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Novel Framework for an Intrusion Detection System Using Multiple Feature Selection Methods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.E.M.Eljialy mohammed Yousuf Uddin Sultan Ahmad Department of Information Systems College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection systems (IDSs) are deployed to detect anomalies in real time. They classify a network’s incoming traffic as benign or anomalous (attack). An efficient and robust IDS in software-defined networks is an inevitable component of network security. The main challenges of such an IDS are achieving zero or extremely low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with minimal resources. This situation makes deploying traditional IDSs in IoT networks unfeasible. Machine learning (ML) techniques are extensively applied to build robust IDSs. Many researchers have utilized different ML methods and techniques to address the above challenges. The development of an efficient IDS starts with a good feature selection process to avoid overfitting the ML model. This work proposes a multiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed model. This model applies multiple feature selection techniques to select high-scoring features from a set of features. Highly relevant features for anomaly detection are selected on the basis of their scores to generate the candidate dataset. Multiple classification algorithms are applied to the candidate dataset to build models. The proposed model exhibits considerable improvement in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

Complex Decision Modeling Framework with Fairly Operators and Quaternion Numbers under Intuitionistic Fuzzy Rough Context

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1893-1932页

作者： Nadeem Salamat Muhammad Kamran Shahzaib Ashraf Manal Elzain mohammed Abdulla Rashad Ismail mohammed M.Al-Shamiri Institute of Mathematics Khwaja Fareed University of Engineering&Information TechnologyRahim Yar Khan64200Pakistan Department of Mathematics Thal University BhakkarPunjab30000Pakistan Department of Mathematics Faculty of Science and ArtsKing Khalid UniversityMuhayl Assir61913Saudi Arabia

The main goal of informal computing is to overcome the limitations of hypersensitivity to defects and uncertainty while maintaining a balance between high accuracy,accessibility,and *** paper investigates the potential applications of intuitionistic fuzzy sets(IFS)with rough sets in the context of sparse *** it comes to capture uncertain information emanating fromboth upper and lower approximations,these intuitionistic fuzzy rough numbers(IFRNs)are superior to intuitionistic fuzzy sets and pythagorean fuzzy sets,*** use rough sets in conjunction with IFSs to develop several fairly aggregation operators and analyze their underlying *** present numerous impartial laws that incorporate the idea of proportionate dispersion in order to ensure that the membership and non-membership activities of IFRNs are treated equally within these *** operations lead to the development of the intuitionistic fuzzy rough weighted fairly aggregation operator(IFRWFA)and intuitionistic fuzzy rough ordered weighted fairly aggregation operator(IFRFOWA).These operators successfully adjust to membership and non-membership categories with fairness and *** highlight the unique qualities of these suggested aggregation operators and investigate their use in the multiattribute decision-making *** use the intuitionistic fuzzy rough environment’s architecture to create a novel strategy in situation involving several decision-makers and non-weighted ***,we developed a novel technique by combining the IFSs with quaternion *** establish a unique connection between alternatives and qualities by using intuitionistic fuzzy quaternion numbers(IFQNs).With the help of this framework,we can simulate uncertainty in real-world situations and address a number of decision-making *** the examples we have released,we offer a sophisticated and systematically constructed illustrative scenario that is intricately wo

关键词： Intuitionistic fuzzy set quaternion numbers fuzzy logic decision-making rough set

Human dental pulp stem/stromal cells in clinical practice

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World Journal of Stem Cells 2024年第2期16卷 54-57页

作者： mohammed E Grawish Department of Oral Biology Faculty of DentistryMansoura UniversityMansoura 35561Egypt Department of Oral Biology Faculty of Oral and Dental MedicineDelta University for Science and TechnologyMansoura 11152Egypt

Dental pulp stem/stromal cells(DPSCs)are fibroblast-like,neural crest-derived,and multipotent cells that can differentiate into several *** are relatively easy to isolate from healthy and inflamed pulps,with little ethical concerns and can be successfully cryopreserved and *** therapeutic effects of DPSCs derived from animal or human sources have been extensively studied through in-vitro and in-vivo animal experiments and the findings indicated that DPSCs are effective not only for dental diseases but also for systemic *** that translational research is a critical step through which the fundamental scientific discoveries could be translated into applicable diagnostics and therapeutics that directly benefit humans,several clinical studies were carried out to generate evidence for the efficacy and safety of autogenous or allogeneic human DPSCs(hDPSCs)as a treatment modality for use in cell-based therapy,regenerative medicine/dentistry and tissue *** clinical medicine,hDPSCs were effective for treating acute ischemic stroke and human exfoliated deciduous teeth-conditioned medium(SHED-CM)repaired vascular damage of the corpus cavernous,which is the main cause of erectile *** in clinical dentistry,autologous SHED was able to rege-nerate necrotic dental pulp after implantation into injured teeth,and micrografts enriched with autologous hDPSCs and collagen sponge were considered a treatment option for human intrabony *** contrast,hDPSCs did not add a significant regenerative effect when they were used for the treatment of post-extraction ***-scale clinical studies across diverse populations are still lacking to provide robust evidence on the safety and efficacy of hDPSCs as a new treatment option for various human diseases including dental-related problems.

