Error modeling for an untethered ultra-wideband system for construction indoor asset tracking

This paper analyzes the performance of an ultra-wideband (UWB) wireless network system for mobile asset tracking at a dynamic construction site. Static and dynamic error tests were performed on a commercial UWB system in different building spaces including open/closed spaces, steel/wood framed construction sites, and a closed office area. All tests were carried out with an untethered UWB configuration for more flexible deployment of the UWB system at construction sites. Statistical approaches including regression analysis, outlier detection, and Kalman filtering were used to build an error model. The research found that each site has a unique pattern of producing errors caused by various types of interference, e.g., electromagnetic interference, multi-path propagation, fading and scattering of signals. Approximately 25% of the errors were reduced by using the proposed error modeling process. The paper concludes that a statistically developed error model process can significantly reduce random errors and improve position accuracy for indoor mobile asset tracking applications in construction.     

Stress–strain relationship in axial compression for concrete using recycled saturated coarse aggregate

In this work the stress–strain curve of the recycled concretes was determined by replacing different percentages of the natural coarse aggregate with recycled coarse aggregate (20%, 50% and 100%). The results made it possible to establish the differences between the stress–strain relationship of a conventional concrete and this relationship for a recycled concrete depending on the percentage of replacement. In this way, it was found that the longitudinal strain of the recycled concretes increases with the percentage of recycled coarse aggregate used.Finally, using the experimental results, an analytical expression of the stress–strain curve accounting for the percentage of replacement was developed. The verification of the proposed model equation was done by comparing it to the experimental data. The results show that the proposed model equation satisfactorily describes the effect of the recycled aggregate on the stress–strain curve.     

Anisotropy of point defect diffusion in alpha-zirconium

Two types of intrinsic defect, i.e., vacancy and self-interstitial atom (SIA), are formed in metals during irradiation with energetic particles. The evolution of defect population leads to significant changes in microstructure and causes a number of radiation-induced property changes. Some phenomena, such as radiation growth of anisotropic materials, are due to anisotropy in the atomic mass transport by point defects. Detailed information on atomic-scale mechanisms is, therefore, necessary to understand such phenomena. In this article, we present results of a computer simulation study of mass transport via point defects in alpha-zirconium. The matrix of self-diffusion coefficients and activation energies for vacancy and SIA defects have been obtained, and different methods of treatment of diffusion have been tested. Molecular dynamics (MD) shows that vacancy diffusion is approximately isotropic in the temperature range studied (1050 to 1650 K), although some preference for basalplane diffusion was observed at the lower end of the range. The mechanism of interstitial diffusion changes from one-dimensional (1-D) in a 〈11 0〉 direction at low temperature (<300 K) to two-dimensional (2-D) in the basal plane and, then, three-dimensional (3-D) at higher temperatures. This article is based on a presentation made in the symposium entitled “Defect Properties and Mechanical Behavior of HCP Metals and Alloys” at the TMS Annual Meeting, February 11–15, 2001, in New Orleans, Louisiana, under the auspices of the following ASM committees: Materials Science Critical Technology Sector, Structural Materials Division, Electronic, Magnetic & Photonic Materials Division, Chemistry & Physics of Materials Committee, Joint Nuclear Materials Committee, and Titanium Committee.     

Anisotropy of point defect diffusion in alpha-zirconium

Two types of intrinsic defect, i.e., vacancy and self-interstitial atom (SIA), are formed in metals during irradiation with energetic particles. The evolution of defect population leads to significant changes in microstructure and causes a number of radiation-induced property changes. Some phenomena, such as radiation growth of anisotropic materials, are due to anisotropy in the atomic mass transport by point defects. Detailed information on atomic-scale mechanisms is, therefore, necessary to understand such phenomena. In this article, we present results of a computer simulation study of mass transport via point defects in alpha-zirconium. The matrix of self-diffusion coefficients and activation energies for vacancy and SIA defects have been obtained, and different methods of treatment of diffusion have been tested. Molecular dynamics (MD) shows that vacancy diffusion is approximately isotropic in the temperature range studied (1050 to 1650 K), although some preference for basal-plane diffusion was observed at the lower end of the range. The mechanism of interstitial diffusion changes from one-dimensional (1-D) in a direction at low temperature (<300 K) to two-dimensional (2-D) in the basal plane and, then, three-dimensional (3-D) at higher temperatures. This article is based on a presentation made in the symposium entitled “Defect Properties and Mechanical Behavior of HCP Metals and Alloys” at the TMS Annual Meeting, February 11–15, 2001, in New Orleans, Louisiana, under the auspices of the following ASM committees: Materials Science Critical Technology Sector, Structural Materials Division, Electronic, Magnetic & Photonic Materials Division, Chemistry & Physics of Materials Committee, Joint Nuclear Materials Committee, and Titanium Committee.     

