An ISS self-triggered implementation of linear controllers

Nowadays control systems are mostly implemented on digital platforms and, increasingly, over shared communication networks. Reducing resources (processor utilization, network bandwidth, etc.) in such implementations increases the potential to run more applications on the same hardware. We present a self-triggered implementation of linear controllers that reduces the amount of controller updates necessary to retain stability of the closed-loop system. Furthermore, we show that the proposed self-triggered implementation is robust against additive disturbances and provide explicit guarantees of performance. The proposed technique exhibits an inherent trade-off between computation and potential savings on actuation.     

An algebraic approach to the design of compilers for object-oriented languages

In this paper we describe an algebraic approach to construct provably correct compilers for object-oriented languages; this is illustrated for programs written in a language similar to a sequential subset of Java. It includes recursive classes, inheritance, dynamic binding, recursion, type casts and test, assignment, and class-based visibility, but a copy semantics. In our approach, we tackle the problem of compiler correctness by reducing the task of compilation to that of program refinement. Compilation is identified with the reduction of a source program to a normal form that models the execution of object code. The normal form is generated by a series of correctness-preserving transformations that are proved sound from the basic laws of the language; therefore it is correct by construction. The main advantages of our approach are the characterisation of compilation within a uniform framework, where comparisons and translations between semantics are avoided, and the modularity and extensibility of the resulting compiler.     

BSSRDF Estimation from Single Images

We present a novel method to estimate an approximation of the reflectance characteristics of optically thick, homogeneous translucent materials using only a single photograph as input. First, we approximate the diffusion profile as a linear combination of piecewise constant functions, an approach that enables a linear system minimization and maximizes robustness in the presence of suboptimal input data inferred from the image. We then fit to a smoother monotonically decreasing model, ensuring continuity on its first derivative. We show the feasibility of our approach and validate it in controlled environments, comparing well against physical measurements from previous works. Next, we explore the performance of our method in uncontrolled scenarios, where neither lighting nor geometry are known. We show that these can be roughly approximated from the corresponding image by making two simple assumptions: that the object is lit by a distant light source and that it is globally convex, allowing us to capture the visual appearance of the photographed material. Compared with previous works, our technique offers an attractive balance between visual accuracy and ease of use, allowing its use in a wide range of scenarios including off‐the‐shelf, single images, thus extending the current repertoire of real‐world data acquisition techniques.     

Convolution‐Based Simulation of Homogeneous Subsurface Scattering

This paper introduces a new method for simulating homogeneous subsurface light transport in translucent objects. Our approach is based on irradiance convolutions over a multi‐layered representation of the volume for light transport, which is general enough to obtain plausible depictions of translucent objects based on the diffusion approximation. We aim at providing an efficient physically based algorithm that can apply arbitrary diffusion profiles to general geometries. We obtain accurate results for a wide range of materials, on par with the hierarchical method by Jensen and Buhler.     

Graphical Analysis for Operation Management: A Graphical Method to Support Operation Decision Making

This paper proposes a graphical method to easy decision‐making in industrial plants operations. The proposed tool ‘Graphical Analysis for Operation Management (GAOM) method’ allows to visualizing and analyzing production‐related parameters, integrating assets/systems maintenance aspects. This integration is based on the Total Productive Maintenance model, using its quantitative management techniques for optimal decision‐making in day‐to‐day operations. On the one hand, GAOM monitors possible production target deviations, and on the other, the tool illustrates different aspects to gain control on the production process, such as availability, repair time, cumulative production, or overall equipment effectiveness. Through appropriate information filtering, individual analysis by class of intervention (corrective maintenance, preventive maintenance, or operational intervention) and production level can be developed. Graphical Analysis for Operation Management (GAOM) integrates maintenance information (number of intervention, type of intervention, required/not required stoppage) with production information (cumulative production, cumulative defective products, and cumulative production target) during a certain timeframe (cumulative calendar time, duration of intervention). Then the tool computes basic performance indicators supporting operational decision‐making. GAOM provides interesting graphical outputs using scatter diagrams integrating indicators on the same graph. GAOM is inspired in the Graphical Analysis for Maintenance Management method, published by the authors (LB, AC, and PV) in 2012. Copyright © 2015 John Wiley & Sons, Ltd.     

Basic Evaluation of the Catalytic Pattern of the CuCeO x System in the Wet Oxidation of Phenol with Oxygen

The working mechanism of a ceria-supported Cu (Cu_at:Ce_at = 1:10) system in the Catalytic Wet Oxidation (CWO) of phenol with O₂ (T_R, 130–170 °C; P_O2, 7 atm) has been thoroughly assessed. Basic relationships amongst pH, extent of leaching and rate of phenol and TOC conversion prove the major contribution of a homogeneous catalytic path by Cu ions on the peculiar CWO pattern of supported copper catalyst. In addition, gas-phase reduction/oxidation tests signal the lack of reversibility of the redox cycle of the CuCeO_x system under typical reaction conditions.     

FTIR spectroscopic investigation of the active sites on different types of silica catalysts for methane partial oxidation to formaldehyde

Several commercial silica samples showing different catalytic activities in the partial oxidation of methane (MPO) to formaldehyde have been investigated using FTIR technique. Two IR absorption bands at 893 and 909 cm^–1, observed upon dehydroxylation of the silica catalysts and assigned to reactive siloxane sites on the surface (strained siloxane bridges), were found to disappear upon heating in methane at high temperature. The catalytic activity increases together with the intensity of the bands due to such strained sites in the different SiO₂ samples.     

Mesitylene solvated platinum atoms in the preparation of efficient supported catalysts for the dehydrogenation of methylcyclohexane to toluene

Mesitylene solvated platinum atoms have been conveniently used for the deposition of active Pt particles on -Al₂O₃ supports. The so prepared catalysts have been compared with traditionally obtained Pt/-Al₂O₃ catalysts in the dehydrogenation of methylcyclohexane to toluene, at 200 and 250 °C, showing, at low Pt loadings, a much greater specific activity.