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.     

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.

     

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.     

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.     

Biobased flexible polyurethane foams manufactured from lactide-based polyester-ether polyols for automotive applications

In this study, biobased polyester-ether polyols derived from meso-lactide and dimer acids were evaluated for flexible polyurethane foams (PUF) applications. Initially, the catalyst concentration was optimized for the biobased PUF containing 30% of biobased polyol (70% petroleum-based polyol). Then, the same formulation was used for biobased PUF synthesis containing 10%–40% of biobased polyols. The performance of biobased PUF was compared with the performance of the control foam made with 100% petroleum-based polyol. The characteristic times (cream, top of the cup, string gel, rise, tack-free) of biobased PUF were determined. The biobased PUF were evaluated for the mechanical (tensile and compressive) and morphological properties. As the wet compression set is important for automotive applications, it was measured for all biobased PUF. The thermal degradation behavior of biobased PUF was also evaluated and compared with the control foam. The effect of different hydroxyl and acid values of polyols on the mechanical properties of biobased PUF is also discussed. The miscibility of all components of PUF formulations is crucial in order to produce a foam with uniform properties. Thus, the miscibility of biobased polyols with commercial petroleum-based polyol was studied.     

Fuzzy and Deep Belief Network Based Malicious Vehicle Identification and Trust Recommendation Framework in VANETs

Wireless Personal Communications - This work aims to implement a clustering scheme to separate vehicles into a cluster that is based on various parameters, such as the total number of relay nodes,...     

Modulated Triple‐Material Nano‐Heterostructures: Where Gold Influenced the Chemical Activity of Silver in Nanocrystals

For efficient charge separations, multimaterial hetero‐nanostructures are being extensively studied as photocatalysts. While materials with one heterojunction are widely established, the chemistry of formation of multijunction heterostructures is not explored. This needs a more sophisticated approach and modulations. To achieve these, a generic multistep seed mediated growth following controlled ion diffusion and ion exchange is reported which successfully leads to triple‐material hetero‐nanostructures with bimetallic‐binary alloy‐binary/ternary semiconductors arrangements. Ag₂S nanocrystals are used as primary seeds for obtaining AuAg‐AuAgS bimetallic‐binary alloyed metal–semiconductor heterostructures via partial reduction of Ag(I) using Au(III) ions. These are again explored as secondary seeds for obtaining a series of triple‐materials heterostructures, AuAg‐AuAgS‐CdS (or ZnS or AgInS₂), with introduction of different divalent and trivalent ions. Chemistry of each step of the gold ion–induced changes in the rate of diffusion and/or ion exchanges are investigated and the formation mechanism for these nearly monodisperse triple material heterostructures are proposed. Reactions without gold are also performed, and the change in the reaction chemistry and growth mechanism in presence of Au is also discussed.     

An equivalent uniaxial fatigue stress model for analyzing landing gear fuse pins

We study the biaxial stress state conditions in landing gear fuse pins in the fuse groove. This biaxial state comprises a combination of shear stresses which are usually the largest stresses in the fuse pin by design, and compressive stresses which keep the half-section of the fuse pin in equilibrium. Conventional fatigue analysis techniques use an equivalent uniaxial stress, based on the Mises stress of a pure-shear condition. The respective predicted fatigue damages are much higher than those obtained from fuse pin cyclic tests. A new equivalent uniaxial fatigue stress model is proposed that includes the additional compressive stress as a relief on the fatigue damage in the fuse groove, thereby explaining the observations from fuse pin tests. The model is used in conventional uniaxial strain-life fatigue software (Goodrich Aerospace’s Fatigue Life V2) to predict the fatigue damage on a landing gear fuse pin with a sample load spectrum. The results are then compared to the pure shear model, and to a biaxial finite element fatigue analysis. As compared to the equivalent Mises model, the proposed model provides less conservative estimation of the fuse pin fatigue life, the latter value being higher than that provided by the two-dimensional finite element calculation. __________ Translated from Problemy Prochnosti, No. 3, pp. 85–98, May–June, 2006.