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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Journal DOI :
Korea Information Processing Society
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Volume & Issues
Volume 8B, Issue 5 - Oct 2001
Volume 8B, Issue 4 - Aug 2001
Volume 8B, Issue 3 - Jun 2001
Volume 8B, Issue 2 - Apr 2001
Volume 8B, Issue 1 - Feb 2001
Volume 8B, Issue 6 - Jan 2001
Selecting the target year
A Mathematics Tutoring Model That Supports Interactive Learning of Problem Solving Based on Domain Principles
Kook, Hyung-Joon ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 429~440
To achieve a computer tutor framework with high learning effects as well as practicality, the goal of this research has been set to developing an intelligent tutor for problem-solving in mathematics domain. The maine feature of the CyberTutor, a computer tutor developed in this research, is the facilitation of a learning environment interacting in accordance with the learners differing inferential capabilities and needs. The pedagogical information, the driving force of such an interactive learning, comprises of tutoring strategies used commonly in various domains such as phvsics and mathematics, in which the main contents of learning is the comprehension and the application of principles. These tutoring strategies are those of testing learners hypotheses test, providing hints, and generating explanations. We illustrate the feasibility and the behavior of our propose framework with a sample problem-solving learning in geometry. The proposed tutorial framework is an advancement from previous works in several aspects. Firstly, it is more practical since it supports handing of a wide range of problem types, including not only proof types but also finding-unkown tpes. Secondly, it is aimed at facilitating a personal tutor environment by adapting to learners of varying capabilities. Finally, learning effects are maximized by its tutorial dialogues which are derived from real-time problem-solving inference instead of from built-in procedures.
A Study on Production Mechanism of Meta-Knowledge for Effectively Managing Contents and Models
Kim, Chul-Soo ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 441~446
On global interconnectivity, the activation of real-time and worldwide contents will permeate and impact all aspects of day-to-day life well throughout this century. In managing contents and models, we too will see the impact of this rapidly changing environment. The real time availability of contents pertaining to a companys supply chain through means of the Internet and mobile networks(e.g., the IMT-2000) will necessitate a change in decision-making processes for effective management of contents and models. To increase the availability of many contents and models, a management system should have adaptive function in proving adequate content and model for companies. In the respect of management of contents and models, this paper discusses a production mechanism of meta-knowledge for effectively managing contents and models. Through two experimental analyses with the production mechanism, it is proven that the system enabling adaptive contents and models provision goes beyond existing ones in view of efficiency of management of contents and models in the wire and wireless networks.
An Automatic Classification System of Korean Documents Using Weight for Keywords of Document and Word Cluster
Hur, Jun-Hui ; Choi, Jun-Hyeog ; Lee, Jung-Hyun ; Kim, Joong-Bae ; Rim, Kee-Wook ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 447~454
The automatic document classification is a method that assigns unlabeled documents to the existing classes. The automatic document classification can be applied to a classification of news group articles, a classification of web documents, showing more precise results of Information Retrieval using a learning of users. In this paper, we use the weighted Bayesian classifier that weights with keywords of a document to improve the classification accuracy. If the system cant classify a document properly because of the lack of the number of words as the feature of a document, it uses relevance word cluster to supplement the feature of a document. The clusters are made by the automatic word clustering from the corpus. As the result, the proposed system outperformed existing classification system in the classification accuracy on Korean documents.
A Learning Agent for Automatic Bookmark Classification
Kim, In-Cheol ; Cho, Soo-Sun ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 455~462
The World Wide Web has become one of the major services provided through Internet. When searching the vast web space, users use bookmarking facilities to record the sites of interests encountered during the course of navigation. One of the typical problems arising from bookmarking is that the list of bookmarks lose coherent organization when the the becomes too lengthy, thus ceasing to function as a practical finding aid. In order to maintain the bookmark file in an efficient, organized manner, the user has to classify all the bookmarks newly added to the file, and update the folders. This paper introduces our learning agent called BClassifier that automatically classifies bookmarks by analyzing the contents of the corresponding web documents. The chief source for the training examples are the bookmarks already classified into several bookmark folders according to their subject by the user. Additionally, the web pages found under top categories of Yahoo site are collected and included in the training examples for diversifying the subject categories to be represented, and the training examples for these categories as well. Our agent employs naive Bayesian learning method that is a well-tested, probability-based categorizing technique. In this paper, the outcome of some experimentation is also outlined and evaluated. A comparison of naive Bayesian learning method alongside other learning methods such as k-Nearest Neighbor and TFIDF is also presented.
