Estimating and reducing the memory requirements of signal processing codes for embedded systems

Most embedded systems have limited amount of memory. In contrast, the memory requirements of the digital signal processing (DSP) and video processing codes (in nested loops, in particular) running on embedded systems is significant. This paper addresses the problem of estimating and reducing the amount of memory needed for transfers of data in embedded systems. First, the problem of estimating the region associated with a statement or the set of elements referenced by a statement during the execution of nested loops is analyzed. For a fixed execution ordering, a quantitative analysis of the number of elements referenced is presented; exact expressions for uniformly generated references and a close upper and lower bound for nonuniformly generated references are derived. Second, in addition to presenting an algorithm that computes the total memory required, this paper also discusses the effect of transformations (that change the execution ordering) on the lifetimes of array variables, i.e., the time between the first and last accesses to a given array location. The term maximum window size is introduced, and quantitative expressions are derived to compute the maximum window size. A detailed analysis of the effect of unimodular transformations on data locality, including the calculation of the maximum window size, is presented.     

Predicting the performance of concrete structures exposed to chemically aggressive environment—Field validation

The behavior of two series of concrete slabs exposed to sulfate-bearing soils was investigated by a numerical model called STADIUM. In addition to the diffusion of ions and moisture, the model also accounts for the effects of dissolution/precipitation reactions on the transport mechanisms. The simulations yielded by the model were compared to the actual degradation of the slabs after 8 years of exposure. The microstructural alterations of concrete resulting from the penetration of magnesium, chloride and sulfate ions were studied by backscatter mode scanning electron microscope observations and energy-dispersive X-ray analyses. The comparison of both series of data indicates that the model can reliably predict the various features of the microstructural alterations of concrete.

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Résumé Le comportement de deux séries de dalles sur sol en béton exposées à des sols chimiquement agressifs a été étudié à l'aide d'un code de calcul numérique appelé STADIUM. Ce modèle permet de décrire le transport couplé de l'eau et des ions dans des matériaux poreux non-saturés en prenant en considération l'influence des réactions chimiques. Les résultats des simultations de la dégradation du béton après huit ans d'exposition à des ions chlore, sulfate et magnésium. Les observations ont été réalisées par microscopie électronique à balayage. Des analyses par dispersion des rayons X ont également été effectuées. Les données démontrent clairement que le modèle perment de prédire avec précision le comportement du béton soumis à différents types d'agression chimique.

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Editorial Note Laval University (Canada) is a RILEM Titular Member. Prof. J. Marchand was awarded the 2000 Robert L'Hermite Medal. He is Editor in Chief for Concrete Science and Engineering and Associate Editor for Materials and Structures. He participates in RILEM TC 186-ISA ‘Internal Sulfate attack’.     

Favorable influence of ssDNA-functionalized SWCNT on the navigation pattern of C. elegans

Microsystem Technologies - Single-Walled Carbon Nanotubes (SWCNTs) are widely used as potential carriers in drug delivery systems. The objective of this work was to observe the effects of pristine,...     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

In Vitro Characterization of Human CD24hiCD38hi Regulatory B Cells Shows CD9 Is Not a Stable Breg Cell Marker

Regulatory B (Breg) cells are endowed with immune suppressive functions. Various human and murine Breg subtypes have been reported. While interleukin (IL)-10 intracellular staining remains the most reliable way to identify Breg cells, this technique hinders further essential functional studies. Recent findings suggest that CD9 is an effective surface marker of murine IL-10 competent Breg cells. However, the stability of CD9 and its relevance as a unique marker for human Breg cells, which have been widely characterized as CD24^hiCD38^hi, have not been investigated. Here, we demonstrate that CD9 expression is sensitive to in vitro B cell stimulations. CD9 expression could either be re-expressed or downregulated in purified CD9-negative B cells and CD9-positive B cells, respectively. We found no significant differences in the Breg differentiation capacity of the CD9-negative and CD9-positive B cells. Furthermore, CD9-positive B cells co-express CD40 and CD86, suggesting their nature as B cell activation or co-stimulatory molecules, rather than regulatory ones. Therefore, we report the relatively unstable CD9 as a distinct surface molecule, indicating the need for further research for a more reliable marker to purify human Breg cells.     

Alkylation of Benzene with Isopropyl Alcohol over SAPO-5 Catalyst in an Integral Pressure Reactor

The alkylation of benzene with isopropyl alcohol was studied in an integral pressure reactor over silicon substituted aluminophosphate molecular sieves, SAPO-5. The influence of various process parameters such as temperature, pressure, time on stream, weight hourly space velocity, and mole ratio of reactants on cumene yield and selectivity were investigated. The activity of SAPO-5 was compared with that of Hbeta for this reaction under similar conditions and in the same reactor. At pressures higher than atmospheric, almost the theoretical maximum yields of cumene were achieved on this SAPO-5. Among the diisopropyl benzenes formed by the alkylation of cumene, the meta-isomer was found to form in a significant amount followed by the para-isomer. The ortho-isomer with relatively high strain energy of 4.26 kcal/mol was almost negligible. The cumene yield goes through a maximum in the temperature range 498-543 K studied. Cumene selectivity was found to decrease at higher temperatures, higher pressures and lower benzene to isopropanol mole ratios.     

Adaptive tracking control of an autonomous underwater vehicle

This paper presents the trajectory tracking control of an autonomous underwater vehicle(AUV). To cope with parametric uncertainties owing to the hydrodynamic effect, an adaptive control law is developed for the AUV to track the desired trajectory. This desired state-dependent regressor matrix-based controller provides consistent results under hydrodynamic parametric uncertainties.Stability of the developed controller is verified using the Lyapunov s direct method. Numerical simulations are carried out to study the efficacy of the proposed adaptive controller.     

Free convection heat transfer over a horizontal plate at low prandtl number

Boundary layer equations for free convection heat transfer along a semi-infinite horizontal plate are derived by giving more importance to the energy equation. The equations are obtained for low Prandtl number and two separate polynomials are used to approximate the temperature and velocity profiles in these regions. The rate of heat transfer is compared with the available analytical and numerical results based on conventional boundary layer equations.     

Ameliorating effect of silica addition in the anode-catalyst layer of the membrane electrode assemblies for polymer electrolyte fuel cells

Incorporation of silica particles through a sol-gel process into the anode-catalyst layer with a sol-gel modified Nafion-silica composite membrane renders easy retention of back-diffused water from the cathode to anode through the composite membrane electrolyte, increases the catalyst-layer wettability and improves the performance of the Polymer Electrolyte Fuel Cell (PEFC) while operating under relative humidity (RH) values ranging between 18% and 100% with gaseous hydrogen and oxygen reactants at atmospheric pressure. A peak power density of 300 mW cm⁻² is achieved at a load current-density value of 1200 mA cm⁻² for the PEFC employing a sol-gel modified Nafion-silica composite membrane and operating at 18% RH. Under similar operating conditions, the PEFC with a Membrane Electrode Assembly (MEA) comprising Nafion-silica composite membrane with silica in the anode-catalyst layer delivers a peak power density of 375 mW cm⁻². By comparison, the PEFC employing commercial Nafion membrane fails to deliver satisfactory performance at 18% RH due to the limited availability of water at its anode, acerbated electro-osmotic drag of water from anode to cathode and insufficient water back diffusion from cathode to anode causing the MEA to dehydrate.     

Low intensity visual data improvement using DWT and LWT based regularizer

Image Completion plays a vital role in compressed sensing, machine learning, and computer vision applications. The Rank Minimization algorithms are used to perform the image completion. The major problem with rank minimization algorithms is the loss of information in the recovered image at high corruption ratios. To overcome this problem Lifting wavelet transform based Rank Minimization (LwRM), and Discrete wavelet transform based Rank Minimization (DwRM) methods are proposed, which can recover the image, if the corrupted observations are more than 80%. The evaluation of the proposed methods are accomplished by Full Reference Image Quality Assessment (FRIQA) and No Reference Image Quality Assessment (NR-IQA) metrics. The simulation results of proposed methods are superior to state-of-the-art methods.