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Natural Convection and Irreversibility of Nanofluid Due to Inclined Magnetohydrodynamics(MHD)Filled in a Cavity with Y-Shape Heated Fin:FEM Computational

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1505-1519页

作者： Afraz Hussain Majeed Rashid Mahmood Sayed M.Eldin imran saddique S.Saleem Muhammad Jawad School of Energy and Power Engineering Jiangsu UniversityZhenjiang212013China Department of Mathematics Air UniversityIslamabad44000Pakistan Center of Research Faculty of EngineeringFuture University in EgyptNew Cairo11835Egypt Department of Mathematics University of Management and TechnologyLahore54770Pakistan Department of Mathematics University of SargodhaSargodha40100Pakistan Department of Mathematics College of ScienceKing Khalid UniversityAbha61413Saudi Arabia Faculty of Sciences The Superior UniversityLahore54000Pakistan

This study explains the entropy process of natural convective heating in the nanofluid-saturated cavity in a heated fin andmagnetic *** temperature is constant on the Y-shaped fin,insulating the topwall while the remaining walls remain *** walls are subject to impermeability and non-slip *** mathematical modeling of the problem is demonstrated by the continuity,momentum,and energy equations incorporating the inclined magnetic *** elucidating the flow characteristics Finite ElementMethod(FEM)is implemented using stable FE pair.A hybrid fine mesh is used for discretizing the *** and thermal plots concerning parameters are *** addition,a detailed discussion regarding generation energy by monitoring changes in magnetic,viscous,total,and thermal irreversibility is *** addition,line graphs are created for the u and v components of the velocity profile to predict the flow *** simulations assume the dimensionless representative of magnetic field Hartmann number Ha between 0 and 100 and a magnetic field inclination between 0 and 90 degrees.A constant 4% volume proportion of nanoparticles is employed throughout all scenarios.

关键词： Finite element method nanomaterials entropy MHD square cavity Y-fin

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A Mathematical Approach for Generating a Highly Non-Linear Substitution Box Using Quadratic Fractional Transformation

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Computers, Materials & Continua 2023年第11期77卷 2565-2578页

作者： Abid Mahboob Muhammad Asif Rana Muhammad Zulqarnain imran saddique Hijaz Ahmad Sameh Askar Department of Mathematics Division of Science and TechnologyUniversity of EducationLahorePakistan Department of Mathematics University of Management and TechnologySialkot Campus51310Pakistan School of Mathematical Sciences Zhejiang Normal UniversityJinhua321004China Department of Mathematics University of Management and TechnologyLahore54770Pakistan Section of Mathematics International Telematic University UninettunoCorso Vittorio Emanuele IIRoma39-00186Italy Department of Statistics and Operations Research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

Nowadays,one of the most important difficulties is the protection and privacy of confidential *** address these problems,numerous organizations rely on the use of cryptographic techniques to secure data from illegal activities and *** cryptographic ciphers use the non-linear component of block cipher to ensure the robust encryption process and lawful decoding of plain data during the decryption *** the designing of a secure substitution box(S-box),non-linearity(NL)which is an algebraic property of the S-box has great ***,the main focus of cryptographers is to achieve the S-box with a high value of *** this suggested study,an algebraic approach for the construction of 16×16 S-boxes is provided which is based on the fractional transformation Q(z)=1/α(z)^(m)+β(mod257)and finite *** technique is only applicable for the even number exponent in the range(2-254)that are not multiples of ***,we choose a quadratic fractional transformation,swap each missing element with repeating elements,and acquire the initial *** the second stage,a special permutation of the symmetric group S256 is utilized to construct the final S-box,which has a higher NL score of 112.75 than the Advanced Encryption Standard(AES)S-box and a lower linear probability score of *** addition,a tabular and graphical comparison of various algebraic features of the created S-box with many other S-boxes from the literature is provided which verifies that the created S-box has the ability and is good enough to withstand linear and differential *** different analyses,it is ensured that the proposed S-boxes are better than as compared to the existing *** these S-boxes can be utilized in the security of the image data and the text data.

