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Numerical investigation to evaluate the effects of gravity and pressure on flame structure and soot formation of turbulent non-premixed methaneair flame

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Propulsion and Power Research 2022年第4期11卷 473-495页

作者： Subrat Garnayak Amjad Ali Pasha Radi Alsulami medhat a.nemitallah Abdul Gani Abdul Jameel Sukanta K.Dash V.Mahendra Reddy School of Energy Science&Engineering Indian Institute of Technology KharagpurWest Bengal721302India Department of Aerospace Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mechanical Engineering King Abdulaziz UniversityJeddah21589Saudi Arabia IRC-Hydrogen and Energy Storage and Mechanical Engineering Department King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Department of Chemical Engineering King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Center for Refining&Advanced Chemicals King Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Department of Mechanical Engineering Indian Institute of Technology KharagpurWest Bengal721302India

In this study,a turbulent non-premixed(diffusion)methane-air flame has been investigated computationally to analyze the influences of pressure and gravity on flame structure and sooting characteristics between 1 and 10 *** simulation has been conducted in a 2-D axisymmetric computational domain using the finite volume-based computational fluid dynamics(CFD)*** interaction of turbulence and chemistry is modeled by considering the steady laminar flamelet model(SLFM)and the GRI Mech 3.0 chemical *** radiative heat transfer calculation is carried out by considering the discrete ordinate(DO)method and the weighted sum grey gas model(WSGGM).The semi-empirical Moss-Brookes model is considered to calculate *** impact of gravity on flame and sooting characteristics are evaluated by comparing the normal-gravity flames with the zero-gravity *** effect of soot and radiation on flame temperature is also *** results show a close agreement with the measurement when both soot and radiation are included in the numerical *** rates of soot formation,surface growth,and oxidation increase with increased operating pressure,regardless of ***-gravity flames have a higher soot volume fraction,a wider soot-containing zone,a higher CO mass fraction,and a lower flame temperature than normal-gravity flames while maintaining constant *** normal-gravity flames,the CO mass fraction decreases with pressure,whereas it increases with pressure rise in flames of zero *** of zero gravity appear taller and broader compared to the flames of normalgravity for a fixed *** increase in pressure significantly reduces the flame length and width in normal-gravity ***,the pressure elevation has little effect on the shape of a zero-gravity *** outcomes of the present study will assist in fully understanding the combustion and sooting characteristics of turbulent diffusion flames that will help design and develop h

关键词： Computational fluid dynamics(CFD) Flamelet Gravity Pressure Soot

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Innovative surfactant of Gemini-type for dissolution mitigation of steel in pickling HCl medium

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Chinese Journal of Chemical Engineering 2021年第6期34卷 125-133页

作者： medhat Kamel Mohamed Hegazy Salah Rashwan Mohamed El Kotb Department of Chemistry Faculty of ScienceSuez Canal UniversityIsmailia 41522Egypt Egyptian Petroleum Research Institute(EPRI) Nasr CityCairo 11727Egypt

A new surfactant of Gemini-type,N,N'-((phthylbis(oxy))bis(ethane-2,1-diyl))bis(N,N-dimethyldodecan-1-aminium bromide)is prepped&*** dissolution suppression impact of the new compound on steel is performed in 1 mol·L^(-1)HCl environment by means of chemical and electrochemical *** prepared surfactant is an agreeable dissolution inhibitor for *** mitigation efficacy rises with the quantity of the *** surfactant belongs to inhibitors of *** adsorption of the synthesized compound followed the Langmuir's *** negative magnitudes of bothΔG_(ads)^(θ) andΔH^(adsθ)indicate that the adsorption process proceeds from its own accord and *** mechanism of adsorption is elucidated by scanning *** is established that the transfer resistance(R_(ct))value rose,where the value of the phase element(CPE)reduced with the amount of synthesized *** to the experimental data arrived by surface tension measurements,the prepared compound is a powerful active agent at the air/water boundary.

关键词： Innovative Gemini surfactant Synthesis Dissolution mitigation Steel Pickling HCl media

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A Computational Study of Cavitation Model Validity Using a New Quantitative Criterion

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Chinese Physics Letters 2012年第6期29卷 193-195页

作者： Hagar Alm El-Din ZHANG Yu-Sheng medhat Elkelawy School of Energy&Power Engineering Huazhong University of Science and TechnologyWuhan 430074

The predictive capability of two different numerical cavitation models accounting for the onset and development of cavitation inside real-sized diesel nozzle holes is assessed on the basis of the referenced experimental *** calculations performed indicate that for the same model assumptions,numerical implementation,discretization scheme,and turbulence grid resolution model,the predictions for differently applied physical cavitation submodels are phenomenologically distinct from each *** present a comparison by applying a new criterion for the quantitative comparison between the results obtained from both cavitation models.

关键词： cavitation Criterion turbulence

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Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

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Computer Systems Science & Engineering 2023年第5期45卷 1531-1544页

作者： Mohsen Eid Tamer medhat Manal E.Ali Department of Mathematics Faculty of ScienceTanta UniversityTantaEgypt Department of Electrical Engineering Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh33516Egypt Department of Physics and Engineering Mathematics Faculty of EngineeringKafrelsheikh UniversityKafrelsheikh33516Egypt

An information system is a type of knowledge representation,and attribute reduction is crucial in big data,machine learning,data mining,and intelligent *** are several ways for solving attribute reduction problems,but they all require a common *** selection of features in most scientific studies is a challenge for the *** working with huge datasets,selecting all available attributes is not an option because it frequently complicates the study and decreases *** the other side,neglecting some attributes might jeopardize data *** this case,rough set theory provides a useful approach for identifying superfluous attributes that may be ignored without sacrificing any significant information;nonetheless,investigating all available combinations of attributes will result in some ***,because attribute reduction is primarily a mathematical issue,technical progress in reduction is dependent on the advancement of mathematical *** the focus of this study is on the mathematical side of attribute reduction,we propose some methods to make a reduction for information systems according to classical rough set theory,the strength of rules and similarity matrix,we applied our proposed methods to several examples and calculate the reduction for each *** methods expand the options of attribute reductions for researchers.

关键词： Rough set reduction strength of rules similarity matrix

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Artificial Fish Swarm for Multi Protein Sequences Alignment in Bioinformatics

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Computers, Materials & Continua 2022年第9期72卷 6091-6106页

作者： medhat A.Tawfeek Saad Alanazi A.A.Abd El-Aziz Department of Computer Science College of Computer and Information SciencesJouf UniversitySaudi Arabia(KSA Department of Computer Science Faculty of Computers and InformationMenoufia UniversityEgypt Department of Information Systems College of Computer and Information SciencesJouf UniversitySaudi Arabia(KSA) Department of Information Systems and Technology Faculty of Graduates Studies and ResearchCairo UniversityEgypt

The alignment operation between many protein sequences or DNAsequences related to the scientific bioinformatics application is very *** is a trade-off in the objectives in the existing techniques of MultipleSequence Alignment (MSA). The techniques that concern with speed ignoreaccuracy, whereas techniques that concern with accuracy ignore speed. Theterm alignment means to get the similarity in different sequences with highaccuracy. The more growing number of sequences leads to a very complexand complicated problem. Because of the emergence;rapid development;anddependence on gene sequencing, sequence alignment has become importantin every biological relationship analysis process. Calculating the numberof similar amino acids is the primary method for proving that there is arelationship between two sequences. The time is a main issue in any alignmenttechnique. In this paper, a more effective MSA method for handling themassive multiple protein sequences alignment maintaining the highest accuracy with less time consumption is proposed. The proposed method dependson Artificial Fish Swarm (AFS) algorithm that can break down the mostchallenges of MSA problems. The AFS is exploited to obtain high accuracyin adequate time. ASF has been increasing popularly in various applicationssuch as artificial intelligence, computer vision, machine learning, and dataintensive application. It basically mimics the behavior of fish trying to getthe food in nature. The proposed mechanisms of AFS that is like preying,swarming, following, moving, and leaping help in increasing the accuracy andconcerning the speed by decreasing execution time. The sense organs that aidthe artificial fishes to collect information and vision from the environmenthelp in concerning the accuracy. These features of the proposed AFS make thealignment operation more efficient and are suitable especially for large-scaledata. The implementation and experimental results put the proposed AFS as afirst choice in th

