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Computer Modelling of Compact 28/38 GHz Dual-Band Antenna for Millimeter-Wave 5G Applications

Computer Modeling in Engineering & Sciences 2023年第12期137卷 2867-2879页

作者： Amit V.Patel Arpan Desai Issa Elfergani Hiren Mewada Chemseddine Zebiri Keyur Mahant Jonathan Rodriguez raed Abd-Alhameed Department of Electronics and Communication Engineering Chandubhai S Patel Institute of Technology(CSPIT)Charotar University of Science and Technology(CHARUSAT)Changa388421India The Instituto de Telecomunica珲es Campus Universitário de SantiagoAveiro3810-193Portugal School of Engineering and Informatics University of BradfordBradfordBD71DPUK Electrical Engineering Department Prince Mohammad Bin Fahd UniversityAl Khobar31952Saudi Arabia Department of Electronics Laboratoire d’Electronique de Puissance et Commande Industrielle(LEPCI)University of Ferhat AbbasSétif19000Algeria

A four-element compact dual-band patch antenna having a common ground plane operating at 28/38 GHz is proposed formillimeter-wave communication systems in this ***-input-multiple-output(MIMO)antenna geometry consists of a slotted ellipse enclosed within a hollow circle which is orthogonally rotated with a connected partial ground at the *** overall size of the four elements MIMO antenna is 2.24λ×2.24λ(at 27.12GHz).The prototype of four-element MIMOresonator is designed and printed using Rogers RTDuroid 5880 withε_(r)=2.2 and loss tangent=0.0009 and having a thickness of 0.8 *** covers dual-band having a fractional bandwidth of 15.7%(27.12-31.34 GHz)and 4.2%(37.21-38.81 GHz)for millimeter-wave applications with a gain of more than 4 dBi at both *** proposed antenna analysis in terms ofMIMOdiversity parameters(Envelope Correlation Coefficient(ECC)and Diversity Gain(DG))is also carried *** experimental result in terms of reflection coefficient,radiation pattern,gain and MIMOdiversity parameter correlates very well with the simulated ones that show the potential of the proposed design for MIMO applications at millimeter-wave frequencies.

关键词： Connected ground diversity parameters dual-band antenna fifth generation(5G) mmwave multiple input multiple output(MIMO)

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Performance Comparison of Deep and Machine Learning Approaches Toward COVID-19 Detection

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Intelligent Automation & Soft Computing 2023年第8期37卷 2247-2261页

作者： Amani Yahyaoui Jawad Rasheed Shtwai Alsubai raed M.Shubair Abdullah Alqahtani Buket Isler Rana Zeeshan Haider Department of Software Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of Software Engineering Nisantasi UniversityIstanbul34398Turkey Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Electrical and Computer Engineering New York University(NYU)Abu Dhabi129188United Arab Emirates College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Engineering Istanbul Topkapi UniversityIstanbul34087Turkey Baqai Institute of Hematology Baqai Medical UniversityKarachi75340Pakistan

The coronavirus(COVID-19)is a disease declared a global pan-demic that threatens the whole *** then,research has accelerated and varied to find practical solutions for the early detection and correct identification of this *** researchers have focused on using the potential of Artificial Intelligence(AI)techniques in disease diagnosis to diagnose and detect the *** paper developed deep learning(DL)and machine learning(ML)-based models using laboratory findings to diagnose *** different methods are used in this study:K-nearest neighbor(KNN),Decision Tree(DT)and Naive Bayes(NB)as a machine learning method,and Deep Neural Network(DNN),Convolutional Neural Network(CNN),and Long-term memory(LSTM)as DL *** approaches are evaluated using a dataset obtained from the Israelita Albert Einstein Hospital in Sao Paulo,*** data consists of 5644 laboratory results from different patients,with 10%being Covid-19 positive *** dataset includes 18 attributes that characterize *** used accuracy,f1-score,recall and precision to evaluate the different developed *** obtained results confirmed these approaches’effectiveness in identifying COVID-19,However,ML-based classifiers couldn’t perform up to the standards achieved by DL-based *** all,NB performed worst by hardly achieving accuracy above 76%,Whereas KNN and DT compete by securing 84.56%and 85%accuracies,*** these,DL models attained better performance as CNN,DNN and LSTM secured more than 90%*** LTSM outperformed all by achieving an accuracy of 96.78%and an F1-score of 96.58%.

