Zobrazeno 1 - 10
of 248
pro vyhledávání: '"Shudo, Kazuyuki"'
Autor:
Sakurai, Akira, Shudo, Kazuyuki
An effective method for suppressing intentional forks in a blockchain is the last-generated rule, which selects the most recent chain as the main chain in the event of a chain tie. This rule helps invalidate blocks that are withheld by adversaries fo
Externí odkaz:
http://arxiv.org/abs/2411.08439
Hypergraphs are generalizations of simple graphs that allow for the representation of complex group interactions beyond pairwise relationships. Clustering coefficients, which quantify the local link density in networks, have been widely studied even
Externí odkaz:
http://arxiv.org/abs/2410.23799
Using random walks for sampling has proven advantageous in assessing the characteristics of large and unknown social networks. Several algorithms based on random walks have been introduced in recent years. In the practical application of social netwo
Externí odkaz:
http://arxiv.org/abs/2409.08599
Autor:
Sakurai, Akira, Shudo, Kazuyuki
Mining fairness in blockchain refers to the equality between the computational resources invested in mining and the block rewards received. There exists a dilemma where increasing the blockchain's transaction processing capacity damages mining fairne
Externí odkaz:
http://arxiv.org/abs/2406.00595
Autor:
Sakurai, Akira, Shudo, Kazuyuki
In the area of blockchain, numerous methods have been proposed for suppressing intentional forks by attackers more effectively than the random rule. However, all of them, except for the random rule, require major updates, rely on a trusted third part
Externí odkaz:
http://arxiv.org/abs/2403.15030
Autor:
Nakajima, Kazuki, Shudo, Kazuyuki
Publikováno v:
ACM Transactions on Knowledge Discovery from Data, Volume 17, Issue 4, Article No. 51, pp 1-28, 2023
Analysis of social networks with limited data access is challenging for third parties. To address this challenge, a number of studies have developed algorithms that estimate properties of social networks via a simple random walk. However, most existi
Externí odkaz:
http://arxiv.org/abs/2305.12314
Publikováno v:
Journal of Informetrics, Volume 17, Issue 4, Article No. 101460, November 2023
Gender imbalance in academia has been confirmed in terms of a variety of indicators, and its magnitude often varies from country to country. Europe and North America, which cover a large fraction of research workforce in the world, have been the main
Externí odkaz:
http://arxiv.org/abs/2302.07843
Publikováno v:
Scientometrics, vol. 128, pp. 2429-2446, 2023
Modern scientific work, including writing papers and submitting research grant proposals, increasingly involves researchers from different institutions. In grant collaborations, it is known that institutions involved in many collaborations tend to de
Externí odkaz:
http://arxiv.org/abs/2206.11470
Autor:
Nakajima, Kazuki, Shudo, Kazuyuki
Analyzing social graphs with limited data access is challenging for third-party researchers. To address this challenge, a number of algorithms that estimate structural properties via a random walk have been developed. However, most existing algorithm
Externí odkaz:
http://arxiv.org/abs/2111.11966
Publikováno v:
IEEE Transactions on Network Science and Engineering, vol. 9, no. 3, pp. 1139-1153, 2022
Many complex systems involve direct interactions among more than two entities and can be represented by hypergraphs, in which hyperedges encode higher-order interactions among an arbitrary number of nodes. To analyze structures and dynamics of given
Externí odkaz:
http://arxiv.org/abs/2106.12162