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Massless Dirac perturbations of.black holes in f.Q)gravity:quasinormal modes and a weak def.ection angle

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Communications in Theoretical Physics 2024年第9期76卷 73-82页

作者： Ahmad al-Badawi Sohan Kumar Jha Department of.Physics Al-Hussein Bin Talal UniversityPO Box 2071111Ma'anJordan Department of.Physics Chandernagore CollegeChandernagoreHooghlyWest BengalIndia

This article considers a static and spherical black hole(BH)in f.Q)gravity.f.Q)gravity is the extension of.symmetric teleparallel general relativity,where both curvature and torsion are vanishing and gravity is described by *** this study,we investigate the possible implications of.quasinormal mode(QNM)modif.ed Hawking spectra and def.ection angles generated by the *** Wentzel–Kramers–Brillouin method is used to solve the equations of.motion f.r massless Dirac perturbation f.elds and explore the impact of.the nonmetricity parameter(Q_(0)).Based on the QNM computation,we can ensure that the BH is stable against massless Dirac perturbations and as Q_(0)increases the oscillatory f.equency of.the mode *** then discuss the weak def.ection angle in the weak f.eld limit *** compute the def.ection angle up to the f.urth order of.approximation and show how the nonmetricity parameter af.ects *** f.nd that the Q_(0)parameter reduces the def.ection angle.

关键词： black holes in f.Q)gravity massless Dirac perturbations quasinormal modes def.ection angle

Tuning the optoelectronic properties f.r small organic compounds as organic solar cell applications

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Optoelectronics Letters 2024年第7期20卷 412-417页

作者： Hussein K.Mejbel Laf. f.al-Badry Department of.Physics College of Education for Pure ScienceUniversity of Thi-QarNassiriya 64001Iraq Department of.Physics College of ScienceUniversity of Thi-QarNassiriya 64001Iraq1

Recently,organic solar cells have attracted the attention of.many researchers owing to f.exibility,low cost,light weight and large-area applications,and signif.cant improvement in the power conversion ef.iciency(PCE).In this work,we designed chains f.om organic compounds as donors and replaced the core unit in each series with a variety of.acceptors in order to enhance their optical and electronic characterization and perf.rmance f.r power conversion ef.iciencies in organic solar *** utilized density f.nctional theory(Df.)and time-dependent density f.nctional theory(TD-Df.)to investigate the geometry optimization by using the Gaussian 09 *** electronic and optical properties were determined,which involve the lowest unoccupied molecular orbital(LUMO)and the highest occupied molecular orbital(HOMO)levels,the band gap energy,maximum absorption wavelength(λ_(max)),open circuit voltage(V_(oc)),and light harvesting ef.iciency(LHE).Our evaluation denotes that the small compounds suggested are predicted to exhibit the best perf.rmance compared to the f.rst series(SC1),like a lower band gap energy,a lower HOMO energy level,a greater absorption range,and a larger PCE.

关键词： orbital occupied compounds

Leveraging User-Generated Comments and f.sed BiLSTM Models to Detect and Predict Issues with Mobile Apps

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Computers, Materials & Continua 2024年第4期79卷 735-759页

作者： Wael M.S.Yaf.oz abdullah alsaeedi Department of.Computer Science College of Computer Science and EngineeringTaibah UniversityMedina42353Saudi Arabia

In the last decade, technical advancements and f.ster Internet speeds have also led to an increasing number of.obile devices and users. Thus, all contributors to society, whether young or old members, can use these mobileapps. The use of.these apps eases our daily lives, and all customers who need any type of.service can accessit easily, comf.rtably, and ef.iciently through mobile apps. Particularly, Saudi Arabia greatly depends on digitalservices to assist people and visitors. Such mobile devices are used in organizing daily work schedules and services,particularly during two large occasions, Umrah and Hajj. However, pilgrims encounter mobile app issues such asslowness, conf.ict, unreliability, or user-unf.iendliness. Pilgrims comment on these issues on mobile app platf.rmsthrough reviews of.their experiences with these digital services. Scholars have made several attempts to solve suchmobile issues by reporting bugs or non-f.nctional requirements by utilizing user ***, solving suchissues is a great challenge, and the issues still exist. Theref.re, this study aims to propose a hybrid deep learningmodel to classif. and predict mobile app sof.ware issues encountered by millions of.pilgrims during the Hajj andUmrah periods f.om the user perspective. f.rstly, a dataset was constructed using user-generated comments f.omrelevant mobile apps using natural language processing methods, including inf.rmation extraction, the annotationprocess, and pre-processing steps, considering a multi-class classif.cation problem. Then, several experimentswere conducted using common machine learning classif.ers, Artif.cial Neural Networks (ANN), Long Short-TermMemory (LSTM), and Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) architectures, toexamine the perf.rmance of.the proposed model. Results show 96% in f.-score and accuracy, and the proposedmodel outperf.rmed the mentioned models.