关键词： Block cipher S-box data security fractional transformation

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Enhanced Steganalysis for Color Images Using Curvelet Features and Support Vector Machine

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Computers, Materials & Continua 2024年第1期78卷 1311-1328页

作者： Arslan Akram imran Khan Javed Rashid Mubbashar saddique Muhammad Idrees Yazeed Yasin Ghadi Abdulmohsen Algarni Faculty of Computer Science and Information Technology Department of Computer ScienceSuperior UniversityLahore54000Pakistan Machine Learning Code(MLC)Lab Meharban HouseHouse Number 209Zafar ColonyOkara56300Pakistan Information Technology Services University of OkaraOkara56310Pakistan Department of Computer Science&Engineering University of Engineering&Technology LahoreNarowal CampusNarowal51601Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain11671Abu Dhabi Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Algorithms for steganography are methods of hiding data transfers in media *** machine learning architectures have been presented recently to improve stego image identification performance by using spatial information,and these methods have made it feasible to handle a wide range of problems associated with image *** with little information or low payload are used by information embedding methods,but the goal of all contemporary research is to employ high-payload images for *** address the need for both low-and high-payload images,this work provides a machine-learning approach to steganography image classification that uses Curvelet transformation to efficiently extract characteristics from both type of *** Vector Machine(SVM),a commonplace classification technique,has been employed to determine whether the image is a stego or *** Wavelet Obtained Weights(WOW),Spatial Universal Wavelet Relative Distortion(S-UNIWARD),Highly Undetectable Steganography(HUGO),and Minimizing the Power of Optimal Detector(MiPOD)steganography techniques are used in a variety of experimental scenarios to evaluate the performance of the *** WOW at several payloads,the proposed approach proves its classification accuracy of 98.60%.It exhibits its superiority over SOTA methods.

关键词： Curvelets fast fourier transformation support vector machine high pass filters steganography

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Appraisal of Deforestation in Murree through Open Source Satellite Imagery

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Advances in Remote Sensing 2018年第2期7卷 61-70页

作者： Tabasam Jamal Shoaib Naseer Syed Shehzad Hassan Hafsa Batool Rashid Mahmood Attia Naz Atif Butt Usman Tanver imran saddique Kaukab Sana Alvi Javed Ahmad Azeem Akhtar Arshid Javed A. Ali Department of Geography University of the Punjab New Campus Lahore Punjab Pakistan Remote Sensing Group Department of Space Science University of the Punjab Lahore Pakistan

Forests are the main source of income for humans and shelter for many rare in habitants. Forests act as carbon sink and help to reduce the effect of natural hazards like floods. The timber is among the main products of forests used for precious furniture. Forest must cover one third of the part of any country but in Pakistan, it covers less than 4%. If the deforestation continues with the same ratio, there will be a drastic change in the upcoming years. The main objective of the study is to determine deforestation rates in Murree for the years 1999-2015 through open source Landsat 7, 8 imageries. The areas with high deforestation rates are also delineated. Supervised classification is used to delineate the area under buildup, vegetation and water that was 83.85 km2, 760.63 km2 and 1.18 km2 respectively in 1999. Built up area increased up to 20% and forests declined by 23% in 2015 as compared to 1999. Remote sensing and GIS tools helped to investigate the deforestation rates with high accuracy.

关键词： Landsat 7 Landsat 8 Supervised Classification Deforestation Vegetation Index

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Environmental Assessment and Analysis of Chemical Properties of Drinking Water Using Geo-Spatial Technologies: Examples from Lahore Metropolitan

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Advances in Remote Sensing 2018年第3期7卷 259-275页

作者： Ali Imam Mirza Ali Iqtadar Mirza Tabasam Jamal Syed Shehzad Hassan Muhammad A. Butt Atif Ali Hafsa Batool Rashid Mahmood Attia Naz Azam Sohail imran saddique Kaukab Sana Alvi Javed Ahmad Safeer Ali Muneeb Aamir Azeem Akhtar Arshad Javed Department of Geography GC University Lahore Pakistan Remote Sensing Group Department of Space Science University of the Punjab Lahore Pakistan

The contamination of drinking water in Pakistan is a serious threat to its citizens. Urbanization leads to an increased demand of drinking water supply that leads to excessive drawdown that further causes lowering of water table. The current WASA (Water and Sanitation Authority) supply network does not fulfill the demand of a growing metropolitan city of Lahore. The drawdown of Lahore is absolutely reliant on Water and Sanitation Authority (WASA) water supply network that causes numerous problems due to inappropriate management of groundwater capital and increased urbanization. This research investigates groundwater qualities: Alkalinity, Arsenic, Calcium, chloride, Total Hardness, Magnesium, Nitrate, pH and Total Dissolved solids using geographic information system (GIS). Residents of high concentrated towns, like Samnabad Town, Allama Iqbal Town, Gulberg, Data Ganj Bakhsh Town, Ravi Town and Wahga town witness cut-down of water supply mainly due to over burden on tube wells. Chemical properties of drinking water show that most of the parameters were within the allowable limits of WHO whereas the pH, and arsenic values are higher than the average. Arsenic is a carcinogenic element which causes cancer and is higher in the drinking water. Finally, this study identifies highly contaminated groundwater zones and makes it convenient to find actual pollutants. Therefore, plans are needed to protect the aquifer.

