• Title/Summary/Keyword: graph-based approach

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Speaker Change Detection Based on a Graph-Partitioning Criterion

  • Seo, Jin-Soo
    • 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.

Bond graph modeling approach for piezoelectric transducer design (압전 트랜스듀서 설계를 위한 bond graph 모델링)

  • 문원규
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.265-271
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    • 1997
  • A bond graph modeling approach which is equivalent to a finite element method is formulated in the case of the piezoelectric thickness vibrator. This formulation suggests a new definition of the generalized displacements for a continuous system as well as the piezoelectric thickness vibrator. The newly defined coordinates are illustrated to be easily interpreted physically and easily used in analysis of the system performance. Compared to the Mason equivalent circuit model, the bond graph model offers the primary advantage of physical realizability. Compared to circuit models based on standard discrete electrical elements, the main advantage of the bond graph model is a greater physical accuracy because of the use of multiport energic elements. While results are presented here for the thickness vibrator, the modeling method presented is general in scope and can be applied to arbitrary physical systems.

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Large Scale Protein Side-chain Packing Based on Maximum Edge-weight Clique Finding Algorithm

  • K.C., Dukka Bahadur;Brown, J.B.;Tomita, Etsuji;Suzuki, Jun'ichi;Akutsu, Tatsuya
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.228-233
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    • 2005
  • The protein side-chain packing problem (SCPP) is known to be NP-complete. Various graph theoretic based side-chain packing algorithms have been proposed. However as the size of the protein becomes larger, the sampling space increases exponentially. Hence, one approach to cope with the time complexity is to decompose the graph of the protein into smaller subgraphs. Some existing approaches decompose the graph into biconnected components at an articulation point (resulting in an at-most 21-residue subgraph) or solve the SCPP by tree decomposition (4-, 5-residue subgraph). In this regard, we had also presented a deterministic based approach called as SPWCQ using the notion of maximum edge weight clique in which we reduce SCPP to a graph and then obtain the maximum edge-weight clique of the obtained graph. This algorithm performs well for a protein of less than 500 residues. However, it fails to produce a feasible solution for larger proteins because of the size of the search space. In this paper, we present a new heuristic approach for the side-chain packing problem based on the maximum edge-weight clique finding algorithm that enables us to compute the side-chain packing of much larger proteins. Our new approach can compute side-chain packing of a protein of 874 residues with an RMSD of 1.423${\AA}$.

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Enhanced Graph-Based Method in Spectral Partitioning Segmentation using Homogenous Optimum Cut Algorithm with Boundary Segmentation

  • S. Syed Ibrahim;G. Ravi
    • International Journal of Computer Science & Network Security
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    • v.23 no.7
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    • pp.61-70
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    • 2023
  • Image segmentation is a very crucial step in effective digital image processing. In the past decade, several research contributions were given related to this field. However, a general segmentation algorithm suitable for various applications is still challenging. Among several image segmentation approaches, graph-based approach has gained popularity due to its basic ability which reflects global image properties. This paper proposes a methodology to partition the image with its pixel, region and texture along with its intensity. To make segmentation faster in large images, it is processed in parallel among several CPUs. A way to achieve this is to split images into tiles that are independently processed. However, regions overlapping the tile border are split or lost when the minimum size requirements of the segmentation algorithm are not met. Here the contributions are made to segment the image on the basis of its pixel using min-cut/max-flow algorithm along with edge-based segmentation of the image. To segment on the basis of the region using a homogenous optimum cut algorithm with boundary segmentation. On the basis of texture, the object type using spectral partitioning technique is identified which also minimizes the graph cut value.

Polygon Modeling with Constraint Management (구속조건 관리를 이용한 다각형 모델링)

  • 김기현;김재정
    • Korean Journal of Computational Design and Engineering
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    • v.3 no.3
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    • pp.145-153
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    • 1998
  • An approach has been developed to generate parametric models with Boolean operations. The approach combines Boolean operations and graph manipulation on the constraints imposed on primitives. A Boolean operation is first performed on two primitives and new geometric elements such as vertices and edges are computed. Then to generate the constraint graph of the polygon the each constraints graph of two primitives are merged by adding the new geometric elements with its corresponding constraints. In the merging process, some of the geometric elements belonging to the primitives may be eliminated based on its contribution to the polygon. A computer implementation in a 2D space is described to illustrate the approach with examples.

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CAS IMPLEMENTATION OF RECURSIVE STRUCTURE IN A SPANNING TREE

  • Song, Kee-Hong
    • East Asian mathematical journal
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    • v.21 no.2
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    • pp.249-260
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    • 2005
  • Experimentation using computer plays an important part in education and research in graph theory. The purpose of this paper is to develop the CAS techniques for the hands-on approach in graph theory specifically on the topic of constructing the spanning tree. This paper discusses the advantages of CAS as the software system for doing graph theory and introduces the software solutions integrating multimedia user interface developed by the author, which extend the functionality of the existing CAS-based graph theory software package.

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A Global Graph-based Approach for Transaction and QoS-aware Service Composition

  • Liu, Hai;Zheng, Zibin;Zhang, Weimin;Ren, Kaijun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.5 no.7
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    • pp.1252-1273
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    • 2011
  • In Web Service Composition (WSC) area, services selection aims at selecting an appropriate candidate from a set of functionally-equivalent services to execute the function of each task in an abstract WSC according to their different QoS values. In despite of many related works, few of previous studies consider transactional constraints in QoS-aware WSC, which guarantee reliable execution of Composite Web Service (CWS) that is composed by a number of unpredictable web services. In this paper, we propose a novel global selection-optimal approach in WSC by considering both transactional constraints and end-to-end QoS constraints. With this approach, we firstly identify building rules and the reduction method to build layer-based Directed Acyclic Graph (DAG) model which can model transactional relationships among candidate services. As such, the problem of solving global optimal QoS utility with transactional constraints in WSC can be regarded as a problem of solving single-source shortest path in DAG. After that, we present Graph-building algorithms and an optimal selection algorithm to explain the specific execution procedures. Finally, comprehensive experiments are conducted based on a real-world web service QoS dataset. The experimental results show that our approach has better performance over other competing selection approaches on success ratio and efficiency.

Similarity Evaluation between Graphs: A Formal Concept Analysis Approach

  • Hao, Fei;Sim, Dae-Soo;Park, Doo-Soon;Seo, Hyung-Seok
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1158-1167
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    • 2017
  • Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and protein-protein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.

GCNXSS: An Attack Detection Approach for Cross-Site Scripting Based on Graph Convolutional Networks

  • Pan, Hongyu;Fang, Yong;Huang, Cheng;Guo, Wenbo;Wan, Xuelin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.12
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    • pp.4008-4023
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    • 2022
  • Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

Remote Diagnosis of Hypertension through HTML-based Backward Inference

  • Song, Yong-Uk;Chae, Young-Moon;Cho, Kyoung-Won;Ho, Seung-Hee
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.496-507
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    • 2001
  • An expert system for the diagnosis and indication of hypertension is implemented through HTML-based backward inference. HTML-based backward inference is performed using the hypertext function of HTML, and many HTML files, which are hyperlinked to each other based on the backward rules, should be prepared beforehand. The development and maintenance of the HTML files are conducted automatically using the decision graph. Still, the drawing and input of the decision graph is a time consuming and tedious job if it is done manually. So, automatic generator of the decision graph for the diagnosis and indication of hypertension was implemented. The HTML-based backward inference ensures accessibility, multimedia facilities, fast response, stability, easiness, and platform independency of the expert system. So, this research reveals that HTML-based inference approach can be used for many Web-based intelligent site with fast and stable performance.

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