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Blockchain for secure and decentralized artificial intelligence in cybersecurity: A comprehensive review

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Blockchain(Research and Applications) 2024年第3期5卷 184-208页

作者： ahmed M.Shamsan Saleh Department of Information Technology University of TabukTabuk47512Saudi Arabia

As the use of artificial intelligence (AI) grows within the field of cybersecurity, so does the demand for secure and decentralized AI systems to protect against potential cyber threats. Blockchain technology has emerged as the ideal approach for increasing both the security and privacy of AI systems since it provides decentralized and immutable data storage. This systematic literature review focuses on the integration of blockchain technology with decentralized AI within cybersecurity. It provides a comprehensive taxonomy of blockchain technology and decentralized AI for cybersecurity, serving as the starting point for the study. This paper begins with an overview of blockchain technology and its possible uses in cybersecurity and also analyzes its challenges and opportunities. Decentralized AI is also covered in the study, along with its potential advantages and difficulties in decentralized AI cybersecurity. Building on that foundation, this study provides convincing findings highlighting the beneficial relationships between blockchain technology and decentralized AI for cybersecurity, contributing to a nuanced comprehension of their integration. Moreover, it offers real-world uses of blockchain-enabled, decentralized AI to discuss its usefulness in tackling cybersecurity concerns. Finally, this paper discusses future research directions for blockchain-enabled decentralized AI in cybersecurity, including potential applications and implications of this technology in the field, emphasizing the potential of blockchain-enabled decentralized AI in cybersecurity to enhance security, privacy, and trust in AI systems.

关键词： Blockchain Artificial intelligence Decentralized Cybersecurity

Enhancing Indoor User Localization:An Adaptive Bayesian Approach for Multi-Floor Environments

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Computers, Materials & Continua 2024年第8期80卷 1889-1905页

作者： Abdulraqeb Alhammadi Zaid ahmed Shamsan Arijit De Center for Artificial Intelligence and Robotics(CAIRO) Malaysia-Japan International Institute of TechnologyUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Department of Electrical Engineering College of EngineeringImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Information Engineering Electronics and TelecommunicationsSapienza UniversityRome00185Italy

Indoor localization systems are crucial in addressing the limitations of traditional global positioning system(GPS)in indoor environments due to signal attenuation *** complex indoor spaces become more sophisticated,indoor localization systems become essential for improving user experience,safety,and operational *** localization methods based on Wi-Fi fingerprints require a high-density location fingerprint database,but this can increase the computational burden in the online *** networks,which integrate prior knowledge or domain expertise,are an effective solution for accurately determining indoor user *** networks use probabilistic reasoning to model relationships among various localization parameters for indoor environments that are challenging to *** article proposes an adaptive Bayesian model for multi-floor environments based on fingerprinting techniques to minimize errors in estimating user *** proposed system is an off-the-shelf solution that uses existing Wi-Fi infrastructures to estimate user’s *** operates in both online and offline *** the offline phase,a mobile device with Wi-Fi capability collects radio signals,while in the online phase,generating samples using Gibbs sampling based on the proposed Bayesian model and radio map to predict user’s *** results unequivocally showcase the superior performance of the proposed model when compared to other existing models and *** proposed model achieved an impressive lower average localization error,surpassing the accuracy of competing ***,this noteworthy achievement was attained with minimal reliance on reference points,underscoring the efficiency and efficacy of the proposed model in accurately estimating user locations in indoor environments.

关键词： Localization positioning Bayesian fingerprinting received signal strength(RSS)

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

Higgs inflation model with non-minimal coupling in hybrid Palatini approach

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Chinese Physics C 2024年第4期48卷 193-201页

作者： Brahim Asfour Aatifa Bargach ahmed Errahmani Taoufik Ouali Laboratory of Physics of Matter and Radiation University of Mohammed firstBP 717OujdaMorocco

In this paper,we propose a hybrid metric Palatini approach in which the Palatini scalar curvature is non minimally coupled to the scalar *** derive Einstein’s field equations,i.e.,the equations of motion of the scalar ***,the background and perturbative parameters are obtained by means of Friedmann equations in the slow roll *** analysis of cosmological perturbations allowed us to obtain the main inflationary parameters,e.g.,the scalar spectral index and tensor to scalar ratio *** this perspective,as an application of our analysis,we consider the Higgs field with quartic potential,which plays the inflaton role,and show that predictions of Higgs hybrid inflation are in good agreement with recent observational data[***.641,61(2020)].

