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Cardiac Arrhythmia Disease Classication Using LSTM Deep Learning Approach

Computers, Materials & Continua 2021年第4期67卷 427-443页

作者： muhammad Ashfaq khan Yangwoo Kim Department of Information and Communication Engineering Dongguk UniversitySeoul100-715Kore

Many approaches have been tried for the classication of *** to the dynamic nature of electrocardiogram(ECG)signals,it is challenging to use traditional handcrafted techniques,making a machine learning(ML)implementation *** monitoring of cardiac arrhythmia patients can save *** arrhythmia prediction and classication has improved signicantly during the last few *** are a group of conditions in which the electrical activity of the heart is abnormal,either faster or slower than *** is the most frequent cause of death for both men and women every year in the *** paper presents a deep learning(DL)technique for the classication of *** proposed technique makes use of the University of California,Irvine(UCI)repository,which consists of a high-dimensional cardiac arrhythmia dataset of 279 *** this research,our goal was to classify cardiac arrhythmia patients into 16 classes depending on the characteristics of the electrocardiography *** DL approach in the form of long short-term memory(LSTM)is an efcient technique to deal with reduced accuracy due to vanishing and exploding gradients in traditional DL frameworks for big data *** goal of this research was to categorize cardiac arrhythmia patients by developing an efcient intelligent system using the LSTM DL *** approach to arrhythmia classication includes classication algorithms along with noise removal ***,we utilized principal components analysis(PCA)for noise removal,and LSTM for *** hybrid comprehensive arrhythmia classication approach performs better than previous approaches to arrhythmia *** attained a highest classication accuracy of 93.5%with the DL based disease classication system,and outperformed the earlier approaches used for cardiac arrhythmia classication.

关键词： Deep learning machine learning LSTM disease classication arrhythmia

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Strong interfacial charge transfer between hausmannite manganese oxide and alumina for efficient photocatalysis

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Chinese Journal of Chemical Engineering 2021年第5期34卷 147-159页

作者： Aisha Kanwal Shamaila Sajjad Sajjad Ahmed khan Leghari muhammad Naeem khan International Islamic University H-10 IslamabadPakistan Pakistan Institute of Engineering and Applied Sciences Islamabad 44000Pakistan Department of Chemistry Government College of ScienceLahorePakistan

Well crystalline manganese oxide(Mn_(3)O_(4))nanoparticles anchored on gamma alumina(γ-Al_(2)O_(3))have been successfully tailored via a proficient and cost effective chemical process as an efficient material for photo *** indicated the composite formation ofγ-Al_(2)O_(3) and hausmannite structure of Mn_(3)O_(4).SEM and TEM revealed that hetero structure of Mn_(3)O_(4)/γ-Al_(2)O_(3) exhibits an amalgam of aggregated nanoparticles and *** demonstrated the chemical states of binary *** band gap tuning has been performed withγ-Al_(2)O_(3) nanoparticles by assimilating hausmannite Mn_(3)O_(4) particles into flower like microstructure of Al_(2)O_(3).The photoluminescence spectra affirmed the enhancement in charge separation in Mn_(3)O_(4)/γ-Al_(2)O_(3) binary hybrid *** band gap becomes narrow with the increase in concentrations of Mn_(3)O_(4).The narrowing of band gap is concorded with crystalline domains of primary aggregated *** elucidate the mechanism of the photocatalytic activity linear sweep voltammetry was *** results showed that Mn_(3)O_(4)/γ-Al_(2)O_(3) nanocomposite revealed the enhancement in current density as compared to pureγ-Al_(2)O_(3) which confirmed the electron transfer from Mn_(3)O_(4) toγ-Al_(2)O_(3) through the interfacial potential gradient in conduction *** optimum concentration of 6.0%Mn_(3)O_(4)/γ-Al_(2)O_(3) for hybrid structure showed an excellent photocatalytic activity under visible light due to narrow band gap *** degree distribution of Mn_(3)O_(4) nano architects overlying onγ-Al_(2)O_(3) induces a significant synergic effect betweenγ-Al_(2)O_(3) and hausmannite phase of manganese oxide(Mn_(3)O_(4)).This strong interfacial contact betweenγ-Al_(2)O_(3) and Mn_(3)O_(4) endures the quick transfer of photo generated charge carriers across interface.

