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Anomaly-Based Intrusion DetectionModel Using Deep Learning for IoT Networks

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Computer Modeling in Engineering & Sciences 2024年第10期141卷 823-845页

作者： Muaadh A.alsoufi Maheyzah Md Siraj Fuad A.Ghaleb Muna al-Razgan Mahfoudh Saeed al-Asaly Taha alfakih Faisal Saeed Faculty of Computing Universiti Teknologi Malaysia(UTM)Johor Bahru81310Malaysia DAAI Research Group College of Computing and Digital TechnologyBirmingham City UniversityBirminghamB47XGUK Department of Software Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11345Saudi Arabia

The rapid growth of Internet of Things(IoT)devices has brought numerous benefits to the interconnected ***,the ubiquitous nature of IoT networks exposes them to various security threats,including anomaly intrusion *** addition,IoT devices generate a high volume of unstructured *** intrusion detection systems often struggle to cope with the unique characteristics of IoT networks,such as resource constraints and heterogeneous data *** the unpredictable nature of network technologies and diverse intrusion methods,conventional machine-learning approaches seem to lack *** numerous research domains,deep learning techniques have demonstrated their capability to precisely detect *** study designs and enhances a novel anomaly-based intrusion detection system(AIDS)for IoT ***,a Sparse Autoencoder(SAE)is applied to reduce the high dimension and get a significant data representation by calculating the reconstructed ***,the Convolutional Neural Network(CNN)technique is employed to create a binary classification *** proposed SAE-CNN approach is validated using the Bot-IoT *** proposed models exceed the performance of the existing deep learning approach in the literature with an accuracy of 99.9%,precision of 99.9%,recall of 100%,F1 of 99.9%,False Positive Rate(FPR)of 0.0003,and True Positive Rate(TPR)of *** addition,alternative metrics,such as training and testing durations,indicated that SAE-CNN performs better.

关键词： IoT anomaly intrusion detection deep learning sparse autoencoder convolutional neural network

Distributed field mapping for mobile sensor teams using a derivative‐free optimisation algorithm

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IET Cyber-Systems and Robotics 2024年第2期6卷 20-34页

作者： Tony X.Lin Jia Guo Said al-Abri Fumin Zhang Fumin Zhang31School of Electrical&Computer Engineering Georgia Institute of TechnologyAtlantaGeorgiaUSA College of Engineering Sultan Qaboos UniversityMuscatOman Department of Electronic&Computer Engineering Hong Kong University of Science and TechnologyHong KongChina

The authors propose a distributed field mapping algorithm that drives a team of robots to explore and learn an unknown scalar field using a Gaussian Process(GP).The authors’strategy arises by balancing exploration objectives between areas of high error and high *** computing high error regions is impossible since the scalar field is unknown,a bio-inspired approach known as Speeding-Up and Slowing-Down is leveraged to track the gradient of the GP *** approach achieves global field-learning convergence and is shown to be resistant to poor hyperparameter tuning of the *** approach is validated in simulations and experiments using 2D wheeled robots and 2D flying mini-ature autonomous blimps.

关键词： environment sensing multi-robot systems

Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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Computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah Abdullah al-Johany Sanaa Abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

Synthetic polymers:A review of applications in drilling fluids

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Petroleum Science 2024年第1期21卷 475-518页

作者： Shadfar Davoodi Mohammed al-Shargabi David A.Wood Valeriy S.Rukavishnikov Konstantin M.Minaev School of Earth Sciences&Engineering Tomsk Polytechnic UniversityLenin AvenueTomskRussia DWA Energy Limited LincolnUnited Kingdom

With the growth of deep drilling and the complexity of the well profile,the requirements for a more complete and efficient exploitation of productive formations increase,which increases the risk of various ***,reagents based on modified natural polymers(which are naturally occurring compounds)and synthetic polymers(SPs)which are polymeric compounds created industrially,are widely used to prevent emerging complications in the drilling ***,compared to modified natural polymers,SPs form a family of high-molecular-weight compounds that are fully synthesized by undergoing chemical polymerization *** provide substantial flexibility in their ***,their size and chemical composition can be adjusted to provide properties for nearly all the functional objectives of drilling *** can be classified based on chemical ingredients,type of reaction,and their responses to ***,some of SPs,due to their structural characteristics,have a high cost,a poor temperature and salt resistance in drilling fluids,and degradation begins when the temperature reaches 130℃.These drawbacks prevent SP use in some medium and deep ***,this review addresses the historical development,the characteristics,manufacturing methods,classification,and the applications of SPs in drilling *** contributions of SPs as additives to drilling fluids to enhance rheology,filtrate generation,carrying of cuttings,fluid lubricity,and clay/shale stability are explained in *** mechanisms,impacts,and advances achieved when SPs are added to drilling fluids are also *** typical challenges encountered by SPs when deployed in drilling fluids and their advantages and drawbacks are also *** issues also impact the applications of SPs in drilling ***,the cost of the most relevant SPs,and the monomers used in their synthesis,are *** impacts of SPs when deployed in drilling fluids,and t

关键词： Synthetic versus natural polymers Nanopolymers Drilling fluid additives Lubricity Clay swelling Hole cleaning

Efficient ECG classification based on Chi-square distance for arrhythmia detection

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Journal of Electronic Science and Technology 2024年第2期22卷 1-15页

作者： Dhiah al-Shammary Mustafa Noaman Kadhim Ahmed M.Mahdi Ayman Ibaida Khandakar Ahmedb College of Computer Science and Information Technology University of Al-QadisiyahAl Diwaniyah58001Iraq Intelligent Technology Innovation Lab Victoria UniversityMelbourne3011Australia

This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia *** proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia *** optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness *** synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia *** results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous *** classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia *** promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.

关键词： Arrhythmia classification Chi-square distance Electrocardiogram(ECG)signal Particle swarm optimization(PSO)

A critical review of microplastics in aquatic ecosystems: Degradation mechanisms and removing strategies

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Environmental Science and Ecotechnology 2024年第5期21卷 62-76页

作者： Sameh S.ali Tamer Elsamahy Rania al-Tohamy Jianzhong Sun Biofuels Institute School of the Environment and Safety EngineeringJiangsu UniversityZhenjiang212013China Botany Department Faculty of ScienceTanta UniversityTanta31527Egypt

Plastic waste discarded into aquatic environments gradually degrades into smaller fragments,known as microplastics(MPs),which range in size from 0.05 to 5 *** ubiquity of MPs poses a significant threat to aquatic ecosystems and,by extension,human health,as these particles are ingested by various marine organisms including zooplankton,crustaceans,and fish,eventually entering the human food *** contamination threatens the entire ecological balance,encompassing food safety and the health of aquatic ***,developing effective MP removal technologies has emerged as a critical area of ***,we summarize the mechanisms and recently reported strategies for removing MPs from aquatic *** combining physical and chemical pretreatments with microbial degradation have shown promise in decomposing *** such as bacteria,fungi,algae,and specific enzymes are being leveraged in MP remediation *** advancements have focused on innovative methods such as membrane bioreactors,synthetic biology,organosilane-based techniques,biofilm-mediated remediation,and nanomaterial-enabled strategies,with nano-enabled technologies demonstrating substantial potential to enhance MP removal *** review aims to stimulate further innovation in effective MP removal methods,promoting environmental and social well-being.

关键词： Persistent organic pollutants Bioremediation Nanomaterial-enabled strategies Aquatic environment Ecotoxicity of microplastics

Tuberculosis-diabetes comorbidities: Mechanistic insights for clinical considerations and treatment challenges

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World Journal of Diabetes 2024年第5期15卷 853-866页

作者： Md Abdul alim al-Bari Nicholas Peake Nabil Eid Department of Pharmacy University of RajshahiRajshahi 6205Bangladesh Biosciences and Chemistry and Biomolecular Research Centre Sheffield Hallam UniversitySheffield S11WBUnited Kingdom Department of Anatomy Division of Human BiologySchool of MedicineInternational Medical UniversityKuala Lumpur 57000Malaysia

Tuberculosis(TB)remains a leading cause of death among infectious diseases,particularly in poor *** infections,multidrug-resistant and ex-tensively drug-resistant TB strains,as well as the coexistence of chronic illnesses such as diabetes mellitus(DM)greatly aggravate TB morbidity and ***[particularly type 2 DM(T2DM)]and TB have converged making their control even more *** contemporary global epidemics,TB-DM behaves like a syndemic,a synergistic confluence of two highly prevalent diseases.T2DM is a risk factor for developing more severe forms of multi-drug resistant-TB and TB recurrence after preventive *** a bidirectional relationship exists between TB and DM,it is necessary to concurrently treat both,and promote recommendations for the joint management of both *** are also some drug-drug interactions resulting in adverse treatment outcomes in TB-DM patients including treatment failure,and *** addition,autophagy may play a role in these ***,the TB-DM comorbidities present several health challenges,requiring a focus on multidisciplinary collaboration and integrated strategies,to effectively deal with this double *** effectively manage the comorbidity,further screening in affected countries,more suitable drugs,and better treatment strategies are required.

