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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 17, Issue 7 - Dec 2007
Volume 17, Issue 6 - Dec 2007
Volume 17, Issue 5 - Oct 2007
Volume 17, Issue 4 - Aug 2007
Volume 17, Issue 3 - Jun 2007
Volume 17, Issue 2 - Apr 2007
Volume 17, Issue 1 - Feb 2007
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Robust Digital Redesign for Observer-based System
Sung, Hwa-Chang ; Joo, Young-Hoon ; Park, Jin-Bae ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 285~290
DOI : 10.5391/JKIIS.2007.17.3.285
In this paper, we presents robust digital redesign (DR) method for observer-based linear time-invariant (LTI) system. The term of DR involves converting an analog controller into an equivalent digital one by considering two condition: state-matching and stability. The design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed the uncertain parts of given observer-based system more precisely, When a sampling period is sufficiently small, the conversion of a analog structured uncertain system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).
An Extraction of Property of Ontology Instance Using Stratification of Domain Knowledge
Chang, Moon-Soo ; Kang, Sun-Mee ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 291~296
DOI : 10.5391/JKIIS.2007.17.3.291
The ontology has been used widely in recent years with its aim to accumulate knowledge that machine can comprehend. We believe that machine can manage and analyze information on its own using the ontology. In this paper, we propose an algorithm that allows us to extract properties of ontology instances from structured information already existing in web documents. In particular, by stratification of the domain knowledge that is composed of property information, we were able to make the algorithm better and improve the quality of extraction results. In our experiments with 20 thousands targeted documents, we were able to extract property information with 83% confidence.
A Stroke-Based Text Extraction Algorithm for Digital Videos
Jeong, Jong-Myeon ; Cha, Ji-Hun ; Kim, Kyu-Heon ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 297~303
DOI : 10.5391/JKIIS.2007.17.3.297
In this paper, the stroke-based text extraction algorithm for digital video is proposed. The proposed algorithm consists of four stages such as text detection, text localization, text segmentation and geometric verification. The text detection stage ascertains that a given frame in a video sequence contains text. This procedure is accomplished by morphological operations for the pixels with higher possibility of being stroke-based text, which is called as seed points. For the text localization stage, morphological operations for the edges including seed points ate adopted followed by horizontal and vortical projections. Text segmentation stage is to classify projected areas into text and background regions according to their intensity distribution. Finally, in the geometric verification stage, the segmented area are verified by using prior knowledge of video text characteristics.
A Model of Context Awareness and Integration for Users Situation Awareness in Mobile P2P Environment
Yoon, Hyo-Gun ; Lee, Sang-Yong ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 304~309
DOI : 10.5391/JKIIS.2007.17.3.304
What is important in ubiquitous computing is collecting users' context information from various sensors and providing services suitable for use's current situation. Particularly in mobile environment, each area has different context awareness structure and this makes it difficult to share information with other areas. As a result, context resources for recognizing users' context ate insufficient. Moreover, because mobile devices have a limited processing capacity, there are difficulties in the real time analysis of users' context. This paper proposed a context awareness and integration model for analyzing users' context actively and providing adaptive services using mobile devices. The proposed model distinguishes users' context between dynamic and static structure to analyze the context, and obtains context resources by sharing context information of users within an area.
Design of intelligent fire detection / emergency based on wireless sensor network
Kim, Sung-Ho ; Youk, Yui-Su ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 310~315
DOI : 10.5391/JKIIS.2007.17.3.310
When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a u!;or preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or non-spam in a meaningful way. We also suggest a nor rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.
Quantitative Annotation of Edges, in Bayesian Networks with Condition-Specific Data
Jung, Sung-Won ; Lee, Do-Heon ; Lee, Kwang-H. ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 316~321
DOI : 10.5391/JKIIS.2007.17.3.316
We propose a quatitative annotation method for edges in Bayesian networks using given sets of condition-specific data. Bayesian network model has been used widely in various fields to infer probabilistic dependency relationships between entities in target systems. Besides the need for identifying dependency relationships, the annotation of edges in Bayesian networks is required to analyze the meaning of learned Bayesian networks. We assume the training data is composed of several condition-specific data sets. The contribution of each condition-specific data set to each edge in the learned Bayesian network is measured using the ratio of likelihoods between network structures of including and missing the specific edge. The proposed method can be a good approach to make quantitative annotation for learned Bayesian network structures while previous annotation approaches only give qualitative one.
