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MoBshield:A Novel XML Approach for securing Mobile Banking

Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： saeed seraj ali safaa sadiq OmprakashKaiwartya Mohammad Aljaidi Alexandros Konios Mohammed ali Mohammed Abazeed Department of Computer science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK Department of Computer science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan Department of Computer science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and *** is due to the growing number of mobile baking applications and their reachability and usefulness to ***,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking *** literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security *** this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBshield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training *** dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission ***,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s *** evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false ***,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art *** promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking ***,MoBshield has the potential to significantly enhance the security and trustworthiness of

关键词： security malware detection deep learning convolutional neural networks deep neural networks

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Prediction of Geopolymer Concrete Compressive strength Using Convolutional Neural Networks

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Computer Modeling in Engineering & sciences 2024年第5期139卷 1455-1486页

作者： Kolli Ramujee Pooja sadula Golla Madhu sandeep Kautish Abdulaziz s.Almazyad Guojiang Xiong ali Wagdy Mohamed Department of Civil Engineering VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Information Technology VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India Department of Computer science LBEF Campus(Asia Pacific University of Technology&InnovationMalaysia)Kathmandu44600Nepal Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Guizhou Key Laboratory of Intelligent Technology in Power system College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied science Research Center Applied Science Private UniversityAmmanJordan

Geopolymer concrete emerges as a promising avenue for sustainable development and offers an effective solution to environmental *** attributes as a non-toxic,low-carbon,and economical substitute for conventional cement concrete,coupled with its elevated compressive strength and reduced shrinkage properties,position it as a pivotal material for diverse applications spanning from architectural structures to transportation *** this context,this study sets out the task of using machine learning(ML)algorithms to increase the accuracy and interpretability of predicting the compressive strength of geopolymer concrete in the civil engineering *** achieve this goal,a new approach using convolutional neural networks(CNNs)has been *** study focuses on creating a comprehensive dataset consisting of compositional and strength parameters of 162 geopolymer concrete mixes,all containing Class F fly *** selection of optimal input parameters is guided by two distinct *** first criterion leverages insights garnered from previous research on the influence of individual features on compressive *** second criterion scrutinizes the impact of these features within the model’s predictive *** to enhancing the CNN model’s performance is the meticulous determination of the optimal *** a systematic trial-and-error process,the study ascertains the ideal number of epochs for data division and the optimal value of k for k-fold cross-validation—a technique vital to the model’s *** model’s predictive prowess is rigorously assessed via a suite of performance metrics and comprehensive score ***,the model’s adaptability is gauged by integrating a secondary dataset into its predictive framework,facilitating a comparative evaluation against conventional prediction *** unravel the intricacies of the CNN model’s learning trajectory,a loss plot is deployed to elucidate its learning rat

关键词： Class F fly ash compressive strength geopolymer concrete prediction deep learning convolutional neural network

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Reflections on the importance of built heritage inventory as a tool for preservation in Karachi-a case study of Wadhumal Odharam(Jail)Quarter in Karachi,sindh,Pakistan

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Built Heritage 2024年第1期8卷 29-45页

作者： Tania ali soomro Department of Architecture and Urban studies Politecnico Di MilanoMilanoItaly

The cultural heritage inventory is an alternate tool to document historic buildings to establish a protected enlistment *** the importance of inventories for developing knowledge of historical and cultural patterns,multiple attempts are being made to record Karachi's historic buildings in the form of inventory *** research investigates the various approaches used for inventorying Karachi's cultural heritage and their potential impact on the survival of the city's historical *** literature,this research provides a brief overview of Karachi's architectural development before and after its annexation to the British Raj(Term used by scholars to represent the British Crown in *** term'The Raj'is also sometimes used.)(1843-1947),which is now considered the historic core of the city of Karachi,together with the systems of inventorying the built heritage over *** Odharam(Jail)Quarter is shortlisted as a case study for this research,which will be examined from the perspective of inventory making in relation to its specific physical and sociocultural context as documented through the inventorying *** Quarter is also referred to as'Jail Quarter'because of the presence of the Jail building within the Quarter precinct,which was demolished during the British era;it is discussed in further detail later in this *** research approach follows a survey of the quarter conducted between August and september 2022,followed by a mapping of the historic *** inventory mapping of the Quarter is performed by using an available database(Database of various historic Quarters of Karachi by Heritage Cell-DAPNED).The data for inventory also helps provide an understanding of the history and development of the *** other aspects of the research methodology include intreating questions and collecting data about various aspects of the Quarter,such as the building information,photographic documentation of the properties,an

