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An Optimized Approach to Deep Learning for Botnet Detection and Classification for Cybersecurity in Internet of Things Environment

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Computers, Materials & Continua 2024年第8期80卷 2331-2349页

作者： abdulrahman alzahrani Department of Computer Science and Engineering College of Computer Science and EngineeringUniversity of Hafr Al BatinP.O.Box 1803Hafr Al Batin39524Saudi Arabia

The recent development of the Internet of Things(IoTs)resulted in the growth of IoT-based DDoS *** detection of Botnet in IoT systems implements advanced cybersecurity measures to detect and reduce malevolent botnets in interconnected *** detection models evaluate transmission patterns,network traffic,and device behaviour to detect deviations from usual *** learning(ML)techniques detect patterns signalling botnet activity,namely sudden traffic increase,unusual command and control patterns,or irregular device *** addition,intrusion detection systems(IDSs)and signature-based techniques are applied to recognize known malware signatures related to *** ML and deep learning(DL)techniques have been developed to detect botnet attacks in IoT *** overcome security issues in an IoT environment,this article designs a gorilla troops optimizer with DL-enabled botnet attack detection and classification(GTODL-BADC)*** GTODL-BADC technique follows feature selection(FS)with optimal DL-based classification for accomplishing security in an IoT *** data preprocessing,the min-max data normalization approach is primarily *** GTODL-BADC technique uses the GTO algorithm to select features and elect optimal feature ***,the multi-head attention-based long short-term memory(MHA-LSTM)technique was applied for botnet ***,the tree seed algorithm(TSA)was used to select the optimum hyperparameter for the MHA-LSTM *** experimental validation of the GTODL-BADC technique can be tested on a benchmark *** simulation results highlighted that the GTODL-BADC technique demonstrates promising performance in the botnet detection process.

关键词： Botnet detection internet of things gorilla troops optimizer hyperparameter tuning intrusion detection system

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A Deep Learning Approach for Landmines Detection Based on Airborne Magnetometry Imaging and Edge Computing

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 2117-2137页

作者： ahmed Barnawi Krishan Kumar Neeraj Kumar Bander alzahrani Amal Almansour Faculty of Computing and Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyDeemed to be UniversityPatialaIndia

Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human *** detonation of these landmines results in thousands of casualties reported worldwide ***,there is a pressing need to employ diverse landmine detection techniques for their *** effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic *** can generate a contour plot or heat map that visually represents the magnetic field *** the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith *** computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine *** processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field *** enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the ***,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during *** paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and *** have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset *** simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry *** trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.

关键词： CNN deep learning landmine detection magnetometer mean average precision UAV

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A Hybrid Classification and Identification of Pneumonia Using African Buffalo Optimization and CNN from Chest X-Ray Images

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2497-2517页

作者： Nasser Alalwan ahmed I.Taloba Amr Abozeid ahmed Ibrahim alzahrani Ali H.Al-Bayatti Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Information System Department Faculty of Computers and InformationAssiut UniversityAssiutEgypt Mathematics Department Faculty of ScienceAl-Azhar UniversityCairoEgypt Cyber Technology Institute(CTI) De Montfort UniversityLeicesterUK

An illness known as pneumonia causes inflammation in the *** there is so much information available fromvarious X-ray images,diagnosing pneumonia has typically proven *** improve image quality and speed up the diagnosis of pneumonia,numerous approaches have been *** date,several methods have been employed to identify *** Convolutional Neural Network(CNN)has achieved outstanding success in identifying and diagnosing diseases in the fields of medicine and ***,these methods are complex,inefficient,and imprecise to analyze a big number of *** this paper,a new hybrid method for the automatic classification and identification of Pneumonia from chest X-ray images is *** proposed method(ABOCNN)utilized theAfrican BuffaloOptimization(ABO)algorithmto enhanceCNNperformance and *** Weinmed filter is employed for pre-processing to eliminate unwanted noises from chest X-ray images,followed by feature extraction using the Grey Level Co-Occurrence Matrix(GLCM)*** features are then selected from the dataset using the ABO algorithm,and ultimately,high-performance deep learning using the CNN approach is introduced for the classification and identification of *** results on various datasets showed that,when contrasted to other approaches,the ABO-CNN outperforms them all for the classification *** proposed method exhibits superior values like 96.95%,88%,86%,and 86%for accuracy,precision,recall,and F1-score,respectively.

