Abstract Wireless sensor network applications interact with the physical world through analog sensors. However, decisions derived from flawed sensor measurements can adversely impact the correctness of the overall sensor network findings. To improve the reliability of decisions and minimize the impact of faulty sensor measurements, it is important to have a distributed scheme that enhances the ...

In recent years, multi-atlas fusion methods have gained significant attention in medical image segmentation. In this paper, we propose a general Markov Random Field (MRF) based framework that can perform edge-preserving smoothing of the labels at the time of fusing the labels itself. More specifically, we formulate the label fusion problem with MRF-based neighborhood priors, as an energy minimi...

We introduce the (j, k)-Kemeny rule – a generalization of Kemeny’s voting rule that aggregates j-chotomous weak orders into a k-chotomous weak order. Special cases of (j, k)Kemeny include approval voting, the mean rule and Borda mean rule, as well as the Borda count and plurality voting. Why, then, is the winner problem computationally tractable for each of these other rules, but intractable fo...

The main functions of an Intrusion Detection System (IDS) are to protect computer networks by analyzing and predicting the actions of processes. Though IDS has been developed for many years, the large number of alerts makes the system inefficient. In this paper, we proposed a classification method based on Support Vector Machines (SVM) with a weighted voting schema to detect intrusions. First, ...

We study the complexity of the destructive bribery problem—an external agent tries to prevent a disliked candidate from winning by bribery actions— in voting over combinatorial domains, where the set of candidates is the Cartesian product of several issues. This problem is related to the concept of the margin of victory of an election which constitutes a measure of robustness of the election ou...

An adaptive voting algorithm for digital media was introduced in this study. Availability was improved by incoherence scoring in voting mechanism of MultiModular Redundancy. Regulation parameters give the algorithm flexibility of adjusting priorities in decision process. Proposed adaptive voting algorithm was shown to be more aware of fault status of redundant modules.

We investigate the distribution of the well-studied Shapley–Shubik values in weighted voting games where the agents are stochastically determined. The Shapley-Shubik value measures the voting power of an agent, in typical collective decision making systems. While easy to estimate empirically given the parameters of a weighted voting game, the Shapley values are notoriously hard to reason about ...

The mean shift algorithm has achieved considerable success in target tracking due to its simplicity and robustness. However, the lack of spatial information may result in its failure to get high tracking precision. This might be even worse when the target is scale variant and the sequences are gray-levels. This paper presents a novel multiple subtemplates based tracking algorithm for the termin...

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...

We have recently introduced an incremental learning algorithm, Learn.NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Learn.NSE is an ensemble of classifiers approach, training a new classifier on each consecutive batch of data that become available, and combining them through an age-adjusted dynamic error based weighted majority voting. ...