866 resultados para Vehicle routing problems with gains


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This study investigates pronoun reference and verbs with non-active morphology in high functioning Greek-speaking children with Autism Spectrum Disorders (ASD). It is motivated by problems with reflexive pronouns demonstrated by English-speaking children with ASD, and the fact that reflexivity is additionally expressed via non-active (reflexive) verbs in Greek. Twenty 5- to 8-year-old children with ASD and twenty vocabulary matched typically developing controls of the same age range completed a sentence-picture matching, an elicitation, and a judgment task. Children with ASD did not differ from controls in interpreting reflexive and strong pronouns, but were less accurate in the comprehension of clitics and omitted clitics in their production. The findings render clitics a vulnerable domain for autism in Greek, and potentially for other languages with clitics, and suggest that this could be a consequence of difficulties in the syntax-pragmatics or the syntax-phonology interface. The two groups did not differ in the comprehension of non-active morphology, but were less accurate in passive than reflexive verbs. This difference is likely to stem from the linguistic representation associated with each type of verb, rather than their input frequency.

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Background Epidemiological studies indicate that the prevalence of psychological problems in patients attending primary care services may be as high as 25%. Aim To identify factors that influence the detection of psychological difficulties in adolescent patients receiving primary care in the UK. Design of study A prospective study of 13-16 year olds consecutively attending general practices. Setting General practices, Norfolk, UK. Method Information was obtained from adolescents and parents using the validated Strengths and Difficulties Questionnaire (SDQ) and from GF`s using the consultation assessment form. Results Ninety-eight adolescents were recruited by 13 GPs in Norfolk (mean age = 14.4 years, SD = 1.08; 38 males, 60 females). The study identified psychological difficulties in almost one-third of adolescents (31/98, 31.6%). Three factors significant to the detection of psychological disorders in adolescents were identified: adolescents' perceptions of difficulties according to the self-report SDQ, the severity of their problems as indicated by the self-report SDQ, and whether psychological issues were discussed in the consultation. GPs did not always explore psychological problems with adolescents, even if GPs perceived these to be present. Nineteen of 31 adolescents with psychological difficulties were identified by GPs (sensitivity = 61.2%, specificity = 85.1%). A management plan or follow-up was made for only seven of 19 adolescents identified, suggesting that ongoing psychological difficulties in many patients are not being addressed. Conclusions GPs are in a good position to identify psychological issues in adolescents, but GPs and adolescents seem reluctant to explore these openly. Open discussion of psychological issues in GP consultations was found to be the most important factor in determining whether psychological difficulties in adolescents are detected by GPs.

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Several real problems involve the classification of data into categories or classes. Given a data set containing data whose classes are known, Machine Learning algorithms can be employed for the induction of a classifier able to predict the class of new data from the same domain, performing the desired discrimination. Some learning techniques are originally conceived for the solution of problems with only two classes, also named binary classification problems. However, many problems require the discrimination of examples into more than two categories or classes. This paper presents a survey on the main strategies for the generalization of binary classifiers to problems with more than two classes, known as multiclass classification problems. The focus is on strategies that decompose the original multiclass problem into multiple binary subtasks, whose outputs are combined to obtain the final prediction.

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Despite the many existing crosslinking procedures, glutaraldehyde (GA) is still the method of choice used in the manufacture of bioprosthesis. The major problems with GA are: (a) uncontrolled reactivity due to the chemical complexity or GA solutions; (b) toxicity due to the release of GA from polymeric crosslinks; and (c) tissue impermeabilization due to polymeric and heterogeneous crosslinks formation, partially responsible for the undesirable calcification of the bioprosthesis. A new method of crosslinking glutaraldehyde acetals has been developed with GA in acid ethanolic solution, and after the distribution inside de matrix, GA is released to crosslinking. Concentrations of hydrochloride acid in ethanolic solutions between 0.1 and 0.001 mol/L with GA concentration between 0.1 and 1.0% were measured in an ultraviolet spectrophotometer to verify the presence of free aldehyde groups and polymeric compounds of GA. After these measurements, the solutions were used to crosslink bovine pericardium. The spectrophotometric results showed that GA was better protected in acetal forms for acid ethanolic solution with HCl at 0.003 mol/L and GA 1.0%(v/v). The shrinkage temperature results of bovine pericardium crosslinked with acetal solutions showed values near 85 C after the exposure to triethylamine vapors.