关键词： African buffalo optimization convolutional neural network pneumonia X-ray

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Tensile Strain Capacity Prediction of Engineered Cementitious Composites (ECC) Using Soft Computing Techniques

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2925-2954页

作者： Rabar H.Faraj Hemn Unis ahmed Hardi Saadullah Fathullah Alan Saeed abdulrahman Farid Abed Civil Engineering Department University of HalabjaHalabjaIraq University of Sulaimani College of EngineeringCivil Engineering DepartmentSulaimaniIraq Civil Engineering Department Komar University of Science and TechnologySulaimaniIraq Department of Engineering Kurdistan Institution for Strategic Studies and Scientific ResearchesSulaimaniIraq Department of Civil Engineering American University of SharjahSharjah26666UAE

Plain concrete is strong in compression but brittle in tension,having a low tensile strain capacity that can significantly degrade the long-term performance of concrete structures,even when steel reinforcing is *** order to address these challenges,short polymer fibers are randomly dispersed in a cement-based matrix to forma highly ductile engineered cementitious composite(ECC).Thismaterial exhibits high ductility under tensile forces,with its tensile strain being several hundred times greater than conventional *** concrete is inherently weak in tension,the tensile strain capacity(TSC)has become one of the most extensively researched *** a result,developing a model to predict the TSC of the ECC and to optimize the mixture proportions becomes ***,the effort required for laboratory trial batches to determine the TSC is *** achieve the research objectives,five distinct models,artificial neural network(ANN),nonlinear model(NLR),linear relationship model(LR),multi-logistic model(MLR),and M5P-tree model(M5P),are investigated and employed to predict the TSCof ECCmixtures containing fly *** from115 mixtures are gathered and analyzed to develop a new *** input variables include mixture proportions,fiber length and diameter,and the time required for curing the various *** model’s effectiveness is evaluated and verified based on statistical parameters such as R2,mean absolute error(MAE),scatter index(SI),root mean squared error(RMSE),and objective function(OBJ)***,the ANN model outperforms the others in predicting the TSC of the ECC,with RMSE,MAE,OBJ,SI,and R2 values of 0.42%,0.3%,0.33%,0.135%,and 0.98,respectively.

关键词： Engineered cementitious composites fly ash curing time tensile strain capacity modeling

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The interplay mechanism between IDH mutation, MGMT-promoter methylation, and PRMT5 activity in the progression of grade 4 astrocytoma: unraveling the complex triad theory

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Oncology Research 2024年第6期32卷 1037-1045页

作者： MAHER KURDI ALAA ALKHOTANI abdulrahman SABBAGH EYAD FAIZO ahmed I.LARY ahmed K.BAMAGA MAJID ALMANSOURI BADR HAFIZ THAMER ALSHARIF SALEH BAEESA Department of Pathology Faculty of MedicineKing Abdulaziz UniversityRabighSaudi Arabia Department of Pathology College of MedicineUmm Al-Qura UniversityMakkahSaudi Arabia Department of Surgery Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Surgery Faculty of MedicineUniversity of TabukTabukSaudi Arabia Section of Neurosurgery Department of SurgeryKing Abdulaziz Medical CityJeddahSaudi Arabia Department of Pediatrics Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Clinical Biochemistry Faculty of MedicineKing Abdulaziz UniversityJeddahSaudi Arabia Department of Neurosciences King Faisal Specialist Hospital and Research CenterJeddahSaudi Arabia Department of Surgery King Abdulaziz Specialist HospitalTaifSaudi Arabia

