Showing papers by "King Fahd University of Petroleum and Minerals published in 2019"
TL;DR: In this paper, the suspension of hydrophobic silica nanoparticles was dip and/or spray coated on the body of a motorcycle, building wall, mini boat, solar cell panel, window glass, cotton shirt, fabric shoes, paper (currency notes), metal, wood, sponges, plastic and marble.
333 citations
TL;DR: The techniques investigated in this paper represent the recent trends in the FPGA-based accelerators of deep learning networks and are expected to direct the future advances on efficient hardware accelerators and to be useful for deep learning researchers.
Abstract: Due to recent advances in digital technologies, and availability of credible data, an area of artificial intelligence, deep learning, has emerged and has demonstrated its ability and effectiveness in solving complex learning problems not possible before. In particular, convolutional neural networks (CNNs) have demonstrated their effectiveness in the image detection and recognition applications. However, they require intensive CPU operations and memory bandwidth that make general CPUs fail to achieve the desired performance levels. Consequently, hardware accelerators that use application-specific integrated circuits, field-programmable gate arrays (FPGAs), and graphic processing units have been employed to improve the throughput of CNNs. More precisely, FPGAs have been recently adopted for accelerating the implementation of deep learning networks due to their ability to maximize parallelism and their energy efficiency. In this paper, we review the recent existing techniques for accelerating deep learning networks on FPGAs. We highlight the key features employed by the various techniques for improving the acceleration performance. In addition, we provide recommendations for enhancing the utilization of FPGAs for CNNs acceleration. The techniques investigated in this paper represent the recent trends in the FPGA-based accelerators of deep learning networks. Thus, this paper is expected to direct the future advances on efficient hardware accelerators and to be useful for deep learning researchers.
308 citations
TL;DR: A review of the recent progress on the synthesis and applications of carbon nanotube (CNT) based membranes in water treatment can be found in this paper, where various synthesis techniques for the preparation of CNT based membranes are discussed.
225 citations
TL;DR: A hybrid feature extraction method with a regularized extreme learning machine (RELM) for developing an accurate brain tumor classification approach and the experimental results proved that the approach is more effective compared with the existing state-of-the-art approaches.
Abstract: Brain cancer classification is an important step that depends on the physician’s knowledge and experience. An automated tumor classification system is very essential to support radiologists and physicians to identify brain tumors. However, the accuracy of current systems needs to be improved for suitable treatments. In this paper, we propose a hybrid feature extraction method with a regularized extreme learning machine (RELM) for developing an accurate brain tumor classification approach. The approach starts by preprocessing the brain images by using a min–max normalization rule to enhance the contrast of brain edges and regions. Then, the brain tumor features are extracted based on a hybrid method of feature extraction. Finally, a RELM is used for classifying the type of brain tumor. To evaluate and compare the proposed approach, a set of experiments is conducted on a new public dataset of brain images. The experimental results proved that the approach is more effective compared with the existing state-of-the-art approaches, and the performance in terms of classification accuracy improved from 91.51% to 94.233% for the experiment of the random holdout technique.
215 citations
TL;DR: In this article, the effects of second order slip on plane Poiseuille nanofluid under the influence of Stefan blowing in a channel are discovered, and the starring role of heat transfer, magnetic field and porosity are all together taken into account.
209 citations
TL;DR: Recent advances on CQDs nanocomposites including their applications in photodegradation of organic pollutants, sensing of heavy metal ions in water and water splitting are discussed critically to narrate the future prospects in this field.
203 citations
TL;DR: A review of the recent trends in the utilization of various nanomaterials as modifiers in electrochemical sensing can be found in this paper, where the authors focus on the recent trend in the use of various materials as modifiers for electrochemical detection.
Abstract: Electroanalytical devices have entered into the entirely new phase due to the utilization of the nanomaterials for the fabrication of electrochemical sensors. Nanomaterials with controlled morphologies and better surface functionalization offer ultrasensitive and selective electrode surfaces for electrochemical detection. The recent literature search on the fabrication of electrochemical sensors clearly reveals a shift toward morphologically controlled and suitably functionalized electrode modifiers to achieve robust electrochemical sensors. This review is specifically focused on the recent trends in the utilization of the various nanomaterials as modifiers in electrochemical sensing. These materials include fullerene, carbon nanotubes, carbon nanohorns, graphene, 3D graphene, carbon quantum dots, nanostructured polymers, and morphologically controlled metal/non-metal nanostructures. Such materials have been applied in the form of wires, nanorods, nanoribbons, core-shell, nanohorns to improve the surface kinetics and specificity of the modified surface toward electroanalytical detection.
