intrusion prevention model that reduces or prevents the danger of Syn Flooding attack.
Image Pattern Classification and Recognition by Using the Associative Memory with Cellular Neural Networks
Shin, Yoon-Cheol ; Park, Yong-Hun ; Kang, Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 154~162
DOI : 10.5391/JKIIS.2003.13.2.154
In this paper, Associative Memory with Cellular Neural Networks classifies and recognizes image patterns as an operator applied to image process. CNN processes nonlinear data in real-time like neural networks, and made by cell which communicates with each other directly through its neighbor cells as the Cellular Automata does. It is applied to the optimization problem, associative memory, pattern recognition, and computer vision. Image processing with CNN is appropriate to 2-D images, because each cell which corresponds to each pixel in the image is simultaneously processed in parallel. This paper shows the method for designing the structure of associative memory based on CNN and getting output image by choosing the most appropriate weight pattern among the whole learned weight pattern memories. Each template represents weight values between cells and updates them by learning. Hebbian rule is used for learning template weights and LMS algorithm is used for classification.
Flame Detection of Steam Boilers using Neural Networks and Image Information
Bae, Hyeon ; Park, Dong-Jae ; Ahan, Hang-Bae ; Kim, Sung-Shin ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 163~168
DOI : 10.5391/JKIIS.2003.13.2.163
Several equipments for flame detection are employed in the power generations. But these flame detectors have some problems for the correct performance. So in this paper, we apply different techniques for the flame detection. Image processing techniques are broadly applied in industrial fields. In this paper, the image information is recorded by a camcoder and then these images are preprocessed for the input values of neural network model. We can test and evaluate the approach that uses image information for the flame detection of burners. If this technique is implemented in physical plant, the economical and effective operation could be achieved.
Adaptive Intrusion Detection Algorithm based on Artificial Immune System
Sim, Kwee-Bo ; Yang, Jae-Won ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 169~174
DOI : 10.5391/JKIIS.2003.13.2.169
The trial and success of malicious cyber attacks has been increased rapidly with spreading of Internet and the activation of a internet shopping mall and the supply of an online, or an offline internet, so it is expected to make a problem more and more. The goal of intrusion detection is to identify unauthorized use, misuse, and abuse of computer systems by both system insiders and external penetrators in real time. In fact, the general security system based on Internet couldn't cope with the attack properly, if ever. other regular systems have depended on common vaccine softwares to cope with the attack. But in this paper, we will use the positive selection and negative selection mechanism of T-cell, which is the biologically distributed autonomous system, to develop the self/nonself recognition algorithm and AIS (Artificial Immune System) that is easy to be concrete on the artificial system. For making it come true, we will apply AIS to the network environment, which is a computer security system.
Convergence Conditions of Iterative Learning Control in the Frequency Domain
Doh, Tae-Yong ; Moon, Jung-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 175~179
DOI : 10.5391/JKIIS.2003.13.2.175
Convergence condition determines performance of iterative learning control (ILC), for example, convergence speed, remaining error, etc. Hence, the performance can be elevated and a feasible set of learning controllers grows if a less conservative condition is obtained. In the frequency domain, the
norm of the transfer function between consecutive errors has been currently used to test convergence of a learning system. However, even if the convergence condition based on the
norm has a clear property about monotonic convergence, it has a few drawbacks, especially in MIMO plants. In this paper, the relation between the condition and the monotonicity of convergence is clarified and a modified convergence condition is found out using a frequency domain Lyapunov equation, which supersedes the conventional one in the frequency domain.
Navigation of Autonomous Mobile Robot with Intelligent Controller
Choi, Jeong-Won ; Kim, Yeon-Tae ; Lee, Suk-Gyu ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 180~185
DOI : 10.5391/JKIIS.2003.13.2.180
This paper proposes an intelligent navigation algorithm for multiple mobile robots under unknown dynamic environment. The proposed algorithm consists of three basic parts as follows. The first part based on the fuzzy rule generates the turning angle and moving distance of the robot for goal approach without obstacles. In the second part, using both fuzzy and neural network, the angle and distance of the robot to avoid collision with dynamic and static obstacles are obtained. The final adjustment of the weighting factor based on fuzzy rule for moving and avoiding distance of the robots is provided in the third stage. The experiments which demonstrate the performance of the proposed intelligent controller is described.