关键词： inventorying inventory making heritage conservation commercialisation pressure

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Elevating Image steganography:A Fusion of MsB Matching and LsB substitution for Enhanced Concealment Capabilities

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Computers, Materials & Continua 2024年第5期79卷 2923-2943页

作者： Muhammad Zaman ali Omer Riaz Hafiz Muhammad Hasnain Waqas sharif Tenvir ali Gyu sang Choi Department of Information Technology The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer science The Islamia University of BahawalpurBahawalpur63100Pakistan school of Computer science and Engineering Yeungnam UniversityGyeongbuk38541Korea

In today’s rapidly evolving landscape of communication technologies,ensuring the secure delivery of sensitive data has become an essential *** overcome these difficulties,different steganography and data encryption methods have been proposed by researchers to secure *** of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LsB *** this work,we have an approach that utilizes a combinationofMost significantBit(MsB)matching andLeast significant Bit(LsB)*** proposed algorithm divides confidential messages into pairs of bits and connects them with the MsBs of individual pixels using pair matching,enabling the storage of 6 bits in one pixel by modifying a maximum of three *** proposed technique is evaluated using embedding capacity and Peak signal-to-Noise Ratio(PsNR)score,we compared our work with the Zakariya scheme the results showed a significant increase in data concealment *** achieved results of ourwork showthat our algorithmdemonstrates an improvement in hiding capacity from11%to 22%for different data samples while maintaining a minimumPeak signal-to-Noise Ratio(PsNR)of 37 *** findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.

关键词： steganography most significant bit(MsB) least significant bit(LsB) peak signal-to-noise ratio(PsNR)

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An Improved Binary Quantum-based Avian Navigation Optimizer Algorithm to select Effective Feature subset from Medical Data:A COVID-19 Case study

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Journal of Bionic Engineering 2024年第1期21卷 426-446页

作者： ali Fatahi Mohammad H.Nadimi-shahraki Hoda Zamani Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityNajafabad ***Iran Big Data Research Center Najafabad BranchIslamic Azad UniversityNajafabad ***Iran

Feature subset selection(Fss)is an NP-hard problem to remove redundant and irrelevant features particularly from medical data,and it can be effectively addressed by metaheuristic ***,existing binary versions of metaheuristic algorithms have issues with convergence and lack an effective binarization method,resulting in suboptimal solutions that hinder diagnosis and prediction *** paper aims to propose an Improved Binary Quantum-based Avian Navigation Optimizer Algorithm(IBQANA)for Fss in medical data preprocessing to address the suboptimal solutions arising from binary versions of metaheuristic *** proposed IBQANA’s contributions include the Hybrid Binary Operator(HBO)and the Distance-based Binary search strategy(DBss).HBO is designed to convert continuous values into binary solutions,even for values outside the[0,1]range,ensuring accurate binary *** the other hand,DBss is a two-phase search strategy that enhances the performance of inferior search agents and accelerates *** combining exploration and exploitation phases based on an adaptive probability function,DBss effectively avoids local *** effectiveness of applying HBO is compared with five transfer function families and thresholding on 12 medical datasets,with feature numbers ranging from 8 to 10,***'s effectiveness is evaluated regarding the accuracy,fitness,and selected features and compared with seven binary metaheuristic ***,IBQANA is utilized to detect *** results reveal that the proposed IBQANA outperforms all comparative algorithms on COVID-19 and 11 other medical *** proposed method presents a promising solution to the Fss problem in medical data preprocessing.