Emotion Recognition Method using Physiological Signals and Gestures
Kim, Ho-Duck ; Yang, Hyun-Chang ; Sim, Kwee-Bo ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 322~327
DOI : 10.5391/JKIIS.2007.17.3.322
Researchers in the field of psychology used Electroencephalographic (EEG) to record activities of human brain lot many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study emotion recognition method which uses one of physiological signals and gestures in the existing research. In this paper, we use together physiological signals and gestures for emotion recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both physiological signals and gestures gets high recognition rates better than using physiological signals or gestures. Both physiological signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.
Ontology-based Image Understanding Systems
Lee, In-K. ; Seo, Suk-T. ; Jeong, Hye-C. ; Son, Seo-H. ; Kwon, Soon-H. ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 328~335
DOI : 10.5391/JKIIS.2007.17.3.328
Ontology is represented by the shared concepts and relations among those. Many studies have been actively working on sharing human's knowledge with that of systems by using it. For a typical example, there is the design and implementation of ontology system for image understanding. However conventional studies on ontology-based image understanding have proposed not concrete methods but conceptual idea. In this paper, we propose an ontology-based image understanding system with following four processes: i)knowledge representation of a specific domain by the ontology, ii)feature extraction of objects through image processing and image analysis, iii)image interpretation by object features, and iv)reduction of ambiguity existing in image interpretation by ontology reasoning. We implement an image understanding system based on the proposed processed, and show the effectiveness of the proposed system from experimental results in a specific domain.
The Design and Implementation of Embedded Linux-Based Industrial Wireless HMI Software Module
Choi, Suk-Young ; Moon, Seung-Jin ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 336~342
DOI : 10.5391/JKIIS.2007.17.3.336
Industrial HMI(Human Machine Interface) system is the main element among the factory automation processes and have been used to monitor and control operation and status of machine in factory with PLC. This HMI often brings heavy loads to the system development and difficult decreasing the system because it tends to use a specific system per each manufacturer. Therefore, in this thesis, we have developed an embedded linux-based embedded industrial HMI software modules which can be used for touch panel embedded system to solve these problem. In this module, we have used the Qt/Embedded software component because it can be used by all systems which support C++ compiler without modifying the existing codes. We can design more flexible system and network configuration because we have used the wireless communication module. In this thesis, we implement linux-based HMI software modules which are capable of wireless communication as well as bringing the mobility to the overall system and finally decreasing the system development loads by using the general purpose OS with competitive price.
Development of autonomous system using magnetic position meter
Kim, Geun-Mo ; Ryoo, Young-Jae ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 343~348
DOI : 10.5391/JKIIS.2007.17.3.343
Development of autonomous vehicle system that use magnetic position meter research of intelligence transportation system is progressed worldwide active by fast increase of vehicles. Among them, research about autonomous of vehicles occupies field. And autonomous of vehicles is element that path recognition is basic. Existent magnetic base autonomous system analyzes three-dimensional data of magnet marker to 3 axises magnetic sensor and recognized route. But because using Magnetic Wire and Magnetic Position Meter in treatise that see, measure side lateral error and propose system that driving. And system that compare with system of autonomous vehicles and propose wishes to verify by hardware of that specification and simple algorithm through an experiment that autonomous is available.
Object Tracking Using Template Based on Adaptive 3-Frame Difference
Kim, Hun-Ki ; Lee, Jin-Hyung ; Cho, Seong-Won ; Chung, Sun-Tae ; Kim, Jae-Min ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 349~354
DOI : 10.5391/JKIIS.2007.17.3.349
To generate the template of a detected object and to track the overlapped object and the object covered by other objects correctly are important research problems in visual surveillance. The frame difference is not capable of generating the template of slowly moving object. To get around the drawback of the conventional frame difference, we propose a new algorithm for generating a template using adaptive 3-frame difference.
A Study on the self-tuning of the design variables and gains using Fuzzy PI+D Controller
Jang, Cheol-Su ; Choi, Jeong-Won ; Oh, Young-Seok ; Chae, Seog ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 355~367
DOI : 10.5391/JKIIS.2007.17.3.355
This paper proposes a design method of the PI(Proportional-Integral)+D(Derivative) controller using self-tuning of the design variables and controller gains. The used fuzzy PI+D controller is the approximated conventional continuos time linear PI+D controller and the used fuzzification method is the fuzzy single tone and the adapted defuzzification method is the simplified tenter of gravity. Fuzzy estimation result would be calculated in the other function elements from the classified fuzzy variables and the result determined by the design variables decides the controller gains. As a result, the proposed method shows the capability of the high speed tuning and can be applied to the case of input variables with many fuzzy partitions and also can bring out the advantage to reduce the reconstruction(digital sampling reconstruction) error. Most simulation results show that this controller makes much bettor efficiency and improvement by using design variables and controller gains.
