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Internet of Things Enabled DDoS Attack Detection Using Pigeon Inspired Optimization algorithm with Deep Learning Approach

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CMC-COMPUTERS MATERIalS & CONTINUA 2024年第3期80卷 4047-4064页

作者： alghamdi, Turki ali alotaibi, Saud S. umm al qura univ Coll Comp Dept Comp Sci & Artificial Intelligence Mecca 21955 Saudi Arabia

Internet of Things (IoTs) provides better solutions in various fields, namely healthcare, smart transportation, home, etc. Recognizing Denial of Service (DoS) outbreaks in IoT platforms is significant in certifying the accessibility and integrity of IoT systems. Deep learning (DL) models outperform in detecting complex, non-linear relationships, allowing them to effectually severe slight deviations from normal IoT activities that may designate a DoS outbreak. The uninterrupted observation and real-time detection actions of DL participate in accurate and rapid detection, permitting proactive reduction events to be executed, hence securing the IoT network's safety and functionality. Subsequently, this study presents pigeon-inspired optimization with a DL-based attack detection and classification (PIODL-ADC) approach in an IoT environment. The PIODL-ADC approach implements a hyperparameter-tuned DL method for Distributed Denial-of-Service (DDoS) attack detection in an IoT platform. Initially, the PIODLADC model utilizes Z-score normalization to scale input data into a uniform format. For handling the convolutional and adaptive behaviors of IoT, the PIODL-ADC model employs the pigeon-inspired optimization (PIO) method for feature selection to detect the related features, considerably enhancing the recognition's accuracy. also, the Elman Recurrent Neural Network (ERNN) model is utilized to recognize and classify DDoS attacks. Moreover, reptile search algorithm (RSA) based hyperparameter tuning is employed to improve the precision and robustness of the ERNN method. A series of investigational validations is made to ensure the accomplishment of the PIODL-ADC method. The experimental outcome exhibited that the PIODL-ADC method shows greater accomplishment when related to existing models, with a maximum accuracy of 99.81%.

关键词： Internet of things denial of service deep learning reptile search algorithm feature selection

Magnetic,dielectric and electrical modulus of Ce^(3+) doped cobalt-magnesium ferrite nanoparticles

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Journal of Rare Earths 2024年第2期42卷 373-382,I0005页

作者： N.M.Basfer Hanaa almaghamsi Department of Physics Umm AL-Qura UniversityMakkahSaudi Arabia Physics Department College of Science and ArtKing Abdulaziz UniversityPOB344Rabigh291Saudi Arabi

In this work,the magnetic,dielectric properties and electric modulus of Ce^(3+) substituted cobaltmagnesium(Co_(0.7)Mg_(0.3)Ce_(x)Fe_(2-x)O_4)(labeled as CMCF) ferrite nanoparticles were investigated in *** magnetization decreases from 50.05 to 34.87 emu/g for further substituting Ce^(3+) ***,coercivity increases from 738.22 Gs for the CMCFO sample to 912.10 Gs for the CMCF2 sample,then decreases monotonically to 762.1 Gs for the CMCF5 *** cerium content and particle size play important roles in controlling the magnetization and coercivity of the CMCF *** CMCF nanoferrites are suitable for microwave applications since their high-frequency response ranges from 7.72 to 11.07 *** CMCF nanoferrites' dielectric parameter dispersion exhibits normal *** pristine Co-Mg nanoferrite only has ε' value of 28.25,but the nanoferrite MCMF2 has ε' value of365.03,with an enhancing ratio of 1192%.The conduction mechanism of the MCMF nanoferrites was determined by fitting the σ_(ac) results via the Jonscher power *** 653 K,large polaron tunnelling is thought to be responsible for this conduction process,which is followed by electron barrier hopping at higher ***-Cole diagrams at different temperatures,assuring the contributions of the grains and their boundaries at lower temperatures(653 K) and only the grains at higher *** on our results,the CMCF nanoferrites hold magnetic and semiconducting nature,which can be used in magnetic devices and dielectrics in lower-frequencies or conductors in higher-frequencies.

