Anthropogenic aerosol emissions mapping and characterization by imaging spectroscopy – application to a metallurgical industry and a petrochemical complex

This paper is focused on the retrieval of industrial aerosol optical thickness (AOT) and microphysical properties by means of airborne imaging spectroscopy. Industrial emissions generally lead to optically thin plumes requiring an adapted detection method taking into account the weak proportion of particles sought in the atmosphere. To this end, a semi-analytical model combined with the Cluster-Tuned Matched Filter (CTMF) algorithm is presented to characterize those plumes, requiring the knowledge of the soil under the plume. The model allows the direct computation of the at-sensor radiance when a plume is included in the radiative transfer. When applied to industrial aerosol classes as defined in this paper, simulated spectral radiances can be compared to ‘real’ MODTRAN (Moderate Resolution Atmospheric Transmission) radiances using the Spectral Angle Mapper (SAM). On the range from 0.4 to 0.7 µm, for three grounds (water, vegetation, and bright one), SAM scores are lower than 0.043 in the worst case (a both absorbing and scattering particle over a bright ground), and usually lower than 0.025. The darker the ground reflectance is, the more accurate the results are (typically for reflectance lower than 0.3). Concerning AOT retrieval capabilities, with a pre-calculated model for a reference optical thickness of 0.25, we are able to retrieve plume AOT at 550 nm in the range 0.0 to 0.4 with an error usually ranging between 9% and 13%. The first test case is a CASI (Compact Airborne Spectrographic Imager) image acquired over the metallurgical industry of Fos-sur-Mer (France). First results of the use of the model coupled with CTMF algorithm reveal a scattering aerosol plume with particle sizes increasing with the distance from the stack (from detection score of 54% near the stack for particles with a diameter of 0.1 µm, to 69% away from it for 1.0 µm particles). A refinement is made then to estimate more precisely aerosol plume properties, using a multimodal distribution based on the previous results. It leads to find a mixture of sulfate and brown carbon particles with a plume AOT ranging between 0.2 and 0.5. The second test case is an AHS (Airborne Hyperspectral Scanner) image acquired over the petrochemical site of Antwerp (Belgium). The first CTMF application results in detecting a brown carbon aerosol of 0.1 µm mode (detection score is 51%). Refined results show the evolution of the AOT decreasing from 0.15 to 0.05 along the plume for a mixture of brown carbon fine mode and 0.3 µm radius of sulfate aerosol.     

Experimental and numerical study of granular medium-rough wall interface friction

Wall roughness plays a crucial role in granular medium - rough wall interface friction. In this study, an experimental device has been designed to study the influence of boundary conditions, more specifically wall roughness, on the behavior of sheared granular medium. The study is based on use of an analog model, and consists of simulating roughness by means of notches and grains in the medium by monodisperse beads and on use of a numerical model based on the discrete element method. The test protocol entails displacing at fixed speed notched rods under confined granular medium. Movement of the beads layer near the rods as well as friction of the beads against the rods are both studied herein. Results indicate that the parameter controlling friction at the granular medium - rough wall interface is primarily the depth of beads embedment in surface asperities. The objective of the associated numerical modeling is to supplement the experimental results.     

Golden-ratio as a substitute to geometric and harmonic counting to determine multi-author publication credit

Countless bibliometric indexes have been proposed to assess researchers’ productivities, in particular, in fields where the author sequence is regarded helpful in determining authors’ individual credits. Unfortunately, the most popular h-index ignores author ranks and leads to bias with multi-author publications; and of the many bibliometric counting methods proposed for assigning credit to authors, such as harmonic or geometric counting, none seems to have been widely adopted yet. In this work, I challenge the assumption that the total credit for a publication be equal to 1. This total-credit normalization assumption diminishes first-author credit and may impede adoption of multi-author-aware credit assignment rules. Other than on relative contributions, author credit could be based on variables such as accountability, which remains unchanged for the first (and potentially, the last) author regardless of additional coauthors. Therefore, I study the adequacy of several counting methods for first-author-normalized credit, giving full credit to the first author while also crediting coauthors. Harmonic counting has been shown to agree well with empirical data; however, unlike geometric counting, harmonic counting results in unbounded total credit for a publication with first-author-credit normalization in the limit of many authors. I therefore propose adaptable geometric counting and evaluate how it combines the advantages of harmonic and geometric counting through an additional parameter. I show that the golden ratio is a parameter for geometric counting that agrees as well as harmonic counting with empirical data for total-credit normalization; and I discuss the impact of using adaptable geometric counting with first-author-normalized credit. In particular, the latter features bounded total credits even when full credit is given to first authors. In conclusion, geometric counting with the golden ratio can be used for credit assignment without having to choose a parameter value, yet offers customization potential and can be combined with either normalization assumption.     

Geometrical shape optimization in fluid mechanics using FreeFem++

Structural and Multidisciplinary Optimization - In this article, we present simple and robust numerical methods for two-dimensional geometrical shape optimization problems, in the context of...     

A robust algorithm for white blood cell nuclei segmentation

Multimedia Tools and Applications - Segmentation of white blood cell nucleus is a crucial step in white blood cell counting and classification system based on peripheral blood smear images. It is...     

High-level synthesis for FPGAs: code optimization strategies for real-time image processing

High-level synthesis (HLS) is a potential solution to increase the productivity of FPGA-based real-time image processing development. It allows designers to reap the benefits of hardware implementation directly from the algorithm behaviors specified using C-like languages with high abstraction level. In order to close the performance gap between the manual and HLS-based FPGA designs, various code optimization forms are made available in today’s HLS tools. This paper proposes a HLS source code and directive manipulation strategy for real-time image processing by taking into account the applying order of different optimization forms. Experiment results demonstrate that our approach can improve more effectively the test implementations comparing to the other optimization strategies.     

A second-order blind source separation method for bilinear mixtures

In this paper, we are interested in the problem of Blind Source Separation using a Second-order Statistics (SOS) method in order to separate autocorrelated and mutually independent sources mixed according to a bilinear (BL) model. In this context, we propose a new approach called Bilinear Second-order Blind Source Separation, which is an extension of linear SOS methods, devoted to separate sources present in BL mixtures. These sources, called extended sources, include the actual sources and their products. We first study the statistical properties of the different extended sources, in order to verify the assumption of identifiability when the actual sources are zero-mean and when they are not. Then, we present the different steps performed in order to estimate these actual centred sources and to extract the actual mixing parameters. The obtained results using artificial mixtures of synthetic and real sources confirm the effectiveness of the new proposed approach.     

Smoke gas analysis by Fourier transform infrared spectroscopy – summary of the SAFIR project results

The determination of toxic components from fire gases is difficult because the environment is hot, reactions are often temperature dependent, and a lot of soot may be produced. Due to the different properties of the gas components, a different time‐consuming procedure for each species has traditionally been used. The use of FTIR (Fourier transform infrared) spectrometers as a continuous monitoring technique overcomes many of the problems in smoke gas analyses. FTIR offers an opportunity to set up a calibration and prediction method for each gas showing a characteristic spectral band in the infrared region of the spectrum. The objective of the SAFIR project was to further develop the FTIR gas analysis of smoke gases to be an applicable and reliable method for the determination of toxic components in combustion gases related to fire test conditions. The optimum probe design, filter parameters and the most suitable sampling lines in terms of flow rate, diameter, construction material and operating temperature have been specified. In the large scale, special concern was given to the probe design and the effects of the probe location as well as practical considerations of the sampling line length. Quantitative calibration and prediction methods have been constructed for different components present in smoke gases. Recommendations on how to deal with interferents, non‐linearities and outliers have been provided and a verification method for the spectrometer for unexpected variations and for the different models have been described. FTIR measurement procedures in different fire test scenarios have been studied using the recommendations of this project for measurement techniques and analysis and an interlaboratory trial of the FTIR technique in smoke gas analysis was carried out to define the repeatability and reproducibility of the method in connection with a small scale fire test method, the cone calorimeter. Copyright © 2000 John Wiley & Sons Ltd.     

A fair method for centralized optimization of multi-TSO power systems

This paper addresses the problem of centralized optimization of an interconnected power system partitioned into several regions controlled by different transmission system operators (TSOs). It is assumed that those utilities have agreed to transferring some of their competencies to a centralized control center, which is in charge of setting the control variables in the entire system to satisfy every utility’s individual objective. This paper proposes an objective method for centralized optimization of such multi-TSO power systems, which relies on the assumption that each TSO has a real-valued optimization function focusing on its control area only. This method is illustrated on the IEEE 118 bus system partitioned into three TSOs. It is applied to the optimal reactive power dispatch problem, where the control variables are the voltage settings for generators and compensators. After showing that the method has some properties of fairness, namely freedom from envy, efficiency, accountability, and altruism, we emphasize its robustness with respect to certain biased behavior of the different TSOs.