关键词： non-minimal coupling hybrid metric Palatini Higgs inflation

A Hybrid Model for Improving Software Cost Estimation in Global Software Development

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Computers, Materials & Continua 2024年第1期78卷 1399-1422页

作者： Mehmood ahmed Noraini B.Ibrahim Wasif Nisar Adeel ahmed Muhammad Junaid Emmanuel Soriano Flores Divya Anand Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit RajaBatu Pahat86400Malaysia Department of Computer Science COMSATS University Wah Cantt CampusIslamabad47010Pakistan Department of Information Technology The University of HaripurKhyber Pakhtunkhwa22620Pakistan Engineering Research Innovation Group Universidad Europea del AtlanticoSantander39011Spain

Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert *** models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate *** addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation ***,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost *** study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these *** proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry *** article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost *** the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing *** findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.

关键词： Artificial neural networks COCOMO II cost drivers global software development linear regression software cost estimation

Flavone improves liver damage in nicotine-exposed rats via the Nrf2/HO-1 pathway

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Asian Pacific Journal of Tropical Biomedicine 2024年第8期14卷 341-349页

作者： Nora A.Elsayed Fatma SM Moawed Esraa SA ahmed ahmed Hammad Omayma AR Abo-Zaid Biochemistry and Molecular Biology Department Faculty of Vet.Med.Benha UniversityBenha cityEgypt Health Radiation Research National Center for Radiation Research and TechnologyEgyptian Atomic Energy AuthorityCairoEgypt Radiation Biology Department National Center for Radiation Research and TechnologyEgyptian Atomic Energy AuthorityCairoEgypt

Objective:To assess the hepatoprotective effects of flavone on nicotine-induced liver ***:Thirty-six rats were allocated into six groups:the control group,the nicotine group,the flavone alone groups(10 and 25 mg/kg/body weight),and the nicotine groups treated with flavone(10 and 25 mg/kg/body weight).Liver function,oxidative stress,Nrf2 pathway(HO-1,Nrf2,and Keap-1),and inflammatory markers(IL-17,TNF-α,and NF-κB)were ***,a histopathological examination of liver tissues was ***:Nicotine increased liver damage,inflammation,and oxidative ***,flavone suppressed nicotine-induced liver enzymes,oxidative stress,and inflammation,as manifested by increased antioxidants and decreased malondialdehyde level,liver enzymatic activities,and inflammatory ***(10 and 25 mg/kg/body weight)also reduced the level of Keap-1 and increased HO-1 and Nrf2 levels in the liver of nicotine-exposed ***:Flavone has hepatoprotective properties and may slow the progression of liver injury by reducing oxidative stress,liver enzymes,and inflammation possibly via the Nrf2 pathway.

关键词： Flavone Nicotine Liver Nrf2 HO-1 NF-κB

Improved Manta Ray Foraging Optimizer-based SVM for Feature Selection Problems:A Medical Case Study

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Journal of Bionic Engineering 2024年第1期21卷 409-425页

作者： Adel Got Djaafar Zouache Abdelouahab Moussaoui Laith Abualigah ahmed Alsayat Faculty of informatics University of Science and Technology Houari BoumedieneAlgiersAlgeria LRIA Laboratory University of Science and Technology Houari BoumedieneAlgiersAlgeria Computer Science Department University of Mohamed El Bachir El IbrahimiBordj Bou ArreridjAlgeria Computer Science Department University of Ferhat AbbasSetifAlgeria Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl al-Bayt UniversityMafraq 25113Jordan Department of Computer Science College of Computer and Information SciencesJouf UniversityJoufSaudi Arabia Department of Electrical and Computer Engineering Lebanese American University13-5053ByblosLebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman 19328Jordan MEU Research Unit Middle East UniversityAmman 11831Jordan Applied science research center Applied science private universityAmman 11931Jordan School of Computer Sciences Universiti Sains Malaysia11800 PenangMalaysia School of Engineering and Technology Sunway University Malaysia27500 Petaling JayaMalaysia