Background:The dysregulation of Isocitrate dehydrogenase(IDH)and the subsequent production of 2-Hydroxyglutrate(2HG)may alter the expression of epigenetic proteins in Grade 4 *** interplay mechanism between IDH,O-6-methylguanine-DNA methyltransferase(MGMT)-promoter methylation,and protein methyltransferase proteins-5(PRMT5)activity,with tumor progression has never been ***:A retrospective cohort of 34 patients with G4 astrocytoma is classified into IDH-mutant and IDH-wildtype *** groups were tested for MGMT-promoter methylation and PRMT5 through methylation-specific and gene expression PCR ***-cohort statistical significance was ***:Both IDH-mutant WHO grade 4 astrocytomas(n=22,64.7%)and IDH-wildtype glioblastomas(n=12,35.3%)had upregulated PRMT5 gene expression except in one *** of the 22 IDH-mutant tumors,10(45.5%)tumors showed MGMT-promoter methylation and 12(54.5%)tumors had unmethylated *** IDH-wildtype tumors had unmethylated *** was a statistically significant relationship between MGMT-promoter methylation and IDH in G4 astrocytoma(p-value=0.006).Statistically significant differences in progression-free survival(PFS)were also observed among all G4 astrocytomas that expressed PRMT5 and received either temozolomide(TMZ)or TMZ plus other chemotherapies,regardless of their IDH or MGMT-methylation status(p-value=0.0014).Specifically,IDH-mutant tumors that had upregulated PRMT5 activity and MGMT-promoter methylation,who received only TMZ,have exhibited longer ***:The relationship between PRMT5,MGMT-promoter,and IDH is not ***,accumulation of D2-hydroxyglutarate(2-HG),which partially activates 2-OG-dependent deoxygenase,may not affect their *** IDH-wildtype glioblastomas,the 2HG-2OG pathway is typically inactive,leading to PRMT5 *** alone,compared to TMZ-plus,can increase PFS in upregulated PRMT5 ***,using a PRMT5 inhibitor in G4

关键词： Grade 4 astrocytoma Glioblastoma Isocitrate dehydrogenase(IDH) O-6-methylguanine-DNA methyltransferase(MGMT) Protein methyltransferase proteins-5(PRMT5) Progression-free survival(PFS)

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Burden of routine orthopedic implant removal a single center retrospective study

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World Journal of Orthopedics 2024年第2期15卷 139-146页

作者： Ammar K AlOmran Nader Alosaimi ahmed A Alshaikhi Omar M Bakhurji Khalid J alzahrani Basil Ziyad Salloot Tamim Omar Alabduladhem ahmed I AlMulhim Arwa Alumran Department of Orthopedic College of MedicineImam Abdulrahman Bin Faisal UniversityDammam 31441Saudi Arabia Health Information Management and Technology Department Imam Abdulrahman Bin Faisal UniversityDammam 31441Saudi Arabia

BACKGROUND Open reduction and internal fixation represent prevalent orthopedic procedures,sparking ongoing discourse over whether to retain or remove asymptomatic *** consensus on this matter is paramount for orthopedic *** study aims to quantify the impact of routine implant removal on patients and healthcare facilities.A retrospective analysis of implant removal cases from 2016 to 2022 at King Fahad Hospital of the University(KFHU)was conducted and subjected to statistical *** these cases,44%necessitated hospitalization exceeding one day,while 56%required only a single *** exhibited a 55%need for extended hospital stays,contrasting with 22.8%among the pediatric *** complication rate was 6%,with all patients experiencing at least one ***,34.1%required sick leave and 4.8%exceeded 14 *** anesthesia was predominant(88%).Routine implant removal introduces unwarranted complications,particularly in adults,potentially prolonging *** procedure strains hospital resources,tying up the operating room that could otherwise accommodate critical *** defined institutional guidelines are imperative to regulate this *** To measure the burden of routine implant removal on the patients and *** This is a retrospective analysis study of 167 routine implant removal cases treated at KFHU,a tertiary hospital in Saudi *** were collected in the orthopedic department at KFHU from February 2016 to August 2022,which includes routine asymptomatic implant removal cases across all age *** indications such as infection,pain,implant failure,malunion,nonunion,restricted range of motion,and prominent hardware were *** who had external fixators removed or joints replaced were also *** Between February 2016 and August 2022,360 implants were retrieved;however,only 167 of those who met the inclusion criteria were included in this

