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Disturbance Evaluation in Power System Based on Machine Learning

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Computers, Materials & Continua 2022年第4期71卷 231-254页

作者： Emad M.Ahmed mohamed A.Ahmed Ziad M.ali Imran Khan Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72388Al-JoufSaudi Arabia Department of Electrical Engineering College of EngineeringPrince Sattam bin Abdulaziz UniversityWadi Addawaser11991Saudi Arabia Department of Electrical Engineering Aswan Faculty of EngineeringAswan UniversityAswan81542Egypt Department of Electrical Engineering University of Engineering and Technology PeshawarPakistan

The operation complexity of the distribution system increases as a large number of distributed generators(DG)and electric vehicles were introduced,resulting in higher demands for fast online reactive power *** a power system,the characteristic selection criteria for power quality disturbance classification are not *** classification effect and efficiency needs to be improved,as does the generalization *** order to categorize the quality in the power signal disturbance,this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality ***,a multi-label classification algorithm based on rating is proposed to understand the relationship between the labels and identify the various power quality *** two algorithms are combined to construct a multi-label classification model based on a multi-level extreme learning machine,and the optimal network structure of the multi-level extreme learning machine as well as the optimal multi-label classification threshold are *** proposed method can be used to classify the single and compound power quality disturbances with improved classification effect,reliability,robustness,and anti-noise performance,according to the experimental *** hamming loss obtained by the proposed algorithm is about 0.17 whereas ML-RBF,SVM and ML-KNN schemes have 0.28,0.23 and 0.22 respectively at a noise intensity of 20 *** average precision obtained by the proposed algorithm 0.85 whereas the ML-RBF,SVM and ML-KNN schemes indicates 0.7,0.77 and 0.78 respectively.

关键词： Optimal power flow optimization algorithm deep learning power systems

Experimental Testing of Cellular Construction Materials Containing Flax Particles

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Fluid Dynamics & Materials Processing 2023年第3期19卷 723-741页

作者： Hamadou-ali mohamed Benazzouk Amar Haïkel Ben Hamed Arash Jamali Laboratoire des Technologies Innovantes(UR-UPJV 3899)-UPJV Amiens80000France Plateforme de Microscopie Electronique-UPJV HUB de l’Energie80039Amiens

The feasibility of a sustainable non-autoclaved cellular concrete,based on flax vegetable co-products,for the production of usable specimen in the lightweight construction field,has been investigated *** produced specimen,containing various volume ratios of flax particles with respect to preformulatd Tradical PF70 lime binder of 0,1,and 2,were lightened by creating a porous structure in the matrix through the addition of 0.3%*** powder(able to react with calcium hydroxide from the binder and result in microscopic air-bubbles).Fresh and hardened specimen properties,including hydration,fresh density,porosity,hardened density,compressive and flexural strengths,toughness energy,and dry thermal conductivity at different temperatures,were assessed for varying flax-to-binder *** have shown that the addition of Aluminum powder leads to restrain the setting time delay of binder-based ***,the hardened material displays a significant decrease in specimen density,thereby resulting in a compressive strength level compatible with that required in the cellular construction materials *** also highlighted the ability of added flax to induce a change in the specimen from brittle to ductile ***,a high degree of thermal insulation can be achieved,which makes the cellular specimen based on flax particle suitable as insulated-bearing walls material.

