1,352 research outputs found

    FM 047-02: a collisional pair of galaxies with a ring

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    Aims. We investigate the nature of the galaxy pair FM 047-02, which has been proposed as an archetype of the Solitaire types of peculiar (collisional) ring galaxies. Methods. The study is based on long-slit spectrophotometric data in the range of 3500-9500 angstrons obtained with the Gemini Multi-ObjectComment: 07 pages, 06 figures, 02 tables. arXiv admin note: text overlap with arXiv:1206.071

    Multiple solutions of mixed variable optimization by multistart hooke and jeeves filter method

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    In this study, we propose a multistart method based on an extended version of the Hooke and Jeeves (HJ) algorithm for computing mul- tiple solutions of mixed variable optimization problems. The inequal- ity and equality constraints of the problem are handled by a filter set methodology. The basic ideas present in the HJ algorithm, namely the exploratory and pattern moves, are extended to consider two objective functions and to handle continuous and integer variables simultaneously. This proposal is integrated into a multistart method as a local search procedure that is repeatedly invoked to converge to different global and non-global optimal solutions starting from randomly generated points. To avoid repeated convergence to previously computed solutions, the concept of region of attraction of an optimizer is implemented. The performance of the new method is tested on benchmark problems. Its effectiveness is emphasized by a comparison with a well-known solver.Fundação para a Ciência e a Tecnologia (FCT

    Theory of mind in children with attention deficit hyperactivity disorder

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    Introduction. Theory of mind (TM) is involved in social cognition, as it evaluates our ability to impute our mental states to the others in order to predict and explain behaviour. In the literature, it has been noticed that children with attention deficit hyperactivity disorder (ADHD) show some impairments of TM when compared with children not neurodevelopmental impaired. Our goal in this study was to compare the TM in two groups: schooler children with normal development and schooler children with ADHD. Subjects and methods. A total of 35 children, aged between 6 and 12 years, were recruited: 17 with ADHD and 18 not neurodevelopmental impaired. TM was evaluated using an assessment method validated for the Portuguese population: Turtle on the Island-Battery of Assessment of Executive Functions in Children. Results. We obtained two comparable groups concerning sociodemographic data. There were no significant differences between the two groups regarding TM. Conclusion. The TM assessment in Portuguese children did not reveal significant impairment regarding this cognitive skill in children with ADHD

    Improving efficiency of a multistart with interrupted Hooke-and-Jeeves filter search for solving MINLP problems

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    Publicado em: "Computational science and its applications – ICCSA 2016: 16th International Conference, Beijing, China, July 4-7, 2016, Proceedings, Part I". ISBN 978-3-319-42084-4This paper addresses the problem of solving mixed-integer nonlinear programming (MINLP) problems by a multistart strategy that invokes a derivative-free local search procedure based on a filter set methodology to handle nonlinear constraints. A new concept of componentwise normalized distance aiming to discard randomly generated points that are sufficiently close to other points already used to invoke the local search is analyzed. A variant of the Hooke-and-Jeeves filter algorithm for MINLP is proposed with the goal of interrupting the iterative process if the accepted iterate falls inside an -neighborhood of an already computed minimizer. Preliminary numerical results are included.FCT - Fundação para a Ciência e Tecnologia, within the projects UID/CEC/00319/2013 and UID/MAT/00013/2013.COMPETE: POCI-01- 0145-FEDER-00704

    Multistart Hooke and Jeeves filter method for mixed variable optimization

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    AIP Conference Proceedings, vol. 1558In this study, we propose an extended version of the Hooke and Jeeves algorithm that uses a simple heuristic to handle integer and/or binary variables and a filter set methodology to handle constraints. This proposal is integrated into a multistart method as a local solver and it is repeatedly called in order to compute different optimal solutions. Then, the best of all stored optimal solutions is selected as the global optimum. The performance of the new method is tested on benchmark problems. Its effectiveness is emphasized by a comparison with other well-known stochastic solvers.Fundação para a Ciência e a Tecnologia (FCT

    Embedding a competitive ranking method in the artificial fish swarm algorithm for global optimization

