Multistage particle windows for fast and accurate object detection

The common paradigm employed for object detection is the sliding window (SW) search. This approach generates grid-distributed patches, at all possible positions and sizes, which are evaluated by a binary classifier: The tradeoff between computational burden and detection accuracy is the real critical point of sliding windows; several methods have been proposed to speed up the search such as adding complementary features. We propose a paradigm that differs from any previous approach since it casts object detection into a statistical-based search using a Monte Carlo sampling for estimating the likelihood density function with Gaussian kernels. The estimation relies on a multistage strategy where the proposal distribution is progressively refined by taking into account the feedback of the classifiers. The method can be easily plugged into a Bayesian-recursive framework to exploit the temporal coherency of the target objects in videos. Several tests on pedestrian and face detection, both on images and videos, with different types of classifiers (cascade of boosted classifiers, soft cascades, and SVM) and features (covariance matrices, Haar-like features, integral channel features, and histogram of oriented gradients) demonstrate that the proposed method provides higher detection rates and accuracy as well as a lower computational burden w.r.t. sliding window detection.     

Pairs of Complementary Unary Languages with “Balanced” Nondeterministic Automata

For each sufficiently large n, there exists a unary regular language L such that both L and its complement L ^c are accepted by unambiguous nondeterministic automata with at most n states, while the smallest deterministic automata for these two languages still require a superpolynomial number of states, at least \(e^{\Omega(\sqrt[3]{n\cdot\ln^{2}n})}\). Actually, L and L ^c are “balanced” not only in the number of states but, moreover, they are accepted by nondeterministic machines sharing the same transition graph, differing only in the distribution of their final states. As a consequence, the gap between the sizes of unary unambiguous self-verifying automata and deterministic automata is also superpolynomial.     

Finite element shakedown analysis of two‐dimensional structures

In the present paper, the formulation proposed by Casciaro and Garcea (Comput. Meth. Appl. Mech. Eng., 2002; 191 :5761–5792) and applied to the shakedown analysis of plane frames, is extended to the analysis of two‐dimensional flat structures in both the cases of plane‐stress and plane‐strain. The discrete formulation is obtained using a mixed finite element in which both stress and displacement fields are interpolated. The material is assumed to be elasto‐plastic and a linearization of the elastic domain is performed. The result is a versatile iterative scheme well suited to implementation in general purpose FEM codes. An extensive series of numerical tests is presented showing the reliability of the proposed formulation. Copyright © 2005 John Wiley & Sons, Ltd.     

Integration of XML Schemas at various “severity” levels

This paper presents a novel approach for the integration of a set of eXtensible Markup Language (XML) Schemas. The proposed approach is specialized for XML, almost automatic, semantic and “light”. Further, an original peculiarity is that it is parametric w.r.t. a “severity” level against which the integration task is performed. The paper describes the approach in all details, illustrates various theoretical results, presents the experiments we have performed for testing it and, finally, compares it with various related approaches already proposed in the literature.     

Nanoconfined mixed Li and Mg borohydrides as materials for solid state hydrogen storage

Several mixtures of LiBH₄ and Mg(BH₄)₂ borohydrides in different stoichiometric ratios (1:0, 2:1, 1:1, 1:2, 0:1), prepared by high energy ball milling, have been investigated with X-ray powder diffraction and thermal programmed desorption (TPD) volumetric analysis to test the dehydrogenation kinetics in correlation with the physical mixture composition. Afterwards mixed and unmixed borohydrides were dispersed on high specific surface area ball milled graphite by means of the solvent infiltration technique. BET and statistical thickness methods were used to characterize the support surface properties, and SEM micrographs gave a better understanding of the preparation techniques. It has been observed by TPD volumetric measurements that the confinement of the reactive borohydrides on the nanoporous supports leads to a lower dehydrogenation temperature compared to unsupported borohydrides. Moreover, a further decrease of the dehydrogenation temperature has been observed by increasing the specific surface area of the support and the pores volume and by using the prepared mixtures instead of pure materials. The dehydrogenation process seems to be favoured by the heterogeneous nucleation on the graphite surface of decomposition products or intermediate phases from melted liquid borohydrides.     

Calcium: A comprehensive review on quantification,interaction with milk proteins and implications for processing of dairy products

Calcium (Ca) is a key micronutrient of high relevance for human nutrition that also influences the texture and taste of dairy products and their processability. In bovine milk, Ca is presented in several speciation forms, such as complexed with other milk components or free as ionic calcium while being distributed between colloidal and serum phases of milk. Partitioning of Ca between these phases is highly dynamic and influenced by factors, such as temperature, ionic strength, pH, and milk composition. Processing steps used during the manufacture of dairy products, such as preconditioning, concentration, acidification, salting, cooling, and heating, all contribute to modify Ca speciation and partition, thereby influencing product functionality, product yield, and fouling of equipment. This review aims to provide a comprehensive understanding of the influence of Ca partition on dairy products properties to support the development of kinetics models to reduce product losses and develop added-value products with improved functionality. To achieve this objective, approaches to separate milk phases, analytical approaches to determine Ca partition and speciation, the role of Ca on protein–protein interactions, and their influence on processing of dairy products are discussed.     

An updated version of BoltzWann: A code for the evaluation of thermoelectric and electronic transport properties with a maximally-localized Wannier functions basis

BoltzWann is a code to evaluate thermoelectric and electronic transport properties of extended systems with a maximally-localized Wannier function basis set. The semiclassical Boltzmann transport equations for the homogeneous infinite system are solved in the constant relaxation-time approximation and band energies and band derivatives are obtained via Wannier interpolations. Thanks to the exponential localization of the Wannier functions obtained, very high accuracy in the Brillouin zone integrals can be achieved with very moderate computational costs. Moreover, the analytical expression for the band derivatives in the Wannier basis resolves any issues that may occur when evaluating derivatives near band crossings. We present here an updated version of the BoltzWann code, which is now fully integrated within Wannier90 version 2.0, with minor bug fixes and the possibility to study also two-dimensional systems.     

Classification of drivers for industrial energy efficiency and their effect on the barriers affecting the investment decision-making process

Industrial energy efficiency represents a priority for European industrial competitiveness. Many studies offer contributions providing evidence of the existence of driving forces supporting the adoption of energy efficiency measures, but a structured approach to drivers for industrial energy efficiency is still lacking. Therefore, in the present study, we propose a definition of drivers, making emphasis on the industrial decision-maker perspective, that is needed for their classification here proposed. Focus is given to point out the difference between internal and external drivers, highlighting the major stakeholders responsible for their promotion. Drivers are further categorized into: regulatory, economic, informative, and vocational training. Moreover, we propose a framework describing the effect of drivers on barriers in the decision-making process, as well as a preliminary identification of the major stakeholders to promote drivers. The study opens several opportunities for further research in the area of industrial energy efficiency.