Mobile robot control by MNN using optimal EN
Choi, Woo-Kyung ; Kim, Seong-Joo ; Seo, Jae-Yong ; Jeon, Hong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 186~191
DOI : 10.5391/JKIIS.2003.13.2.186
Skills in tracing of the MR divide into following, approaching, avoiding and warning and so on. It is difficult to have all these skills learned as neural network. To make this up for, skills consisted of each module, and Mobile Robot was controlled by the output of module adequate for the situation. A mobile Robot was equipped multi-ultrasonic sensor and a USB Camera, which can be in place of human sense, and the measured environment information data is learned through Modular Neural Network. MNN consisted of optimal combination of activation function in the Expert Network and its structure seemed to improve learning time and errors. The Gating Network(GN) used to control output values of the MNN by switching for angle and speed of the robot. In the paper, EN of Modular Neural network was designed optimal combination. Traveling with a real MR was performed repeatedly to verity the usefulness of the MNN which was proposed in this paper. The robot was properly controlled and driven by the result value and the experimental is rewarded with good fruits.
A Negotiation Mechanism for BDI Agents in Distributed Cooperative Environments
Lee, Myung-Jin ; Kim, Jin-Sang ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 192~199
DOI : 10.5391/JKIIS.2003.13.2.192
Agents in multi-agent systems (MAS ) are required to achieve their own goals. An agent s goal, however, can conflict with others either when agents compete with each other to achieve a common goal or when they have to use a set of limited resources to accomplish agents divergent goals. In either case, agents need to be designed to reach a mutual acceptable state where they can avoid any goal conflicts through negotiation with others to achieve their goals. In this paper, we consider a BDI agent architecture where belief, desire, and intention are the three major components for agents mental attitudes and represent resource-bounded BDI agents in logic programming framework. We propose a negotiation algorithm for BDI agents solving their problems without goal conflicts in distributed cooperative environments. Finally, we describe a simple scenario to show the effectiveness of the negotiation algorithm implemented in a negotiation meta-language.
Separations and Feature Extractions for Image Signals Using Independent Component Analysis Based on Neural Networks of Efficient Learning Rule
Cho, Yong-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 200~208
DOI : 10.5391/JKIIS.2003.13.2.200
This paper proposes a separation and feature extraction of image signals using the independent component analysis(ICA) based on neural networks of efficient learning rule. The proposed learning rule is a hybrid fixed-point(FP) algorithm based on secant method and momentum. Secant method is applied to improve the performance by simplifying the 1st-order derivative computation for optimizing the objective function, which is to minimize the mutual informations of the independent components. The momentum is applied for high-speed convergence by restraining the oscillation in the process of converging to the optimal solution. The proposed algorithm has been applied to the composite images generated by random mixing matrix from the 10 images of
-pixel. The simulation results show that the proposed algorithm has better performances of the separation speed and rate than those using the FP algorithm based on Newton and secant method. The proposed algorithm has been also applied to extract the features using a 3 set of 10,000 image patches from the 10 fingerprints of
-pixel and the front and the rear paper money of
-pixel, respectively, The simulation results show that the proposed algorithm has also better extraction speed than those using the another methods. Especially, the 160 basis vectors(features) of
-pixel show the local features which have the characteristics of spatial frequency and oriented edges in the images.
A Construction of Fuzzy Model for Data Mining
Kim, Do-Wan ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 209~215
DOI : 10.5391/JKIIS.2003.13.2.209
A new GA-based methodology using information granules is suggested for the construction of fuzzy classifiers. The proposed scheme consists of three steps: selection of information granules, construction of the associated fuzzy sets, and tuning of the fuzzy rules. First, the genetic algorithm (GA) is applied to the development of the adequate information granules. The fuzzy sets are then constructed from the analysis of the developed information granules. An interpretable fuzzy classifier is designed by using the constructed fuzzy sets. Finally, the GA are utilized for tuning of the fuzzy rules, which can enhance the classification performance on the misclassified data (e.g., data with the strange pattern or on the boundaries of the classes). To show the effectiveness of the proposed method, an example, the classification of the Iris data, is provided.
