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Improving Prediction of Chronic Kidney Disease Using KNN Imputed SMOTE Features and TrioNet Model

Computer Modeling in Engineering & Sciences 2024年第6期139卷 3513-3534页

作者： Nazik Alturki Abdulaziz Altamimi muhammad umer Oumaima Saidani Amal Alshardan Shtwai Alsubai Marwan Omar Imran Ashraf Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department College of Computer Science and Engineering University of Hafr Al-BatinHafarAl-Batin39524Saudi Arabia Department of Computer Science&Information Technology The Islamia University of BahawalpurP.O.Box 63100BahawalpurPakistan Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Information Technology and Management Illinois Institute of TechnologyChicagoIL 60616-3793USA Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Chronic kidney disease(CKD)is a major health concern today,requiring early and accurate *** learning has emerged as a powerful tool for disease detection,and medical professionals are increasingly using ML classifier algorithms to identify CKD *** study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California,UC Irvine Machine Learning *** research introduces TrioNet,an ensemble model combining extreme gradient boosting,random forest,and extra tree classifier,which excels in providing highly accurate predictions for ***,K nearest neighbor(KNN)imputer is utilized to deal withmissing values while synthetic minority oversampling(SMOTE)is used for class-imbalance *** ascertain the efficacy of the proposed model,a comprehensive comparative analysis is conducted with various machine learning *** proposed TrioNet using KNN imputer and SMOTE outperformed other models with 98.97%accuracy for *** in-depth analysis demonstrates the model’s capabilities and underscores its potential as a valuable tool in the diagnosis of CKD.

关键词： Precisionmedicine chronic kidney disease detection SMOTE missing values healthcare KNNimputer ensemble learning

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Efficient and Secure IoT Based Smart Home Automation Using Multi-Model Learning and Blockchain Technology

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3387-3415页

作者： Nazik Alturki Raed Alharthi muhammad umer Oumaima Saidani Amal Alshardan Reemah M.Alhebshi Shtwai Alsubai Ali Kashif Bashir Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia Department of Computer Science and Engineering University of Hafr Al-BatinHafar Al-BatinSaudi Arabia Department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalpurPakistan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUK Woxsen School of Business Woxsen UniversityHyderabadIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

The concept of smart houses has grown in prominence in recent *** challenges linked to smart homes are identification theft,data safety,automated decision-making for IoT-based devices,and the security of the device *** home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical *** paper proposes a smart home system based on ensemble learning of random forest(RF)and convolutional neural networks(CNN)for programmed decision-making tasks,such as categorizing gadgets as“OFF”or“ON”based on their normal routine in *** have integrated emerging blockchain technology to provide secure,decentralized,and trustworthy authentication and recognition of IoT *** system consists of a 5V relay circuit,various sensors,and a Raspberry Pi server and database for managing *** have also developed an Android app that communicates with the server interface through an HTTP web interface and an Apache *** feasibility and efficacy of the proposed smart home automation system have been evaluated in both laboratory and real-time *** is essential to use inexpensive,scalable,and readily available components and technologies in smart home automation ***,we must incorporate a comprehensive security and privacy-centric design that emphasizes risk assessments,such as cyberattacks,hardware security,and other cyber *** trial results support the proposed system and demonstrate its potential for use in everyday life.

关键词： Blockchain Internet of Things(IoT) smart home automation cybersecurity

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Enhancing alkyne semi-hydrogenation through engineering metal-support interactions of Pd on oxides

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Nano Research 2024年第5期17卷 3707-3713页

作者： Yuefeng Wu Xiaotong Lu Pengfei Cui Wenyu Jia Jun Zhou Yuan Wang Hussain Zahid Yuxin Wu muhammad umer Rafique Xiong Yin Baoshan Li Leyu Wang Guolei Xiang State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical TechnologyBeijing 100029China CAS Key Laboratory of Science and Technology on Applied Catalysis Dalian Institute of Chemical PhysicsChinese Academy of SciencesDalian 116023China College of Chemical Engineering Beijing University of Chemical TechnologyBeijing 100029China

Supported Pd catalysts show superior activities for olefin productions from alkynes through semi-hydrogenation reactions,but over-hydrogenation into alkanes highly decreases olefin *** phenylacetylene semi-hydrogenation as a model reaction,here we explore the optimization approaches toward better Pd catalysts for alkyne semi-hydrogenation through investigating support effect and metal-support *** results show that the states of Pd with supports can be tuned by varying oxide reducibility,loading ratios,and *** our system,0.06 wt.%Pd on rutile-TiO_(2) nanorods shows the highest activity owing to the synergistic effects of single-atoms and *** reducibility can change the filling degrees of Pd 4d orbitals through varying interfacial bonding strengths,which further affect catalytic activity and selectivity.

