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Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.Alrayes Mohammed Zakariah Syed Umar Amin zafar iqbal Khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

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Enhanced Topic-Aware Summarization Using Statistical Graph Neural Networks

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Computers, Materials & Continua 2024年第8期80卷 3221-3242页

作者： Ayesha Khaliq Salman Afsar Awan Fahad Ahmad Muhammad Azam Zia Muhammad zafar iqbal Department of Computer Science University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan School of Computing Faculty of TechnologyUniversity of PortsmouthSouthseaPortsmouthPO12UPUK Department of Mathematics and Statistics University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan

The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original *** approaches in Extractive Text Summarization(ETS)leverage the modeling of inter-sentence relationships,a task of paramount importance in producing coherent *** study introduces an innovative model that integrates Graph Attention Networks(GATs)with Transformer-based Bidirectional Encoder Representa-tions from Transformers(BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Inverse Document Frequency(TF-IDF)values,to improve sentence selection by capturing comprehensive topical *** approach constructs a graph with nodes representing sentences,words,and topics,thereby elevating the interconnectivity and enabling a more refined understanding of text *** model is stretched to Multi-Document Summarization(MDS)from Single-Document Summarization,offering significant improvements over existing models such as THGS-GMM and Topic-GraphSum,as demonstrated by empirical evaluations on benchmark news datasets like Cable News Network(CNN)/Daily Mail(DM)and *** results consistently demonstrate superior performance,showcasing the model’s robustness in handling complex summarization tasks across single and multi-document *** research not only advances the integration of BERT and LDA within a GATs but also emphasizes our model’s capacity to effectively manage global information and adapt to diverse summarization challenges.

关键词： Summarization graph attention network bidirectional encoder representations from transformers Latent Dirichlet Allocation term frequency-inverse document frequency

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CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online *** goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify *** NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection ***,maintaining operating efficiency while improving detection accuracy is the primary goal of this ***,typical NIDS examines both risky and typical behavior using a variety of *** the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel *** to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection ***,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this *** efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDS) NSL-KDD dataset deep-learning machine-learning CNN channel Attention network security

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The Influence of Depression on Different Age and Gender Groups in Bahawalpur

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Journal of Clinical and Nursing Research 2024年第7期8卷 196-207页

作者： Mehran Khan Muhammad Shahbaz Tooba Waris Shoaib Yaseen Iqra Afzal Emaan Khadim Sawera Usman Muhammad Ismail Shah Sulaiman Aslam zafar iqbal Bahawalpur College of Pharmacy BMDC Complex63100PunjabPakistan

In Bahawalpur,a cross-sectional study assessed depression prevalence across age and gender groups,involving 442 participants from diverse socioeconomic backgrounds and *** the PHQ9 questionnaire,84%were found to meet depression *** findings revealed a higher incidence in females(88%)than males(79%),with the greatest disparity among young adults,particularly young women,due to factors like academic pressure and financial *** children had the lowest depression rates(68%),possibly due to better *** individuals exhibited more severe depression,likely related to aging and domestic *** study’s findings highlight a significant variation in depression severity across different demographic groups,with an overall higher incidence in *** research underscores the necessity for targeted mental health resources and interventions tailored to the specific needs of each demographic *** also points to the importance of addressing academic and socioeconomic stressors to mitigate depression,particularly among young *** the study provides valuable insights,it relies on self-reported data,which may introduce ***,future research should include clinical assessments to validate these findings and ensure a more accurate representation of depression within the community.

关键词： Influence Depression Different age Gender groups Bahawalpur

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Biosorption characteristics of unicellular green alga Chlorella sorokiniana immobilized in loofa sponge for removal of Cr(Ⅲ)

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Journal of Environmental Sciences 2008年第2期20卷 231-239页

作者： AKHTAR Nasreen iqbal Muhammad zafar Saeed iqbal iqbal Javed Department of Biology Government lslamia College for WomenCooper RoadLahore-54550Pakistan. Environment Biotechnology Group Biotechnology and Food Research CentrePCSIR Laboratories ComplexLahore-54600Pakistan. School of Biological Sciences University of PunjabLahore-54570Pakistan.