关键词： Multiple sequence alignment swarm intelligence artificial fish swarm protein sequences

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Applying and Comparison of Chaotic-Based Permutation Algorithms for Audio Encryption

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Computers, Materials & Continua 2021年第6期67卷 3161-3176页

作者： Osama M.Abu Zaid medhat A.Tawfeek Saad Alanazi Department of Computer Science Faculty of Computers and InformationKafrelsheikh UniversityEgypt Department of Computer Science College of Computer and Information SciencesJouf UniversityKSA Department of Computer Science Faculty of Computers and InformationMenoua UniversityEgypt

This research presents,and claries the application of two permutation algorithms,based on chaotic map systems,and applied to a le of speech *** are the Arnold cat map-based permutation algorithm,and the Baker’s chaotic map-based permutation *** algorithms are implemented on the same speech signal ***,both the premier and the encrypted le histograms are documented and *** speech signal amplitude values with time signals of the original le are recorded and plotted against the encrypted and decrypted ***,the original le is plotted against the encrypted le,using the spectrogram frequencies of speech signals with the signal *** permutation algorithms are used to shufe the positions of the speech les signals’values without any changes,to produce an encrypted speech le.A comparative analysis is introduced by using some of sundry statistical and experimental analyses for the procedures of encryption and decryption,e.g.,the time of both procedures,the encrypted audio signals histogram,the correlation coefcient between specimens in the premier and encrypted signals,a test of the Spectral Distortion(SD),and the Log-Likelihood Ratio(LLR)*** outcomes of the different experimental and comparative studies demonstrate that the two permutation algorithms(Baker and Arnold)are sufcient for providing an efcient and reliable voice signal encryption ***,the Arnold’s algorithm gives better results in most cases as compared to the results of Baker’s algorithm.

关键词： Arnold’s cat map chaotic maps permutation algorithms speech encryption Baker’s chaotic map

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High-response n-butanol gas sensor based on ZnO/In_(2)O_(3) heterostructure

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Rare Metals 2023年第1期42卷 198-209页

作者： Zhen-Yu Yuan Fan Yang Hong-Min Zhu Fan-Li Meng medhat Ibrahim College of Information Science and Engineering Northeastern UniversityShenyang110819China Spectroscopy Department National Research CentreGiza12622Egypt

In this study,ZnO/In_(2)O_(3)-heterostructured nanosheets were prepared using a one-step hydrothermal *** effects of ZnO content on the gas-sensing performance were discussed,with ZnO/In_(2)O_(3)-2 exhibiting the highest performance among the prepared *** response of ZnO/In_(2)O_(3)-2 to n-butanol was 302 at 26℃,which was 11.93 times higher than that of pure In_(2)O_(3).Among the eight tested gases,ZnO/In_(2)O_(3)-2 displayed the highest response to ***,the lower detection limit of the ZnO/In_(2)O_(3)nanosheets was reduced from 10×10^(-6)to 0.1×10^(-6)(for pure In_(2)O_(3)nanosheets)toward *** is because the doping of Zn2+increases the number of oxygen vacancies on the sensor surface and allows the formation of an n-n heterostructure between ZnO and In_(2)O_(3),which increases the initial resistance of the sensor.

关键词： High-response N-N heterostructure N-butanol Gas sensor

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Arabic Fake News Detection Using Deep Learning

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Computers, Materials & Continua 2022年第5期71卷 3647-3665页

作者： Khaled M.Fouad Sahar F.Sabbeh Walaa medhat Faculty of Computers&Artificial Intelligence Benha UniversityEgypt University of Jeddah College of Computer Science and EngineeringJeddah21493Saudi Arabia Information Technology and Computer Science Nile UniversityEgypt

Nowadays,an unprecedented number of users interact through social media platforms and generate a massive amount of content due to the explosion of online ***,because user-generated content is unregulated,it may contain offensive content such as fake news,insults,and harassment *** identification of fake news and rumors and their dissemination on social media has become a critical *** have adverse effects on users,businesses,enterprises,and even political regimes and *** of the art has tackled the English language for news and used feature-based *** paper proposes a model architecture to detect fake news in the Arabic language by using only textual *** learning and deep learning algorithms were *** deep learning models are used depending on conventional neural nets(CNN),long short-term memory(LSTM),bidirectional LSTM(BiLSTM),CNN+LSTM,and CNN+*** datasets were used in the experiments,each containing the textual content of Arabic news articles;one of them is reallife *** results indicate that the BiLSTM model outperforms the other models regarding accuracy rate when both simple data split and recursive training modes are used in the training process.

