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Cloud-Based Diabetes Decision Support System Using Machine Learning Fusion

Computers, Materials & Continua 2021年第7期68卷 1341-1357页

作者： Shabib Aftab Saad Alanazi Munir Ahmad Muhammad Adnan Khan Areej Fatima Nouh Sabri Elmitwally School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Riphah School of Computing&Innovation Riphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Faculty of Computers and Articial IntelligenceCairo University12613Egypt

Diabetes mellitus,generally known as diabetes,is one of the most common diseases *** is a metabolic disease characterized by insulin deciency,or glucose(blood sugar)levels that exceed 200 mg/dL(11.1 ml/L)for prolonged periods,and may lead to death if left uncontrolled by medication or insulin *** is categorized into two main types—type 1 and type 2—both of which feature glucose levels above“normal,”dened as 140 mg/*** is triggered by malfunction of the pancreas,which releases insulin,a natural hormone responsible for controlling glucose levels in blood *** and comprehensive analysis of this potentially fatal disease necessitate application of techniques with minimal rates of *** primary purpose of this research study is to assess the potential role of machine learning in predicting a person’s risk of developing ***,research has supported the use of various machine algorithms,such as naïve Bayes,decision trees,and articial neural networks,for early diagnosis of ***,to achieve maximum accuracy and minimal error in diagnostic predictions,there remains an immense need for further research and innovation to improve the machine-learning tools and techniques available to healthcare ***,in this paper,we propose a novel cloud-based machine-learning fusion technique involving synthesis of three machine algorithms and use of fuzzy systems for collective generation of highly accurate nal decisions regarding early diagnosis of diabetes.

关键词： Machine learning fusion articial neural network decision trees naïve Bayes diabetes prediction

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Prediction of Cloud Ranking in a Hyperconverged Cloud Ecosystem Using Machine Learning

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Computers, Materials & Continua 2021年第6期67卷 3129-3141页

作者： Nadia Tabassum Allah Ditta Tahir Alyas Sagheer Abbas Hani Alquhayz Natash Ali Mian Muhammad Adnan Khan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Information Sciences Division of Science&TechnologyUniversity of EducationLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Computer Science NCBA&ELahore54000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia School of Computer and Information Technology Beaconhouse National UniversityTarogilLahore53700Pakistan Faculty of Computing Riphah School of Computing&InnovationRiphah International University Lahore CampusLahore54000Pakistan

Cloud computing is becoming popular technology due to its functional properties and variety of customer-oriented services over the *** design of reliable and high-quality cloud applications requires a strong Quality of Service QoS parameter *** a hyperconverged cloud ecosystem environment,building high-reliability cloud applications is a challenging *** selection of cloud services is based on the QoS parameters that play essential roles in optimizing and improving cloud *** emergence of cloud computing is significantly reshaping the digital ecosystem,and the numerous services offered by cloud service providers are playing a vital role in this *** software-based unified utilities combine storage virtualization,compute virtualization,and network *** availability of the latter has also raised the demand for *** to the diversity of services,the respective quality parameters are also in abundance and need a carefully designed mechanism to compare and identify the critical,common,and impactful *** is also necessary to reconsider the market needs in terms of service requirements and the QoS provided by various *** research provides a machine learning-based mechanism to monitor the QoS in a hyperconverged environment with three core service parameters:service quality,downtime of servers,and outage of cloud services.

关键词： Cloud computing hyperconverged neural network QoS parameter cloud service providers ranking prediction

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Modelling Intelligent Driving Behaviour Using Machine Learning

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Computers, Materials & Continua 2021年第9期68卷 3061-3077页

作者： Qura-Tul-Ain Khan Sagheer Abbas Muhammad Adnan Khan Areej Fatima Saad Alanazi Nouh Sabri Elmitwally School of Computer Science NCBA&ELahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science College of Computer and Information SciencesJouf UniversitySkakaAljouf72341Saudi Arabia Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt

In vehicular systems,driving is considered to be the most complex task,involving many aspects of external sensory skills as well as cognitive *** skills include the estimation of distance and speed,time perception,visual and auditory perception,attention,the capability to drive safely and action-reaction *** intelligence works as an internal mechanism that manages and holds the overall driver’s intelligent *** cognitive capacities constitute the frontiers for generating adaptive behaviour for dynamic *** parameters for understanding intelligent behaviour are knowledge,reasoning,decision making,habit and cognitive *** intelligent behaviour reveals that many of these parameters operate simultaneously to enable drivers to react to current *** changes prompt the parameter values to change,a process which continues unless and until all processes are *** paper model intelligent behaviour by using a‘driver behaviour model’to obtain accurate intelligent driving behaviour *** model works on layering patterns in which hierarchy and coherence are maintained to transfer the data with accuracy from one module to *** patterns constitute the outcome of different modules that collaborate to generate appropriate *** this case,accurate patterns were acquired using ANN static and dynamic non-linear autoregressive approach was used and for further accuracy validation,time-series dynamic backpropagation artificial neural network,multilayer perceptron and random sub-space on real-world data were also applied.

关键词： Machine learning artificial neural network ann time series intelligent behaviour agent

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Vertical Pod Autoscaling in Kubernetes for Elastic Container Collaborative Framework

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Computers, Materials & Continua 2023年第1期74卷 591-606页

作者： Mushtaq Niazi Sagheer Abbas Abdel-Hamid Soliman Tahir Alyas Shazia Asif Tauqeer Faiz School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan School of Digital Technologies and ArtStaffordshire UniversityST42DFUK Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Higher Colleges of Technology Abu DhabiUAE Department of Enterprise Computing Skyline University CollegeSharjahUAE

Kubernetes is an open-source container management tool which automates container deployment,container load balancing and container(de)scaling,including Horizontal Pod Autoscaler(HPA),Vertical Pod Autoscaler(VPA).HPA enables flawless operation,interactively scaling the number of resource units,or pods,without *** Resource Metrics,such as CPU and memory use of host machines and pods,are monitored by *** Computing has emerged as a platform for individuals beside the corporate *** provides cost-effective infrastructure,platform and software services in a shared *** the other hand,the emergence of industry 4.0 brought new challenges for the adaptability and infusion of cloud *** the global work environment is adapting constituents of industry 4.0 in terms of robotics,artificial intelligence and IoT devices,it is becoming eminent that one emerging challenge is collaborative *** of such autonomous mechanism that can develop,manage and operationalize digital resources like CoBots to perform tasks in a distributed and collaborative cloud environment for optimized utilization of resources,ensuring schedule *** schematics are also linked with Bigdata management produced by large scale industry 4.0 *** use cases and simulation results showed a significant improvement in Pod CPU utilization,latency,and throughput over Kubernetes environment.

关键词： Autoscaling query optimization pods kubernetes container orchestration

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Data and Machine Learning Fusion Architecture for Cardiovascular Disease Prediction

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Computers, Materials & Continua 2021年第11期69卷 2717-2731页

作者： Munir Ahmad Majed Alfayad Shabib Aftab Muhammad Adnan Khan Areej Fatima Bilal Shoaib Mohammad Sh.Daoud Nouh Sabri Elmitwally School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan College of Computer and Information Sciences Jouf UniversitySakaka72341Saudi Arabia Department of Computer Science Virtual University of PakistanLahore54000Pakistan Riphah School of Computing&Innovation Riphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Minhaj University LahoreLahore54000Pakistan College of Engineering Al Ain UniversityAbu Dhabi112612UAE Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt

Heart disease,which is also known as cardiovascular disease,includes various conditions that affect the heart and has been considered a major cause of death over the past *** and timely detection of heart disease is the single key factor for appropriate investigation,treatment,and prescription of *** technologies such as fog,cloud,and mobile computing provide substantial support for the diagnosis and prediction of fatal diseases such as diabetes,cancer,and cardiovascular *** computing provides a cost-efficient infrastructure for data processing,storage,and retrieval,with much of the extant research recommending machine learning(ML)algorithms for generating models for sample *** is considered best suited to explore hidden patterns,which is ultimately helpful for analysis and ***,this study combines cloud computing with ML,collecting datasets from different geographical areas and applying fusion techniques to maintain data accuracy and consistency for the ML *** recommended model considered three ML techniques:Artificial Neural Network,Decision Tree,and Naïve ***-time patient data were extracted using the fuzzy-based model stored in the cloud.

关键词： Machine learning fusion cardiovascular disease data fusion fuzzy system disease prediction

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An Optimized Convolution Neural Network Architecture for Paddy Disease Classification

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Computers, Materials & Continua 2022年第6期71卷 6053-6067页

作者： Muhammad Asif Saleem Muhammad Aamir Rosziati Ibrahim Norhalina Senan Tahir Alyas Faculty of Computer Science Universiti Tun Hussein Onn MalaysiaBatu Pahat54000Malaysia School of Electronics Computing and MathematicsUniversity of DerbyDerbyDE221GBUnited Kingdom Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan

Plant disease classification based on digital pictures is *** learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize,identify,and diagnose plant diseases in the previous *** the yield quantity and quality of rice forming is an important cause for the paddy production ***,some diseases that are blocking the improvement in paddy production are considered as an ominous *** Neural Network(CNN)has shown a remarkable performance in solving the early detection of paddy leaf diseases based on its images in the fast-growing era of science and ***,the significant CNN architectures construction is dependent on expertise in a neural network and domain *** approach is time-consuming,and high computational resources are *** this research,we propose a novel method based on Mutant Particle swarm optimization(MUT-PSO)Algorithms to search for an optimum CNN architecture for Paddy leaf disease *** results show that Mutant Particle swarm optimization Convolution Neural Network(MUTPSO-CNN)can find optimumCNNarchitecture that offers better performance than existing hand-crafted CNN architectures in terms of accuracy,precision/recall,and execution time.

关键词： Deep learning optimum CNN architecture particle swarm optimization convolutional neural network parameter optimization

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Fusion-Based Machine Learning Architecture for Heart Disease Prediction

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Computers, Materials & Continua 2021年第5期67卷 2481-2496页

作者： Muhammad Waqas Nadeem Hock Guan Goh Muhammad Adnan Khan Muzammil Hussain Muhammad Faheem Mushtaq Vasaki a/p Ponnusamy Faculty of Information and Communication Technology(FICT) Universiti Tunku Abdul Rahman(UTAR)KamparPerak31900Malaysia Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science School of Systems and TechnologyUniversity of Management and TechnologyLahore54000Pakistan Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan

The contemporary evolution in healthcare technologies plays a considerable and signicant role to improve medical services and save human *** disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes,as numerous people have been suffering from this disease *** attacks occur when the ranges of vital signs such as blood pressure,pulse rate,and body temperature exceed their normal *** efcient diagnosis of heart diseases could play a substantial role in the eld of cardiology,while diagnostic time could be *** has been a key challenge for researchers and medical experts to diagnose heart diseases accurately and ***,machine learning-based techniques are used for the diagnosis with higher accuracy,using datasets compiled from former medical patients’*** recent years,numerous studies have been presented in the literature propose machine learning techniques for diagnosing heart ***,the existing techniques have some limitations in terms of their *** this paper,a novel Support Vector Machine(SVM)based architecture for heart disease prediction,empowered with a fuzzy based decision level fusion,is *** SVMbased architecture has improved the accuracy signicantly as compared to existing solutions,where 96.23%accuracy has been achieved.

关键词： Heart disease machine learning support vector machine fuzzy logic fusion cardiovascular

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QoS Based Cloud Security Evaluation Using Neuro Fuzzy Model

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Computers, Materials & Continua 2022年第1期70卷 1127-1140页

作者： Nadia Tabassum Tahir Alyas Muhammad Hamid Muhammad Saleem Saadia Malik Syeda Binish Zahra Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Statistics and Computer science University of veterinary and animal sciencesLahore54000Pakistan Department of Industrial Engineering Faculty of EngineeringRabighKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology-RabighKing Abdulaziz UniversityJeddah21589Saudi Arabia

Cloud systems are tools and software for cloud computing that are deployed on the Internet or a cloud computing network,and users can use them at any *** assessing and choosing cloud providers,however,customers confront the variety and difficulty of quality of service(QoS).To increase customer retention and engagement success rates,it is critical to research and develops an accurate and objective evaluation *** is the emerging environment for distributed services at various *** to the benefits of this environment,globally cloud is being taken as a standard environment for individuals as well as for the corporate sector as it reduces capital expenditure and provides secure,accessible,and manageable services to all stakeholders but Cloud computing has security challenges,including vulnerability for clients and association acknowledgment,that delay the rapid adoption of computing *** of resources in the Cloud is difficult because resources provide numerous measures of quality of *** this paper,the proposed resource allocation approach is based on attribute QoS Scoring that takes into account parameters the reputation of the asset,task completion time,task completion ratio,and resource *** article is focused on the cloud service’s security,cloud reliability,and could *** this paper,the machine learning algorithm neuro-fuzzy has been used to address the cloud security issues to measure the parameter security and privacy,trust *** findings reveal that the ANFIS-dependent parameters are primarily designed to discern anomalies in cloud security and features output normally yields better results and guarantees data consistency and computational power.

关键词： Cloud computing performance quality of service machine learning neuro-fuzzy

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Low Impedance Fault Identification and Classification Based on Boltzmann Machine Learning for HVDC Transmission Systems

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Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 440-449页

作者： Raheel Muzzammel Ali Raza the Department of Electrical Engineering University of LahoreLahore 54000Pakistan

Identification and classification of DC faults are considered as fundamentals of DC grid protection.A sudden rise of DC fault current must be identified and classified to immediately operate the corresponding interrupting *** this paper,the Boltzmann machine learning(BML)approach is proposed for identification and classification of DC faults using travelling waves generated at fault point in voltage source converter based high-voltage direct current(VSC-HVDC)transmission *** unsupervised way of feature extraction is performed on the frequency spectrum of the travelling *** class logistic regression(BCLR)classifies the HVDC transmission system into faulty and healthy *** proposed technique reduces the time for fault identification and classification because of reduced tagged data with few ***,the faults near or at converter stations are readily identified and *** performance of the proposed technique is assessed via simulations developed in MATLAB/Simulink and tested for pre-fault and post-fault data both at VSC1 and VSC2,***,the proposed technique is supported by analyzing the root mean square error to show practicality and realization with reduced computations.

关键词： Binary class logistic regression(BCLR) Boltzmann machine learning(BML) DC grid protection fault identification and classification voltage source converter based high-voltage direct current(VSC-HVDC)transmission system

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An innovative design of septic tank for wastewater treatment and its performance evaluation： An applicable model for developing countries

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Chinese Journal of Chemical Engineering 2018年第4期26卷 886-891页

作者： Sajjad Haydar Mehwish Anis Gul E Hina Javed Anwar Aziz Mudasar Arbi Institute of Environmental Engineering & Research (IEER) University of Engineering & Technology (UET) Lahore Pakistan university of lahore Lahore Pakistan

A study was carried out to evaluate the treatment efficiency of modified model of septic tank（ST）for the treatment of domestic *** objective was to explore the possibility of increasing the removal efficiency,at household level,thereby reducing cost and treatment burden on city level treatment *** this purpose,a bench scale model of ST was prepared and operated continuously for 78 days at different detention times i.e.,48,24 and 12 h and at two reactor temperatures viz.15℃ and 25℃.Domestic wastewater was fed to the bench scale ST without *** was conducted under two different ***,by installing baffles in the bench scale ST（called Run-1 setup）,and secondly by installing perforated plates between the baffles（called Run-2 setup）.Results demonstrated that Run-2 setup is better than Run-1 *** significantly affects the *** time of 24 h was found ***-2 setup demonstrated a percentage BOD removal of 45%with effluent BOD of 113 mg·L^-1 at 15℃ and 85%removal with effluent BOD of 31 mg·L^-1 at 25℃.It is concluded that if a modified design of ST using Run-2 setup is provided at household level,the effluent coming out of the house will meet the National Environmental Quality Standards（NEQS）when reactor temperature is close to 25℃.Development authorities are suggested to change their by-laws and make modified ST mandatory for all *** may significantly reduce the cost and footprint of city level wastewater treatment plants being planned.

关键词： Wastewater treatment Septic tank Anaerobic baffled reactor

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