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Gauss Gradient and sURF Features for Landmine Detection from GPR Images

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 objects.However,its output has a low resolution,and it needs more processing for more interpretation.This paper presents two algorithms for landmine detection from GPR images.The first algorithm depends on a multi-scale technique.A Gaussian kernel with a particular scale is convolved with the image,and after that,two gradients are estimated;horizontal and vertical gradients.Then,histogram and cumulative histogram are estimated for the overall gradient image.The bin values on the cumulative histogram are used for discrimination between images with and without landmines.Moreover,a neural classifier is used to classify images with cumulative histograms as feature vectors.The second algorithm is based on scale-space analysis with the number of speeded-up robust feature(sURF)points as the key parameter for classification.In addition,this paper presents a framework for size reduction of GPR images based on decimation for efficient storage.The further classification steps can be performed on images after interpolation.The 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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Improved Manta Ray Foraging Optimizer-based sVM for Feature selection Problems:A Medical Case study

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Journal of Bionic Engineering 2024年第1期21卷 409-425页

作者： adel Got Djaafar Zouache Abdelouahab Moussaoui Laith Abualigah Ahmed Alsayat Faculty of informatics University of Science and Technology Houari BoumedieneAlgiersAlgeria LRIA Laboratory University of Science and Technology Houari BoumedieneAlgiersAlgeria Computer science Department University of Mohamed El Bachir El IbrahimiBordj Bou ArreridjAlgeria Computer science Department University of Ferhat AbbasSetifAlgeria Computer science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq 25113Jordan Department of Computer science College of Computer and Information SciencesJouf UniversityJoufSaudi Arabia Department of Electrical and Computer Engineering Lebanese American University13-5053ByblosLebanon Hourani Center for Applied scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied science research center Applied science private universityAmman 11931Jordan school of Computer sciences Universiti Sains Malaysia11800 PenangMalaysia school of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

support Vector Machine(sVM)has become one of the traditional machine learning algorithms the most used in prediction and classification tasks.However,its behavior strongly depends on some parameters,making tuning these parameters a sensitive step to maintain a good performance.On the other hand,and as any other classifier,the performance of sVM is also affected by the input set of features used to build the learning model,which makes the selection of relevant features an important task not only to preserve a good classification accuracy but also to reduce the dimensionality of datasets.In this paper,the MRFO+sVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the sVM parameters and identify the optimal feature subset simultaneously.The proposed approach is validated and compared with four sVM-based algorithms over eight benchmarking datasets.Additionally,it is applied to a disease Covid-19 dataset.The experimental results show the high ability of the proposed algorithm to find the appropriate sVM’s parameters,and its acceptable performance to deal with feature selection problem.

关键词： support vector machine Parameters tuning Feature selection Bioinspired algorithms Manta ray foraging optimizer

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Mafic and felsic magmatism in the Wadi Kalalat area, south Eastern Desert, Egypt: mineralogy, geochemistry and geodynamic evolution during the Neoproterozoic in the Nubian shield

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Acta Geochimica 2024年第1期43卷 150-173页

作者： adel A.surour Ahmed A.Madani Mohamed A.El-sobky Faculty of science Galala UniversityNew Galala CitySuez 43511Egypt Department of Geology Faculty of ScienceCairo UniversityGiza 12613Egypt Egyptian Mineral Resources Authority P.O.Box 11517AbbasiyaCairoEgypt

