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Relevant bibliographies by topics / MODULARITY SCORE

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Journal articles

Academic literature on the topic 'MODULARITY SCORE'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "MODULARITY SCORE"

1

Miyauchi, Atsushi, and Yasushi Kawase. "Z-Score-Based Modularity for Community Detection in Networks." PLOS ONE 11, no. 1 (2016): e0147805. http://dx.doi.org/10.1371/journal.pone.0147805.

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Sun, Huaqi, Hui Shu, Fei Kang, and Yan Guang. "ModDiff: Modularity Similarity-Based Malware Homologation Detection." Electronics 12, no. 10 (2023): 2258. http://dx.doi.org/10.3390/electronics12102258.

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In recent years, the number and scale of malicious codes have grown exponentially, posing an increasing threat to cybersecurity. Hence, it is of great research value to quickly identify variants of malware and master their family information. Binary code similarity detection, as a key technique in reverse analysis, plays an indispensable role in malware analysis. However, most existing methods focus on similarity at the function or basic block level, ignoring the modular composition of malware. Implementing similarity detection among malware modules would greatly improve the efficiency and acc

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Sachdeva, Shubhangini, Sridhar Mangalesh, and Sharmila Dudani. "Knowledge, Attitude and Practices of Breast Self-Examination Amongst Indian Women: A Pan-India Study." Asian Pacific Journal of Cancer Care 6, no. 2 (2021): 141–47. http://dx.doi.org/10.31557/apjcc.2021.6.2.141-147.

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Objective: Breast Cancer is the leading cause of mortality and morbidity amongst Indian females. Breast self-examination (BSE) as an early detection modularity can have a profound effect on lowering mortality, if it is practiced regularly. The aim of this study was to assess the knowledge, attitude, and practice of Breast Self-examination amongst Indian women, aged 30 years and above. Methods: A validated questionnaire, consisting 35 questions measuring ‘Knowledge, Attitudes and Practice of Breast Self-Examination’ was widely circulated amongst 1000 females throughout India and responses were

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De Meo, Federico, Giorgio Cacciola, Vittorio Bellotti, Antongiolio Bruschetta, and Pietro Cavaliere. "Trabecular Titanium acetabular cups in hip revision surgery: mid-term clinical and radiological outcomes." HIP International 28, no. 2_suppl (2018): 61–65. http://dx.doi.org/10.1177/1120700018812992.

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Introduction: Severe acetabular bone loss during revision hip arthroplasty can be restored with different surgical techniques. Best results have been observed using porous tantalum cementless cups. Trabecular Titanium (TT) cups were designed to reproduce the structure, mechanical and biological characteristics of trabecular bone. Few clinical studies have been published with these cups. The aim of this study is to evaluate the clinical and radiological outcome of patients with large acetabular defects (Paprosky IIb or higher) revised using TT cups. Materials and methods: 64 consecutive patient

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Wang, Guohai, Yang Huang, Wei Yao, et al. "Structure and characteristics of the plant-frugivore bird network from the Guilin Botanical Garden." PeerJ 11 (March 16, 2023): e15028. http://dx.doi.org/10.7717/peerj.15028.

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The interaction between plants and frugivores is crucial to ecosystem function and community diversity. However, little is known about the interaction between plants and frugivorous bird species in urban green spaces. We observed interactions between plants and frugivorous birds in the Guilin Botanical Garden for one year and determined the structure and characteristics of the interaction network. We also analyzed the impact of species traits on their network roles. Interactions between 14 frugivorous birds and 13 fruit plant species were recorded in the study area. Autumn interactions compris

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Feklicheva, Inna, Ilya Zakharov, Nadezda Chipeeva, et al. "Assessing the Relationship between Verbal and Nonverbal Cognitive Abilities Using Resting-State EEG Functional Connectivity." Brain Sciences 11, no. 1 (2021): 94. http://dx.doi.org/10.3390/brainsci11010094.

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The present study investigates the relationship between individual differences in verbal and non-verbal cognitive abilities and resting-state EEG network characteristics. We used a network neuroscience approach to analyze both large-scale topological characteristics of the whole brain as well as local brain network characteristics. The characteristic path length, modularity, and cluster coefficient for different EEG frequency bands (alpha, high and low; beta1 and beta2, and theta) were calculated to estimate large-scale topological integration and segregation properties of the brain networks.

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7

Liu, Zhihua, Hongmei Wang, Guishen Wang, and Yu Zhou. "Link community detection based on ensemble learning." Modern Physics Letters B 34, no. 27 (2020): 2050293. http://dx.doi.org/10.1142/s0217984920502930.

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Overlapping community detection is a hot topic in the research of data mining and graph theory. In this paper, we propose a link community detection method based on ensemble learning (LCDEL). First, we transform graph into line graph and construct node adjacency matrix of line graph. Second, we calculate node distance of line graph through a new distance metric and get node distance matrix of line graph. Third, we use PCA method to reduce dimensions of node distance matrix of line graph. Then, we cluster on the reduced node distance matrix by k-means clustering algorithm. Finally, we convert l

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LU, ZAIXIN, WEILI WU, WEIDONG CHEN, JIAOFEI ZHONG, YUANJUN BI, and ZHENG GAO. "THE MAXIMUM COMMUNITY PARTITION PROBLEM IN NETWORKS." Discrete Mathematics, Algorithms and Applications 05, no. 04 (2013): 1350031. http://dx.doi.org/10.1142/s1793830913500316.

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The community structure detection is an important problem in many areas such as biology network, computer network and social network. The objective of this problem is to analyze the relationships among data via the network topology. In the literature, many works have been done for partitioning a network into communities or clustering data into groups. In this paper, we define a series of conditions for communities and formulate the community detection problem into a combinatorial optimization problem which aims at partitioning a given network into disjoint communities such that all the communi

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9

Wang, Lu, Yong Quan Liang, Qi Jia Tian, Jie Yang, Chao Song, and Zhuang Wu. "A Community Detection Method Based on Multi-Objective Optimization Method." Applied Mechanics and Materials 571-572 (June 2014): 177–82. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.177.

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Community detection in complex network has been an active research area in data mining and machine learning. This paper proposed a community detection method based on multi-objective evolutionary algorithm, named CDMOEA, which tries to find the Pareto front by maximize two objectives, community score and community fitness. Fast and Elitist Multi-objective Genetic Algorithm is used to attained a set of optimal solutions, and then use Modularity function to choose the best one from them. The locus based adjacency representation is used to realize genetic representation, which ensures the effecti

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10

Zheng, Gang, Liping Zhang, Long Jiang Zhang, et al. "Altered Modular Organization of Functional Connectivity Networks in Cirrhotic Patients without Overt Hepatic Encephalopathy." BioMed Research International 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/727452.

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Minimal hepatic encephalopathy (MHE) is associated with changes in functional connectivity. To investigate the patterns of modular changes of the functional connectivity in the progression of MHE, resting-state functional magnetic resonance imaging was acquired in 24 MHE patients, 31 cirrhotic patients without minimal hepatic encephalopathy (non-HE), and 38 healthy controls. Newman’s metric, the modularityQvalue, was maximized and compared in three groups. Topological roles with the progression of MHE were illustrated by intra- and intermodular connectivity changes. Results showed that theQval

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