Electrical properties and chemical compatibility of PZT thick film on Ni substrates

The characteristics of Pb(Zr,Ti)O₃(PZT) thick films that were printed and fired on Ni substrates were studied. The dielectric characteristics of samples sintered at 850°C on Ni substrates could not be measured due to the formation of a NiO layer at the Ni/PZT interface. The scanning electron microscope and energy dispersive X-ray analysis of cross-sections of the PZT thick films on Ni substrates, and of a mixture of PZT and NiO powders, fired at 850°C, did not indicate the formation of secondary phases. However, the transmission electron microscopy showed around 8% solid solubility of NiO in the PZT. A new structure with a prefired, Au thick-film layer was designed in order to prevent the diffusion of the NiO to the PZT layer during sintering. The dielectric properties of the PZT layers printed and fired on the Ni substrates with the prefired Au electrode were significantly better than those of the layers on the uncoated substrate, the dielectric losses decreased from 0.23 to 0.05.     

Compact spot-size converters with fiber-matched antiresonant reflecting optical waveguides

We propose a concept for InGaAsP-InP 1.55-microm lasers integrated with spot-size converters based on modal interference between the modes of the structure formed by an active waveguide and an underlying fiber-matched antiresonant reflecting optical waveguide. Simulation results show that the spot-size converters exhibit low transformation loss, and narrowed far-field emission patterns (10 degrees x 20 degrees) and reduce the coupling loss to standard single-mode fibers from 8 to 2.6 dB over lengths approximately 200 microm shorter than the adiabatic concept. A tolerant design to fabrication variations is also proposed, which could be realized by standard processing techniques.     

A characterisation of thick film resistors for strain gauge applications

Some commercial thick film resistors with sheet resistivities from 1 kohm/sq. up to 1 Mohm/sq. were evaluated for strain gauge applications. Temperature coefficients of resistivity, noise indices and gauge factors (GFs) were measured. For the same resistor series GFs and noise indices increase with increasing sheet resistivity. However, both GFs and noise indices are different for resistors with the same nominal sheet resistivity but from different resistor series. The results indicated that the microstructure rather than the different chemical composition of the conductive phase in thick film resistors is the primary reason for the different gauge factors.     

Usability evaluation of anti-phishing toolbars

Phishing is considered as one of the most serious threats for the Internet and e-commerce. Phishing attacks abuse trust with the help of deceptive e-mails, fraudulent web sites and malware. In order to prevent phishing attacks some organizations have implemented Internet browser toolbars for identifying deceptive activities. However, the levels of usability and user interfaces are varying. Some of the toolbars have obvious usability problems, which can affect the performance of these toolbars ultimately. For the sake of future improvement, usability evaluation is indispensable. We will discuss usability of five typical anti-phishing toolbars: built-in phishing prevention in the Internet Explorer 7.0, Google toolbar, Netcraft Anti-phishing toolbar and SpoofGuard. In addition, we included Internet Explorer plug-in we have developed, Anti-phishing IEPlug. Our hypothesis was that usability of anti-phishing toolbars, and as a consequence also security of the toolbars, could be improved. Indeed, according to the heuristic usability evaluation, a number of usability issues were found. In this article, we will describe the anti-phishing toolbars, we will discuss anti-phishing toolbar usability evaluation approach and we will present our findings. Finally, we will propose advices for improving usability of anti-phishing toolbars, including three key components of anti-phishing client side applications (main user interface, critical warnings and the help system). For example, we found that in the main user interface it is important to keep the user informed and organize settings accordingly to a proper usability design. In addition, all the critical warnings an anti-phishing toolbar shows should be well designed. Furthermore, we found that the help system should be built to assist users to learn about phishing prevention as well as how to identify fraud attempts by themselves. One result of our research is also a classification of anti-phishing toolbar applications. Linfeng Li is a student at the University of Tampere, Finland. Marko Helenius is Assistant Professor at the Department of Computer Sciences, University of Tampere, Finland.     

