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 20, Issue 6 - Dec 2010
Volume 20, Issue 5 - Oct 2010
Volume 20, Issue 4 - Aug 2010
Volume 20, Issue 3 - Jun 2010
Volume 20, Issue 2 - Apr 2010
Volume 20, Issue 1 - Feb 2010
Selecting the target year
A Navigation Algorithm of Modular Robots with 3 DOF Docking Arm in Uneven Environments
Na, Doo-Young ; Min, Hyun-Hong ; Lee, Chang-Seok ; Noh, Su-Hee ; Moon, Hyung-Pil ; Jung, Jin-Woo ; Kim, Yong-Tae ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 311~317
DOI : 10.5391/JKIIS.2010.20.3.311
In the paper, we propose an improved mobility method of modular robots by physical docking in the uneven environments. The modular robot system consists of autonomous docking device, 3 DOF robotic arm, motion controller, and main controller. Real-time location and direction of the robot are estimated using inner GPS and they are used to control direction and path of each robot for physical docking between modular robots. We design a navigation algorithm of modular robot using physical docking and cooperative navigation in the environment with broken road and low stair. The proposed method is verified by navigation experiments of three developed modular robots in the uneven environments.
Design and Implementation of Web Crawler Wrappers to Collect User Reviews on Shopping Mall with Various Hierarchical Tree Structure
Kang, Han-Hoon ; Yoo, Seong-Joon ; Han, Dong-Il ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 318~325
DOI : 10.5391/JKIIS.2010.20.3.318
A Study on the Implementation of a Data Acquisition System with a Large Number of Multiple Signal
Son, Do-Sun ; Lee, Sang-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 326~331
DOI : 10.5391/JKIIS.2010.20.3.326
This paper presents the design and implementation of a data acquisition system with a large number of multi-channels for manufacturing machine. The system having a throughput of 800-ch analog signals has been designed with Quartus II tool and Cyclone II FPGA. The proposed system is suitable for the large scale data handling in order to distinguish whether the operation is correct or not. The designed system is composed of a control unit, voltage divider and USB interface. To reduce the data throughput, we utilized an algorithm which can extract the same data from the achieved data. The test results of the system adapted to a manufacturing machine, show a relevant data acquisition operation of 800 channels in short time.
Vision Based Position Detection System of Used Oil Filter using Line Laser
Xing, Xiong ; Song, Un-Ji ; Choi, Byung-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 332~336
DOI : 10.5391/JKIIS.2010.20.3.332
There are so many successful applications to image processing systems in industries. In this study we propose a position detection system for used oil filter by using a line laser. We have been done on the development of line laser as interaction devices. A camera captures images of a display surface of a used oil filter and then a laser beam location is extracted from the captured image. This image is processed and used as a cursor position. We also discuss an algorithm that can distinguish the front part and rear part. In particular we present a robust and efficient linear detection algorithm that allows us to use our system under a variety lighting conditions, and allows us to reduce the amount of image parsing required to find a laser position by an order of magnitude.
A Playlist Generation System based on Musical Preferences
Bang, Sun-Woo ; Kim, Tae-Yeon ; Jung, Hye-Wuk ; Lee, Jee-Hyong ; Kim, Yong-Se ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 337~342
DOI : 10.5391/JKIIS.2010.20.3.337
The rise of music resources has led to a parallel rise in the need to manage thousands of songs on user devices. So users are tend to build play-list for manage songs. However the manual selection of songs for creating play-list is bothersome task. This paper proposes an auto play-list recommendation system considering user`s context of use and preference. This system has two separate systems: mood and emotion classification system and music recommendation system. Users need to choose just one seed song for reflection their context of use and preference. The system recommends songs before the current song ends in order to fill up user play-list. User also can remove unsatisfied songs from recommended song list to adapt user preferences of the system for the next recommendation precess. The generated play-lists show well defined mood and emotion of music and provide songs that user preferences are reflected.
Image Recognition by Using Hybrid Coefficient Measure of Correlation and Distance
Hong, Seong-Jun ; Cho, Yong-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 343~347
DOI : 10.5391/JKIIS.2010.20.3.343
This paper presents an efficient image recognition method using the hybrid coefficient measure of correlation and distance. The correlation coefficient is applied to measure the statistical similarity by using Pearson coefficient, and distance coefficient is also applied to measure the spacial similarity by using city-block. The total similarity among images is calculated by extending the similarity between the feature vectors, then the feature vectors can be extracted by PCA and ICA, respectively. The proposed method has been applied to the problem for recognizing the 960(30 persons * 4 expressions * 2 lights * 4 poses) facial images of 40*50 pixels. The experimental results show that the proposed method of ICA has a superior recognition performances than the method using PCA, and is affected less by the environmental influences so as lighting.
