Guidance of a mobile robot using an array of static cameras located in the environment

This paper presents a new proposal for positioning and guiding mobile robots in indoor environments. The proposal is based on the information provided by static cameras located in the movement environment. This proposal falls within the scope of what are known as intelligent environments; in this case, the environment is provided with cameras that, once calibrated, allow the position of the robots to be obtained. Based on this information, control orders for the robots can be generated using a radio frequency link. In order to facilitate identification of the robots, even under extremely adverse ambient lighting conditions, a beacon consisting of four circular elements constructed from infrared diodes is mounted on board the robots. In order to identify the beacon, an edge detection process is carried out. This is followed by a process that, based on the algebraic distance, obtains the estimated ellipses associated with each element of the beacon. Once the beacon has been identified, the coordinates of the centroids for the elements that make up the beacon are obtained on the various image planes. Based on these coordinates, an algorithm is proposed that takes into account the standard deviation of the error produced in the various cameras in ascertaining the coordinates of the beacon’s elements. An odometric system is also used in guidance that, in conjunction with a Kalman Filter, allows the position of the robot to be estimated during the time intervals required to process the visual information provided by the cameras.

Preoperative selection for curable renovascular hypertension

Clinical research has defined the criteria for identifying "curable" renovascular hypertension. The prediction is based on the measurement of plasma renin activity in peripheral veins, renal veins, and the aorta. Renin profiles can be examined with the method of Laragh and coworkers (the so-called incremental method), in which values for plasma renin activity are incorporated into formulas to compute indexed parameters. A score is attributed to each index and the prediction is based on the final score. Because the identification of curable renovascular hypertension is made according to numerical rules, the method is easily transformed into a computer-assisted process. The program is written in BASIC, and it is short enough to run on a personal computer.     

Exploring different technological platforms for supporting co-located collaborative games in the classroom

Computer Supported Collaborative Learning is a pedagogical approach that can be used for deploying educational games in the classroom. However, there is no clear understanding as to which technological platforms are better suited for deploying co-located collaborative games, nor the general affordances that are required. In this work we explore two different technological platforms for developing collaborative games in the classroom: one based on augmented reality technology and the other based on multiple-mice technology. In both cases, the same game was introduced to teach electrostatics and the results were compared experimentally using a real class.     

Multi‐objective optimization using metaheuristics: non‐standard algorithms

In recent years, the application of metaheuristic techniques to solve multi‐objective optimization problems has become an active research area. Solving this kind of problems involves obtaining a set of Pareto‐optimal solutions in such a way that the corresponding Pareto front fulfils the requirements of convergence to the true Pareto front and uniform diversity. Most of the studies on metaheuristics for multi‐objective optimization are focused on Evolutionary Algorithms, and some of the state‐of‐the‐art techniques belong this class of algorithms. Our goal in this paper is to study open research lines related to metaheuristics but focusing on less explored areas to provide new perspectives to those researchers interested in multi‐objective optimization. In particular, we focus on non‐evolutionary metaheuristics, hybrid multi‐objective metaheuristics, parallel multi‐objective optimization and multi‐objective optimization under uncertainty. We analyze these issues and discuss open research lines.     

Characterization of nickel-bearing ferrites obtained as by-products of hydrochemical wastewater purification processes

