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IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

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Digital Communications and Networks 2024年第1期10卷 190-204页

作者： Farhan ullah Shamsher ullah Gautam Srivastava Jerry Chun-Wei Lin School of Software Northwestern Polytechnical UniversityXian710072ShaanxiChina Knowledge Unit of Systems and Technology University of Management and TechnologySialkot 51040Pakistan Department of Math and Computer Science Brandon UniversityBrandonMB R7A 6A9Canada Department of Computer Science and Math Lebanese American UniversityBeirut1102Lebanon Western Norway University of Applied Sciences BergenNorway Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina

A network intrusion detection system is critical for cyber security against llegitimate *** terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,*** terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal *** is challenging to identify a specific attack due to complex features and data imbalance *** address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced ***,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,***,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic ***,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority ***,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network ***,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep *** experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and *** explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

关键词： Network intrusion detection Transfer learning Features extraction Imbalance data Explainable AI Cybersecurity

Considering solid shear stress in MP-PIC simulation of a CFB riser

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Particuology 2024年第6期89卷 79-87页

作者： Tagir Kadyrov Fei Li Atta ullah Nature-inspired Engineering Center University of TyumenTyumen 625003Russia Laboratory of Theory and Optimization of Chemical and Technological Processes University of TyumenTyumen625003Russia State Key Laboratory of Multi-phase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China Department of Chemical Engineering Pakistan Institute of Engineering&Applied SciencesIslamabad 45650Pakistan

To enable successful multi-phase particle-in-cell(MP-PIC)simulations of circulating fluidized beds(CFBs),both the interphase drag force and interparticle collisions need to be carefully *** collisions are usually represented by the solid stress consisting of the normal and shear components,in which the normal stress was found to have a leading role in the numerical stability of MP-PIC simulations,whereas the impact of the shear stress has seldom been *** this work,the effects of the solid shear stress are investigated by using two-dimensional simulations of the moderately dense laboratory-scale CFB riser with in-house MP-PIC code implemented on MFIX open-source *** including only normal solid stress and those considering both normal and shear solid stresses are *** results of solids flux,axial and radial solids profiles are compared with available experimental *** results show that the solid shear stress plays a minor role on the accuracy of simulation,and the increase of PPP(number particles per parcel)leads to a lower accuracy of simulation.

关键词： Simulation Fluidization Multiphase particle-in-cell(MP-PIC) Solid shear stress

Seasonal abundance and Diversity of Birds of Prey and Owls in al Wathba Wetland Reserve in abu Dhabi, UAE

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Open Journal of Ecology 2024年第3期14卷 228-244页

作者： Shakeel Ahmed Salim Jáved Shahid B. Khan Eissa al hammadi ab.ullah al hammadi Nouf Sameer alqadi Environment Agency-abu Dhabi Abu Dhabi United Arab Emirates

Inland wetlands in abu Dhabi Emirate are wintering and stopover sites for migratory birds of prey. We conducted long-term regular monitoring surveys in al Wathba Wetland Reserve (AWWR) from January 1995 to December 2022. Both diurnal and occasionally nocturnal surveys were undertaken to record the migratory raptors and owls in the Wetland Reserve. During the study, a total of 1282 regular monitoring visits were undertaken and 27 species of diurnal raptors and owls representing five families and three orders were detected. These represent 57% of the total species of birds of prey recorded in the UAE. Overall, 63% of all the species that we observed were Accipitriformes followed by 26% Falconiformes and 11% Strigiformes. We found that changes in mean daily temperature have a positive effect on raptor species diversity and abundance in the Wetland Reserve. The species encounter rate was higher in low temperature as compared to high temperature and overall regression equation was statistically significant F (4, 1126) = 8.49), p = 0.00). However, the numbers of raptors did not vary significantly across the years (p = 0.51). Western Marsh-harrier (Circus aeruginosus) and Greater Spotted Eagle (Clanga clanga) were recorded to be the most abundant species in the wetland reserve followed by Common Kestrel (Falco tinnunculus). However, the encounter rate of globally threatened Greater Spotted Eagle was detected to have significantly decreased since 2016. Moreover, 63% of the species detected were uncommon and rarely recorded such as 1) Saker Falcon 2) Lanner Falcon 3) Long-eared Owl & Merlin, which were the rare records from the wetland reserve. Furthermore, 27 years of regular monitoring in the wetland have yielded diverse diurnal raptors and owl fauna (H) = 0.83, (E) = 1.43 (Shannon Diversity Index). The results demonstrate that long-term monitoring surveys in arid environments are essential to determine the trends in the raptor populations and to document rare and globally