Robust Feature Extraction Based on Image-based Approach for Visual Speech Recognition
Gyu, Song-Min ; Pham, Thanh Trung ; Min, So-Hee ; Kim, Jing-Young ; Na, Seung-You ; Hwang, Sung-Taek ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 348~355
DOI : 10.5391/JKIIS.2010.20.3.348
In spite of development in speech recognition technology, speech recognition under noisy environment is still a difficult task. To solve this problem, Researchers has been proposed different methods where they have been used visual information except audio information for visual speech recognition. However, visual information also has visual noises as well as the noises of audio information, and this visual noises cause degradation in visual speech recognition. Therefore, it is one the field of interest how to extract visual features parameter for enhancing visual speech recognition performance. In this paper, we propose a method for visual feature parameter extraction based on image-base approach for enhancing recognition performance of the HMM based visual speech recognizer. For experiments, we have constructed Audio-visual database which is consisted with 105 speackers and each speaker has uttered 62 words. We have applied histogram matching, lip folding, RASTA filtering, Liner Mask, DCT and PCA. The experimental results show that the recognition performance of our proposed method enhanced at about 21% than the baseline method.
On some properties of vague bi-groups and fuzzy bi-functions
Jang, Lee-Chae ; Kim, Tae-Kyun ; Lee, Byung-Je ; Kim, Won-Joo ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 356~361
DOI : 10.5391/JKIIS.2010.20.3.356
M. Demirci[Vague groups, J. math. Anal. Appl. vol.230, pp. 142-156, 1999] studied the vague group operation on a crisp set as a fuzzy function and estabished the vague group structure on a crisp set. In this paper we consider bi-groups which are studied by A.A.A. Agboola and L.S. Akinola. And we also will define vague bi-groups and fuzzy bi-functions and we investigate some basic operations on the vague bi-group and fuzzy bi-functions.
An Implementation of Linux Device Drivers of Nios II Embedded Processor System for Image Surveillance System
Kim, Dong-Jin ; Jung, Young-Bee ; Kim, Tae-Hyo ; Park, Young-Seak ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 362~367
DOI : 10.5391/JKIIS.2010.20.3.362
In this paper, we describe implementation of FPGA-based Nios II embedded processor system and linux device driver for image monitoring system which is supplement weakness for fixed surveillance area of existing CCTV system and by manual operation of the camera`s moving. Altera Nios II processor 8.0 is supported MMU which is stable and efficient managed memory. We designed the image monitoring and control system by using Altera Nios II soft-core processor system which is flexible in various application and excellent adaptability. By implementation of camera device driver and VGA decvice driver for Linux-based Nios II system, we implemented image serveillance system for Nios II embedded processor system.
Space Partition using Context Fuzzy c-Means Algorithm for Image Segmentation
Roh, Seok-Beom ; Ahn, Tae-Chon ; Baek, Yong-Sun ; Kim, Yong-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 368~374
DOI : 10.5391/JKIIS.2010.20.3.368
Image segmentation is the basic step in the field of the image processing for pattern recognition, environment recognition, and context analysis. The Otsu`s automatic threshold selection, which determines the optimal threshold value to maximize the between class scatter using the distribution information of the normalized histogram of a image, is the famous method among the various image segmentation methods. For the automatic threshold selection proposed by Otsu, it is difficult to determine the optimal threshold value by considering the sub-region characteristic of the image because the Otsu`s algorithm analyzes the global histogram of a image. In this paper, to alleviate this difficulty of Otsu`s image segmentation algorithm and to improve image segmentation capability, the original image is divided into several sub-images by using context fuzzy c-means algorithm. The proposed fuzzy Otsu threshold algorithm is applied to the divided sub-images and the several threshold values are obtained.
Design of Robust Support Vector Machine Using Genetic Algorithm
Lee, Hee-Sung ; Hong, Sung-Jun ; Lee, Byung-Yun ; Kim, Eun-Tai ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 375~379
DOI : 10.5391/JKIIS.2010.20.3.375
The support vector machine (SVM) has been widely used in variety pattern recognition problems applicable to recommendation systems due to its strong theoretical foundation and excellent empirical successes. However, SVM is sensitive to the presence of outliers since outlier points can have the largest margin loss and play a critical role in determining the decision hyperplane. For robust SVM, we limit the maximum value of margin loss which includes the non-convex optimization problem. Therefore, we proposed the design method of robust SVM using genetic algorithm (GA) which can solve the non-convex optimization problem. To demonstrate the performance of the proposed method, we perform experiments on various databases selected in UCI repository.