关键词： Hausmannite Mn_(3)O_(4) Alumina Band gap tuning Interfacial charge transfer Nanomaterials Catalysis

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On Edge Irregular Reflexive Labeling of Categorical Product of Two Paths

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Computer Systems Science & Engineering 2021年第3期36卷 485-492页

作者： muhammad Javed Azhar khan muhammad Ibrahim Ali Ahmad Centre for Advanced Studies in Pure and Applied Mathematics Bahauddin Zakariya UniversityMultanPakistan College of Computer Science and Information Technology Jazan UniversityJazanSaudi Arabia

Among the huge diversity of ideas that show up while studying graph theory,one that has obtained a lot of popularity is the concept of labelings of *** labelings give valuable mathematical models for a wide scope of applications in high technologies(cryptography,astronomy,data security,various coding theory problems,communication networks,etc.).A labeling or a valuation of a graph is any mapping that sends a certain set of graph elements to a certain set of numbers subject to certain *** labeling is a mapping of elements of the graph,i.e.,vertex and for edges to a set of numbers(usually positive integers),called *** the domain is the vertex-set or the edge-set,the labelings are called vertex labelings or edge labelings ***,if the domain is V(G)[E(G)],then the labeling is called total labeling.A reflexive edge irregular k-labeling of graph introduced by Tanna et al.:A total labeling of graph such that for any two different edges ab and a'b'of the graph their weights has wt_(x)(ab)=x(a)+x(ab)+x(b) and wt_(x)(a'b')=x(a')+x(a'b')+x(b') are *** smallest value of k for which such labeling exist is called the reflexive edge strength of the graph and is denoted by res(G).In this paper we have found the exact value of the reflexive edge irregularity strength of the categorical product of two paths (P_(a)×P_(b))for any choice of a≥3 and b≥3.

关键词： Edge irregular reflexive labeling reflexive edge strength categorical product of two paths

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Modelling Insurance Losses with a New Family of Heavy-Tailed Distributions

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Computers, Materials & Continua 2021年第1期66卷 537-550页

作者： muhammad Arif Dost muhammad khan Saima khan Khosa muhammad Aamir Adnan Aslam Zubair Ahmad Wei Gao Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan Department of Statistics Bahauddin Zakariya UniversityMultan60800Pakistan Department of Natural Sciences and Humanities University of Engineering and TechnologyLahore54000Pakistan Department of Statistics Yazd UniversityYazd89175-741Iran School of Information Science and Technology Yunnan Normal UniversityKunming650500China

The actuaries always look for heavy-tailed distributions to model data relevant to business and actuarial risk *** this article,we introduce a new class of heavy-tailed distributions useful for modeling data in financial sciences.A specific sub-model form of our suggested family,named as a new extended heavy-tailed Weibull distribution is examined in *** basic characterizations,including quantile function and raw moments have been *** estimates of the unknown parameters of the new model are obtained via the maximum likelihood estimation *** judge the performance of the maximum likelihood estimators,a simulation analysis is performed in ***,some important actuarial measures such as value at risk and tail value at risk are also computed.A simulation study based on these actuarial measures is conducted to exhibit empirically that the proposed model is *** usefulness of the proposed family is illustrated by means of an application to a heavy-tailed insurance loss data *** practical application shows that the proposed model is more flexible and efficient than the other six competing models including(i)the two-parameter models Weibull,Lomax and Burr-XII distributions(ii)the three-parameter distributions Marshall-Olkin Weibull and exponentiated Weibull distributions,and(iii)a well-known four-parameter Kumaraswamy Weibull distribution.

关键词： Weibull distribution actuarial measures heavy-tailed distributions estimations insurance losses

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Modelling and Simulation of COVID-19 Outbreak Prediction Using Supervised Machine Learning

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Computers, Materials & Continua 2021年第3期66卷 2397-2407页

作者： Rachid Zagrouba muhammad Adnan khan Atta-ur-Rahman muhammad Aamer Saleem muhammad Faheem Mushtaq Abdur Rehman muhammad Farhan khan Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Science Riphah International UniversityLahore CampusLahore54000Pakistan Hamdard Institute of Engineering and Technology Hamdard UniversityIslamabad44000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan School of Computer Science NCBA&ELahore54000Pakistan Department of Forensic Sciences University of Health SciencesLahore54000Pakistan