关键词： Artificial intelligence COVID-19 deep learning diagnosis machine learning

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Multivariate Aggregated NOMA for Resource Aware Wireless Network Communication Security

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Computers, Materials & Continua 2023年第1期74卷 1693-1708页

作者： V.Sridhar K.V.Ranga Rao Saddam Hussain Syed Sajid Ullah Roobaea Alroobaea Maha Abdelhaq raed Alsaqour ECE Department Vidya Jyothi Institute of TechnologyIndia CSE Department Neil Gogte Institute of TechnologyIndia School of Digital Science Universiti Brunei DarussalamJalanTungku LinkGadong BE1410Brunei Darussalam Department of Information and Communication Technology University of Agder(UiA)N-4898 GrimstadNorway Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourahbint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Information Technology College of Computing and InformaticsSaudi Electronic University93499RiyadhSaudi Arabia

NonorthogonalMultiple Access(NOMA)is incorporated into the wireless network systems to achieve better connectivity,spectral and energy effectiveness,higher data transfer rate,and also obtain the high quality of services(QoS).In order to improve throughput and minimum latency,aMultivariate Renkonen Regressive Weighted Preference Bootstrap Aggregation based Nonorthogonal Multiple Access(MRRWPBA-NOMA)technique is introduced for network *** the downlink transmission,each mobile device’s resources and their characteristics like energy,bandwidth,and trust are *** by,the Weighted Preference Bootstrap Aggregation is applied to recognize the resource-efficient mobile devices for aware data transmission by constructing the different weak hypotheses i.e.,Multivariate Renkonen Regression *** on the classification,resource and trust-aware devices are selected for *** of the proposed MRRWPBA-NOMA technique and existing methods are carried out with different metrics such as data delivery ratio,throughput,latency,packet loss rate,and energy efficiency,signaling *** simulation results assessment indicates that the proposed MRRWPBA-NOMA outperforms well than the conventional methods.

关键词： Mobile network multivariate renkonen regression weighted preference bootstrap aggregation resource-aware secure data communication NOMA

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Volterra Integral Equation of Hermite Matrix Polynomials

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Analysis in Theory and Applications 2013年第2期29卷 97-103页

作者： raed S. Batahan Department of Mathematics Faculty of Science Hadhramout University of Science and Technology

The primary purpose of this paper is to present the Volterra integral equa- tion of the two-variable Hermite matrix polynomials. Moreover, a new representation of these matrix polynomials are established here.

关键词： Hermite matrix polynomials three terms recurrence relation and Volterra integralequation.

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Performance analysis of space-shift keying over negative-exponential and log-normal FSO channels

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Chinese Optics Letters 2015年第5期13卷 26-30页

作者： Mohamed Abaza raed Mesleh Ali Mansour el-Hadi Aggoune Sensor Networks and Cellular Systems (SNCS) Research Center University of Tabuk Electrical Engineering Department University of Tabuk Lab STICC ENSTA Bretagne

The average bit-error rate （ABER） performance of free-space optical （FSO） communication links is investigated for space-shift keying （SSK） over log-normal and negative-exponential atmospheric turbulence channels. SSK is compared with repetition codes and a single-input single-output system using multiple pulse amplitude mod- ulations. Simulation results show that the signal-to-noise ratio gain of SSK largely increases with greater spectral efficiencies and/or higher turbulence effects. A tight bound for ABER is derived based on an exact moment generation function （MGF） for negative-exponential channel and an approximate MGF for log-normal channel. Finally, extensive Monte Carlo simulations are run to validate the analytical analysis.

关键词： SSK Performance analysis of space-shift keying over negative-exponential and log-normal FSO channels FSO over

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Generalized Form of Hermite Matrix Polynomials via the Hypergeometric Matrix Function

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Advances in Linear Algebra & Matrix Theory 2014年第2期4卷 134-141页

作者： raed S. Batahan Department of Mathematics Faculty of Science Hadhramout University Hadhranout Yemen

The object of this paper is to present a new generalization of the Hermite matrix polynomials by means of the hypergeometric matrix function. An integral representation, differential recurrence relation and some other properties of these generalized forms are established here. Moreover, some new properties of the Hermite and Chebyshev matrix polynomials are obtained. In particular, the two-variable and two-index Chebyshev matrix polynomials of two matrices are presented.

关键词： Hermite and Chebyshev Matrix Polynomials Three Terms Recurrence Relation Hypergeometric Matrix Function and Gamma Matrix Function

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Chaotic Flower Pollination with Deep Learning Based COVID-19 Classification Model

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Computers, Materials & Continua 2023年第3期74卷 6195-6212页

作者： T.Gopalakrishnan Mohamed Yacin Sikkandar raed Abdullah Alharbi P.Selvaraj Zahraa H.Kareem Ahmed Alkhayyat Ali Hashim Abbas Department of Information Technology Manipal Institute of Technology BengaluruManipal Academy of Higher EducationManipalIndia Department of Medical Equipment Technology College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Public Health Department College of Applied Medical SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Computing Technologies College of Engineering and TechnologyFaculty of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203TamilnaduIndia Medical Instrumentation Techniques Engineering Department Al-Mustaqbal University CollegeBabylonIraq College of Technical Engineering The Islamic UniversityNajafIraq College of Information Technology Imam Ja’afar Al-Sadiq UniversityAl-Muthanna66002Iraq