关键词： Flax particles cellular concrete lightening porous structure physico-mechanical properties thermal conductivity

Preparation of composite tubular grafts for vascular repair via electrospinning

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Progress in Natural Science:Materials International 2012年第2期22卷 108-114页

作者： Salem S.Al-deyab mohamed El-Newehy Petrochemical Research Chair Department of ChemistryCollege of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of Chemistry Faculty of ScienceTanta UniversityTanta 31527Egypt

A novel type of composite vascular graft was developed via electrospinning in the present *** and chitosan were blended to form the inner and outer ***(l-lactide-co-caprolactone)(P(LLA-CL))was selected as a material for the middle layer of composite vascular *** morphology and diameter of the composite grafts were studied by Scanning Electron Microscope(SEM).The results of mechanical tests showed that the composite scaffolds provided the whole grafts with better strength and flexibility compared with blended grafts,mainly due to the fact that the middle layer was P(LLA-CL).Cell viability studies with endothelial cells suggested a prompt adhesion and proliferation duo to the fact that the outer layer was collagen and *** microscopy demonstrated that a monolayer of endothelial cells could be formed after 7 days of *** above results indicated that the composite fibrous scaffolds could be a good candidate for blood vessel repair by electrospinning method.

关键词： Electrospinning Composite Vascular graft Endothelial cell Nanofiber

Comparative phytochemical,thin layer chromatographic profiling and antioxidant activity of extracts from some Indian herbal drugs

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Journal of Bioresources and Bioproducts 2022年第2期7卷 46-52页

作者： Md Sohail Akhtar mohamed Rafiullah Wegdan Aly Shehata Amzad Hossain Mohammed ali School of Pharmacy College of Pharmacy and NursingUniversity of NizwaNizwaOman Phytochemistry Research Laboratory Department of Pharmacognosy and PhytochemistryFaculty of PharmacyJamia HamdardNew DelhiIndia Strategic Center for Diabetes Research College of MedicineKing Saud UniversityRiyadhSaudi Arabia

Natural antioxidants play a significant role to prevent cell breaking and regenerate *** plants native to India named dwarf morning-glory(Evolvulus alsinoides),Indian banyan(Ficus bengalensis)and chicory(Chicorium intybus)are used as medicine in India traditionally to treat *** aim of this study is to evaluate and compare the antioxidant activity as well as to compare phytochemical profiles of the aqueous extracts of the selected three *** dried plant powder was extracted with ethanol individually by using the Soxhlet method for eight hours and the solvent was evaporated under reduced ***,the air-dried powder was ex-tracted with water,and the water was *** thin layer chromatography(TLC)profile of the extracts was determined by using TLC densitometer and the antioxidant activity was deter-mined by the conventional 2,2-diphenyl-1-picrylhydrazyl(DPPH)*** TLC profile shows that there are no similarities of retention factor(R f)values among the plant extracts which means all three plants contain different chemical *** antioxidant activities of the aqueous extracts at different concentrations show different antioxidant *** inhibition is dose dependent,as doses are increasing then percentage inhibition is also increasing for all three plant *** the selected plants,the highest activity was found in *** and the lowest was in *** order of the antioxidant activity among the selected plants was ***<***<*** on the TLC profile and antioxidant activities,the highest activity of the selected plant species was evaluated.

关键词： Indian drug Thin layer chromatography(TLC)profile Plant extract Antioxidant activity

Machine Learning-Based Channel State Estimators for 5G Wireless Communication Systems

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工程与科学中的计算机建模（英文） 2023年第4期135卷 755-778页

作者： mohamed Hassan Essai ali Fahad Alraddady Mo’ath Y.Al-Thunaibat Shaima Elnazer Department of Electrical Engineering Faculty of EngineeringAl-Azhar UniversityQena83513Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Management Information Systems Taif UniversityTaif21944Saudi Arabia

For a 5G wireless communication system,a convolutional deep neural network(CNN)is employed to synthesize a robust channel state estimator(CSE).The proposed CSE extracts channel information from transmit-and-receive pairs through offline training to estimate the channel state ***,it utilizes pilots to offer more helpful information about the communication *** proposedCNN-CSE performance is compared with previously published results for Bidirectional/long short-term memory(BiLSTM/LSTM)NNs-based *** CNN-CSE achieves outstanding performance using sufficient pilots only and loses its functionality at limited pilots compared with BiLSTM and LSTM-based *** three different loss function-based classification layers and the Adam optimization algorithm,a comparative study was conducted to assess the performance of the presented DNNs-based *** BiLSTM-CSE outperforms LSTM,CNN,conventional least squares(LS),and minimum mean square error(MMSE)*** addition,the computational and learning time complexities for DNN-CSEs are *** estimators are promising for 5G and future communication systems because they can analyze large amounts of data,discover statistical dependencies,learn correlations between features,and generalize the gotten knowledge.