The efficiency of the ‘ferrite process’ for the purification of wastewater heavily contaminated with nickel is evaluated, and the solid residues formed are characterised. The efficiency of the purification process is always above 99.9% for Fe²⁺/Ni²⁺ ratios greater than 3. The tested Fe²⁺/Ni²⁺ molar ratios (15/1, 7/1 and 3/1) yielded three different nickel ferrites. Inductively-coupled plasma atomic emission spectroscopy (ICP-AES), potentiometric titration, X-ray fluorescence (XRF), X-ray diffractometry (XRD) and differential scanning calorimetry (DSC) yielded Ni_xFe_1−x^IIFe₂^IIIO₄ (x=0.18, 0.40 and 0.65, respectively) as the most probable stoichiometry, and inverse spinel as the most probable structure. Heating at 600 °C causes the transformation of the solids into a mixture of NiFe₂O₄, α-Fe₂O₃ and NiO. Electrochemical analysis of the solid nickel ferrites was performed using carbon paste electrodes (CPEs) in HClO₄ and HCl media. In each case, the first cyclic voltammogram showed the participation of solid species in the electrochemical transformation process, since the shape of the redox peaks could be related to the structure and stoichiometry of the ferrites. In second and successive scans, the voltammograms indicated the redox couples Fe_ads³⁺+1e⁻⇔Fe_ads²⁺ (0.525 V vs. Ag/AgCl) and Ni_ads²⁺+2e⁻⇔Ni(s) (−0.470 V) in HClO₄, and FeCl_2,ads⁺+1e⁻⇔FeCl_ads⁺+Cl⁻ (0.475 V) and NiCl_x,ads^(x−2)−+2e⁻⇔Ni(s)+xCl⁻ (−0.550 V) in HCl.     

Interactive structural learning of Bayesian networks

We propose an hybrid approach for structure learning of Bayesian networks, in which a computer system and a human expert cooperate to search for the best structure. The system builds an initial tree structure which is graphically presented to the expert, and then the expert can modify this structure according to his knowledge of the domain. The system has several tools for aiding the human in this task: it allows for graphical editing (adding, deleting, inverting arcs) of the network, it shows graphically the correlation between variables, and it gives a measure of the quality and complexity for each structure. A measure which combines both quality and complexity, that we call quality, is defined. We have tested the tool in two domains: atmospheric pollution and car insurance, with good results.     

Direct-EI in LC-MS: towards a universal detector for small-molecule applications

This review article will give an up-to-date and exhaustive overview on the efficient use of electron ionization (EI) to couple liquid chromatography and mass spectrometry (LC-MS) with an innovative interface called Direct-EI. EI is based on the gas-phase ionization of the analytes, and it is suitable for many applications in a wide range of LC-amenable compounds. In addition, thanks to its operating principles, it prevents unwelcome matrix effects (ME). In fact, although atmospheric pressure ionization (API) methodologies have boosted the use of LC-MS, the related analytical methods are sometime affected by inaccurate quantitative results, due to unavoidable and unpredictable ME. In addition, API's soft ionization spectra always demand for costly and complex tandem mass spectrometry (MS/MS) instruments, which are essential to acquire an "information-rich" spectrum and to obtain accurate quantitative information. In EI a one-stage analyzer is sufficient for a qualitative investigation and MS/MS detection is only used to improve sensitivity and to cut chemical noise. The technology illustrated here provides a robust and straightforward access to classical, well-characterized EI data for a variety of LC applications, and readily interpretable spectra for a wide range of areas of research. The Direct-EI interface can represent the basis for a forthcoming universal LC-MS detector for small molecules.     

Dealing with hardware heterogeneity: a new parallel search model

In this article we present Ethane, a parallel heterogeneous metaheuristic model specifically designed for its execution on heterogeneous hardware environments. With Ethane we propose a hybrid parallel search algorithm inspired in the structure of the chemical compound of the same name, implementing a heterogeneous island model based in the structure of the chemical bonds of the ethane compound. Here we also shape a schema for describing a complete family of parallel heterogeneous metaheuristics inspired by the structure of hydrocarbons in nature, HydroCM (HydroCarbon inspired Metaheuristics), establishing a resemblance between atoms and computers, and between chemical bonds and communication links. Our goal is to gracefully match computers of different computing power to algorithms of different behavior (genetic algorithm and simulated annealing in this study), all them collaborating to solve the same problem. In addition to the nice natural metaphor we will show that Ethane, though simple, can solve search problems in a faster and more robust way than well-known panmictic and distributed algorithms very popular in the literature, as well as can achieve a better exploration/exploitation balance during the search process.