This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologie...
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ISBN:
(纸本)9781424441198
This paper evaluates existing taxonomies aimed at characterizing the interaction between robots and their users and modifies them for health care applications. The modifications are based on existing robot technologies and user acceptance of robotics. Characterization of the user, or in this case the patient, is a primary focus of the paper, as they present a unique new role as robot users. While therapeutic and monitoring-related applications for robots are still relatively uncommon, we believe they will begin to grow and thus it isimportant that the spurring relationship between robot and patient is well understood.
The low-frequency 1/f noise in graphene transistors has been studied extensively owing to the proposed graphene applications in analog devices and communication systems [1-5]. The studies were motivated by the fact th...
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The low-frequency 1/f noise in graphene transistors has been studied extensively owing to the proposed graphene applications in analog devices and communication systems [1-5]. The studies were motivated by the fact that the low-frequency noise can be up-converted by device nonlinearity and contribute to the phase noise of the system. Similarly, the sensor sensitivity is often limited by the electronic low-frequency noise. Therefore, noise is usually considered as one of the main limiting factors for the device or overall system operation. However, the electronic noise spectrum itself can be used as a sensing parameter increasing the sensor sensitivity and selectivity. Here, we show that vapors of different chemicals produce distinguishably different effects on the low-frequency noise spectra of the graphene-on-Si transistor. Our study showed that some gases change the electrical resistance of pristine graphene devices without changing their low-frequency noise spectra while other gases modify the noise spectra by inducing Lorentzian components with distinctive features. The characteristic corner frequency f C of the Lorentzian noise bulges in graphene devices is different for different chemicals and varies from f C =10 - 20 Hz for tetrahydrofuran to f C =1300 - 1600 Hz for chloroform. We tested the selected set of chemicals vapors on different graphene device samples and alternated different vapors for the same samples. The obtained results indicate that 1/f noise in combination with other sensing parameters can allow one to achieve the selective gas sensing with a single pristine graphene transistor. Our method of gas sensing with graphene does not require graphene surface functionalization or fabrication of an array of the devices with each tuned to a certain chemical. The observation of the Lorentzian components in the vapor-exposed graphene can also help in developing an accurate theoretical description of the noise mechanism in graphene.
PatternLab for proteomics is a self-contained computational environment for analyzing shotgun proteomic data. Recent improvements incorporate modules to facilitate the computational analysis, such as FastaDBXtractor f...
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In modern software engineering the task of migration from one system environment to another may arise very often (e.g. software migrating from Windows to Linux or from desktop PC to some mobile platform). This task ma...
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Software Product Lines (SPLs) have been used to develop mobile and context-aware applications, which provide services and data for their users from anywhere and at any time using context information. In SPLs, commonal...
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Artificial bee colony (ABC) is an optimization algorithm inspired on the intelligent behavior of honey bee swarms. It is suitable to be applied when mathematical techniques are impractical or provide suboptimal soluti...
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ISBN:
(纸本)9781467312073
Artificial bee colony (ABC) is an optimization algorithm inspired on the intelligent behavior of honey bee swarms. It is suitable to be applied when mathematical techniques are impractical or provide suboptimal solutions. As a population-based algorithm, the ABC suffers on large execution times specifically for embedded optimization problems with computational limitations. For that we propose a hardware parallel architecture of the opposition-based ABC algorithm (HPOABC) that facilitates the implementation in Field programmable Gate Arrays (FPGAs). Numerical simulations using four well-known benchmark problems demonstrate that the opposition-based approach allows the algorithm to improve its functionality, preserving the swarm diversity. Additionally, synthesis results point outs that the HPOABC architecture is effectively mapped in hardware and is suitable for embedded applications.
This work extends Propositional Dynamic Logic (PDL) with parallel composition operator and four atomic programs which formalize the storing and recovering of elements in data structures. A generalization of Kripke sem...
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Designing an overlay network for publish/subscribe communication in a system where nodes may subscribe to many different topics of interest is of fundamental importance. For scalability and efficiency, it is important...
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Obtaining the Jacobian parameters for a nonlinear system, such as in X-parameter or S-function measurement, requires excitation of tickle tones either on or slightly off of the main harmonic frequencies. Traditional o...
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This research examines U.S. electric utilities' transition from closed to open systems, while taking steps towards market orientation and subsequent changes in their product portfolios. It lists the reasons drivin...
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ISBN:
(纸本)9781618393616
This research examines U.S. electric utilities' transition from closed to open systems, while taking steps towards market orientation and subsequent changes in their product portfolios. It lists the reasons driving this change and includes a detailed analysis of the current product portfolios of the U.S. utilities focusing on adding more renewable energy sources. Copyright, American Society for engineering Management, 2011.
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