186 citations
TL;DR: In this paper, the authors discuss the role of fossil fuels in an increasing generation of pollutants; many of these harmful products have been of serious environmental concern, and the authors propose a solution to the problem.
Abstract: Proliferating energy consumption, particularly of fossil fuels, has led to an increasing generation of pollutants; many of these harmful products have been of serious environmental concern. While e...
179 citations
TL;DR: Most of the reported supercooling mitigation techniques for various types of phase change materials and nanofluids are reviewed in this paper, which are based mainly on adding nucleating agents (such as carbon nanotubes, fine salt particles, and nanoaditives), thickeners, and macroporous structures.
178 citations
TL;DR: In this article, the authors summarize the recent progress of layered double hydroxide (LDH)-containing hybrids as highly efficient adsorbents for dye removal from aqueous phase.
177 citations
TL;DR: In this article, a review of plant biomaterials as metals corrosion inhibitor in different corrosive media is presented, including acidic, basic, neutral, aqueous, geothermal fluid and artificial saliva.
TL;DR: This paper surveys the literature on security aspects of CPSs, and presents some of existing methods for detecting cyber attacks, which are: Denial of service (DoS), deception, and replay attacks.
TL;DR: In this article, a review of the mechanical properties and corrosion behavior of modern Mg-based biocomposites and alloys for biomedical applications is presented. And the corrosion resistance is related to the stability of deposits and their chemical stability in in vitro and in vitro environments.
TL;DR: In this paper, the authors considered a multiuser communication system, in which a single-antenna UAV-BS serves a large number of ground users by employing non-orthogonal multiple access (NOMA).
Abstract: Unmanned aerial vehicles (UAVs) can be deployed as flying base stations (BSs) to leverage the strength of line-of-sight connections and effectively support the coverage and throughput of wireless communication. This paper considers a multiuser communication system, in which a single-antenna UAV-BS serves a large number of ground users by employing non-orthogonal multiple access (NOMA). The max-min rate optimization problem is formulated under total power, total bandwidth, UAV altitude, and antenna beamwidth constraints. The objective of max-min rate optimization is non-convex in all optimization variables, i.e., UAV altitude, transmit antenna beamwidth, power allocation, and bandwidth allocation for multiple users. A path-following algorithm is proposed to solve the formulated problem. Next, orthogonal multiple access (OMA) and dirty paper coding (DPC)-based max-min rate optimization problems are formulated and respective path-following algorithms are developed to solve them. The numerical results show that NOMA outperforms OMA and achieves rates similar to those attained by DPC. In addition, a clear rate gain is observed by jointly optimizing all the parameters rather than optimizing a subset of parameters, which confirms the desirability of their joint optimization.
TL;DR: In this paper, a hybrid renewable energy system (HRESs) consisting of photovoltaic (PV), and self-charging fuel cells (SCFC) is designed for securing electrical energy required to operate brackish water pumping (BWP) and reverse osmosis desalination (RO) plant of 150m3/d-1 for irrigation purposes in remote areas.
TL;DR: In this article, the authors provide a general overview of membrane fouling by minerals usually found in sea and inland water resources and discuss some important aspects of the phenomena itself: different mechanisms; concentration polarization; the major types of mineral scales including their prevalence and characteristics; and consequences of fouling on membrane performance.
TL;DR: In this article, the application of conducting polymers, polymer composites and nanocomposites for corrosion protection of different industrial metal substrates are explored based on reported experimental data and their mechanism of inhibition explained.
02 May 2019
TL;DR: Results from PDP show that, NTETD acted as a mixed type corrosion inhibitor but with principal effect on cathodic corrosion half reactions, and the possible corrosion inhibition mechanism byNTETD has been proposed.