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    Nonlinear programming problems are known to be difficult to solve, especially those that involve a multimodal objective function and/or non-convex and at the same time disjointed solution space. Heuristic methods that do not require derivative calculations have been used to solve this type of constrained problems. The most used constraint-handling technique has been the penalty method. This method converts the constrained optimization problem to a sequence of unconstrained problems by adding, to the objective function, terms that penalize constraint violation. The selection of the appropriate penalty parameter value is the main difficulty with this type of method. To address this issue, we use a global competitive ranking method. This method is embedded in a stochastic population based technique known as the artificial fish swarm (AFS) algorithm. The AFS search for better points is mainly based on four simulated movements: chasing, swarming, searching, and random. For each point, the movement that gives the best position is chosen. To assess the quality of each point in the population, the competitive ranking method is used to rank the points with respect to objective function and constraint violation independently. When points have equal constraint violations then the objective function values are used to define their relative fitness. The AFS algorithm also relies on a very simple and random local search to refine the search towards the global optimal solution in the solution space. A benchmarking set of global problems is used to assess this AFS algorithm performance

    Perception of reality vs. professional reality in unilateral lower limb prothesis user amputees

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    Introduction To understand the perception of lower limb amputees, regarding movement with prothesis, wellbeing and perceived appearance, and to elaborate a socio-professional demographic and clinical study, to establish patterns and relations that may help enjoy a better quality of life. Methods We conducted a questionnaire survey of socio-professional, demographic and clinical data of 103 lower limb amputees, between 29th March 2018 and 9th July 2018. 74 interviewees also replied to sub-scales from the PEQPT questionnaire. Results The values attributed to movement, wellbeing and perceived appearance, were on average, 59.3%, 62.7% and 75.3%, respectively. A large number of patients (80.6%) stated that because of the amputation, there is an increase in the monthly expenses and a reduction in the monthly income. The value attributed to the prosthetics perceived appearance for males and females, was, on average, 79.32% and 65.03% respectively, this difference being significant. Conclusions Our main aim was to study the perception regarding movement with prothesis; the perception regarding wellbeing with prothesis; the perception regarding prothesis perceived appearance; to elaborate a socioprofessional, demographic and clinical analysis.In the first three points, the values attributed are good, mainly the perceived appearance issue. In the fourth point, we can conclude that it was successfully undertaken.info:eu-repo/semantics/publishedVersio

    An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method

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    This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed convergence to an ϵ-global minimizer of a constrained nonlinear optimization problem. The bound constrained subproblems that emerge at each iteration k of the framework are solved by an improved artificial fish swarm algorithm. Convergence to an ϵk-global minimizer of the HAL function is guaranteed with probability one, where ϵk→ϵ as k→∞. Preliminary numerical experiments show that the proposed paradigm compares favorably with other penalty-type methods.Fundação para a Ciência e a Tecnologia (FCT

    AFSFilter: artificial fish swarm filter-based algorithm for global optimization

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    A fish swarm intelligence algorithm based on the filter set concept to accept, at each iteration, a population of trial solutions whenever they improve constraint violation or objective function, relative to the current solutions, is proposed for constrained global continuous optimization problems. Preliminary numerical results are provided.Fundação para a Ciência e a Tecnologia (FCT

    A penalty approach for solving nonsmooth and nonconvex MINLP problems

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    This paper presents a penalty approach for globally solving nonsmooth and nonconvex mixed-integer nonlinear programming (MINLP) problems. Both integrality constraints and general nonlinear constraints are handled separately by hyperbolic tangent penalty functions. Proximity from an iterate to a feasible promising solution is enforced by an oracle penalty term. The numerical experiments show that the proposed oracle-based penalty approach is effective in reaching the solutions of the MINLP problems and is competitive when compared with other strategies.FCT - Fundação para a Ciência e a Tecnologia.The authors would like to thank two anonymous referees for their valuable comments and suggestions to improve the paper. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundação para a Ciência e a Tecnologia within the projects UID/CEC/00319/2013 and UID/MAT/00013/ 2013.info:eu-repo/semantics/publishedVersio
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