The Coronavirus Disease(COVID-19)pandemic has exposed the vulnerabilities of medical services across the globe,especially in underdeveloped *** the aftermath of the COVID-19 outbreak,a strong demand exists for developing novel computer-assisted diagnostic tools to execute rapid and cost-effective screenings in locations where many screenings cannot be executed using conventional *** imaging has become a crucial component in the disease diagnosis process,whereas X-rays and Computed Tomography(CT)scan imaging are employed in a deep network to diagnose the *** general,four steps are followed in image-based diagnostics and disease classification processes by making use of the neural networks,such as network training,feature extraction,model performance testing and optimal feature *** current research article devises a Chaotic Flower Pollination Algorithm with a Deep Learning-Driven Fusion(CFPADLDF)approach for detecting and classifying *** presented CFPA-DLDF model is developed by integrating two DL models to recognize COVID-19 in medical ***,the proposed CFPA-DLDF technique employs the Gabor Filtering(GF)approach to pre-process the input *** addition,a weighted voting-based ensemble model is employed for feature extraction,in which both VGG-19 and the MixNet models are ***,the CFPA with Recurrent Neural Network(RNN)model is utilized for classification,showing the work’s novelty.A comparative analysis was conducted to demonstrate the enhanced performance of the proposed CFPADLDF model,and the results established the supremacy of the proposed CFPA-DLDF model over recent approaches.

关键词： Deep learning medical imaging fusion model chaotic models ensemble model COVID-19 detection

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Wind Driven Optimization-Based Medical Image Encryption for Blockchain-Enabled Internet of Things Environment

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Computers, Materials & Continua 2022年第11期73卷 3219-3233页

作者： C.S.S.Anupama raed Alsini N.Supriya E.Laxmi Lydia Seifedine Kadry Sang-Soo Yeo Yongsung Kim Department of Electronics&Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Malla Reddy Engineering College(A)Hyderabad500100India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University College4612KristiansandNorway Department of Computer Engineering Mokwon UniversityDaejeon35349Korea Department of Technology Education Chungnam National University 99Daehak-roYuseong-guDaejeon34134Korea

Internet of Things(IoT)and blockchain receive significant interest owing to their applicability in different application areas such as healthcare,finance,transportation,*** image security and privacy become a critical part of the healthcare sector where digital images and related patient details are communicated over the public *** paper presents a new wind driven optimization algorithm based medical image encryption(WDOA-MIE)technique for blockchain enabled IoT *** WDOA-MIE model involves three major processes namely data collection,image encryption,optimal key generation,and data ***,the medical images were captured from the patient using IoT ***,the captured images are encrypted using signcryption *** addition,for improving the performance of the signcryption technique,the optimal key generation procedure was applied by WDOA *** goal of the WDOA-MIE algorithm is to derive a fitness function dependent upon peak signal to noise ratio(PSNR).Upon successful encryption of images,the IoT devices transmit to the closest server for storing it in the blockchain *** performance of the presented method was analyzed utilizing the benchmark medical image *** security and the performance analysis determine that the presented technique offers better security with maximum PSNR of 60.7036 dB.

关键词： Internet of things image security medical images encryption optimal key generation blockchain

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Radiographic study of the root canal system of mandibular incisors in Palestinian population

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Open Journal of Stomatology 2013年第8期3卷 452-456页

作者： raed Mukhaimer Maher Jarbawi Department of Conservative Dentistry Arab American University Jenin Palestine

Aim: The aim of this study was to survey the root canal morphology of mandibular incisor teeth in a Palestinian population using radiographic approach. Materials and Methods: Five hundred and twenty two extracted mandibular incisor teeth were randomly collected from Palestinian population. The teeth were radiographed from a mesiodistal direction and examined for the presence of a second canal and for the type of canal configuration. Results: All teeth had single root. Three hundred and sixty nine teeth (70.7%) had one canal (type I Vertucci classification). The rest (29.3%) had a second canal (type II and III). Conclusion: Mandibular central and lateral teeth were mostly found to have one root and Type I canal system.

关键词： Mandibular Incisors Radiography Root Canal System

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一种适于信号压缩正弦模型的匹配跟踪方法(英文)

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华南理工大学学报（自然科学版） 2001年第10期29卷 38-41页

作者： Al-Moussawy raed 尹俊勋熊鹰黄建成华南理工大学电子与信息工程学院广东广州510640 中国研究中心上海200041

在基于包方式传输的网络中进行高频信号的实时传输时 ,利用信号模型对信号进行压缩有强大的生命力 .基于帧结构的匹配跟踪原理 ,提出了一种有效而灵活的正弦模型分解方法 .利用匹配跟踪算法 ,通过迭代抽取每帧信号的一组正弦成分 ,把这... 详细信息

在基于包方式传输的网络中进行高频信号的实时传输时 ,利用信号模型对信号进行压缩有强大的生命力 .基于帧结构的匹配跟踪原理 ,提出了一种有效而灵活的正弦模型分解方法 .利用匹配跟踪算法 ,通过迭代抽取每帧信号的一组正弦成分 ,把这些成分通过帧重叠相加就可以重构原来的信号 .使用高频域的快速傅氏变换算法 (FFT)能有效快速地实现整个模型 .本文提出的方法可用于信号压缩和调整 ,由于抽取的正弦成分是以人耳感觉的好坏排序的 ,因此该方法特别适合于音频信号的逐级压缩 .

关键词：正弦模型匹配跟踪音频压缩信号压缩

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