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Deep Learning Approach for Automatic Cardiovascular Disease Prediction Employing ECG Signals

Computer Modeling in Engineering & Sciences 2023年第11期137卷 1677-1694页

作者： Muhammad Tayyeb Muhammad Umer Khaled Alnowaiser Saima Sadiq Ala’Abdulmajid Eshmawi rizwan majeed Abdullah Mohamed Houbing Song Imran Ashraf Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Science Khwaja Fareed University of Engineering and Information TechnologyRahim Yar KhanPakistan Department of Cybersecurity College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computer Science and Information Technology Universiti Tun Husein OnnMalaysia(UTHM)Bahru80536Malaysia Research Centre Future University in EgyptNew Cairo11745Egypt Department of Information Systems University of MarylandBaltimore CountyBaltimoreMD 21250USA Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-si38541Korea

Cardiovascular problems have become the predominant cause of death worldwide and a rise in the number of patients has been observed ***,electrocardiogram(ECG)data is analyzed by medical experts to determine the cardiac abnormality,which is *** addition,the diagnosis requires experienced medical experts and is ***,automated identification of cardiovascular disease using ECGs is a challenging problem and state-of-the-art performance has been attained by complex deep learning *** study proposes a simple multilayer perceptron(MLP)model for heart disease prediction to reduce computational *** dataset containing averaged signals with window size 10 is used as an *** competing deep learning and machine learning models are used for comparison.K-fold cross-validation is used to validate the *** outcomes reveal that the MLP-based architecture can produce better outcomes than existing approaches with a 94.40%accuracy *** findings of this study show that the proposed system achieves high performance indicating that it has the potential for deployment in a real-world,practical medical environment.

关键词： Cardiovascular disease prediction electrocardiograms deep learning multilayer perceptron

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Coronavirus: A “Mild” Virus Turned Deadly Infection

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Computers, Materials & Continua 2021年第5期67卷 2631-2646页

作者： rizwan Ali Naqvi Muhammad Faheem Mushtaq Natash Ali Mian Muhammad Adnan Khan Atta-ur-Rahman Muhammad Ali Yousaf Muhammad Umair rizwan majeed Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea Department of Information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan School of Computer and Information Technology Beaconhouse National UniversityTarogilLahore53700Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Faculty of Information Technology University of Central PunjabLahore54782Pakistan Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan

Coronaviruses are a family of viruses that can be transmitted from one person to *** strains have only been mild viruses,but the current form,known as coronavirus disease 2019(COVID-19),has become a deadly *** outbreak originated in Wuhan,China,and has since spread *** symptoms of COVID-19 include a dry cough,sore throat,fever,and nasal *** drugs,pathogen–host interaction,and 2 weeks of isolation have been recommended for the treatment of the *** operating procedures,such as the use of face masks,hand sanitizer,handwashing with soap,and social distancing,are also ***,travel bans for cities,states,and countries have been put in place,along with lockdowns to control the *** restrictions,mask use,sanitizer or soap use,and avoidance of touching the face and nose have produced encouraging results,whereas the effectiveness of antibiotics has not been *** results of isolation for the recovery of infected people have also been *** bans and lockdowns have caused a slump in economies,and unemployment has risen sharply,resulting in an increase in mental health cases *** date,vaccines have been developed and are in use in certain countries,but following standard operating procedures remain *** countries following the guidelines can eradicate this *** Zealand was the rst country to eliminate the virus from their territory.

