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Effect of Some Heterocyclic derivatives on the Removal of Copper Ions from Wastewater by Cementation

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Journal of materials Science & Technology 2004年第5期20卷 539-546页

作者： A.A.Taha m.G.marei d.E.abd el-khalek department of Chemistry Faculty of ScienceUniversity of AlexandriaAlexandriaEgyptDepartment of ChemistryFaculty of ScienceUniversity of AlexandriaAlexandriaEgyptDepartment of ChemistryFaculty of ScienceUniversity of AlexandriaAlexandriaEgypt

Removal of copper ions from copper sulphate solutions on a rotating zinc rod in absence and in presence of 3(2H)-furanones and 4H-pyran-4-one derivatives was investigated experimentally. Variables studied were initial copper ions concentration, rotational speed of the zinc rod, temperature and concentration of organic additives. It was found that cementation reaction is first order in presence and in absence of additives. Increasing concentration of initial copper ions, rotational speed of the zinc rod and temperature were found to increase the rate of cementation. In presence of organic additives an enhancement of the rate was observed, except in presence of methoxyfuranone the rate was found to decrease by an amount ranging from 11.74% to 33.79%. Rate acceleration or inhibition is associated mainly with changes in the structure of the additives as well as its concentration. The apparent activation energy for the cementation process in presence of different additives was estimated and was found to be ranged between 11.8 kJ/mol and 25.95 kJ/mol. These values suggest that the copper removal process in presence of these additives is controlled by diffusion. A scanning electron microscopy study of copper deposits obtained in presence of tolylfuranone, phenylpyrone and methoxyfuranone correlate with their behaviour during the kinetic study. different reaction conditions and the physical properties of solutions were studied to obtain dimensionless correlation among all these parameters. It was found that on applying cementation reaction on a sample from industrial wastewater in presence of phenylpyrone about 91.9% of Cu2+ are removed.

关键词： Cementation of copper Furanone and pyrone derivatives

Efficient deep-Learning-Based Autoencoder denoising Approach for medical Image diagnosis

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Computers, materials & Continua 2022年第3期70卷 6107-6125页

作者： Walid el-Shafai Samy abd el-Nabi el-Sayed mel-Rabaie Anas m.Ali Naglaa F.Soliman Abeer d.Algarni Fathi E.abd el-Samie department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Effective medical diagnosis is dramatically expensive,especially in third-world *** of the common diseases is pneumonia,and because of the remarkable similarity between its types and the limited number of medical images for recent diseases related to pneumonia,themedical diagnosis of these diseases is a significant ***,transfer learning represents a promising solution in transferring knowledge from generic tasks to specific ***,experimentation and utilization of different models of transfer learning do not achieve satisfactory *** this study,we suggest the implementation of an automatic detectionmodel,namelyCAdTra,to efficiently diagnose pneumonia-related *** model is based on classification,denoising autoencoder,and transfer ***,pre-processing is employed to prepare the medical *** depends on an autoencoder denoising(Ad)algorithm with a modified loss function depending on a Gaussian distribution for decoder output to maximize the chances for recovering inputs and clearly demonstrate their features,in order to improve the diagnosis ***,classification is performed using a transfer learning model and a four-layer convolution neural network(FCNN)to detect *** proposed model supports binary classification of chest computed tomography(CT)images and multi-class classification of chest X-ray ***,a comparative study is introduced for the classification performance with and without the denoising *** proposed model achieves precisions of 98%and 99%for binary classification and multi-class classification,respectively,with the different ratios for training and *** demonstrate the efficiency and superiority of the proposed CAdTra model,it is compared with some recent state-of-the-art CNN *** achieved outcomes prove that the suggested model can help radiologists to detect pneumonia-related diseases and improve the diagnostic efficiency compared to the exis

关键词： medical images CAdTra Ad CT and X-ray images autoencoder

Congruence Pairs of decomposable mS-Algebras

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Chinese Annals of mathematics,Series B 2021年第4期42卷 561-574页

作者： Sanaa el-ASSAR abd el-mohsen BAdAWY department of mathematics Faculty of ScienceTanta UniversityTantaEgypt

In this paper,the authors first introduce the concept of congruence pairs on the class of decomposable mS-algebras generalizing that for principal mS-algebras(see[13]).They show that every congruence relationθon a decomposable mS-algebra L can be uniquely determined by a congruence pair(θ_(1),θ_(2)),whereθ_(1)is a congruence on the de morgan subalgebra L^(∞)of L andθ_(2)is a lattice congruence on the sublattice d(L)of *** obtain certain congruence pairs of a decomposable mS-algebra L via central elements of ***,they characterize the permutability of congruences and the strong extensions of decomposable mS-algebras in terms of congruence pairs.

