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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 21, Issue 6 - Dec 2011
Volume 21, Issue 5 - Oct 2011
Volume 21, Issue 4 - Aug 2011
Volume 21, Issue 3 - Jun 2011
Volume 21, Issue 2 - Apr 2011
Volume 21, Issue 1 - Feb 2011
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Occluded Object Motion Tracking Method based on Combination of 3D Reconstruction and Optical Flow Estimation
Park, Jun-Heong ; Park, Seung-Min ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 537~542
DOI : 10.5391/JKIIS.2011.21.5.537
A mirror neuron is a neuron fires both when an animal acts and when the animal observes the same action performed by another. We propose a method of 3D reconstruction for occluded object motion tracking like Mirror Neuron System to fire in hidden condition. For modeling system that intention recognition through fire effect like Mirror Neuron System, we calculate depth information using stereo image from a stereo camera and reconstruct three dimension data. Movement direction of object is estimated by optical flow with three-dimensional image data created by three dimension reconstruction. For three dimension reconstruction that enables tracing occluded part, first, picture data was get by stereo camera. Result of optical flow is made be robust to noise by the kalman filter estimation algorithm. Image data is saved as history from reconstructed three dimension image through motion tracking of object. When whole or some part of object is disappeared form stereo camera by other objects, it is restored to bring image date form history of saved past image and track motion of object.
Image Thresholding based on the Entropy Using Variance of the Gray Levels
Kwon, Soon-H. ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 543~548
DOI : 10.5391/JKIIS.2011.21.5.543
Entropy measuring the richness in details of the image is generally obtained by using the histogram of gray levels in an image, and has been widely used as an index for thresholding of the image. In this paper, we propose an entropy-based thresholding method, where the entropy is obtained not by the histogram but by the variance of the gray levels, to binalize a given image. The effectiveness of the proposed method is demonstrated by thresholding experiments on nine test images and comparison with conventional two thresholding methods, that is, Otsu method and entropy-based method using the histogram.
Design of Output Feedback Controller for Polynomial Fuzzy Large-Scale System : Sum-of-Square Approach
Kim, Han-Sol ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 549~554
DOI : 10.5391/JKIIS.2011.21.5.549
This paper presents the stabilization method for polynomial fuzzy large-scale system by using output feedback controller. Each sub system of the large-scale system is transformed into polynomial fuzzy model, and then output feedback controller is designed to stabilize the large-scale system. Stabilization condition is derived as sum-of-square (SOS) condition by applying the polynomial Lyapunov function. This condition can be easily solved by SOSTOOLS which is the third party of the MATLAB. From these solutions, output feedback controller gain can be obtained by SOS condition. Finally, a simulation example is presented to illustrate the effectiveness and the suitability of the proposed method.
Performance Criterion-based Polynomial Calibration Model for Laser Scan Camera
Baek, Gyeong-Dong ; Cheon, Seong-Pyo ; Kim, Su-Dae ; Kim, Sung-Shin ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 555~563
DOI : 10.5391/JKIIS.2011.21.5.555
The goal of image calibration is to find a relation between image and world coordinates. Conventional image calibration uses physical camera model that is able to reflect camera`s optical properties between image and world coordinates. In this paper, we try to calibrate images distortion using performance criterion-based polynomial model which assumes that the relation between image and world coordinates can be identified by polynomial equation and its order and parameters are able to be estimated with image and object coordinate values and performance criterion. In order to overcome existing limitations of the conventional image calibration model, namely, over-fitting feature, the performance criterion-based polynomial model is proposed. The efficiency of proposed method can be verified with 2D images that were taken by laser scan camera.
A Study on Graph-based Topic Extraction from Microblogs
Choi, Don-Jung ; Lee, Sung-Woo ; Kim, Jae-Kwang ; Lee, Jee-Hyong ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 564~568
DOI : 10.5391/JKIIS.2011.21.5.564
Microblogs became popular information delivery ways due to the spread of smart phones. They have the characteristic of reflecting the interests of users more quickly than other medium. Particularly, in case of the subject which attracts many users, microblogs can supply rich information originated from various information sources. Nevertheless, it has been considered as a hard problem to obtain useful information from microblogs because too much noises are in them. So far, various methods are proposed to extract and track some subjects from particular documents, yet these methods do not work effectively in case of microblogs which consist of short phrases. In this paper, we propose a graph-based topic extraction and partitioning method to understand interests of users about a certain keyword. The proposed method contains the process of generating a keyword graph using the co-occurrences of terms in the microblogs, and the process of splitting the graph by using a network partitioning method. When we applied the proposed method on some keywords. our method shows good performance for finding a topic about the keyword and partitioning the topic into sub-topics.
Mining of Subspace Contrasting Sample Groups in Microarray Data
Lee, Kyung-Mi ; Lee, Keon-Myung ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 569~574
DOI : 10.5391/JKIIS.2011.21.5.569
In this paper, we introduce the subspace contrasting group identification problem and propose an algorithm to solve the problem. In order to identify contrasting groups, the algorithm first determines two groups of which attribute values are in one of the contrasting ranges specified by the analyst, and searches for the contrasting groups while increasing the dimension of subspaces with an association rule mining strategy. Because the dimension of microarray data is likely to be tens of thousands, it is burdensome to find all contrasting groups over all possible subspaces by query generation. It is very useful in the sense that the proposed method allows to find those contrasting groups without analyst`s involvement.
Candidate Marker Identification from Gene Expression Data with Attribute Value Discretization and Negation
Lee, Kyung-Mi ; Lee, Keon-Myung ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 575~580
DOI : 10.5391/JKIIS.2011.21.5.575
With the increasing expectation on personalized medicine, it is getting importance to analyze medical information in molecular biology perspective. Gene expression data are one of representative ones to show the microscopic phenomena of biological activities. In gene expression data analysis, one of major concerns is to identify markers which can be used to predict disease occurrence, progression or recurrence in the molecular level. Existing markers candidate identification methods mainly depend on statistical hypothesis test methods. This paper proposes a search method based decision tree induction to identify candidate markers which consist of multiple genes. The propose method discretizes numeric expression level into three categorical values and allows candidate markers` genes to be expressed by their negation as well as categorical values. It is desirable to have some number of genes to be included in markers. Hence the method is devised to try to find candidate markers with restricted number of genes.
A Project-Based Embedded Software Design Course
Moon, Jung-Ho ; Park, Lae-Jeong ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 581~587
DOI : 10.5391/JKIIS.2011.21.5.581
This paper presents a senior-level embedded software design course using a customized training kit. Embedded software design courses commonly entail a lot of practice hours and a semester-long project and thus requires a hardware platform on which the embedded software runs. A training kit has been designed such that both hardware system and operating system are not too complicated or heavy for undergraduate students to fully understand and to develop embedded software on their own. The course using the customized training kit gives the students hands-on experience of embedded software design and programming ranging from device drivers to user interface, thereby enabling them to have in-depth understanding of embedded software and to improve their programming skills more easily and faster than when using commercial training kits.
System Development for Guiding Job Information Based on Android Smart-phone
Cho, Yong-Hyun ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 588~594
DOI : 10.5391/JKIIS.2011.21.5.588
This paper presents the development of application and management system for guiding job information based on android smart-phone. The real-time informations which are provided from the job portal site, become known by using the smart-phone, and the sever system for saving and managing the related informations has been implemented. Especially, the relay and synchronization protocol of job informations have been designed and the system for managing a transmitting and receiving information is also designed and modelled. The developed application has been made up for and registered in the application store for making good use.
Intelligent Balancing Control of Inverted Pendulum on a ROBOKER Arm Using Visual Information
Kim, Jeong-Seop ; Jung, Seul ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 595~601
DOI : 10.5391/JKIIS.2011.21.5.595
This paper presents balancing control of inverted pendulum on the ROBOKER arm using visual information. The angle of the inverted pendulum placed on the robot arm is detected by a stereo camera and the detected angle is used as a feedback and tracking error for the controller. Thus, the overall closed loop forms a visual servoing control task. To improve control performance, neural network is introduced to compensate for uncertainties. The learning algorithm of radial basis function(RBF) network is performed by the digital signal controller which is designed to calculate floating format data and embedded on a field programmable gate array(FPGA) chip. Experimental studies are conducted to confirm the performance of the overall system implementation.
