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A Machine Learning Approach for Early COVID-19 Symptoms Identification

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Computers, Materials & Continua 2022年第2期70卷 3803-3820页

作者： Omer ali Mohamad Khairi Ishak Muhammad kamran Liaquat Bhatti School of Electrical and Electronic Engineering Universiti Sains Malaysia(USM)Nibong Tebal14300PenangMalaysia Department of Electrical Engineering NFC Institute of Engineering and Technology(NFC IET)Multan60000Pakistan

Symptom identification and early detection are the first steps towards a health condition ***-19 virus causes pneumonialike symptoms such as fever,cough,and shortness of ***-19 contraction tests necessitate extensive clinical protocols in medical *** studies help with the accurate analysis of COVID-19,where the virus has already spread to the lungs in most *** majority of existing supervised machine learning-based disease detection techniques are based on clinical data like x-rays and computerized *** is heavily reliant on a larger clinical study and does not emphasize early symptom *** aim of this study is to investigate anomalies in patient physiological data for early COVID-19 symptoms *** this context,two of the most prevalent symptoms,fever and cough,were examined in a two-fold manner utilizing an unsupervised machine *** examine disease progression,physiological features from a chest-worn device were ***,a Single Vector Activity Index(SVAI)parameter is proposed to monitor the breathing and cough ***,the dataset’s variance is examined using the DBSCAN method for clustering and outlier ***,the model accuracy is evaluated to identify outliers on real-time data based on feature dissimilarities,yielding an overall detection accuracy of 90.34%.

关键词： COVID-19 symptoms identification machine learning dbscan

Deep Learning with a Novel Concoction Loss Function for Identification of Ophthalmic Disease

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Computers, Materials & Continua 2023年第9期76卷 3763-3781页

作者： Sayyid kamran Hussain ali Haider Khan Malek Alrashidi Sajid Iqbal Qazi Mudassar Ilyas kamran Shah Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering Faculty of Computer ScienceLahore Garrison UniversityLahore54000Pakistan Department of Computer Science Applied CollegeUniversity of TabukTabukSaudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl Hofuf31982Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl HofufSaudi Arabia

As ocular computer-aided diagnostic(CAD)tools become more widely accessible,many researchers are developing deep learning(DL)methods to aid in ocular disease(OHD)*** eye diseases like cataracts(CATR),glaucoma(GLU),and age-related macular degeneration(AMD)are the focus of this study,which uses DL to examine their *** imbalance and outliers are widespread in fundus images,which can make it difficult to apply manyDL algorithms to accomplish this analytical *** creation of efficient and reliable DL algorithms is seen to be the key to further enhancing detection *** the analysis of images of the color of the retinal fundus,this study offers a DL model that is combined with a one-of-a-kind concoction loss function(CLF)for the automated identification of *** study presents a combination of focal loss(FL)and correntropy-induced loss functions(CILF)in the proposed DL model to improve the recognition performance of classifiers for biomedical *** is done because of the good generalization and robustness of these two types of losses in addressing complex datasets with class imbalance and *** classification performance of the DL model with our proposed loss function is compared to that of the baseline models using accuracy(ACU),recall(REC),specificity(SPF),Kappa,and area under the receiver operating characteristic curve(AUC)as the evaluation *** testing shows that the method is reliable and efficient.

关键词： Deep learning multi-classification focal loss CNN eye disease

A Genetic Based Leader Election Algorithm for IoT Cloud Data Processing

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Computers, Materials & Continua 2021年第8期68卷 2469-2486页

作者： Samira Kanwal Zeshan Iqbal Aun Irtaza Rashid ali kamran Siddique Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan School of Intelligent Mechatronics Engineering Sejong UniversitySeoulKorea School of Electrical and Computer Engineering Department of Information and Communication TechnologyXiamen University MalaysiaSepang43900Malaysia

In IoT networks,nodes communicate with each other for computational services,data processing,and resource *** of the time huge data is generated at the network edge due to extensive communication between IoT ***,this tidal data is transferred to the cloud data center(CDC)for efficient processing and effective data *** CDC,leader nodes are responsible for higher performance,reliability,deadlock handling,reduced latency,and to provide cost-effective computational services to the ***,the optimal leader selection is a computationally hard problem as several factors like memory,CPU MIPS,and bandwidth,etc.,are needed to be considered while selecting a leader amongst the set of available *** existing approaches for leader selection are monolithic,as they identify the leader nodes without taking the optimal approach for leader ***,for optimal leader node selection,a genetic algorithm(GA)based leader election(GLEA)approach is presented in this *** proposed GLEA uses the available resources to evaluate the candidate nodes during the leader election *** the first phase of the algorithm,the cost of individual nodes,and overall cluster cost is computed on the bases of available *** the second phase,the best computational nodes are selected as the leader nodes by applying the genetic operations against a cost function by considering the available *** GLEA procedure is then compared against the Bees Life Algorithm(BLA).The experimental results show that the proposed scheme outperforms BLA in terms of execution time,SLA Violation,and their utilization with state-of-the-art schemes.