关键词： Nanoferrites Rare earth ions Magnetic properties Dielectric parameters Impedance spectroscopy

Eco-toxicity and health risk assessment of polycyclic aromatic hydrocarbons in surface sediments of Burullus Lake in Egypt

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China Geology 2024年第3期7卷 460-468页

作者： Hanan E Osman Mohamed H E El-Morsy Hazem T Abd El-Hamid Department of Biology Faculty of Applied ScienceUmm Al-Qura UniversityMecca 24382Saudi Arabia Deanship of Scientific Research Umm Al-Qura UniversityMakkah 24372Saudi Arabia National Institute of Oceanography and Fisheries(NIOF) Cairo 11865Egypt Botany and Microbiology Department Faculty of ScienceAl-Azhar UniversityCairo 11651Egypt

Polycyclic aromatic hydrocarbons(PAHs)are ubiquitous environmental contaminants of growing concern due to their potential ecological and human health *** study presents a comprehensive assessment of PAHs contamination in the surface sediments of Burullus Lake,a vital and second largest delta lake in *** aim was to evaluate the eco-toxicity and potential health risks associated with the presence of these *** seven sediment samples were collected from various drains in the southern part of Burullus *** extraction method was employed to extract PAHs(16PAHs)from the sediment ***,target compounds were located using *** results showed that samples contained PAHs levels ranging from 0.038×10^(-6)to 0.459×10^(-6),which is considered heavily polluted by the European standard for PAHs ***,there was no apparent source of PAHs in the ElKhashah drain or the Brinbal Canal,as HPLC found none of the *** most prevalent compound in sediment samples along the study area was *** diagnostic indices in the present study indicated that the hydrocarbons in the region originated from pyrolytic and man-made sources along the drains of Burullus *** principal component analysis(PCA)and diagnostic ratios revealed that coal combustion and pyrolytic sources were responsible for the PAHs contamination in the surface *** non-carcinogenic risk(HI),which is the product of the HQs for the adult and child populations,respectively,was *** values under 1,therefore,demonstrated that they had no carcinogenic effects on human *** and MEQs in the sediments of Burullus Lake do not have a cancer-causing impact on *** the safety of nearby wildlife,aquatic life,and people,all activities that raise petroleum hydrocarbon levels in Burullus Lake must be adequately regulated and *** to the ecological risk assessment,there is little chance that PAHs will be found

关键词： Polycyclic aromatic hydrocarbons Diagnostic indices Toxicity Delta lake sediment Burullus Lake Human health risk Aquatic ecosystem HPLC Coal combustion

Early Detection of Colletotrichum Kahawae Disease in Coffee Cherry Based on Computer Vision Techniques

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 759-782页

作者： Raveena Selvanarayanan Surendran Rajendran Youseef alotaibi Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical ScienceChennai602105India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia

Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is hard to control because wind,rain,and insects carry *** researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93%accuracy using a random forest *** the dataset is too small and noisy,the algorithm may not learn data patterns and generate accurate *** overcome the existing challenge,early detection of Colletotrichum Kahawae disease in coffee cherries requires automated processes,prompt recognition,and accurate *** proposed methodology selects CBD image datasets through four different stages for training and *** to train a model on datasets of coffee berries,with each image labeled as healthy or *** themodel is trained,SHAP algorithmto figure out which features were essential formaking predictions with the proposed *** of these characteristics were the cherry’s colour,whether it had spots or other damage,and how big the Lesions *** inception is important for classification to virtualize the relationship between the colour of the berry is correlated with the presence of *** evaluate themodel’s performance andmitigate excess fitting,a 10-fold cross-validation approach is *** involves partitioning the dataset into ten subsets,training the model on each subset,and evaluating its *** comparison to other contemporary methodologies,the model put forth achieved an accuracy of 98.56%.

关键词： Computer vision coffee berry disease colletotrichum kahawae XG boost shapley additive explanations

HB-Continuous Mappings in L-Topological Space

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Advances in Pure Mathematics 2024年第5期14卷 333-353页

作者： Najah A. alSaedi Department of Mathematics Faculty of Applied Science Umm Al-Qura University Makkah Saudi Arabia

In this paper, we introduce and study the notion of HB-closed sets in L-topological space. Then, HB-convergence theory for L-molecular nets and L-ideals is established in terms of HB-closedness. Finally, we give a new definition of fuzzy H-continuous [1] which is called HB-continuity on the basis of the notion of H-bounded L-subsets in L-topological space. Then we give characterizations and properties by making use of HB-converges theory of L-molecular nets and L-ideals.