Simulation of atmospheric phenomena

This paper presents a physically based simulation of atmospheric phenomena. It takes into account the physics of non-homogeneous media in which the index of refraction varies continuously, creating curved light paths. As opposed to previous research on this area, we solve the physically based differential equation that describes the trajectory of light. We develop an accurate expression of the index of refraction in the atmosphere as a function of wavelength, based on real measured data. We also describe our atmosphere profile manager, which lets us mimic the initial conditions of real-world scenes for our simulations. The method is validated both visually (by comparing the images with the real pictures) and numerically (with the extensive literature from other areas of research such as optics or meteorology). The phenomena simulated include the inferior and superior mirages, the Fata Morgana, the Novaya–Zemlya, the Viking's end of the world, the distortions caused by heat waves and the green flash.     

A speed and accuracy test of backpropagation and RBF neural networks for small-signal models of active devices

Backpropagation networks are compared to radial basis function (RBF) networks when it comes to small signal modeling RF/microwave active devices. The modeled device is a 4×50 μm gate width, 0.25 μm gate length gallium arsenide (GaAs) Metal semiconductor field-effect transistor (MESFET). It is the authors’ intent to prove that RBF networks provide much better performance than backpropagation when it comes to this type of modeling. First, two separate backpropagation networks are created to determine the best training algorithm in terms of convergence speed. Then, the backpropagation network, using its best training algorithm, is compared to the RBF network in terms of speed and accuracy. Simulation results are presented in tables and figures for better understanding. All tests and simulations for the backpropagation and RBF networks are done using Matlab's Neural Network Toolbox.     

Parameter bounds evaluation of Wiener models with noninvertible polynomial nonlinearities

In this paper a three stage procedure is presented for deriving parameters bounds of SISO Wiener models when the nonlinear block is modeled by a possibly noninvertible polynomial and the output measurement errors are bounded. First, using steady-state input-output data, parameters of the nonlinear part are bounded by a tight orthotope. Then, given the estimated uncertain nonlinearity and the output measurements collected exciting the system with an input dynamic signal, bounds on the unmeasurable inner signal are computed. Finally, such bounds, together with noisy output measurements, are used for bounding the parameters of the linear block.     

Using <Superscript>1</Superscript>H and <Superscript>13</Superscript>C NMR techniques and artificial neural networks to detect the adulteration of olive oil with hazelnut oil

The lack of any official analytical method to detect the adulteration of olive oil with a low percentage of hazelnut oil is explained by the similarities in the chemical compositions of both kinds of oils. To counter this problem, an artificial neural network based on ¹H-NMR and ¹³C-NMR data has been developed to detect olive oil adulteration, and the results from this ANN are presented here. A training set consisting of hazelnut oils, pure olive oils, and olive oils blended with 2–20% hazelnut oils was used to design and train a multilayer perceptron with 100% correct classifications. This mathematical model was also validated using an external validation set of blend samples (3–15%) and genuine samples. The detection limit of the model was around 8%.     

Metal oxide-based monolithic complementary metal oxide semiconductor gas sensor microsystem

A fully integrated gas sensor microsystem is presented, which comprises for the first time a micro hot plate as well as advanced analog and digital circuitry on a single chip. The micro hot plate is coated with a nanocrystalline SnO2 thick film. The sensor chip is produced in an industrial 0.8-microm CMOS process with subsequent micromachining steps. A novel circular micro hot plate, which is 500 x 500 microm(2) in size, features an excellent temperature homogeneity of +/-2% over the heated area (300-microm diameter) and a high thermal efficiency of 6.0 degrees C/mW. A robust prototype package was developed, which relies on standard microelectronic packaging methods. Apart from a microcontroller board for managing chip communication and providing power supply and reference signals, no additional measurement equipment is needed. The on-chip digital temperature controller can accurately adjust the membrane temperature between 170 and 300 degrees C with an error of +/-2 degrees C. The on-chip logarithmic converter covers a wide measurement range between 1 kOmega and 10 MOmega. CO concentrations in the sub-parts-per-million range are detectable, and a resolution of +/-0.1 ppm CO was achieved, which renders the sensor capable of measuring CO concentrations at threshold levels.