关键词： Diabetes mellitus Tuberculosis Coinfections Comorbidity Drug-drug interactions Autophagy Treatment challenges

Coating powder beds with liquids and foams based on viscous formulations using a twin screw mixer:A continuous process study

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Particuology 2024年第10期93卷 364-376页

作者： Mohamed S.Manga Dimitrios Kontziampasis Mustafa al-Maqdad Sean Clifford Serafim Bakalis David W.York School of Chemical and Process Engineering Faculty of Engineering and Physical SciencesUniversity of LeedsLeedsLS29JTUK School of Mechanical Engineering Faculty of Engineering and Physical SciencesUniversity of LeedsLeedsLS29JTUK School of Science and Engineering University of DundeeDD14HNDundeeScotlandUK Dundee International Institute of Central South University Tongzipo RoadCentral South UniversityChangshaHunan410013China Department of Chemical Engineering School of EngineeringUniversity of NewcastleNewcastleNE17RUUK School of Chemical Engineering University of BirminghamBirminghamB152TTUK Department of Chemical Engineering Faculty of EngineeringUniversity of NottinghamNG72RDUK

Coating with viscous formulations has been essential in numerous industries as it can be a means for providing functionalization, additional properties, as well as other benefits. However, there have been scarce studies that have investigated and proposed methodologies in literature. Continuous coating of powders with viscous liquids poses as a promising technology, which has been mentioned in some studies, but has not yet been thoroughly investigated. This paper employs the use of image processing and analysis, in combination with statistical analysis of particles to evaluate the effectiveness of foams and liquids as a means of coating powder beds. Two different sizes of twin screw mixers that are working in continuous operation are employed, and a new continuous foaming device is fabricated and used for the experiments of coating. The effect of materials and process parameters (as for example rotational speed, and flowrate) on the quality of coating are investigated. Image analysis is used to assess the coating quality. The results clearly showcase the potential of using twin screw mixers for coating purposes and not only for mixing. The hypothesis that using large bubble foams to improve the coating of viscous liquids on particles is proven correct, as they provide higher quality coatings compared to their equivalent liquids, when used in the twin screw mixer. Surprisingly, using a larger scale twin screw mixer, does not show a substantial effect on the mixing, regarding quality, however there is still a requirement for mix optimization for achieving scale-up of this process. These results provide a new pathway for coating powders with viscous formulations in industrial applications, requiring less energy and effort in this process, and can pave the way towards introducing more sustainable industrial methodologies for coating.

关键词： Powder coating Continuous processing Viscous liquid Foam Image analysis Positron emission particle traking(PEPT)

Improved Dwarf Mongoose Optimization algorithm for Feature Selection:Application in Software Fault Prediction Datasets

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Journal of Bionic Engineering 2024年第4期21卷 2000-2033页

作者： Abdelaziz I.Hammouri Mohammed A.Awadallah Malik Sh.Braik Mohammed Azmi al-Betar Majdi Beseiso Department of Computer Science Al-Balqa Applied UniversityAl-Salt19117Jordan Department of Scientific Research and Graduate Studies University of Prince Mugrin42241MedinaSaudi Arabia Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Information Technology Al-Huson University CollegeAl-Balqa Applied UniversityAl-HusonIrbid21110Jordan

Feature selection(FS)plays a crucial role in pre-processing machine learning datasets,as it eliminates redundant features to improve classification accuracy and reduce computational *** paper presents an enhanced approach to FS for software fault prediction,specifically by enhancing the binary dwarf mongoose optimization(BDMO)algorithm with a crossover mechanism and a modified positioning updating *** proposed approach,termed iBDMOcr,aims to fortify exploration capability,promote population diversity,and lastly improve the wrapper-based FS process for software fault prediction *** gained superb performance compared to other well-esteemed optimization methods across 17 benchmark *** ranked first in 11 out of 17 datasets in terms of average classification ***,iBDMOcr outperformed other methods in terms of average fitness values and number of selected features across all *** findings demonstrate the effectiveness of iBDMOcr in addressing FS problems in software fault prediction,leading to more accurate and efficient models.

关键词： Dwarf mongoose optimization algorithm Optimization Feature selection Classification