A New Similarity Measure based on RMF and It s Application to Linguistic Approximation
Choe, Dae-Yeong ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 463~468
We propose a new similarity measure based on relative membership function (RMF). In this paper, the RMF is suggested to represent the relativity between fuzzy subsets easily. Since the shape of the RMF is determined according to the values of its parameters, we can easily represent the relativity between fuzzy subsets by adjusting only the values of its parameters. Hence, we can easily reflect the relativity among individuals or cultural differences when we represent the subjectivity by using the fuzzy subsets. In this case, these parameters may be regarded as feature points for determining the structure of fuzzy subset. In the sequel, the degree of similarity between fuzzy subsets can be quickly computed by using the parameters of the RMF. We use Euclidean distance to compute the degree of similarity between fuzzy subsets represented by the RMF. In the meantime, we present a new linguistic approximation method as an application area of the proposed similarity measure and show its numerical example.
A Study on Classification of Medical Information Documents using Word Correlation
Lim, Hyeong-Geon ; Jang, Duk-Sung ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 469~476
As the service of information through web system increases in modern society, many questions and consultations are going on through Home page and E-mail in the hospital. But there are some burdens for the management and postponements for answering the questions. In this paper, we investigate the document classification methods as a primary research of the auto-answering system. On the basis of 1200 documents which are questions of patients, 66% are used for the learning documents and 34% for test documents. All of are also used for the document classification using NBC (Naive Bayes Classifier), common words and coefficient of correlation. As the result of the experiments, the two methods proposed in this paper, that is, common words and coefficient of correlation are higher as much as 3% and 5% respectively than the basic NBC methods. This result shows that the correlation between indexes and categories is more effective than the word frequency in the document classification,
Hybrid Learning Algorithm for Improving Performance of Regression Support Vector Machine
Jo, Yong-Hyeon ; Park, Chang-Hwan ; Park, Yong-Su ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 477~484
This paper proposes a hybrid learning algorithm combined momentum and kernel-adatron for improving the performance of regression support vector machine. The momentum is utilized for high-speed convergence by restraining the oscillation in the process of converging to the optimal solution, and the kernel-adatron algorithm is also utilized for the capability by working in nonlinear feature spaces and the simple implementation. The proposed algorithm has been applied to the 1-dimension and 2-dimension nonlinear function regression problems. The simulation results show that the proposed algorithm has better the learning speed and performance of the regression, in comparison with those quadratic programming and kernel-adatron algorithm.
The Implementation of the Personalized Emotional Character Agent
Baek, Hye-Jung ; Park, Young-Tack ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 485~492
Recently, character agents are used as a user-friendly interface. In this paper, we have studied a generic framework for emotional character agents which are designed to infer emotions from diverse personalities, situations, user behaviors and to express them. The method of emotion inference is based on blackboard systems which are used to solve the problems in AI. Because it keeps independence between knowledge sources which are rules of emotions, a blackboard-based inference engine is easy to manage knowledge sources, Blackboard-based systems gave the system flexibility. So we can adapt the engine to various application systems. Each emotional agent monitors user behavior, learns user profile and infers user behavior. And it generates characters emotions according to the user profile. So, in case of same situations, the agent can generate different emotions according to users. We have studied to build an personalized emotional character agent which according to situations and user modeling.
Video Data Scene Segmentation Method Using Region Segmentation
Yeom, Seong-Ju ; Kim, U-Saeng ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 493~500
Video scene segmentation is fundamental role for content based video analysis. In this paper, we propose a new region based video scene segmentation method using continuity test for each object region which is segmented by the watershed algorithm for all frames in video data. For this purpose, we first classify video data segments into classes that are the dynamic and static sections according to the object movement rate by comparing the spatial and shape similarity of each region. And then, try to segment each sections by grouping each sections by comparing the neighbor section sections by comparing the neighbor section similarity. Because, this method uses the region which represented on object as a similarity measure, it can segment video scenes efficiently without undesirable fault alarms by illumination and partial changes.
Fuzzy-Based Object Manager for Multimedia Post-Office Box Construction
Lee, Jong-Deuk ; Jeong, Taek-Won ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 501~506
According to the current increase of the usefulness of information by Internet and Communication network, several methods are proposed in which multimedia information may be efficiently managed and serviced. This paper proposes FBOM(Fuzzy-Based Object Manager) using
-cut in Object manager for Fuzzy-Based Multimedia Post-Office Box construction. The proposed system utilizes object discrimination, fuzzy filtering, and class generation structure in order to manage object using Fuzzy filtering. To know how well the proposed system are able to work, this paper have tested against the methods with 1000 items of multimedia information, and our system are compared with Random-key method and FBOM method.
