Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

Local calibration of rigid pavement performance models using resampling methods

The performance prediction models in the Pavement-ME design software are nationally calibrated using in-service pavement material properties, pavement structure, climate and truck loadings, and performance data obtained from the Long-Term Pavement Performance programme. The nationally calibrated models may not perform well if the inputs and performance data used to calibrate those do not represent the local design and construction practices. Therefore, before implementing the new M-E design procedure, each state highway agency (SHA) should evaluate how well the nationally calibrated performance models predict the measured field performance. The local calibrations of the Pavement-ME performance models are recommended to improve the performance prediction capabilities to reflect the unique conditions and design practices. During the local calibration process, the traditional calibration techniques (split sampling) may not necessarily provide adequate results when limited number of pavement sections are available. Consequently, there is a need to employ statistical and resampling methodologies that are more efficient and robust for model calibrations given the data related challenges encountered by SHAs. The main objectives of the paper are to demonstrate the local calibration of rigid pavement performance models and compare the calibration results based on different resampling techniques. The bootstrap is a non-parametric and robust resampling technique for estimating standard errors and confidence intervals of a statistic. The main advantage of bootstrapping is that model parameters estimation is possible without making distribution assumptions. This paper presents the use of bootstrapping and jackknifing to locally calibrate the transverse cracking and IRI performance models for newly constructed and rehabilitated rigid pavements. The results of the calibration show that the standard error of estimate and bias are lower compared to the traditional sampling methods. In addition, the validation statistics are similar to that of the locally calibrated model, especially for the IRI model, which indicates robustness of the local model coefficients.     

Artificial Neural Networks for Prediction of COVID-19 in Saudi Arabia

In this study, we have proposed an artificial neural network (ANN) model to estimate and forecast the number of confirmed and recovered cases of COVID-19 in the upcoming days until September 17, 2020. The proposed model is based on the existing data (training data) published in the Saudi Arabia Coronavirus disease (COVID-19) situation—Demographics. The Prey-Predator algorithm is employed for the training. Multilayer perceptron neural network (MLPNN) is used in this study. To improve the performance of MLPNN, we determined the parameters of MLPNN using the prey-predator algorithm (PPA). The proposed model is called the MLPNN–PPA. The performance of the proposed model has been analyzed by the root mean squared error (RMSE) function, and correlation coefficient (R). Furthermore, we tested the proposed model using other existing data recorded in Saudi Arabia (testing data). It is demonstrated that the MLPNN-PPA model has the highest performance in predicting the number of infected and recovering in Saudi Arabia. The results reveal that the number of infected persons will increase in the coming days and become a minimum of 9789. The number of recoveries will be 2000 to 4000 per day.     

On Structural,Optical, and Electrical Properties of Chromium Oxide Cr2O3 Thin Film for Applications

Protection of Metals and Physical Chemistry of Surfaces - Chromium oxide thin films were grown on Al2O3 substrates by ablating a pure Cr2O3 target using a KrF excimer laser. The energy density on...     

Hydrogen accumulation in graphite and etching of graphite on hydrogen desorption

Studies of Atomic Hydrogen accumulation in highly oriented pyrolytical graphite (HOPG) have been performed using scanning tunnelling microscope (STM) and atomic force microscope (AFM). It is found that after intercalation atomic hydrogen is stored among graphene layers in H₂ gas form, captured inside graphene blisters. On desorption of hydrogen, some lateral etching of upper graphene layers takes place. Significant information about intake, retention and possibility of manifold accumulation of hydrogen in HOPG has been found.     

A group theoretic approach to construct cryptographically strong substitution boxes

In this paper, we present a method to construct a substitution box used in encryption applications. The proposed algorithm for the construction of substitution box relies on the linear fractional transform method. The design methodology is simple, while the confusion-creating ability of the new substitution box is complex. The strength of the proposed substitution box is evaluated, and an insight is provided to quantify the confusion-creating ability. In addition, tests are performed to assess the vulnerability of the encrypted data to algebraic and statistical attacks. The substitution box is critically analyzed by strict avalanche criterion, bit independent criterion, differential approximation probability test, linear approximation probability test, non-linearity test, and majority logic criterion. The performance of the proposed substitution box is also compared with those of some of the well-known counterparts including AES, APA, Gray, S₈, Skipjack, Xyi, and prime of residue substitution boxes. It is apparent that the performance, in terms of confusion-creating ability, of the new substitution box is better than those of some of the existing non-linear components used in encryption systems. The majority logic criterion is applied to these substitution boxes to further evaluate the strength and usefulness.     

Optimization of municipal solid waste (MSW) disposal in Saudi Arabia

Municipal solid waste (MSW) mainly comprises organics, paper, glass, plastics, metals, wood, etc. Rapid industrialization, high population growth rate, and fast urbanization have resulted in increased levels of pollution and MSW in Saudi Arabia. The amount of waste has been steadily increasing due to increasing human population and urbanization. Recovery refers to materials removed from the waste stream for the purpose of recycling and/or composting. There are various options available to convert solid waste to energy. Mainly, the following types of technologies are available: (1) sanitary landfill, (2) incineration, (3) pyrolysis, (4) gasification, and (5) anaerobic digestion. An integrated MSW disposal policy comprises (1) reduction of MSW source, (2) reuse of MSW, (3) recycling of MSW, (4) landfill and gas-to-energy conversion, and (5) MSW-to-energy conversion. Traditionally, MSWs have been disposed in landfills. Landfill is the most inexpensive waste disposal option. The main MSW disposal policies and barriers have been concluded in this study.     

Mixed Convection of Water at 4 °C Along a Wedge with Variable Surface Temperature in a Porous Medium

In this study, the mixed convection of water at 4 °C along a wedge in a porous medium is investigated numerically using a finite difference method. To explore the effect of mixed convection, both forced and free convection-dominated regimes are considered. Non-similarity solutions are obtained for the variable walltemperature boundary condition. Velocity and temperature profiles as well as local dimensionless skin friction and the Nusselt number are obtained and compared with available numerical results for various values of different parameters. The wedge angle geometry parameter m and mixed convection parameter ξ ranged from 0 to 1 in both regimes, whereas different values of λ are considered for the purpose of comparison of heat transfer results.