Novel Coronavirus-19(COVID-19)is a newer type of coronavirus that has not been formally detected in *** is established that this disease often affects people of different age groups,particularly those with body disorders,blood pressure,diabetes,heart problems,or weakened immune *** epidemic of this infection has recently had a huge impact on people around the globe with rising mortality *** levels of mortality are attributed to their transmitting behavior through physical contact between *** is extremely necessary to monitor the transmission of the infection and also to anticipate the early stages of the disease in such a way that the appropriate timing of effective precautionary measures can be *** latest global coronavirus epidemic(COVID-19)has brought new challenges to the scientific *** Intelligence(AI)-motivated methodologies may be useful in predicting the conditions,consequences,and implications of such an *** forecasts may help to monitor and prevent the spread of these *** article proposes a predictive framework incorporating Support Vector Machines(SVM)in the forecasting of a potential outbreak of *** findings indicate that the suggested system outperforms cutting-edge *** method could be used to predict the long-term spread of such an outbreak so that we can implement proactive measures in *** findings of the analyses indicate that the SVM forecasting framework outperformed the Neural Network methods in terms of accuracy and computational *** proposed SVM system model exhibits 98.88%and 96.79%result in terms of accuracy during training and validation respectively.

关键词： Coronavirus outbreak machine learning artificial intelligence

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Image-Based Automatic Energy Meter Reading Using Deep Learning

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Computers, Materials & Continua 2023年第1期74卷 203-216页

作者： muhammad Imran Hafeez Anwar muhammad Tufail Abdullah khan Murad khan Dzati Athiar Ramli Institute of Computer Sciences and Information Technology Faculty of Management and Computer SciencesThe University of AgriculturePeshawarPakistan Department of Electrical and Computer Engineering COMSATS University IslamabadAttock CampusAttock CityPakistan Kuwait College of Science and Technology Kuwait CityKuwait School of Electrical&Electronic Engineering USM Engineering CampusUniversiti Sains MalaysiaPenang14300Malaysia

We propose to perform an image-based framework for electrical energy meter *** aim is to extract the image region that depicts the digits and then recognize them to record the consumed *** the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time ***,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by *** this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and *** image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image *** training and evaluation,the image dataset is annotated to produce the ground truth of all the ***,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the *** proves to be robust against the mentioned image variations compared with the traditional handcrafted *** proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.

关键词： Convolutional neural network object localization machine learning

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Correction:Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space

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Computers, Materials & Continua 2025年第1期82卷 1461-1461页

作者： Mudassir Khalil muhammad Imran Sharif Ahmed Naeem muhammad Umar Chaudhry Hafiz Tayyab Rauf Adham E.Ragab Department of Computer Engineering Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science Kansas State UniversityManhattanKS 66506USA Department of Computer Science University of Management and TechnologyLahore54000Pakistan Independent Researcher BradfordBD80HSUK Industrial Engineering Department Collage of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia

In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir Khalil,muhammad Imran Sharif,Ahmed Naeem,muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham *** Computers,Materials&Continua,2023,Vol.77,No.2,pp.2031–***:10.32604/cmc.2023.043687,URL:https://***/cmc/v77n2/54831,there was an error regarding the affiliation for the author Hafiz Tayyab *** of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,ST42DE,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.

关键词： Deep Code CIELAB

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Gastrointestinal Tract Infections Classification Using Deep Learning

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Computers, Materials & Continua 2021年第12期69卷 3239-3257页

作者： muhammad Ramzan Mudassar Raza muhammad Sharif muhammad Attique khan Yunyoung Nam Department of Computer Science COMSATS University IslamabadWah Campus47040Pakistan Department of Computer Science HITEC University TaxilaTaxila47080Pakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Automatic gastrointestinal(GI)tract disease recognition is an important application of biomedical image ***,microscopic analysis of pathological tissue is used to detect abnormal areas of the GI *** procedure is subjective and results in significant inter-/intraobserver variations in disease ***,a huge frame rate in video endoscopy is an overhead for the pathological findings of gastroenterologists to observe every frame with a detailed ***,there is a huge demand for a reliable computer-aided diagnostic system(CADx)for diagnosing GI tract *** this work,a CADx was proposed for the diagnosis and classification of GI tract diseases.A novel framework is presented where preprocessing(LAB color space)is performed first;then local binary patterns(LBP)or texture and deep learning(inceptionNet,ResNet50,and VGG-16)features are fused serially to improve the prediction of the abnormalities in the GI ***,principal component analysis(PCA),entropy,and minimum redundancy and maximum relevance(mRMR)feature selection methods were analyzed to acquire the optimized characteristics,and various classifiers were trained using the fused ***-source color image datasets(KVASIR,NERTHUS,and stomach ULCER)were used for performance *** study revealed that the subspace discriminant classifier provided an efficient result with 95.02%accuracy on the KVASIR dataset,which proved to be better than the existing state-of-the-art approaches.

