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A Novel Approach to Energy Optimization:Efficient Path Selection in Wireless Sensor Networks with Hybrid ANN

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Computers, Materials & Continua 2024年第5期79卷 2945-2970页

作者： muhammad Salman Qamar Ihsan ulHaq Amil Daraz Atif MAlamri Salman A.AlQahtani muhammad Fahad Munir Department of Electrical and Computer Engineering International Islamic UniversityIslamabad44000Pakistan School of Information Science and Engineering NingboTech UniversityNingbo315100China Software Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia Computer Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia

In pursuit of enhancing the Wireless Sensor Networks(WSNs)energy efficiency and operational lifespan,this paper delves into the domain of energy-efficient routing ***,the limited energy resources of Sensor Nodes(SNs)are a big challenge for ensuring their efficient and reliable *** data gathering involves the utilization of a mobile sink(MS)to mitigate the energy consumption problem through periodic network *** mobile sink(MS)strategy minimizes energy consumption and latency by visiting the fewest nodes or predetermined locations called rendezvous points(RPs)instead of all cluster heads(CHs).CHs subsequently transmit packets to neighboring *** unique determination of this study is the shortest path to reach *** the mobile sink(MS)concept has emerged as a promising solution to the energy consumption problem in WSNs,caused by multi-hop data collection with static *** this study,we proposed two novel hybrid algorithms,namely“ Reduced k-means based on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans with ANN”(DBRkM-ANN)for designing a fast,efficient,and most proficient MS path depending upon rendezvous points(RPs).The first algorithm optimizes the MS’s latency,while the second considers the designing of delay-bound paths,also defined as the number of paths with delay over bound for the *** methods use a weight function and k-means clustering to choose RPs in a way that maximizes efficiency and guarantees network-wide *** addition,a method of using MS scheduling for efficient data collection is *** simulations and comparisons to several existing algorithms have shown the effectiveness of the suggested methodologies over a wide range of performance indicators.

关键词： Wireless Sensor Networks(WSNs) mobile sink(MS) rendezvous point(RP) machine learning Artificial Neural Networks(ANNs)

Comparative analysis of jet and underlying event properties across various models as a function of charged particle multiplicity at 7 TeV

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Chinese Physics C 2024年第9期48卷 118-125页

作者： Maryam Waqar Haifa I.Alrebdi muhammad Waqas K.S.Al-mugren muhammad Ajaz Department of Physics Abdul Wali Khan University MardanMardan 23200Pakistan Department of Physics College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia School of Nuclear Science and Technology University of Chinese Academy of SciencesBeijing 100049China

In this study,a comprehensive analysis of jets and underlying events as a function of charged particle multiplicity in proton-proton(pp)collisions at a center-of-mass energy of √s=7 TeV is *** Monte Carlo(MC)event generators,including Pythia8.308,EPOS 1.99,EPOSLHC,EPOS4_(Hydro),and EPOS4_(noHydro),are employed to predict particle *** predictions from these models are compared with experimental data from the CMS *** charged particles are categorized into those associated with underlying events and those linked to jets,and the analysis is restricted to charged particles with|η|0.25 GeV/*** comparing the MC predictions with CMS data,we find that EPOS4_(Hydro),EPOSLHC,and Pythia8 consistently reproduce the experimental results for all charged particles,underlying events,intrajets,and leading charged *** charged jet rates with p_T^(***)>5 GeV/c,EPOS4_(Hydro)and Pythia8 perform exceptionally *** the case of charged jet rates with p_T^(***)→30 GeV/c,EPOSLHC reproduces satisfactorily good results,whereas EPOS4 Hydro exhibits good agreement with the data at higher charged particle multiplicities compared to the other *** can be attributed to the conversion of energy into flow when"Hydro=on"leading to an increase in *** EPOSLHC model describes the data better owing to the new collective flow effects,correlated flow treatment,and parameterization compared to EPOS ***,the examination of the jet p_T spectrum and normalized charged p_T density reveals that EPOS4_(Hydro),EPOS4_(noHydro),and EPOSLHC exhibit good agreement with the experimental results,whereas Pythia8 and EPOS 1.99 do not perform as well owing to the lack of correlated flow treatment.

关键词： Monte Carlo models underlying event jets charged particle multiplicity

Advances in Zika virus vaccines and therapeutics:A systematic review

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Asian Pacific Journal of Tropical Medicine 2024年第3期17卷 97-109页

作者： Shiza Malik Khalid muhammad Omar Ahsan muhammad Tahir Khan Ranjit Sah Yasir Waheed Bridging Health Foundation Rawalpindi 46000Pakistan Department of Biology College of SciencesUAE University15551Al AinUnited Arab Emirates Department of Medicine Foundation University Medical CollegeFoundation University IslamabadIslamabad 44000Pakistan INTI International university Persiaran Perdana BBN Putra Nilai71800 NilaiNegeri SembilanMalaysia Institute of Molecular Biology and Biotechnology the University of LahoreKM Defence RoadLahore 58810Pakistan Zhongjing Research and Industrialization Institute of Chinese Medicine Zhongguancun Scientific ParkNanyang 473006China Department of Microbiology Tribhuvan University Teaching HospitalInstitute of MedicineKathmandu 44600Nepal Department of Microbiology Dr.D.Y.Patil Medical CollegeHospital and Research CentreDr.D.Y.Patil VidyapeethPune 411018MaharashtraIndia Department of Public Health Dentistry Dr.D.Y.Patil Dental College and HospitalDr.D.Y.Patil VidyapeethPune 411018MaharashtraIndia Gilbert and Rose-Marie Chagoury School of Medicine Lebanese American UniversityByblos 1401Lebanon