A Study on Image Segmentation and Tracking based on Fuzzy Method
Lee, Min-Jung ; Jin, Tae-Seok ; Hwang, Gi-Hyung ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 368~373
DOI : 10.5391/JKIIS.2007.17.3.368
In recent year s there have been increasing interests in real-time object tracking with image information. This dissertation presents a real-time object tracking method through the object recognition based on neural networks that have robust characteristics under various illuminations. This dissertation proposes a global search and a local search method to track the object in real-time. The global search recognizes a target object among the candidate objects through the entire image search, and the local search recognizes and track only the target object through the block search. This dissertation uses the object color and feature information to achieve fast object recognition. The experiment result shows the usefulness of the proposed method is verified.
A Study on the Improvement of Fault Detection Capability for Fault Indicator using Fuzzy Clustering and Neural Network
Hong, Dae-Seung ; Yim, Hwa-Young ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 374~379
DOI : 10.5391/JKIIS.2007.17.3.374
This paper focuses on the improvement of fault detection algorithm in FRTU(feeder remote terminal unit) on the feeder of distribution power system. FRTU is applied to fault detection schemes for phase fault and ground fault. Especially, cold load pickup and inrush restraint functions distinguish the fault current from the normal load current. FRTU shows FI(Fault Indicator) when the fault current is over pickup value or inrush current. STFT(Short Time Fourier Transform) analysis provides the frequency and time Information. FCM(Fuzzy C-Mean clustering) algorithm extracts characteristics of harmonics. The neural network system as a fault detector was trained to distinguish the inruih current from the fault status by a gradient descent method. In this paper, fault detection is improved by using FCM and neural network. The result data were measured in actual 22.9kV distribution power system.
Detection and Analysis of the Liver Region and Hepatoma in CT Images Using Shape-based Interpolation and Quantization Method
Kim, Kwang-Baek ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 380~389
DOI : 10.5391/JKIIS.2007.17.3.380
In Korea, undoubtedly, the cancer is one of the most common reasons of death, and hepatoma is the second highest fatal cancer regardless of the gender only next to the stomach cancer In the middle and prime-aged between 40 and 60 years, the incidence of hepatoma is the highest in the world, and the death rate due to hepatoma is the highest among OECD countries. In this paper, we propose a novel method for automatic identification of hepatoma from a contrast enhanced CT images, which is used in an expert system that helps medical specialists. First, consecutive
contrail enhanced CT images are photographed by every 5mm from the upper part of the chest, and using position information on the rib, we classify the internal area including only internal organs and the external one that consists of the rib, subcutaneous fat layers, and the background from the CT images. Then, the region of the liver is extracted from the classified internal area by using information on the intensity, the distribution of brightness, and using the regions extracted from consecutive images, we restore information on the 5 mm space occurred between the consecutive two slides tty applying a shape-based interpolation method. Lastly, using the characteristics such as the brightness and the morphology, we are able to extract the regions of hepatoma. The expert system based on our method is sufficiently competitive when it is compared with the diagnoses by specialists in the diagnostic radiology.
Conceptual Model for Fuzzy-CBR Support System for Collision Avoidance at Sea Using Ontology
Park, Gyei-Kark ; Kim, Woong-Gyu ; Benedictos, John Leslie RM ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 390~396
DOI : 10.5391/JKIIS.2007.17.3.390
Fuzzy-CBR Collision Avoidance Support System is a system that finds a solution from past knowledge retrieved from the database and adapted to a new situation. Its algorithm has resulted to an adapting a solution for a new situation. However, ontology is needed in identifying concepts, relations and instances that are involved in a situation in order to improve and facilitate the efficient retrieval of similar cases from the CBR database. This paper proposes the way to apply ontology for identifying the concepts involved in a new environment and use them as inputs, for a ship collision avoidance support system., Similarity will be obtained through document articulation and using abstraction levels. A conceptual model of a maneuvering situation will be built using these ontologies.