Caching Framework for Multimedia
Kim, Baek-Hyeon ; U, Yo-Seop ; Kim, Ik-Su ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 507~514
In VOD(Video-on-Demand) system, the real-time interactive service is one of the most important factor to determine the degree of QoS(Quality of Service). In this paper, we propose the head-end system consisted of switching agent and head-end node, which needs to receive the only video stream for multiple users which have requested the same video, to serve the unlimited interactive service which has no service delay and block. The unlimited VCR services can be served by storing the video stream with buffer at client and head-end node. And the proposed algorithm presents the method to enhance the efficiency by buffer, offer the true interactive VOD services to users because all of service requested by clients are processed immediately. In this paper, we implemented the VOD system which has the VCR functions without service delay and block. Simulation results indicate that the proposed algorithm has better performance in the number of service request and time interval.
A Method of Highspeed Similarity Retrieval based on Self-Organizing Maps
Oh, Kun-Seok ; Yang, Sung-Ki ; Bae, Sang-Hyun ; Kim, Pan-Koo ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 515~522
Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Map(SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data, and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. We implemented about k-NN search for similar image classification as to (1) access to topological feature map, and (2) apply to pruning strategy of high speed search. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.
Design and Evaluation of a Reservation-Based Hybrid Disk Bandwidth Reduction Policy for Video Servers
Oh, Sun-Jin ; Lee, Kyung-Sook ; Bae, Ihn-Han ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 523~532
A Critical issue in the performance of a video-on-demand system is the required I/O bandwidth of the Video server in order to satisfy clients requests, and it is the crucial resource that may cause delay increasingly. Several approaches such as batching and piggybacking are used to reduce the I/O demand on the video server through sharing. Bathing approach is to make single I/O request for storage server by grouping the requests for the same object. Piggybacking is th policy for altering display rates of requests in progress for the same object to merge their corresponding I/O streams into a single stream, and serve it as a group of merged requests. In this paper, we propose a reservation-based hybrid disk bandwidth reduction policy that dynamically reserves the I/O stream capacity of a video server for popular videos according to the loads of video server in order to schedule the requests for popular videos immediately. The performance of the proposed policy is evaluated through simulations, and is compared with that of bathing and piggybacking. As a result, we know that the reservation-based hybrid disk bandwidth reduction policy provides better probability of service, average waithing time and percentage of saving in frames than batching and piggybacking policy.
Content-based Image Retrieval Using Fuzzy Multiple Attribute Relational Graph
Jung, Sung-Hwan ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 533~538
In this paper, we extend FARGs single mode attribute to multiple attributes for real image application and present a new CBIR using FMARG(Fuzzy Multiple Attribute Relational Graph), which can handle queries involving multiple attributes, not only object label, but also color, texture and spatial relation. In the experiment using the synthetic image database of 1,024 images and the natural image database of 1.026 images built from NETRA database and Corel Draw, the proposed approach shows 6~30% recall increase in the synthetic image database and a good performance, at the displacements and the retrieved number of similar images in the natural image database, compared with the single attribute approach.
A Study on Tracking Algorithm for Moving Object Using Partial Boundary Line Information
Jo, Yeong-Seok ; Lee, Ju-Sin ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 539~548
In this paper, we propose that fast tracking algorithm for moving object is separated from background, using partial boundary line information. After detecting boundary line from input image, we track moving object by using the algorithm which takes boundary line information as feature of moving object. we extract moving vector on the imput image which has environmental variation, using high-performance BMA, and we extract moving object on the basis of moving vector. Next, we extract boundary line on the moving object as an initial feature-vector generating step for the moving object. Among those boundary lines, we consider a part of the boundary line in every direction as feature vector. And then, as a step for the moving object, we extract moving vector from feature vector generated under the information of the boundary line of the moving object on the previous frame, and we perform tracking moving object from the current frame. As a result, we show that the proposed algorithm using feature vector generated by each directional boundary line is simple tracking operation cost compared with the previous active contour tracking algorithm that changes processing time by boundary line size of moving object. The simulation for proposed algorithm shows that BMA operation is reduced about 39% in real image and tracking error is less than 2 pixel when the size of feature vector is [
] using the information of each direction boundary line. Also the proposed algorithm just needs 200 times of search operation bout processing cost is varies by the size of boundary line on the previous algorithm.
