Search Results - "clique"

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    On self-clique graphs / Ong Poh Hwa by Ong, Poh Hwa

    Published 2010
    “…The clique graph of a graph G is the graph obtained by taking the cliques of G as vertices, and two vertices are adjacent if and only if the corresponding cliques have non-empty intersection. …”
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    Alpha Clique Sdn. Bhd. / Nurul Hidayah Mohd Kamal by Mohd Kamal, Nurul Hidayah

    Published 2020
    “…Alpha Clique Sdn. Bhd. is introducing a new product to the customers which is a towel UV sterilizer with an air purifier known as Smartlux. …”
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    Approximate maximum clique algorithm (AMCA): A clever technique for solving the maximum clique problem through near optimal algorithm for minimum vertex cover problem by Fayaz, Muhammad, Arshad,, Shakeel, Shah,, Abdul Salam, Shah, Asadullah

    Published 2018
    “…Background and Objective: The process of solving the Maximum Clique (MC) problem through approximation algorithms is harder, however, the Maximum Vertex Cover (MVC) problem can easily be solved using approximation algorithms. …”
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    A maximal-clique-based clustering approach for multi-observer multi-view data by using k-nearest neighbor with S-pseudo-ultrametric induced by a fuzzy similarity by Khameneh, Azadeh Zahedi, Ghaznavi, Mehrdad, Kilicman, Adem, Mahad, Zahari, Mardani, Abbas

    Published 2024
    “…To this end, we first build a k-nearest neighbor (kNN) directed graph using the proposed S-distance, then transform it into an undirected graph based on the neighborhood information of the nodes so that the resultant graph is characterized based on nodes interactions and initial features information of the nodes. Next, a new maximal-clique-based clustering is designed to complete the node partitioning. …”
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    On graphs without multicliqual edges by Lim, Chong Keang, Peng, Yee Hock

    Published 1981
    “…An edge which belongs to more than one clique of a given graph is called a multicliqual edge. …”
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    Epidemics on random intersection graphs by Ball, Frank G., Sirl, David J., Trapman, Pieter

    Published 2014
    “…Both the clique sizes and the number of cliques an individual belongs to follow mixed Poisson distributions. …”
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    Numerical Algorithms for Polynomial Optimisation Problems with Applications by Alqahtani, Mohammed Aeyed M

    Published 2019
    “…Furthermore, we develop an efficient and effective algorithm for the maximum clique problem.…”
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    A multi-view clustering algorithm for attributed weighted multi-edge directed networks by Khameneh, Azadeh Zahedi, Kilicman, Adem, Mahad, Zahari

    Published 2022
    “…Then, the concept of the maximum clique is adopted to complete the clustering task. …”
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    Consumer ethnocentrism, market mavenism and social network analysis by Cheah, Isaac, Shimul, A.

    Published 2018
    “…The social network analysis shows that within the 2-clique, the market mavens outnumbered the non-mavens. …”
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    Conflict management: a survey on style of behavior of FTMSK's lecturers / Siti Suzawati Sulaiman by Sulaiman, Siti Suzawati

    Published 2005
    “…The purpose of this study is to explore the lecturers' style of behavior and how these styles of behavior influence their conflict management style with their clique. A number of behavioral styles and conflict-handling style have been described in the literatures, however four behavioral styles were identified. …”
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    A study on some graphs associated with finite groups / Lim Ming Chyang by Lim , Ming Chyang

    Published 2019
    “…For conjugate graphs and order graphs associated with certain groups, we determine the number of complete components in the graphs and their clique numbers. The main focus of this research is on generalised order graphs of finite groups. …”
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    Expectation-Maximization with Image-Weighted Markov Random Fields to Handle Severe Pathology by Pagnozzi, A., Dowson, N., Bradley, A., Boyd, Roslyn, Bourgeat, P., Rose, S.

    Published 2016
    “…We propose a prior-less approach combined with a modification of the Expectation Maximization (EM)/Markov Random Field (MRF) segmentation by imposing a continuous weighting scheme to penalize intensity discrepancies between pairs of neighbors within each clique neighborhood, to provide robustness to the unique clinical problem of severe anatomical distortion. …”
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    High-quality draft genome sequence of Rhizobium mesoamericanum strain STM6155, a Mimosa pudica microsymbiont from New Caledonia. by Klonowska, A., López-López, A., Moulin, L., Ardley, J., Gollagher, M., Marinova, Dora, Tian, R., Huntemann, M., Reddy, T., Varghese, N., Woyke, T., Markowitz, V., Ivanova, N., Seshadri, R., Baeshen, M., Baeshen, N., Kyrpides, N., Reeve, W.

    Published 2017
    “…Strain STM6155 forms an ANI clique (ID 2435) with the sequenced R. mesoamericanum strain STM3625, and the nodulation genes are highly conserved in these strains and the type strain of Rhizobium grahamii CCGE501(T). …”
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    Peer Culture and Body Image Concern Among Australian Adolescent Girls: A Hierarchical Linear Modelling Analysis by Carey, Renee, Donaghue, N., Broderick, P.

    Published 2013
    “…Peers may influence the body image concerns and disordered eating behaviours of adolescent girls through the creation of appearance cultures within friendship cliques. The present study investigates the role of friendship cliques and school gender composition in impacting upon adolescent girls' body image concern and disordered eating behaviours, using hierarchical linear modelling (HLM), a statistical procedure employed in the analysis of nested data. …”
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    Twitter as safe space for self-disclosure among Malaysian LGBTQ youths by Khadijah Mohamad Tuah, Ummu Syafiqah Mazlan

    Published 2020
    “…The results are organized around three primary themes. 1) The motivation includes knowledge, private life, self-acceptance, and movement and clique. 2) Reciprocity in self-disclosure from both the giving and receiving end which can be positive or negative. …”
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    Image matching using relational graph representation by Lai, Chui Yen

    Published 2005
    “…The methodology is consists of six steps: (1) input image, (2) line segment extraction from the image, (3) the interpretation and derivation of structural descriptions from the line-extracted image, (4) the construction of relational graph to represent the structural descriptions, (5) the derivation of association graph from relational graphs to perform relational graph matching, and (6) the searching of the largest maximal clique in the association graph to determine the best matching. …”
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