• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.498-509
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• 2001

Collaborative systems allow users, who may be far removed from each other geographically, to do collaborative work such as 3D animation, computer game, and industrial design in a single virtual space. This paper describes our experience to develop a collaborative system framework that aims at expanding the some functions of a stand-alone visual modeling tool, called 3D Studio Max, into those of the distributed collaborative working environments. The paper mainly deals with design and implementation of a 3D shared-object Plug-In with respect to the 3D Studio Max Plug-In Software Development Kit in the distributed collaborative system developed by the authors. There are two major functions of the proposed scheme; one is to write 3D object-information to the shared memory after extracting it from the 3D Studio Max, the other is to create 3D objects after retrieving them from the shared memory. Also, the proposed scheme provides a simple way of storing 3D objects that have variable size, by means of shared memory which located in between the collaborative system clients and 3D studio Max. One of the remarkable virtures of the Plug-In is to reduce a considerable amount of shared object data which in consequence can mitigate the network overhead. This can be achieved by the fact that the system is able to extract a minimum amount of 3D objects that are required to transmit. Also, using the proposed scheme, user can facilitate 3D Studio Max into distributed collaborative working environments. This, in consequence give many benefits such as saving time as well as eliminating space constraints in the course of 3D modeling when we are under industrial design process.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.108-121
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• 2004

In this paper, we propose an enhanced snapshot technique that solves performance degradation when snapshot is initiated for the storage cluster system. However, traditional snapshot technique has some limits adapted to large amount storage shared by multi-hosts in the following aspects. As volume size grows, (1) it deteriorates crucially the performance of write operations due to additional disk access to verify COW is performed. (2) Also it increases excessively the blocking time of write operation performed during the snapshot creation time. (3)Finally, it deteriorates the performance of write operations due to additional disk I/O for mapping block caused by the verification of COW. In this paper, we propose an efficient snapshot technique for large amount storage shared by multi-hosts in SAN Environments. We eliminate the blocking time of write operation caused by freezing while a snapshot creation is performing. Also to improve the performance of write operation when snapshot is taken, we introduce First Allocation Bit(FAB) and Snapshot Status Bit(SSB). It improves performance of write operation by reducing an additional disk access to volume disk for getting snapshot mapping block. We design and implement an efficient snapshot technique, while the snapshot deletion time, improve performance by deallocation of COW data block using SSB of original mapping entry without snapshot mapping entry obtained mapping block read from the shared disk.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.623-634
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• 2003

In this paper, we propose a collaborative multimedia authoring system. Our authoring system represents a multimedia presentation in a 3D coordinate system. One axis represents the traditional timeline information (T-zone), and the other two axes represent spatial coordinates (XY-zone). Our system represents a visual media objects as a 3D parallelepipeds and audio media objects as cylinders. This interface allows for simultaneous authoring and manipulation of both the temporal and the spatial aspects of a presentation. Using our system, users can design multimedia presentations collaboratively in the unified spatio-temporal space while freely traversing the spatial domain and the temporal domain without changing the context of authoring. In addition, we suggest an efficient mechanism of concurrency control for shared objects generated by our collaborative writing system. The mechanism is mainly based on the user awareness, the multiple versions, and the access permission of shared objects. Our concurrency control mechanism is designed to keep data consistency by minimizing the collision due to the delay or the failure of network communication and to allow maximum responsiveness for users using optimistic concurrency control. Also, the mechanism maximize the responsiveness by refining the locking granularity and applying different concurrency control mechanisms to each.

• Journal of KIISE:Software and Applications
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• v.35 no.2
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• pp.70-80
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• 2008

Today, businesses have to respond with flexibility and speed to ever-changing customer demand and market opportunities. Service-oriented architecture (SOA) is the best methodology for minimizing the complexity and the cost of enterprise-level infrastructure and for maximizing the productivity and the flexibility of an enterprise. Most of the enterprise-level SOA delivery strategies deal with the top-down approach, which organization has to define the business processes, to model business services, and to find the required services or to develop new services. However, a lot of peoples want to maximally reuse legacy component-based systems as well as to deliver SOA into their organizations. In this paper, we propose a bottom-up approach for identifying business services with proper granularity. It can improve the reusability and maintenance of services by considering not data I/O of components of legacy applications but GUI event patterns. Our proposed method is applied to MIS with 129 GUIs and 13 components. As a result, the valiance of the coupling value of components is increased five times and three business services are distinctly exposed. It also provides a 49% improvement in reducing the relationship problems between services over a service identification method using only partitioning information of components.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.1-10
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• 2007