关键词： Dental pulp stem/stromal cells Human clinical studies Regenerative medicine Regenerative dentistry Cell-based therapy

Learning Dual-Layer User Representation for Enhanced Item Recommendation

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Computers, Materials & Continua 2024年第7期80卷 949-971页

作者： Fuxi Zhu Jin Xie mohammed Alshahrani Applied Research Center of Artificial Intelligence Wuhan CollegeWuhan430212China College of Computer Science South-Central MINZU UniversityWuhan430074China Unmanned.Company Riyadh11564Saudi Arabia

User representation learning is crucial for capturing different user preferences,but it is also critical challenging because user intentions are latent and dispersed in complex and different patterns of user-generated data,and thus cannot be measured ***-based data models can learn user representations by mining latent semantics,which is beneficial to enhancing the semantic function of user ***,these technologies only extract common features in historical records and cannot represent changes in user ***,sequential feature can express the user’s interests and intentions that change time by *** the sequential recommendation results based on the user representation of the item lack the interpretability of preference *** address these issues,we propose in this paper a novel model with Dual-Layer User Representation,named DLUR,where the user’s intention is learned based on two different layer ***,the latent semantic layer adds an interactive layer based on Transformer to extract keywords and key sentences in the text and serve as a basis for *** sequence layer uses the Transformer model to encode the user’s preference intention to clarify changes in the user’s ***,this dual-layer user mode is more comprehensive than a single text mode or sequence mode and can effectually improve the performance of *** extensive experiments on five benchmark datasets demonstrate DLUR’s performance over state-of-the-art recommendation *** addition,DLUR’s ability to explain recommendation results is also demonstrated through some specific cases.

关键词： User representation latent semantic sequential feature interpretability

Dynamic thermal performance of multilayer hollow clay walls filled with insulation materials:Toward energy saving in hot climates

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Energy and Built Environment 2024年第1期5卷 70-80页

作者： Yassine Chihab mohammed Garoum Najma Laaroussi mohammed V University in Rabat MaterialsEnergy and Acoustics TEAMRabatMorocco

This study examines the benefits of incorporating passive techniques into multilayer hollow clay brick walls to improve their dynamic thermal *** finite element approach was used to solve the incompressible Navier-Stokes and energy equations to analyze the dynamic thermal response of walls exposed to real thermal excitations of the Marrakesh *** results show that increasing the emissivity from 0.1 to 0.9 significantly increases the total heat load over 24 ***,filling 100% of the cavities with insulation materials delayed the temperature peak by about 2.3 h and lowered the decrement factor by roughly 43%,with a value smaller than *** addition,it is demonstrated that the total thermal load is reduced by approximately 28% for improved wall configurations(100% insulation filling cavities)compared to traditional wall configurations(100% air filling cavities),which aids in improving building energy efficiency.

关键词： Time lag Decrement factor Coupled heat transfer Analytical solution Hollow clay brick Insulation filling cavities Energy savings in building

Fluorophosphates and fluorosulfates cathode materials: Progress towards high energy density sodium-ion battery

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Nano Research 2024年第3期17卷 1427-1440页

作者： mohammed Hadouchi Jingrong Hou Toshinari Koketsu abdelilah Lahmar Jiwei Ma Laboratoire de Chimie Appliquée des Matériaux Centre des Sciences des MatériauxFaculty of ScienceMohammed V University in RabatAvenue Ibn BattoutaBP 1014RabatMorocco Shanghai Key Laboratory for R&D and Application of Metallic Functional Materials Institute of New Energy for VehiclesSchool of Materials Science and EngineeringTongji UniversityShanghai 201804China Battery Materials Development Section Business Creation Sector R&D CenterMitsui Mining&Smelting Co.Ltd.362-0021 SaitamaJapan Laboratoiry of Condensed Matter Physics University of Picardie Jules Verne33 Rue Saint-Leu 80039AmiensFrance

The rapid diffusion of renewable energy boosts the wide deployment of large-scale energy storage *** the low cost and high crustal abundance,sodium-ion battery(SIB)technology is expected to become a dominant technology in that area in the *** the practical application,novel cathode materials are urged to develop that show high energy density without sacrificing their cost and benignity to the *** the years of many studies,this still remains a huge challenge to battery *** this review,we discuss recent breakthroughs in SIB cathode materials with high energy density,namely fluorphosphates and *** design of materials,the crystal structure,the electrochemical performance,and the underlaying intercalation mechanism are systematically *** strategies and research directions are also provided to advance future high-energy,low-cost,and ecofriendly cathode materials for next generation SIB.

