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Resolvability in Circulant Graphs

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Acta Mathematica Sinica,English Series 2012年第9期28卷 1851-1864页

作者： muhammad SALMAN Imran JAVAID muhammad anwar CHAUDHRY Center for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University

A set W of the vertices of a connected graph G is called a resolving set for G if for every two distinct vertices u, v E V（G） there is a vertex w E W such that d（u, w） ≠ d（v, w）. A resolving set of minimum cardinality is called a metric basis for G and the number of vertices in a metric basis is called the metric dimension of G, denoted by dim（G）. For a vertex u of G and a subset S of V（G）, the distance between u and S is the number minses d（u,s）. A k-partition II = {$1,$2,..., Sk} of V（G） is called a resolving partition if for every two distinct vertices u, v E V（G） there is a set Si in H such that d（u, Si） ≠ d（v, Si）. The minimum k for which there is a resolving k-partition of V（G） is called the partition dimension of G, denoted by pd（G）. The circulant graph is a graph with vertex set Zn, an additive group of integers modulo n, and two vertices labeled i and j adjacent if and only if i - j （rood n） E C, where C C Zn has the property that C = -C and 0 ￠ C. The circulant graph is denoted by Xn,△ where A = ｜C｜. In this paper, we study the metric dimension of a family of circulant graphs Xn,3 with connection set C = {1, 3, n - 1} and prove that dim（Xn,3） is independent of choice of n by showing that dim（Xn,a） = {3 for all n ≡0 （mod 4）,4 for all n≡2 （mod4）.We also study the partition dimension of a family of circulant graphs Xm,4 with connection set C = {±1, ±2} and prove that pd（Xn,4） is independent of choice of n and show that pd（X5,4） = 5 and pd（Xn,a） ={ 3 for all odd n≥9,4 for all even n≥6 and n=7.

关键词： Circulant graphs metric dimension partition dimension

Automated Video Generation of Moving Digits from Text Using Deep Deconvolutional Generative Adversarial Network

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Computers, Materials & Continua 2023年第11期77卷 2359-2383页

作者： anwar Ullah Xinguo Yu muhammad Numan National Engineering Research Center for E-Learning Central China Normal UniversityWuhan430079China Wollongong Joint Institute Central China Normal UniversityWuhan430079China

Generating realistic and synthetic video from text is a highly challenging task due to the multitude of issues involved,including digit deformation,noise interference between frames,blurred output,and the need for temporal coherence across *** this paper,we propose a novel approach for generating coherent videos of moving digits from textual input using a Deep Deconvolutional Generative Adversarial Network(DD-GAN).The DDGAN comprises a Deep Deconvolutional Neural Network(DDNN)as a Generator(G)and a modified Deep Convolutional Neural Network(DCNN)as a Discriminator(D)to ensure temporal coherence between adjacent *** proposed research involves several ***,the input text is fed into a Long Short Term Memory(LSTM)based text encoder and then smoothed using Conditioning Augmentation(CA)techniques to enhance the effectiveness of the Generator(G).Next,using a DDNN to generate video frames by incorporating enhanced text and random noise and modifying a DCNN to act as a Discriminator(D),effectively distinguishing between generated and real *** research evaluates the quality of the generated videos using standard metrics like Inception Score(IS),Fréchet Inception Distance(FID),Fréchet Inception Distance for video(FID2vid),and Generative Adversarial Metric(GAM),along with a human study based on realism,coherence,and *** conducting experiments on Single-Digit Bouncing MNIST GIFs(SBMG),Two-Digit Bouncing MNIST GIFs(TBMG),and a custom dataset of essential mathematics videos with related text,this research demonstrates significant improvements in both metrics and human study results,confirming the effectiveness of *** research also took the exciting challenge of generating preschool math videos from text,handling complex structures,digits,and symbols,and achieving successful *** proposed research demonstrates promising results for generating coherent videos from textual input.

关键词： Generative Adversarial Network(GAN) deconvolutional neural network convolutional neural network Inception Score(IS) temporal coherence Fréchet Inception Distance(FID) Generative Adversarial Metric(GAM)

Analysis of the effect of passive measures on the energy consumption and zero-energy prospects of residential buildings in Pakistan

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Building Simulation 2021年第4期14卷 1325-1342页

作者： muhammad Wasim anwar Zaib Ali Abdullah Javed Emad Ud Din muhammad Sajid School of Mechanical and Manufacturing Engineering National University of Sciences and TechnologyIslamabadPakistan

Climate change can adversely impact the thermal comfort and energy efficiency of the buildings stock. The South Asian countries are particularly vulnerable to the adverse impacts of climate change specially in the form of rising temperatures and increasing frequency of heat waves. The passive building design measures can be useful in mitigating and adapting to the climate change by increasing energy efficiency and reducing greenhouse gas (GHG) emissions. In this study various passive climate change adaptation measures (PCAMs) have been used individually and in form of combinations in order to analyze their impact on the energy efficacy of residential buildings in Pakistan. It has been found that the natural ventilation and front green wall are the most efficient options for reducing the overall energy consumption. By implementation of these PCAMs, cooling demand can be decreased by 27.75% while heating demand can be reduced by 35%. Secondly, the prospect of net zero-energy building and reduced CO2 emissions are also studied. It has been shown that building can achieve net-zero energy on an annual basis at every orientation and it can attain the status of nearly zero-energy building on a monthly basis. Moreover, emitted CO2 can be reduced by 31% by using the renewable energy.

关键词： building energy simulations net zero-energy passive climate adaptation measures climate change energy consumption Pakistan

NewBee: Context-Free Grammar (CFG) of a New Programming Language for Novice Programmers

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Intelligent Automation & Soft Computing 2023年第7期37卷 439-453页

作者： muhammad Aasim Qureshi muhammad Asif Saira anwar Department of Computer Science Bahria University Lahore54000Pakistan Department of Law Science and TechnologyUniversity of Bologna40126Italy Department of Multidisciplinary Engineering Texas A&M UniversityCollege Station77843USA

Learning programming and using programming languages are the essential aspects of computer science *** use programming languages to write their *** computer programs(students or practitioners written)make computers artificially intelligent and perform the tasks needed by the *** these programs,the computer may be visioned as a pointless *** the premise of writing programs is situated with specific programming languages,enormous efforts have been made to develop and create programming ***,each program-ming language is domain-specific and has its nuances,syntax and seman-tics,with specific pros and *** language-specific details,including syntax and semantics,are significant hurdles for novice ***,the instructors of introductory programming courses find these language specificities as the biggest hurdle in students learning,where more focus is on syntax than logic development and actual implementation of the *** the conceptual difficulty of programming languages and novice students’struggles with the language syntax,this paper describes the design and development of a Context-Free Grammar(CFG)of a programming language for the novice,newcomers and students who do not have computer science as their *** to its syntax proximity to daily conversations,this paper hypothesizes that this language will be easy to use and understand by novice *** paper systematically designed the language by identifying themes from various existing programming languages(e.g.,C,Python).Additionally,this paper surveyed computer science experts from industry and academia,where experts self-reported their satisfaction with the newly designed *** results indicate that 93%of the experts reported satisfaction with the NewBee for novice,newcomer and non-Computer Sci-ence(CS)major students.

关键词： Programming language formal language computer language language grammar simple syntax programming language novice programmer

Estimation of soil carbon pools in the forests of Khyber Pakhtunkhwa Province, Pakistan

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Journal of Forestry Research 2020年第6期31卷 2313-2321页

作者： anwar Ali muhammad Irfan Ashraf Saeed Gulzar muhammad Akmal Bilal Ahmad Pakistan Forest Institute Peshawar 25130Pakistan Department of Forestry and Range Management PMAS Arid Agriculture UniversityRawalpindi 46300Pakistan Institute of Soil Science PMAS Arid Agriculture UniversityRawalpindi 46300Pakistan Institute of Agriculture Sciences and Forestry University of SwatSwat 19130Pakistan

Forest soils have high carbon densities compared to other *** carbon sequestration is important to reduce CO 2 concentrations in the *** eff ective climate change mitigation strategy involves limiting the emissions of greenhouse gases from *** Pakhtunkhwa is the most forested province of Pakistan,hosting about one-third of the country’s 4.5×106 ha forest *** organic carbon in the province’s forests was estimated through a fi eld-based study carried out during 2014–17 covering the whole *** was collected from 373 sample plots laid out in diff erent forest types using a stratifi ed cluster sampling *** total quantity of soil organic carbon was estimated at 59.4×106 t with an average of 52.4±5.3 t/*** 69%of the total soil carbon is present in temperate *** broad-leaved and subtropical pine forests constitute 11.4%and 8.8%of the soil carbon stock ***,subalpine and oak forests have respective shares of 5.1%and 5.7%in the soil carbon *** lowest carbon stock(0.1%)was found in dry-tropical thorn *** highest soil carbon density was found in subalpine forests(69.5±7.2 t/ha)followed by moist temperate forests(68.5±6.7 t/ha)and dry temperate forests(60.7±6.5 t/ha).Oak forests have carbon density of 43.4±7.1 t/*** pine,subtropical broad-leaved and dry tropical thorn forests have soil carbon densities of 36.3±3.7,32.8±6.2 and 31.5±3.5 t/ha,*** forests of the Khyber Pakhtunkhwa province have substantial amounts of soil carbon which must be conserved for climate change mitigation and maintenance of sound forest health.

关键词： Soil carbon Carbon sequestration Climate change Carbon sink Forests Khyber Pakhtunkhwa

Numerical investigations of asymmetric flow of a micropolar fluid between two porous disks

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Acta Mechanica Sinica 2009年第6期25卷 787-794页

作者： muhammad Ashraf M.anwar Kamal K.S.Syed Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya University Multan Pakistan Department of Mathematics King Saud University RiyadhSaudi Arabia

Numerical solution is presented for the two- dimensional flow of a micropolar fluid between two porous coaxial disks of different permeability for a range of Reynolds number Re （-300≤ Re 〈 0） and permeability parameter A （1.0≤A ≤2.0）. The main flow is superimposed by the injection at the surfaces of the two disks. Von Karman＇s similarity transformations are used to reduce the governing equations of motion to a set of non-linear coupled ordinary differential equations （ODEs） in dimensionless form. An algorithm based on the finite difference method is employed to solve these ODEs and Richardson＇s extrapolation is used to obtain higher order accuracy. The results indicate that the parameters Re and A have a strong influence on the velocity and microrotation profiles, shear stresses at the disks and the position of the viscous/shear layer. The micropolar material constants cl, c2, c3 have profound effect on microrotation as compared to their effect on streamwise and axial velocity profiles. The results of micropolar fluids are compared with the results for Newtonian fluids.

关键词： Porous disks . Asymmetric flow .Micropolar fluid . Finite differences.Viscous layer

Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases

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Computers, Materials & Continua 2023年第6期75卷 6269-6286页

作者： Wasif Akbar Adbul Mannan Qaisar Shaheen Mohammad Hijji muhammad anwar muhammad Ayaz Department of Computer Science NFC Institute of Engineering and TechnologyMultanPakistan Faculty of Computer Science&Information Technology University of MalayaKuala LumpurMalaysia Department of Computer Science and Information Technology The Islamia University of BahawalpurRahim Yar Khan CampusPunjabPakistan Faculty of Computers and Information Technology University of TabukTabuk47512Saudi Arabia Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Sensor Networks and Cellular Systems(SNCS)research center University of TabukTabuk47512Saudi Arabia