Thermal Annealing and Propagation of Shockley Stacking Faults in 4H-SiC PiN Diodes

Stacking faults within 4H-SiC PiN diodes are known to be detrimental to device operation. Here, we present electroluminescence (EL) images of 4H-SiC PiN diodes providing evidence that electrically and optically stimulated Shockley stacking fault (SSF) propagation is a reversible process at temperatures as low as 210°C. Optical beam induced current (OBIC) images taken following complete optical stressing of a PiN diode and that lead to a small number of completely propagated SSFs provide evidence that such defects propagate across the n–/p+ interface and continue to grow throughout the p+ layer. These observations bring about questions regarding the validity of the currently accepted driving force mechanism for SSF propagation.     

Accelerated testing of on‐board diagnostics

Modern products frequently feature monitors designed to detect actual or impending malfunctions. False alarms (Type I errors) or excessive delays in detecting real malfunctions (Type II errors) can seriously reduce monitor utility. Sound engineering practice includes physical evaluation of error rates. Type II error rates are relatively easy to evaluate empirically. However, adequate evaluation of a low Type I error rate is difficult without using accelerated testing concepts, inducing false alarms using artificially low thresholds and then selecting production thresholds by appropriate extrapolation, as outlined here. This acceleration methodology allows for informed determination of detection thresholds and confidence in monitor performance with substantial reductions over current alternatives in time and cost required for monitor development. Copyright © 2006 John Wiley & Sons, Ltd.     

NICE h : a higher-order explicit numerical scheme for integration of constitutive models in plasticity

The article introduces, as a result of further development of the first-order scheme NICE, a simple and efficient higher-order explicit numerical scheme for the integration of a system of ordinary differential equations which is constrained by an algebraic condition (DAE). The scheme is based on the truncated Taylor expansion of the constraint equation with order h of the scheme being determined by the highest exponent in the truncated Taylor series. The integration scheme thus conceived will be named NICE ^h , considering both principal premises of its construction. In conjunction with a direct solution technique used to solve the boundary value problem, the NICE ^h scheme is very convenient for integrating constitutive models in plasticity. The plasticity models are defined mostly by a system of algebraic and differential equations in which the yield criterion represents the constraint condition. To study the properties of the new integration scheme, which, like the forward-Euler scheme, is characterised by its implementation simplicity due to the explicitness of its formulations, a damage constitutive model (Gurson–Tvergaard–Needleman model) is considered. The general opinion that the implicit backward-Euler scheme is much more accurate than the thus-far known explicit schemes is challenged by the introduction of the NICE ^h scheme. The accuracy of the higher-order explicit scheme in the studied cases is significantly higher than the accuracy of the classical backward-Euler scheme, if we compare them under the condition of a similar CPU time consumption.     

Adaptive atomic capture of multiple molecules

Facing the scale, heterogeneity and dynamics of the global computing platform emerging on top of the Internet, autonomic computing has been raised recently as one of the top challenges of computer science research. Such a paradigm calls for alternative programming abstractions, able to express autonomic behaviours. In this quest, nature-inspired analogies regained a lot of interest. More specifically, the chemical programming paradigm, which envisions a program’s execution as a succession of reactions between molecules representing data to produce a result, has been shown to provide some adequate abstractions for the high-level specification of autonomic systems.     

Neural network Reinforcement Learning for visual control of robot manipulators

It is known that most of the key problems in visual servo control of robots are related to the performance analysis of the system considering measurement and modeling errors. In this paper, the development and performance evaluation of a novel intelligent visual servo controller for a robot manipulator using neural network Reinforcement Learning is presented. By implementing machine learning techniques into the vision based control scheme, the robot is enabled to improve its performance online and to adapt to the changing conditions in the environment. Two different temporal difference algorithms (Q-learning and SARSA) coupled with neural networks are developed and tested through different visual control scenarios. A database of representative learning samples is employed so as to speed up the convergence of the neural network and real-time learning of robot behavior. Moreover, the visual servoing task is divided into two steps in order to ensure the visibility of the features: in the first step centering behavior of the robot is conducted using neural network Reinforcement Learning controller, while the second step involves switching control between the traditional Image Based Visual Servoing and the neural network Reinforcement Learning for enabling approaching behavior of the manipulator. The correction in robot motion is achieved with the definition of the areas of interest for the image features independently in both control steps. Various simulations are developed in order to present the robustness of the developed system regarding calibration error, modeling error, and image noise. In addition, a comparison with the traditional Image Based Visual Servoing is presented. Real world experiments on a robot manipulator with the low cost vision system demonstrate the effectiveness of the proposed approach.