• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.1
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• pp.57-68
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• 1993

In this paper, we describe a multiprocessor system using the HiPi bus with pended protocol and multiple cache memories, and evalute the performance of the multiprocessor system in terms of processor utilization for various cache coherence protocols. The HiPi bus is delveloped as the shared bus of TICOM II which is a main computer system to establish a nation-wide computing network in ETRI. The HiPi bus has high data transfer rate, but it doesn't allow cache-to-cache transfer. In order to evaluate the effect of cache-to-cache transfer upon the performance of system and to choose a best-performed protocol for HiPi bus, we simulate as follows: First, we analyze the performance of multiprocessor system with HiPi bus in terms of processor utilizatIOn through simulation. Each of cache coherence protocol is described by state transition diagram, and then the probability of each state is calculated by Markov steady state. The calculated probability of each state is used as input parameters of simulation, and modeling and simulation are implemented and performed by using SLAM II graphic symbols and language. Second, we propose the HiPi bus which supports cache-to-cache transfer, and analyze the performance of multiprocessor system with proposed HiPi bus in terms of processor utilization through simulation. Considered cache coherence protocols for the simulation are Write-through, Write-once, Berkely, Synapse, Illinois, Firefly, and Dragon.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• Computational Structural Engineering
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• v.6 no.2
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• pp.95-102
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• 1993

A modeling method is described to provide a smaller structural dynamic model which can be used to compare finite element model of a structure with its experimental counterpart. A structural dynamic model is assumed to be represented by dynamic stiffness matrix. To validate a finite element model, it is often necessary to condense a large degrees of freedom (dofs) to a relatively small number of dofs. For these purpose, static reduction techniques are widely used. However, errors in these techniques are caused by neglecting frequency dependent terms in the functions relating slave dofs and master dofs. An alternative method is proposed in this paper in which the frequency dependent terms are considered by expressing the reduced dynamic stiffness matrix with orthogonal polynomials. The reduced model has finally a minimum set of dofs, such as sensors and excitation points and it is under the same condition as the physical system. It is proposed that the reduced model can be derived from finite element model. The procedure is applied to example structure and the results are discussed.

• Journal of the Korea Computer Graphics Society
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• v.5 no.2
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• pp.33-41
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• 1999

This paper presents a new algorithm about motion adjustment for dynamic balance. It adjusts an unbalanced motion to an balanced motion while preserving the nuance of original motion. We solve dynamic balancing problem using the zero moment point (ZMP) which is often used for controlling the balance of biped robot. Our algorithm is consists of four steps. First, it fits joint angle data to spline curves for reducing noise. Second, the algorithm analyzes the ZMP trajectory so that it can detects the dynamically-unbalanced duration. Third, the algorithm project the ZMP trajectory into the supporting area if the trajectory deviates from the area. Finally, the algorithm produces the balanced motion that satisfies the new ZMP trajectory. In this step, the constrained optimization method is used so that the new motion keeps the original motion characteristics as much as possible. We make several experiments in order to prove that our algorithm is useful to add physical realism to a kinematically edited motion.

• Database Research
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• v.34 no.3
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• pp.69-85
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• 2018

Many researches proposed federated query engines to perform query on several homogeneous or heterogeneous datasets simultaneously that significantly improve the quality of query results. The existing techniques allow querying only over a few heterogeneous datasets considering the static binding using the non-standard query. However, we observe that a simultaneous system considering the integration of heterogeneous metadata standards can offer better opportunity to generalize the query over any homogeneous and heterogeneous datasets. In this paper, we propose a transparent federated engine (DRAZ) to query over multiple data sources using SPARQL. In our system, we first develop the ontology for a non-RDF metadata standard based on the metadata kernel dictionary elements, which are standardized by the metadata provider. For a given SPARQL query, we translate any triple pattern into an API call to access the dataset of corresponding non-RDF metadata standard. We convert the results of every API call to N-triples and summarize the final results considering all triple patterns. We evaluated our proposed DRAZ using modified Fedbench benchmark queries over heterogeneous metadata standards, such as DCAT and DOI. We observed that DRAZ can achieve 70 to 100 percent correctness of the results despite the unavailability of the JOIN operations.

• Journal of KIISE:Information Networking
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• v.32 no.6
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• pp.687-695
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• 2005

With increasing demand of using mobile Internet, HMIPv6 is proposed by IETF to reduce location management traffics due to micro mobility and to provide IP-based movement. A paging mechanism combined with HMIPv6 can reduce the signaling traffics of a mobile node. We propose a dynamic paging mechanism in HMIPv6 which decides an optimal paging area for each mobile node by considering its characteristics. Total costs of a static paging mechanism and a dynamic paging mechanism are analyzed by mathematical formulas. As a result, we proved that the dynamic paging mechanism reduced total signal traffic costs more than a static paging mechanism.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.169-177
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• 2009

In this paper, we propose a new shot boundary detection method which is optimized for news video story parsing. This new news shot boundary detection method was designed to satisfy all the following requirements: 1) minimizing the incorrect data in data set for anchor shot detection by improving the recall ratio 2) detecting abrupt cuts and gradual transitions with one single algorithm so as to divide news video into shots with one scan of data set; 3) classifying shots into static or dynamic, therefore, reducing the search space for the subsequent stage of anchor shot detection. The proposed method, based on singular value decomposition with incremental clustering and mercer kernel, has additional desirable features. Applying singular value decomposition, the noise or trivial variations in the video sequence are removed. Therefore, the separability is improved. Mercer kernel improves the possibility of detection of shots which is not separable in input space by mapping data to high dimensional feature space. The experimental results illustrated the superiority of the proposed method with respect to recall criteria and search space reduction for anchor shot detection.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.55-62
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• 2009

Location based Services in the ubiquitous computing environment, namely u-LBS, use very large and skewed spatial objects that are closely related to locational information. It is especially essential to achieve fast search, which is looking for POI(Point of Interest) related to the location of users. This paper examines how to search large and skewed POI efficiently in the u-LBS environment. We propose the Dynamic-level Grid based R-Tree(DGR-Tree), which is an index for point data that can reduce the cost of stationary POI search. DGR-Tree uses both R-Tree as a primary index and Dynamic-level Grid as a secondary index. DGR-Tree is optimized to be suitable for point data and solves the overlapping problem among leaf nodes. Dynamic-level Grid of DGR-Tree is created dynamically according to the density of POI. Each cell in Dynamic-level Grid has a leaf node pointer for direct access with the leaf node of the primary index. Therefore, the index access performance is improved greatly by accessing the leaf node directly through Dynamic-level Grid. We also propose a K-Nearest Neighbor(KNN) algorithm for DGR-Tree, which utilizes Dynamic-level Grid for fast access to candidate cells. The KNN algorithm for DGR-Tree provides the mechanism, which can access directly to cells enclosing given query point and adjacent cells without tree traversal. The KNN algorithm minimizes sorting cost about candidate lists with minimum distance and provides NEB(Non Extensible Boundary), which need not consider the extension of candidate nodes for KNN search.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.447-458
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• 2008

In this paper, we address an efficient processing scheme for k-nearest neighbor queries to retrieve k static objects in road network databases. Existing methods cannot expect a query processing speed-up by index structures in road network databases, since it is impossible to build an index by the network distance, which cannot meet the triangular inequality requirement, essential for index creation, but only possible in a totally ordered set. Thus, these previous methods suffer from a serious performance degradation in query processing. Another method using pre-computed network distances also suffers from a serious storage overhead to maintain a huge amount of pre-computed network distances. To solve these performance and storage problems at the same time, this paper proposes a novel approach that creates an index for moving objects by approximating their network distances and efficiently processes k-nearest neighbor queries by means of the approximate index. For this approach, we proposed a systematic way of mapping each moving object on a road network into the corresponding absolute position in the m-dimensional space. To meet the triangular inequality this paper proposes a new notion of average network distance, and uses FastMap to map moving objects to their corresponding points in the m-dimensional space. After then, we present an approximate indexing algorithm to build an R*-tree, a multidimensional index, on the m-dimensional points of moving objects. The proposed scheme presents a query processing algorithm capable of efficiently evaluating k-nearest neighbor queries by finding k-nearest points (i.e., k-nearest moving objects) from the m-dimensional index. Finally, a variety of extensive experiments verifies the performance enhancement of the proposed approach by performing especially for the real-life road network databases.

• Journal of The Korean Association of Information Education
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• v.1 no.1
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• pp.49-59
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• 1997

In this thesis, To provide the base of effective data access methods, performance of some indexing techniques used gent-Tally are compared. They are classified as primary key and multikey. For primary key method, made a comparative analysis on Static index. Dynamic index and Hashing. For multikey indexing method K-d tree, K-d-B tree, Inverted file and Grid file of which characteristics are compared. In many applications, multikey indexings are more requested, but are not supplied enough. So, to satisfy users' request - more fast, more exact and to be applied according to the trend of being huge database systems, it is requested more study about multikey data access methods.