Unsupervised Segmentation of Stereoscopic Video Objects: Constrained Segmentation Fusion Versus Greedy Active Contours

In this paper, we present a novel memory access reduction scheme (MARS) for two-dimension fast cosine transform (2-D FCT). It targets programmable DSPs with high memory-access latency. It reduces the number of memory accesses by: 1) reducing the number of weighting factors and 2) combining butterflies in vector-radix 2-D FCT pruning diagram from two stages to one stage with an efficient structure. Hardware platform based on general purpose processor is used to verify the effectiveness of the proposed method for vector-radix 2-D FCT pruning implementation. Experimental results validate the benefits of the proposed method with reduced memory access, less clock cycle and fewer memory space compared with the conventional implementation.     

Hydrogen production in solar reactors

The present work summarizes the recent activities of our laboratory in the field of solar-aided hydrogen production with structured monolithic solar reactors. This reactor concept, “transferred” from the well-known automobile exhaust catalytic after-treatment systems, employs ceramic supports optimized to absorb effectively solar radiation and develop sufficiently high temperatures, that are coated with active materials capable to perform/catalyze a variety of “solar-aided” reactions for the production of hydrogen such as water splitting or natural gas reforming. Our work evolves in an integrated approach starting from the synthesis of active powders tailored to particular hydrogen production reactions, their deposition upon porous absorbers, testing of relevant properties of merit such as thermomechanical stability and hydrogen yield and finally to the design, operation simulation and performance optimization of structured monolithic solar hydrogen production reactors. This approach, among other things, has culminated to the world's first closed, solar-thermochemical cycle in operation that is capable of continuous hydrogen production employing entirely renewable and abundant energy sources and raw materials – solar energy and water, respectively – without any CO₂ emissions and holds, thus, a significant potential for large-scale, emissions-free hydrogen production, particularly for regions of the world that lack indigenous resources but are endowed with ample solar energy.     

Parametric and nonparametric Bayesian model specification: A case study involving models for count data

In this paper we present the results of a simulation study to explore the ability of Bayesian parametric and nonparametric models to provide an adequate fit to count data of the type that would routinely be analyzed parametrically either through fixed-effects or random-effects Poisson models. The context of the study is a randomized controlled trial with two groups (treatment and control). Our nonparametric approach uses several modeling formulations based on Dirichlet process priors. We find that the nonparametric models are able to flexibly adapt to the data, to offer rich posterior inference, and to provide, in a variety of settings, more accurate predictive inference than parametric models.     

Kinetics of phenol oxidation in a trickle bed reactor over active carbon catalyst

The wet air oxidation of phenol over a commercial active carbon catalyst was studied in a trickle bed reactor (TBR) in the temperature and oxygen partial pressure ranges of 120–160 °C and 0.1–0.2 MPa, respectively. The performance of the active carbon was compared in terms of phenol and COD destruction. The weight change of active carbon due to reaction was also measured. Finally, oxic phenol adsorption isotherms were assessed in batch conditions at 25, 125 and 160 °C. In order to use the conversion data obtained from the TBR for a kinetic study, special care was taken to check the kinetic control in the TBR experiments. Several kinetic models including power law or Langmuir–Hinshelwood expressions were considered to describe the catalytic oxidation of phenol over active carbon. The simple power law model with first order dependence on both phenol and oxygen concentration predicted satisfactorily the experimental data not only over the entire range of operating conditions studied, but also outside its validity range. Copyright © 2005 Society of Chemical Industry     

Semi‐global and global containment control of multi‐agent systems with second‐order dynamics and input saturation

This paper considers both semi‐global and global containment control for a second‐order multi‐agent system that is composed by a network of identical harmonic oscillators or double integrators with multiple leaders and input saturation. A distributed low gain feedback algorithm is proposed to solve the semi‐global containment control problem for the network whose topology is directed and initial condition is taken from any a priori given bounded set. In particular, by using a parametric Lyapunov equation approach, M‐matrix properties and algebraic graph theory, an upper bound of the low gain parameter is estimated such that the low gain feedback matrix can be analytically determined without involving numerical computation. Furthermore, under the assumption that the induced subgraph formed by the followers is strongly connected and detail balanced, two linear feedback protocols are designed for coupled harmonic oscillators and coupled double integrators, respectively, to asymptotically achieve the global containment control of the network with any initial condition. Finally, numerical examples are given to illustrate the effectiveness of the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

A fuzzy evolutionary framework for combining ensembles

We propose an evolutionary framework for the production of fuzzy rule bases where each rule executes an ensemble of predictors. The architecture, the rule base and the composition of the ensembles are evolved over time. To achieve this, we employ a context-free grammar within a hybrid genetic programming system using a multi-population model. As base predictors, multilayer perceptron neural networks and support vector machines are available. We apply the system to several function approximation and regression tasks and compare the results with recent research and state-of-the-art models. We conclude that the proposed architecture is competitive and has a number of very desirable features supporting automation of predictive model building and their adaptation over time. Finally, we suggest further potential research directions.     

On the Modelling and Monitoring of General Inflated Poisson Processes

In this work, we propose and study general inflated probability distributions that can be used for modelling and monitoring unusual count data. The considered models extend the well‐known zero‐inflated Poisson distribution because they allow the excess of values, other than zero. Four simple upper‐sided control schemes are considered for the monitoring of count data based on the proposed general inflated Poisson distributions, and their performance is evaluated under various out‐of‐control situations. The usefulness of the considered models and techniques is illustrated via two real‐data examples, while practical guidelines are provided as well. Copyright © 2015 John Wiley & Sons, Ltd.     

Analysis and performance evaluation of a pilot-aided interpolated channel estimator for OFDM systems

In this paper, we propose a novel pilot-aided channel estimator through interpolation for Orthogonal Frequency Division Multiplexing (OFDM) systems that replaces part of the virtual subcarriers with pilot subcarriers (pilots) reducing the interpolation error while keeping the code rate stable. A novel thorough analysis of the Mean Square Error (MSE) of the proposed estimator is given for the general case where data subcarriers are positioned before the first and after the last pilot. Simulations show the improvement of the proposed scheme in MSE and Bit Error Rate (BER) when applied to a practical OFDM wireless local area network type of system with realistic channel conditions.     

Lossless fitness inheritance in genetic algorithms for decision trees

When genetic algorithms are used to evolve decision trees, key tree quality parameters can be recursively computed and re-used across generations of partially similar decision trees. Simply storing instance indices at leaves is sufficient for fitness to be piecewise computed in a lossless fashion. We show the derivation of the (substantial) expected speedup on two bounding case problems and trace the attractive property of lossless fitness inheritance to the divide-and-conquer nature of decision trees. The theoretical results are supported by experimental evidence.     

Towards an ICT-based psychology: E-psychology

Cognitive science is the scientific domain which studies, analyzes, simulates and infers for various aspects, functions and procedures of human mentality such as, thinking, logic, language, knowledge, memory, learning, perception and the ability to solve problems. E-psychology is in close relation with the cognitive science domain, but expands beyond it, as e-psychology is the efficient convergence of psychology and Information and Communication Technologies (ICTs). E-psychology offers a number of services such as supporting, diagnosis, assessment, therapy, counseling, intervention and tests through an effective exploitation of ICTs. This article presents a user-friendly, flexible and adaptive electronic platform, which supports both synchronous and asynchronous e-psychology activities through the use of informative and communicative tools and services, which can be adapted to support various methods of e-psychology activities. It is important to underline that e-psychology is not an alternative psychology field, but a resource to enhance the conventional psychology process.