Induction Motor Diagnosis System by Effective Frequency Selection and Linear Discriminant Analysis
Lee, Dae-Jong ; Cho, Jae-Hoon ; Yun, Jong-Hwan ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 380~387
DOI : 10.5391/JKIIS.2010.20.3.380
For the fault diagnosis of three-phase induction motors, we propose a diagnosis algorithm based on mutual information and linear discriminant analysis (LDA). The experimental unit consists of machinery module for induction motor drive and data acquisition module to obtain the fault signal. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by mutual information As the next step, feature extraction is performed by LDA, and then diagnosis is evaluated by k-NN classifier. The results to verify the usability of the proposed algorithm showed better performance than various conventional methods.
Development of EEG Signals Measurement and Analysis Method based on Timbre
Park, Seung-Min ; Lee, Young-Hwan ; Ko, Kwang-Eun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 388~393
DOI : 10.5391/JKIIS.2010.20.3.388
Cultural Content Technology(CT, Culture Technology) for the development of cultural industry and the commercialization of technology, cultural contents, media, mount, pass the value chain process and increase the added value of cultural products that are good for all forms of intangible technology. In the field of Culture Technology, Music by analyzing the characteristics of the development of a variety of applications has been studied. Associated with EEG measures and the results of their research in response to musical stimuli are used to detect and study is getting attention. In this paper, the musical stimuli in EEG signals by amplifying the corresponding reaction to the averaging method, ERP (Event-Related Potentials) experiments based on the process of extracting sound methods for removing noise from the ICA algorithm to extract the tone and noise removal according to the results are applied to analyze the characteristics of EEG.
Velocity Control Method of AGV for Heavy Material Transport
Woo, Seung-Beom ; Jung, Kyung-Hoon ; Kim, Jung-Min ; Park, Jung-Je ; Kim, Sung-Shin ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 394~399
DOI : 10.5391/JKIIS.2010.20.3.394
This paper presents to study the velocity control method of AGV for heavy material transport. Generally, in the industries, fork-type AGV using path tracking requires high stop-precision with performing operations for 20 hours. To obtain the high stop-precision of AGV for heavy material transport, AGV requires driving technic during low speed. Hence, we use encoder with keeping the speed of AGV and study the velocity control method to improve for the stop-precision of AGV. To experiment the proposed the velocity control method, we performed the experiments engaging the pallet located 4m in front of the AGV. In the experimental result, the maximum error of stop-precision was less than 18.64mm, and we verified that the proposed method is able to control stable.
Implement of Intelligent Head-Up Display for Vehicle
Son, Hui-Bae ; Ban, Hyeong-Jin ; Yang, Kwun ; Rhee, Young-Chul ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 400~405
DOI : 10.5391/JKIIS.2010.20.3.400
This paper deals with implementation of intelligent head up display for vehicle safety system. The Implanted new intelligent transport system offer the potential for improved vehicle to driver communication. The most commonly viewed information in a vehicle is from the Head up display, where speed, tachometer, engine RPM, navigation, engine temperature, fuel gauge, turn indicators and warning lights provide the driver with an array of fundamental information. TFT LCD, LCD Back light led, plane mirror, lens and controllers parts were designed to head up display system. Finally, In this paper, we analyze intelligent head up display system for vehicle of driver safety.
Genetic Algorithms for Maximizing the Coverage of Sensor Deployment
Yoon, You-Rim ; Kim, Yong-Hyuk ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 406~412
DOI : 10.5391/JKIIS.2010.20.3.406
In this paper, we formally define the problem of maximizing the coverage of sensor deployment, which is the optimization problem appeared in real-world sensor deployment, and analyze the properties of its solution space. To solve the problem, we proposed novel genetic algorithms, and we could show their superiority through experiments. When applying genetic algorithms to maximum coverage sensor deployment, the most important issue is how we evaluate the given sensor deployment efficiently. We could resolve the difficulty by using Monte Carlo method. By regulating the number of generated samples in the Monte Carlo evaluation of genetic algorithms, we could also reduce the computing time significantly without loss of solution quality.
Self-Organization of Swarm Robots Based on Color Recognition
Jung, Hah-Min ; Hwang, Young-Gi ; Kim, Dong-Hun ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 413~421
DOI : 10.5391/JKIIS.2010.20.3.413
In the study, self-organization by color detection is proposed to overcome required constraints for existing self-organization by an external ceiling camera and communication. In the proposed self-organization, each swarm robot can follow its colleague robot and all swarm robots can follow a target by LOS(Line of Sight). The swarm robots follow the moving target by the proposed potential field, avoiding confliction with neighboring robots and obstacles. Finally, all swarm robots are reached by a sight among swarm robots. In this paper, for unicycle robots with non-holonomic constraints instead of point robot with holonomic constraints self-organization is presented, it enhances the possibility of H/W realization.
