scholarly journals Finding Dense Components in Large-Scale Network Using Randomized Binary Search Tree

2020 ◽  
Vol 30.8 (147) ◽  
pp. 65-69
Author(s):  
Anh Phuc Trinh ◽  
◽  
Dang Hai Pham ◽  
Thi Thuy Dung Phan ◽  

Given a simple undirected graph G=(V, E), the density of a subgraph on vertex set S is defined as a ratio between the number of edges |E(S)| and the number of vertices |S|, where E(S) is the set of edges induced by vertices in S. Finding the maximum density subgraph has become an intense study in recent years, especially in the social network era. Being based on a greedy algorithm that connects with a suitable graph data structure, we have reduced its time complexity by using a randomized binary search tree, also called treap. We make the complexity analysis in both time and memory requirements, including computational experiments in large scale real networks.

2006 ◽  
Vol 14 (4) ◽  
pp. 456-487 ◽  
Author(s):  
James H. Fowler

Using large-scale network analysis I map the cosponsorship networks of all 280,000 pieces of legislation proposed in the U.S. House and Senate from 1973 to 2004. In these networks, a directional link can be drawn from each cosponsor of a piece of legislation to its sponsor. I use a number of statistics to describe these networks such as the quantity of legislation sponsored and cosponsored by each legislator, the number of legislators cosponsoring each piece of legislation, the total number of legislators who have cosponsored bills written by a given legislator, and network measures of closeness, betweenness, and eigenvector centrality. I then introduce a new measure I call “connectedness” which uses information about the frequency of cosponsorship and the number of cosponsors on each bill to make inferences about the social distance between legislators. Connectedness predicts which members will pass more amendments on the floor, a measure that is commonly used as a proxy for legislative influence. It also predicts roll call vote choice even after controlling for ideology and partisanship.


MIS Quarterly ◽  
2016 ◽  
Vol 40 (4) ◽  
pp. 849-868 ◽  
Author(s):  
Kunpeng Zhang ◽  
◽  
Siddhartha Bhattacharyya ◽  
Sudha Ram ◽  
◽  
...  

Cryptography ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 4
Author(s):  
Bayan Alabdullah ◽  
Natalia Beloff ◽  
Martin White

Data security has become crucial to most enterprise and government applications due to the increasing amount of data generated, collected, and analyzed. Many algorithms have been developed to secure data storage and transmission. However, most existing solutions require multi-round functions to prevent differential and linear attacks. This results in longer execution times and greater memory consumption, which are not suitable for large datasets or delay-sensitive systems. To address these issues, this work proposes a novel algorithm that uses, on one hand, the reflection property of a balanced binary search tree data structure to minimize the overhead, and on the other hand, a dynamic offset to achieve a high security level. The performance and security of the proposed algorithm were compared to Advanced Encryption Standard and Data Encryption Standard symmetric encryption algorithms. The proposed algorithm achieved the lowest running time with comparable memory usage and satisfied the avalanche effect criterion with 50.1%. Furthermore, the randomness of the dynamic offset passed a series of National Institute of Standards and Technology (NIST) statistical tests.


2014 ◽  
Vol 26 (7) ◽  
pp. 1377-1389 ◽  
Author(s):  
Bo-Cheng Kuo ◽  
Mark G. Stokes ◽  
Alexandra M. Murray ◽  
Anna Christina Nobre

In the current study, we tested whether representations in visual STM (VSTM) can be biased via top–down attentional modulation of visual activity in retinotopically specific locations. We manipulated attention using retrospective cues presented during the retention interval of a VSTM task. Retrospective cues triggered activity in a large-scale network implicated in attentional control and led to retinotopically specific modulation of activity in early visual areas V1–V4. Importantly, shifts of attention during VSTM maintenance were associated with changes in functional connectivity between pFC and retinotopic regions within V4. Our findings provide new insights into top–down control mechanisms that modulate VSTM representations for flexible and goal-directed maintenance of the most relevant memoranda.


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