BACKGROUND Recent research has highlighted the role of emotion-based impulsivity (negative and positive urgency personality traits) for alcohol use and abuse, but has yet to examine how these personality traits interact with the brain's motivational systems. Using functional magnetic resonance imaging (fMRI), we tested whether urgency traits and mood induction affected medial prefrontal respons...

This study determined and compared the influences of various processing techniques including air circulating oven (ACO), dry heat (DHO) water bath (WB) on impact strength (IS) microhardness (HV) conventional cure acrylic resin (CHCAR) rubber reinforced (RRHCAR). Samples were fabricated using CHCAR (control Group A; n=114) RRHCAR (experimental B; n=114). A B further divided into subgroups accord...

In this paper a metaheuristic technique called Ant Colony Optimization (ACO) is proposed to derive operating policies for a multi-purpose reservoir system. Most of the real world problems often involve non-linear optimization in their solution with high dimensionality and large number of equality and inequality constraints. Often the conventional techniques fail to yield global optimal solution...

BACKGROUND The accountable care organization (ACO) model being adopted across the United States aims to improve patient care and reduce costs. Little is known about whether commercial ACO contracts include accountability for prescription drug spending or how ACOs are engaging outpatient pharmacies and managing prescription drug use. OBJECTIVE To explore how ACOs are addressing drug spending a...

BACKGROUND The accountable care organization (ACO) is a new organizational form to manage patients across the continuum of care. There are numerous questions about how ACOs should be optimally structured, including compensation arrangements with primary care physicians. METHODS Using data from a national survey of physician practices, we compared primary care physicians' compensation between ...

<span>This study proposed a hybrid approach of firefly algorithm (FA) and ant colony optimization (ACO) for solving multi-depot multiple traveling salesman problem, TSP with more than one departure city. The FA is fast converging but easily trapped into the local optimum. ACO has great ability to search solution it converges slowly. To get better result convergence time, we integrate find...

Ant colony optimization (ACO) algorithms have originally been designed for static problems, where the input data is known in advance and not subject to changes over time. Later, long term memory of ACO proved effective reoptimization environment when extended deal with dynamic combinatorial problems (DCOPs). Among major proposals this kind, several adaptations procedures improve information reu...

The application of ACO-based algorithms in data mining is growing over the last few years and several supervised and unsupervised learning algorithms have been developed using this bio-inspired approach. Most recent works concerning unsupervised learning have been focused on clustering, showing great potential of ACO-based techniques. This work presents an ACO-based clustering algorithm inspire...

This paper studies the effect of fixing the length of the selected feature subsets on the performance of ant colony optimization (ACO) for feature selection (FS) for supervised learning. It addresses this concern by investigating: (1) determining the optimal feature subset from datamining perspective, (2) demonstrating the solution convergence in case of fixing the length of the selected featur...

This article proposes to solve the oversaturated network traffic signal coordination problem using the Ant Colony Optimization (ACO) algorithm. The traffic networks used are discrete time models which use green times at all the intersections throughout the considered period of oversaturation as the decision variables. The ACO algorithm finds intelligent timing plans which take care of dissipati...