In the south Eastern Desert of Egypt,two contrasting types of magmatism(mafic and felsic) are recorded in the Wadi Kalalat area,and form the Gabal El Motaghiarat and Gabal Batuga intrusions,respectively.The two intrusions post-dates ophiolitic and arc associations represented by serpentinite and metagabbro-diorite,respectively.The mafic intrusion has a basal ultramafic member represented by fresh peridotite,which is followed upward by olivine gabbro and anorthositic or leucogabbro.This mafic intrusion pertains to the Alaskan-type mafic-ultramafic intrusions in the Arabian-Nubian shield(ANs)being of tholeiitic nature and emplaced in a typical arc setting.On the other hand,the Gabal Batuga intrusion comprises three varieties of fresh A-type granites of high K-calc alkaline nature,which is peraluminous and garnetbearing in parts.A narrow thermal aureole in the olivine gabbro of the mafic intrusion was developed due to the intrusion of the Batuga granites.This results in the development of a hornfelsic melagabbro variety in which the composition changed from tholeiitic to a calc-alkaline composition due to the addition of s_(i)O_(2),Al_(2)O_(3),alkalis,lithosphile elements(LILEs) such as Rb(70 ppm) and Y(28 ppm) from the felsic intrusion.Outside the thermal aureole,Rb amounts 2-8 ppm and Y lies in the range s believed that the Gabal Batuga felsic intrusion started to emplace during the waning stage of an arc system,with transition from the pre-collisional(i.e.,arc setting) to post-collisional and within plate settings.Magma from which the Gabal Batuga granites were fractionated is high-K calc-alkaline giving rise to a typical post-collisional A-type granite(A_(2)-subtype) indicating an origin from an underplating crustal source.Accordingly,it is stressed here that the younger granites in the ANs are not exclusively post-collisional and within-plate but most likely they started to develop before closure of the arc system.The possible source(s) of mafic magmas that resulted in the formation of the two intru

关键词： Wadi Kalalat Gabal El Motaghairat mafic intrusion Gabal Batuga felsic intrusion Arc setting Post-collision Within-plate

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Exploring sequential Feature selection in Deep Bi-LsTM Models for speech Emotion Recognition

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Computers, Materials & Continua 2024年第2期78卷 2689-2719页

作者： Fatma Harby Mansor Alohali adel Thaljaoui Amira samy Talaat Computer science Department Future Academy-Higher Future Institute for Specialized Technological StudiesCairo12622Egypt Department of Computer science and Information College of science at Zulfi Majmaah UniversityP.O.Box 66Al-Majmaah11952Saudi Arabia Preparatory Institute for Engineering studies of Gafsa ZarrougGafsa2112Tunisia Computers and systems Department Electronics Research InstituteCairo12622Egypt

Machine Learning(ML)algorithms play a pivotal role in speech Emotion Recognition(sER),although they encounter a formidable obstacle in accurately discerning a speaker’s emotional state.The examination of the emotional states of speakers holds significant importance in a range of real-time applications,including but not limited to virtual reality,human-robot interaction,emergency centers,and human behavior assessment.Accurately identifying emotions in the sER process relies on extracting relevant information from audio inputs.Previous studies on sER have predominantly utilized short-time characteristics such as Mel Frequency Cepstral Coefficients(MFCCs)due to their ability to capture the periodic nature of audio signals effectively.Although these traits may improve their ability to perceive and interpret emotional depictions appropriately,MFCCs has some limitations.so this study aims to tackle the aforementioned issue by systematically picking multiple audio cues,enhancing the classifier model’s efficacy in accurately discerning human emotions.The utilized dataset is taken from the EMO-DB database,preprocessing input speech is done using a 2D Convolution Neural Network(CNN)involves applying convolutional operations to spectrograms as they afford a visual representation of the way the audio signal frequency content changes over time.The next step is the spectrogram data normalization which is crucial for Neural Network(NN)training as it aids in faster convergence.Then the five auditory features MFCCs,Chroma,Mel-spectrogram,Contrast,and Tonnetz are extracted from the spectrogram sequentially.The attitude of feature selection is to retain only dominant features by excluding the irrelevant ones.In this paper,the sequential Forward selection(sFs)and sequential Backward selection(sBs)techniques were employed for multiple audio cues features selection.Finally,the feature sets composed from the hybrid feature extraction methods are fed into the deep Bidirectional Long short Term Memory(Bi-LsTM)network to discern emotions.