关键词： Wetland Reserve Raptors abundance Diversity abu Dhabi Inland Wetland AWWR Greater Spotted Eagle

CD9 role in proliferation, rejuvenation, and therapeutic applications

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Genes & Diseases 2024年第3期11卷 95-97页

作者： Sai Priyanka Kodam Neda Baghban Mujib ullah Institutefor Immunityand Transplantation Stem Cell Biology and Regenerative MedicineSchool of MedicineMolecular Medicine Department of MedicineStanford UniversityPaloAltoCA94304USA

The CD9 gene,also known as the Tspan29 gene,codes for a protein called CD9,which is a member of the tetraspanin family of transmembrane proteins.^(1) The CD9 protein is involved in various cellular processes,including cell proliferation,differentiation,adhesion,and migration.^(1,2) CD9 has also been found to play a role in the regulation of stem cell proliferation and differentiation.

关键词： migration. therapeutic CD9

Mechanical and magneto-electronic properties of europium lanthanide-based cubic perovskites EuYO_(3)(Y=Cr, Mn, Fe): An ab initio study

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Journal of Rare Earths 2024年第3期42卷 562-569,I0005页

作者： Hayat ullah Azra Sarwar Sajad ali Rabah Khenata abdelmadjid Bouhemadou Saad Bin-Omran Department of Physics Women University of Azad Jammu&Kashmir Bagh 10250Pakistan Department of Physics Abdul Wali Khan UniversityMardan23200KPPakistan LPQ3M Laboratory Institute of Science and TechnologyUniversity of Mascara29000MascaraAlgeria Laboratory for Developing New Materials and Their Characterization Farhat Abbas University Setif l19000SetifAlgeria Department of Physics and Astronomy College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

Computational calculations using density functional theory(DFT) were performed for the first time using the full potential linearized augmented plane wave plus local orbital method(FP-LAPW + LO) to determine the structural, elastic, electronic and magnetic properties of europium-based cubic perovskites EuYO_(3)(Y=Cr, Mn, Fe). The exchange correlation potentials of GGA along with some analytical methods were adopted for the computation of structural and elastic properties. Moreover, the GGA + U formalism was also added for obtaining more precise electronic and magnetic properties, particularly to address the Eu-4f and Y-3d orientations in the spin-polarized double cell symmetry. The observed lattice parameters of these compounds are consistent with experiment. The observed bulk moduli predict that EuCrO_(3) is harder and less compressible than EuMnO_(3) and EuFeO_(3). The calculated tolerance factors of these compounds are within the cubic symmetry range. Our computed critical radius of EuCrO_(3) shows that EuCrO_(3) has a larger migration energy. Based on their elastic properties, these compounds are ductile in nature. We also computed the thermal properties of these compounds. The band structures and density of states show that these compounds are metallic in character. The lowest ground state energy and magnetic moments of these compounds expose their ferromagnetic nature. The metallic nature and strong ferromagnetism of these compounds make them promising applicants for application in spintronic.

