Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Journal of Korean Institute of Intelligent Systems
Journal Basic Information
Journal DOI :
Korean Institute of Intelligent Systems
Editor in Chief :
Volume & Issues
Volume 16, Issue 6 - Dec 2006
Volume 16, Issue 5 - Oct 2006
Volume 16, Issue 4 - Aug 2006
Volume 16, Issue 3 - Jun 2006
Volume 16, Issue 2 - Apr 2006
Volume 16, Issue 1 - Feb 2006
Selecting the target year
Nucleus Segmentation and Recognition of Uterine Cervical Pap-Smears using Enhanced Fuzzy ART Algorithm
Kim, Kwang-Baek ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 519~524
DOI : 10.5391/JKIIS.2006.16.5.519
Segmentation for the region of nucleus in the image of uterine cervical cytodiagnosis is known as the most difficult and important part in the automatic cervical cancer recognition system. In this paper, the region of nucleus is extracted from an image of uterine cervical cytodiagnosis using the fuzzy grey morphology operation. The characteristics of the nucleus are extracted from the analysis of morphemetric features, densitometric features, colormetric features, and textural features based on the detected region of nucleus area. The classification criterion of a nucleus is defined according to the standard categories of the Bethesda system. The enhanced fuzzy ART algorithm is used to the extracted nucleus and the results show that the proposed method is efficient in nucleus recognition and uterine cervical Pap-Smears extraction.
Input Variable Selection by Using Fixed-Point ICA and Adaptive Partition Mutual Information Estimation
Cho, Yong-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 525~530
DOI : 10.5391/JKIIS.2006.16.5.525
This paper presents an efficient input variable selection method using both fixed-point independent component analysis(FP-ICA) and adaptive partition mutual information(AP-MI) estimation. FP-ICA which is based on secant method, is applied to quickly find the independence between input variables. AP-MI estimation is also applied to estimate an accurate dependence information by equally partitioning the samples of input variable for calculating the probability density function(PDF). The proposed method has been applied to 2 problems for selecting the input variables, which are the 7 artificial signals of 500 samples and the 24 environmental pollution signals of 55 samples, respectively The experimental results show that the proposed methods has a fast and accurate selection performance. The proposed method has also respectively better performance than AP-MI estimation without the FP-ICA and regular partition MI estimation.
A Data Aggregation Scheme for Enhancing the Efficiency of Data Aggregation and Correctness in Wireless Sensor Networks
Kim, Hyun-Tae ; Yu, Tae-Young ; Jung, Kyu-Su ; Jeon, Yeong-Bae ; Ra, In-Ho ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 531~536
DOI : 10.5391/JKIIS.2006.16.5.531
Recently, many of researchers have been studied in data processing oriented middleware for wireless sensor networks with the rapid advances on sensor and wireless communication technologies. In a wireless sensor network, a middleware should handle the data loss problem at an intermediate sensor node caused by instantaneous data burstness to support efficient processing and fast delivering of the sensing data. To handle this problem, a simple data discarding or data compressing policy for reducing the total amount of data to be transferred is typically used. But, data discarding policy decreases the correctness of a collected data, in other hand, data compressing policy requires additional processing overhead with the high complexity of the given algorithm. In this paper, it proposes a data-average method for enhancing the efficiency of data aggregation and correctness where the sensed data should be delivered only with the limited computing power and energy resource. With the proposed method, unnecessary data transfer of the overlapped data is eliminated and data correctness is enhanced by using the proposed averaging scheme when an instantaneous data burstness is occurred. Finally, with the TOSSTM simulation results on TinyBB, we show that the correctness of the transferred data is enhanced.
Rainfall-Runoff Analysis Utilizing Multiple Impulse Responses
Yoo, Chul-Sang ; Park, Joo-Young ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 537~543
DOI : 10.5391/JKIIS.2006.16.5.537
There have been many recent studies on the nonlinear rainfall-runoff modeling, where the use of neural networks is shown to be quite successful. Due to fundamental limitation of linear structures, employing linear models has often been considered inferior to the neural network approaches in this area. However, we believe that with an appropriate extension, the concept of linear impulse responses can be a viable tool since it enables us to understand underlying dynamics principles better. In this paper, we propose the use of multiple impulse responses for the problem of rainfall-runoff analysis. The proposed method is based on a simple and fixed strategy for switching among multiple linear impulse-response models, each of which satisfies the constraints of non-negativity and uni-modality. The computational analysis performed for a certain Korean hydrometeorologic data set showed that the proposed method can yield very meaningful results.
