Freeway travel time estimation and prediction using dynamic neural networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. ^ This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.^

Developing a high density platinum/alumina hermetic feedthrough

Typically, hermetic feedthroughs for implantable devices, such as pacemakers, use a alumina ceramic insulator brazed to a platinum wire pin. This combination of material has a long history in implantable devices and has been approved by the FDA for implantable hermetic feedthroughs. The growing demand for increased input/output (I/O) hermetic feedthroughs for implantable neural stimulator applications could be addressed by developing a new, cofired platinum/alumina multilayer ceramic technology in a configuration that supports 300 plus I/Os, which is not commercially available. Seven platinum powders with different particle sizes were used to develop different conductive cofire inks to control the densification mismatch between platinum and alumina. Firing profile (ramp rate, burn- out and holding times) and firing atmosphere and concentrations (hydrogen (wet/dry), air, neutral, vacuum) were also optimized. Platinum and alumina exhibit the alloy formation reaction in a reduced atmosphere. Formation of any compound can increase the bonding of the metal/ceramic interface, resulting in enhanced hermeticity. The feedthrough fabricated in a reduced atmosphere demonstrated significantly superior performance than that of other atmospheres. A composite structure of tungsten/platinum ratios graded thru the via structure (pure W, 50/50 W/Pt, 80/20 Pt/W and pure Pt) exhibited the best performance in comparison to the performance of other materials used for ink metallization. Studies on the high temperature reaction of platinum and alumina, previously unreported, showed that, at low temperatures in reduced atmosphere, Pt 3Al or Pt8Al21 with a tetragonal structure would be formed. Cubic Pt3Al is formed upon heating the sample to temperatures above 1350 °C. This cubic structure is the equilibrium state of Pt-Al alloy at high temperatures. The alumina dissolves into the platinum ink and is redeposited as a surface coating. This was observed on both cofired samples and pure platinum thin films coated on a 99.6 Wt% alumina and fired at 1550 °C. Different mechanisms are proposed to describe this behavior based on the size of the platinum particle

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

Desenvolvimento teórico e experimental de FSS com elementos fractais de Gosper em estruturas de multicamadas

The fractal self-similarity property is studied to develop frequency selective surfaces (FSS) with several rejection bands. Particularly, Gosper fractal curves are used to define the shapes of the FSS elements. Due to the difficulty of making the FSS element details, the analysis is developed for elements with up to three fractal levels. The simulation was carried out using Ansoft Designer software. For results validation, several FSS prototypes with fractal elements were fabricated. In the fabrication process, fractals elements were designed using computer aided design (CAD) tools. The prototypes were measured using a network analyzer (N3250A model, Agilent Technologies). Matlab software was used to generate compare measured and simulated results. The use of fractal elements in the FSS structures showed that the use of high fractal levels can reduce the size of the elements, at the same time as decreases the bandwidth. We also investigated the effect produced by cascading FSS structures. The considered cascaded structures are composed of two FSSs separated by a dielectric layer, which distance is varied to determine the effect produced on the bandwidth of the coupled geometry. Particularly, two FSS structures were coupled through dielectric layers of air and fiberglass. For comparison of results, we designed, fabricated and measured several prototypes of FSS on isolated and coupled structures. Agreement was observed between simulated and measured results. It was also observed that the use of cascaded FSS structures increases the FSSs bandwidths and, in particular cases, the number of resonant frequencies, in the considered frequency range. In future works, we will investigate the effects of using different types of fractal elements, in isolated, multilayer and coupled FSS structures for applications on planar filters, high-gain microstrip antennas and microwave absorbers

Produção e estudo de multicamadas magnéticas em substrato flexível

Magnetic multilayers are the support for the production of spintronic devices, representing great possibilities for miniaturized electronics industry. having the control to produce devices as well as their physical properties from simple multilayer films to highly complex at the atomic scale is a fundamental need for progress in this area, in recent years has highlighted the production of organic and flexible spintronic devices. Because of this trend, the objective of this work was to produce magnetic multilayers deposited on flexible substrate using magnetron sputtering dc technique. Three sets of samples were prepared. The first set composed of the trilayer type CoFe=Cu(t)=CoFe with different thickness of the metallic spacer. The second set consists of two multilayer subgroups, CoFe=Cu in the presence of IrMn layer as a buffer and the next multilayer as cap layer. The third set consisting of non-magnetostrictive multilayer permalloy (Py=Ta and Py=Ag) on flexible substrate and glass. The magnetic properties, were investigated by magnetometry measurements, ferromagnetic resonance and magnetoimpedance (MI), measurements were carried out at room temperature with the magnetic field always applied on the sample plane. For structural analysis, the diffraction X-ray was used. The results of the trilayer showed a high uniaxial anisotropy field for the sample with a spacer of 4.2 nm. For the multilayer in the presence of IrMn layer as the buffer, the study of static and dynamic magnetic properties showed isotropic behavior. For the multilayer in the presence of IrMn layer as a cap, the results of static magnetic properties of the magnetic behavior exhibited a spin valve structure type. However there was a disagreement with results of ferromagnetic resonance measurements, which was justified by the contribution of the unstable and stable grain to the rotatable anisotropy and Exchange bias in ferromagneticantiferromagnetic interface. The third serie of samples showed similar results behavior for the MI Ag multilayers spacer in both substrates. There are also significant MI changes with the Ta spacer, possible associated with the compressive stress on the flexible substrate sample.