Large area Ag-TiO2 UV radiation sensor fabricated on a thermally oxidized titanium chip

A Schottky-type ultraviolet (UV) light sensor is fabricated on a thermally oxidized titanium chip. The device is of Ag-TiO₂-Ti structure, and the Schottky junction between silver and rutile is formed subsequent to the vacuum deposition of silver on the thermally grown rutile layer by a controlled thermal annealing in air. The device operates at −300 mV biasing established between silver and titanium electrodes. The dark reverse current of this diode increases four orders of magnitude when illuminated with UV light (355 nm) of 10 μW/mm² intensity. The device is almost insensitive to visible light and requires no filtering when used for ambient UV level detection. The operation mechanism of the device is described by photonic electron-hole pair generation in the carrier depleted titanium dioxide layer adjacent to the silver electrode. The electrode-to-electrode distance is 1 μm only affording much faster performance compared to photoconductive UV detectors fabricated based on titanium dioxide; the response and recovery times of the device are 10 ms and 17 ms, respectively. At its standby mode, a 1 mm² active area device consumes less than 10 pW of electric power. Sensors with sensitive areas as large as ∼10 mm² are easy to fabricate. The fabricated devices are rugged, resistant to UV degradation, and cost effective.     

An effective operations permutation-based discrete harmony search approach for the flexible job shop scheduling problem with makespan criterion

The Flexible Job Shop Scheduling Problem (FJSSP) represents a challenging applicative problem for metaheuristic algorithms because it imposes the development of innovative domain-dependent search operators that have to deal both with its combined discrete and permutation nature. Emerging as an effective approach for the resolution of a broad spectrum of hard optimization problems, some few discrete declinations of the Harmony Search (HS) algorithm have been recently proposed for tackling the FJSSP. Recent advances include an investigation of an innovative and promising permutation-based proposal. Accordingly, this paper proposes an Effective Operations Permutation-based Discrete Harmony Search (EOP-DHS) approach for FJSSP with Makespan criterion. The approach adopts an integrated two-part “affectation-sequencing” representation of the solution harmony and a dedicated improvisation operator particularly adapted to the integer-valued and operations permutation-based used coding scheme. Besides, a Modified Intelligent Mutation (MIM) operator is integrated to the adopted framework in order to enhance its overall search ability. Mainly, by balancing maximum machine workload during the overall search process, MIM operator allows essentially maintaining and enhancing the reciprocal equilibrium of diversification and intensification abilities of the proposed EOP-DHS algorithm. Conducted numerical experimentations on 188 benchmarking instances validate the proposal comparatively to a representative set of previously deployed metaheuristic approaches to FJSSP with Makespan criterion. Furthermore, main contribution of the paper is extended with an experimental procedure proving the effectiveness of the adopted permutation-based HS scheme for the resolution of combinatorial optimization problems. Hard benchmarking instances of the classical Job Shop Scheduling Problem (JSSP) are thus considered for exemplification.     

A multiple multilayer perceptron neural network with an adaptive learning algorithm for thyroid disease diagnosis in the internet of medical things

The Journal of Supercomputing - Medical information systems such as Internet of Medical Things (IoMT) are gained special attention over recent years. X-ray and MRI images are important sources of...     

Semi-analytical solution for time-fractional diffusion equation based on finite difference method of lines (MOL)

In this article, we apply the method of lines (MOL) for solving the time-fractional diffusion equations (TFDEs). The use of MOL yields a system of fractional differential equations with the initial value. The solution of this system could be obtained in the form of Mittag–Leffler matrix function. A direct method which computes the Mittag–Leffler matrix by applying its eigenvalues and eigenvectors analytically has been discussed. The direct approach has been applied on one-, two-, and three-dimensional TFDEs with Dirichlet, Neumann, and periodic boundary conditions as well.

     

Finite Element Simulation of Flow Localization During Equal Channel Angular Pressing

The hardening or softening behavior of materials is one of the major factors affecting the deformation homogeneity in work-pieces during processing by equal channel angular pressing. In the present study, the difference between plastic flow behavior and deformation homogeneity of strain hardening and strain softening materials were investigated with the aid of finite element simulation. Results showed that localization of plastic strain occurred in the strain softening materials and fluctuations were observed in the strain distribution along work-piece. In strain hardening materials, a more uniform distribution of plastic strain was obtained compared to strain softening material.     