Zika virus(ZIKV)is the causative agent of a viral infection that causes neurological complications in newborns and adults *** wide transmission route and alarming spread rates are of great concern to the scientific *** trials have been conducted to develop treatment options for ZIKV *** review highlights the latest developments in the fields of vaccinology and pharmaceuticals developments for ZIKV infection.A systematic and comprehensive approach was used to gather relevant and up-to-date data so that inferences could be made about the gaps in therapeutic *** results indicate that several therapeutic interventions are being tested against ZIKV infection,such as DNA vaccines,subunit vaccines,live-attenuated vaccines,virus-vector-based vaccines,inactivated vaccines,virus-like particles,and mRNA-based *** addition,approved anti-ZIKV drugs that can reduce the global burden are *** many vaccine candidates for ZIKV are at different stages of development,none of them have received Food and Drug Authority approval for use up to *** issue of side effects associated with these drugs in vulnerable newborns and pregnant women is a major obstacle in the therapeutic pathway.

关键词： Zika virus Infection Therapeutics Antiviral agents Vaccines Therapies Treatment Novel therapeutic Clinical management

Data Information integrated Neural Network (DINN) algorithm for modelling and interpretation performance analysis for energy systems

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Energy and AI 2024年第2期16卷 306-315页

作者： Waqar muhammad Ashraf Vivek Dua The Sargent Centre for Process Systems Engineering Department of Chemical EngineeringUniversity College LondonTorrington PlaceLondon WC1E 7JEUK

Developing a well-predictive machine learning model that also offers improved interpretability is a key challenge to widen the application of artificial intelligence in various application domains. In this work, we present a Data Information integrated Neural Network (DINN) algorithm that incorporates the correlation information present in the dataset for the model development. The predictive performance of DINN is also compared with a standard artificial neural network (ANN) model. The DINN algorithm is applied on two case studies of energy systems namely energy efficiency cooling (ENC) & energy efficiency heating (ENH) of the buildings, and power generation from a 365 MW capacity industrial gas turbine. For ENC, DINN presents lower mean RMSE for testing datasets (RMSE_test = 1.23 %) in comparison with the ANN model (RMSE_test = 1.41 %). Similarly, DINN models have presented better predictive performance to model the output variables of the two case studies. The input perturbation analysis following the Gaussian distribution for noise generation reveals the order of significance of the variables, as made by DINN, can be better explained by the domain knowledge of the power generation operation of the gas turbine. This research work demonstrates the potential advantage to integrate the information present in the data for the well-predictive model development complemented with improved interpretation performance thereby opening avenues for industry-wide inclusion and other potential applications of machine learning.

关键词： Explainable AI Model interpretation Scientific machine learning Artificial neural network Loss function

Al^(3+) doped CeO_(2) for proton conducting fuel cells

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International Journal of Minerals,Metallurgy and Materials 2024年第10期31卷 2253-2262页

作者： Sarfraz Shahzad Rasool muhammad Khalid MAKYousaf Shah Bin Zhu Jung-Sik Kim muhammad Imran Asghar Nabeela Akbar Wenjing Dong Jiangsu Provincial Key Laboratory of Solar Energy Science and Technology/Energy Storage joint Research Center School of Energy and EnvironmentSoutheast UniversityNanjing 210096China School of Microelectronics Hubei UniversityWuhan 430062China Sino-French Engineer School/School of General Engineering Beihang UniversityBeijing 100191China Renewable Energy Technologies Group Faculty of Engineering and Natural SciencesTampere UniversityFI-33014Finland

Developing high ionic conducting electrolytes is crucial for applying proton-conducting fuel cell(PCFCs)*** cur-rent study investigates the effect of alumina on the structural,morphological,electrical,and electrochemical properties of CeO_(2).Lattice oxygen vacancies are induced in CeO_(2) by a general doping concept that enables fast ionic conduction at low-temperature ranges(300-500℃)for *** refinement of the X-ray diffraction(XRD)patterns established the pure cubic fluorite structure of Al-doped CeO_(2)(ADC)samples and confirmed Al ions’fruitful integration in the CeO_(2) *** electronic structure of the alumina-doped ceria of the materials(10ADC,20ADC,and 30ADC)has been *** a result,it was found that the best composition of 30ADC-based electrolytes induced maximum lattice oxygen *** corresponding PCFC exhibited a maximum power output of 923 mW/cm^(2)at 500℃.Moreover,the investigation proves the proton-conducting ability of alumina-doped ceria-based fuel cells by using an oxide ion-blocking layer.