关键词： Feature subset selection Optimization Binary metaheuristic algorithms Bioinspired Machine learning Medical datasets

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Analysis of cohesive particles mixing behavior in a twin-paddle blender:DEM and machine learning applications

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Particuology 2024年第7期90卷 350-363页

作者： Behrooz Jadidi Mohammadreza Ebrahimi Farhad Ein-Mozaffari ali Lohi Department of Chemical Engineering Toronto Metropolitan University350 Victoria StreetToronto M5B 2K3Canada

This research paper presents a comprehensive discrete element method(DEM)examination of the mixing behaviors exhibited by cohesive particles within a twin-paddle blender.A comparative analysis between the simulation and experimental results revealed a relative error of 3.47%,demonstrating a strong agreement between the results from the experimental tests and the DEM *** main focus centers on systematically exploring how operational parameters,such as impeller rotational speed,blender's fill level,and particle mass ratio,influence the *** investigation also illustrates the significant influence of the mixing time on the mixing *** gain a deeper understanding of the DEM simulation findings,an analytical tool called multivariate polynomial regression in machine learning is *** method uncovers significant connections between the DEM results and the operational parameters,providing a more comprehensive insight into their *** multivariate polynomial regression model exhibited robust predictive performance,with a mean absolute percentage error of less than 3%for both the training and validation sets,indicating a slight deviation from actual *** model's precision was confirmed by low mean absolute error values of 0.0144(80%of the dataset in the training set)and 0.0183(20%of the dataset in the validation set).The study offers valuable insights into granular mixing behaviors,with implications for enhancing the efficiency and predictability of the mixing processes in various industrial applications.

关键词： Machine learning Granular mixing Discrete element method Mixing kinetics and mechanism Cohesive particles

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Metabolic complications of psychotropic medications in psychiatric disorders:Emerging role of de novo lipogenesis and therapeutic consideration

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World Journal of Psychiatry 2024年第6期14卷 767-783页

作者： Mohammad M Khan Zaw ali Khan Mohsin ali Khan Laboratory of Translational Neurology and Molecular Psychiatry Department of BiotechnologyEra’s Lucknow Medical College and Hospitaland Faculty of ScienceEra UniversityLucknow 226003India Era’s Lucknow Medical College and Hospital Era UniversityLucknow 226003India

Although significant advances have been made in understanding the pathophysiology of psychiatric disorders(PDs),therapeutic advances have not been very *** psychotropic medications can reduce classical symptoms in patients with PDs,their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes,obesity and non-alcoholic fatty liver disease(NAFLD).The mechanism(s)underlying these metabolic abnormalities is not clear;however,lipid/fatty acid accumulation due to enhanced de novo lipogenesis(DNL)has been shown to reduce membrane fluidity,increase oxidative stress and inflammation leading to the development of the aforementioned metabolic ***,emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity,diabetes and NAFLD after long-term treatment with psychotropic medications in patients with *** support of this,several adjunctive drugs comprising of anti-oxidants and antiinflammatory agents,that are used in treating PDs in combination with psychotropic medications,have been shown to reduce insulin resistance and development of *** conclusion,the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities,and a new avenue for translational research and therapeutic drug designing in PDs.

关键词： Psychotropic medications Metabolic complications De novo lipogenesis Obesity Diabetes Non-alcoholic fatty liver disease

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Using neural network modeling to improve the detection accuracy of land subsidence due to groundwater withdrawal

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Journal of Mountain science 2024年第7期21卷 2320-2333页

作者： ali M.RAJABI ali EDALAT Yasaman ABOLghasemi Mahdi KHODAPARAsT Department of Engineering Geology University of TehranTehran ***Iran Department of Civil Engineering University of QomQom ***Iran

Despite the high efficiency of remote sensing methods for rapid and large-scale detection of subsidence phenomena,this technique has limitations such as atmospheric impact and temporal and spatial decorrelation that affect the accuracy of the *** paper proposes a method based on an artificial neural network to improve the results of monitoring land subsidence due to groundwater overexploitation by radar interferometry in the aliabad plain(Central Iran).In this regard,vertical ground deformations were monitored over 18 months using the sentinel-1A sAR *** model the land subsidence by a multilayer perceptron(MLP)artificial neural network,four parameters,including groundwater level,alluvial thickness,elastic modulus,and transmissivity have been *** model's generalizability was assessed using data derived for 144 *** to the results,the neural network estimates the land subsidence at each ground point with an accuracy of 6.8 mm.A comparison between the predicted and actual values indicated a significant *** MLP model can be used to improve the results of subsidence detection in the study area or other areas with similar characteristics.

