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Enhancing Healthcare Data Security and Disease Detection Using Crossover-Based Multilayer Perceptron in Smart Healthcare Systems

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 977-997页

作者： mustufa haider abidi Hisham Alkhalefah Mohamed K.Aboudaif Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box-800Riyadh11421Saudi Arabia

The healthcare data requires accurate disease detection analysis,real-timemonitoring,and advancements to ensure proper treatment for ***,Machine Learning methods are widely utilized in Smart Healthcare Systems(SHS)to extract valuable features fromheterogeneous and high-dimensional healthcare data for predicting various diseases and monitoring patient *** methods are employed across different domains that are susceptible to adversarial attacks,necessitating careful ***,this paper proposes a crossover-based Multilayer Perceptron(CMLP)*** collected samples are pre-processed and fed into the crossover-based multilayer perceptron neural network to detect adversarial attacks on themedical records of *** an attack is detected,healthcare professionals are promptly alerted to prevent data *** paper utilizes two datasets,namely the synthetic dataset and the University of Queensland Vital Signs(UQVS)dataset,from which numerous samples are *** results are conducted to evaluate the performance of the proposed CMLP model,utilizing various performancemeasures such as Recall,Precision,Accuracy,and F1-score to predict patient *** the proposed method with existing approaches,it achieves the highest accuracy,precision,recall,and ***,the proposedmethod achieves a precision of 93%,an accuracy of 97%,an F1-score of 92%,and a recall of 92%.

关键词： Smart healthcare systems multilayer perceptron cybersecurity adversarial attack detection Healthcare 4.0

Unknown Environment Measurement Mapping by Unmanned Aerial Vehicle Using Kalman Filter-Based Low-Cost Estimated Parallel 8-Beam LIDAR

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Computers, Materials & Continua 2024年第9期80卷 4263-4279页

作者： Mohamed Rabik Mohamed Ismail Muthuramalingam Thangaraj Khaja Moiduddin Zeyad Almutairi mustufa haider abidi Department of Mechatronics Engineering SRM Institute of Science and TechnologySRM NagarKattankulathurChengalpattu DistrictTamil Nadu603203India Advanced Manufacturing Institute King Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia

The measurement and mapping of objects in the outer environment have traditionally been conducted using ground-based monitoring systems,as well as *** recently,unmanned aerial vehicles have also been employed for this *** accurate detection and mapping of a target such as buildings,trees,and terrains are of utmost importance in various applications of unmanned aerial vehicles(UAVs),including search and rescue operations,object transportation,object detection,inspection tasks,and mapping ***,the rapid measurement and mapping of the object are not currently achievable due to factors such as the object’s size,the intricate nature of the sites,and the complexity of mapping *** present system introduces a costeffective solution for measurement and mapping by utilizing a small unmanned aerial vehicle(UAV)equipped with an 8-beam Light Detection and Ranging(LiDAR)*** approach offers advantages over traditional methods that rely on expensive cameras and complex algorithm-based *** reflective properties of laser beams have also been *** system provides prompt results in comparison to traditional camerabased surveillance,with minimal latency and the need for complex *** Kalman estimation method demonstrates improved performance in the presence of *** measurement and mapping of external objects have been successfully conducted at varying distances,utilizing different resolutions.

关键词： 8 beam LiDAR UAV measurement mapping Kalman filter

RSS-Based Selective Clustering Technique Using Master Node for WSN

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Computers, Materials & Continua 2021年第12期69卷 3917-3930页

作者： Vikram Rajpoot Vivek Tiwari Akash Saxena Prashant Chaturvedi Dharmendra Singh Rajput Mohammed Alkahtani mustufa haider abidi GLA University MathuraIndia DPSM IIIT Naya RaipurIndia Compucom Institute of Technology&Management JaipurIndia Lakshmi Narain College of Technology BhopalIndia Vellore Institute of Technology Vellore632014India Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia

Wireless sensor networks(WSN)are designed to monitor the physical properties of the target *** received signal strength(RSS)plays a significant role in reducing sensor node power consumption during data *** utilization of RSS values with clustering is required to harvest the energy of each network node to prolong the network life *** paper introduces the RSS-based energy-efficient selective clustering technique using a master node(RESCM)to improve energy utilization using a master *** master node positioned at the center of the network area and base station(BS)is placed outside the network *** cluster head(CH)selection,the node with a high RSS value is more likely to become *** network is divided into segments according to the distance from the master *** nodes near BS or master node transmit their data using direct transmission without the clustering *** simulation results showed that the RESCM method improves the total network lifespan effectively.

关键词： Wireless sensor network received signal strength clustering base station master node

Formability of Materials with Small Tools in Incremental Forming

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Chinese Journal of Mechanical Engineering 2020年第4期33卷 150-158页

作者： Hongyu Wei G.Hussain X.Shi B.B.L Isidore Mohammed Alkahtani mustufa haider abidi College Mechanical&Electrical Engineering Nanjing University of Aeronautics&AstronauticsNanjingPeople’s Republic of China Faculty of Mechanical Engineering GIK Institute of Engineering Sciences&TechnologyTopi 23460Pakistan College of Mechanical Engineering Shanghai University of Engineering ScienceShanghaiPeople’s Republic of China Bradenburg University of Technology CottbusGermany Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh 11421Saudi Arabia Advanced Manufacturing Institute King Saud UniversityRiyadh 11421Saudi Arabia

Single point incremental forming(SPIF)is an innovative sheet forming process with a high economic *** formability in this process can be maximized by executing forming with a tool of specific small radius,regarded as threshold critical *** value has been reported as 2.2 mm for 1 mm thick sheet ***,with a change in the forming conditions specifically in the sheet thickness and step size,the critical radius is likely to alter due to a change in the bending *** main aim of the present study is to undertake this point into account and develop a relatively generic *** study is composed of experimental and numerical *** maximum wall angle(θmax)without sheet fracturing is regarded as sheet formability.A number of sheet materials are formed to fracture and the trends correlating formability with normalized radius(i.e.,R/To where R is the tool-radius and To is the sheet thickness)are *** trends confirm that there is a critical tool-radius(Rc)that maximizes the formability in ***,it is found that the critical radius is not fixed rather it shows dependence on the sheet thickness such that Rc=βTo,whereβvaries from 2.2 to 3.3 as the thickness increases from 1 mm to 3 *** critical radius,however,remains insensitive to variation in step size ranging from 0.3 mm to 0.7 *** is also observed that the selection of tool with R

关键词： Incremental forming Critical tool-radius Formability curve Finite element analysis

Addressing Economic Dispatch Problem with Multiple Fuels Using Oscillatory Particle Swarm Optimization

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Computers, Materials & Continua 2021年第12期69卷 2863-2882页

作者： Jagannath Paramguru Subrat Kumar Barik Ajit Kumar Barisal Gaurav Dhiman Rutvij HJhaveri Mohammed Alkahtani mustufa haider abidi KIIT University BhubaneswarOdishaIndia Department of Electrical Engineering CETBhubaneswarOdishaIndia Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Computer Science&Engineering Pandit Deendayal Petroleum UniversityGandhinagarIndia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Economic dispatch has a significant effect on optimal economical operation in the power systems in industrial revolution 4.0 in terms of considerable savings in *** non-linearity are added to make the fossil fuel-based power systems more *** order to achieve an accurate economical schedule,valve point loading effect,ramp rate constraints,and prohibited operating zones are being considered for realistic *** this paper,an improved,and modified version of conventional particle swarm optimization(PSO),called Oscillatory PSO(OPSO),is devised to provide a cheaper schedule with optimum *** conventional PSO is improved by deriving a mechanism enabling the particle towards the trajectories of oscillatory motion to acquire the entire search space.A set of differential equations is implemented to expose the condition for trajectory motion in *** adaptive inertia weights,this OPSO method provides an optimized cost of generation as compared to the conventional particle swarm optimization and other new meta-heuristic approaches.