A Judgment System for Intelligent Movement Using Soft Computing
Choi, Woo-Kyung ; Seo, Jae-Yong ; Kim, Seong-Hyun ; Yu, Sung-Wook ; Jeon, Hong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 544~549
DOI : 10.5391/JKIIS.2006.16.5.544
This research is to introduce about Judgment System for Intelligent Movement(JSIM) that can perform assistance work of human brain. JSIM can order autonomous command and also it can be directly controlled by user. This research assumes that control object is limited to Mobile Robot(MR) Mobile robot offers image and ultrasonic sensor information to user carrying JSIM and it performs guide to user. JSIM having PDA and Sensor-box controls velocity and direction of the mobile robot by soft-computing method that inputs user's command and information that is obtained to mobile robot. Also it controls mobile robot to achieve various movement. This paper introduces wearable JSIM that communicates with around devices and that can do intelligent judgment. To verify the possibility of the proposed system, in real environment, the simulation of control and application problem lot mobile robot will be introduced. Intelligent algorithm in the proposed system is generated by mixed hierarchical fuzzy and neural network.
A study on the Choquet distance measures and their applications
Jang, Lee-Chae ; Kim, Won-Joo ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 550~555
DOI : 10.5391/JKIIS.2006.16.5.550
Internal-valued fuzzy sets were suggested for the first time by Gorzalczang(1983). Based on this, Wang and Li extended their operations on interval-valued fuzzy numbers. Recently, Hong(2002) generalized results of Wang and Li and extended to interval-valued fuzzy numbers with Riemann integral. By using interval-valued Choquet integrals with respect to a fuzzy measure instead of Riemann integrals with respect to a classical measure, we studied some characterizations of interval-valued Choquet distance(2005). In this paper, we define Choquet distance measure for fuzzy number-valued fuzzy numbers and investigate some properties of them.
Pattern Classification Algorithm of DNA Chip Image using ANN
Joo, Jong-Tae ; Kim, Dae-Wook ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 556~561
DOI : 10.5391/JKIIS.2006.16.5.556
It is very important to classify the DNA Chip image pattern in order to acquire useful information about genetic disease of people. In this paper, we developed the novel pattern classification method of DNA Chip image using MLP based back-propagation and Self organizing Map learning algorithm. And then we compared and analyzed these classified pattern results. Also we carried out experiment in the MV2440 board using CPU Cote for S3C2440(ARM 920T) and PC environment, and displayed its results in order to give the genetic information to user mote easily in various environment.
Model Predictive Control System Design with Real Number Coding Genetic Algorithm
Bang, Hyun-Jin ; Park, Jong-Chon ; Hong, Jin-Man ; Lee, Hong-Gi ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 562~567
DOI : 10.5391/JKIIS.2006.16.5.562
Model Predictive Control(MPC) system uses the current input which minimizes the difference between the desired output and the estimated output in the receding horizon scheme. In many cases (for example, system with constraints or nonlinear system), however, it is not easy to find the optimal solution to the above problem. In this paper, we show that real number coding genetic algorithm can be used to solve the optimal problem for MPC effectively. Also, we show by simulation that the real coding algorithm is mote natural and advantageous than the digital coding one.
A Spatiotemporal Location Prediction Method of Moving Objects Based on Path Data
Yoon, Tae-Bok ; Park, Kyo-Hyun ; Lee, Jee-Hyong ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 568~574
DOI : 10.5391/JKIIS.2006.16.5.568
User adaptive services have been important features in many applications. To provide such services, various techniques with various kinds of data are being used. In this paper, we propose a method to analyze user's past moving paths and predict the goal position and the path to the goal by observing the user's current moving path. We develop a spatiotemporal similarity measure between paths. We choose a past path which is the most similar to the current path using the similarity. Based on the chosen path, user's spatiotemporal position is estimated. Through experiments we confirm this method is useful and effective.
