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Exploration of uniform heat flux on the flow and heat transportation of ferrofluids along a smooth plate： Comparative investigation

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International Journal of Biomathematics 2018年第4期11卷 57-75页

作者： muhammad usman muhammad Hamid Syed Tauseef Mohyud Din Asif Waheed Wei Wang School of Mathematical Sciences Peking University Beijing 100871 P. R. China Department of Mathematics Faculty of Sciences HITEC University Taxila Cantt Pakistan Department of Mathematics COMSATS Institute of Information Technology Attock Pakistan

The paper is devoted to a new extension in Gegenbauer wavelet method （GWM） to investigate the transfer of heat and MHD boundary-layer flow of ferrofluids beside a flat plate with velocity slip. A homogenous model study is conducted in which we assumed the heat transfer and forced convective flow of ferrofluids along a flat plate with a uniform wall heat flux. In the direction of transverse to plate, a magnetic field is imposed. Three various magnetic nanoparticle types including Mn-ZnFe204, CoFe204, Fe3O4 are incorporated inside the base fluid. Two types of base fluids （water and kerosene） with bad thermal conductivity as compared to nanoparticles of solid magnetic have been assumed. The mathematical model is tackled via modified Gegenbauer wavelet method （MGWM）. A simulation is accomplished for individual ferrofluid mixture by assuming the prevailing impacts of uniform and slip heat fluxes. The variation of heat transfers and skin friction were also observed at the surface of the plate and we analyzed the better heat transfer for every mixture. Kerosene-based magnetite （Fe304） delivers the better rate of heat transfer at wall due to its association with the kerosene-based Mn-Zn and cobalt ferrites. The slip velocity and magnetic field effects on the temperature, dimensionless velocity, rate of heat transfer and skin friction are examined for various magnetic nanoparticles inside the kerosene oil and water. We observed that the primary influence of magnetic field reduces the dimensionless surface temperature and accelerates the dimensionless velocity as compared to the hydrodynamic case, thus enhancing the rate of heat transfer and skin friction ferrofluids. Moreover, a detailed evaluation of outcomes obtained by MGWM, already published work and numerical RK-4 were found to be in excellent agreement. The error and convergence analysis are presented. Comparison of results,graphical plots, error and convergence analysis reveal the appropriateness of proposed method. T

关键词： Gegenbauer polynomials collocation method ferrofluids heat flux numericalsolution.

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Inception-CNN for Improvement of P300 Detection in Brain-Computer Interface

Inception-CNN for Improvement of P300 Detection in Brain-Com...

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作者： usman muhammad 华南理工大学

学位级别：硕士

P300 detection is a difficult task in the P300 speller-based brain-computer interface（BCI）system due to its low signal-to-noise ratio（SNR）.Previously Convolutional Neural Networks（CNN）have shown prominent results for P300 detection as compared to various machine learning ***,current CNN architectures limit P300 detection accuracy because these models usually only extract single-scale *** Inception module has been proposed by Google Net to improve the classification ability of CNN using a multi-kernel convolutional *** to enhance the P300 detection accuracy,the proposed model in this paper employed an inception module to traditional CNN architecture,which increases the width of a *** proposed P300 detection model can extract multi-scale features using filters of different sizes to efficiently improve the P300 detection ***,the proposed model effectively learns discriminative spatial and temporal features of *** proposed P300 detection model was evaluated on dataset II of the third BCI *** experimental results show the effectiveness of the proposed *** importantly,the character spelling accuracy over early epochs is greatly improved as compared to existing CNN architectures.

