An economic and sensitive method for extracting chromium speciation in airborne inhalable dust,using a green sample treatment coupled with electrothermal atomic absorption

ABSTRACT

A new approach of cloud point extraction CPE procedure is optimized for hexavalent chromium determination in airborne dusts. Triton X-114 is used as a surfactant and 1-(2-pyridylazo)-2-naphthol as a specific complexing agent for the trivalent chromium’s removal from the aqueous phase to isolate hexavalent chromium compounds. The parameters influencing the extraction protocol (pH, surfactant concentration, and temperature are optimized. The obtained detection and quantification limits are 0.1 and 0.4 μg/L, respectively. The linearity is verified, with a regression coefficient close to 0.999 and the extraction recovery exceeds 99%. The method was successfully applied to analyze airborne samples collected from workplaces.     

Effects of frequency dimming electronic ballast on a high‐pressure mercury thallium iodide discharge

This study focuses on the behavior of a cylindrical metal halide discharge lamp powered by frequency‐controlled electronic ballast. Half‐bridge electronic ballast was designed and achieved.     

The pleural thickening approximation from thoracic CT scans

Multimedia Tools and Applications - The involvement of medical imaging in medical procedures plays an important role in the diagnosis and planning of a therapeutic treatment. Computerized...     

On business process monitoring using cross-flow coordination

This paper presents an approach for monitoring the execution progress of business processes. The monitoring focuses on the exceptions that could arise during this execution and, hence, could make the processes fail if not handled properly and timely. The approach relies on three flows known as control, communication, and navigation. The control flow connects tasks together with respect to a certain business logic. The communication flow captures the messages exchanged between persons/machines when they perform tasks of processes. Finally, the navigation flow captures the interactions between specialized networks that offer solutions to exceptions. These networks are built upon relations between tasks, between persons, and between machines. The coordination of control, communication, and navigation flows focuses on both the actions that are taken and the messages that are exchanged when handling exceptions. A system demonstrating flow development and coordination is, also, presented in the paper.     

A geostatistical approach for groundwater head monitoring network optimisation: case of the Sfax superficial aquifer (Tunisia)

In many developing countries, the groundwater monitoring network is randomly designed, and consequently needs to be revised and optimised to reduce operation time and cost, remove redundant piezometric data, and strengthen sparseness data zone with supplementary observation well. The geostatistical approach used in this work is based on the universal kriging variance combined with cross‐validation test. Hence, a rational interpolation of water table elevations was performed to evaluate the accuracy of data employed in the piezometric head modelling. In this study, the groundwater monitoring network of the Sfax superficial aquifer in the south east of Tunisia was optimised. The elimination of five observation wells induces the invariability in the variance of estimate due to their less contribution in interpretations of the groundwater level behaviour. However, 38 wells were added at areas of high variance of the kriging in order to ameliorate the spatial coverage of the monitoring network.     

New pulse mode neuro-fuzzy hardware architecture and application to image denoising

This paper focuses on a new digital architecture of pulse mode neuro-fuzzy system (PMNFS) with on-chip learning ability. The main purpose goal is to make use of the outstanding features of neuro-fuzzy in function approximation, and implement a reconfigurable architecture with on-chip learning on a field-programmable gate array (FPGA) platform. Details of the whole design with on-chip learning solutions are given. As an application illustrating the efficiency and scalability of the proposed PMNFS, we have considered the approximation of image denoising, which is a very important step in image processing. Experimental results show great efficiency of the proposed method, outperforming other denoising techniques. It was also demonstrated that such a system is strongly adaptive and gives good restored images independently of the kind of noises. Owing to learning, such feature cannot be met with conventional denoising techniques. Design synthesis results on a virtex II PRO FPGA platform are presented. Comparisons with conventional techniques as well as neural ones show higher performances of the designed PMNFS.     

Probabilistic analysis of ultimate seismic bearing capacity of strip foundations

This paper presents a reliability analysis of the pseudo-static seismic bearing capacity of a strip foundation using the limit equilibrium theory. The first-order reliability method (FORM) is employed to calculate the reliability index. The response surface methodology (RSM) is used to assess the Hasofer–Lind reliability index and then it is optimized using a genetic algorithm (GA). The random variables used are the soil shear strength parameters and the seismic coefficients (k_h and k_v). Two assumptions (normal and non-normal distribution) are used for the random variables. The assumption of uncorrelated variables was found to be conservative in comparison to that of negatively correlated soil shear strength parameters. The assumption of non-normal distribution for the random variables can induce a negative effect on the reliability index of the practical range of the seismic bearing capacity.     

A multi-level conceptual data reduction approach based on the Lukasiewicz implication

Starting from fuzzy binary data represented as tables in the fuzzy relational database, in this paper, we use fuzzy formal concept analysis to reduce the tables size to only keep the minimal rows in each table, without losing knowledge (i.e., association rules extracted from reduced databases are identical at given precision level). More specifically, we develop a fuzzy extension of a previously proposed algorithm for crisp data reduction without loss of knowledge. The fuzzy Galois connection based on the Lukasiewicz implication is mainly used in the definition of the closure operator according to a precision level, which makes data reduction sensitive to the variation of this precision level.     

H∞ control for uncertain one‐sided Lipschitz nonlinear systems in finite frequency domain

The current article discusses the H_∞ disturbance attenuation control design problem for one‐sided Lipschitz systems in finite frequency domain. Models containing norm‐bounded parameter uncertainties, disturbances, and input nonlinearities are considered. By contrast to existing full frequency methods, the H_∞ controller is computed depending on the frequency ranges of disturbances. The finite frequency disturbance attenuation index is initially defined. Thanks to Finsler's lemma, sufficient and less conservative analysis conditions are also derived for the closed‐loop system. Then, synthesis conditions in the low, middle, and high frequency ranges as well as the whole frequency range, are formulated in terms of linear matrix inequalities. At last, to prove the effectiveness and the superiority of the proposed approach, a physical example is used and a comparative study is done.