Development of Autonomous Algorithm Using an Online Feedback-Error Learning Based Neural Network for Nonholonomic Mobile Robots
Lee, Hyun-Dong ; Myung, Byung-Soo ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 602~608
DOI : 10.5391/JKIIS.2011.21.5.602
In this study, a method of designing a neurointerface using neural network (NN) is proposed for controlling nonholonomic mobile robots. According to the concept of virtual master-slave robots, in particular, a partially stable inverse dynamic model of the master robot is acquired online through the NN by applying a feedback-error learning method, in which the feedback controller is assumed to be based on a PD compensator for such a nonholonomic robot. The NN for the online feedback-error learning can composed that the input layer consists of six units for the inputs
Hybrid Food Recommendation System Using Auto-generated User Profiles
Jeong, Ju-Seok ; Kang, Sin-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 609~617
DOI : 10.5391/JKIIS.2011.21.5.609
This paper proposes a personalized food recommendation system using user profiles auto-generated from Twitter. The user profiles are generated by extracting nouns from Twitter, and calculating emotional scores according to whether each noun is collocated with emotion words. Representative noun information for each food is constructed by analyzing web pages relevant to foods. Appropriate foods for users can be recommended by calculating similarities among the extracted resources. The proposed system has an advantage in that it can always recommend foods even if a user is a newcomer.
Kernelized Structure Feature for Discriminating Meaningful Table from Decorative Table
Son, Jeong-Woo ; Go, Jun-Ho ; Park, Seong-Bae ; Kim, Kweon-Yang ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 618~623
DOI : 10.5391/JKIIS.2011.21.5.618
This paper proposes a novel method to discriminate meaningful tables from decorative one using a composite kernel for handling structural information of tables. In this paper, structural information of a table is extracted with two types of parse trees: context tree and table tree. A context tree contains structural information around a table, while a table tree presents structural information within a table. A composite kernel is proposed to efficiently handle these two types of trees based on a parse tree kernel. The support vector machines with the proposed kernel dised kuish meaningful tables from the decorative ones with rich structural information.
A New Kernelized Approach to Recommender System
Lee, Jae-Hun ; Hwang, Jae-Pil ; Kim, Eun-Tai ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 624~629
DOI : 10.5391/JKIIS.2011.21.5.624
In this paper, a new kernelized approach for use in a recommender system (RS) is proposed. Using a machine learning technique, the proposed method predicts the user`s preferences for unknown items and recommends items which are likely to be preferred by the user. Since the ratings of the users are generally inconsistent and noisy, a robust binary classifier called a dual margin Lagrangian support vector machine (DMLSVM) is employed to suppress the noise. The proposed method is applied to MovieLens databases, and its effectiveness is demonstrated via simulations.
Design of the Robust Fuzzy Controller based on Fuzzy Lyapunov Functions
Kim, Ho-Jun ; Park, Jin-Bae ; Joo, Young-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 630~636
DOI : 10.5391/JKIIS.2011.21.5.630
This paper is concerned with the stability analysis and stabilization for the Takagi-Sugeno(T-S) fuzzy systems with parametric uncertainties. To reduce conservativeness in stability analysis for T-S fuzzy systems, fuzzy Lyapunov functions are used. Stability analysis is performed and robust fuzzy controller is designed for stabilization of the system with parametric uncertainties. The stability and stabilization conditions are formulated in terms of linear matrix inequalities (LMIs). Finally, simulation example is presented to show the effectiveness of the proposed approach.
The Weight Decision of Multi-dimensional Features using Fuzzy Similarity Relations and Emotion-Based Music Retrieval
Lim, Jee-Hye ; Lee, Joon-Whoan ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 637~644
DOI : 10.5391/JKIIS.2011.21.5.637
Being digitalized, the music can be easily purchased and delivered to the users. However, there is still some difficulty to find the music which fits to someone`s taste using traditional music information search based on musician, genre, tittle, album title and so on. In order to reduce the difficulty, the contents-based or the emotion-based music retrieval has been proposed and developed. In this paper, we propose new method to determine the importance of MPEG-7 low-level audio descriptors which are multi-dimensional vectors for the emotion-based music retrieval. We measured the mutual similarities of musics which represent a pair of emotions expressed by opposite meaning in terms of each multi-dimensional descriptor. Then rough approximation, and inter- and intra similarity ratio from the similarity relation are used for determining the importance of a descriptor, respectively. The set of weights based on the importance decides the aggregated similarity measure, by which emotion-based music retrieval can be achieved. The proposed method shows better result than previous method in terms of the average number of satisfactory musics in the experiment emotion-based retrieval based on content-based search.