Abstract: There is a high demand of effective and eco-friendly corrosion inhibitor for industrial applications. In an attempt to prepare a benign and effective corrosion inhibitor for acidizing purpose, an imidazoline derivative, N-(2-(2-tridecyl-4,5-dihydro-1H-imidazol-1-yl)ethyl)tetradecanamide (NTETD) was synthesized from myristic acid and diethyleneamine. The characterization of the newly synthesized compound was done using 1H NMR, FTIR, and elemental analysis techniques. NTETD was examined as a corrosion inhibitor for low carbon steel in 15% HCl solution using weight loss, electrochemical impedance spectroscopy (EIS), potentiodynamic polarization (PDP), linear polarization (LPR), scanning electron microscope (SEM), energy dispersive spectroscopy (EDAX), atomic force spectroscopy (AFM), and X-ray photoelectron spectroscopy (XPS) techniques. It was found that, the optimum concentration of NTETD is 300 mg/L. With this concentration, inhibition efficiency above 93% is achievable. Results from PDP show that, NTETD acted as a mixed type corrosion inhibitor but with principal effect on cathodic corrosion half reactions. The calculated value of the adsorption-desorption equilibrium constant (1.015 × 103) reveals a strong bonding between NTETD molecules and the steel surface. The EDAX, FTIR, and XPS results confirm the adsorption of NTETD molecules on the steel surface. SEM and AFM results agree with experimental findings that NTETD is effective in corrosion mitigation of steel in 15% HCl solution. The possible corrosion inhibition mechanism by NTETD has been proposed.
TL;DR: This article reviews the synthesis and application of graphene-based adsorbents for the removal of organic pollutants from water and provides a critical account on synthesis methods, applications, adsorption mechanisms, the figure of merits, and removal performances.
TL;DR: The results of simulations and experimental prototypes show great consistency and prove the capability of the new AFL-MPPT methodology to extract MPPT rapidly and precisely.
Abstract: An adaptive fuzzy logic (FL)-based new maximum power point (MPP) tracking (MPPT) methodology for controlling photovoltaic (PV) systems is proposed, designed, and implemented in this paper. The existing methods for implementing FL-based MPPTs lack for adaptivity with the operating point, which varies in wide range in practical PV systems with operating irradiance and ambient temperature. The new proposed adaptive FL-based MPPT (AFL-MPPT) algorithm is simple, accurate, and provides faster convergence to optimal operating point. The effectiveness and feasibility verifications of the proposed AFL-MPPT methodology are validated with considering various operating conditions at slow and fast change of solar radiation. In addition, the simplified implementation of the proposed algorithm is carried out using C-block in PSIM software environment, wherein the proposed algorithm and system are simulated. Additionally, experimental results are performed using a floating-point digital signal processing (DSP) controller (TMS320F28335) for verifying the feasibility of the proposed AFL-MPPT methodology. The results of simulations and experimental prototypes show great consistency and prove the capability of the new AFL-MPPT methodology to extract MPPT rapidly and precisely. The new proposed AFL-MPPT method achieves accurate output power of the PV system with smooth and low ripple. In addition, the new proposed AFL-MPPT method benefits fast dynamics and it reaches steady state within 0.01 s.
TL;DR: A literature review on the selected applications of renewable resource and power forecasting models to facilitate the optimal integration of renewable energy in power systems and the impact of forecasting improvement on optimal power system design and operation is presented.
Abstract: This paper presents a literature review on the selected applications of renewable resource and power forecasting models to facilitate the optimal integration of renewable energy (RE) in power systems. This review is drafted on the basis of the selected high quality research publications from the past decade. Although the development of forecast models for RE generation, i.e., wind and solar energy, is a well-researched area, however, the performance of these models is usually evaluated using statistical error metrics. With regard to application, determining the optimality of accurate forecasts in terms of system economics and major planning aspects is an emerging phenomenon, that chalks out the main subject area of this survey. Specifically, the application domains include: 1) optimal power system dispatch (unit commitment, generation scheduling, economic dispatch), 2) optimal sizing of energy storage system, 3) energy market policies and profit maximization of market participants, 4) reliability assessment, and 5) optimal reserve size determination in power systems. The application-oriented review on these vital areas can be used by the power sector for familiarization with the recent trends and for analyzing the impact of forecasting improvement on optimal power system design and operation.
TL;DR: In this article, the authors review the emerging research in the field of VLC networks and lay out the challenges, technological solutions, and future work predictions, and propose several open research problems to optimize the various VLC network by maximizing either the sum rate, fairness, energy efficiency, secrecy rate, or harvested energy.
Abstract: The evolving explosion in high data rate services and applications will soon require the use of untapped, abundant unregulated spectrum of the visible light for communications to adequately meet the demands of the fifth-generation (5G) mobile technologies. Radio-frequency (RF) networks are proving to be too scarce to cover the escalation in data rate services. Visible light communication (VLC) has emerged as a great potential solution, either in replacement of, or a complement to, existing RF networks, to support the projected traffic demands. Despite the prolific advantages of VLC networks, VLC faces many challenges that must be resolved in the near future to achieve full standardization and to be integrated to future wireless systems. Here, we review the emerging research in the field of VLC networks and lay out the challenges, technological solutions, and future work predictions. Specifically, we first review the VLC channel capacity derivation and discuss the performance metrics and the associated variables. The optimization of VLC networks are also discussed, including resources and power allocation techniques, user-to-access point (AP) association and APs-to-clustered-users-association, APs coordination techniques, non-orthogonal multiple access (NOMA) VLC networks, simultaneous energy harvesting and information transmission using the visible light, and the security issues in VLC networks. Finally, we propose several open research problems to optimize the various VLC networks by maximizing either the sum rate, fairness, energy efficiency, secrecy rate, or harvested energy.
TL;DR: In this paper, the authors investigated the wind characteristics of Jhampir (district Thatta Sindh, Pakistan) are investigated and wind energy potential is determined using 10-min averaged wind speed data obtained from Alternate Energy Development Board of Pakistan for a period of three years (2007-2010).
TL;DR: In this article, a two-dimensional and quasi-three-dimensional shear deformation model is proposed to model the free vibration of FG plates resting on elastic foundations using a new shear strain shape function.
Abstract: The aim of this work is to establish a two dimensional (2D) and quasi three dimensional (quasi-3D) shear deformation theories, which can model the free vibration of FG plates resting on elastic foundations using a new shear strain shape function. The proposed theories have a novel displacement field which includes undetermined integral terms and contains fewer unknowns with taking into account the effects of both transverse shear and thickness stretching. The mechanical properties of the plates are assumed to vary through the thickness according to a power law distribution in terms of the volume fractions of the constituents. The elastic foundation parameters are introduced in the present formulation by following the Pasternak (two-parameters) mathematical model. Hamilton's principle is employed to determine the equations of motion. The closed form solutions are derived by using Navier's method and then fundamental frequencies are obtained by solving the results of eigenvalue problems. The efficiency of the proposed theory is ascertained by comparing the results of numerical examples with the different 2D, 3D and quasi-3D solutions found in literature.
TL;DR: In this paper, the authors present a collection of earlier works that have been carried out on the topic of corrosion inhibitors derived from bi-component reactions (BCRs) and multistep reactions (MCRs) for metals and alloys.
TL;DR: In this article, the basic theories of molecular dynamics and Monte Carlo simulations are highlighted and some mechanistic and energetic information on how organic corrosion inhibitors interact with iron and copper metals are provided.
Abstract: It is difficult to understand the atomistic information on the interaction at the metal/corrosion inhibitor interface experimentally which is a key to understanding the mechanism by which inhibitors prevent the corrosion of metals. Atomistic simulations (molecular dynamics and Monte Carlo) are mostly performed in corrosion inhibition research to give deeper insights into the mechanism of inhibition of corrosion inhibitors on metal surfaces at the atomic and molecular time scales. A lot of works on the use of molecular dynamics and Monte Carlo simulation to investigate corrosion inhibition phenomenon have appeared in the literature in recent times. However, there is still a lack of comprehensive review on the understanding of corrosion inhibition mechanism using these atomistic simulation methodologies. In this review paper, we first of all introduce briefly some important molecular modeling simulations methods. Thereafter, the basic theories of molecular dynamics and Monte Carlo simulations are highlighted. Several studies on the use of atomistic simulations as a modern tool in corrosion inhibition research are presented. Some mechanistic and energetic information on how organic corrosion inhibitors interact with iron and copper metals are provided. This atomic and molecular level information could aid in the design, synthesis and development of new and novel corrosion inhibitors for industrial applications.
TL;DR: The most widely used form of liquid phase microextraction (DLLME) is the DLLME-LPME as discussed by the authors, which is a miniaturized version of classical liquid-liquid extraction.
TL;DR: In this article, the effects of heat transfer and Hall current on the sinusoidal motion of solid particles through a planar channel has been discussed and the walls of the channel are considered as compressive barriers.
Abstract: In this paper, the effects of heat transfer and Hall current on the sinusoidal motion of solid particles through a planar channel has been discussed. The walls of the channel are considered as comp...
TL;DR: A resilience-driven multi-objective restoration model using mixed-integer programming that aims to maximize the resilience of the system of interdependent infrastructure networks while minimizing the total cost associated with the restoration process is proposed.
TL;DR: In this paper, the authors describe the synthesis of cobalt-oxide nanoparticles by simple precipitation technique and their environmental application, and the nano-adsorbent displayed its efficiency in methyl orange removal from aqueous solution.