• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.42-53
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• 2020

With the development of social network services, graph structures have been utilized to represent relationships among objects in various applications. Recently, a demand of subgraph matching in real-time graph streams has been increased. Therefore, an efficient approximate Top-k subgraph matching scheme for low latency in real-time graph streams is required. In this paper, we propose an approximate Top-k subgraph matching scheme considering data reuse in graph stream environments. The proposed scheme utilizes the distributed stream processing platform, called Storm to handle a large amount of stream data. We also utilize an existing data reuse scheme to decrease stream processing costs. We propose a distance based summary indexing technique to generate Top-k subgraph matching results. The proposed summary indexing technique costs very low since it only stores distances among vertices that are selected in advance. Finally, we provide k subgraph matching results to users by performing an approximate Top-k matching on the summary indexing. In order to show the superiority of the proposed scheme, we conduct various performance evaluations in diverse real world datasets.

• The Journal of the Acoustical Society of Korea
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• v.30 no.2
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• pp.80-85
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• 2011

Speaker change detection involves the identification of time indices of an audio stream, where the identity of the speaker changes. In this paper, we propose novel measures for the speaker change detection based on a graph-partitioning criterion over the pairwise distance matrix of feature-vector stream. Experiments on both synthetic and real-world data were performed and showed that the proposed approach yield promising results compared with the conventional statistical measures.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.185-198
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• 2000

Recently the technological advance in the hardware dealing with multimedia data as well as the explosive increase of the volume of multimedia data bring about new interest in the use of multimedia presentations in many application domains. To use multimedia presentations efficiently, the integration of multimedia presentations into DBMS is necessary. This paper presents a multimedia presentatation query language based on contents and query processing techniques. Presently, multimedia presentation authoring tools denote a multimedia presentation using a presentation graph which is a DAG. A Node in the graph is a same type of media stream and edges denote a play-out order and a synchronization way among nodes. The contents of presentations graphs are the information of each stream, the sequential order of the information inside each stream and the play-out order among the streams. GCalculus/S is a calculus-based query language and can deal with the contents of a presentation graph and physical characteristics of multimedia data. It expresses the sequential order of information inside each stream and the play-out order of streams of a presentation graph using temporal operators Next, Connected and Until. O-Algebra, which is object algebra, is extended to process GCalculus/S queries.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.35-46
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• 2022

Recently, with the development of network technologies, as IoT and social network service applications have been actively used, a lot of graph stream data is being generated. In this paper, we propose a graph compression scheme that considers the stream graph environment by applying graph mining to the existing compression technique, which has been focused on compression rate and runtime. In this paper, we proposed Incremental frequent pattern based compression technique for graph streams. Since the proposed scheme keeps only the latest reference patterns, it increases the storage utilization and improves the query processing time. In order to show the superiority of the proposed scheme, various performance evaluations are performed in terms of compression rate and processing time compared to the existing method. The proposed scheme is faster than existing similar scheme when the number of duplicated data is large.

• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.188-196
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• 2003

In this paper, a demultiplexer for MPEG-2 Transport Stream which can be applied to terrestrial digital broadcast is developed. The demultiplexer separates video, audio, and data from MPEG-2 multimedia stream and transports them to each decoders respectively. While most existing demultiplexers of MPEG-2 transport stream have been developed as hardware systems, but the fast increment of computer's performance enables a software demultiplexer to be worked in realtime. The developed demultiplexer is implemented as a software module called a filter using DirectShow of Microsoft which is based on COM(Component Object Model)and works on the Windows system. The operation of the demultiplexer is verified by using the GraphEdit tool and rendering a test file formatted as MPEG-2 transport stream.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.423-430
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• 2021

Aiming Graph convolutional networks (GCNs) have achieved outstanding performances on skeleton-based action recognition. However, several problems remain in existing GCN-based methods, and the problem of low recognition rate caused by single input data information has not been effectively solved. In this article, we propose a Dual-stream fusion method that combines video data and skeleton data. The two networks respectively identify skeleton data and video data and fuse the probabilities of the two outputs to achieve the effect of information fusion. Experiments on two large dataset, Kinetics and NTU-RGBC+D Human Action Dataset, illustrate that our proposed method achieves state-of-the-art. Compared with the traditional method, the recognition accuracy is improved better.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.1-8
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• 2024

In the API gateway, API composition is an essential function that can reduce the number of client calls and prevent over-fetching and under-fetching. API composition that operate with IMJ (In-Memory Join) consume a lot of resources, putting a burden on the performance of the API gateway. In this paper, to improve the problem of IMJ-style API composition, we propose SAPIC (Stream-based API Composition), which delivers the data to be composed to the client by streaming. SAPIC calls each MSA API that makes up the client response data and immediately streams the received response data to the client, reducing the resource consumption of the API gateway and providing faster response time compared to IMJ. As a result of a comparison experiment with GraphQL, a representative API combination technology, SAPIC recorded a maximum CPU occupancy rate of approximately 21 to 70 % lower, a maximum heap usage rate of approximately 16 to 74 % lower, and a throughput rate that was 1 to 2.3 times higher than GraphQL.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.465-475
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• 2018

Recently, as the use of social media and IoT has increased, large graph streams has been generating and studies on real-time processing for them have been actively carrying out. In this paper we propose a incremental graph stream processing scheme that reuses previous result data when the graph changes continuously. We also propose a cost model to selectively perform incremental processing and static processing. The proposed cost model computes the predicted value of the detection cost and the processing cost of the recalculation area based on the actually processed history and performs the incremental processing when the incremental processing is more profit than the static processing. The proposed incremental processing increases the efficiency by processing only the part that changes when the graph update occurs. Also, by collecting only the previous result data of the changed part and performing the incremental processing, the disk I/O costs are reduced. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1121-1124
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• 1987

Previous methods to map from a FORTRAN-like specification into a systolic array were difficult to find data dependencies because the specification was expressed and executed sequentially. Data-flow graph(DFG)s show data dependencies explicitly. In this paper we show a mapping tool from a DFG specification into a systolic array. We introduce the concept of a Systolic Pattern Stream(SPS) and use that concept to derive a systolic array.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.377-380
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• 2019

To accommodate for the difficult task of satisfying application's system timing constraints, we are developing Splash, a real time stream processing language for embedded AI applications. Splash is a graphical programming language that designs applications through data flow graph which, later automatically generates into codes. The codes are compiled and executed on top of the Splash runtime system. The Splash runtime system supports two aspects of the application. First, it supports the basic stream processing functions required for an application to operate on multiple streams of data. Second, it supports the checking and handling of the user configurated timing constraints. In this paper we explain the implementation of the first aspect of the Splash runtime system which is being developed using a real time communication middleware called DDS.