关键词： IoT cloud computing datacenter leader election algorithm machine learning genetic algorithm

A numerical simulation case study of the coastal currents and upwelling in the western Persian Gulf

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Journal of Ocean Engineering and Science 2020年第4期5卷 323-332页

作者： Hesameddin Mehrfar Masoud Torabi Azad kamran Lari Abbas-ali ali-Akbari Bidokhti Department of Natural Resources and Environment Islamic Azad UniversityScience and Research BranchTehranIran Department of Marine Science and Technology Islamic Azad UniversityNorth Tehran BranchTehranIran Institute of Geophysics University of TehranTehranIran

The present study employed COHERENS model as a three-dimensional hydrodynamic model to address the coastal currents in the western Persian Gulf with a horizontal resolution of 2-minutes of latitude and *** obtained results suggested that Iranian northwestward coastal currents developed from January to April and experienced their maximum intensity from June to August when the rate of the surface inflow current increases through the Strait of Hormuz and the stability of the seasonal thermocline becomes gradually *** simulation results reflected that expansions of the thermocline area began by the arrival of the warm *** such circumstances,some stronger coastal currents were generated in *** strong coastal surface current in the vicinity of the western part of Iranian coasts flew southeastward,while the reverse current flew with a northwestern direction in the *** obtained results suggested that a consequence of the influence of salinity flux,especially on the Iranian coasts,the speed of currents *** findings of this study showed that more kinetic energy was accumulated along Iranian ***,the current vectors on Iranian coasts were greater than those on Arabian coasts,which in turn resulted in the creation of the upwelling currents along western Iranian coasts.

关键词： Coastal Currents COHERENS Model Numerical Simulation Persian Gulf(PG) Upwelling

Heat Transfer Enhancement of an Automobile Engine Radiator using ZnO Water Base Nanofluids

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Journal of Thermal Science 2020年第4期29卷 1010-1024页

作者： Muhammad QASIM Muhammad SAJID kamran Muhammad AMMAR Muhammad ali JAMAL Muhammad YASAR JAVAID Department of Mechanical Engineering University of Engineering and TechnologyLahore 54890Pakistan Department of Chemical Engineering Technology Government College UniversityFaisalabad 38000Pakistan Department of Mechanical Engineering Technology Government College UniversityFaisalabad 38000Pakistan

In this research paper, the forced convective heat transfer enhancement of a Suzuki Mehran(VXR) 2016 radiator(heat exchanger) along with pressure drop and friction factor by utilizing Zinc oxide(Zn O) water based nanofluids has been experimentally studied. Three types of nanofluids with different volumetric concentrations of Zn O nanoparticles(0–0.3%) were employed in order to understand its effect on heat transfer enhancement. The experimental setup was completely designed as closely as possible to the car cooling system. The experimentation has been done under laminar flow conditions(186≤Re≤1127) at different fluid volume flow rates(2–12 L/min) and constant fluid inlet temperature(70°C) to the automobile radiator. A maximum enhancement in heat transfer rate, overall heat transfer coefficient and Nusselt number was obtained up to 41%, 50% and 31% by using nanofluid with 0.2% volumetric concentration of nanoparticles respectively. On the other hand, the mean enhancement in pressure drop and friction factor was obtained up to 47% and 46% by using nanofluid with the same volumetric concentration of nanoparticles i.e. 0.2% respectively. The experimental results also revealed that the heat transfer rate, overall heat transfer coefficient and Nusselt number of nanofluids increases by increasing the volume flow rates and volumetric concentration of nanoparticles. However, these thermal performance parameters of nanofluids started to decline when the volumetric concentration of nanoparticles was increased from 0.2% to 0.3%. Furthermore, pressure drop and friction factor of nanofluids increase by increasing the volumetric concentration of nanoparticles, while pressure drop increases and friction factor decreases by increasing the volume flow rate of nanofluids respectively. At the end, the thermal efficiency of automobile radiator with high cooling rates was obtained by using nanofluid with 0.2% volumetric concentration of nanoparticles.

关键词： ZnO nanoparticles heat transfer enhancement thermal efficiency automobile radiator

A numerical analysis on different-generation prototypes of ventricular assist device

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International Journal of Modeling, Simulation, and Scientific Computing 2019年第5期10卷 34-42页

作者： ali Tavakoli Golpaygani kamran Hassani alireza Karimi Amin Nokhbe Zaeim Department of Biomedical Engineering Standard Research Institute KarajIran Department of Biomechanics Science and Research Branch Islamic Azad UniversityTehranIran Department of Mechanical Engineering Kyushu University 744 MotookaNishi-kuFukuoka 819-0395Japan

The ventricular assist device(VAD)assists the patients with heart diseases for limited and prolonged *** device synchronizes with normal heart activities to help foster its ***,its sensitive design requires high *** pumps are the essential part of every VAD which should operate in wide ranges of flow and *** there are various types of VAD under different designs,it is neither practical nor plausible to experimentally/clinically investigate their ***,in the concurrent study,a numerical study was carried out on four different generation prototypes of VAD pumps for reaching an optimum *** computational fluid dynamics(CFD)method,the software derived,showed and streamlined the flow field shear stress both inside the VAD and its ***,the vortices and flow rate-pressure curves were *** results showed that the curved blade pumps operate better compared to that of the straight blade types,concerning the provision of enough pressure and less damage to the red blood *** results have implications not only for comparing different types of VAD designs but also for understanding the resulted shear stresses and pressures as a result of the blade’s structure.

关键词： Pump generation CFD ventricular assist device numerical simulation ventricular blade

A Machine Learning Based Algorithm to Process Partial Shading Effects in PV Arrays

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Computers, Materials & Continua 2021年第7期68卷 29-43页

作者： kamran Sadiq Awan Tahir Mahmood Mohammad Shorfuzzaman Rashid ali Raja Majid Mehmood Department of Electrical Engineering University of Engineering and TechnologyTaxila47080Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Intelligent Mechatronics Engineering Sejong UniversityKorea Department of Information and Communication Technology School of Electrical and Computer EngineeringXiamen University MalaysiaSepang43900Malaysia

Solar energy is a widely used type of renewable *** arrays are used to harvest solar *** major goal,in harvesting the maximum possible power,is to operate the system at its maximum power point(MPP).If the irradiation conditions are uniform,the P-V curve of the PV array has only one peak that is called its *** when the irradiation conditions are non-uniform,the P-V curve has multiple *** peak represents an MPP for a specific irradiation *** highest of all the peaks is called Global Maximum Power Point(GMPP).Under uniform irradiation conditions,there is zero or no partial *** the changing irradiance causes a shading effect which is called Partial *** conventional and soft computing techniques have been in use to harvest solar *** techniques perform well under uniform and weak shading conditions but fail when shading conditions are *** this paper,a new method is proposed which uses Machine Learning based algorithm called Opposition-Based-Learning(OBL)to deal with partial shading *** studies on different cases of partial shading have proven this technique effective in attaining MPP.

关键词： Maximum power point tracking flower pollination algorithm opposition-based-learning flower pollination algorithm hybridized with opposition based learning

Dynamic Response and Deformation Behavior of Kadui-2 Landslide Influenced by Reservoir Impoundment and Rainfall,Baoxing,China

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Journal of Earth Science 2023年第3期34卷 911-923页

作者： Muhammad kamran Xiewen Hu Muhammad Awais Hussain Muhammad Sanaullah Randa ali Kun He Faculty of Geosciences and Environmental Engineering Southwest Jiaotong UniversityChengdu 611756China College of Civil Engineering and Architecture Zhejiang UniversityHangzhou 310058China Department of Civil Engineering Technology National Skills UniversityIslamabadPakistan Institute of Geology Unversity of the PunjabLahore 54590Pakistan

This study focuses on the deformation characteristics of Kadui-2 Landslide by the influence of reservoir filling-drawdown and precipitation.A three-year monitoring project was implemented in order to observe the short/long-term *** slide mass experienced consistent deformation with a maximum cumulative displacement of 331.34 *** on the recorded data of reservoir water level and precipitation during this period,a two-dimensional(2-D)finite element model using Geostudio software was set up for deformation simulation under different conditions to understand the real influence of these triggering factors on *** numerical simulation results are in consistent with monitoring field *** numerical simulation and field monitoring results exhibit that the maximum deformation occurred at the foreside of slumping *** slip surface shows significant creep characteristics decreasing as long-term shear strength reducing *** water level fluctuation is the primary triggering factor to reactivate the landslide mass and has a negative correlation with deformation *** rate increases with the reservoir drawdown and decreases with impoundment *** with reservoir filling-drawdown operation,rainfall has no significant effect on the slide motion of landslide due to limited penetration from the ground surface.

关键词： landslide reservoir water level fluctuation rainfall finite element method cumulative displacement deformation characteristics

Electro-optomechanical switch via tunable bistability and four-wave mixing

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Chinese Physics B 2019年第11期28卷 193-203页

作者： kamran Ullah Department of Physics Quaid-i-Azam University

We investigate the tunable bistable behavior of a hybrid nano-electro-optomechanical system(NEOMS) composed of S-shaped in the presence of two-level atoms, trapped inside a Fabry–Pérot cavity, and driven by a strong driving field and a weak probe field. The bistable behavior of the steady-state photon number and the mechanical steady-state positions are discussed. Further, we tune bistability by tuning all the coupling frequencies involved in the system and amplitude of the driving field. The present study provides the possibility of realization of a controllable optical switch depending on atom-field coupling, optomechanical coupling, electrostatic Coulomb coupling, and threshold power. In addition, we discuss that the non-linear effect of the hybrid NEOMS generates the four-wave mixing(FWM) process. Moreover, we show that the FWM process can be suppressed by the atom-field detuning and cavity-field detuning, which exhibits low photon transmission.

关键词： nano-electro-optomechanics nano-resonators two-level atom optical switch optical bistability four-wave mixing