Loofa sponge （LS） immobilized biomass of Chlorella sorokiniana （LSIBCS）, isolated from industrial wastewater, was investigated as a new biosorbent for the removal of Cr（Ⅲ） from aqueous solution. A comparison of the biosorption of Cr（Ⅲ） by LSIBCS and free biomass of C. sorokiniana （FBCS） from 10-300 mg Cr（Ⅲ）/L aqueous solutions showed an increase in uptake of 17.79% when the microalgal biomass was immobilized onto loofa sponge. Maximum biosorption capacity for LSIBCS and FBCS was found to be 69.26 and 58.80 mg Cr（Ⅲ）/g biosorbent, respectively, whereas the amount of Cr（Ⅲ） ions adsorbed onto naked LS was 4.97 mg/g. The kinetics of Cr（Ⅲ） biosorption was extremely rapid and equilibrium was established in about 15 and 20 min by LSIBCS and FBCS, respectively. The biosorption equilibrium was well defined by Langmuir adsorption isotherm model. The biosorption kinetics followed the pseudo-second order kinetic model. The biosorption was found to be pH dependent and the maximum sorption occurred at the solution pH 4.0. Desorption studies showed that 98% of the adsorbed Cr（Ⅲ） could be desorbed with 0.1 mol/L HNO3, while other desorbing agents were less effective in the order： EDTA 〉 H2SO4 〉 CH3COOH 〉 HCl. The regenerated LSIBCS retained 92.68% of the initial Cr（Ⅲ） binding capacity up to five cycles of reuse in continuous flow-fixed bed columns. The study revealed that LSIBCS could be used as an effective biosorbent for the removal of Cr（Ⅲ） from wastewater.

关键词： biosorption immobilization loofa sponge Chlorella sorokiniana Cr(Ⅲ) desorption fixed bed column reactor

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Metal-free, carbon-based catalysts for oxygen reduction reactions

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Frontiers of Chemical Science and Engineering 2015年第3期9卷 280-294页

作者： Zhiyi Wu zafar iqbal Xianqin Wang Department of Materials Science and Engineering New Jersey Institute of Technology Newark NJ 07102 USA Department of Chemistry and Environmental Science New Jersey Institute of Technology Newark NJ 07102 USA Department of Chemical Biological and Pharmaceutical Engineering New Jersey Institute of Technology Newark NJ 07102 USA

Developing metal-free, carbon-based catalysts to replace platinum-based catalysts for oxygen reduction reactions （ORRs） is an emerging area of research. In recent years, different carbon structures including carbon doped with IIIA-VIIA heteroatoms （C-M site-based, where M represents the doped heteroatom） and polynitrogen （PN） compounds encapsulated in carbon nanotubes （CNTs）（N N site-based） have been synthesized. Compared to metallic catalysts, these materials are highly active, stable, inexpensive, and environmentally friendly. This review discusses the development of these materials, their ORR performances and the mechanisms for how the incorpora- tion of heteroatoms enhances the ORR activity. Strategies for tailoring the structures of the carbon substrates to improve ORR performance are also discussed. Future studies in this area will need to include optimizing synthetic strategies to control the type, amount and distribution of the incorporated heteroatoms, as well as better understanding the ORR mechanisms in these catalysts.

关键词： oxygen reduction reaction electrocatalysis metal-flee carbon-based polynitrogen

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A Structure Preserving Numerical Method for Solution of Stochastic Epidemic Model of Smoking Dynamics

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Computers, Materials & Continua 2020年第10期65卷 263-278页

作者： Ali Raza Muhammad Rafiq Nauman Ahmed Ilyas Khan Kottakkaran Sooppy Nisar zafar iqbal Department of Mathematics National College of Business Administration and EconomicsLahorePakistan Faculty of Engineering University of Central PunjabLahorePakistan Department of Mathematics and Statistics The University of LahoreLahorePakistan Faculty of Mathematics and Statistics Ton Duc Thang UniversityHo Chi Minh CityVietnam Department of Mathematics College of Arts and Science at Wadi AldawaserPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia

In this manuscript,we consider a stochastic smoking epidemic model from behavioural ***,we develop a structure preserving numerical method to describe the dynamics of stochastic smoking epidemic model in a human *** structural properties of a physical system include positivity,boundedness and dynamical *** properties play a vital role in non-linear *** solution for nonlinear stochastic models necessitates the conservation of these ***,the aforementioned properties of the model have not been restored in the existing stochastic ***,it is essential to construct a structure preserving numerical method for a reliable analysis of stochastic smoking *** usual explicit stochastic numerical methods are time-dependent and violate most of the structural *** this work,we have developed the implicitly driven explicit method for the solution of stochastic smoking *** is also proved that the newly developed method sustains all the aforementioned properties of the ***,the convergence analysis of the newly developed method and graphical illustrations are presented.