Machine Learning(ML)has changed clinical diagnostic procedures *** in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human *** studies focused on disease prediction but depending on multiple parameters,further investigations are required to upgrade the clinical ***-layered implementation of ML also called Deep Learning(DL)has unfolded new horizons in the field of clinical *** formulates reliable accuracy with big datasets but the reverse is the case with small *** paper proposed a novel method that deals with the issue of less data *** by the regression analysis,the proposed method classifies the data by going through three different *** the first stage,feature representation is converted into probabilities using multiple regression techniques,the second stage grasps the probability conclusions from the previous stage and the third stage fabricates the final *** experiments were carried out on the Cleveland heart disease *** results show significant improvement in classification *** is evident from the comparative results of the paper that the prevailing statistical ML methods are no more stagnant disease prediction techniques in demand in the future.

关键词： Machine learning heart disease cardiac disease deep regression regression learning

Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure

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Computers, Materials & Continua 2023年第3期74卷 5267-5281页

作者： muhammad Javaid Iqbal muhammad Waseem Iqbal muhammad anwar muhammad Murad Khan Abd Jabar Nazimi Mohammad Nazir Ahmad Department of Information Technology The Superior UniversityLahorePakistan Department of Software Engineering The Superior UniversityLahorePakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Department of Computer Science Government College UniversityFaisalabadPakistan Deptment of Oral and Maxillofacial Surgery Faculty of DentistryUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia

The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their *** brain tumour masses occur due to malignant *** tissues must die so that new tissues are allowed to be born and take their *** segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance *** finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and *** could not work for large volume images simultaneously,and many errors occurred due to overwhelming image *** main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning *** research study proposed an automatic model for tumor segmentation in MRI *** proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics Technology Initiative(NIFTI)volumes into the 3D NumPy *** the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated *** the third step,the proposed model uses state-of-the-art Medical Image Computing and Computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour *** of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and *** proposed model is evaluated and gets the Dice Coefficient(DSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively.

关键词： Brain tumour segmentation magnetic resonance images modalities dice coefficient low-grade glioma U-Net

Imbalanced Data Classification Using SVM Based on Improved Simulated Annealing Featuring Synthetic Data Generation and Reduction

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Computers, Materials & Continua 2023年第4期75卷 547-564页

作者： Hussein Ibrahim Hussein Said Amirul anwar muhammad Imran Ahmad Department of Computer Techniques Engineering AlSafwa University CollegeKarbala56001Iraq Faculty of Electronic Engineering&Technology Universiti Malaysia PerlisArau02600PerlisMalaysia

Imbalanced data classification is one of the major problems in machine *** imbalanced dataset typically has significant differences in the number of data samples between its *** most cases,the performance of the machine learning algorithm such as Support Vector Machine(SVM)is affected when dealing with an imbalanced *** classification accuracy is mostly skewed toward the majority class and poor results are exhibited in the prediction of minority-class *** this paper,a hybrid approach combining data pre-processing technique andSVMalgorithm based on improved Simulated Annealing(SA)was ***,the data preprocessing technique which primarily aims at solving the resampling strategy of handling imbalanced datasets was *** this technique,the data were first synthetically generated to equalize the number of samples between classes and followed by a reduction step to remove redundancy and duplicated *** is the training of a balanced dataset using *** this algorithm requires an iterative process to search for the best penalty parameter during training,an improved SA algorithm was proposed for this *** this proposed improvement,a new acceptance criterion for the solution to be accepted in the SA algorithm was introduced to enhance the accuracy of the optimization *** works based on ten publicly available imbalanced datasets have demonstrated higher accuracy in the classification tasks using the proposed approach in comparison with the conventional implementation of *** at an average of 89.65%of accuracy for the binary class classification has demonstrated the good performance of the proposed works.

关键词： Imbalanced data resampling technique data reduction support vector machine simulated annealing