关键词： alkyne semi-hydrogenation support effect metal-support interaction Pd catalyst single-atom catalyst

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Focus on current and emerging treatment options for glioma:A comprehensive review

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World Journal of Clinical Oncology 2024年第4期15卷 482-495页

作者： Brandon Lucke-Wold Burhanuddin Sohail Rangwala muhammad Ashir Shafique Mohammad Arham Siddiq muhammad Saqlain Mustafa Fnu Danish Rana muhammad umer Nasrullah Noor Zainab Abdul Haseeb Department of Neurosurgery University of FloridaGainesvilleFL 32608United States Department of Neurosurgery Jinnah Sindh Medical UniversityKarachi 75510Pakistan Department of Neurosurgery Army Medical CollegeRawalpindi 46000Pakistan

This comprehensive review delves into the current updates and challenges associated with the management of low-grade gliomas(LGG),the predominant primary tumors in the central nervous *** a general incidence rate of 5.81 per 100000,gliomas pose a significant global concern,necessitating advancements in treatment techniques to reduce mortality and *** review places a particular focus on immunotherapies,discussing promising agents such as Zotiraciclib and ***,a CDK9 inhibitor,has demonstrated efficacy in glioblastoma treatment in preclinical and clinical studies,showing its potential as a therapeutic ***,a viral immunotherapy,induces inflammation in glioblastoma and displays positive outcomes in both adult and pediatric *** of immunotherapy extends to Pembrolizumab,Nivolumab,and Entrectinib,revealing the challenges and variabilities in patient *** promising preclinical data,the monoclonal antibody Depatuxizumab has proven ineffective in glioblastoma treatment,emphasizing the critical need to understand resistance *** review also covers the success of radiation therapy in pediatric LGG,with evolving techniques,such as proton therapy,showing potential improvements in patient quality of *** treatment is discussed in the context of achieving a balance between preserving the patient’s quality of life and attaining gross total resection,with the extent of surgical resection significantly influencing the survival *** addition to advancements in cancer vaccine development,this review highlights the evolving landscape of LGG treatment,emphasizing a shift toward personalized and targeted *** research is essential for refining strategies and enhancing outcomes in the management of LGG.

关键词： Low-grade gliomas Monoclonal antibody Lerapolturev Glioblastoma CDK9 inhibitor

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Hydrological response under CMIP6 climate projection in Astore River Basin,Pakistan

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Journal of Mountain Science 2023年第8期20卷 2263-2281页

作者： Zeshan ALI Mudassar IQBAL Ihsan Ullah KHAN muhammad umer MASOOD muhammad umer muhammad Usama Khan LODHI muhammad Atiq Ur Rehman TARIQ Centre of Excellence in Water Resources Engineering University of Engineering and TechnologyLahore 54890Pakistan International Water Management Institute Lahore 53700Pakistan Department of Civil Engineering University of TokyoTokyo 113-8656Japan College of Engineering IT&EnvironmentCharles Darwin UniversityDarwinNT 0810Australia

Climate change strongly influences the available water resources in a watershed due to direct linkage of atmospheric driving forces and changes in watershed hydrological *** how these climatic changes affect watershed hydrology is essential for human society and environmental *** Model Intercomparison Project phase 6(CMIP6)dataset of three GCM's(BCC-CSM2-MR,INM-CM5-0,and MPIESM1-2-HR)with resolution of 100 km has been analyzed to examine the projected changes in temperature and precipitation over the Astore catchment during *** correction method was used to reduce *** this study,statistical significance of trends was performed by using the Man-Kendall ***'s estimator determined the magnitude of the trend on both seasonal and annual scales at Rama Rattu and Astore ***-ESM1-2-HR showed better results with coefficient of determination(COD)ranging from 0.70-0.74 for precipitation and 0.90-0.92 for maximum and minimum temperature at Astore,Rama,and Rattu followed by INM-CM5-0 and *** of British Columbia Watershed model was used to attain the future hydrological series and to analyze the hydrological response of Astore River Basin to climate *** revealed that by the end of the 2070s,average annual precipitation is projected to increase up to 26.55%under the SSP1-2.6,6.91%under SSP2-4.5,and decrease up to 21.62%under the *** also showed considerable variability during summer and *** projected temperature showed an increasing trend that may cause melting of *** projected increase in temperature ranges from-0.66℃ to 0.50℃,0.9℃ to 1.5℃ and 1.18℃ to 2℃ under the scenarios of SSP1-2.6,SSP2-4.5 and SSP5-8.5,*** streamflows presented a slight increase by all *** streamflow was generated under SSP5-8.5 followed by SSP2-4.5 and *** snowmelt and groundwater contributions to streamflow have decreased whereas rainfa