关键词： L-Topological Space HB-Closed Set H-Bounded Set HB-Continuous Mappings HB-Convergence L-Molecular Nets L-Ideals

Improving Channel Estimation in a NOMA Modulation Environment Based on Ensemble Learning

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Computer Modeling in Engineering & Sciences 2024年第8期140卷 1315-1337页

作者： Lassaad K.Smirani Leila Jamel Latifah almuqren Elearning Deanship and Distance Education Umm Al-Qura UniversityP.O.Box 715MekkahSaudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

This study presents a layered generalization ensemble model for next generation radio mobiles,focusing on supervised channel estimation *** estimation typically involves the insertion of pilot symbols with a well-balanced rhythm and suitable *** model,called Stacked Generalization for Channel Estimation(SGCE),aims to enhance channel estimation performance by eliminating pilot insertion and improving *** SGCE model incorporates six machine learning methods:random forest(RF),gradient boosting machine(GB),light gradient boosting machine(LGBM),support vector regression(SVR),extremely randomized tree(ERT),and extreme gradient boosting(XGB).By generating meta-data from five models(RF,GB,LGBM,SVR,and ERT),we ensure accurate channel coefficient predictions using the XGB *** validate themodeling performance,we employ the leave-one-out cross-validation(LOOCV)approach,where each observation serves as the validation set while the remaining observations act as the training *** performances’results demonstrate higher mean andmedian accuracy compared to the *** achieves an average accuracy of 98.4%,precision of 98.1%,and the highest F1-score of 98.5%,accurately predicting channel ***,our proposedmethod outperforms prior traditional and intelligent techniques in terms of throughput and bit error ***’s superior performance highlights its efficacy in optimizing channel *** can effectively predict channel coefficients and contribute to enhancing the overall efficiency of radio mobile *** extensive experimentation and evaluation,we demonstrate that SGCE improved performance in channel estimation,surpassing previous ***,SGCE’s capabilities have significant implications for optimizing channel estimation in modern communication systems.

关键词： Stacked generalization ensemble learning Non-Orthogonal Multiple Access(NOMA) channel estimation 5G

Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1635-1654页

作者： Shahad alzahrani Hatim alsuwat Emad alsuwat Independent Researcher Specializing in Data Security and Privacy Taif26571Saudi Arabia Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah24382Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif26571Saudi Arabia

Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among ***,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data *** of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their *** this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning *** framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over *** use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian *** regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC *** doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky ***,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost *** results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning ***,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.

关键词： Bayesian networks data poisoning attacks latent variables structure learning algorithms adversarial attacks

Trends in upper gastrointestinal bleeding management

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World Journal of Clinical Cases 2024年第27期12卷 6007-6010页

作者： Yasir M Khayyat Department of Medicine Faculty of MedicineUmm AL-Qura UniversityMakkah 8156-24381Saudi Arabia

Upper gastrointestinal bleeding(UGIB)can be attributed to either non-variceal or variceal *** latter is more aggressive with hemodynamic instability secondary to decompensated cirrhosis and portal ***-variceal UGIB(NVUGIB)occurs due to impaired gastroprotective mechanisms attributed to several drugs such as anticoagulants and nonsteroidal anti-inflammatory *** pylori infection contributes to the development of peptic ulcer bleeding as *** presentation can be either hemodynamically stable or *** the initial assessment a scoring system including patient-related factors(current cardiac,renal,and liver diseases and hemodynamic and labo-ratory parameters)is used to determine the patient’s *** Glasgow Blatchford score has been shown to be the most useful and *** with high-risk NVUGIB require urgent assessment and upper endoscopy to achieve better short-term and long-term outcomes such as less hospitalization,blood transfusion,and surgery.

关键词： Gastric Peptic Non-steroidal anti-inflammatory drugs Anticoagulants Melena

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1925-1950页

作者： Huzaira Razzaque Shahzaib Ashraf Muhammad Naeem Yu-Ming Chu Institute of Mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Department of Mathematics Deanship of Applied SciencesUmm Al-Qura UniversityMeccaSaudi Arabia Department of Mathematics Huzhou UniversityHuzhou313000China

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric *** Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is *** measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive *** instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different *** the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria *** to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both *** to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one *** suggested DFM’s fundamental characteristics are *** on the newly developed DFM,a unique approach tomultiple criterion group decision-making is *** suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in *** proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter *** method’s applicability and validity shown by the findings are contrasted with those obtained using various

关键词： Multi-criteria group decision-making spherical q-linear Diophantine fuzzy sets differencemeasures photovoltaic cells medical diagnosis