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 ...

Classifications of several gesture types are very helpful in several applications. This paper tries to address fast classifications of hand gestures using DTW over multi-core simple processors. We presented a methodology to distribute templates over multi-cores and then allow parallel execution of the classification. The results were presented to voting algorithm in which the majority vote was ...

In many real-world decision making settings, situations arise in which the parties (or: players) involved must collectively make decisions while not every player is supposed to have an equal amount of influence in the outcome of such a decision. The weighted voting game is a model that is often used to make such decisions. The amount of influence that a player has in a weighted voting game can ...

Voting algorithms are extensively used to make decisions in fault tolerant systems where each redundant module gives inconsistent outputs. Popular voting algorithms include majority voting, weighted voting, and inexact majority voters. Each of these techniques suffers from scenarios where agreements do not exist for the given voter inputs. This has been successfully overcome in literature using...

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...

Malicious software (malware) represents a threat to the security and the privacy of computer users. Traditional signature-based and heuristic-based methods are inadequate for detecting some forms of malware. This paper presents a malware detection method based on supervised learning. The main contributions of the paper are two ensemble learning algorithms, two pre-processing techniques, and an ...

BOOTSTRAP VOTING EXPERTS (BVE) is an extension to the VOTING EXPERTS algorithm for unsupervised chunking of sequences. BVE generates a series of segmentations, each of which incorporates knowledge gained from the previous segmentation. We show that this method of bootstrapping improves the performance of VOTING EXPERTS in a variety of unsupervised word segmentation scenarios, and generally impr...

BOOTSTRAP VOTING EXPERTS (BVE) is an extension to the VOTING EXPERTS algorithm for unsupervised chunking of sequences. BVE generates a series of segmentations, each of which incorporates knowledge gained from the previous segmentation. We show that this method of bootstrapping improves the performance of VOTING EXPERTS in a variety of unsupervised word segmentation scenarios, and generally impr...