Cluster Analysis of Incomplete Microarray Data with Fuzzy Clustering
Kim, Dae-Won ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 397~402
DOI : 10.5391/JKIIS.2007.17.3.397
In this paper, we present a method for clustering incomplete Microarray data using alternating optimization in which a prior imputation method is not required. To reduce the influence of imputation in preprocessing, we take an alternative optimization approach to find better estimates during iterative clustering process. This method improves the estimates of missing values by exploiting the cluster Information such as cluster centroids and all available non-missing values in each iteration. The clustering results of the proposed method are more significantly relevant to the biological gene annotations than those of other methods, indicating its effectiveness and potential for clustering incomplete gene expression data.
Face Recognition using Contourlet Transform and PCA
Song, Chang-Kyu ; Kwon, Seok-Young ; Chun, Myung-Geun ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 403~409
DOI : 10.5391/JKIIS.2007.17.3.403
Contourlet transform is an extention of the wavelet transform in two dimensions using the multiscale and directional fillet banks. The contourlet transform has the advantages of multiscale and time-frequency-localization properties of wavelets, but also provides a high degree of directionality. In this paper, we propose a face recognition system based on fusion methods using contourlet transform and PCA. After decomposing a face image into directional subband images by contourlet, features are obtained in each subband by PCA. Finally, face recognition is performed by fusion technique that effectively combines similarities calculated respectively In each local subband. To show the effectiveness of the proposed method, we performed experiments for ORL and CBNU dataset, and then we obtained better recognition performance in comparison with the results produced by conventional methods.
A Study on Assessment Model of Interoperability in Weapon Systems based on LISI
Oh, Haeng-Rok ; Koo, Heung-Seo ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 410~416
DOI : 10.5391/JKIIS.2007.17.3.410
There are many demands for interoperability between weapon systems as the operational needs for joint and coalition based on network in modern and future warfare have been increasingly needed. In DoD, LISI has been applied throughout information system life cycle from the planning phase to the development phase to assess the level of interoperability. We also developed SITES which is a tool to assess the level of interoperability in information systems. But we should extend the assessment model from the previous information systems to the weapon systems to assess the level of interoperability including weapon systems as well as information systems. In this paper, we proposed the assessment model of interoperability, implemented the E-SITE based on the proposed model, applied 12 weapon systems and analyzed the experimental result.
Queen-bee and Mutant-bee Evolution for Genetic Algorithms
Jung, Sung-Hoon ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 417~422
DOI : 10.5391/JKIIS.2007.17.3.417
A new evolution method termed queen-bee and mutant-bee evolution is based on the previous queen-bee evolution . Even though the queen-bee evolution has shown very good performances, two parameters for strong mutation are added to the genetic algorithms. This makes the application of genetic algorithms with queen-bee evolution difficult because the values of the two parameters are empirically decided by a trial-and-error method without a systematic method. The queen- bee and mutant-bee evolution has no this problem because it does not need additional parameters for strong mutation. Experimental results with typical problems showed that the queen-bee and mutant-bee evolution produced nearly similar results to the best ones of queen-bee evolution even though it didn't need to select proper values of additional parameters.
The Fuzzy Jacobson Radical of a κ-Semiring
Kim, Chang-Bum ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 423~429
DOI : 10.5391/JKIIS.2007.17.3.423
We define and study the fuzzy Jacobson radical of a
-semiring. Also it is shown that the Jacobson radical of the quotient semiring R/FJR(R) of a
-semiring by the fuzzy Jacobson radical FJR(R) is semisimple. And the algebraic properties of the fuzzy ideals FJR(R) and FJR(S) under a homomorphism from R onto S are also discussed.
XSTAR: XQuery to SQL Translation Algorithms on RDBMS
Hong, Dong-Kweon ; Jung, Min-Kyoung ;
Journal of Korean Institute of Intelligent Systems, volume 17, issue 3, 2007, Pages 430~433
DOI : 10.5391/JKIIS.2007.17.3.430
There have been several researches to manipulate XML Queries efficiently since XML has been accepted in many areas. Among the many of the researches majority of them adopt relational databases as underlying systems because relational model which is used the most widely for managing large data efficiently. In this paper we develop XQuery to SQL Translation Algorithms called XSTAR that can efficiently handle XPath, XQuery FLWORs with nested iteration expressions, element constructors and keywords retrieval on relational database as well as constructing XML fragments from the transformed SQL results. The entire algorithms mentioned in XSTAR have been implemented as the XQuery processor engine in XML management system, XPERT, and we can test and confirm it's prototype from "http ://dblab.kmu.ac.kr/project.jsp".