A Study on the Channel Allocation and CPU Job scheduling Scheme in Cellular Network
Heo, Bo-Jin ; Son, Dong-Cheul ; Kim, Chang-Suk ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 575~580
DOI : 10.5391/JKIIS.2006.16.5.575
It is important matter that inflect well allocated frequency resource in cellular network and is still more serious element in environment that provide multimedia services. This paper describes model and algorithm that increase two elements that is frequency allocation and job scheduling that consider multimedia service traffic special quality by emphasis that do mapping present in CDMA cellular system. We proposed the model composed three parts (channel allocation algorithm, mapping algorithm and scheduling algorithm) and simulation results.
Ground Detection Method for Removement of Earth Field for Magnetic Guidance System
Im, Dae-Yeong ; Jung, Young-Yoon ; Ryoo, Young-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 581~586
DOI : 10.5391/JKIIS.2006.16.5.581
In this paper, describes ground detection method for removal earth field of magnet guidance system Magnetic guidance system is magnetic markers are installed just under the surface of roadway pavement and the magnetic fields generated these markers are detected by magnetic field sensor mounted of vehicles. vehicle is know lot lateral distance using magnetic field. But sensor is together measuring the magnetic field and earth field. It is operate error. Thus in this paper, proposed new method removing earth field or development experiment device via show the for practical and excellence.
Development of Emotion-Based Human Interaction Method for Intelligent Robot
Joo, Young-Hoon ; So, Jea-Yun ; Sim, Kee-Bo ; Song, Min-Kook ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 587~593
DOI : 10.5391/JKIIS.2006.16.5.587
This paper is to present gesture analysis for human-robot interaction. Understanding human emotions through gesture is one of the necessary skills for the computers to interact intelligently with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. For efficient operation we used recognizing a gesture with HMM(Hidden Markov Model). We constructed a large gesture database, with which we verified our method. As a result, our method is successfully included and operated in a mobile system.
Optimal Economical Running Patterns Based on Fuzzy Model
Lee, Tae-Hyung ; Hwang, Hee-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 594~600
DOI : 10.5391/JKIIS.2006.16.5.594
The optimization has been performed to search an economical running pattern in the view point of trip time and energy consumption. Fuzzy control model has been applied to build the meta-model. To identify the structure and its parameters of a fuzzy model, fuzzy c-means clustering method and differential evolutionary scheme ate utilized, respectively. As a result, two meta-models for trip time and energy consumption are constructed. The optimization to search an economical running pattern is achieved by differential evolutionary scheme. The result shows that the proposed methodology is very efficient and conveniently applicable to the operation of railway system.
Balance Control of a Biped Robot Using the ZMP State Prediction of the Kalman Estimator
Park, Sang-Bum ; Han, Young-Jun ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 601~607
DOI : 10.5391/JKIIS.2006.16.5.601
This paper proposes a novel balance control scheme of a biped robot to predict the next position of ZMP using Kalman Filter. The mathematical model of the biped robot is generally approximated by 3D-LIPM(3D-Linear Inverted Pendulum Mode), but it cannot completely express the robot's dynamics. The stability of the biped robot depends on whether the ZMP(Zero Moment Point) position is in the stability region or out of. And the internal error between the robot mechanism and its model could affect the stability of a robot. Therefore, the proposed balance control not reduces the internal error, but also timely generates the proper control. The experiment of the proposed balance control is simulated on the virtual workspace where the biped robot may encounter with various difficulties.
Data Modeling using Cluster Based Fuzzy Model Tree
Lee, Dae-Jong ; Park, Jin-Il ; Park, Sang-Young ; Jung, Nahm-Chung ; Chun, Meung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 608~615
DOI : 10.5391/JKIIS.2006.16.5.608
This paper proposes a fuzzy model tree consisting of local linear models using fuzzy cluster for data modeling. First, cluster centers are calculated by fuzzy clustering method using all input and output attributes. And then, linear models are constructed at internal nodes with fuzzy membership values between centers and input attributes. The expansion of internal node is determined by comparing errors calculated in parent node with ones in child node, respectively. As a final step, data prediction is performed with a linear model having the highest fuzzy membership value between input attributes and cluster centers in leaf nodes. To show the effectiveness of the proposed method, we have applied our method to various dataset. Under various experiments, our proposed method shows better performance than conventional model tree and artificial neural networks.