关键词：脑-计算机接口卷积神经网络 P300检测

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A Hybrid Duo-Deep Learning and Best Features Based Framework for Action Recognition

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Computers, Materials & Continua 2022年第11期73卷 2555-2576页

作者： muhammad Naeem Akbar Farhan Riaz Ahmed Bilal Awan muhammad Attique Khan usman Tariq Saad Rehman National University of Sciences and Technology(NUST) Islamabad46000Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj 11942Saudi Arabia

Human Action Recognition(HAR)is a current research topic in the field of computer vision that is based on an important application known as video *** in computer vision have introduced various intelligent methods based on deep learning and machine learning,but they still face many challenges such as similarity in various actions and redundant *** proposed a framework for accurate human action recognition(HAR)based on deep learning and an improved features optimization algorithm in this *** deep learning feature extraction to feature classification,the proposed framework includes several critical *** training fine-tuned deep learning models–MobileNet-V2 and Darknet53–the original video frames are *** feature extraction,pre-trained deep models are used,which are fused using the canonical correlation *** that,an improved particle swarm optimization(IPSO)-based algorithm is used to select the best *** that,the selected features were used to classify actions using various *** experimental process was performed on six publicly available datasets such as KTH,UT-Interaction,UCF Sports,Hollywood,IXMAS,and UCF YouTube,which attained an accuracy of 98.3%,98.9%,99.8%,99.6%,98.6%,and 100%,*** comparison with existing techniques,it is observed that the proposed framework achieved improved accuracy.

关键词： Action recognition deep learning features fusion features selection recognition

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Cascade Human Activity Recognition Based on Simple Computations Incorporating Appropriate Prior Knowledge

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Computers, Materials & Continua 2023年第10期77卷 79-96页

作者： Jianguo Wang Kuan Zhang Yuesheng Zhao Xiaoling Wang muhammad Shamrooz aslam School of Biomedical Engineering Capital Medical UniversityBeijing100054China School of Automation Guangxi University of Science and TechnologyLiuzhou545006China

The purpose of Human Activities Recognition(HAR)is to recognize human activities with sensors like accelerometers and *** normal research strategy is to obtain better HAR results by finding more efficient eigenvalues and classification *** this paper,we experimentally validate the HAR process and its various algorithms *** the base of which,it is further proposed that,in addition to the necessary eigenvalues and intelligent algorithms,correct prior knowledge is even more *** prior knowledge mentioned here mainly refers to the physical understanding of the analyzed object,the sampling process,the sampling data,the HAR algorithm,***,a solution is presented under the guidance of right prior knowledge,using Back-Propagation neural networks(BP networks)and simple Convolutional Neural Networks(CNN).The results show that HAR can be achieved with 90%–100%*** analysis shows that intelligent algorithms for pattern recognition and classification problems,typically represented by HAR,require correct prior knowledge to work effectively.

关键词： Human activities recognition prior knowledge physical understanding sensors HAR algorithms

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Hyperchaos and MD5 Based Efficient Color Image Cipher

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Computers, Materials & Continua 2022年第7期72卷 1645-1670页

作者： muhammad Samiullah Waqar aslam Saima Sadiq Arif Mehmood Gyu Sang Choi Department of Computer Science&IT The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

While designing and developing encryption algorithms for text and images,the main focus has remained on *** has led to insufficient attention on the improvement of encryption efficiency,enhancement of hyperchaotic sequence randomness,and dynamic DNA-based *** this regard,a new symmetric block cipher scheme has been *** uses dynamic DNA-based S-box connected with MD5 and a hyperchaotic system to produce confusion and diffusion for encrypting color *** proposed scheme supports various size color *** generates three DNA based Sboxes for substitution namely DNA_1_s-box,DNA_2_s-box and DNA_3_sbox,each of size 16×***,the 4D hyperchaotic system followed by MD5 is employed in a novel way to enhance *** three DNAbased S-boxes are generated from real DNA sequences taken from National Center for Biotechnology Information(NCBI)databases and are dependent on the mean intensity value of an input image,thus effectively introducing content-based ***,Conservative Site-Specific Recombination(CSSR)is applied on the output DNA received from DNA based *** experimental results indicate that the proposed encryption scheme is more secure,robust,and computationally efficient than some of the recently published similar *** computational efficient,our proposed scheme is feasible on many emergent resource-constrained platforms.

关键词： Block cipher substitution permutation diffusion confusion

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A Progressive Approach to Generic Object Detection: A Two-Stage Framework for Image Recognition

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Computers, Materials & Continua 2023年第6期75卷 6351-6373页

作者： muhammad Aamir Ziaur Rahman Waheed Ahmed Abro Uzair aslam Bhatti Zaheer Ahmed Dayo muhammad Ishfaq College of Computer Science Huanggang Normal UniversityHuanggangHubei438000China FAST School of Computing National University of Computer&Emerging Science(NUCES)Karachi CampusKarachi75030Pakistan School of Information and Communication Engineering Hainan UniversityHaikou68000China

Object detection in images has been identified as a critical area of research in computer vision image *** has developed several novel methods for determining an object’s location and category from an ***,there is still room for improvement in terms of detection *** study aims to develop a technique for detecting objects in *** enhance overall detection performance,we considered object detection a two-fold problem,including localization and *** proposed method generates class-independent,high-quality,and precise proposals using an agglomerative clustering *** then combine these proposals with the relevant input image to train our network on convolutional ***,a network refinement module decreases the quantity of generated proposals to produce fewer high-quality candidate ***,revised candidate proposals are sent into the network’s detection process to determine the object *** algorithm’s performance is evaluated using publicly available the PASCAL Visual Object Classes Challenge 2007(VOC2007),VOC2012,and Microsoft Common Objects in Context(MS-COCO)*** only 100 proposals per image at intersection over union((IoU)=0.5 and 0.7),the proposed method attains Detection Recall(DR)rates of(93.17%and 79.35%)and(69.4%and 58.35%),and Mean Average Best Overlap(MABO)values of(79.25%and 62.65%),for the VOC2007 and MS-COCO datasets,***,it achieves a Mean Average Precision(mAP)of(84.7%and 81.5%)on both VOC *** experiment findings reveal that our method exceeds previous approaches in terms of overall detection performance,proving its effectiveness.

关键词： Deep neural network deep learning features agglomerative clustering localizations refinement region of interest(ROI) object detection

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Physiological and biochemical appraisal for mulching and partial rhizosphere drying of cotton

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Journal of Arid Land 2019年第5期11卷 785-794页

作者： Rashid IQBAL muhammad A S RAZA muhammad F SALEEM Imran H KHAN Salman AHMAD muhammad S ZAHEER muhammad U aslam Imran HAIDER Department of Agronomy College of Agriculture and Environmental SciencesIslamia University of BahawalpurBahawalpur 63100Pakistan Department of Agronomy University of AgricultureFaisalabad 38040Pakistan Department of Agronomy Nanjing Agricultural UniversityNanjing 210000China

Water is the main factor for the healthy life of *** of the main negative effects of climate change is the increasing scarcity of water that is lethal for ***,for water deficit regions(arid and semi-arid),drought is the main factor responsible for low production of agriculture,especially for *** efforts have been and are being made to find alternatives to water saving *** study aimed to examine the effects of partial rhizosphere drying(PRD,half of the root system irrigated at one event,and the other half irrigated in the next event,and so on)with and/or without various mulching treatments on physiological and biochemical traits of *** explore this objective,we laid out experiments in completely randomized design with factorial arrangement in the Islamia University of Bahawalpur,Pakistan in *** factors included were four mulching treatments(M0,no mulching;M1,black plastic mulching;M2,wheat straw mulching;and M3,cotton sticks mulching)and two irrigation levels(I0,control(full irrigation);and I1,PRD).Fisher's analysis of variance among means of treatments was compared using least significant difference test at 5% probability *** revealed that the maximum plant height,leaf area,leaf gas exchange(photosynthetic rate and stomata conductance),chlorophyll,proline and total sugar contents,and enzyme activities were higher under M2 than under other three mulching *** for irrigation levels,higher values of plant height,photosynthesis and water related parameters(leaf water potential,leaf osmotic potential,leaf turgor potential,etc.)were *** of total sugar and proline and activities of antioxidant enzymes were significantly higher in PRD-treated plants than in control *** was concluded that combined application of PRD and mulching was more effective than the rest of the treatments used in the *** study can be conducted in the field by applying irrigation water in alternate row

关键词： antioxidant enzymes mulching partial rhizosphere drying photosynthetic rate stomatal conductance

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The outbreak of dengue during the COVID-19 pandemic in Pakistan:The emergence of overlapping crises

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Asian Pacific Journal of Tropical Medicine 2022年第2期15卷 53-55页

作者： muhammad Suleman Rana muhammad usman muhammad Masroor Alam Aamer Ikram muhammad Salman Rani Faryal Massab Umair National Institute of Health IslamabadPakistan Department of Microbiology Quaid-I-Azam University Islamabad Pakistan

COVID-19 pandemic has become a serious public health crisis for developed and developing countries around the *** of February 17,2022,over 420 million cases including 5.8 million deaths have been reported across the globe[1].The first case of COVID-19 in Pakistan was detected on February 26,2020;since then,the toll of confirmed COVID-19 cases reached 1491423 including 29877 deaths as of February 17,2022[1].

关键词： cases Pakistan COV

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Fake News Classification: Past, Current, and Future

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Computers, Materials & Continua 2023年第11期77卷 2225-2249页

作者： muhammad usman Ghani Khan Abid Mehmood Mourad Elhadef Shehzad Ashraf Chaudhry Department of Computer Science University of Engineering and TechnologyLahore54890Pakistan Department of Computer Science&Information Technology Abu Dhabi UniversityAbu Dhabi59911United Arab Emirates Department of Software Engineering Faculty of Engineering and ArchitectureNisantasi UniversityIstanbulTurkey

The proliferation of deluding data such as fake news and phony audits on news web journals,online publications,and internet business apps has been aided by the availability of the web,cell phones,and social *** can quickly fabricate comments and news on social *** most difficult challenge is determining which news is real or ***,tracking down programmed techniques to recognize fake news online is *** an emphasis on false news,this study presents the evolution of artificial intelligence techniques for detecting spurious social media *** study shows past,current,and possible methods that can be used in the future for fake news *** different publicly available datasets containing political news are utilized for performing *** supervised learning algorithms are used,and their results show that conventional Machine Learning(ML)algorithms that were used in the past perform better on shorter text *** contrast,the currently used Recurrent Neural Network(RNN)and transformer-based algorithms perform better on longer ***,a brief comparison of all these techniques is provided,and it concluded that transformers have the potential to revolutionize Natural Language Processing(NLP)methods in the near future.

关键词： Supervised learning algorithms fake news classification online disinformation transformers recurrent neural network(RNN)disinformation transformers recurrent neural network(RNN)

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MagneFi: Multiuser, Multi-Building and Multi-Floor Geomagnetic Field Dataset for Indoor Positioning

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Computers, Materials & Continua 2022年第10期73卷 1747-1768页

作者： Imran Ashraf muhammad usman Ali Soojung Hur Gunzung Kim Yongwan Park Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea Department of Computer Science University of GujratGujrat50700Pakistan

Indoor positioning and localization have emerged as a potential research area during the last few years owing to the wide proliferation of smartphones and the inception of location-attached services for the consumer *** to the importance of precise location information,several positioning technologies are adopted such as Wi-Fi,ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,*** Wi-Fi and magnetic field-based positioning are more attractive concerning the deployment of Wi-Fi access points and ubiquity of magnetic field data,the latter is preferred as it does not require any additional infrastructure as other approaches *** the advantages of magnetic field positioning,comparing the performance of positioning and localization algorithms is very difficult due to the lack of good public datasets that cover various aspects of the magnetic field *** datasets do not provide the data to analyze the impact of device heterogeneity,user heights,and time-specific magnetic field ***,multi-floor and multibuilding data are available for the evaluation of state-of-the-art *** overcome the above-mentioned issues,this study presents multi-user,multidevice,multi-building magnetic field data which is collected over a longer *** dataset contains the data from five different smartphones including Samsung Galaxy S8,S9,A8,LG G6,and LG G7 for three geographically separated *** users including one female and two males collected the data for various path geometry and data collection ***,the data contains the magnetic field samples collected on stairs to test multifloor *** the magnetic field data,the data from inertial measurement unit sensors like the accelerometer,motion sensors,and barometer is provided as well.

关键词： Magnetic field dataset magnetic-field based positioning smartphone sensors benchmark analysis indoor positioning and localization

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