关键词： Implant removal Healed fracture Orthopedic implant Complications Healthcare system

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Extra-Oral Digital Panoramic Radiographic Interpretation and Clinical Findings of Stage IV Periodontitis among Some Samples Concerning Saudi/Non-Saudi Nationality

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Open Journal of Stomatology 2022年第2期12卷 42-61页

作者： Mohammed M. A. Abdulla Al-Abdaly Amer Hassan Alasmari Saeed J. Alqahtani ahmed abdulrahman alzahrani Jawaher Moshabab A. Al Ahmari Ghadeer Mohammed Mohammed Al-Abdaly Ibrahim Hassan Ibrahim Alqaysi Mohammed Dhafer Mohammed Al-Shamrani Periodontics and Community Dental Sciences Department College of Dentistry King Khalid University Abha Saudi Arabia College of Dentistry King Khalid University Abha Saudi Arabia Faculty of Dentistry Sana’a University Sana’a Republic of Yemen

Background: There are associations between the severity of periodontal diseases and some predisposing factors, such as age, race, and income rate. Therefore, the present study was designed to evaluate the extra-oral digital panoramic radiographic interpretation and clinical findings of stage IV periodontitis among some samples concerning Saudi/non-Saudi nationality. Material and Methods: The study comprised a random sample of 298 residents in Saudi Arabia referred to the internship program clinics at the College of Dentistry, King Khalid University. They were according to the age of participants as follows: youth (15 - 24 years), adults (25 - 64 years), and seniors (65 years and over) within two groups according to nationality (Saudi and non-Saudi). Clinical periodontal examination and radiographic extra oral digital panoramic radiographs were done, and then the periodontal parameters, the percentage of bone loss, and the pattern of bone loss were recorded. The data was collected, and the statistical analysis was performed with ANOVA test, Tukey’s test, Chi-square test, and T-test and considered a P-value at (p Results: The samples included 62 (20%) youth participants with mean of age (21.806 ± 3.390), 182 (57%) adults’ participants with mean age (42.802 ± 9.094), and 54 (23%) seniors participants with a mean age (69.074 ± 6.810). There were highly statistically significant differences in the comparison between the participants’ ages (P 0.05). Conclusion: At the end of this study, we concluded that there are alterations in clinical and radiographic and clinical findings of stage IV periodontitis with the alteration of participants’ ages and nationality.

关键词： Extra-Oral Digital Panoramic Radiographs Nationality Stage IV Periodontitis

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The Impact of Severity of Periodontal Bone Loss and the Levels of Glycated Hemoglobin (HbA1c) on the Periodontal Clinical Parameters of the 2017 World Workshop among Type 2 Diabetic Patients in Saudi Arabia

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International Journal of Clinical Medicine 2021年第12期12卷 570-591页

作者： Mohammed M. A. Abdullah Al-Abdaly Amer Hassan Alasmari ahmed Khalid Asiri Saeed J. Alqahtani ahmed abdulrahman alzahrani Joharah Mughaddi Alwadai Mohammed Abdullah Thabit Periodontics and Community Dental Sciences Department College of Dentistry King Khalid University Abha Saudi Arabia College of Dentistry King Khalid University Abha Saudi Arabia