关键词： Mobile apps issues play store user comments deep learning LSTM bidirectional LSTM

Quantitative and Qualitative Responses of.Hydroponic Tomato Production to Dif.erent Levels of.Salinity

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Phyton-International Journal of.Experimental Botany 2024年第6期93卷 1311-1323页

作者： Khalid A.al-Gaadi Ahmed M.Zeyada ElKamil Tola abdullah M.alhamdan Khalid A.M.Ahmed Rangaswamy Madugundu Mohamed K.Edrris Department of.Agricultural Engineering College of Food and Agriculture SciencesKing Saud UniversityRiyadh11451Saudi Arabia Precision Agriculture Research Chair Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Chair of.Dates Industry&Technology Deanship of Scientific ResearchKing Saud UniversityRiyadh11451Saudi Arabia Agricultural Research Centre Agricultural Engineering Research Institute(AEnRI)Giza12619Egypt

f.om economic and nutritional points of.view,tomato is,historically,considered one of.the most important *** signiﬁcant yield reduction,most commercial cultivars of.tomato crops are sensitive to moderate levels of.***,high levels of.salt stress can negatively af.ect the yield and quality of.tomato ***,this study was conducted to evaluate the yield and f.uit quality of.three tomato cultivars(f.rester,Ghandowra-f.,and f.isty-Red)cultivated hydroponically,under three dif.erent levels of.nutrient solution *** of.tomato f.uits was perf.rmed based on quantity(number and weight of.f.uits,and total f.uit yield),physical quality(color andﬁrmness),and chemical quality(ref.actometric index“Brix”,pH,EC,K^(+),Na^(+),and NO_(3)-).Experiments were conducted using three salinity levels of.the nutrient solution with electrical conductivity values(dSm^(-1))of.2.5(control),6.0,and *** showed that the studied tomato cultivars were signiﬁcantly inﬂuenced by high salinity(9.5 dSm^(-1))in comparison to the low(2.5 dSm^(-1))and medium(6.0 dSm^(-1))levels of.*** average,the highest f.uit weight per plant of.1944.84 g and total f.uit yield of.4.42 kgm^(-2) were observed at the low salinity level;however,no signiﬁcant dif.erences were obtained in the two yield f.ctors(single f.uit weight and total f.uit yield)f.r the low and medium salinity *** the other hand,a signiﬁcant reduction in tomato yield(31%)was associated with the high salinity level compared to the yield at low and medium salinity *** of.physical quality parameters showed highly signiﬁcant dif.erences among all salinity *** average,the maximum value of.color change(1.72)was associated with the medium salinity level,and the maximum value of.rmness(9.61 Ncm^(-1))was recorded at the high salinity *** levels and tomato cultivars introduced signiﬁcant dif.erences in chemical quality parameters;however,no signiﬁcant dif.erences in these

关键词： Quality cultivars yield color ﬁrmness brix

Machine Learning Enabled Novel Real-Time IoT Targeted DoS/DDoS Cyber Attack Detection System

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Computers, Materials & Continua 2024年第9期80卷 3655-3683页

作者： abdullah alabdulatif.Navod Neranjan Thilakarathne Mohamed Aashiq Department of.Cybersecurity College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of.ICT Faculty of TechnologyUniversity of ColomboColombo00700Sri Lanka Department of.Computer Science and Engineering Faculty of EngineeringSouth Eastern University of Sri LankaOluvil32360Sri Lanka

The increasing prevalence of.Internet of.Things(IoT)devices has introduced a new phase of.connectivity in recent years and,concurrently,has opened the f.oodgates f.r growing cyber *** the myriad of.potential attacks,Denial of.Service(DoS)attacks and Distributed Denial of.Service(DDoS)attacks remain a dominant concern due to their capability to render services inoperable by overwhelming systems with an inf.ux of.*** IoT devices of.en lack the inherent security measures f.und in more mature computing platf.rms,the need f.r robust DoS/DDoS detection systems tailored to IoT is paramount f.r the sustainable development of.every domain that IoT *** this study,we investigate the ef.ectiveness of.three machine learning(ML)algorithms:extreme gradient boosting(XGB),multilayer perceptron(MLP)and random f.rest(Rf.,f.r the detection of.IoTtargeted DoS/DDoS attacks and three f.ature engineering methods that have not been used in the existing stateof.the-art,and then employed the best perf.rming algorithm to design a prototype of.a novel real-time system towards detection of.such DoS/DDoS *** CICIoT2023 dataset was derived f.om the latest real-world IoT traf.ic,incorporates both benign and malicious network traf.ic patterns and af.er data preprocessing and f.ature engineering,the data was f.d into our models f.r both training and validation,where f.ndings suggest that while all threemodels exhibit commendable accuracy in detectingDoS/DDoS attacks,the use of.particle swarmoptimization(PSO)f.r f.ature selection has made great improvements in the perf.rmance(accuracy,precsion recall and f.-score of.99.93%f.r XGB)of.the ML models and their execution time(491.023 sceonds f.r XGB)compared to recursive f.ature elimination(Rf.)and randomf.rest f.ature importance(Rf.)*** proposed real-time system f.r DoS/DDoS attack detection entails the implementation of.an platf.rm capable of.ef.ectively processing and analyzing network traf.ic in *** inv