关键词： fluorophosphates fluorosulfates crystal structure intercalation mechanism high energy density sodium-ion battery

Effectiveness of external prestressing in enhancing the non-ductile hanger failure mechanism in reinforced concrete inverted T-beams

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1050-1065页

作者： Ahmed M.ATTA Reda N.BEHIRY mohammed I.HARAZ Structural Engineering Department Faculty of EngineeringTanta UniversityTanta 33511Egypt Nile Higher Institute for Engineering and Technology Mansoura 11001Egypt

Recently,inverted T-beams have been used in reinforced concrete(RC)bridges to support transverse precast *** T-beams,contrary to practice with conventional beams,are loaded on the flanges upper *** loading configuration causes hanger failure due to the generation of vertical tensile stresses near the bottom of the *** key purpose of this study is to investigate the efficiency of vertical external prestressing stainless-steel bars in mitigating non-ductile hanger failure in reinforced concrete inverted *** experimental study on six inverted-T beams,including two un-strengthened specimens,was carried *** study showed that the value of the prestressing level had a considerable impact on the performance of hanger mechanism in relation to crack pattern,ultimate loads,cracking behavior,load-deflection,strains,and *** experimental results indicated that the suggested method for strengthening inverted T-beams had efficacy in reducing the seriousness of the non-ductile hanger failure and resulted in a strength increase of up to 53% when compared to that of the un-strengthened ***,two analytical models for estimating the hanger capacity and the average crack width of the strengthened RC inverted T-beams were *** models that were proposed exhibited a high degree of agreement with the experimental results.

关键词： RC bridges inverted T-beams strengthening hanger failure external prestressing

An Effective Hybrid Model of ELM and Enhanced GWO for Estimating Compressive Strength of Metakaolin-Contained Cemented Materials

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1521-1555页

作者： Abidhan Bardhan Raushan Kumar Singh mohammed Alatiyyah Sulaiman Abdullah Alateyah Department of Civil Engineering National Institute of Technology PatnaPatnaIndia Department of Computer Engineering and Applications GLA UniversityMathuraIndia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science College of Science and ArtsQassim UniversityUnaizahSaudi Arabia

This research proposes a highly effective soft computing paradigm for estimating the compressive strength(CS)of metakaolin-contained cemented *** proposed approach is a combination of an enhanced grey wolf optimizer(EGWO)and an extreme learning machine(ELM).EGWO is an augmented form of the classic grey wolf optimizer(GWO).Compared to standard GWO,EGWO has a better hunting mechanism and produces an optimal *** EGWO was used to optimize the ELM structure and a hybrid model,ELM-EGWO,was *** train and validate the proposed ELM-EGWO model,a sum of 361 experimental results featuring five influencing factors was *** on sensitivity analysis,three distinct cases of influencing parameters were considered to investigate the effect of influencing factors on predictive *** consequences show that the constructed ELM-EGWO achieved the most accurate precision in both training(RMSE=0.0959)and testing(RMSE=0.0912)*** outcomes of the ELM-EGWO are significantly superior to those of deep neural networks(DNN),k-nearest neighbors(KNN),long short-term memory(LSTM),and other hybrid ELMs constructed with GWO,particle swarm optimization(PSO),harris hawks optimization(HHO),salp swarm algorithm(SSA),marine predators algorithm(MPA),and colony predation algorithm(CPA).The overall results demonstrate that the newly suggested ELM-EGWO has the potential to estimate the CS of metakaolin-contained cemented materials with a high degree of precision and robustness.

关键词： Metakaolin-contained cemented materials compressive strength extreme learning machine grey wolf optimizer swarm intelligence uncertainty analysis artificial intelligence

Secure android IoT mobile and collaborative machine learning for controlling the management of enterprise

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Journal of Control and Decision 2024年第1期11卷 15-25页

作者： Hamza mohammed Ridha Al-Khafaji Refed Adnan Jaleel Biomedical Engineering Department Al-Mustaqbal University CollegeHillahIraq Information and Communication Engineering Department Al-Nahrain UniversityBaghdadIraq

There is a need for increased security measures because of wide variety of android Internet of Thing(IoT)mobile devices that can communicate with each other via networks for controlling the management of *** Curve Deffie Hellman(ECDH)and Rivest Shamir Adleman(RSA)are used to secure data in android IoT phones in efficient *** mobile can store a lot of data,including sensitive *** data saved on mobile has become a critical *** android IoT,Collaborative Machine Learning describes a method for collaboratively mining data,which makes it easier to manage and lowers cost of *** increase security in IoT phones,suggested system uses ECDH,RSA,and CML algorithms,which have been considered novelty of this *** and ECDH are computed using time of decryption,encryption,and key *** show ECDH beats other alternatives like ***,all users of the network have been tested.

关键词： IoT ECDH RSA CML android encryption decryption