关键词： Artificial intelligence application multi features sequential selection speech emotion recognition deep Bi-LsTM

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New solutions for four novel generalized nonlinear fractional fifth-order equations

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Journal of Ocean Engineering and science 2024年第1期9卷 59-65页

作者： Mehmet senol Lanre Akinyemi Henrietta Nkansah Waleed adel Nevsehir HacıBekta¸s Veli University Department of MathematicsNevsehirTurkey Department of Mathematics Lafayette CollegeEastonPennsylvaniaUSA Department of Mathematics University of Cape CoastCape CoastGhana Department of Mathematics and Engineering Physics Faculty of EngineeringMansoura UniversityEgypt UniversitéFrançaise dÉgypte Ismailia Desert RoadEl ShoroukCairoEgypt

In this paper,new four fifth-order fractional nonlinear equations are derived and investigated.The frac-tional terms are defined in the conformable sense and these equations are then solved using two effective methods,namely,the sub-equation and the generalized Kudryashov methods.These methods were tested on the proposed models and succeeded in finding new solutions with different values of parameters.A graphical representation of some results is provided and proves the efficiency and applicability of the proposed methods for providing solutions with known physical behavior.These methods are good candi-dates for solving other similar problems in the future.

关键词： Conformable derivative Generalized Kudryashov method sub-equation method Riccati equation solitons

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Microphallus early management in infancy saves adulthood sensual life:A comprehensive review

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World Journal of Clinical Pediatrics 2024年第2期13卷 16-37页

作者： Mohammed Al-Beltagi Nermin Kamal saeed adel salah Bediwy Majed A shaikh Reem Elbeltagi Department of Pediatric Faculty of MedicineTanta UniversityTanta 31511Egypt Department of Pediatric University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityManama 26671Bahrain Department of Pediatric University Medical CenterSulaiman Al Habib Medical GroupManama 26671Bahrain Department of Medical Microbiology section and Pathology Salmaniya Medical ComplexMinistry of HealthKingdom of BahrainManama 12Bahrain Department of Medical Microbiology section and Pathology Irish Royal College of SurgeonBusaiteen 15503Bahrain Department of Pulmonology Faculty of MedicineTanta UniversityTanta 31527Egypt Department of Pulmonology University Medical CenterKing Abdulla Medical CityArabian Gulf UniversityManama 26671Bahrain Department of Pulmonology University Medical CenterSulaiman Al Habib Medical GroupManama 26671Bahrain Department of Pediatrics Ibn Al Nafees HospitalManama 54533Bahrain Department of Medicine The Royal College of Surgeons in Ireland-BahrainBusiateen 15503Bahrain

Microphallus/Micropenis is a rare condition with significant physical and psychological implications for affected individuals.This article comprehensively reviews micropenis,its etiology,epidemiology,and various treatment options.We conducted a thorough literature review to collect relevant information on micropenis and microphallus,as well as related disorders.Our primary databases were PubMed,Medline,and Google scholar.We searched for articles published in English between 2000 and 2023.Our analysis included 67 review articles,56 research studies,11 case reports,one guideline,and one editorial.Our search terms included"microphallus","micropenis","congenital hypogonadotropic hypogonadism","androgen insensitivity syndrome","pediatric management of micropenis","testosterone therapy",and"psychosocial implications of micropenis".We focused on diagnosing micropenis and related conditions,including hormonal assessments,medical and surgical treatment options,psychosocial and psychological well-being,sexual development of adolescents,and sociocultural influences on men's perceptions of penile size.Additionally,we explored parenting and family dynamics in cases of micropenis and disorders of sex development,implications of hormonal treatment in neonates,and studies related to penile augmentation procedures and their effectiveness.The article highlights the importance of early diagnosis and intervention in addressing the physical and psychological well-being of individuals with micropenis.surgical procedures,such as penile lengthening and girth enhancement,and non-surgical approaches like hormonal therapy are explored.The significance of psychological support,education,and lifestyle modifications is emphasized.Early management and comprehensive care are crucial for individuals with micropenis,from infancy to adolescence and beyond.A multidisciplinary approach involving urologists,endocrinologists,and mental health professionals is recommended.Regular assessment of treatment effectiveness and the need for updated guidelines

关键词： Microphallus Micropenis Hypogonadism Children Adults sensual life Testosterone therapy

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赛德西港用于船舶减排的陆上可再生能源供电评估

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哈尔滨工程大学学报（英文版） 2024年第2期23卷 506-524页