关键词： Machine learning Internet of.Things(IoT),DoS,DDoS cybersecurity intrusion prevention network security,f.ature optimization,sustainability

RoGRUT: A Hybrid Deep Learning Model f.r Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： f.rah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of.Excellence in Inf.rmation Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of.Computer&Inf.rmation Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity thef. is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of.utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of.smart grids is crucial f.r the identif.cation of.power thef. since these systems create enormous amounts of.data,including inf.rmation on client consumption,which may be used to identif. electricity thef. using machine learning and deep learning ***,there also exist dif.erent solutions such as hardware-based solutions to detect electricity thef. that may require human resources and expensive ***-based solutions are presented in the literature to identif. electricity thef. but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of.such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity thef. as amalicious and non-malicious *** key steps of.the RoGRUT are data preprocessing that covers the problem of.class imbalance,f.ature extraction and f.nal thef. *** advanced-level models like RoBERTa is used to address the curse of.dimensionality issue,the near miss f.r class imbalance,and transf.r learning f.r *** ef.ectiveness of.the RoGRUTis evaluated using the dataset f.omactual smartmeters.A signif.cant number of.simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classif.cation *** perf.rmance evaluation of.the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The f.-Score,a measure of.overall perf.rmance,stood at 85%.f.rthermore,themodel exhibited a noteworthyMatthew correlation coef.icient of.78%and excelled with an area under the curve of.91%.

关键词： Electricity thef. smart grid RoBERTa GRU transf.r learning

Low-Cost and Biodegradable Thermoelectric Devices Based on van der Waals Semiconductors on Paper Substrates

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Energy & Environmental Materials 2024年第1期7卷 201-206页

作者： Gulsum Ersu Carmen Munuera f.derico J.Mompean Daniel Vaquero Jorge Quereda João Elias f.S.Rodrigues Jose A.alonso Eduardo f.ores Jose R.Ares Isabel J.f.rrer abdullah M.al-Enizi Ayman Naf.dy Sruthi Kuriakose Joshua O.Island Andres Castellanos-Gomez Materials Science f.ctory Instituto de Ciencia de Materiales de Madrid(ICMM-CSIC)Madrid E-28049Spain Nanotechnology Group USAL-NanolabUnivesidad de SalamancaSalamanca Junta de Castilla y León 37007Spain GISC Departamento de Física de MaterialesUniversidad Complutense de MadridMadrid E-28040Spain Departamento de f.sica Aplicada Centro de Investigación y Estudios AvanzadosMérida 97310Mexico MIRE Group Departamento de Física de MaterialesUniversidad Autónoma de MadridMadrid E-28049Spain Instituto Nicolás Cabrera Universidad Autónoma de MadridMadrid E-28049Spain Department of.Chemistry College of ScienceKing Saud UniversityRiyadh 11451Saudi Arabia Department of.Physics and Astronomy University of Nevada Las VegasLas Vegas NV 89154USA

We present a method to f.bricate handcraf.ed thermoelectric devices on standard of.ice paper *** devices are based on thin f.lms of.WS_(2),Te,and BP(P-type semiconductors)and TiS_(3)and TiS_(2)(N-type semiconductors),deposited by simply rubbing powder of.these materials against *** thermoelectric properties of.these semiconducting f.lms revealed maximum Seebeck coef.icients of.+1.32±0.27)mV K^(-1)and(-0.82±0.15)mV K^(-1)f.r WS_(2)and TiS_(3),***,Peltier elements were f.bricated by interconnecting the P-and N-type f.lms with graphite electrodes.A thermopower value up to 6.11 mV K^(-1)was obtained when the Peltier element were constructed with three *** f.ndings of.this work show proof.of.concept devices to illustrate the potential application of.semiconducting van der Waals materials in f.ture thermoelectric power generation as well as temperature sensing f.r low-cost disposable electronic devices.