关键词： Fake news detection deep learning machine learning natural language processing

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Efficient Image Captioning Based on Vision Transformer Models

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Computers, Materials & Continua 2022年第10期73卷 1483-1500页

作者： Samar Elbedwehy T.medhat Taher Hamza Mohammed F.Alrahmawy Department of Data Science Faculty of Artificial IntelligenceKafrelsheikh UniversityEgypt Department of Electrical Engineering Faculty of EngineeringKafrelsheikh UniversityEgypt Department of Computer Science Faculty of Computer and Information ScienceMansouraEgypt

Image captioning is an emerging field in machine *** refers to the ability to automatically generate a syntactically and semantically meaningful sentence that describes the content of an *** captioning requires a complex machine learning process as it involves two sub models:a vision sub-model for extracting object features and a language sub-model that use the extracted features to generate meaningful ***-based vision transformers models have a great impact in vision field *** this paper,we studied the effect of using the vision transformers on the image captioning process by evaluating the use of four different vision transformer models for the vision sub-models of the image captioning The first vision transformers used is DINO(self-distillation with no labels).The second is PVT(Pyramid Vision Transformer)which is a vision transformer that is not using convolutional *** third is XCIT(cross-Covariance Image Transformer)which changes the operation in self-attention by focusing on feature dimension instead of token *** last one is SWIN(Shifted windows),it is a vision transformer which,unlike the other transformers,uses shifted-window in splitting the *** a deeper evaluation,the four mentioned vision transformers have been tested with their different versions and different configuration,we evaluate the use of DINO model with five different backbones,PVT with two versions:PVT_v1and PVT_v2,one model of XCIT,SWIN *** results show the high effectiveness of using SWIN-transformer within the proposed image captioning model with regard to the other models.

关键词： Image captioning sequence-to-sequence self-distillation transformer convolutional layer

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Adaptive Deep Learning Model to Enhance Smart Greenhouse Agriculture

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Computers, Materials & Continua 2023年第11期77卷 2545-2564页

作者： medhat A.Tawfeek Nacim Yanes Leila Jamel Ghadah Aldehim Mahmood A.Mahmood Department of Computer Science College of Computer and Information SciencesJouf UniversityP.O.Box 72314SkakaSaudi Arabia Department of Computer Science Faculty of Computers and InformationMenoufia UniversityP.O.Box 6121890MenoufiaEgypt Department of Software Engineering College of Computer and Information SciencesJouf UniversityP.O.Box 72314SkakaSaudi Arabia RIADI Laboratory La Manouba UniversityP.O.Box2010ManoubaTunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems and Technology Faculty of Graduate Studies and ResearchCairo UniversityP.O.Box 3753450GizaEgypt

The trend towards smart greenhouses stems from various factors,including a lack of agricultural land area owing to population concentration and housing construction on agricultural land,as well as water *** study proposes building a full farming adaptation model that depends on current sensor readings and available datasets from different agricultural research *** proposed model uses a one-dimensional convolutional neural network(CNN)deep learning model to control the growth of strategic crops,including cucumber,pepper,tomato,and *** proposed model uses the Internet of Things(IoT)to collect data on agricultural operations and then uses this data to control and monitor these operations in real *** helps to ensure that crops are getting the right amount of fertilizer,water,light,and temperature,which can lead to improved yields and a reduced risk of crop *** dataset is based on data collected from expert farmers,the photovoltaic construction process,agricultural engineers,and research *** experimental results showed that the precision,recall,F1-measures,and accuracy of the one-dimensional CNN for the tested dataset were approximately 97.3%,98.2%,97.25%,and 97.56%,*** new smart greenhouse automation system was also evaluated on four crops with a high turnover *** system has been found to be highly effective in terms of crop productivity,temperature management and water conservation.

关键词： Greenhouse wireless sensor network deep learning Internet of Things strategic crops monitoring smart irrigation

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