作者： Merna Makram Ameen M.Bassam adel A.Tawfik Waleed Yehia Naval Architecture and Marine Eng.Dept. Faculty of EngineeringPort Said UniversityPort Fuad 42526Egypt

Air pollution from shipping is becoming a critical issue,particularly in dense hub port cities.One proposed solution to minimize ship-based emissions at ports is the implementation of an Onshore Power supply(OPs)system.OPs allows ships to shut off their auxiliary engines and instead connect to the port grid.While there have been numerous studies conducted on ports in Europe and the United states,little research has been done on Egyptian ports.Therefore,this paper aims to investigate the feasibility of implementing OPs at Port said West Port in Egypt,aligning with Egypt Vision 2030’s goals for addressing climate change.The research primarily focuses on analyzing data collected from calling ships to generate socio-economic and cost-effectiveness analyses of OPs.To further enhance the environmental benefits of OPs,the paper proposes the use of solar energy as the OPs electricity source.The findings of the study revealed that by relying on the national grid,emissions can be reduced by 28%.Moreover,it is predicted that this reduction could reach 100%if electricity generation is solely based on solar energy.Additionally,the economic analysis demonstrates promising profitability,with a payback period of approximately two years.

关键词： Onshore power supply Port sustainability shipping emissions inventory solar energy Photovoltaic systems

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Metabolic reprogramming by syntenin-1 directs RA FLs and endothelial cell-mediated inflammation and angiogenesis

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Cellular & Molecular Immunology 2024年第1期21卷 33-46页

作者： Anja Meyer stephanie R.Zack Wes Nijim adel Burgos Vishwa Patel Brian Zanotti Michael V.Volin M.Asif Amin Myles J.Lewis Costantino Pitzalis shiva Arami Joseph A.Karam Nadera J.sweiss shiva shahrara Jesse Brown VA Medical Center ChicagoILUSA Department of Medicine Division of RheumatologyThe University of Illinois at ChicagoChicagoILUSA Department of Microbiology and Immunology Midwestern UniversityDowners GroveILUSA Division of Rheumatology and Clinical Autoimmunity Center of Excellence University of MichiganAnn ArborMIUSA Centre for Experimental Medicine and Rheumatology William Harvey Research InstituteBarts and The London School of Medicine and DentistryQueen Mary University of LondonLondonUnited Kingdom Centre for Experimental Medicine&Rheumatology William Harvey Research InstituteQueen Mary University of London and Barts NIHR BRC&NHS TrustLondonUK Department of Biomedical sciences Humanitas Universityand Humanitas Research HospitalMilanItaly Department of Orthopedic surgery the University of Illinois at ChicagoChicagoILUSA

A novel rheumatoid arthritis(RA)synovial fluid protein,syntenin-1,and its receptor,syndecan-1(sDC-1),are colocalized on RA synovial tissue endothelial cells and fibroblast-like synoviocytes(FLs).syntenin-1 exacerbates the inflammatory landscape of endothelial cells and RA FLs by upregulating transcription of IRF1/5/7/9,IL-1β,IL-6,and CCL2 through sDC-1 ligation and HIF1α,or mTOR activation.Mechanistically,syntenin-1 orchestrates RA FLs and endothelial cell invasion via sDC-1 and/or mTOR signaling.In syntenin-1 reprogrammed endothelial cells,the dynamic expression of metabolic intermediates coincides with escalated glycolysis along with unchanged oxidative factors,AMPK,PGC-1α,citrate,and inactive oxidative phosphorylation.Conversely,RA FLs rewired by syntenin-1 displayed a modest glycolytic-ATP accompanied by a robust mitochondrial-ATP capacity.The enriched mitochondrial-ATP detected in syntenin-1 reprogrammed RA FLs was coupled with mitochondrial fusion and fission recapitulated by escalated Mitofusin-2 and DRP1 expression.We found that VEGFR1/2 and Notch1 networks are responsible for the crosstalk between syntenin-1 rewired endothelial cells and RA FLs,which are also represented in RA explants.similar to RA explants,morphological and transcriptome studies authenticated the importance of VEGFR1/2,Notch1,RAPTOR,and HIF1αpathways in syntenin-1 arthritic mice and their obstruction in sDC-1 deficient animals.Consistently,dysregulation of sDC-1,mTOR,and HIF1αnegated syntenin-1 inflammatory phenotype in RA explants,while inhibition of HIF1αimpaired synovial angiogenic imprint amplified by syntenin-1.In conclusion,since the current therapies are ineffective on syntenin-1 and sDC-1 expression in RA synovial tissue and blood,targeting this pathway and its interconnected metabolic intermediates may provide a novel therapeutic strategy.