关键词： proton ceramic fuel cells oxygen vacancies higher fuel cell performance doping fast ions transportation

ROBO-SPOT:Detecting Robocalls by understanding User Engagement and Connectivity Graph

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Big Data Mining and Analytics 2024年第2期7卷 340-356页

作者： muhammad Ajmal Azad Junaid Arshad Farhan Riaz College of Comnputer Science Birmingham City UniversityBirminghamB55JUUK School of Computer Science University of LincolnLincolnLN67TSUK

Robo or unsolicited calls have become a persistent issue in telecommunication networks,posing significant challenges to individuals,businesses,and regulatory *** calls not only trick users into disclosing their private and financial information,but also affect their productivity through unwanted phone ringing.A proactive approach to identify and block such unsolicited calls is essential to protect users and service providers from potential ***,this paper proposes a solution to identify robo-callers in the telephony network utilising a set of novel features to evaluate the trustworthiness of callers in a *** trust score of the callers is then used along with machine learning models to classify them as legitimate or *** use a large anonymized dataset(call detailed records)from a large telecommunication provider containing more than 1 billion records collected over 10 *** have conducted extensive evaluation demonstrating that the proposed approach achieves high accuracy and detection rate whilst minimizing the error ***,the proposed features when used collectively achieve a true-positive rate of around 97%with a false-positive rate of less than 0.01%.

关键词： social network analysis reputation unwanted calls robo-callers telephone network Spam Over Internet Technology(SPIT)

The Impact of Domain Name Server(DNS)over Hypertext Transfer Protocol Secure(HTTPS)on Cyber Security:Limitations,Challenges,and Detection Techniques

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Computers, Materials & Continua 2024年第9期80卷 4513-4542页

作者： muhammad Dawood Shanshan Tu Chuangbai Xiao muhammad Haris Hisham Alasmary muhammad Waqas Sadaqat Ur Rehman Faculty of Information Technology Beijing University of TechnologyBeijing100124China National Center of Robotics and Automation University of Engineering and TechnologyPeshawar25000Pakistan Department of Computer Science College of Computer ScienceKing Khalid UniversityAbha61421Saudi Arabia School of Computing and Engineering Sciences Faculty of Engineering and ScienceUniversity of GreenwichLondonSE109LSUnited Kingdom School of Engineering Edith Cowan UniversityPerthWA 6027Australia School of Computer Science and Engineering University of SalfordManchesterM54BRUnited Kingdom

The DNS over HTTPS(Hypertext Transfer Protocol Secure)(DoH)is a new technology that encrypts DNS traffic,enhancing the privacy and security of ***,the adoption of DoH is still facing several research challenges,such as ensuring security,compatibility,standardization,performance,privacy,and increasing user *** significantly impacts network security,including better end-user privacy and security,challenges for network security professionals,increasing usage of encrypted malware communication,and difficulty adapting DNS-based security ***,it is important to understand the impact of DoH on network security and develop newprivacy-preserving techniques to allowthe analysis of DoH traffic without compromising user *** paper provides an in-depth analysis of the effects of DoH on *** discuss various techniques for detecting DoH tunneling and identify essential research challenges that need to be addressed in future security ***,this paper highlights the need for continued research and development to ensure the effectiveness of DoH as a tool for improving privacy and security.

关键词： DNS DNS over HTTPS cybersecurity machine learning

A Hybrid SIR-Fuzzy Model for Epidemic Dynamics:A Numerical Study

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3417-3434页

作者： muhammad Shoaib Arif Kamaleldin Abodayeh Yasir Nawaz Department of Mathematics and Sciences College of Humanities and SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Mathematics Air UniversityIslamabad44000Pakistan

This study focuses on the urgent requirement for improved accuracy in diseasemodeling by introducing a newcomputational framework called the Hybrid SIR-Fuzzy *** integrating the traditional Susceptible-Infectious-Recovered(SIR)modelwith fuzzy logic,ourmethod effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model *** main aim of this research is to provide a model for disease transmission using fuzzy theory,which can successfully address uncertainty in mathematical *** main emphasis is on the imprecise transmission rate parameter,utilizing a three-part description of its membership *** enhances the representation of disease processes with greater complexity and tackles the difficulties related to quantifying uncertainty in mathematical *** investigate equilibrium points for three separate scenarios and perform a comprehensive sensitivity analysis,providing insight into the complex correlation betweenmodel parameters and epidemic *** order to facilitate a quantitative analysis of the fuzzy model,we propose the implementation of a resilient numerical *** convergence study of the scheme demonstrates its trustworthiness,providing a conditionally positive solution,which represents a significant improvement compared to current forward Euler *** numerical findings demonstrate themodel’s effectiveness in accurately representing the dynamics of disease ***,when the mortality coefficient rises,both the susceptible and infected populations decrease,highlighting the model’s sensitivity to important epidemiological ***,there is a direct relationship between higher Holling type rate values and a decrease in the number of individuals who are infected,as well as an increase in the number of susceptible *** correlation offers a significant understanding of how many elements affect the con

关键词： Fuzzy-based model sensitivity equilibriumpoints proposed numerical scheme convergence and stability analysis

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