Behavior Pattern Modeling based Game Bot detection
Park, Sang-Hyun ; Jung, Hye-Wuk ; Yoon, Tae-Bok ; Lee, Jee-Hyong ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 422~427
DOI : 10.5391/JKIIS.2010.20.3.422
Korean Game industry, especially MMORPG(Massively Multiplayer Online Game) has been rapidly expanding in these days. But As game industry is growing, lots of online game security incidents have also been increasing and getting prevailing. One of the most critical security incidents is `Game Bots`, which are programs to play MMORPG instead of human players. If player let the game bots play for them, they can get a lot of benefic game elements (experience points, items, etc.) without any effort, and it is considered unfair to other players. Plenty of game companies try to prevent bots, but it does not work well. In this paper, we propose a behavior pattern model for detecting bots. We analyzed behaviors of human players as well as bots and identified six game features to build the model to differentiate game bots from human players. Based on these features, we made a Naive Bayesian classifier to reasoning the game bot or not. To evaluated our method, we used 10 game bot data and 6 human Player data. As a result, we classify Game bot and human player with 88% accuracy.
An Efficient In-Place Block Rotation Algorithm and its Complexity Analysis
Kim, Pok-Son ; Kutzner, Arne ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 428~433
DOI : 10.5391/JKIIS.2010.20.3.428
The notion "block rotation" denotes the operation of exchanging two consecutive sequences of elements uv to vu. There are three already well-known block rotation algorithms called BlockRotation, Juggling and Reversal algorithm. Recently we presented a novel block rotation algorithm called QuickRotation. In this paper we compare QuickRotation to these three known block rotation algorithms. This comparison covers a complexity analysis as well as benchmarking and shows that a switch to QuickRotation is almost always advantageous.
An approach based on the generalized ILOWHM operators to group decision making
Park, Jin-Han ; Park, Yong-Beom ; Lee, Bu-Young ; Son, Mi-Jung ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 434~440
DOI : 10.5391/JKIIS.2010.20.3.434
In this paper, we define generalized induced linguistic aggregation operator called generalized induced linguistic ordered weighted harmonic mean(GILOWHM) operator. Each object processed by this operator consists of three components, where the first component represents the importance degree or character of the second component, and the second component isused to induce an ordering, through the first component, over the third components which are linguistic variables and then aggregated. It is shown that the induced linguistic ordered weighted harmonic mean(ILOWHM) operator and linguistic ordered weighted harmonic mean(LOWHM) operator are the special cases of the GILOWHM operator. Based on the GILOWHM and LWHM operators, we develop an approach to group decision making with linguistic preference relations. Finally, a numerical example is used to illustrate the applicability of the proposed approach.
Behavior Learning and Evolution of Swarm Robot based on Harmony Search Algorithm
Kim, Min-Kyung ; Ko, Kwang-Eun ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 441~446
DOI : 10.5391/JKIIS.2010.20.3.441
Each robot decides and behaviors themselves surrounding circumstances in the swarm robot system. Robots have to conduct tasks allowed through cooperation with other robots. Therefore each robot should have the ability to learn and evolve in order to adapt to a changing environment. In this paper, we proposed learning based on Q-learning algorithm and evolutionary using Harmony Search algorithm and are trying to improve the accuracy using Harmony Search Algorithm, not the Genetic Algorithm. We verify that swarm robot has improved the ability to perform the task.
Design of Multiple Fuzzy Prediction System based on Interval Type-2 TSK Fuzzy Logic System
Bang, Young-Keun ; Lee, Chul-Heui ;
Journal of Korean Institute of Intelligent Systems, volume 20, issue 3, 2010, Pages 447~454
DOI : 10.5391/JKIIS.2010.20.3.447
This paper presents multiple fuzzy prediction systems based on an Interval type-2 TSK fuzzy Logic System so that the uncertainty and the hidden characteristics of nonlinear data can be reflected more effectively to improve prediction quality. In proposed method, multiple fuzzy systems are adopted to handle the nonlinear characteristics of data, and each of multiple system is constructed by using interval type-2 TSK fuzzy logic because it can deal with the uncertainty and the characteristics of data better than type-1 TSK fuzzy logic and other methods. For input of each system, the first-order difference transformation method are used because the difference data generated from it can provide more stable statistical information to each system than the original data. Finally, computer simulations are performed to show the effectiveness of the proposed method for two typical time series examples.