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This paper aims to propose a hybrid meta-heuristics for the Heterogeneous Fleet Vehicle Routing Problem (HVRP), which is a combinatorial optimization problem NP-hard, and is characterized by the use of a limited fleet consists of different vehicles with different capacities. The hybrid method developed makes use of a memetic algorithm associated with the component optimizer Vocabulary Building. The resulting hybrid meta-heuristic was implemented in the programming language C + + and computational experiments generated good results in relation to meta-heuristic applied in isolation, proving the efficiency of the proposed method.

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This paper presents metaheuristic strategies based on the framework of evolutionary algorithms (Genetic and Memetic) with the addition of Technical Vocabulary Building for solving the Problem of Optimizing the Use of Multiple Mobile Units Recovery of Oil (MRO units). Because it is an NP-hard problem, a mathematical model is formulated for the problem, allowing the construction of test instances that are used to validate the evolutionary metaheuristics developed

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In this Thesis, the development of the dynamic model of multirotor unmanned aerial vehicle with vertical takeoff and landing characteristics, considering input nonlinearities and a full state robust backstepping controller are presented. The dynamic model is expressed using the Newton-Euler laws, aiming to obtain a better mathematical representation of the mechanical system for system analysis and control design, not only when it is hovering, but also when it is taking-off, or landing, or flying to perform a task. The input nonlinearities are the deadzone and saturation, where the gravitational effect and the inherent physical constrains of the rotors are related and addressed. The experimental multirotor aerial vehicle is equipped with an inertial measurement unit and a sonar sensor, which appropriately provides measurements of attitude and altitude. A real-time attitude estimation scheme based on the extended Kalman filter using quaternions was developed. Then, for robustness analysis, sensors were modeled as the ideal value with addition of an unknown bias and unknown white noise. The bounded robust attitude/altitude controller were derived based on globally uniformly practically asymptotically stable for real systems, that remains globally uniformly asymptotically stable if and only if their solutions are globally uniformly bounded, dealing with convergence and stability into a ball of the state space with non-null radius, under some assumptions. The Lyapunov analysis technique was used to prove the stability of the closed-loop system, compute bounds on control gains and guaranteeing desired bounds on attitude dynamics tracking errors in the presence of measurement disturbances. The controller laws were tested in numerical simulations and in an experimental hexarotor, developed at the UFRN Robotics Laboratory

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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A neural network model for solving constrained nonlinear optimization problems with bounded variables is presented in this paper. More specifically, a modified Hopfield network is developed and its internal parameters are completed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points. The network is shown to be completely stable and globally convergent to the solutions of constrained nonlinear optimization problems. A fuzzy logic controller is incorporated in the network to minimize convergence time. Simulation results are presented to validate the proposed approach.

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The widespread growth in the use of smart cards (by banks, transport services, and cell phones, etc) has brought an important fact that must be addressed: the need of tools that can be used to verify such cards, so to guarantee the correctness of their software. As the vast majority of cards that are being developed nowadays use the JavaCard technology as they software layer, the use of the Java Modeling Language (JML) to specify their programs appear as a natural solution. JML is a formal language tailored to Java. It has been inspired by methodologies from Larch and Eiffel, and has been widely adopted as the de facto language when dealing with specification of any Java related program. Various tools that make use of JML have already been developed, covering a wide range of functionalities, such as run time and static checking. But the tools existent so far for static checking are not fully automated, and, those that are, do not offer an adequate level of soundness and completeness. Our objective is to contribute to a series of techniques, that can be used to accomplish a fully automated and confident verification of JavaCard applets. In this work we present the first steps to this. With the use of a software platform comprised by Krakatoa, Why and haRVey, we developed a set of techniques to reduce the size of the theory necessary to verify the specifications. Such techniques have yielded very good results, with gains of almost 100% in all tested cases, and has proved as a valuable technique to be used, not only in this, but in most real world problems related to automatic verification

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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We proposed a simple feedback control method to suppress chaotic behavior in oscillators with limited power supply. The small-amplitude controlling signal is applied directly to the power supply system, so as to alter the characteristic curve of the driving motor. Numerical results are presented showing the method efficiency for a wide range of control parameters. Moreover, we have found that, for some parameters, this kind of control may introduce coexisting periodic attractors with complex basins of attraction and, therefore, serious problems with predictability of the final state the system will asymptote to. (c) 2006 Elsevier Ltd. All rights reserved.

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Classical and modified Lagrangian bounds for the optimal value of optimization problems with a double decomposable structure are studied. For the class of many-to-many assignment problems, this property of constraints is used to design a subgradient algorithm for solving the modified dual problem. Numerical results are presented to compare the quality of classical and modified bounds, as well as the properties of the corresponding Lagrangian solutions.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)