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Sepsis Prediction Using CNNBDLSTM and Temporal Derivatives Feature Extraction in the IoT Medical Environment

Computers, Materials & Continua 2024年第4期79卷 1157-1185页

作者： Sapiah Sakri Shakila Basheer Zuhaira Muhammad Zain Nurul Halimatul Asmak Ismail Dua’Abdellatef Nassar Manal Abdullah Alohali Mais Ayman Alharaki department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia department of Computer science and Information Technology Applied CollegePrincess Nourah Bint Abdulrahman UniversityRiyadh11671Kingdom of Saudi Arabia

Background:Sepsis,a potentially fatal inflammatory disease triggered by infection,carries significant healthimplications *** detection is crucial as sepsis can rapidly escalate if left *** in deep learning(DL)offer powerful tools to address this ***:Thus,this study proposeda hybrid CNNBDLSTM,a combination of a convolutional neural network(CNN)with a bi-directional long shorttermmemory(BDLSTM)model to predict sepsis *** the proposed model provides a robustframework that capitalizes on the complementary strengths of both architectures,resulting in more accurate andtimelier ***:The sepsis prediction method proposed here utilizes temporal feature extraction todelineate six distinct time frames before the onset of *** time frames adhere to the sepsis-3 standardrequirement,which incorporates 12-h observation windows preceding sepsis *** models were trained usingthe Medical Information Mart for Intensive Care III(MIMIC-III)dataset,which sourced 61,522 patients with 40clinical variables obtained from the IoT medical *** confusion matrix,the area under the receiveroperating characteristic curve(AUCROC)curve,the accuracy,the precision,the F1-score,and the recall weredeployed to evaluate ***:The CNNBDLSTMmodel demonstrated superior performance comparedto the benchmark and other models,achieving an AUCROC of 99.74%and an accuracy of 99.15%one hour beforesepsis *** results indicate that the CNNBDLSTM model is highly effective in predicting sepsis onset,particularly within a close proximity of one ***:The results could assist practitioners in increasingthe potential survival of the patient one hour before sepsis onset.

关键词： Temporal derivatives hybrid deep learning predicting sepsis onset MIMIC III machine learning(ML) deep learning

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Evaluations of Chris-Jerry Data Using Generalized Progressive Hybrid Strategy and Its Engineering Applications

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Computer Modeling in Engineering & sciences 2024年第9期140卷 3073-3103页

作者： Refah Alotaibi Hoda Rezk Ahmed Elshahhat department of mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Statistics Al-Azhar UniversityCairo11884Egypt faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A new one-parameter Chris-Jerry distribution,created by mixing exponential and gamma distributions,is discussed in this article in the presence of incomplete lifetime *** examine a novel generalized progressively hybrid censoring technique that ensures the experiment ends at a predefined period when the model of the test participants has a Chris-Jerry(CJ)*** the indicated censored data is present,Bayes and likelihood estimations are used to explore the CJ parameter and reliability indices,including the hazard rate and reliability *** acquire the estimated asymptotic and credible confidence intervals of each unknown ***,via the squared-error loss,the Bayes’estimators are obtained using gamma *** Bayes estimators cannot be expressed theoretically since the likelihood density is created in a complex manner;nonetheless,Markov-chain Monte Carlo techniques can be used to evaluate *** effectiveness of the investigated estimations is assessed,and some recommendations are given using Monte Carlo ***,an analysis of two engineering applications,such as mechanical equipment and ball bearing data sets,shows the applicability of the proposed approaches that may be used in real-world settings.

关键词： Chris-Jerry model generalized censoring likelihood and Bayes estimations MCMC algorithms engineering applications

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Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

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Computers, Materials & Continua 2024年第4期79卷 651-673页

作者： Ahsan Wajahat Jingsha He Nafei Zhu Tariq Mahmood Tanzila Saba Amjad Rehman Khan Faten S.A.lamri faculty of Information Technology Beijing University of TechnologyBeijing100124China Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia faculty of Information sciences University of EducationVehari CampusVehari61100Pakistan department of mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy *** escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital *** methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false *** meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in *** proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data *** Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction *** study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert *** proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,*** empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both *** app

关键词： Android malware detection machine learning SVC K-Nearest Neighbors(KNN) RF

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On the analytical soliton approximations to fractional forced Korteweg-de Vries equation arising in fluids and plasmas using two novel techniques

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Communications in Theoretical Physics 2024年第8期76卷 1-10页

作者： Weaam Alhejaili Emad A Az-Zo’bi Rasool Shah S A El-Tantawy department of mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityPO Box 84428Riyadh 11671Saudi Arabia department Mathematics and Statistics Mutah UniversityAl-KarakJordan department of Computer science and Mathematics Lebanese American UniversityBeirutLebanon department of Physics Faculty of SciencePort Said UniversityPort Said 42521Egypt department of Physics Faculty of ScienceAl-Baha UniversityAl-Baha P.O.Box 1988Saudi Arabia

The current investigation examines the fractional forced Korteweg-de Vries(FF-KdV) equation,a critically significant evolution equation in various nonlinear branches of science. The equation in question and other associated equations are widely acknowledged for their broad applicability and potential for simulating a wide range of nonlinear phenomena in fluid physics, plasma physics, and various scientific domains. Consequently, the main goal of this study is to use the Yang homotopy perturbation method and the Yang transform decomposition method, along with the Caputo operator for analyzing the FF-KdV equation. The derived approximations are numerically examined and discussed. Our study will show that the two suggested methods are helpful, easy to use, and essential for looking at different nonlinear models that affect complex processes.

