Search results for "Maximization"
showing 10 items of 84 documents
Under-over benefitting perceptions and evaluation of services
2016
Purpose– In the context of service exchanges, the purpose of this paper is to examine the form of the link from under-benefitting (customers receive less than they invest) vs over-benefitting (customers receive more than they invest) perceptions to customer service evaluations. The authors assess three competing hypotheses: maximization, fairness, and the asymmetric hypotheses.Design/methodology/approach– Linear and nonlinear relationships between under-over benefitting perceptions and service evaluations are examined following a test-retest approach. These relationships are investigated in four samples from two survey studies: hotels (Time 1,n=591; Time 2,n=512) and restaurants (Time 1,n=5…
Robust Maintenance Scheduling for Reliability Maximization
2009
The present paper aims to single out the maintenance actions to perform on a system constrained to be maintained only during some planned stops. Since system failure implies costs and risks for people and/or the environment, then it is necessary to minimize the probability of its occurrence. Thus, maintenance actions need to maximize the system reliability up to the next planned stop, in respect to some constraint. The originality of the problem discussed in the present paper lies in considering reliability values affected with uncertainty within a range of vagueness. Consequently, a further problem is added to the constrained reliability maximization, that is the search for a robust soluti…
Selection of Series System Components to Maximize Reliability
2010
The paper tackles the problem of maximizing the reliability of a series system by an opportune choice of components. Each type of component must be selected among the available alternatives for that component whereas a fixed amount of budget can not be overcome. The problem can be formulated by a binary non linear programming model and it is equivalent to a knapsack problem with multiple-choice constraints, well known to be NP-hard. An exact algorithm is proposed for solving large dimension problems to the optimum in a short time. The algorithm efficiency is finally compared with the recent heuristics proposed in literature to approach the same problem.
Composite laminates buckling optimization through Levy based Ant Colony Optimization
2010
In this paper, the authors propose the use of the Levy probability distribution as leading mechanism for solutions differentiation in an efficient and bio-inspired optimization algorithm, ant colony optimization in continuous domains, ACOR. In the classical ACOR, new solutions are constructed starting from one solution, selected from an archive, where Gaussian distribution is used for parameter diversification. In the proposed approach, the Levy probability distributions are properly introduced in the solution construction step, in order to couple the ACOR algorithm with the exploration properties of the Levy distribution. The proposed approach has been tested on mathematical test functions…
Morphological exponential entropy driven-HUM.
2006
This paper presents an improvement to the Ex- ponential Entropy Driven - Homomorphic Unsharp Masking (E 2 D − HUM ) algorithm devoted to illumination artifact sup- pression on Magnetic Resonance Images. E 2 D−HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E 2 D − HUM without a segmentation phase, whose parameters should be chosen in relation to the image. I. INTRODUCTION Most of the studies on illumination correction found in literature are oriented to brain (18) magnetic resonance images (…
Maximizing versus satisficing in the digital age: Disjoint scales and the case for “construct consensus”
2018
Abstract A question facing us today, in the new and rapidly evolving digital age, is whether searching for the best option – being a maximizer – leads to greater happiness and better outcomes than settling on the first good enough option found – or “satisficing.” Answers to this question inform behavioural insights to improve well-being and decision-making in policy and organizational settings. Yet, the answers to this fundamental question of measurement of the happiness of a maximizer versus a satisficer in the current psychological literature are: 1) conflicting; 2) anchored on the use of the first scale published to measure maximization as an individual-difference, and 3) unable to descr…
Network-Assisted Resource Allocation with Quality and Conflict Constraints for V2V Communications
2018
The 3rd Generation Partnership Project (3GPP) has recently established in Rel. 14 a network-assisted resource allocation scheme for vehicular broadcast communications. Such novel paradigm is known as vehicle--to--vehicle (V2V) \textit{mode-3} and consists in eNodeBs engaging only in the distribution of sidelink subchannels among vehicles in coverage. Thereupon, without further intervention of the former, vehicles will broadcast their respective signals directly to their counterparts. Because the allotment of subchannels takes place intermittently to reduce signaling, it must primarily be conflict-free in order not to jeopardize the reception of signals. We have identified four pivotal types…
Spectrum cartography using adaptive radial basis functions: Experimental validation
2017
In this paper, we experimentally validate the functionality of a developed algorithm for spectrum cartography using adaptive Gaussian radial basis functions (RBF). The RBF are strategically centered around representative centroid locations in a machine learning context. We assume no prior knowledge about neither the power spectral densities (PSD) of the transmitters nor their locations. Instead, the received signal power at each location is estimated as a linear combination of different RBFs. The weights of the RBFs, their Gaussian decaying parameters and locations are jointly optimized using expectation maximization with a least squares loss function and a quadratic regularizer. The perfor…
ICA of full complex-valued fMRI data using phase information of spatial maps.
2015
Background ICA of complex-valued fMRI data is challenging because of the ambiguous and noisy nature of the phase. A typical solution is to remove noisy regions from fMRI data prior to ICA. However, it may be more optimal to carry out ICA of full complex-valued fMRI data, since any filtering or voxel-based processing may disrupt information that can be useful to ICA. New method We enable ICA of the full complex-valued fMRI data by utilizing phase information of estimated spatial maps (SMs). The SM phases are first adjusted to properly represent spatial phase changes of all voxels based on estimated time courses (TCs), and then these are used to segment the voxels into BOLD-related and unwant…
Spatio‐temporal classification in point patterns under the presence of clutter
2019
We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions o…