The growing abundance of information necessitates the need for appropriate methods for organization and evaluation. Mining data for information and extracting conclusions has been a fertile field of research. However data mining needs methods to preprocess the data. Feature selection is a growing field of interest about selecting proper information from information repositories. The aim of this...

Label fusion is used in medical image segmentation to combine several different labels of the same entity into a single discrete label, potentially more accurate, with respect to the exact, sought segmentation, than the best input element. Using simulated data, we compared three existing label fusion techniques-STAPLE, Voting, and Shape-Based Averaging (SBA)-and observed that none could be cons...

We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal strategy in incomplete information settings. Specifically, an agent learns the optimal strategy to play against an opponent whose strategy varies with time, assuming no prior information about its negotiation parameters. In so doin...

The challenging task to synthesize automatically a time-to-amplitude converter, which unites by its functionality several digital circuits, has been successfully solved with the help of a novel methodology. The proposed approach is based on a paradigm according to which the substructures are regarded as additional mutation types and when ranged with other mutations form a new adaptive individua...

This study is devoted to overcome the underflow problem and poorly cost-effective limitation of model-set adaptive IMM algorithm. Cause of underflow problem in NovelIMM is addressed firstly, based on which an underflow prevented selection probabilities (UPSP) algorithm is presented to solve this problem. This paper then presents a fast model-set adaptive (FAIMM) IMM algorithm based on steady st...

Cloud service selection in a multi-cloud computing environment is receiving more and more attentions. There is an abundance of emerging cloud service resources that makes it hard for users to select the better services for their applications in a changing multi-cloud environment, especially for online real time applications. To assist users to efficiently select their preferred cloud services, ...

stock selection criteria play a key role in contrarian portfolio construction. the usual approach is applying cumulative return as stock selection criteria however applying this criterion leads to ranking stocks without considering investment risk. in this study, we analyze contrarian strategies that are based on reward–risk stock selection criteria in contrast to ordinary contrarian strategies...

According to a definition found in the summary of the Workshop on Adaptable and Adaptive Software[LL95]: “A program is called adaptive if it changes its behaviour automatically according to its context”. Within this context, we restrict our research domain to the automatic runtime adaptation of existing behaviours. In this paper, we propose an Adaptive Strategy Design Pattern that can be used t...

Climate change challenges conservation planners in making decisions about habitat site selection and augmentation. This pilot study explores the use of Robust Decision Making (RDM), a decision analytic approach employed in water and coastal management, for conservation decision-making. It employs the RDM approach to design a theoretical decision experiment that compares the differences in perfo...

In this paper, the tracking control problem of a class of Euler-Lagrange systems subjected to unknown uncertainties is addressed and an adaptive-robust control strategy, christened as Time-Delayed Adaptive Robust Control (TARC) is presented. The proposed control strategy approximates the unknown dynamics through time-delayed logic, and the switching logic provides robustness against the approxi...