Autocalibration with the Minimum Number of Cameras with Known Pixel Shape

In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction of a rigid scene, we address the problem of the autocalibration of a minimal set of cameras with known pixel shape and otherwise arbitrarily varying intrinsic and extrinsic parameters. We propose an algorithm that only requires 5 cameras (the theoretical minimum), thus halving the number of cameras required by previous algorithms based on the same constraint. To this purpose, we introduce as our basic geometric tool the six-line conic variety (SLCV), consisting in the set of planes intersecting six given lines of 3D space in points of a conic. We show that the set of solutions of the Euclidean upgrading problem for three cameras with known pixel shape can be parameterized in a computationally efficient way. This parameterization is then used to solve autocalibration from five or more cameras, reducing the three-dimensional search space to a two-dimensional one. We provide experiments with real images showing the good performance of the technique.     

Silphinene Sesquiterpenes as Model Insect Antifeedants

Silphinene sesquiterpenes are established chrysomelid antifeedants. In this work, nine silphinene analogs, 11-acetoxy-5-angeloyloxysilphinen-3-one (1), 11-acetoxy-5-tigloyloxysilphinen-3-one (2), 11-acetoxy-5-iso- butyryloxysilphinen-3-one (3), 11-hydroxy-5-angeloyloxysilphinen-3-one (4), 11,5-dihydroxysilphinen-3-one (5), 11,5-diacetoxysilphinen-3-one (6), 5,11-diisobutyryloxysilphinen-3-one (7), silphinen-3,5,11-trione (8), and O-methyl-5-epicantabrenolic acid methyl ester (10), and a presilphiperfolane sesquiterpene (9) were tested against several divergent insect species, including the lepidopteran Spodoptera littoralis, the chrysomelid Leptinotarsa decemlineata, and five aphid species, and their antifeedant effects were compared with those of picrotoxinin, a GABA-antagonist, and thymol, an allosteric modulator for insect GABA receptors. All insects tested responded to at least one silphinene analog and/or GABA antagonist. Compound 3 and thymol were effective antifeedants against all species tested except S. littoralis, with varying potencies according to their feeding ecologies. The toxicity of these compounds was species-dependent and did not correlate with their antifeedant effect.     

Synthesis,characterization, and chelating properties of the polymacromonomer: Poly[(ethyleneglycol) methyl ether methacrylate]

The radical polymerization of the macromonomer poly(ethyleneglycol) methyl ether methacrylate with ammonium persulfate at 60°C was carried out. The polymer was completely soluble in water. Yield was 75%. The polymacromonomer was characterized by Fourier transform infrared, proton nuclear magnetic resonance (NMR), and ¹³C NMR spectroscopy. M_n, M_w, and the polydispersity were determined by gel permeation chromatography. The polymacromonomer showed a high thermal stability with a TDT_50% of 420°C. The metal ion binding capacity of this polychelatogen with respect to different metal ions was investigated through the liquid‐phase polymer‐based retention (LPR) technique. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2929–2934, 2002     

Eicosapentaenoic acid (20∶5n-3) from the marine microalgaPhaeodactylum tricornutum

Eicosapentaenoic acid (EPA, 20∶5n-3) was obtained from the marine microalgaePhaeodactylum tricornutum by a three-step process: fatty acid extraction by direct saponification of biomass, polyunsaturated fatty acid (PUFA) concentration by formation of urea inclusion compounds, and EPA isolation by semipreparative high-performance liquid chromatography (HPLC). Alternatively, EPA was obtained by a similar two-step process without the PUFA concentration step by the urea method. Direct saponification of biomass was carried out with two solvents that contained KOH for lipid saponification. An increase in yield was obtained because the problems associated with emulsion formation were avoided by separating the biomass from the soap solution before adding hexane for extraction of insaponifiables. The most efficient solvent, ethanol (96%) at 60°C for 1 h, extracted 98.3% of EPA. PUFA were concentrated by the urea method with a urea/fatty acid ratio of 4∶1 at a crystallization temperature of 28°C and by using methanol and ethanol as urea solvents. An EPA concentration ratio of 1.73 (55.2∶31.9) and a recover yield of 78.6% were obtained with methanol as the urea solvent. This PUFA concentrate was used to obtain 93.4% pure EPA by semipreparative HPLC with a reverse-phase, C₁₈, 10 mm i.d.×25-cm column and methanol/water (1% acetic acid), 80∶20 w/w, as the mobile phase. Eighty-five percent of EPA loaded was recovered, and 65.7% of EPA present inP. tricornutum biomass was recovered in highly pure form by this three-step downstream process. Alternatively, 93.6% pure EPA was isolated from the fatty acid extract (without the PUFA concentration step) with 100% EPA recovery yield. This two-step process increases the overall EPA yield to 98.3%, but it is only possible to obtain 20% as much EPA as that obtained by three-step downstream processing.     