Support Vector Machine(SVM)has become one of the traditional machine learning algorithms the most used in prediction and classification ***,its behavior strongly depends on some parameters,making tuning these parameters a sensitive step to maintain a good *** the other hand,and as any other classifier,the performance of SVM is also affected by the input set of features used to build the learning model,which makes the selection of relevant features an important task not only to preserve a good classification accuracy but also to reduce the dimensionality of *** this paper,the MRFO+SVM algorithm is introduced by investigating the recent manta ray foraging optimizer to fine-tune the SVM parameters and identify the optimal feature subset *** proposed approach is validated and compared with four SVM-based algorithms over eight benchmarking ***,it is applied to a disease Covid-19 *** experimental results show the high ability of the proposed algorithm to find the appropriate SVM’s parameters,and its acceptable performance to deal with feature selection problem.

关键词： Support vector machine Parameters tuning Feature selection Bioinspired algorithms Manta ray foraging optimizer

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

Evaluating mechanism of banana pseudo-stem retting using seawater:A cost-effective surface pre-treatment approach

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Journal of Bioresources and Bioproducts 2024年第3期9卷 322-335页

作者： Prince Hotor ahmed H.Hassanin Osbert Akatwijuka Mohamed A.H.Gepreel Mitsuo Yamamoto Yukie Saito ahmed Abdel-Mawgood Egypt-Japan University of Science and Technology Biotechnology ProgramAlexandria GovernorateNew Borg Al Arab 21934Egypt Alexandria University Department of Textile EngineeringAlexandria GovernorateBab Sharqi 5424041Egypt Egypt-Japan University of Science and Technology Material Science and EngineeringAlexandria GovernorateNew Borg Al Arab 21934Egypt Graduate School of Agricultural and Life Sciences The University of TokyoBunkyo-KuTokyo 113-8657Japan

Retting has been employed to extract natural fibers from agricultural wastes as a biological and cost-effective approach for *** its global abundance,banana pseudo-stem is a promising agro-waste for lignocellulosic fiber *** this study,fibers were extracted from the pseudo-stems after being pre-treated under four conditions using seawater at room temperature for up to 35 d Bacterial isolation from the fresh seawater sample and screening for ligninolytic ability were *** load as well as laccase and manganese peroxidase enzyme activity profile assay during the retting duration were *** transform infrared(FT-IR)and X-day diffraction(XRD)analyses were also examined for both pre-treated and untreated extracted *** results shows that six out of the eight bacterial isolates had the ability to degrade *** treatments(Raw stem+Raw seawater)and(Autoclaved stem+Raw seawater)recorded the highest viable bacterial load of 9.24×102 and 4.46×102 CFU,respectively,on the 14th day of the retting ***,the highest laccase and manganese peroxidase enzymes activity was recorded for(Raw stem+Raw seawater)and(Autoclaved stem+Raw seawater)treatments in the second to the third *** FT-IR spectra of the pre-treated fibers revealed relative reductions in peaks attributed to polysaccharides and other amorphous substances for all retting *** XRD diffractogram revealed that the crystallinity index(CI)of pre-treated fibers increased in all seawater retting treatment ***,the CI for fibers pre-treated under enzymatic conditions were enhanced even after five *** analysis for selected bacterial isolates showed homology to sequences of Bacillus velezensis,Shewanella sp.L8–5,and Citrobacter amalonaticus and Bacillus subtilis j8 *** these findings,it was suggested that physical,biological,and chemical actions were collectively involved in the seawater retting process of banana ps

关键词： Seawater retting Banana pseudo-stem Natural fiber Enzyme activity Colony forming unit