关键词： Perovskites GGA+U Elastic constants Band structure Magnetic moments Rare earths

DeBERTa-GRU: Sentiment Analysis for Large Language Model

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Computers, Materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri abdu Gumaei Faisal Mehmood Touqeer abbas Sami ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

Modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves F1-scores of 97%on the Twitter Large Language Model(LLM)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTM sentiment analysis large language model

Insight into the dynamics of non-Newtonian Carreau fluid when viscous dissipation,entropy generation,convective heating and diffusion are significant

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Applied Mathematics(A Journal of Chinese Universities) 2024年第1期39卷 34-46页

作者： ZHOU Shuang-shuang Muhammad Ijaz Khan Sami ullah Khan Sumaira Qayyum School of Science Hunan City UniversityYiyang 413000China Department of Mechanical Engineering Prince Mohammad Bin Fahd UniversityP.O.Box1664Al-Khobar 31952Kingdom of Saudi Arabia Department of Mathematics Namal UniversityMianwali 42250Pakistan Department of Mathematics Quaid-I-Azam University 45320Islamabad 44000Pakistan

The investigation endorsed the convective flow of Carreau nanofluid over a stretched surface in presence of entropy generation *** novel dynamic of viscous dissipation is utilized to analyze the thermal mechanism of magnetized *** convective boundary assumptions are directed in order to examine the heat and mass transportation of *** thermal concept of thermophoresis and Brownian movements has been re-called with the help of Buongiorno *** problem formulated in dimensionless form is solved by NDSolve *** graphical analysis for parameters governed by the problem is performed with physical *** affiliation of entropy generation and Bejan number for different parameters is inspected in *** numerical data for illustrating skin friction,heat and mass transfer rate is also *** motion of the fluid is highest for the viscosity ratio *** temperature of the fluid rises via thermal Biot *** generation rises for greater Brinkman number and diffusion parameter.

关键词： heat generation surface reaction CNTs based nano uid stretching/shrinking sheet thermal radiation

Detection of onset of agglomeration in a bubbling fluidized bed biomass combustor using reactive Eulerian computational fluid dynamics

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Particuology 2024年第7期90卷 504-515页

作者： ab.ullah Tasleem Atta ullah Fei Li Qun Yi William Nimmo Syed Sheraz Daood Department of Chemical Engineering Pakistan Institute of Engineering and Applied Sciences(PIEAS)Lehtrar RoadP.O.Nilore45650IslamabadPakistan Institute of Process Engineering Chinese Academy of SciencesBeijing100190China School of Chemical Engineering and Pharmacy Wuhan Institute of TechnologyWuhan430205China Energy Engineering Group Energy 2050Department of Mechanical EngineeringUniversity of SheffieldSheffieldS37RDUnited Kingdom Institute of Energy and Environmental Engineering Faculty of ElectricalEnergy&Environmental EngineeringUniversity of the PunjabQuaid-e-Azam CampusLahorePakistan Energy Engineering Research and Development Centre Faculty of ElectricalEnergy&Environmental EngineeringUniversity of the PunjabQuaid-e-Azam CampusLahorePakistan

The choice of a type of combustion technology to be used for heat or power generation depends on economic,technical,operational and fuel availability *** benefits associated with the evolving market driven by the fluidised bed combustion(FBC)technology cannot be overlooked especially when gauged at 65 GWth of worldwide installed capacity alongside added benefits of handling fuel variation,low pollutant emissions and high combustion *** or biomass waste will continue to have a vital role to play in the future FBC technology-based power *** often contains high levels of inorganic species that can form sticky agglomerates posing a significant risk to boiler operation resulting in unscheduled *** added complexity of the behaviour of the fuel and bed material mix highlights the requirement for simulation models to identify agglomeration to help improve the overall performance and reliability of FBC *** resolve this problem,this research devised a simulation strategy for the detection of agglomeration using the Eulerian–Eulerian *** developed modelling strategy is validated with the experimental data available in literature for two-dimensional simplified geometry of a pilot-scale fluidised bed *** model results were found promising and robust to predict bed defluidisation times and other parameters consistent with the experimental data.

关键词： Fluidized bed combustion Eulerian Models Biomass Agglomeration Defluidisation

A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： Farhan ullah Xuexia Zhang Mansoor Khan Muhammad abid ab.ullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting