based on a meta-theoretical analysis of voting, the present paper is an attempt to present a theoretical model encompassing all the possible aspects of voting in an election action system, proposing four sub-systems of voting as follows: economic voting, political voting, cultural voting and moral voting. having distinguished among these sub-systems, the writer describes the constitutive elemen...

BACKGROUND Communities and nations seeking to foster social responsibility in their youth are interested in understanding factors that predict and promote youth involvement in public activities. Orphans and separated children (OSC) are a vulnerable population whose numbers are increasing, particularly in resource-poor settings. Understanding whether and how OSC are engaged in civic activities i...

This paper proposes a real-time 3D feature extraction hardware algorithm with feature point matching capability between neighboring frames, which realizes 3D tracking of moving objects. This hardware algorithm is based on a 3D voting method. Both the 3D voting and tlie featiire point matching arc directly carried out through highly parallel processing by content addressable memory (CAM) i11 rea...

This study presents evidence for the mediation effect of political knowledge through political self-efficacy (i.e. internal political efficacy) in the prediction of political participation. It employs an action theoretic approach-by and large grounded on the Theory of Planned Behaviour-and uses data from the German Longitudinal Election Study to examine whether political knowledge has distinct ...

We introduce pyMune, an open-source Python library for robust clustering of complex real-world datasets without density cutoff parameters. It implements DenMune (Abbas et al., 2021), a mutual nearest neighbor algorithm that uses dimensionality reduction and approximate search to identify expand cluster cores. Noise is removed with nearest-neighbor voting system. In addition clustering, pyMune p...

In this paper, we propose a thorough investigation of a nearest neighbor rule which we call the “Symmetric Nearest Neighbor (sNN) rule”. Basically, it symmetrises the classical nearest neighbor relationship from which are computed the points voting for some instances. Experiments on 29 datasets, most of which are readily available, show that the method significantly outperforms the traditional ...

K-nearest neighbor rule (KNN) is the wellknown non-parametric technique in the statistical pattern classification, owing to its simplicity, intuitiveness and effectiveness. In this paper, we firstly review the related works in brief and detailedly analyze the sensitivity issue on the choice of the neighborhood size k, existed in the KNN rule. Motivated by the problem, a novel dual weighted voti...

Support Vector Machines (SVMs) are a powerful classification technique. For large datasets, SVM training is computationally expensive. In this paper, we propose VOKNN, a novel nearest neighbor-based voting data reduction algorithm for SVM training. The proposed approach eliminates part of the training dataset based on the votes each point gains from all the other points in the other class. We d...

It is often argued in the e-voting community that in the presence of write-in candidates, forced abstention attacks are always possible. Therefore, write-in candidates are often excluded in existing definitions of coercion-resistance arguing that those definitions cannot be achieved by write-in supporting schemes. This is only true if the tally is made public directly. Coercionresistance may we...