关键词： Economic load dispatch valve point loading industry 4.0 prohibited operating zones ramp rate limit oscillatory particle swarm optimization

Classification and Categorization of COVID-19 Outbreak in Pakistan

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Computers, Materials & Continua 2021年第10期69卷 1253-1269页

作者： Amber Ayoub Kainaat Mahboob Abdul Rehman Javed Muhammad Rizwan Thippa Reddy Gadekallu mustufa haider abidi Mohammed Alkahtani Department of Computer Science Kinnaird College for WomenLahore54000Pakistan Department of Cyber Security Air UniversityIslamabadPakistan School of Information Technology and Engineering Vellore Institute of TechnologyTamil NaduIndia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Coronavirus is a potentially fatal disease that normally occurs in mammals and ***,in humans,the virus spreads through aerial droplets of any type of fluid secreted from the body of an infected *** is a family of viruses that is more lethal than other unpremeditated *** December 2019,a new variant,i.e.,a novel coronavirus(COVID-19)developed in Wuhan province,*** January 23,2020,the number of infected individuals has increased rapidly,affecting the health and economies of many countries,including *** objective of this research is to provide a system to classify and categorize the COVID-19 outbreak in Pakistan based on the data collected every day from different regions of *** research also compares the performance of machine learning classifiers(i.e.,Decision Tree(DT),Naive Bayes(NB),Support Vector Machine,and Logistic Regression)on the COVID-19 dataset collected in *** to the experimental results,DT and NB classifiers outperformed the other *** addition,the classified data is categorized by implementing a Bayesian Regularization Artificial Neural Network(BRANN)*** results demonstrate that the BRANN classifier outperforms state-of-the-art classifiers.

关键词： COVID-19 pandemic neural network BRANN machine learning

Deep Neural Networks Based Approach for Battery Life Prediction

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Computers, Materials & Continua 2021年第11期69卷 2599-2615页

作者： Sweta Bhattacharya Praveen Kumar Reddy Maddikunta Iyapparaja Meenakshisundaram Thippa Reddy Gadekallu Sparsh Sharma Mohammed Alkahtani mustufa haider abidi School of Information Technology and Engineering Vellore Institute of TechnologyVelloreIndia Department of Computer Science and Engineering Baba Ghulam Shah Badshah UniversityRajouriIndia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadhSaudi Arabia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadhSaudi Arabia

The Internet of Things(IoT)and related applications have witnessed enormous growth since its *** diversity of connecting devices and relevant applications have enabled the use of IoT devices in every *** the applicability of these applications are predominant,battery life remains to be a major challenge for IoT devices,wherein unreliability and shortened life would make an IoT application completely *** this work,an optimized deep neural networks based model is used to predict the battery life of the IoT *** present study uses the Chicago Park Beach dataset collected from the publicly available data repository for the experimentation of the proposed *** dataset is pre-processed using the attribute mean technique eliminating the missing values and then One-Hot encoding technique is implemented to convert it to numerical *** processed data is normalized using the Standard Scaler *** Flame Optimization(MFO)Algorithm is then implemented for selecting the optimal features in the *** optimal features are finally fed into the DNN model and the results generated are evaluated against the stateof-the-art models,which justify the superiority of the proposed MFO-DNN model.

关键词： Battery life prediction moth flame optimization one-hot encoding standard scaler

Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

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Computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed mustufa haider abidi Abdulrahman Al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： Automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

Analysis of defects in clean fabrication process of friction stir welding

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Transactions of Nonferrous Metals Society of China 2017年第7期27卷 1507-1516页

作者： Noor Zaman KHAN Zahid A.KHAN Arshad Noor SIDDIQUEE Abdulrahman M.AL-AHMARI mustufa H.abidi Department of Mechanical Engineering Jamia Millia Islamia (A Central University) New Delhi PIN-110025 India Princess Fatima Alnijris Research Chair for Advanced Manufacturing Technology Advanced Manufacturing Institute King Saud University Riyadh-11421 Saudi Arabia

Striving for cleaner production is a sought-after manufacturing *** stir welding(FSW)is a joiningtechnique with par excellence and far less invasive to the environment than even best conventional welding *** is energyefficient and free from consumables,affluent and *** is,thus,accepted as a clean welding process that can produceacceptable quality *** suffers from some major challenges of defects of its own kind that subject the process open toimprovements so as to prove itself a reliable production *** study presents a holistic characterization of defects commonlyfound in FSW *** finding of the present study reveals that most defects are caused by inadequate heat generation,impropermaterial movement around the pin and inadequate material consolidation behind the *** amount of heat generation andmaterial stirring depends on several FSW parameters which may lead to the defect formation,if not selected *** resultsreported in this work are derived from sound literature support and *** are made in the form ofcharacteristics of defects such as likelihood of their location,main responsible parameters along with the recommendations forminimizing them.

关键词： clean welding process friction stir welding defect process parameter