In this paper reliable computational methods (RCMs) based on the monomial stan-dard polynomials have been executed to solve the problem of Jeffery-Hamel flow (JHF). In addition, convenient base functions, namely Bernoulli, Euler and Laguerre polynomials, have been used to enhance the reliability of the computational methods. Using such functions turns the problem into a set of solvable nonlinear algebraic system that MathematicaⓇ12 can solve. The JHF problem has been solved with the help of Improved Reliable Computational Methods (I-RCMs), and a review of the methods has been given. Also, published facts are used to make comparisons. As further evidence of the accuracy and dependability of the proposed methods, the maximum error remainder

    In data mining and machine learning methods, it is traditionally assumed that training data, test data, and the data that will be processed in the future, should have the same feature space distribution. This is a condition that will not happen in the real world. In order to overcome this challenge, domain adaptation-based methods are used. One of the existing challenges in domain adaptation-based methods is to select the most efficient features so that they can also show the most efficiency in the destination database. In this paper, a new feature selection method based on deep reinforcement learning is proposed. In the proposed method, in order to select the best and most appropriate features, the essential policies

This paper analysed the effect of electronic internal auditing (EIA) based on the Control Objectives for Information and Related Technologies (COBIT) framework. Organisations must implement an up-to-date accounting information system (AIS) capable of meeting their auditing requirements. Electronic audit risk (compliance assessment, control assurance, and risk assessment) is a development by Weidenmier and Ramamoorti (2006) to improve AIS. In order to fulfil the study’s objectives, a questionnaire was prepared and distributed to a sample comprising 120 employees. The employees were financial managers, internal auditors, and workers involved in the company’s information security departments in the General Company for Electricity D

Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

Optimizing the Access Point (AP) deployment has a great role in wireless applications due to the need for providing an efficient communication with low deployment costs. Quality of Service (QoS), is a major significant parameter and objective to be considered along with AP placement as well the overall deployment cost. This study proposes and investigates a multi-level optimization algorithm called Wireless Optimization Algorithm for Indoor Placement (WOAIP) based on Binary Particle Swarm Optimization (BPSO). WOAIP aims to obtain the optimum AP multi-floor placement with effective coverage that makes it more capable of supporting QoS and cost-effectiveness. Five pairs (coverage, AP deployment) of weights, signal thresholds and received s

In this work, a chemical optical fiber sensor based on Surface Plasmon Resonance (SPR) was designed and implemented using plastic optical fiber. The sensor is used for estimating refractive indices and concentrations of various chemical materials (methanol, distilled water, ethanol, kerosene) as well as for evaluating the performance parameters such as sensitivity, signal to noise ratio, resolution and the figure of merit of the fabricated sensor. It was found that the value of the sensitivity of the optical fiber-based SPR sensor, with 40 nm thick and 10 mm long Au metal film of exposed sensing region, was 3μm/RIU, while the SNR was 0.24, the figure of merit was 20, and the resolution was 0.00066. The sort of optical fiber utilized i

     Drought is a complex phenomenon that has severe impacts on the environment. Vegetation and its conditions are very sensitive to drought effects. This study aimed to monitor and assess the drought severity and its relationships to some ecological variables in ten districts of Erbil Governorate (Kurdistan Region), Iraq, throughout 20 years (1998-2017). The results revealed that droughts frequently hit Erbil throughout the study period. The Landsat time-series- based on Vegetation Condition Index (VCI) significantly correlated with precipitation, Digital Elevation Model (DEM), and latitude. Extreme VCI-based drought area percentages were recorded in 1999, 2000, 2008, and 2011 by 43.4%, 67.9%, 43.3%, and 40.0%, respe

Technological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video strea

Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates