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Multiclass Cucumber Leaf Diseases Recognition Using Best Feature selection

Computers, Materials & Continua 2022年第2期70卷 3281-3294页

作者： Nazar Hussain Muhammad Attique Khan Usman Tariq seifedine Kadry Muhammad Asfand E.Yar almetwally M.Mostafa abeer ali alnuaim shafiq Ahmad Department of Computer science HITEC University TaxilaTaxilaPakistan College of Computer Engineering and sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Applied Data science Noroff University CollegeNorway Department of Computer science Bahria UniversityIslamabadPakistan Department of Information systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543KSASaudi Arabia Department of natural and engineering sciences College of Applied Studies and Community ServiceKing Saud UniversityRiyadh11421Saudi Arabia Faculty of Engineering Industrial Engineering DepartmentKing Saud UniversityRiyadh11421Saudi Arabia

Agriculture is an important research area in the field of vis.al recognition by *** diseases affect the quality and yields of ***-stage identification of crop disease decreases financial losses and positively impacts crop *** manual identification of crop diseases,which aremostly visible on leaves,is a very time-consuming and costly *** this work,we propose a new framework for the recognition of cucumber leaf *** proposed framework is based on deep learning and involves the fusion and selection of the best *** the feature extraction phase,VGG(Vis.al Geometry Group)and Inception V3 deep learning models are considered and *** fine-tuned models are trained using deep transfer *** are extracted in the later step and fused using a parallel maximum fusion *** the later step,best features are selected usingWhale Optimization *** best-selected features are classified using supervised learning algorithms for the final classification *** experimental process was conducted on a privately collected dataset that consists of five types of cucumber disease and achieved accuracy of 96.5%.A comparison with recent techniques shows the significance of the proposed method.

关键词： Cucumber diseases database preparation deep learning parallel fusion features selection

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Efficient Deep Learning Modalities for Object Detection from Infrared Images

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Computers, Materials & Continua 2022年第8期72卷 2545-2563页

作者： Naglaa F.soliman E.A.alabdulkreem abeer D.algarni Ghada M.El Banby Fathi E.Abd El-samie Ahmed sedik 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 Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafr el-sheikhEgypt

For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video *** vision is a vis.al search trend that is used to identify objects in images or video *** military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime ***,there is a need for such a system,which provides a continuous surveillance task to support the drone *** a system can be called a Hybrid surveillance system(Hss).This system is based on a distributed network of wireless sensors for continuous *** addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious *** paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long short-Term Memory(ConvLsTM).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video *** accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented *** addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关键词： Deep learning object detection military applications OFDM sPIHT IoT

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Characterization and Catalytic Activity of New Metal-organic Frameworks Resulted from self-assembly of Ph3snCI, K[Cu（CN）2] and Nitrogen Donor Ligands

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Chinese Journal of Chemistry 2011年第7期29卷 1401-1410页

作者： Etaiw, safaa El-din H. Elsherbiny, abeer s. Badr El-din, Ahmed s. Chemistry Department Faculty of Science Tanta University Tanta Egypt

Five new metal-organic frameworks （MOFs） of the general composition [Ph3snCu（CN）2.L], where L= pyrazine （pyz）（1）, methylpyrazine （mepyz）（2）, 4,4＇-bipyridine （bpy）（3）, trans-l,2-bis（4-pyridyl）ethene （tbpe）（4） or 1,2-bis（4-pyridyl）ethane （bpe）（5）, have been synthesized and characterized to test their potential applications as catalysts. The structures of the MOFs 1--5 mainly consist of Cu（CN）2 building blocks connected by the Ph3sn cations and the bipodal ligand forming polymeric networks. They exhibit strong fluorescence in the solid state. also, they are used as heterogeneous catalysts for the degradation of azo-dyes, metanil yellow （MY） by diluted solution of hydrogen peroxide as oxidant. The reaction is first order with respect to MY dye, while the factors affecting the rate constant of the degradation reaction are investigated. The activation parameters of the reaction have been estimated and a possible mechanism has been proposed.