Emotional Recognition System Using Eigenfaces
Joo, Young-Hoon ; Lee, Sang-Yun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 216~221
DOI : 10.5391/JKIIS.2003.13.2.216
Emotions recognition is a topic on which little research has been done to date. This paper proposes a new method that can recognize the human s emotion from facial image by using eigenspace. To do so, first, we get the face image by using the skin color from the original color image acquired by CCD color camera. Second, we get the vector image which is projected the obtained face image into eigenspace. And then, we propose the method for finding out each person s identification and emotion from the weight of vector image. Finally, we show the practical application possibility of the proposed method through the experiment.
Investigation of the Reliability of Knowledge Source in CLINAID using Fuzzy Relational Method
Noe, Chan-Sook ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 222~230
DOI : 10.5391/JKIIS.2003.13.2.222
Once the medical knowledge-based system has been developed, it is essential to investigate the knowledge sources of the system because knowledge sources can affect the performance of the system in great deal. This paper presents the method and the results of the reliability test done on the medical knowledge-based system CLINAID. A knowledge source tested is Cardiovascular body system data used in CLINAID. The reliability test will be done by investigating structural relationships revealed by fuzzy relational method between the components of the knowledge sources of individual body systems using syndromes as its main component. These partitions are going to be compared with the syndromes elicited from the medical experts. This paper also reports the outcome of the computations using 7 implication operators performed on Cardiovascular body system data.
Notes on the compatibility between defuzzification and t-norm based fuzzy arithmetic operations
Hong, Dug-Hun ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 231~236
DOI : 10.5391/JKIIS.2003.13.2.231
Recently, Oussalah 〔Fuzzy Sets and Systems 128(2002) 247-260〕 investigated some theoretical results about some invariance properties concerning the relationships between the defuzzification outcomes and the arithmetic of fuzzy numbers. But, in this note we introduce some explicit calculations of the resulting fuzzy set or possibility distribution when the matter is the determination of the defuzzified value pertaining to the result of some manipulation of fuzzy quantities under t-norm based fuzzy arithmetic operations.
Adaptive Intrusion Detection System Based on SVM and Clustering
Lee, Han-Sung ; Im, Young-Hee ; Park, Joo-Young ; Park, Dai-Hee ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 237~242
DOI : 10.5391/JKIIS.2003.13.2.237
In this paper, we propose a new adaptive intrusion detection algorithm based on clustering: Kernel-ART, which is composed of the on-line clustering algorithm, ART (adaptive resonance theory), combining with mercer-kernel and concept vector. Kernel-ART is not only satisfying all desirable characteristics in the context of clustering-based IDS but also alleviating drawbacks associated with the supervised learning IDS. It is able to detect various types of intrusions in real-time by means of generating clusters incrementally.
Weak positive implicative hyperBCK-ideal
Kim, Y.H. ; Namkoong, Y.M. ; T.E. Jeong ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 243~246
DOI : 10.5391/JKIIS.2003.13.2.243
In this paper we define a weak positive implicative hyperBCK-ideal of hyperBCK-algebra. Also we investigate that every positive implicative hyperBCK-algebra is a positive implicative hyperK-algebra and then we prove that every positive implicative hyperK-algebra is a weak positive implicative hyperk-algebra.
Design of a pen-shaped input device using the low-cost inertial measurement units
Chang, Wook ; Kang, Kyoung-Ho ; Choi, Eun-Seok ; Bang, Won-Chul ; Potanin, Alexy ; Kim, Dong-Yoon ;
Journal of Korean Institute of Intelligent Systems, volume 13, issue 2, 2003, Pages 247~258
DOI : 10.5391/JKIIS.2003.13.2.247
In this paper, we present a pen-shaped input device equipped with accelerometers and gyroscopes that measure inertial movements when a user writes on 2 or 3 dimensional space with the pen. The measurements from gyroscope are integrated once to find the attitude of the system and are used to compensate gravitational effect in the accelerations. Further, the compensated accelerations are integrated twice to yield the position of the system, whose basic concept stems from the field of inertial navigation. However, the accuracy of the position measurement significantly deteriorates with time due to the integrations involved in recovering the handwriting trajectory This problem is common in the inertial navigation system and is usually solved by the periodic or aperiodic calibration of the system with external reference sources or other information in the filed of inertial navigation. In the presented paper, the calibration of the position or velocity is performed on-line and off-line. In the on-line calibration stage, the complementary filter technique is used, where a Kalman filter plays an important role. In the off-line calibration stage, the constant component of the resultant navigational error of the system is removed using the velocity information and motion detection algorithm. The effectiveness and feasibility of the presented system is shown through the experimental results.