关键词： forced fractional KdV equation Caputo operator Yang homotopy perturbation method Yang transform decomposition method solitons

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Image Fusion Using Wavelet Transformation and XGboost Algorithm

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Computers, Materials & Continua 2024年第4期79卷 801-817页

作者： Shahid Naseem Tariq Mahmood Amjad Rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba department of Information sciences Division of S&TUniversity of EducationLahore54770Pakistan Artificial Intelligence and Data Analytics(AIDA)Lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia faculty of Information sciences University of EducationVehari CampusVehari61100Pakistan department of Computer science University of Engineering and TechnologyTaxila47050Pakistan department of mathematical sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Recently,there have been several uses for digital image *** fusion has become a prominent application in the domain of imaging *** create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same *** fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual *** fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on *** research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet *** fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient *** precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain *** tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is *** use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter *** simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original *** study enhances the performance of the eXtreme Gradient Boosting(XGBoos

关键词： Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain

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Analysis of Progressively Type-Ⅱ Inverted Generalized Gamma Censored Data and Its Engineering Application

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Computer Modeling in Engineering & sciences 2024年第10期141卷 459-489页

作者： Refah Alotaibi Sanku Dey Ahmed Elshahhat department of mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Statistics St.Anthony’s CollegeShillong793001India faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A novel inverted generalized gamma(IGG)distribution,proposed for data modelling with an upside-down bathtub hazard rate,is *** many real-world practical situations,when a researcher wants to conduct a comparative study of the life testing of items based on cost and duration of testing,censoring strategies are frequently *** this point of view,in the presence of censored data compiled from the most well-known progressively Type-Ⅱ censoring technique,this study examines different parameters of the IGG *** a classical point of view,the likelihood and product of spacing estimation methods are *** Fisher information and the deltamethod are used to obtain the approximate confidence intervals for any unknown parametric function of the *** the Bayesian paradigm,the same traditional inferential approaches are used to estimate all unknown ***-Chain with Monte-Carlo steps are considered to approximate all Bayes’*** numerical comparisons are presented to examine the performance of the proposed methodologies using various criteria of ***,using several optimality criteria,the optimumprogressive censoring design is *** highlight how the proposed estimators can be used in practice and to verify the flexibility of the proposed model,we analyze the failure times of twenty mechanical components of a diesel engine.

关键词： Inverted generalized gamma censoring spacing function likelihood Bayesian optimal plan

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Computational Analysis of Novel Extended Lindley Progressively Censored Data

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Computer Modeling in Engineering & sciences 2024年第3期138卷 2571-2596页

作者： Refah Alotaibi Mazen Nassar Ahmed Elshahhat department of mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia department of Statistics Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia department of Statistics Faculty of CommerceZagazig UniversityZagazigEgypt faculty of Technology and Development Zagazig UniversityZagazig44519Egypt

A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing,bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is *** this research, using a progressive Type-II censored, various inferences of the MOL model parameters oflife are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of themodel parameters and various reliability measures are investigated. Against both symmetric and asymmetric lossfunctions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with theassumption of independent gamma priors. From the Fisher information data and the simulatedMarkovian chains,the approximate asymptotic interval and the highest posterior density interval, respectively, of each unknownparameter are calculated. Via an extensive simulated study, the usefulness of the various suggested strategies isassessedwith respect to some evaluationmetrics such as mean squared errors, mean relative absolute biases, averageconfidence lengths, and coverage percentages. Comparing the Bayesian estimations based on the asymmetric lossfunction to the traditional technique or the symmetric loss function-based Bayesian estimations, the analysisdemonstrates that asymmetric loss function-based Bayesian estimations are preferred. Finally, two data sets,representing vinyl chloride and repairable mechanical equipment items, have been investigated to support theapproaches proposed and show the superiority of the proposed model compared to the other fourteen lifetimemodels.

