996 resultados para automated meter reading (AMR)
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The validation of a fully automated dissolved Ni monitor for in situ estuarine studies is presented, based on adsorptive cathodic stripping voltammetry (AdCSV). Dissolved Ni concentrations were determined following on-line filtration and UV digestion, and addition of an AdCSV ligand (dimethyl glyoxime) and pH buffer (N-2-hydroxyethylpiperazine-N′-2-ethanesulphonic acid). The technique is capable of up to six fully quantified Ni measurements per hour. The automated in situ methodology was applied successfully during two surveys on the Tamar estuary (south west Britain). The strongly varying sample matrix encountered in the estuarine system did not present analytical interferences, and each sample was quantified using internal standard additions. Up to 37 Ni measurements were performed during each survey, which involved 13 h of continuous sampling and analysis. The high resolution data from the winter and summer tidal cycle studies allowed a thorough interpretation of the biogeochemical processes in the studied estuarine system.
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An automated and semi-intelligent voltammetric system is described for trace metal analysis. The system consists of a voltammeter interfaced with a personal computer, a sample changer, 2 peristaltic pumps, a motor burette and a hanging mercury drop electrode. The system carries out fully automatically approximately 5 metal determinations per hour (including at least 3 repetitive scans and calibration by standard addition) at trace levels encountered in clean sea water. The computer program decides what level of standard addition to use and evaluates the data prior to switching to the next sample. Alternatively, the system can be used to carry out complexing ligand titration with copper whilst recording the labile copper concentration; in this mode up to 8 full titrations are carried out per day. Depth profiles for chromium speciation in the Mediterranean Sea and a profile for copper complexing ligand concentrations in the North Atlantic Ocean measured on board-ship with the system are presented. The chromium speciation was determined using a new method to differentiate between Cr(III) and Cr(VI) utilizing adsorption of Cr(III) on silica particles.
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Association for Computing Machinery, ACM; IEEE; IEEE Computer Society; SIGSOFT
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A simple and rapid colorimetric pH meter has been developed based on the conformational switch of i-motif DNA and non-crosslinking AuNP aggregation, the average accuracy of the nano-meter was found to be +/- 0.04 pH unit across the physiological operating range.
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It is important to detect the aromaticity of structures during the process of structure elucidation and output. In this paper, an alogrithm was proposed to detect the aromaticity of structures by the use of algorithm on ring identification. The results show that it could be used to identify most of the aromatic structure. It have been used as constraints of Expert System on Elucidation Structure of Organic Compounds(ESESOC) and a good result has been achieved.
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Measurement of iron and manganese is very important in evaluating the quality of natural waters. We have constructed an automated Fe(II), total dissolved iron(TDI), Mn(II), and total dissolved manganese(TDM) analysis system for the quality control of underground drinking water by reverse flow injection analysis and chemiluminescence detection(rFIA-CL), The method is based on the measurement of the metal-catalyzed light emission from luminol oxidation by potassium periodate. The typical signal is a narrow peak, in which the height is proportional to light emitted and hence to the concentration of metal ions. The detection limits were 3 x 10(-6) mu g ml(-1) for Fe(II) and the linear range extents up to 1.0 x 10(-4) and 5 x 10(-6) mu g ml(-1) for Mn(II) cover a linear range to 1.0 x 10(-4) mu g ml(-1). This method was used for automated in-situ monitoring of total dissolved iron and total dissolved in underground water during water treatment. (C) 1997 Elsevier Science B.V.
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AMR在科研和军事方面的应用决定了其需要一个能够准确、实时估计出锂电池SOC的估计值。由于AMR工作中的放电具有很强的动态性,使得传统估计方法用于锂电池SOC的动态估计效果很不理想。本文描述了EKF方法在AMR锂电池SOC动态估计中的应用。模拟AMR工况进行动态放电试验。试验结果表明,该估计方法能够实时而准确地得到SOC值。
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Recognizing standard computational structures (cliches) in a program can help an experienced programmer understand the program. We develop a graph parsing approach to automating program recognition in which programs and cliches are represented in an attributed graph grammar formalism and recognition is achieved by graph parsing. In studying this approach, we evaluate our representation's ability to suppress many common forms of variation which hinder recognition. We investigate the expressiveness of our graph grammar formalism for capturing programming cliches. We empirically and analytically study the computational cost of our recognition approach with respect to two medium-sized, real-world simulator programs.