Search results for "UML"
showing 10 items of 407 documents
Selection Correction in Panel Data Models: An Application to Labour Supply and Wages
2000
In recent years a number of panel estimators have been suggested for sample selection models, where both the selection equation and the equation of interest contain individual effects which are correlated with the explanatory variables. We review and compare some of these estimators, and apply them to estimating the return to actual labour market experience for females, using a panel of twelve years. All these estimators rely on the assumption of strict exogeneity of regressors in the equation of interest, conditional on individual specific effects and the selection mechanism. This assumption is likely to be violated in many applications. Also, life history variables are often measured with…
R&D Network Formation with Myopic and Farsighted Firms
2018
We study the formation of R&D networks when each firm benefits from the research done by other firms it is connected to. Firms can be either myopic or farsighted when deciding about the links they want to form. We propose the notion of myopic-farsighted stable set to determine the R&D networks that emerge in the long run. When the majority of firms is myopic, stability leads to R&D networks consisting of either two asymmetric components with the largest component comprises three-quarters of firms or two symmetric components of nearly equal size with the largest component having only myopic firms. But, once the majority of firms becomes farsighted, only R&D networks with two asymmetric compo…
Exploring Multi-Objective Optimization for Multi-Label Classifier Ensembles
2019
Multi-label classification deals with the task of predicting multiple class labels for a given sample. Several performance metrics are designed in the literature to measure the quality of any multi-label classification technique. In general existing multi-label classification approaches focus on optimizing only a single performance measure. The current work builds on the hypothesis that a weighted ensemble of multiple multi-label classifiers will lead to obtain improved results. The appropriate weight combinations for combining the outputs of multiple classifiers can be selected after simultaneously optimizing different multi-label classification metrics like micro F1, hamming loss, 0/1 los…
Multiphysics Optimization for First Wall Design Enhancement in Water-Cooled Breeding Blankets
2021
Abstract The commercial feasibility of the first fusion power plant generation adopting D-T plasma is strongly dependent upon the self-sustainability in terms of tritium fuelling. Within such a kind of reactor, the component selected to house the tritium breeding reactions is the breeding blanket, which is further assigned to heat power removal and radiation shielding functions. As a consequence of both its role and position, the breeding blanket is heavily exposed to both surface and volumetric heat loads and, hence, its design requires a typical multiphysics approach, from the neutronics to the thermo-mechanics. During last years, a great deal of effort has been put in the optimization of…
Technical and economical comparison between different topologies of PV plant under mismatch effect
2014
This paper presents a technical and economical comparative analysis between two topology of photovoltaic plant. In particular the performances of series-parallel (SP) and total cross tied (TCT), topologies are taken into account, referring to a partially shaded photovoltaic plant. Thanks to a simulation model developed, in the paper the mismatch effects due to three different shading conditions, for SP and TCT topology plant, are quantified. Since the TCT solution, even though increase the energy production, raise the complexity of plants as well as their costs, an evaluation of the individual costs of each component of a SP and TCT plant topology, as PV modules, support structure, inverter…
Classifier Optimized for Resource-constrained Pervasive Systems and Energy-efficiency
2017
Computational intelligence is often used in smart environment applications in order to determine a user’scontext. Many computational intelligence algorithms are complex and resource-consuming which can beproblematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. Thesetypes of devices are, however, highly useful in pervasive and mobile computing due to their small size,energy-efficiency and ability to provide fast real-time responses. In this paper, we propose a classi-fier, CORPSE, specifically targeted for implementation in FPGA:s, ASIC:s or low-level microcontrollers.CORPSE has a small memory footprint, is computationally inexpensive, and is suitable for…
Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm
2019
We formulate and solve a real-world shape design optimization problem of an air intake ventilation system in a tractor cabin by using a preference-based surrogate-assisted evolutionary multiobjective optimization algorithm. We are motivated by practical applicability and focus on two main challenges faced by practitioners in industry: 1) meaningful formulation of the optimization problem reflecting the needs of a decision maker and 2) finding a desirable solution based on a decision maker’s preferences when solving a problem with computationally expensive function evaluations. For the first challenge, we describe the procedure of modelling a component in the air intake ventilation system wi…
Support vector machine classification of brain metastasis and radiation necrosis based on texture analysis in MRI
2015
Purpose To develop a classification model using texture features and support vector machine in contrast-enhanced T1-weighted images to differentiate between brain metastasis and radiation necrosis. Methods Texture features were extracted from 115 lesions: 32 of them previously diagnosed as radiation necrosis, 23 as radiation-treated metastasis and 60 untreated metastases; including a total of 179 features derived from six texture analysis methods. A feature selection technique based on support vector machine was used to obtain a subset of features that provide optimal performance. Results The highest classification accuracy evaluated over test sets was achieved with a subset of ten features…
An inquiry-based approach to Maxwell distribution: a case study with engineering students
2013
The concept of distribution is a fundamental component of statistical thinking. This paper describes a teaching approach for it that uses a specific activity related to the field of statistical mechanics. The concept of the velocity distribution of a particle system is dealt with using an inquiry-based approach involving an experimental examination of Maxwell’s distribution. Some outcomes of a teaching experiment held at the Faculty of Engineering of the University of Palermo, Italy are described.
A new multidimensional adaptive mesh refinement hydro + gravity cosmological code
2004
A new cosmological multidimensional hydrodynamic and N-body code based on an Adaptive Mesh Refinement scheme is described and tested. The hydro part is based on modern high-resolution shock-capturing techniques, whereas N-body approach is based on the Particle Mesh method. The code has been specifically designed for cosmological applications. Tests including shocks, strong gradients, and gravity have been considered. A cosmological test based on Santa Barbara cluster is also presented. The usefulness of the code is discussed. In particular, this powerful tool is expected to be appropriate to describe the evolution of the hot gas component located inside asymmetric cosmological structures.