关键词： Marshall-Olkin-Lindleymodel reliability inference Bayesian and classical inference progressive Type-II censoring

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A Comprehensive Survey for Privacy-Preserving Biometrics: Recent Approaches, Challenges, and Future Directions

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Computers, Materials & Continua 2024年第2期78卷 2087-2110页

作者： Shahriar Md Arman Tao Yang Shahadat Shahed Alanoud AlMazroa Afraa Attiah Linda Mohaisen School of Computer science and Technology Zhejiang Gongshang UniversityHangzhou310018China School of Computer science and Technology Hangzhou Dianzi UniversityHangzhou310018China College of Computer and Information sciences Princess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia

The rapid growth of smart technologies and services has intensified the challenges surrounding identity authenti-cation *** credentials are increasingly being used for verification due to their advantages over traditional methods,making it crucial to safeguard the privacy of people’s biometric data in various *** paper offers an in-depth exploration for privacy-preserving techniques and potential threats to biometric *** proposes a noble and thorough taxonomy survey for privacy-preserving techniques,as well as a systematic framework for categorizing the field’s existing *** review the state-of-the-art methods and address their advantages and limitations in the context of various biometric modalities,such as face,fingerprint,and eye *** survey encompasses various categories of privacy-preserving mechanisms and examines the trade-offs between security,privacy,and recognition performance,as well as the issues and future research *** aims to provide researchers,professionals,and decision-makers with a thorough understanding of the existing privacy-preserving solutions in biometric recognition systems and serves as the foundation of the development of more secure and privacy-preserving biometric technologies.

关键词： Biometric modalities biometric recognition biometric security privacy-preserving security threats

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Dependence of thermodynamic quantities at freeze-out on pseudorapidity and collision energy in p-p collisions at LHC energies

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Chinese Physics C 2024年第10期48卷 235-246页

作者： Murad Badshah Yahia A.H.Obaidat Haifa I.Alrebdi M.Waqas Muhammad Ajaz Refka Ghodhbani department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan department of Physics College of ScienceUniversity of BishaBisha 61922Saudi Arabia department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia School of Mathematics Physics and Optoelectronic EngineeringHubei University of Automotive TechnologyShiyan 442002China department of Computer sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafhaSaudi Arabia

The transverse momentum distributions of charged hadrons produced in proton-proton collisions at center-of-mass energies(√s)of 0.9 TeV and 2.36 TeV,as measured by the CMS detector at the Large Hadron Collider(LHC),have been analyzed within various pseudorapidity classes utilizing the thermodynamically consistent Tsallis *** fitting procedure resulted in the key parameters,namely,effective temperature(T),non-extensivity parameter(q),and kinetic freezeout volume(V).Additionally,the mean transverse momentum()and initial temperature(T_(i))of the particle source are determined through the fit function and string percolation method,*** alternative method is employed to calculate the kinetic freezeout temperature(T_(0))and transverse flow velocity(β_(T))from ***,thermodynamic quantities at the freezeout,including energy density(ε),particle density(n),entropy density(s),pressure(P),and squared speed of sound(C_(s)^(2)),are computed using the extracted T and *** is also observed that,with a decrease in pseudorapidity,all thermodynamic quantities except V and q *** trend is attributed to greater energy transfer along the mid pseudorapidity.q increases towards higher values of pseudorapidity,indicating that particles close to the beam axis are far from ***,V remains nearly independent of *** excitation function of these parameters(q)shows a direct(inverse)correlation with collision *** ε,n,s,and P show a strong dependence on collision energies at low *** verification of the thermodynamic inequality ε≥3P suggests the formation of a highly dense droplet-like Quark-Gluon Plasma(QGP).Additionally,the inequality T_(i)>T>T_(0)is explicitly confirmed,aligning with the evolution of the produced fireball.

关键词： charged hadrons tsallis statistics effective temperature non-extensivity parameter pseudorapidity kinetic freeze-out stage multiple freeze-out scenario QGP QCD matter squared speed of sound

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Multiple scales method for analyzing a forced damped rotational pendulum oscillatorwithgallows

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Communications in Theoretical Physics 2024年第5期76卷 58-67页

作者： Haifa A Alyousef Alvaro H Salas B M Alotaibi S A El-Tantawy department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia department of Mathematics and Statistics Universidad Nacional de ColombiaFIZMAKO Research GroupColombia department of Physics Faculty of SciencePort Said UniversityPort Said 42521Egypt Research Center for Physics(RCP) Department of PhysicsFaculty of Science and ArtsAl-MikhwahAl-Baha UniversityAl-Baha 1988Saudi Arabia

This study reports the analytical solution for a generalized rotational pendulum system with gallows and periodic excited *** multiple scales method(MSM)is applied to solve the proposed *** types of rotational pendulum oscillators are studied and talked about in *** include the forced damped rotating pendulum oscillator with gallows,the damped standard simple pendulum oscillator,and the damped rotating pendulum oscillator without *** MSM first-order approximations for all the cases mentioned are derived in *** obtained results are illustrated with concrete numerical *** first-order MSM approximations are compared to the fourth-order Runge-Kutta(RK4)numerical ***,the maximum error is estimated for the first-order approximations obtained through the MSM,compared to the numerical approximations obtained by the RK4 ***,we conducted a comparative analysis of the outcomes obtained by the used method(MSM)and He-MSM to ascertain their respective levels of *** proposed method can be applied to analyze many strong nonlinear oscillatory equations.

关键词： rotational pendulum system multiple scales method approximate solution damped oscillations forced pendulum with gallows he-multiple scales method

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