3D Depth Information Extraction Algorithm Based on Motion Estimation in Monocular Video Sequence
Park, Jun-Ho ; Jeon, Dae-Seong ; Yun, Yeong-U ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 549~556
The general problems of recovering 3D for 2D imagery require the depth information for each picture element form focus. The manual creation of those 3D models is consuming time and cost expensive. The goal in this paper is to simplify the depth estimation algorithm that extracts the depth information of every region from monocular image sequence with camera translation to implement 3D video in realtime. The paper is based on the property that the motion of every point within image which taken from camera translation depends on the depth information. Full-search motion estimation based on block matching algorithm is exploited at first step and ten, motion vectors are compensated for the effect by camera rotation and zooming. We have introduced the algorithm that estimates motion of object by analysis of monocular motion picture and also calculates the averages of frame depth and relative depth of region to the average depth. Simulation results show that the depth of region belongs to a near object or a distant object is in accord with relative depth that human visual system recognizes.
Optimal Block Matching Motion Estimation Using the Minimal Deviation of Motion Compensation Error Between Moving Regions
Jo, Yeong-Chang ; Lee, Tae-Heung ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 557~564
In general, several moving regions with different motions coexist in a block located on motion boundaries in the block-based motion estimation. In this case the motion compensation error(MCEs) are different with the moving regions. This is inclined to deteriorate the quality of motion compensated images because of the inaccurate motions estimated from the conventional mean absolute error(MAE) based matching function in which the matching error per pixel is accumulate throughout the block. In this paper, we divided a block into the regions according to their motions using the motion information of the spatio-temporally neighboring blocks and calculate the average MCF for each moving mentioned. From the simulation results, we showed the improved performance of the proposed method by comparing the results from other methods such as the full search method and the edge oriented block matching algorithm. Especially, we improved the quality of the motion compensated images of blocks on motion boundaries.
A New Metric for Joint Effective Width Computation
Lee, Jeok-Sik ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 565~572
Analyzing functions with small values of the product of position and frequency uncertainties have many advantages in image processing and data compression. Until now, this values has been computed based on the uncertainty principle, but the computed frequency uncertainty is not practical the human visual filters which have on-zero peak response frequencies. A new metric for the frequency uncertainty is used to calculate a deviation about the frequency which has maximum response. The joint effective widths for various functions are derived. As the result of analysis, the joint uncertainty for many functions converges to 0.5 as the joint parameter increases. Furthermore. Gabor cosine function shows an excellent performance among the mentioned functions.
LSG;(Local Surface Group); A Generalized Local Feature Structure for Model-Based 3D Object Recognition
Lee, Jun-Ho ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 573~578
This research proposes a generalized local feature structure named "LSG(Local Surface Group) for model-based 3D object recognition". An LSG consists of a surface and its immediately adjacent surface that are simultaneously visible for a given viewpoint. That is, LSG is not a simple feature but a viewpoint-dependent feature structure that contains several attributes such as surface type. color, area, radius, and simultaneously adjacent surface. In addition, we have developed a new method based on Bayesian theory that computes a measure of how distinct an LSG is compared to other LSGs for the purpose of object recognition. We have experimented the proposed methods on an object databaed composed of twenty 3d object. The experimental results show that LSG and the Bayesian computing method can be successfully employed to achieve rapid 3D object recognition.
A Study on Digital Watermarking of MPEG Coded Video Using Wavelet Transform
Lee, Hak-Chan ; Jo, Cheol-Hun ; Song, Jung-Won ;
The KIPS Transactions:PartB, volume 8B, issue 5, 2001, Pages 579~586
Digital watermarking is to embed imperceptible mark into image, video, audio, and text data to prevent the illegal copy of multimedia data. arbitrary modification, and also illegal sales of the copies without agreement of copyright ownership. In this paper, we study for the embedding and extraction of watermark key using wavelet in the luminance signal in order to implement the system to protect the copyright for image MPEG. First, the original image is analyzed into frequency domain by discrete wavelet transform. The RSA(Rivest, Shamir, Aldeman) public key of the coded target is RUN parameter of VLD(variable length coding). Because the high relationship among the adjacent RUN parameters effect the whole image, it prevents non-authorizer not to possess private key from behaving illegally. The Results show that the proposed method provides better moving picture and the distortion more key of insert than direct coded method on low-frequency domain based DCT.