关键词： Water Contamination Urbanization Geographic Information System (GIS) Chemical Properties Carcinogenic Elements WHO WebGIS RS WASA DNA pH TDS

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A Hybrid Deep Learning Approach to Classify the Plant Leaf Species

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Computers, Materials & Continua 2023年第9期76卷 3897-3920页

作者： Javed Rashid imran Khan Irshad Ahmed Abbasi Muhammad Rizwan Saeed Mubbashar saddique Mohamed Abbas Department of CS&SE Islamic International UniversityIslamabad44000Pakistan Department of IT Services University of OkaraOkara56310Pakistan Faculty of Science and Arts Belqarn University of BishaSabtul Alaya61985Saudi Arabia Department of CS University of OkaraOkara56310Pakistan Department of Computer Science&Engineering University of Engineering&Technology LahoreNarowalCampusNarowal51601Pakistan Electrical Engineering Department College of EngineeringKing Khalid UniversityAbha61421Saudi Arabia Research Center for Advanced Materials Sciences(RCAMS) King Khalid UniversityAbhaSaudi Arabia

Many plant species have a startling degree of morphological similarity,making it difficult to split and categorize them *** plant species can be challenging to classify and segment using deep *** using deep learning architectures has helped improve classification accuracy,the resulting models often need to be more flexible and require a large dataset to *** the sake of taxonomy,this research proposes a hybrid method for categorizing guava,potato,and java *** new approaches are used to formthe hybridmodel suggested *** guava,potato,and java plum plant species have been successfully segmented using the first model built on the MobileNetV2-UNET *** a second model,we use a Plant Species Detection Stacking Ensemble Deep Learning Model(PSD-SE-DLM)to identify potatoes,java plums,and *** proposed models were trained using data collected in Punjab,Pakistan,consisting of images of healthy and sick leaves from guava,java plum,and *** datasets are known as PLSD and *** levels of 99.84%and 96.38%were achieved for the suggested PSD-SE-DLM and MobileNetV2-UNET models,respectively.

关键词： Plant leaf species stacking ensemble model guava potato java plum MobileNetV2-UNET hybrid deep learning segmentation

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Binary Oriented Feature Selection for Valid Product Derivation in Software Product Line

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Computers, Materials & Continua 2023年第9期76卷 3653-3670页

作者： Muhammad Fezan Afzal imran Khan Javed Rashid Mubbashar saddique Heba G.Mohamed Department of CS&SE International Islamic UniversityIslamabad44000Pakistan Information Technology Services University of OkaraOkara56300Pakistan Departmet of Computer Science MLC LabOkara56300Pakistan Department of Computer Science&Engineering University of Engineering&Technology LahoreNarowal CampusNarowal51601Pakistan Department of Electrical Engineering College of EngineeringPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

Software Product Line(SPL)is a group of software-intensive systems that share common and variable resources for developing a particular *** feature model is a tree-type structure used to manage SPL’s common and variable features with their different relations and problem of Crosstree Constraints(CTC).CTC problems exist in groups of common and variable features among the sub-tree of feature models more diverse in Internet of Things(IoT)devices because different Internet devices and protocols are ***,managing the CTC problem to achieve valid product configuration in IoT-based SPL is more complex,time-consuming,and ***,the CTC problem needs to be considered in previously proposed approaches such as Commonality VariabilityModeling of Features(COVAMOF)andGenarch+tool;therefore,invalid products are *** research has proposed a novel approach Binary Oriented Feature Selection Crosstree Constraints(BOFS-CTC),to find all possible valid products by selecting the features according to cardinality constraints and cross-tree constraint problems in the featuremodel of ***-CTC removes the invalid products at the early stage of feature selection for the product ***,this research developed the BOFS-CTC algorithm and applied it to,IoT-based feature *** findings of this research are that no relationship constraints and CTC violations occur and drive the valid feature product configurations for the application development by removing the invalid product *** accuracy of BOFS-CTC is measured by the integration sampling technique,where different valid product configurations are compared with the product configurations derived by BOFS-CTC and found 100%*** BOFS-CTC eliminates the testing cost and development effort of invalid SPL products.

关键词： Software product line feature model internet of things crosstree constraints variability management

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