关键词： DLNNs channel state estimator 5G and beyond communication systems robust loss functions

A Compact 28 GHz Millimeter Wave Antenna for Future Wireless Communication

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Computers, Materials & Continua 2022年第7期72卷 301-314页

作者： Shahid Khan Adil Bashir Haider ali Abdul Rauf mohamed Marey Hala Mostafa Ikram Syed LCOMS ASECUniversity de LorraineMetz57070France Department of Electrical and Computer Engineering Comsats University IslamabadAbbottabad Campus22060Pakistan Electrical Engineering Department Bahauddin Zakariya UniversityMultan60800Pakistan Department of Electronics Technology University of TechnologyNowshera24100Pakistan Department of Electrical Engineering National University of Sciences and TechnologyH-12Islamabad44000Pakistan Smart Systems Engineering Laboratory College of EngineeringPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Computer Software Engineering Military College of SignalsNational University of Sciences and TechnologyIslamabad44000Pakistan

This article presents a novel modified chuck wagon dinner bell shaped millimeter wave(mm-wave)antenna at 28 *** proposed design has ultra-thin Rogers 5880 substrate with relative permittivity of *** design consists of T shaped resonating elements and two open ended side *** desired 28 GHz frequency response is achieved by careful parametric modeling of the proposed *** maximum achieved single element gain at the desired resonance frequency is 3.45 *** efficiency of the proposed design over the operating band is more than 88%.The impedance bandwidth achieved for−10 dB reference value is nearly 2.9 *** proposed antenna is transformed into four element linear array which increases the gain up to 10.5 *** fabricated prototype is tested for the measured *** is observed that measured results closely match the simulated *** considering its simple structure and focused radiation patterns,the proposed design is well suited for IoT(Internet of Things),mmWave microwave sensing,5G and future RF(Radio Frequency)frontends.

关键词： RF front-ends mmWave partial ground plane 28 GHz IoT 5G antenna

Improving Performance of Recurrent Neural Networks Using Simulated Annealing for Vertical Wind Speed Estimation

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Energy Engineering 2023年第4期120卷 775-789页

作者： Shafiqur Rehman HilalH.Nuha ali Al Shaikhi Satria Akbar mohamed Mohandes Interdisciplinary Research Center for Renewable Energy and Power Systems(IRC-REPS) KFUPMDhahran31261Saudi Arabia HUMIC Engineering School of ComputingTelkom UniversityBandung40257Indonesia Electrical Engineering Department King Fahd University of Petroleum&Minerals(KFUPM)Dhahran31261Saudi Arabia

An accurate vertical wind speed(WS)data estimation is required to determine the potential for wind farm *** general,the vertical extrapolation of WS at different heights must consider different parameters fromdifferent locations,such as wind shear coefficient,roughness length,and atmospheric *** novelty presented in this article is the introduction of two steps optimization for the Recurrent Neural Networks(RNN)model to estimate WS at different heights using measurements from lower *** first optimization of the RNN is performed to minimize a differentiable cost function,namely,mean squared error(MSE),using the Broyden-Fletcher-Goldfarb-Shanno ***,the RNN is optimized to reduce a non-differentiable cost function using simulated annealing(RNN-SA),namely mean absolute error(MAE).Estimation ofWS vertically at 50 m height is done by training RNN-SA with the actualWS data a 10–40 m *** estimatedWS at height of 50 m and the measured WS at 10–40 heights are further used to train RNN-SA to obtain WS at 60 m *** procedure is repeated continuously until theWS is estimated at a height of 180 *** RNN-SA performance is compared with the standard RNN,Multilayer Perceptron(MLP),Support Vector Machine(SVM),and state of the art methods like convolutional neural networks(CNN)and long short-term memory(LSTM)networks to extrapolate theWS *** estimated values are also compared with realWS dataset acquired using LiDAR and tested using four error metrics namely,mean squared error(MSE),mean absolute percentage error(MAPE),mean bias error(MBE),and coefficient of determination(R2).The numerical experimental results show that the MSE values between the estimated and actualWS at 180mheight for the RNN-SA,RNN,MLP,and SVM methods are found to be 2.09,2.12,2.37,and 2.63,respectively.