Effect of low‐temperature plasma and chitosan treatment on wool dyeing with Acid Red 27

This study examines in detail the influence of low‐temperature plasma and biopolymer chitosan treatments on wool dyeability. Wool knitted fabrics were treated and characterized by whiteness and shrink‐resistance measurements. Surface modification was assessed by contact‐angle measurements of human hair fibers, which were used as a model to study the wetting properties of the treated wool knitted fabrics. The dyeing behavior was assessed from the diffusion mechanism point of view. The dyeing kinetics were measured at two different pHs (4.2 and 6.5) and three different temperatures (60, 85, and 100°C) to gain information about the contribution of the surface modification treatment to the dyeing mechanism. The exhaustion and reflectance data were compared, and the apparent diffusion coefficients were calculated. On the basis of the obtained results, a model for the dyeing mechanism of the chitosan treated wool was proposed. When treated with chitosan, the polymer sheath spread on the surface of the fibers acted as a predominant dyeing site in very short dyeing times, thus interacting with the dye and in later stages imparting the dye to the wool fiber. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 2204–2214, 2005     

Preconditioning the solution of the time-dependent neutron diffusion equation by recycling Krylov subspaces

Spectral preconditioners are based on the fact that the convergence rate of the Krylov subspace methods is improved if the eigenvalues of the smallest magnitude of the system matrix are ‘removed’. In this paper, two preconditioning strategies are studied to solve a set of linear systems associated with the numerical integration of the time-dependent neutron diffusion equation. Both strategies can be implemented using the matrix–vector product as the main operation and succeed at reducing the total number of iterations needed to solve the set of systems.     

Straightforward modeling of dynamic I–V characteristics for microwave FETs

This work presents a straightforward approach aimed at modeling the dynamic I–V characteristics of microwave active solid‐state devices. The drain‐source current generator represents the most significant source of nonlinearity in a transistor and, therefore, its correct modeling is fundamental to predict accurately the current and voltage waveforms under large‐signal operation. The proposed approach relies on using a small set of low‐frequency time‐domain waveform measurements combined with numerical optimization‐based estimation of the nonlinear model parameters. The procedure is applied to a gallium nitride HEMT and silicon FinFET. The effectiveness of the modeling procedure in terms of prediction accuracy and generalization capability is demonstrated by validation of the extracted models under operating conditions different than the ones used for the parameters estimation. Good agreement between measurements and model simulations is achieved for both technologies and in both low‐ and high‐frequency range. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:109–116, 2014.     

Smoothing: A natural way to detect contour features

This work presents a dominant point detector. The angles of the contour are characterized through local entropy produced by a rotationally symmetric smoothing. The proposed scheme uses a punctual multi-scale approach in which only the candidates are analyzed in higher scales. To preserve the angle-entropy relationship in higher scales, we propose a smoothing kernel which presents special features that ensure its steepness in every scale. It is built from the sum of two Gaussians with different openings resembling center-surround receptive fields. The outputs of the proposed method are confronted to a ground-truth found in the literature, and to popular boundary based corner detectors that used the same set of images. Results reveal that the proposed detector performs extremely well.     

Binary and m-ary encoding in applications of tree-based genetic algorithms for QoS routing

Ubiquitous and Pervasive Computing (UPC) applications often have Quality of Service (QoS) requirements. These become constraints for the UPC network infrastructure. In this paper, we refer to Mobile ad Hoc Networks, one of the most important technologies supporting UPC, and investigate on Genetic Algorithms (GAs) for QoS routing. GAs are part of the soft computing paradigm and can solve the NP search of QoS routes with multiple constraints. We elaborate on tree-based GAs, which represent the set of paths from source to destination as a tree and encode them through the crossed junctions. While their most well-known applications use m-ary encoding representing single paths in the chromosomes, in this paper we discuss a binary encoding with the objective of improving the convergence speed. The binary encoding represents classes of paths in the chromosomes and allows local search on classes of paths. These classes are both collectively exhaustive and mutually exclusive. Simulation results compare convergence speed and scalability of GA applications with binary and m-ary encoding in networks with an increasing number of nodes and links per node. As the per-class processing is reason of additional computational cost, an hybrid GA application that uses both binary and m-ary encoding is introduced.     

Mobile digcovery: discovering and interacting with the world through the Internet of things

The application of Internet-enabled devices in the real world for the development of Smart Cities, environmental monitoring, bus tracking, and parking requires scalability, extensibility, and integration of emerging resources to reach a suitable ecosystem for data acquisition and interaction with citizens. Internet of things needs to offer efficient support for global communications and access to services and information. It needs to enable homogeneous and seamless machine-to-machine communication for different solutions and applications. This work presents an homogeneous and suitable mechanism for global resource discovery, device access for deployed smart objects in different scenarios, and sensors and devices from end users (participative sensing). The integration of legacy and sensors already available from smart buildings and smart objects is presented. For this purpose, a resolution infrastructure called “digcovery” is defined for maximizing efficiency and sustainability of deployments. Digcovery architecture offers the framework to allow users to register/include their own sensors into a common infrastructure and access/discover the available resources through mobile digcovery. Mobile digcovery exploits the context-awareness, geo-location, and identification technologies available in mobile platforms such as smartphones to discover, interact, and access the resources through its ElasticSearch engine.