951 resultados para FIELD MEASUREMENT


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In this paper, a plasmonic “ac Wheatstone bridge” circuit is proposed and theoretically modeled for the first time. The bridge circuit consists of three metallic nanoparticles, shaped as rectangular prisms, with two nanoparticles acting as parallel arms of a resonant circuit and the third bridging nanoparticle acting as an optical antenna providing an output signal. Polarized light excites localized surface plasmon resonances in the two arms of the circuit, which generate an optical signal dependent on the phase-sensitive excitations of surface plasmons in the antenna. The circuit is analyzed using a plasmonic coupling theory and numerical simulations. The analyses show that the plasmonic circuit is sensitive to phase shifts between the arms of the bridge and has the potential to detect the presence of single molecules.

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The measurement error model is a well established statistical method for regression problems in medical sciences, although rarely used in ecological studies. While the situations in which it is appropriate may be less common in ecology, there are instances in which there may be benefits in its use for prediction and estimation of parameters of interest. We have chosen to explore this topic using a conditional independence model in a Bayesian framework using a Gibbs sampler, as this gives a great deal of flexibility, allowing us to analyse a number of different models without losing generality. Using simulations and two examples, we show how the conditional independence model can be used in ecology, and when it is appropriate.

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The concept of system use has suffered from a "too simplistic definition" (DeLone and McLean [9], p. 16). This paper reviews various attempts at conceptualization and measurement of system use and then proposes a re-conceptualization of it as "the level of incorporation of an information system within a user's processes." We then go on to develop the concept of a Functional Interface Point and four dimensions of system usage: automation level, the proportion of the business process encoded by the information system; extent, the proportion of the FIPs used by the business process; frequency, the rate at which FIPs are used by the participants in the process; and thoroughness, the level of use of information/functionality provided by the system at an FIP. The article concludes with a discussion of some implications of this re-conceptualization and areas for follow on research.

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Organizations invest heavily in Customer Relationship Management (CRM) and Supply Chain Management (SCM) systems, and their related infrastructure, presumably expecting positive benefits to the organization. Assessing the benefits of such systems is an important aspect of managing such systems. Given the substantial differences between CRM and SCM systems with traditional intra-organizational applications, existing Information Systems benefits measurement models and frameworks are ill-suited to gauge CRM and SCM benefits. This paper reports the preliminary findings of a research that seeks to develop a measurement model to assess benefits of CRM and SCM applications. The a-priori benefits measurement model is developed reviewing the 55 academic studies and 40 practitioner papers. The review of related literature yielded 606 benefits, which were later synthesized into 74 mutually exclusive benefit measures of CRM and SCM applications arranged under five dimensions.

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There has recently been noted a rapid increase in research attention to projects that involve outside partners. Our knowledge of such inter-organizational projects, however, is limited. This paper reports large scale data from a repeated trend survey amongst 2000 SMEs in 2006 and 2009 that focused on inter-organizational project ventures. Our major findings indicate that the overall prevalence of inter-organizational project ventures remained significant and stable over time, even despite the economic crisis. Moreover, we find that these ventures predominantly solve repetitive rather than unique tasks and are embedded in prior relations between the partnering organizations. These findings provide empirical support for the recent claims that project management should pay more attention to inter-organizational forms of project organization, and suggest that the archetypical view of projects as being unique in every respect should be reconsidered. Both have important implications for project management, especially in the area of project-based learning.

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Background: To compare the intraocular pressure readings obtained with the iCare rebound tonometer and the 7CR non-contact tonometer with those measured by Goldmann applanation tonometry in treated glaucoma patients. Design: A prospective, cross sectional study was conducted in a private tertiary glaucoma clinic. Participants: 109 (54M:55F) patients including only eyes under medical treatment for glaucoma. Methods: Measurement by Goldmann applanation tonometry, iCare rebound tonometry and 7CR non-contact tonometry. Main Outcome Measures: Intraocular pressure. Results: There were strong correlations between the intraocular pressure measurements obtained with Goldmann and both the rebound and non-contact tonometers (Spearman r values ≥ 0.79, p < 0.001). However, there were small, statistically significant differences between the average readings for each tonometer. For the rebound tonometer, the mean intraocular pressure was slightly higher compared to the Goldmann applanation tonometer in the right eyes (p = 0.02), and similar in the left eyes (p = 0.93) however these differences did not reach statistical significance. The Goldmann correlated measurements from the noncontact tonometer were lower than the average Goldmann reading for both right (p < 0.001) and left (p > 0.01) eyes. The corneal compensated measurements from the non-contact tonometer were significantly higher compared to the other tonometers (p ≤ 0.001). Conclusions: The iCare rebound tonometer and the 7CR non-contact tonometer measure IOP in fundamentally different ways to the Goldmann applanation tonometer. The resulting IOP values vary between the instruments and will need to be considered when comparing clinical versus home acquired measurements.