Search results for "machines"
showing 10 items of 113 documents
Automatic classification of tissues on pelvic MRI based on relaxation times and support vector machine
2019
International audience; Tissue segmentation and classification in MRI is a challenging task due to a lack of signal intensity standardization. MRI signal is dependent on the acquisition protocol, the coil profile, the scanner type, etc. While we can compute quantitative physical tissue properties independent of the hardware and the sequence parameters, it is still difficult to leverage these physical properties to segment and classify pelvic tissues. The proposed method integrates quantitative MRI values (T1 and T2 relaxation times and pure synthetic weighted images) and machine learning (Support Vector Machine (SVM)) to segment and classify tissues in the pelvic region, i.e.: fat, muscle, …
Least-Norm Regularization For Weak Two-Level Optimization Problems
1992
In this paper, we consider a regularization for weak two-level optimization problems by adaptation of the method presented by Solohovic (1970). Existence and approximation results are given in the case in which the constraints to the lower level problems are described by a multifunction. Convergence results for the least-norm regularization under perturbations are also presented.
Design of a Permanent Magnet Synchronous Generator using Interactive Multiobjective Optimization
2017
We consider an analytical model of a permanent magnet synchronous generator and formulate a mixed-integer constrained multiobjective optimization problem with six objective functions. We demonstrate the usefulness of solving such a problem by applying an interactive multiobjective optimization method called NIMBUS. In the NIMBUS method, a decision is iteratively involved in the optimization process and directs the solution process in order to find her/his most preferred Pareto optimal solution for the problem. We also employ a commonly used noninteractive evolutionary multiobjective optimization method NSGA-II to generate a set of solutions that approximates the Pareto set and demonstrate t…
Verification of scope-dependent hierarchical state machines
2008
AbstractA hierarchical state machine (Hsm) is a finite state machine where a vertex can either expand to another hierarchical state machine (box) or be a basic vertex (node). Each node is labeled with atomic propositions. We study an extension of such model which allows atomic propositions to label also boxes (Shsm). We show that Shsms can be exponentially more succinct than Shsms and verification is in general harder by an exponential factor. We carefully establish the computational complexity of reachability, cycle detection, and model checking against general Ltl and Ctl specifications. We also discuss some natural and interesting restrictions of the considered problems for which we can …
Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models.
2012
Item does not contain fulltext The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape des…
Structure of the altitude adapted hemoglobin of Guinea pig in the R2-state
2010
Background: Guinea pigs are considered to be genetically adapted to a high altitude environment based on the consistent finding of a high oxygen affinity of their blood. Methodology/Principal Findings: The crystal structure of guinea pig hemoglobin at 1.8 A u resolution suggests that the increased oxygen affinity of guinea pig hemoglobin can be explained by two factors, namely a decreased stability of the Tstate and an increased stability of the R2-state. The destabilization of the T-state can be related to the substitution of a highly conserved proline (P44) to histidine (H44) in the a-subunit, which causes a steric hindrance with H97 of the b-subunit in the switch region. The stabilizatio…
Classification and retrieval on macroinvertebrate image databases
2011
Aquatic ecosystems are continuously threatened by a growing number of human induced changes. Macroinvertebrate biomonitoring is particularly efficient in pinpointing the cause-effect structure between slow and subtle changes and their detrimental consequences in aquatic ecosystems. The greatest obstacle to implementing efficient biomonitoring is currently the cost-intensive human expert taxonomic identification of samples. While there is evidence that automated recognition techniques can match human taxa identification accuracy at greatly reduced costs, so far the development of automated identification techniques for aquatic organisms has been minimal. In this paper, we focus on advancing …
The combined distribution/assignment problem in transportation network planning: a parallel approach on hypercube architecture
1995
The joint distribution/assignment problem plays a central role in urban transport network planning. In this problem, according to the mathematical model proposed by S. P. Evans, the trips are iteratively calculated and assigned to the network in such a way that the resulting traffic flows pattern satisfies the selfish equilibrium condition. Unfortunately the number of variables and constraints increase hardly with the greatness of the networks causing long computational time for the equilibrium solution. In this paper an nCUBE 2 parallel computing architecture is employed to solve the combined problem and to asses the potential of MIMD machines to handle large scale transportation network p…
Minimizing weighted earliness-tardiness on parallel machines using hybrid metaheuristics
2015
We consider the problem of scheduling a set of jobs on a set of identical parallel machines where the objective is to minimize the total weighted earliness and tardiness penalties with respect to a common due date. We propose a hybrid heuristic algorithm for constructing good solutions, combining priority rules for assigning jobs to machines and a local search with exact procedures for solving the one-machine subproblems. These solutions are then used in two metaheuristic frameworks, Path Relinking and Scatter Search, to obtain high quality solutions for the problem. The algorithms are tested on a large number of test instances to assess the efficiency of the proposed strategies. The result…
Noise enhanced stability in magnetic systems
2009
In this paper noise enhanced stability in magnetic systems is studied by both an Ising-type model and a Preisach–Arrhenius model as well as a dynamic Preisach model. It is shown that in one nonequilibrium Ising system noise enhanced stability occurs and that dynamic Preisach model has the capability to predict the occurrence of noise enhanced stability in magnetic systems. On the contrary, in a Preisach–Arrhenius model of a single quadrant magnetic material, noise enhanced stability is not detected.