关键词： mS-Algebras decomposable mS-algebras Congruence pairs Strong extension Permutability Congruence lattices

Effects of rotation and magnetic field on the nonlinear peristaltic flow of a second-order fluid in an asymmetric channel through a porous medium

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Chinese Physics B 2013年第7期22卷 303-313页

作者： A. m. abd-Alla S. m. Abo-dahab H. d. el-Shahrany department of mathematics Faculty of ScienceTaif University department of mathematics Faculty of Science department of mathematics Faculty of ScienceSouth Valley University

In this paper, the effects of both rotation and magnetic field of the peristaltic transport of a second-order fluid through a porous medium in a channel are studied analytically and computed numerically. The material is represented by the constitutive equations for a second-order fluid. Closed-form solutions under the consideration of long wavelength and low Reynolds number is presented. The analytical expressions for the pressure gradient, pressure rise, friction force, stream function, shear stress, and velocity are obtained in the physical domain. The effects of the non-dimensional wave amplitude, porosity, magnetic field, rotation, and the dimensionless time-mean flow in the wave frame are analyzed theoretically and computed numerically. Numerical results are given and illustrated graphically in each case considered. Comparison was made with the results obtained in the presence and absence of rotation, magnetic field, and porosity. The results indicate that the effects of the non-dimensional wave amplitude, porosity, magnetic field, rotation, and the dimensionless time-mean flow are very pronounced in the phenomena.

关键词： peristaltic flow second-order fluid magnetic field porous medium

Neoproterozoic Tectonic Events of Egypt

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Acta Geologica Sinica(English Edition) 2021年第4期95卷 1366-1405页

作者： mohamed abd el-WAHEd Zakaria HAmImI Geology department Faculty of ScienceTanta UniversityTanta 31527Egypt department of Geology Faulty of ScienceBen ha UniversityBenha 13518Egypt

The Egyptian Nubian Shield(ENS)represents the northwestern part of the Arabian-Nubian Shield and the northern extension of the East African *** ENS is regarded as being formed due to northward-directed escape *** is characterized by mild accretion and suture zones dominated by major strike-slip zones with a commonly sinistral sense of movement;some shear zones display a dextral sense of *** is dominated by gneisses and migmatites in the south,arc volcaniclastic metasediments and highly dismembered ophiolites in the central parts,whereas its northern part is dominated by late-to post-tectonic *** southern Sinai,the Neoproterozoic rocks are grouped into four complexes,namely Feiran–Solaf,Sa’al–Zaghra,Kid and *** ENS ophiolites were formed between 730–750 ma,mainly in a supra-subduction zone *** ENS has undergone a Neoproterozoic deformation history involving three successive phases:(1)Early N–S shortening phase(d1),(2)Syn-accretionary phase(d2)and(3)Post-accretionary phase(d3).The initial island-arc stage(780–730 ma)is a N–S shortening phase initiated by collision between the Eastern desert tectonic terrane to the north with both the Gebeit and Gabgaba terranes to the south(830–720 ma).during the arc-splitting and back-arc spreading stage(730–620),voluminous syn-tectonic granitoids intruded into the ENS(750–610 ma).The E–W-directed compressional/transpressional phase(620–450 ma)led to the overall uplift of the central part of the ENS and consequently the development and exhumation of the core complexes in oblique convergent *** E–W intense shortening deformation resulted also in the formation of NW-and NE-striking sinistral and dextral strike-slip shear zones,*** latest periods of the E–W-directed compressional/transpressional regime were characterized by deposition of the molasse-type Hammamat Sediments unconformably over the dokhan Volcanics,or interbedded with *** combined thrusting,folding and sin

关键词： Neoproterozoic deformation N–S shortening syn-accretionary phase post-accretionary phase Egyptian Nubian Shield

An Efficient GCd-Based Cancelable Biometric Algorithm for Single and multiple Biometrics

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Computers, materials & Continua 2021年第11期69卷 1571-1595页

作者： Naglaa F.Soliman Abeer d.Algarni Walid el-Shafai Fathi E.abd el-Samie Ghada m.el Banby department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)*** objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT *** original biometric is blurred with two co-prime ***,it can be recovered as the Greatest Common divisor(GCd)between its two blurred *** changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCd ***,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric ***,we test the utility of the proposed algorithm in the single-and multi-biometric *** multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable *** metrics such as Equal Error Rate(EER)and Area and Receiver Operator Characteristic curve(AROC)are *** results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low EER values down to 0.04%.