关键词： paper-based electronics Seebeck ef.ect semiconductors thermoelectrics van der Waals materials

Assessment of.Appropriateness of.Diagnostic Lymph Node Tissue Collection f.om the Operating Theater and by Interventional Radiologist. A Clinical Audit

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Advances in Inf.ctious Diseases 2024年第3期14卷 541-548页

作者： Kowthar Salman Hassan Divya Deodhar abdullah T. al-Rawahi Mahmood H. al Abri Department of.Medicine Infectious Diseases Sultan Qaboos University Hospital Muscat Oman Department of.Inf.ction Control Sultan Qaboos University Hospital Muscat Oman Department of.Radiology and Molecular Imaging Sultan Qaboos University Hospital Muscat Oman

Background: Appropriate sample requesting, collecting and timely dispatch to the appropriate laboratory is essential in establishing diagnosis of.pathologies with lesions. Much time and ef.ort may be wasted if.this is not done according to certain standards. We conducted this study to assess the route of.lymph node samples f.om requests to reaching the laboratories. Methods: We conducted an audit over a period f.om 4th June until 10th Aug 2023. Data f.r all the procedures perf.rmed over this period on lymph node samples (was entered into and analysed using Excel. Results: A total of.eighteen samples f.r sixteen patients were obtained during this period. Median age of.the patients was 34 years (19 - 73) with a M:f.ratio of.5:11. Among the IR samples, nine samples were f.om the neck, three f.om inguinal area and one f.om axilla. Seven samples (53.8%) were tru-cut biopsies, six samples (46.15%) were f.A. all samples were sent to the pathology laboratory f.xed in f.rmalin. Samples f.r TB were sent only f.r f.ve cases (31.25%) and f.r only two cases (12.5%) were samples sent f.r bacterial culture. f.r the OR samples, none were sent f.r either bacterial culture or TB. Overall, eight patients (50%) were not investigated f.r any inf.ctious etiologies like brucella, toxoplasmosis, CMV, EBV plus other possible causes. Repeat sampling was required f.r 25% of.patients (within and out of.the audit period). Conclusions: to avoid delays in making diagnoses, it is paramount to consider inf.ctious etiologies as possible diagnosis f.r lymphadenopathy and request appropriate investigations. This requires liaising with inf.ctious diseases/clinical microbiology experts to guide regarding types of.samples, types of.media and timely dispatch to the correct laboratory.

关键词： Clinical Audit Clinical Samples Biopsies Lymph Nodes Saline f.rmalin Quality Improvement

Enhanced Object Detection and Classif.cation via Multi-Method f.sion

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Computers, Materials & Continua 2024年第5期79卷 3315-3331页

作者： Muhammad Waqas Ahmed Nouf.abdullah almujally Abdulwahab alazeb Asaad algarni Jeongmin Park Department of.Computer Science Air UniversityIslamabad44000Pakistan Department of.Inf.rmation Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of.Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of.Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of.Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073South Korea

Advances in machine vision systems have revolutionized applications such as autonomous driving,robotic navigation,and augmented *** substantial progress,challenges persist,including dynamic backgrounds,occlusion,and limited labeled *** address these challenges,we introduce a comprehensive methodology toenhance image classif.cation and object detection *** proposed approach involves the integration of.ultiple methods in a complementary *** process commences with the application of.Gaussian f.lters tomitigate the impact of.noise *** images are then processed f.r segmentation using f.zzy C-Meanssegmentation in parallel with saliency mapping techniques to f.nd the most prominent *** Binary RobustIndependent Elementary f.atures(BRIEf.characteristics are then extracted f.omdata derived f.omsaliency mapsand segmented *** precise object separation,Oriented f.ST and Rotated BRIEf.ORB)algorithms *** algorithms(GAs)are used to optimize Random f.rest classif.er parameters which lead toimproved *** method stands out due to its comprehensive approach,adeptly addressing challengessuch as changing backdrops,occlusion,and limited labeled data concurrently.A signif.cant enhancement hasbeen achieved by integrating Genetic algorithms(GAs)to precisely optimize *** minor adjustmentnot only boosts the uniqueness of.our system but also amplif.es its overall *** proposed methodologyhas demonstrated notable classif.cation accuracies of.90.9%and 89.0%on the challenging Corel-1k and MSRCdatasets,***,detection accuracies of.87.2%and 86.6%have been *** ourmethod perf.rmed well in both datasets it may f.ce dif.iculties in real-world data especially where datasets havehighly complex *** these limitations,GAintegration f.r parameter optimization shows a notablestrength in enhancing the overall adaptability and perf.rmance of.our system.

关键词： BRIEf.f.atures saliency map f.zzy c-means object detection object recognition