Background: Type-2 diabetic patients (uncontrolled levels of glucose blood) usually have periodontal diseases and alveolar bone loss. Objectives: The present study was designed to clarify the impact of severity of periodontal bone loss and the levels of glycated hemoglobin (HbA1c) on the periodontal clinical parameters of the 2017 World Workshop among type 2 diabetic patients in Saudi Arabia (Saudi and non-Saudi). Material and Methods: This study was done on 298 type 2 diabetic patients, selected from the internship clinics, College of Dentistry, King Khalid University, Abha, Saudi Arabia. The selection of patients was dependent on the levels of glycated hemoglobin (HbA1c), and they were categorized into controlled (7% HbA1c). All patients were divided according to the severity of periodontal bone loss into three groups, group I: mild periodontal bone loss, group II: moderate periodontal bone loss, and group III: severe periodontal bone loss. Clinical evaluation of periodontal diseases was carried out by clinical parameters according to the 2017 World Workshop. All data were collected and analyzed. A p-value of Results: The severity of periodontal bone loss were determined in controlled type 2 diabetics (7% HbA1c). An increased percentage of patients with severe periodontal bone loss was observed in uncontrolled type 2 diabetics (>7% HbA1c) (42.9%), as compared to controlled type 2 diabetics (7% HbA1c). In contrast, we found an increased mea

关键词： Glycated Hemoglobin Periodontal Bone Loss Saudi Arabia Type 2 Diabetic

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The Impact of Simulation Education on Self-Efficacy in Pre-Registration Nursing Students

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Open Journal of Nursing 2024年第1期14卷 51-76页

作者： ahmed A. Hakami Aisha Hussin Rabie Sultan Ghormallah M. alzahrani Faisal Mohammed Alnakhilan Khalid Awaidhalharbi College of Nursing Umm Al-Qura University Makkah Saudi Arabia Al-Noor Specialist Hospital Makkah Saudi Arabia (MOH) Ministry of Health King Fahad Hospital Al Baha Saudi Arabia (MOH) Ministry of Health Eradah Complex Riyadh Saudi Arabia King Salman Medical City Al Madinah Saudi Arabia

This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .

关键词： Simulation Education Self-Efficacy Pre-Registration Nursing Students Clinical Skills Undergraduate Nursing Education Teaching Techniques Decision-Making

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UNet Based onMulti-Object Segmentation and Convolution Neural Network for Object Recognition

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Computers, Materials & Continua 2024年第7期80卷 1563-1580页

作者： Nouf Abdullah Almujally Bisma Riaz Chughtai Naif Al Mudawi Abdulwahab Alazeb Asaad Algarni Hamdan A.alzahrani Jeongmin Park Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan 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 Information Technology Department College of Computing and InformaticsSaudi Electronic UniversityRiyadh13316Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Republic of Korea

The recent advancements in vision technology have had a significant impact on our ability to identify multiple objects and understand complex *** technologies,such as augmented reality-driven scene integration,robotic navigation,autonomous driving,and guided tour systems,heavily rely on this type of scene *** paper presents a novel segmentation approach based on the UNet network model,aimed at recognizing multiple objects within an *** methodology begins with the acquisition and preprocessing of the image,followed by segmentation using the fine-tuned UNet ***,we use an annotation tool to accurately label the segmented *** labeling,significant features are extracted from these segmented objects,encompassing KAZE(Accelerated Segmentation and Extraction)features,energy-based edge detection,frequency-based,and blob *** the classification stage,a convolution neural network(CNN)is *** comprehensive methodology demonstrates a robust framework for achieving accurate and efficient recognition of multiple objects in *** experimental results,which include complex object datasets like MSRC-v2 and PASCAL-VOC12,have been *** analyzing the experimental results,it was found that the PASCAL-VOC12 dataset achieved an accuracy rate of 95%,while the MSRC-v2 dataset achieved an accuracy of 89%.The evaluation performed on these diverse datasets highlights a notably impressive level of performance.

关键词： UNet segmentation blob fourier transform convolution neural network

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