A Study on Focus Position Control of Reflector Using Fuzzy Controller
Jeong, Hoi-Seong ; Kim, Jun-Su ; Kim, Hye-Ran ; Kim, Gwan-Hyung ; Lee, Hyung-Ki ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 645~652
DOI : 10.5391/JKIIS.2011.21.5.645
The present study investigated the tracking system of a reflector to trace the movement of sun. The system was designed to minimize the error between the vertical vector of reflector and the position of sun. The proposed system was able to collect the sun lights at a point as a useful source of light energy and transmit the collected light to a remote area through optical fibers. Also the study successfully solved the controller design problem due to the complexity of modeling of the sun tracking system using a fuzzy logic controller which mimics human reasoning.
ECG signal compression based on B-spline approximation
Ryu, Chun-Ha ; Kim, Tae-Hun ; Lee, Byung-Gook ; Choi, Byung-Jae ; Park, Kil-Houm ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 653~659
DOI : 10.5391/JKIIS.2011.21.5.653
In general, electrocardiogram(ECG) signals are sampled with a frequency over 200Hz and stored for a long time. It is required to compress data efficiently for storing and transmitting them. In this paper, a method for compression of ECG data is proposed, using by Non Uniform B-spline approximation, which has been widely used to approximation theory of applied mathematics and geometric modeling. ECG signals are compressed and reconstructed using B-spline basis function which curve has local controllability and control a shape and curve in part. The proposed method selected additional knot with each step for minimizing reconstruction error and reduced time complexity. It is established that the proposed method using B-spline approximation has good compression ratio and reconstruct besides preserving all feature point of ECG signals, through the experimental results from MIT-BIH Arrhythmia database.
Design of Leg Length for a Legged Walking Robot Based on Theo Jansen Using PSO
Kim, Sun-Wook ; Kim, Dong-Hun ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 660~666
DOI : 10.5391/JKIIS.2011.21.5.660
In this paper, we proposed a Particle Swarm Optimization(PSO) to search the optimal link lengths for legged walking robot. In order to apply the PSO algorithm for the proposed, its walking robot kinematic analysis is needed. A crab robot based on four-bar linkage mechanism and Jansen mechanism is implemented in H/W. For the performance index of PSO, the stride length of the legged walking robot is defined, based on the propose kinematic analysis. Comparative simulation results present to illustrate the viability and effectiveness of the proposed method.
Sensor Fusion of Localization using Unscented Kalman Filter
Lee, Jun-Ha ; Jung, Kyung-Hoon ; Kim, Jung-Min ; Kim, Sung-Shin ;
Journal of Korean Institute of Intelligent Systems, volume 21, issue 5, 2011, Pages 667~672
DOI : 10.5391/JKIIS.2011.21.5.667
This paper presents to study the sensor fusion of positioning sensors using UKF(unscented Kalman filter) for positioning accuracy improvement of AGV(automatic guided vehicle). The major guidance systems for AGV are wired guidance and magnetic guidance system. Because they have high accuracy and fast response time, they are used in most of the FMS(flexible manufacturing system). However, they had weaknesses that are high maintenance cost and difficult of existing path modification. they are being changed to the laser navigation in recent years because of those problems. The laser navigation is global positioning sensor using reflecters on the wall, and it have high accuracy and easy to modify the path. However, its response time is slow and it is influenced easily by disturbance. In this paper, we propose the sensor fusion method of the laser navigation and local sensors using UKF. The proposed method is improvement method of accuracy through error analysis of sensors. For experiments, we used the axle-driven forklift AGV and compared the positioning results of the proposed method with positioning results of the laser navigation. In experimental result, we verified that the proposed method can improve positioning accuracy about 16%.