This paper proposes a new indexing mechanism for MPEG-7 visual descriptors, especially Dominant Color and Contour Shape descriptors, that guarantees an efficient similarity search for the multimedia database whose visual meta-data are represented with MPEG-7. Since the similarity metric used in the Dominant Color descriptor is based on Gaussian mixture model, the descriptor itself could be transform into a color histogram in which the distribution of the color values follows the Gauss distribution. Then, the transformed Dominant Color descriptor (i.e., the color histogram) is indexed in the proposed indexing mechanism. For the indexing of Contour Shape descriptor, we have used a two-pass algorithm. That is, in the first pass, since the similarity of two shapes could be roughly measured with the global parameters such as eccentricity and circularity used in Contour shape descriptor, the dissimilar image objects could be excluded with these global parameters first. Then, the similarities between the query and remaining image objects are measured with the peak parameters of Contour Shape descriptor. This two-pass approach helps to reduce the computational resources to measure the similarity of image objects using Contour Shape descriptor. This paper also proposes two integration schemes of visual descriptors for an efficient retrieval of multimedia database. The one is to use the weight of descriptor as a yardstick to determine the number of selected similar image objects with respect to that descriptor, and the other is to use the weight as the degree of importance of the descriptor in the global similarity measurement. Experimental results show that the proposed indexing and integration schemes produce a remarkable speed-up comparing to the exact similarity search, although there are some losses in the accuracy because of the approximated computation in indexing. The proposed schemes could be used to build a multimedia database represented in MPEG-7 that guarantees an efficient retrieval.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.226-234
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• 2007

In this paper, we develop a speech recognition system using a throat microphone. The use of this kind of microphone minimizes the impact of environmental noise. However, because of the absence of high frequencies and the partially loss of formant frequencies, previous systems developed with those devices have shown a lower recognition rate than systems which use standard microphone signals. This problem has led to researchers using throat microphone signals as supplementary data sources supporting standard microphone signals. In this paper, we present a high performance ASR system which we developed using only a throat microphone by taking advantage of Korean Phonological Feature Theory and a detailed throat signal analysis. Analyzing the spectrum and the result of FFT of the throat microphone signal, we find that the conventional MFCC feature vector that uses a critical pass filter does not characterize the throat microphone signals well. We also describe the conditions of the feature extraction algorithm which make it best suited for throat microphone signal analysis. The conditions involve (1) a sensitive band-pass filter and (2) use of feature vector which is suitable for voice/non-voice classification. We experimentally show that the ZCPA algorithm designed to meet these conditions improves the recognizer's performance by approximately 16%. And we find that an additional noise-canceling algorithm such as RAST A results in 2% more performance improvement.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.420-436
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• 2007

The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

• Journal of KIISE:Information Networking
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• v.32 no.3
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• pp.318-326
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• 2005

This paper presents the image feature extraction method and the image classification technique to select the harmful image flowed from the Internet by grade of image contents such as harmlessness, sex-appealing, harmfulness (nude), serious harmfulness (adult) by the characteristic of the image. In this paper, we suggest skin area detection technique to recognize whether an input image is harmful or not. We also propose the ROI detection algorithm that establishes region of interest to reduce some noise and extracts harmful degree effectively and defines the characteristics in the ROI area inside. And this paper suggests the multiple-SVM training method that creates the image classification model to select as 4 types of class defined above. This paper presents the multiple-SVM classification algorithm that categorizes harmful grade of input data with suggested classification model. We suggest the skin likelihood image made of the shape information of the skin area image and the color information of the skin ratio image specially. And we propose the image feature vector to use in the characteristic category at a course of traininB resizing the skin likelihood image. Finally, this paper presents the performance evaluation of experiment result, and proves the suitability of grading image using image feature classification algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.510-521
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• 2001

Image retrieval system should be construct for searching fast, efficient image be extract the accurate feature information of image with more massive and more complex characteristics. Image retrieval system are essential differences between image databases and traditional databases. These differences lead to interesting new issues in searching of image, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of image. In this paper, To extract feature information of edge using in searching from input image, we was performed to extract the edge by convolution Laplacian mask and input image, and we implemented the annotation-based and content-based image retrieval system for searching fast, efficient image by generation image database from extracting feature information of edge and metadata. We can improve the performance of the image contents retrieval, because the annotation-based and content-based image retrieval system is using image index which is made up of the content-based edge feature extract information represented in the low level of image and annotation-based edge feature information represented in the high level of image. As a conclusion, image retrieval system proposed in this paper is possible the accurate management of the accumulated information for the image contents and the information sharing and reuse of image because the proposed method do construct the image database by metadata.

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1111-1120
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• 2005

In collaborative filtering systems most users do not rate preferences; so User-Item matrix shows great sparsity because it has missing values for items not rated by users. Generally, the systems predict the preferences of an active user based on the preferences of a group of users. However, default voting methods predict all missing values for all users in User-Item matrix. One of the most common methods predicting default voting values tried two different approaches using the average rating for a user or using the average rating for an item. However, there is a problem that they did not consider the characteristics of items, users, and the distribution of data set. We replace the missing values in the User-Item matrix by the default noting method using user coefficient of variance. We select the threshold of user coefficient of variance by using equations automatically and determine when to shift between the user averages and item averages according to the threshold. However, there are not always regular relations between the averages and the thresholds of user coefficient of variances in datasets. It is caused that the distribution information of user coefficient of variances in datasets affects the threshold of user coefficient of variance as well as their average. We decide the threshold of user coefficient of valiance by combining them. We evaluate our method on MovieLens dataset of user ratings for movies and show that it outperforms previously default voting methods.