74 resultados para Artificial satellites, American


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The trapped magnetic field is examined in bulk high-temperature superconductors that are artificially drilled along their c-axis. The influence of the hole pattern on the magnetization is studied and compared by means of numerical models and Hall probe mapping techniques. To this aim, we consider two bulk YBCO samples with a rectangular cross-section that are drilled each by six holes arranged either on a rectangular lattice (sample I) or on a centered rectangular lattice (sample II). For the numerical analysis, three different models are considered for calculating the trapped flux: (i), a two-dimensional (2D) Bean model neglecting demagnetizing effects and flux creep, (ii), a 2D finite-element model neglecting demagnetizing effects but incorporating magnetic relaxation in the form of an E-J power law, and, (iii), a 3D finite element analysis that takes into account both the finite height of the sample and flux creep effects. For the experimental analysis, the trapped magnetic flux density is measured above the sample surface by Hall probe mapping performed before and after the drilling process. The maximum trapped flux density in the drilled samples is found to be smaller than that in the plain samples. The smallest magnetization drop is found for sample II, with the centered rectangular lattice. This result is confirmed by the numerical models. In each sample, the relative drops that are calculated independently with the three different models are in good agreement. As observed experimentally, the magnetization drop calculated in the sample II is the smallest one and its relative value is comparable to the measured one. By contrast, the measured magnetization drop in sample (1) is much larger than that predicted by the simulations, most likely because of a change of the microstructure during the drilling process.

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The paper describes a new approach to artificial intelligence (AI) and its role in design. This approach argues that AI can be seen as 'text', or in other words as a medium for the communication of design knowledge and information between designers. This paper will apply these ideas to reinterpreting an existing knowledge-based system (KBS) design tool, that is, CADET - a product design evaluation tool. The paper will discuss the authorial issues, amongst others, involved in the development of AI and KBS design tools by adopting this new approach. Consequently, the designers' rights and responsibilities will be better understood as the knowledge medium, through its concern with authorship, returns control to users rather than attributing the system with agent status. © 1998 Elsevier Science Ltd. All rights reserved.

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Shearing rate is among the most important factors affecting the undrained shear strength of clays. In particular, for seismic or storm-wave loading conditions, the shearing rate is much higher than that used in many common laboratory or field tests. The testing program described here evaluates the effect of peripheral velocity on the undrained strength inferred from the shear vane test. The study was conducted on a lightly cemented bentonite-kaolinite mixture manufactured in the laboratory, which possesses many characteristics similar to those of natural materials. Results show that the shear strength increases with increasing peripheral velocity, while the residual shear strength seems to be nearly independent of rotation rate.

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We study magnetic artificial flagella whose swimming speed and direction can be controlled using light and magnetic field as external triggers. The dependence of the swimming velocity on the system parameters (e.g., length, stiffness, fluid viscosity, and magnetic field) is explored using a computational framework in which the magnetostatic, fluid dynamic, and solid mechanics equations are solved simultaneously. A dimensionless analysis is carried out to obtain an optimal combination of system parameters for which the swimming velocity is maximal. The swimming direction reversal is addressed by incorporating photoresponsive materials, which in the photoactuated state can mimic natural mastigonemes.

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Factors that affect the engineering properties of cement stabilized soils such as strength are discussed in this paper using data on these factors. The selected factors studied in this paper are initial soil water content, grain size distribution, organic matter content, binder dosage, age and curing temperature, which has been collated from a number of international deep mixing projects. Some resulting correlations from this data are discussed and presented. The concept of Artificial Neural Networks and its applicability in developing predictive models for deep mixed soils is presented and discussed using a subset of the collated data. The results from the neural network model were found to emulate the known trends and reasonable estimates of strength as a function of the selected variables were obtained. © 2012 American Society of Civil Engineers.

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Biomimetic micro-swimmers can be used for various medical applications, such as targeted drug delivery and micro-object (e.g. biological cells) manipulation, in lab-on-a-chip devices. Bacteria swim using a bundle of flagella (flexible hair-like structures) that form a rotating cork-screw of chiral shape. To mimic bacterial swimming, we employ a computational approach to design a bacterial (chirality-induced) swimmer whose chiral shape and rotational velocity can be controlled by an external magnetic field. In our model, we numerically solve the coupled governing equations that describe the system dynamics (i.e. solid mechanics, fluid dynamics and magnetostatics). We explore the swimming response as a function of the characteristic dimensionless parameters and put special emphasis on controlling the swimming direction. Our results provide fundamental physical insight on the chirality-induced propulsion, and it provides guidelines for the design of magnetic bi-directional micro-swimmers. © 2013 The Author(s) Published by the Royal Society. All rights reserved.

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Highly sensitive biosensor for detection of acetylcholine (ACh) and competitive acetylcholinesterase (AChE) inhibitor, eserine, is investigated. Peculiar microelectronic configuration of an ion-sensitive field-effect transistor (ISFET) in addition to a right choice of the pH-transducing nanolayers allows recording a response of the enzyme-modified ISFET (EnFET) to a wide range of ACh concentrations. We demonstrate a remarkable improvement of at least three orders of magnitude in dose response to ACh. Described bioelectronic system reveals clear response, when the catalytic activity of the immobilized AChE is inhibited in a reversible manner by eserine, competitive inhibitor of AChE. ©2007 IEEE.

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This book is devoted to the rapidly growing highly interdisciplinary field of embodied artificial intelligence involving researchers from areas as diverse as computer science, engineering, cognitive science, neuroscience, biology, ...

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The field of Artificial Intelligence, which started roughly half a century ago, has a turbulent history. In the 1980s there has been a major paradigm shift towards embodiment. While embodied artificial intelligence is still highly diverse, changing, and far from "theoretically stable", a certain consensus about the important issues and methods has been achieved or is rapidly emerging. In this non-technical paper we briefly characterize the field, summarize its achievements, and identify important issues for future research. One of the fundamental unresolved problems has been and still is how thinking emerges from an embodied system. Provocatively speaking, the central issue could be captured by the question "How does walking relate to thinking?" © Springer-Verlag Berlin Heidelberg 2004.