关键词： copper tin heterogeneous catalyst metanil yellow hydrogen peroxide

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synthesis, Characteristic and Antimicrobial Activity of some New spiro[indol-thiazolidon-2,4-diones] and Bis(5-fluorospiro[indoline-3,2’-thiazolidine]-2,4’-dione) Probes

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International Journal of Organic Chemistry 2020年第2期10卷 77-87页

作者： abeer N. al-Romaizan Department of Chemistry Faculty of Science King Abdul Aziz University Jeddah KSA

In a search for new antimicrobial agents, some new spiro[indol-thiazolidon- 2,4-diones] (6a-c) were synthesized by condensation of 5-substituted isatins 1 with sulfanilamide in MeOH, followed by aroylation with p-nitr... 详细信息

In a search for new antimicrobial agents, some new spiro[indol-thiazolidon- 2,4-diones] (strong>6a-cstrong>) were synthesized by condensation of 5-substituted isatins strong>1 strong>with sulfanilamide in MeOH, followed by aroylation with p-nitrobenzoyl chloride in DMF to get compounds strong>4a-cstrong>. Cycloaddition of strong>4astrong>strong>-cstrong> with thioglycolic acid in a dry non-polar solvent (dioxane) gave the targets strong>6a-cstrong>. also, bis(5-fluorospiro[indoline-3,2’-thiazolidine]-2,4’-dione) (strong>9strong>) was synthesized by condensation of 5-fluoroindoline-2,3-dione with benzene-1,4-diamine (2:1 by mol) in MeOH, which followed by cycloaddition with thioglycolic acid in dioxane gave compound strong>8strong>. Acylation of the later with 2,2,2-trifluoroacetic anhydride in THF has yielded the target strong>9strong>. structures of the products have been deduced from their elemental analysis and spectral data. The in vitro antimicrobial activity of the new systems strong>6a-cstrong>, and strong>9strong> was tested.

关键词： synthesis spiroindoline-Thiazolidine Mercaptoacetic Acid Antimicrobial 5-substituted Isatin sulfanilamide

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Enhanced Robotic Vision system Based on Deep Learning and Image Fusion

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Computers, Materials & Continua 2022年第10期73卷 1845-1861页

作者： E.A.alabdulkreem Ahmed sedik abeer D.algarni Ghada M.El Banby Fathi E.Abd El-samie Naglaa F.soliman Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafrelsheikh33511Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Image fusion has become one of the interesting fields that attract researchers to integrate information from different image *** is involved in several *** of the recent applications is the robotic *** application necessitates image enhancement of both infrared(IR)and visible *** paper presents a Robot Human Interaction system(RHIs)based on image fusion and deep *** basic objective of this system is to fuse vis.al and IR images for efficient feature extraction from the captured ***,an enhancement model is carried out on the fused image to increase its *** image enhancement models such as fuzzy logic,Convolutional Neural Network(CNN)and residual network(ResNet)pre-trained model are utilized on the fusion results and they are compared with each other and with the state-of-the-art *** results prove that the fuzzy logic enhancement gives the best results from the image quality ***,the proposed system can be considered as an efficient solution for the robotic vision problem with multi-modality images.

关键词： Deep learning fuzzy logic image fusion IR images

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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

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Engineering homologous platelet-rich plasma,platelet-rich plasma-derived exosomes,and mesenchymal stem cell-derived exosomes-based dual-crosslinked hydrogels as bioactive diabetic wound dressings

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Bioactive Materials 2023年第10期28卷 74-94页

作者： Bianza Moise Bakadia abeer Ahmed Qaed Ahmed Lallepak Lamboni Zhijun shi Biampata Mutu Mukole Ruizhu Zheng Mazono Pierre Mbang Bi Zhang Mario Gauthier Guang Yang Department of Biomedical Engineering College of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan430074China College of Life science and Technology Key Laboratory of Molecular Biophysics of MOEHuazhong University of Science and TechnologyWuhanChina Institut sup´erieur des Techniques M´edicales de Lubumbashi LubumbashiCongo Department of Molecular Medicine Biochemistry UnitUniversity of Pavi127100Pavi1Italy e Institut National de Recherche Biom´edicale Minist`ere de la Sant´eCongo Department of Chemistry University of WaterlooWaterlooOntarioN2L 3G1Canada

The management of diabetic wounds remains a critical therapeutic challenge. Platelet-rich plasma (PRP) gel, PRP-derived exosomes (PRP-Exos), and mesenchymal stem cell-derived exosomes (MsC-Exos) have demonstrated therapeutic potential in wound treatment. Unfortunately, their poor mechanical properties, the short half-lives of growth factors (GFs), and the burst release of GFs and exosomes have limited their clinical applications. Furthermore, proteases in diabetic wounds degrade GFs, which hampers wound repair. silk fibroin is an enzyme-immobilization biomaterial that could protect GFs from proteases. Herein, we developed novel dual-crosslinked hydrogels based on silk protein (sP) (sericin and fibroin), including sP@PRP, sP@MsC-Exos, and sP@PRP-Exos, to promote diabetic wound healing synergistically. sP@PRP was prepared from PRP and sP using calcium gluconate/thrombin as agonist, while sP@PRP-Exos and sP@MsC-Exos were derived from exosomes and sP with genipin as crosslinker. sP provided improved mechanical properties and enabled the sustained release of GFs and exosomes, thereby overcoming the limitations of PRP and exosomes in wound healing. The dual-crosslinked hydrogels displayed shear-induced thinning, self-healing, and eradication of microbial biofilms in a bone-mimicking environment. In vivo, the dual-crosslinked hydrogels contributed to faster diabetic wound healing than PRP and sP by upregulating GFs expression, down-regulating matrix metalloproteinase-9 expression, and by promoting an anti-NETotic effect, angiogenesis, and re-epithelialization. Hence, these dual-crosslinked hydrogels have the potential to be translated into a new generation of diabetic wound dressings.

关键词： Platelet-rich plasma(PRP) Exosomes(Exos) silk protein Dual-crosslinked hydrogel Diabetic wound

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An automated framework for advertisement detection and removal from sports videos using audio-vis.al cues

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Frontiers of Computer science 2021年第2期15卷 185-188页

作者： abeer TOHEED ali JAVED Aun IRTAZA Hassan DAWOOD Hussain DAWOOD Ahmed s.alFAKEEH Department of software Engineering University of Engineering and Technology-TaxilaTaxila47050Pakistan Department of Computer&Network Engineering University of JeddahJeddah21577Saudi Arabia Information system Department King Abdulaziz UniversityJeddah21577Saudi Arabia

1 Introduction Advertisements detection and replacement with different ads based on the user preferences is employed during sports rebroadcasts that offers more value to both the distributor and *** advertisements detection is a laborious activity and demands an urgent need to develop automated advertisement detection techniques to save the time,storage space,and transmission bandwidth.

关键词： automated vis.al framework

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Platelet indices in evaluation of patients with recurrent pregnancy loss

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Asian pacific Journal of Reproduction 2018年第1期7卷 15-18页

作者： abeer Abdul-Rahman al-Aghbary Mohammed Abdul Wahid almorish Dikra Waheeb Mohamed Jaffar Waiel Mohmed al-Kahiry Department of Gynecology and Obstetrics Taiz UniversityYemen Department of Hematology Sanaa UniversityYemen Department of Gynecology and Obstetrics Aden UniversityYemen Department of Hematology Oncology Aden UniversityYemen

Objective: To explore the change of platelet indices namely plateletcrit, platelet distribution width and mean platelet volume among patients with recurrent pregnancy loss (RPL). Methods: The medical records of 45 women with a history of RPL and 45 women who gave birth without RPL were reviewed retrospectively from three governmental hospitals in Yemen. The personal, obstetric and complete blood count reports were analyzed. Results: Platelets' count and indices were significantly higher among RPL patients when compared to the control and the receiver operating characteristic curve for each platelet index showed significant area under the curve, with higher area for plateletcrit followed by platelet distribution width and then mean platelet volume. While the multiple logistic regression analysis for all platelets indices revealed that the platelet distribution width was the significant predictor for RPL in this study. Conclusions: The use of platelet indices may help gynecologists in predicting high risk pregnancy (pregnancy loss) in the low resources areas inYemen.

关键词： Pregnancy loss Platelets Platelet distribution width Mean platelet volume Plateletcrit

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Gauss Gradient and sURF Features for Landmine Detection from GPR Images

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Computers, Materials & Continua 2022年第6期71卷 4457-4486页

作者： Fatma M.El-Ghamry Walid El-shafai Mahmouad I.Abdalla Ghada M.El-Banby abeer D.algarni Moawad I.Dessouky Adel s.Elfishawy Fathi E.Abd El-samie Naglaa F.soliman Department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Recently,ground-penetrating radar(GPR)has been extended as a well-known area to investigate the subsurface ***,its output has a low resolution,and it needs more processing for more *** paper presents two algorithms for landmine detection from GPR *** first algorithm depends on a multi-s.ale technique.A Gaussian kernel with a particular s.ale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical ***,histogram and cumulative histogram are estimated for the overall gradient *** bin values on the cumulative histogram are used for discrimination between images with and without ***,a neural classifier is used to classify images with cumulative histograms as feature *** second algorithm is based on s.ale-space analysis with the number of speeded-up robust feature(sURF)points as the key parameter for *** addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient *** further classification steps can be performed on images after *** sensitivity of classification accuracy to the interpolation process is studied in detail.

关键词： GPR images cumulative histogram gradient image neural classifier sURF

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