关键词： syntenin-1 syndecan-1 RA FLs RA explants immunometabolism

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Optical Ciphering scheme for Cancellable speaker Identification system

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Computer systems science & Engineering 2023年第4期45卷 563-578页

作者： Walid El-shafai Marwa A.Elsayed Mohsen A.Rashwan Moawad I.Dessouky adel s.El-Fishawy Naglaa F.soliman Amel A.Alhussan Fathi EAbd El-samie Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Communications Faculty of EngineeringCairo UniversityCairoEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia

Most current security and authentication systems are based on personal biometrics.The security problem is a major issue in the field of biometric systems.This is due to the use in databases of the original biometrics.Then biometrics will forever be lost if these databases are attacked.Protecting privacy is the most important goal of cancelable biometrics.In order to protect privacy,therefore,cancelable biometrics should be non-invertible in such a way that no information can be inverted from the cancelable biometric templates stored in personal identification/verification databases.One methodology to achieve non-invertibility is the employment of non-invertible transforms.This work suggests an encryption process for cancellable speaker identification using a hybrid encryption system.This system includes the 3D Jigsaw transforms and Fractional Fourier Transform(FrFT).The proposed scheme is compared with the optical Double Random Phase Encoding(DRPE)encryption process.The evaluation of simulation results of cancellable biometrics shows that the algorithm proposed is secure,authoritative,and feasible.The encryption and cancelability effects are good and reveal good performance.Also,it introduces recommended security and robustness levels for its utilization for achieving efficient cancellable biometrics systems.

关键词： Cancellable biometrics jigsaw transform FrFT DRPE speaker identification

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Efficient Deep CNN Model for COVID-19 Classification

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Computers, Materials & Continua 2022年第3期70卷 4373-4391页

作者： Walid El-shafai Amira A.Mahmoud El-sayed M.El-Rabaie Taha E.Taha Osama F.Zahran adel s.El-Fishawy Mohammed Abd-Elnaby Fathi E.Abd El-samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Coronavirus(COVID-19)infection was initially acknowledged as a global pandemic in Wuhan in China.World Health Organization(WHO)stated that the COVID-19 is an epidemic that causes a 3.4%death rate.Chest X-Ray(CXR)and Computerized Tomography(CT)screening of infected persons are essential in diagnosis applications.There are numerous ways to identify positive COVID-19 cases.One of the fundamental ways is radiology imaging through CXR,or CT images.The comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high quality.Hence,automated classification techniques are required to facilitate the diagnosis process.Deep Learning(DL)is an effective tool that can be utilized for detection and classification this type of medical images.The deep Convolutional Neural Networks(CNNs)can learn and extract essential features from different medical image datasets.In this paper,a CNN architecture for automated COVID-19 detection from CXR and CT images is offered.Three activation functions as well as three optimizers are tested and compared for this task.The proposed architecture is built from scratch and the COVID-19 image datasets are directly fed to train it.The performance is tested and investigated on the CT and CXR datasets.Three activation functions:Tanh,sigmoid,and ReLU are compared using a constant learning rate and different batch sizes.Different optimizers are studied with different batch sizes and a constant learning rate.Finally,a comparison between different combinations of activation functions and optimizers is presented,and the optimal configuration is determined.Hence,the main objective is to improve the detection accuracy of COVID-19 from CXR and CT images using DL by employing CNNs to classify medical COVID-19 images in an early stage.The proposed model achieves a classification accuracy of 91.67%on CXR image dataset,and a classification accuracy of 100%on CT dataset with training times of 58 min and 46 min on CXR and CT datasets,respectively.The best results are

关键词： COVID-19 image classification CNN DL activation functions optimizers

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