Hot Deformation Behavior of Beta Titanium Ti-13V-11Cr-3Al Alloy

Hot compression tests were conducted on Ti-13V-11Cr-3Al beta-Ti alloy in the temperature range of 1203 K to 1353 K (930 °C to 1080 °C) and at strain rates between 0.001 and 1 s^?1 The stress–strain curves showed pronounced yield point phenomena at high strain rates and low temperatures. The yield point elongation and flow stresses at the upper and lower yield points were related to the Zener–Hollomon parameter. It was found that dynamic recovery at low strain rates and dynamic recrystallization at high strain rates were the controlling mechanisms of microstructural evolution. The results also showed that strain rate had a stronger influence on the hot deformation behavior than temperature. The microstructural observations and constitutive analysis of flow stress data supported the change in the hot deformation behavior of the studied alloy varies with strain rate. For various applied strain rates, the activation energy for hot deformation was calculated in range of 199.5 to 361.7 kJ/mol. At low strain rates (0.001 and 0.01 s^?1), the value of activation energy was very close to the activation energy for the diffusion of V, Cr, and Al in beta titanium. The higher value of activation energy for deformation at high strain rates (0.1 and 1 s^?1) was attributed to the accumulation of dislocations and the tendency to initiate dynamic recrystallization.     

Prediction of water saturation in a tight gas sandstone reservoir by using four intelligent methods: a comparative study

Neural Computing and Applications - Reservoir water saturation is an important property of tight gas reservoirs. Improper calculation of water saturation leads to remarkable errors in following...     

Sum‐of‐Squares‐Based Finite‐Time Adaptive Sliding Mode Control of Uncertain Polynomial Systems With Input Nonlinearities

This paper proposes a novel adaptive sliding mode control (ASMC) for a class of polynomial systems comprising uncertain terms and input nonlinearities. In this approach, a new polynomial sliding surface is proposed and designed based on the sum‐of‐squares (SOS) decomposition. In the proposed method, an adaptive control law is derived such that the finite‐time reachability of the state trajectories in the presence of input nonlinearity and uncertainties is guaranteed. To do this, it is assumed that the uncertain terms are bounded and the input nonlinearities belong to sectors with positive slope parameters. However, the bound of the uncertain terms is unknown and adaptation law is proposed to effectively estimate the uncertainty bounds. Furthermore, based on a novel polynomial Lyapunov function, the finite‐time convergence of the sliding surface to a pre‐chosen small neighborhood of the origin is guaranteed. To eliminate the time derivatives of the polynomial terms in the stability analysis conditions, the SOS variables of the Lyapunov matrix are optimally selected. In order to show the merits and the robust performance of the proposed controller, chaotic Chen system is provided. Numerical simulation results demonstrate chattering reduction in the proposed approach and the high accuracy in estimating the unknown parameters.     

Time-splitting pseudo-spectral domain decomposition method for the soliton solutions of the one- and multi-dimensional nonlinear Schrödinger equations

In this paper, we study the simulation of nonlinear Schrödinger equation in one, two and three dimensions. The proposed method is based on a time-splitting method that decomposes the original problem into two parts, a linear equation and a nonlinear equation. The linear equation in one dimension is approximated with the Chebyshev pseudo-spectral collocation method in space variable and the Crank–Nicolson method in time; while the nonlinear equation with constant coefficients can be solved exactly. As the goal of the present paper is to study the nonlinear Schrödinger equation in the large finite domain, we propose a domain decomposition method. In comparison with the single-domain, the multi-domain methods can produce a sparse differentiation matrix with fewer memory space and less computations. In this study, we choose an overlapping multi-domain scheme. By applying the alternating direction implicit technique, we extend this efficient method to solve the nonlinear Schrödinger equation both in two and three dimensions, while for the solution at each time step, it only needs to solve a sequence of linear partial differential equations in one dimension, respectively. Several examples for one- and multi-dimensional nonlinear Schrödinger equations are presented to demonstrate high accuracy and capability of the proposed method. Some numerical experiments are reported which show that this scheme preserves the conservation laws of charge and energy.     

An LP-based hyperparameter optimization model for language modeling

In order to find hyperparameters for a machine learning model, algorithms such as grid search or random search are used over the space of possible values of the models’ hyperparameters. These search algorithms opt the solution that minimizes a specific cost function. In language models, perplexity is one of the most popular cost functions. In this study, we propose a fractional nonlinear programming model that finds the optimal perplexity value. The special structure of the model allows us to approximate it by a linear programming model that can be solved using the well-known simplex algorithm. To the best of our knowledge, this is the first attempt to use optimization techniques to find perplexity values in the language modeling literature. We apply our model to find hyperparameters of a language model and compare it to the grid search algorithm. Furthermore, we illustrate that it results in lower perplexity values. We perform this experiment on a real-world dataset from SwiftKey to validate our proposed approach.