weighted voting
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2022 ◽  
Vol 16 (1) ◽  
pp. 0-0

To avoid information systems malfunction, their integrity disruption, availability violation as well as data confidentiality, it is necessary to detect anomalies in information system operation as quickly as possible. The anomalies are usually caused by malicious activity – information systems attacks. However, the current approaches to detect anomalies in information systems functioning have never been perfect. In particular, statistical and signature-based techniques do not allow detection of anomalies based on modifications of well-known attacks, dynamic approaches based on machine learning techniques result in false responses and frequent anomaly miss-outs. Therefore, various hybrid solutions are being frequently offered on the basis of those two approaches. The paper suggests a hybrid approach to detect anomalies by combining computationally efficient classifiers of machine learning with accuracy increase due to weighted voting. Pilot evaluation of the developed approach proved its feasibility for anomaly detection systems.


Games ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 6
Author(s):  
Jochen Staudacher ◽  
Felix Wagner ◽  
Jan Filipp

We study the efficient computation of power indices for weighted voting games with precoalitions amongst subsets of players (reflecting, e.g., ideological proximity) using the paradigm of dynamic programming. Starting from the state-of-the-art algorithms for computing the Banzhaf and Shapley–Shubik indices for weighted voting games, we present a framework for fast algorithms for the three most common power indices with precoalitions, i.e., the Owen index, the Banzhaf–Owen index and the symmetric coalitional Banzhaf index, and point out why our new algorithms are applicable for large numbers of players. We discuss implementations of our algorithms for the three power indices with precoalitions in C++ and review computing times, as well as storage requirements.


2021 ◽  
pp. 147488512110626
Author(s):  
Andrei Poama ◽  
Alexandru Volacu

Are there any prima facie reasons that democracies might have for disenfranchising older citizens? This question reflects increasingly salient, but often incompletely theorized complaints that members of democratic publics advance about older citizens’ electoral influence. Rather than rejecting these complaints out of hand, we explore whether, suitably reconstructed, they withstand democratic scrutiny. More specifically, we examine whether the account of political equality that seems to most fittingly capture the logic of these complaints – namely, equal opportunity of political influence over electoral outcomes – can justify disenfranchising older citizens. We conclude that equal opportunity of influence cannot ground a blanket disenfranchisement of older people and that, taken in conjunction with other general considerations that apply to all sound electoral policies, partial disenfranchisement proposals (i.e. proposals for reducing the electoral influence of older citizens via age-weighted voting) are both quasi-inapplicable and practically unrobust across a relevant range of political contexts.


2021 ◽  
Vol 17 (12) ◽  
pp. 1172-1185
Author(s):  
Assia Ennouni ◽  
Noura Ouled Sihamman ◽  
My Abdelouahed Sabri ◽  
Abdellah Aarab

Author(s):  
Jochen Staudacher ◽  
Felix Wagner ◽  
Jan Filipp

We study the efficient computation of power indices for weighted voting games with precoalitions amongst subsets of players (reflecting, e.g., ideological proximity) using the paradigm of dynamic programming. Starting from the state-of-the-art algorithms for computing the Banzhaf and Shapley-Shubik indices for weighted voting games we present a framework for fast algorithms for the three most common power indices with precoalitions, i.e. the Owen index, the Banzhaf-Owen index and the Symmetric Coalitional Banzhaf index, and point out why our new algorithms are applicable for large numbers of players. We discuss implementations of our algorithms for the three power indices with precoalitions in C++ and review computing times as well as storage requirements.


2021 ◽  
Author(s):  
Ali Marjaninejad ◽  
Christian Klaes ◽  
Francisco J. Valero-Cuevas

2021 ◽  
Vol 12 ◽  
Author(s):  
Zhen-Wei Zhang ◽  
Zhen Gao ◽  
Chun-Hou Zheng ◽  
Lei Li ◽  
Su-Min Qi ◽  
...  

An increasing number of experiments had verified that miRNA expression is related to human diseases. The miRNA expression profile may be an indicator of clinical diagnosis and provides a new direction for the prevention and treatment of complex diseases. In this work, we present a weighted voting-based model for predicting miRNA–disease association (WVMDA). To reasonably build a network of similarity, we established credibility similarity based on the reliability of known associations and used it to improve the original incomplete similarity. To eliminate noise interference as much as possible while maintaining more reliable similarity information, we developed a filter. More importantly, to ensure the fairness and efficiency of weighted voting, we focus on the design of weighting. Finally, cross-validation experiments and case studies are undertaken to verify the efficacy of the proposed model. The results showed that WVMDA could efficiently identify miRNAs associated with the disease.


2021 ◽  
Vol 72 ◽  
pp. 99-135
Author(s):  
Yotam Gafni ◽  
Ron Lavi ◽  
Moshe Tennenholtz

Weighted voting games apply to a wide variety of multi-agent settings. They enable the formalization of power indices which quantify the coalitional power of players. We take a novel approach to the study of the power of big vs. small players in these games. We model small (big) players as having single (multiple) votes. The aggregate relative power of big players is measured w.r.t. their votes proportion. For this ratio, we show small constant worst-case bounds for the Shapley-Shubik and the Deegan-Packel indices. In sharp contrast, this ratio is unbounded for the Banzhaf index. As an application, we define a false-name strategic normal form game where each big player may split its votes between false identities, and study its various properties. Together, our results provide foundations for the implications of players’ size, modeled as their ability to split, on their relative power.


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