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Web Intelligence with Enhanced Sunflower Optimization Algorithm for Sentiment Analysis

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Computer Systems Science & Engineering 2023年第10期47卷 1233-1247页

作者： abeer d.algarni department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Exponential increase in the quantity of user generated content in websites and social networks have resulted in the emergence of web intelligence *** natural language processing(NLP)tools are commonly used to examine the large quantity of data generated ***,sentiment analysis(SA)is an effective way of classifying the data into different classes of user opinions or *** latest advances in machine learning(ML)and deep learning(dL)approaches offer an intelligent way of analyzing *** this view,this study introduces a web intelligence with enhanced sunflower optimization based deep learning model for sentiment analysis(WIESFO-dLSA)*** major intention of the WIESFO-dLSA technique is to identify the expressions or sentiments that exist in the social networking *** WIESFO-dLSA technique initially performs pre-processing and word2vec feature extraction processes to generate a meaningful set of *** the same time,bidirectional long short term memory(BiLSTM)model is applied for classification of sentiments into different class ***,an enhanced sunflower optimization(ESFO)algorithm is exploited to optimally adjust the hyperparameters of the BiLSTM model.A wide range of simulation analyses is performed to report the better outcomes of the WISFO-dLSA technique and the experimental outcomes ensured its promising performance under several measures.

关键词： Sentiment analysis web intelligence deep learning social networking natural language processing

drone-based AI/IoT Framework for Monitoring,Tracking and Fighting Pandemics

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Computers, Materials & Continua 2022年第6期71卷 4677-4699页

作者： Abdelhamied A.Ateya abeer d.algarni Andrey Koucheryavy Naglaa.F.Soliman department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia department of Electronics and Communications Engineering Zagazig UniversityZagazigSharqia44519Egypt department of Telecommunication Networks and data Transmission the Bonch-Bruevich Saint-Petersburg State University of TelecommunicationsSaint Petersburg193232Russia

Since World Health Organization(WHO)has declared the Coronavirus disease(COVId-19)a global pandemic,the world has *** life’s fields and daily habits have moved to adapt to this new *** to WHO,the probability of such virus pandemics in the future is high,and recommends preparing for worse *** this end,this work provides a framework for monitoring,tracking,and fighting COVId-19 and future *** proposed framework deploys unmanned aerial vehicles(UAVs),e.g.;quadcopter and drone,integrated with artificial intelligence(AI)and Internet of Things(IoT)to monitor and fight *** consists of two main systems;AI/IoT for COVId-19 monitoring and drone-based IoT system for *** two systems are integrated with the IoT paradigm and the developed algorithms are implemented on distributed fog units connected to the IoT network and controlled by software-defined networking(SdN).The proposed work is built based on a thermal camera mounted in a face-shield,or on a helmet that can be used by people during *** detected images,thermal images,are processed by the developed AI algorithm that is built based on the convolutional neural network(CNN).The drone system can be called,by the IoT system connected to the helmet,once infected cases are *** drone is used for sterilizing the area that contains multiple infected *** proposed framework employs a single centralized SdN controller to control the network *** developed system is experimentally evaluated,and the results are *** indicate that the developed framework provides a novel,efficient scheme for monitoring and fighting COVId-19 and other future pandemics.

关键词： Internet of Things convolutional neural network fog computing software-defined networking COVId-19 drone

digital Object Architecture for IoT Networks

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Intelligent Automation & Soft Computing 2023年第1期35卷 97-110页

作者： Mahmood Al-Bahri Abdelhamied Ateya Ammar Muthanna abeer d.algarni Naglaa F.Soliman department of Computing and IT Sohar UniversitySohar311Oman department of Electronics and Communications Engineering Zagazig UniversityZagazig44519SharqiaEgypt Telecommunication Networks and data Transmission St.Petersburg State University of TelecommunicationSt.Petersburg193232Russia department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

The Internet of Things(IoT)is a recent technology,which implies the union of objects,“things”,into a single worldwide *** promising paradigm faces many design challenges associated with the dramatic increase in the number of *** identification is one of these challenges that becomes complicated with the increase of network *** this,there is still no universally accepted method of identifying things that would satisfy all requirements of the existing IoT devices and *** this regard,one of the most important problems is choosing an identification system for all IoT devices connected to the public communication *** unique soft-ware and hardware solutions are used as a unique global identifier;however,such solutions have many *** article proposes a novel solution,based on the digital Object Architecture(dOA),that meets the requirements of identifying devices and applications of the *** work analyzes the benefits of using the dOA as an identification platform in modern telecommunication *** propose a model of an identification system based on the architecture of digital objects,which differs from the well-known *** proposed model ensures an acceptable quality of service(QoS)in the common architecture of the existing public communication networks.A novel interaction architecture is developed by introducing a Middle Handle Register(MHR)between the global register,i.e.,Global Handle Register(GHR),and local register,i.e.,Local Handle Register(LHR).The aspects of the network interaction and the compatibility of IoT end-devices with the integrated dOA identifiers in heterogeneous communication networks are *** developed model is simulated for a wide-area network with allocated registers,and the results are introduced and discussed.

关键词： Internet of things identification digital object architecture handle system security

Hyperspectral Images-Based Crop Classification Scheme for Agricultural Remote Sensing

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Computer Systems Science & Engineering 2023年第7期46卷 303-319页

作者： Imran Ali Zohaib Mushtaq Saad Arif abeer d.algarni Naglaa F.Soliman Walid El-Shafai department of Mechanical Engineering National Taiwan University of Science and TechnologyTaipei City106335TaiwanChina department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan department of Mechanical Engineering HITEC University TaxilaTaxila Cantt.47080Pakistan department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia

Hyperspectral imaging is gaining a significant role in agricultural remote sensing *** data unit is the hyperspectral cube which holds spatial information in two dimensions while spectral band information of each pixel in the third *** classification accuracy of hyperspectral images(HSI)increases significantly by employing both spatial and spectral *** this work,the data was acquired using an airborne hyperspectral imager system which collected HSI in the visible and near-infrared(VNIR)range of 400 to 1000 nm wavelength within 180 spectral *** dataset is collected for nine different crops on agricultural land with a spectral resolution of 3.3 nm wavelength for each *** data was cleaned from geometric distortions and stored with the class labels and annotations of global localization using the inertial navigation *** this study,a unique pixel-based approach was designed to improve the crops'classification accuracy by using the edge-preserving features(EPF)and principal component analysis(PCA)in *** preliminary processing generated the high-dimensional EPF stack by applying the edge-preserving filters on acquired *** the second step,this high dimensional stack was treated with the PCA for dimensionality reduction without losing significant spectral *** resultant feature space(PCA-EPF)demonstrated enhanced class separability for improved crop classification with reduced dimensionality and computational *** support vector machines classifier was employed for multiclass classification of target crops using *** classification performance evaluation was measured in terms of individual class accuracy,overall accuracy,average accuracy,and Cohen kappa *** proposed scheme achieved greater than 90%results for all the performance evaluation *** PCA-EPF proved to be an effective attribute for crop classification using hyperspectral imaging in the VNIR *** proposed scheme

关键词： Hyperspectral imaging visible and near-infrared edge preserving feature dimensionality reduction crop classification

Efficient Forgery detection Approaches for digital Color Images

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Computers, Materials & Continua 2022年第5期71卷 3257-3276页

作者： Amira Baumy abeer d.algarni Mahmoud Abdalla Walid El-Shafai Fathi E.Abd El-Samie Naglaa F.Soliman department of Communications High Institute for Engineering and TechnologyAl-Obour Obour CityEgypt department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia

This paper is concerned with a vital topic in image processing:color image forgery detection. The development of computing capabilitieshas led to a breakthrough in hacking and forgery attacks on signal, image,and data communicated over networks. Hence, there is an urgent need fordeveloping efficient image forgery detection algorithms. Two main types offorgery are considered in this paper: splicing and copy-move. Splicing isperformed by inserting a part of an image into another image. On the otherhand, copy-move forgery is performed by copying a part of the image intoanother position in the same image. The proposed approach for splicingdetection is based on the assumption that illumination between the originaland tampered images is different. To detect the difference between the originaland tampered images, the homomorphic transform separates the illuminationcomponent from the reflectance component. The illumination histogramderivative is used for detecting the difference in illumination, and henceforgery detection is accomplished. Prior to performing the forgery detectionprocess, some pre-processing techniques, including histogram equalization,histogram matching, high-pass filtering, homomorphic enhancement, andsingle image super-resolution, are introduced to reinforce the details andchanges between the original and embedded sections. The proposed approachfor copy-move forgery detection is performed with the Speeded Up RobustFeatures (SURF) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matchingwith Euclidian distance and hierarchical clustering. In addition, some preprocessing methods are used with the SURF algorithm, such as histogramequalization and single-mage super-resolution. Simulation results proved thefeasibility and the robustness of the pre-processing step in homomorphicdetection and SURF detection algorithms for splicing and copy-move forgerydetection, respectively.