A Study on Human-friendly Path Decision using Fuzzy Logic
Choi, Woo-Kyung ; Kim, Seong-Joo ; Jeon, Hong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 616~621
DOI : 10.5391/JKIIS.2006.16.5.616
Recently many cars are equipping a navigation system. The main purpose of the early system guides a user through the route. A navigation system includes various abilities by development of various technologies and it has given more convenience to user. It can play various records on the tape and announces which are useful information about each road. Also it can use various multi-media contents by DMB device during driving. However, guide function of basic and important road in the navigation system has not grown greatly yet. In this paper, we proposed recommendation method of human-friendly road considering user's condition through various information of outside environment, user's velocity intention, a driver's emotion and a preference of the road. Modules consists of hierarchical structure that can easily correct and add each algorithm and those use fuzzy logic algorithm.
Pattern Analysis of the Learning Personality Types Using Fuzzy TAM Network
Um, Jae-Geuk ; Hwang, Seung-Gook ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 622~626
DOI : 10.5391/JKIIS.2006.16.5.622
In this paper, we show the usefulness of an methodology using a neural network that it analyzes a relation between learning personality related variables of the Enneargram and learning personality types. The Enneargram is a tool to classify learning personality types. In other words, we analyzed patterns of learning personality types-actaul-spontaneous type, actual-routine type, conceptual-specific type, conceptual-global type - by using the fuzzy TAM network that are very useful tool for pattern analysis.
CMOS neuron activation function
Kang, Min-Jae ; Kim, Ho-Chan ; Song, Wang-Cheol ; Lee, Sang-Joon ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 627~634
DOI : 10.5391/JKIIS.2006.16.5.627
We have proposed the methods how to control the slope of CMOS inverter's characteristic and how to shift it in y axis. We control the MOS transistor threshold voltage for these methods. By observing that two transistors are in saturation region at the center of the CMOS inverter's characteristic, we have presented how to make the characteristic for one pole neuron. The circuit level simulation is used for verifying the proposed method. PSpice(OrCAD Co.) is used for circuit level simulation.
Ship's Collision Avoidance Support System Using Fuzzy-CBR
Park, Gyei-Kark ; Benedictos John Leslie RM. ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 635~641
DOI : 10.5391/JKIIS.2006.16.5.635
Ship's collision avoidance is a skill that masters of merchant marine vessels have acquired through years of experience and that makes them feel at ease to guide their ship out from danger quickly compared to inexperienced officers. Case based reasoning (CBR) uses the same technique in solving tasks that needs reference from variety of situations. CBR can render decision-making easier by retrieving past solutions from situations that are similar to the one at hand and make necessary adjustments in order to adapt them. In this paper, we propose to utilize the advantages of CBR in a support system for ship's collision avoidance while using fuzzy algorithm for its retrieval of similar navigational situations, stored in the casebase, thus avoiding the cumbersome tasks of creating a new solution each time a new situation is encountered. There will be two levels within the Fuzzy-CBR. The first level will identify the dangerous ships and infer the new case. The second level will retrieve cases from casebase and adapt the solution to solve for the output. While CBR's accuracy depends on the efficient retrieval of possible solutions to be adapted from stored cases, fuzzy algorithm will improve the effectiveness of solving the similarity to a new case at hand.
Fuzzy TAM Network Model Using SOM
Hong, Jung-Pyo ; Hwang, Seung-Gook ;
Journal of Korean Institute of Intelligent Systems, volume 16, issue 5, 2006, Pages 642~646
DOI : 10.5391/JKIIS.2006.16.5.642
The fuzzy TAM(Topographical Attentive Mapping) network is a supervised method of pattern analysis which is composed of input layer, category layer, and output layer. But if we don't know the target value of the pattern, the network can not be trained. In this case, the target value can be replaced by a result induced by using an unsupervised neural network as the SOM (Self-organizing Map). In this paper, we apply the results of SOM to fuzzy TAM network and show its usefulness through the case study.