关键词： DInsAR Land subsidence Groundwater withdrawal aliabad plain Artificial neural network

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Tubular Heat Enhancement Using Twisted Tape Inserts with Large Holes

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Energy Engineering 2024年第2期121卷 273-290页

作者： ali Jaber Abdulhamed Aws Al-Akam Wisam J.Khudhayer ali sabri Allw Faculty of Engineering-Al-Mussayib University of BabylonHillaBabylon15001Iraq

Heat augmentation techniques play a vital role in the heating and cooling processes in industries,including solar collectors and many applications that utilize heat *** studies are based on inserting fillers inside the tubes to enhance heat *** investigation considered the effects of twisted tapes with large holes on a tubular heat exchanger’s(HX)heat transmission,pressure drop,and thermal boosting *** the experimental section,counter-swirl flow generators used twisted tapes with pairs of 1.0 cm-diameter holes and changes in porosity(Rp)at 1.30%and 2.70%.In the experiments,air was utilized as a working fluid in a tube with a circular *** turbulent flow was considered,with Reynolds numbers(Re)domain from 4800 to 9500,and a boundary condition with a uniform wall heat flux was *** findings expound that when the number of holes rose,the Nusselt number(Nu),the factor of friction(f),and the thermal enhancement factor(η)all increased as ***,as the friction factor increased,the Nusselt number of the tape-equipped tube was noticeably ***,it was discovered that the friction factor was between 70%and 94%lower than the values of the tube without tape,while the(Nu)was between 87%and 97%higher than the conventional tube *** maximum value ofηis 89%.According to the experimental results,empirical correlations for Nu,f,andηwere also generated.

关键词： Tubular heat exchanger tape inserts twisted tape

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Evolutionary safe Padé Approximation scheme for Dynamical study of Nonlinear Cervical Human Papilloma Virus Infection Model

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Computer Modeling in Engineering & sciences 2024年第9期140卷 2275-2296页

作者： Javaid ali Armando Ciancio Kashif ali Khan Nauman Raza Haci Mehmet Baskonus Muhammad Luqman Zafar-Ullah Khan Department of Mathematics Govt.Graduate College TownshipLahore54770Pakistan Universitàdegli studi di Messina Dipartimento di Scienze BiomedicheOdontoiatriche e delle Immagini Morfologiche e FunzionaliMessina98122Italy Department of Mathematics University of Engineering and TechnologyLahore54890Pakistan Department of Mathematics University of the PunjabLahore54590Pakistan Mathematics Research Center Near East University TRNCMersin 10Nicosia99138Turkey Department of Mathematics and science Education Faculty of EducationHarran UniversitySanliurfa63190Turkey Department of Dermatology Rashid Latif Medical CollegeLahore54600Pakistan

This study proposes a structure-preserving evolutionary framework to find a semi-analytical approximate solution for a nonlinear cervical cancer epidemic(CCE)*** underlying CCE model lacks a closed-form exact *** solutions obtained through traditional finite difference schemes do not ensure the preservation of the model’s necessary properties,such as positivity,boundedness,and ***,the development of structure-preserving semi-analytical approaches is always *** research introduces an intelligently supervised computational paradigm to solve the underlying CCE model’s physical properties by formulating an equivalent unconstrained optimization ***-free safe Padérational functions approximate the mathematical shape of state variables,while the model’s physical requirements are treated as problem *** primary model of the governing differential equations is imposed to minimize the error between approximate *** evolutionary algorithm,the Genetic Algorithm with Multi-Parent Crossover(GA-MPC),executes the optimization *** resulting method is the Evolutionary safe PadéApproximation(EsPA)*** proof of unconditional convergence of the EsPA scheme on the CCE model is supported by numerical *** performance of the EsPA scheme on the CCE model is thoroughly investigated by considering various orders of non-singular Padéapproximants.

关键词： Nonlinear cervical cancer epidemic non-singular Padéapproximants approximate solutions computational biology

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