关键词： Image forgery splicing algorithm copy-move algorithm histogram matching homomorphic enhancement SISR SURF

Secure and Robust Optical Multi-Stage Medical Image Cryptosystem

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Computers, Materials & Continua 2022年第1期70卷 895-913页

作者： Walid El-Shafai Moustafa H.Aly abeer d.algarni Fathi E.Abd El-Samie Naglaa F.Soliman department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt department of Electronics and Communications Engineering College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

due to the rapid growth of telemedicine and healthcare services,color medical image security applications have been expanded *** this paper,an asymmetric PTFrFT(Phase Truncated Fractional Fourier Transform)-based color medical image cryptosystem is *** different phases in the fractional Fourier and output planes are provided as deciphering ***,the ciphering keys will not be employed for the deciphering ***,the introduced PTFrFT algorithm comprises asymmetric ciphering and deciphering processes in contrast to the traditional optical symmetric OSH(Optical Scanning Holography)and dRPE(double Random Phase Encoding)*** of the principal impacts of the introduced asymmetric cryptosystem is that it eliminates the onedimensionality aspects of the related symmetric cryptosystems due to its remarkable feature of phase nonlinear truncation *** comparisons on various colormedical images are examined and analyzed to substantiate the cryptosystem *** achieved experimental outcomes ensure that the introduced cryptosystem is robust and *** has terrific cryptography performance compared to conventional cryptography algorithms,even in the presence of noise and severe channel attacks.

关键词： Optical encryption medical image security symmetric and asymmetric encryption OSH dRPE PTFrFT

Proposed different Signal Processing Tools for Efficient Optical Wireless Communications

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Computers, Materials & Continua 2022年第5期71卷 3293-3318页

作者： Hend Ibrahim abeer d.algarni Mahmoud Abdalla Walid El-Shafai Fathi E.Abd El-Samie Naglaa F.Soliman department of Electronics and Communications Engineering Faculty of EngineeringZagazig UniversityZagazig44519Egypt 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 Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh 11586Saudi Arabia

Optical Wireless Communication(OWC)is a new trend in communication systems to achieve large bandwidth,high bit rate,high security,fast deployment,and low *** basic idea of the OWC is to transmit data on unguided media with *** system requires multi-carrier modulation such as Orthogonal Frequency division Multiplexing(OFdM).This paper studies optical OFdM performance based on Intensity Modulation with direct detection(IM/dd)*** system requires a non-negativity *** paper presents a framework for wireless optical OFdM system that comprises(IM/dd)with different forms,direct Current biased Optical OFdM(dCO-OFdM),Asymmetrically Clipped Optical OFdM(ACO-OFdM),Asymmetrically dC-biased Optical OFdM(AdO-OFdM),and *** also considers channel coding as a tool for error control,channel equalization for reducing deterioration due to channel effects,and investigation of the turbulence *** evaluation results of the proposed framework reveal enhancement of *** performance of the IM/dd-OFdM system is investigated over different channel models such as AWGN,log-normal turbulence channel model,and ceiling bounce channel *** simulation results show that the BER performance of the IM/dd-OFdM communication system is enhanced while the fading strength is *** results reveal also that Hamming codes,BCH codes,and convolutional codes achieve better BER ***,two algorithms of channel estimation and equalization are considered and *** algorithms include the Least Squares(LS)and the Minimum Mean Square Error(MMSE).The simulation results show that the MMSE algorithm gives better BER performance than the LS algorithm.

关键词： Optical communication systems OWC IM/dd OFdM MMSE LS AdO-OFdM dCO-OFdM ACO-OFdM

COVId-19 Classification from X-Ray Images:An Approach to Implement Federated Learning on decentralized dataset

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Computers, Materials & Continua 2023年第5期75卷 3883-3901页

作者： Ali Akbar Siddique S.M.Umar Talha M.Aamir abeer d.algarni Naglaa F.Soliman Walid El-Shafai department of Telecommunication Engineering Sir Syed University of Engineering&TechnologyKarachi75300Pakistan department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The COVId-19 pandemic has devastated our daily lives,leaving horrific repercussions in its *** to its rapid spread,it was quite difficult for medical personnel to diagnose it in such a big *** who test positive for Covid-19 are diagnosed via a nasal PCR *** comparison,polymerase chain reaction(PCR)findings take a few hours to a few *** PCR test is expensive,although the government may bear expenses in certain ***,subsets of the population resist invasive testing like ***,chest X-rays or Computerized Vomography(CT)scans are preferred in most cases,and more importantly,they are non-invasive,inexpensive,and provide a faster response *** advances in Artificial Intelligence(AI),in combination with state-of-the-art methods,have allowed for the diagnosis of COVId-19 using chest *** article proposes a method for classifying COVId-19 as positive or negative on a decentralized dataset that is based on the Federated learning *** order to build a progressive global COVId-19 classification model,two edge devices are employed to train the model on their respective localized dataset,and a 3-layered custom Convolutional Neural Network(CNN)model is used in the process of training the model,which can be deployed from the *** two edge devices then communicate their learned parameter and weight to the server,where it aggregates and updates the *** proposed model is trained using an image dataset that can be found on *** are more than 13,000 X-ray images in Kaggle database collection,from that collection 9000 images of Normal and COVId-19 positive images are *** edge node possesses a different number of images;edge node 1 has 3200 images,while edge node 2 has *** is no association between the datasets of the various nodes that are included in the *** doing it in this manner,each of the nodes will have access to a separate image collection that has no correl

关键词： Artificial intelligence deep learning federated learning COVId-19 decentralized image dataset

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