关键词： Convolutional neural network feature fusion gastrointestinal tract handcrafted features features selection

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Hydrological response under CMIP6 climate projection in Astore River Basin,Pakistan

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Journal of Mountain Science 2023年第8期20卷 2263-2281页

作者： Zeshan ALI Mudassar IQBAL Ihsan Ullah khan muhammad Umer MASOOD muhammad UMER muhammad Usama khan LODHI muhammad Atiq Ur Rehman TARIQ Centre of Excellence in Water Resources Engineering University of Engineering and TechnologyLahore 54890Pakistan International Water Management Institute Lahore 53700Pakistan Department of Civil Engineering University of TokyoTokyo 113-8656Japan College of Engineering IT&EnvironmentCharles Darwin UniversityDarwinNT 0810Australia

Climate change strongly influences the available water resources in a watershed due to direct linkage of atmospheric driving forces and changes in watershed hydrological *** how these climatic changes affect watershed hydrology is essential for human society and environmental *** Model Intercomparison Project phase 6(CMIP6)dataset of three GCM's(BCC-CSM2-MR,INM-CM5-0,and MPIESM1-2-HR)with resolution of 100 km has been analyzed to examine the projected changes in temperature and precipitation over the Astore catchment during *** correction method was used to reduce *** this study,statistical significance of trends was performed by using the Man-Kendall ***'s estimator determined the magnitude of the trend on both seasonal and annual scales at Rama Rattu and Astore ***-ESM1-2-HR showed better results with coefficient of determination(COD)ranging from 0.70-0.74 for precipitation and 0.90-0.92 for maximum and minimum temperature at Astore,Rama,and Rattu followed by INM-CM5-0 and *** of British Columbia Watershed model was used to attain the future hydrological series and to analyze the hydrological response of Astore River Basin to climate *** revealed that by the end of the 2070s,average annual precipitation is projected to increase up to 26.55%under the SSP1-2.6,6.91%under SSP2-4.5,and decrease up to 21.62%under the *** also showed considerable variability during summer and *** projected temperature showed an increasing trend that may cause melting of *** projected increase in temperature ranges from-0.66℃ to 0.50℃,0.9℃ to 1.5℃ and 1.18℃ to 2℃ under the scenarios of SSP1-2.6,SSP2-4.5 and SSP5-8.5,*** streamflows presented a slight increase by all *** streamflow was generated under SSP5-8.5 followed by SSP2-4.5 and *** snowmelt and groundwater contributions to streamflow have decreased whereas rainfa

关键词： GCMs UBCWM Astore River Climate Change Upper Indus Basin Bias Correction

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Fractional Analysis of Viscous Fluid Flow with Heat and Mass Transfer Over a Flexible Rotating Disk

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Computer Modeling in Engineering & Sciences 2020年第4期123卷 377-400页

作者： muhammad Shuaib muhammad Bilal muhammad Altaf khan Sharaf J.Malebary Department of Mathematics City University of Science and Information TechnologyPeshawarPakistan Institute for Groundwater Studies Faculty of Natural and Agricultural SciencesUniversity of the Free StateBloemfonteinSouth Africa Department of Information Technology Faculty of Computing and Information TechnologyKing Abdulaziz UniversityRabighSaudia Arabia

An unsteady viscous fluid flow with Dufour and Soret effect,which results in heat and mass transfer due to upward and downward motion of flexible rotating disk,has been *** upward or downward motion of non rotating disk results in two dimensional flow,while the vertical action and rotation of the disk results in three dimensional *** using an appropriate transformation the governing equations are transformed into the system of ordinary differential *** system of ordinary differential equations is further converted into first order differential equation by selecting suitable ***,we generalize the model by using the Caputo *** numerical result for the fractional model is presented and validated with Runge Kutta order 4 method for classical *** compared results are presented in Table and *** is concluded that the fractional model is more realistic than that of classical one,because it simulates the fluid behavior at each fractional value rather than the integral values.

关键词： Caputo derivatives similarity transformation RK4 soret effect Dufour effect

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