Search results for " image processing."
showing 10 items of 2265 documents
A Survey of Prostate Segmentation Methodologies in Ultrasound, Magnetic Resonance and Computed Tomography Images
2012
Prostate segmentation is a challenging task, and the challenges significantly differ from one imaging modality to another. Low contrast, speckle, micro-calcifications and imaging artifacts like shadow poses serious challenges to accurate prostate segmentation in transrectal ultrasound (TRUS) images. However in magnetic resonance (MR) images, superior soft tissue contrast highlights large variability in shape, size and texture information inside the prostate. In contrast poor soft tissue contrast between prostate and surrounding tissues in computed tomography (CT) images pose a challenge in accurate prostate segmentation. This article reviews the methods developed for prostate gland segmenta…
Occupational Hazards Management Using a Grey-Based Decision-Making Approach
2019
Abstract The objective of this paper is to present and verify the decision-making model which makes it possible to streamline the occupational hazards that tend to occur in the work environment, according to the adopted decision-making criteria. In this way, it will be possible to reduce inconsistencies of decision-makers deciding to focus their preventive measures upon the most important hazards, in the situation when the same assessments for hazards are obtained using classical matrix techniques. Within this model, a grey approach was proposed, which makes it possible for experts to use linguistic variables in such assessments. The following three risk assessment parameters were used as t…
Special Issue on Innovative Artificial Intelligence Solutions for Crisis Management
2015
International audience
A GRASP algorithm for constrained two-dimensional non-guillotine cutting problems
2005
This paper presents a greedy randomized adaptive search procedure (GRASP) for the constrained two-dimensional non-guillotine cutting problem, the problem of cutting the rectangular pieces from a large rectangle so as to maximize the value of the pieces cut. We investigate several strategies for the constructive and improvement phases and several choices for critical search parameters. We perform extensive computational experiments with well-known instances previously reported, first to select the best alternatives and then to compare the efficiency of our algorithm with other procedures.
Bayesian forecasting with the Holt–Winters model
2010
Exponential smoothing methods are widely used as forecasting techniques in inventory systems and business planning, where reliable prediction intervals are also required for a large number of series. This paper describes a Bayesian forecasting approach based on the Holt–Winters model, which allows obtaining accurate prediction intervals. We show how to build them incorporating the uncertainty due to the smoothing unknowns using a linear heteroscedastic model. That linear formulation simplifies obtaining the posterior distribution on the unknowns; a random sample from such posterior, which is not analytical, is provided using an acceptance sampling procedure and a Monte Carlo approach gives …
Franchising in Europe: Exploring the Case of Spain with Self-organizing Time Maps
2016
Economic crises affect both the organizational side and the brand side of the franchise. Using self-organizing time maps, this study examines how franchise brand behavior influences decisions by potential franchisees in Spain. The findings confirm that franchising offers an alternative to the business turnaround strategy, which firms apply when faced with adverse changes in the environment such as those caused by the economic crisis in Spain. Results show that all franchise brands within the same sector behaved similarly, except for brands in the catering sector, which displayed varying responses to the economic changes. The authors discuss the implications of these results for future franc…
Tabu search with strategic oscillation for the maximally diverse grouping problem
2013
We propose new heuristic procedures for the maximally diverse grouping problem (MDGP). This NP-hard problem consists of forming maximally diverse groups—of equal or different size—from a given set of elements. The most general formulation, which we address, allows for the size of each group to fall within specified limits. The MDGP has applications in academics, such as creating diverse teams of students, or in training settings where it may be desired to create groups that are as diverse as possible. Search mechanisms, based on the tabu search methodology, are developed for the MDGP, including a strategic oscillation that enables search paths to cross a feasibility boundary. We evaluate co…
On the generalized directed rural postman problem
2014
The generalized directed rural postman problem (GDRPP) is a generic type of arc routing problem. In the present paper, it is described how many types of practically relevant single-vehicle routing problems can be modelled as GDRPPs. This demonstrates the versatility of the GDRPP and its importance as a unified model for postman problems. In addition, an exact and a heuristic solution method are presented. Computational experiments using two large sets of benchmark instances are performed. The results show high solution quality and thus demonstrate the practical usefulness of the approach.
GRASP with path relinking for the orienteering problem
2014
In this paper, we address an optimization problem resulting from the combination of the well-known travelling salesman and knapsack problems. In particular, we target the orienteering problem, originated in the context of sport, which consists of maximizing the total score associated with the vertices visited in a path within the available time. The problem, also known as the selective travelling salesman problem, is NP-hard and can be formulated as an integer linear program. Since the 1980s, several solution methods for this problem have been developed and applied to a variety of fields, particularly in routing and tourism. We propose a heuristic method—based on the Greedy Randomized Adapt…
Improving demand forecasting accuracy using nonlinear programming software
2006
We address the problem of forecasting real time series with a proportion of zero values and a great variability among the nonzero values. In order to calculate forecasts for a time series, the model coefficients must be estimated. The appropriate choice of values for the smoothing parameters in exponential smoothing methods relies on the minimization of the fitting errors of historical data. We adapt the generalized Holt–Winters formulation so that it can consider the starting values of the local components of level, trend and seasonality as decision variables of the nonlinear programming problem associated with this forecasting procedure. A spreadsheet model is used to solve the problems o…