In this paper, a new MSM-UV-photodetector (PD) based on dual wide band-gap material (DM) engineering aspect is proposed to achieve high-performance self-powered device. Comprehensive analytical models for the proposed sensor photocurrent and the device properties are developed incorporating the impact of DM aspect on the device photoelectrical behavior. The obtained results are validated with the numerical data using commercial TCAD software. Our investigation demonstrates that the adopted design amendment modulates the electric field in the device, which provides the possibility to drive appropriate photo-generated carriers without an external applied voltage. This phenomenon suggests achieving the dual role of effective carriers’ separation and an efficient reduce of the dark current. Moreover, a new hybrid approach based on analytical modeling and Particle Swarm Optimization (PSO) is proposed to achieve improved photoelectric behavior at zero bias that can ensure favorable self-powered MSM-based UV-PD. It is found that the proposed design methodology has succeeded in identifying the optimized design that offers a self-powered device with high-responsivity (98 mA/W) and superior ION/IOFF ratio (480 dB). These results make the optimized MSM-UV-DM-PD suitable for providing low cost self-powered devices for high-performance optical communication and monitoring applications.

In this paper, graded channel doping (GCD) and junctionless paradigms are proposed as a new ways to improve the optical controlled field effect transistor (OCFET) and bridging the gap between the high responsivity and ultra-low power consumption. A careful mechanism study based on numerical investigation and a performance comparison between the proposed structure and both the conventional inversion mode (IM-OCFET) and the junctionless (JL-OCFET) designs is presented. It is found that the graded channel doping feature can efficiently improve the overall device optical and electrical performances. Moreover, the proposed design exhibits superior device figures of merit (FoMs) and provides ultra-sensitivity behavior as compared to both the conventional IM-OCFET and the JL-OCFET counterparts. Our investigation reveals also the outstanding capability of the proposed structure for offering the weak signal detection advantage that demonstrates the unique property of our phototransistor with GCD aspect. These characteristics not only underline the excellent switching behavior of the proposed design but also demonstrate the ability for overcoming the trade-off between the low cost and readily fabrication process in addition to ultrasensitive aspect with low power consumption. This makes the proposed GCD-JL-OCFET a potential alternative for developing low power communication systems.

Over the past few years, multicore systems have become increasingly powerful and thereby very useful in high-performance computing. However, many applications, such as some linear algebra algorithms, still cannot take full advantage of these systems. This is mainly due to the shortage of optimization techniques dealing with irregular control structures. In particular, the well-known polyhedral model fails to optimize loop nests whose bounds and/or array references are not affine functions. This is more likely to occur when handling sparse matrices in their packed formats. In this article, we propose using 2d-packed layouts and simple affine transformations to enable optimization of triangular and banded matrix operations. The benefit of our proposal is shown through an experimental study over a set of linear algebra benchmarks.

In this work, an optimization study of the delivered power density by the solid oxide fuel cells is presented according to a thermodynamic model. The power density is defined by the current density, the Nernst potential and the three losses: concentration, activation and ohmic. A comparison between the Tafel and Butler-Volmer formulations was performed to quantify the activation loss. A program in FORTRAN language was developed locally for the resolution of the mathematical equations representing the used physical model. The obtained results show that the SOFCs power density is inversely proportional to the anode thickness, electrolyte thickness and cathode thickness. The optimum fuel water content ensures the maximum power density is 6.25%. The cell power density is proportional to the oxygen concentration in the oxidant, the operating temperature and the operating pressure.

Zn(1–x)MgxO thin films with various concentrations of magnesium were deposited using the spray pyrolysis method. The transmittance spectra recorded for all films exhibit maxima exceeding 90%. The band gap energy of the films with wurtzite structure increases from 3.22 up to 3.60 eV by incorporating Mg into ZnO. However, when the atomic ratio of Mg exceeded 0.4, a second crystalline phase (assigned to cubic MgO) became discernable in XRD patterns, a compressive strain was observed in the wurtzite lattice, and crystallite sizes decreased significantly. In accordance with these observations, finer grains with a pronounced columnar growth were observed in 3D AFM representations and the surface roughness decreases significantly. Finally, selective etching in water yields to porous films with a great surface-to-volume ratio, a lower refractive index and a better light transmission. These porous films with tunable band gap seem to be excellent candidates to various interesting applications.

Over the last few years, different traffic sign recognition systems were proposed. The present paper introduces an overview of some recent and efficient methods in the traffic sign detection and classification. Indeed, the main goal of detection methods is localizing regions of interest containing traffic sign, and we divide detection methods into three main categories: color-based (classified according to the color space), shape-based, and learning-based methods (including deep learning). In addition, we also divide classification methods into two categories: learning methods based on hand-crafted features (HOG, LBP, SIFT, SURF, BRISK) and deep learning methods. For easy reference, the different detection and classification methods are summarized in tables along with the different datasets. Furthermore, future research directions and recommendations are given in order to boost TSR’s performance.

The path-planning problem is commonly formulated to handle the obstacle avoidance constraints. This problem becomes more complicated when further restrictions are added. It often requires efficient algorithms to be solved. In this paper, a new approach is proposed where the path is described by means of Non Uniform Rational B-Splines (NURBS for short) with more additional constraints. An evolutionary technique called Particle Swarm Optimization (PSO) with three options of particles velocity updating offering three alternatives namely the PSO with inertia weight (PSO-W), the constriction factor PSO (PSO-C) and the combination of the two(PSO-WC); are used to optimize the weights of the control points that serve as parameters of the algorithm describing the path. Simulation results show how the mixture of the first two options produces a powerful algorithm, specifically (PSO-WC), in producing a compromise between fast convergence and large number of potential solution. In addition, the whole approach seems to be flexible, powerful and useful for the generation of successful smooth trajectories for robot manipulator which are independent from environment conditions.