关键词： Coronavirus severe acute respiratory syndrome middle east respiratory syndrome world health organization

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Prediction of Time Series Empowered with a Novel SREKRLS Algorithm

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Computers, Materials & Continua 2021年第5期67卷 1413-1427页

作者： Bilal Shoaib Yasir Javed Muhammad Adnan Khan Fahad Ahmad rizwan majeed Muhammad Saqib Nawaz Muhammad Adeel Ashraf Abid Iqbal Muhammad Idrees School of Computer Science Minhaj University LahoreLahore54000Pakistan Prince Sultan University Riyadh11586Saudi Arabia Department of Computer Science Riphah International University Lahore CampusLahore54000Pakistan Department of Basic Sciences Deanship of Common First YearJouf UniversitySakakaAljouf72341Saudi Arabia Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Computer Science University of Management and TechnologyLahore54770Pakistan PUCIT University of the PunjabLahore54000Pakistan

For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this *** proposed algorithm lends itself towards the parallel implementation as in the FPGA *** the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is *** computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this *** proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its *** the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than *** new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input *** experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm.

关键词： Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm

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Supervised Machine Learning-Based Prediction of COVID-19

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Computers, Materials & Continua 2021年第10期69卷 21-34页

作者： Atta-ur-Rahman Kiran Sultan Iftikhar Naseer rizwan majeed Dhiaa Musleh Mohammed Abdul Salam Gollapalli Sghaier Chabani Nehad Ibrahim Shahan Yamin Siddiqui Muhammad Adnan Khan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of CIT Faculty of Applied StudiesKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Directorate of IT The Islamia University of BahawalpurBahawalpur63100Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Minhaj University LahoreLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan

COVID-19 turned out to be an infectious and life-threatening viral disease,and its swift and overwhelming spread has become one of the greatest challenges for the *** yet,no satisfactory vaccine or medication has been developed that could guarantee its mitigation,though several efforts and trials are *** around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely *** this regard,healthcare experts,researchers and scientists have delved into the investigation of existing as well as new *** situation demands development of a clinical decision support system to equip the medical staff ways to timely detect this *** state-of-the-art research in Artificial intelligence(AI),Machine learning(ML)and cloud computing have encouraged healthcare experts to find effective detection *** study aims to provide a comprehensive review of the role of AI&ML in investigating prediction techniques for the COVID-19.A mathematical model has been formulated to analyze and detect its potential *** proposed model is a cloud-based smart detection algorithm using support vector machine(CSDC-SVM)with cross-fold validation *** experimental results have achieved an accuracy of 98.4%with 15-fold cross-validation *** comparison with similar state-of-the-art methods reveals that the proposed CSDC-SVM model possesses better accuracy and efficiency.

关键词： COVID-19 CSDC-SVM artificial intelligence machine learning cloud computing support vector machine

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Formation of crystalline particles from phase change emulsion： Influence of different parameters

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Chinese Journal of Chemical Engineering 2016年第7期24卷 929-936页

作者： Javed Iqbal Zulfiqar Ali Murid Hussain rizwan Sheikh Khaliq majeed Asad Ullah Khan Joachim Ulrich COMSATS Institute of Information Technology Department of Chemical Engineering Defence Road Off Raiwind Road Lahore Pakistan Martin-Luther-Universitat Halle-Wittenberg Zentrum fur Ingenieurwissenschaften Verfahrenstechnik/TVT D-06099 Halle (Saale) Germany

Solidification or crystallization of phase change emulsion in the form of fine emulsion drops in a direct contact coolant at temperatures below their freezing point was studied. This work is mainly focused on the size and shape of the generated particles from phase change emulsified fats. Size of the particles is the major or key factor being considered during their formation, however, other factors that govern the particle size and shape were also observed. The operating parameters of the process were optimized in order to obtain particles of smaller size ranges in the window of current operating conditions. The crystallization of complex emulsion matrices is very difficult to control in the bulk at desired requirement. Hence, the emulsion drop to particle formation has advantage in comparison with the bulk solidification or crystallization. The main objective of this work is to achieve spherical emulsion particles in a direct contact cooling system. Parameters like: stability, characterization, viscosity, and the effect of different energy inputs were examined. Moreover, the effects of the capillary size, interfacial tension, temperature of the emulsion on the particle size were also monitored.

关键词：结晶颗粒复合乳液物相变化直接接触颗粒大小操作参数操作条件冷却系统

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