关键词： Smoking model stochastic numerical techniques convergence

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Hybrid Global Optimization Algorithm for Feature Selection

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Computers, Materials & Continua 2023年第1期74卷 2021-2037页

作者： Ahmad Taher Azar zafar iqbal Khan Syed Umar Amin Khaled M.Fouad Faculty of Computers and Artificial Intelligence Benha UniversityBenha13511Egypt College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information Technology and Computer Science Nile UniversitySheikh ZaidEgypt

This paper proposes Parallelized Linear Time-Variant Acceleration Coefficients and Inertial Weight of Particle Swarm Optimization algorithm(PLTVACIW-PSO).Its designed has introduced the benefits of Parallel computing into the combined power of TVAC(Time-Variant Acceleration Coefficients)and IW(Inertial Weight).Proposed algorithm has been tested against linear,non-linear,traditional,andmultiswarmbased optimization *** experimental study is performed in two stages to assess the proposed *** I uses 12 recognized Standard Benchmarks methods to evaluate the comparative performance of the proposed PLTVACIWPSO *** based Particle Swarm Optimization(PSO)algorithms,TVAC based PSO algorithms,traditional PSO,Genetic algorithms(GA),Differential evolution(DE),and,finally,Flower Pollination(FP)*** phase II,the proposed PLTVACIW-PSO uses the same 12 known Benchmark functions to test its performance against the BAT(BA)and Multi-Swarm BAT *** phase III,the proposed PLTVACIW-PSO is employed to augment the feature selection problem formedical *** experimental study shows that the planned PLTVACIW-PSO outpaces the performances of other comparable *** from the experiments shows that the PLTVACIW-PSO is capable of outlining a feature subset that is capable of enhancing the classification efficiency and gives the minimal subset of the core features.

关键词： Particle swarm optimization(PSO) time-variant acceleration coefficients(TVAC) genetic algorithms differential evolution feature selection medical data

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Vibration characteristics of FGM circular cylindrical shells filled with fluid using wave propagation approach

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Applied Mathematics and Mechanics(English Edition) 2009年第11期30卷 1393-1404页

作者： zafar iqbal Muhammad Nawaz Naeem Nazra Sultana Shahid Hussain Arshad Abdul Ghafar Shah Department of Mathematics University of Sargodha Department of Mathematics G. C. University Faisalabad Department of Mathematics University of Sargodha Department of Mathematics The Islamia University of Bahawalpur

The vibration characteristics of a functionally graded material circular cylindrical shell filled with fluid are examined with a wave propagation approach. The shell is filled with an incompressible non-viscous fluid. Axial modal dependence is approximated by exponential functions. A theoretical study of shell vibration frequencies is analyzed for simply supported-simply supported, clamped-simply supported, and clamped-clamped boundary conditions with the fluid effect. The validity and the accuracy of the present method are confirmed by comparing the present results with those available in the literature. Good agreement is observed between the two sets of results.

关键词： functionally graded material Love's shell theory cylindrical shell volumefraction law natural frequency wave propagation

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ChainApparel: A Trustworthy Blockchain and IoT-Based Traceability Framework for Apparel Industry 4.0

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Computers, Materials & Continua 2023年第11期77卷 1837-1854页

作者： Muhammad Shakeel Faridi Saqib Ali Guojun Wang Salman Afsar Awan Muhammad zafar iqbal Department of Computer Science University of AgricultureFaisalabad38000Pakistan School of Computer Science Guangzhou UniversityGuangzhou510006China Department of Mathematics and Statistics University of AgricultureFaisalabad38000Pakistan

Trustworthiness and product traceability are essential factors in the apparel industry 4.0 for establishing successful business relationships among stakeholders such as customers,manufacturers,suppliers,and *** stakeholder has implemented different technology-based systems to record and track product ***,these systems work in silos,and there is no intra-system communication,leading to a lack of complete supply chain traceability for all apparel ***,apparel stakeholders are reluctant to share their business information with business competitors;thus,they involve third-party auditors to ensure the quality of the final ***,the apparel manufacturing industry faces challenges with counterfeit products,making it difficult for consumers to determine the authenticity of the ***,in this paper,a trustworthy apparel product traceability framework called ChainApparel is developed using the Internet of Things(IoT)and blockchain to address these challenges of authenticity and traceability of apparel ***,multiple smart contracts are designed and developed for registration,process execution,audit,fault,and product traceability to authorize,validate,and trace every business transaction among the apparel ***,the real-time performance analysis of ChainApparel is carried out regarding transaction throughput and latency by deploying the compute nodes at different geographical locations using Hyperledger *** results conclude that ChainApparel accomplished significant performance under diverse workloads while ensuring complete traceability along the complex supply chain of the apparel ***,the ChainApparel framework helps make the apparel product more trustworthy and transparent in the market while safeguarding trust among the industry stakeholders.

关键词： Blockchain smart contracts hyperledger fabric Internet of Things traceability apparel industry 4.0

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