关键词： Vertical wind speed estimation recurrent neural networks simulated annealing multilayer perceptron support vector machine

A review on the mechanisms of low salinity water/surfactant/nanoparticles and the potential synergistic application for c-EOR

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Petroleum Research 2023年第3期8卷 324-337页

作者： Stanley Sim Sze Lim Henry Elochukwu Jobrun Nandong Ziad Bennour mohamed ali Hamid Chemical and Energy Department Faculty of Engineering and ScienceCurtin University MalaysiaMalaysia School of Engineering and Physical Sciences Heriot Watt UniversityMalaysia

Chemical enhanced oil recovery(c-EOR)is a conventional and promising strategy to recover oil from reservoir techniques such as low salinity water flooding(LSWF),surfactant flooding,alkaline flooding,polymers flooding,and nanofluid *** use of various types of chemical materials for c-EOR method has recently attracted the attention of the oil and gas *** primary objective of this review work is to explore the synergy of low salinity water/surfactant/nanoparticle flooding for effective c-EOR method and investigate the mechanism behind these *** advantages of combining these chemical materials for c-EOR methods is also *** and limitations of this synergy and their economic feasibility for additional oil recovery and potential return on investment are *** have been successfully used in various applications in several industries and have also shown good application for EOR in terms of wettability *** contributes to wettability alteration,while surfactant contributes to wettability alteration and interfacial tension(IFT)***,fines migration caused by LSWF and nanoparticle agglomeration can cause formation damage,while excessive surfactant adsorption can lead to cost overrun on surfactant *** the characteristics of reservoir formation mineralogy and appropriate nanoparticle type,size,and concentration can be used to resolve this *** synergy of LSWF and nanoparticles in alkaline medium can serve as sacrificial agent to reduce excessive surfactant ***,the appropriate synergistic formulation of LSFW/surfactant/nanoparticle can improve additional oil recovery and support return on investment for c-EOR projects.

关键词： Surfactant Low salinity water Nanoparticles Nanofluid Enhanced oil recovery

UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

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Computers, Materials & Continua 2022年第9期72卷 5999-6013页

作者： Rania M Tawfik Hazem A.A.Nomer M.Saeed Darweesh ali Wagdy mohamed Hassan Mostafa Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGiza12677Egypt School of Information Technology and Computer Science(ITCS) Nile UniversityGiza12677Egypt Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Department of Mathematics and Actuarial Science School of Science and EngineeringThe American University in CairoEgypt Electronics and Communications Engineering Department Cairo UniversityEgypt University of Science and Technology Nanotechnology and Nanoelectronics ProgramZewal City of Science and TechnologyOctober Gardens6th of OctoberGiza12578Egypt

Unmanned Aerial Vehicles(UAVs)provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things(NB-IoT)***,the UAV’s deployment optimization,including locations of the UAV’s stop points,is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection *** this regard,this paper proposes GainingSharing Knowledge(GSK)algorithm for optimizing the UAV’s *** GSK,the number of UAV’s stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire *** superiority of using GSK in the tackled problem is verified by simulation in seven *** provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same ***,the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.

关键词： NB-IoT UAV GSK stop points optimization