关键词： Cloud IoT cancelable biometrics GCd single-and multi-biometrics security applications

An Efficient CNN-Based Hybrid Classification and Segmentation Approach for COVId-19 detection

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Computers, materials & Continua 2022年第3期70卷 4393-4410页

作者： Abeer d.Algarni Walid el-Shafai Ghada m.el Banby Fathi E.abd el-Samie Naglaa F.Soliman department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 84428Saudi Arabia department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt department of Industrial electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt department of electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia 44519Egypt

COVId-19 remains to proliferate precipitously in the *** has significantly influenced public health,the world economy,and the persons’***,there is a need to speed up the diagnosis and precautions to deal with COVId-19 *** this explosion of this pandemic,there is a need for automated diagnosis tools to help specialists based onmedical *** paper presents a hybrid Convolutional Neural Network(CNN)-based classification and segmentation approach for COVId-19 detection from Computed Tomography(CT)*** proposed approach is employed to classify and segment the COVId-19,pneumonia,and normal CT *** classification stage is firstly applied to detect and classify the input medical CT ***,the segmentation stage is performed to distinguish between pneumonia and COVId-19 CT *** classification stage is implemented based on a simple and efficient CNN deep learning *** model comprises four Rectified Linear Units(RelUs),four batch normalization layers,and four convolutional(Conv)*** layer depends on filters with sizes of 64,32,16,and 8.A2×2windowand a stride of 2 are employed in the utilized four max-pooling layers.A soft-max activation function and a Fully-Connected(FC)layer are utilized in the classification stage to perform the detection *** the segmentation process,the Simplified Pulse Coupled Neural Network(SPCNN)is utilized in the proposed hybrid *** proposed segmentation approach is based on salient object detection to localize the COVId-19 or pneumonia region,*** summarize the contributions of the paper,we can say that the classification process with a CNN model can be the first stage a highly-effective automated diagnosis *** the images are accepted by the system,it is possible to perform further processing through a segmentation process to isolate the regions of interest in the *** region of interest can be assesses both automatically and through ***

关键词： COVId-19 segmentation classification CNN SPCNN CT images

An Improved Convolutional Neural Network model for dNA Classification

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Computers, materials & Continua 2022年第3期70卷 5907-5927页

作者： Naglaa.F.Soliman Samia m.abd-Alhalem Walid el-Shafai Salah eldin S.E.abdulrahman N.Ismaiel el-Sayed m.el-Rabaie Abeer d.Algarni Fathi E.abd el-Samie department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia department of electronics and electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt department of Computer Science and Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt

Recently,deep learning(dL)became one of the essential tools in bioinformatics.A modified convolutional neural network(CNN)is employed in this paper for building an integratedmodel for deoxyribonucleic acid(dNA)*** any CNN model,convolutional layers are used to extract features followed by max-pooling layers to reduce the dimensionality of features.A novel method based on downsampling and CNNs is introduced for feature *** downsampling is an improved form of the existing pooling layer to obtain better classification *** two-dimensional discrete transform(2d dT)and two-dimensional random projection(2d RP)methods are applied for *** convert the high-dimensional data to low-dimensional data and transform the data to the most significant feature ***,there are parameters which directly affect how a CNN model is *** this paper,some issues concerned with the training of CNNs have been *** CNNs are examined by changing some hyperparameters such as the learning rate,size of minibatch,and the number of *** and assessment of the performance of CNNs are carried out on 16S rRNA bacterial *** results indicate that the utilization of a CNN based on wavelet subsampling yields the best trade-off between processing time and accuracy with a learning rate equal to 0.0001,a size of minibatch equal to 64,and a number of epochs equal to 20.

关键词： dNA classification CNN downsampling hyperparameters dL 2d dT 2d RP

Automated COVId-19 detection Based on Single-Image Super-Resolution and CNN models

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Computers, materials & Continua 2022年第1期70卷 1141-1157页

作者： Walid el-Shafai Anas m.Ali el-Sayed m.el-Rabaie Naglaa F.Soliman Abeer d.Algarni Fathi E.abd el-Samie department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

In developing countries,medical diagnosis is expensive and time ***,automatic diagnosis can be a good cheap *** task can be performed with artificial intelligence tools such as deep Convolutional Neural Networks(CNNs).These tools can be used on medical images to speed up the diagnosis process and save the efforts of *** deep CNNs allow direct learning from the medical ***,the accessibility of classified data is still the largest challenge,particularly in the field of medical *** learning can deliver an effective and promising solution by transferring knowledge from universal object detection CNNs to medical image ***,because of the inhomogeneity and enormous overlap in intensity between medical images in terms of features in the diagnosis of Pneumonia and COVId-19,transfer learning is not usually a robust ***-Image Super-Resolution(SISR)can facilitate learning to enhance computer vision functions,apart from enhancing perceptual image ***,it helps in showing the main features of *** by the challenging dilemma of Pneumonia and COVId-19 diagnosis,this paper introduces a hybrid CNN model,namely SIGTra,to generate super-resolution versions of X-ray and CT *** depends on aGenerative Adversarial Network(GAN)for the super-resolution reconstruction ***,Transfer learning with CNN(TCNN)is adopted for the classification of *** different categories of chest X-ray and CT images can be classified with the proposed model.A comparison study is presented between the proposed SIGTra model and the other relatedCNNmodels for COVId-19 detection in terms of precision,sensitivity,and accuracy.

关键词： medical images SIGTra GAN CT and X-ray images SISR TCNN