关键词： GCMs UBCWM Astore River Climate Change Upper Indus Basin Bias Correction

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Customer Prioritization for Medical Supply Chain During COVID-19 Pandemic

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Computers, Materials & Continua 2022年第1期70卷 59-72页

作者： Iram Mushtaq muhammad umer muhammad Imran Inzamam Mashood Nasir Ghulam muhammad Mohammad Shorfuzzaman Department of Management Sciences Sir Syed CASE Institute of Technology45230IslamabadPakistan Department of Operation&Supply Chain Management NUST Business SchoolNational University of Sciences&Technology45200IslamabadPakistan Department of Computer Science HITEC University TaxilaTaxilaPakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

During COVID-19,the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their *** study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals,pharmacies,and retail stores as its *** studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of customers.A questionnaire has been developed to collect primary data from pharmaceutical suppliers pertaining to customerselection *** criteria have been prioritized with respect to eigenvalues obtained from Principal Component Analysis and also validated with the experts’domain-related knowledge using Analytical Hierarchy *** potential appeared to be the most important criteria of customer selection followed by trust and service convenience brand loyalty,commitment,brand awareness,brand image,sustainable behavior,and ***,Multi Criteria Decision Analysis has been performed to prioritize the customerselection criteria and customers with respect to selection *** experts with seven and three and ten years of experience have participated in the *** of the study suggest large hospitals,large pharmacies,and small retail stores are the highly preferred ***,findings of prioritization of customer-selection criteria fromboth Principal Component Analysis and Analytical Hierarchy Process are ***,this study considers the experience of three experts to calculate an aggregate score of priorities to reach an effective *** traditional supply chain problems of supplier selection,this study considers a selection

关键词： Pandemic customer prioritization pharmaceutical supply chain principal component analysis multi-criteria decision-making

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Real-Time Safety Helmet Detection Using Yolov5 at Construction Sites

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Intelligent Automation & Soft Computing 2023年第4期36卷 911-927页

作者： Kisaezehra muhammad umer Farooq muhammad Aslam Bhutto Abdul Karim Kazi Department of Computer Science and Information Technology NED University of Engineering&TechnologyKarachi75270Pakistan Department of Civil Engineering NED University of Engineering&TechnologyKarachi75270Pakistan

The construction industry has always remained the economic and social backbone of any country in the world where occupational health and safety(OHS)is of prime *** in other developing countries,this industry pays very little,rather negligible attention to OHS practices in Pakistan,resulting in the occurrence of a wide variety of accidents,mishaps,and near-misses every *** of the major causes of such mishaps is the non-wearing of safety helmets(hard hats)at construction sites where falling objects from a height are *** most cases,this leads to serious brain injuries in people present at the site in general and the workers in *** is one of the leading causes of human fatalities at construction *** the United States,the Occupational Safety and Health Administration(OSHA)requires construction companies through safety laws to ensure the use of well-deﬁned personal protective equipment(PPE).It has long been a problem to ensure the use of PPE because round-the-clock human monitoring is not ***,such monitoring through technological aids or automated tools is very much *** present study describes a systema-tic strategy based on deep learning(DL)models built on the You-Only-Look-Once(YOLOV5)architecture that could be used for monitoring workers’hard hats in *** can indicate whether a worker is wearing a hat or *** proposed system usesﬁve different models of the YOLOV5,namely YOLOV5n,YOLOv5s,YOLOv5 m,YOLOv5l,and YOLOv5x for object detection with the support of PyTorch,involving 7063 *** results of the study show that among the DL models,the YOLOV5x has a high performance of 95.8%in terms of the mAP,while the YOLOV5n has the fastest detection speed of 70.4 frames per second(FPS).The proposed model can be successfully used in practice to recognize the hard hat worn by a worker.

关键词： Object detection computer-vision personal protective equipment(PPE) deep learning industry revolution(IR)4.0 safety helmet detection

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On Riemann-Type Weighted Fractional Operators and Solutions to Cauchy Problems

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Computer Modeling in Engineering & Sciences 2023年第7期136卷 901-919页

作者： muhammad Samraiz muhammad umer Thabet Abdeljawad Saima Naheed Gauhar Rahman Kamal Shah Department of Mathematics University of SargodhaP.O.Box 40100Sargodha40100Pakistan Department of Mathematics and Sciences Prince Sultan UniversityP.O.Box 66833Riyadh11586Saudi Arabia Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Mathematics and Statistics Hazara University MansehraMansehra21300Pakistan Department of Mathematics University of MalakandChakdara Dir(L)KPK18000Pakistan

In this paper,we establish the new forms of Riemann-type fractional integral and derivative *** novel fractional integral operator is proved to be bounded in Lebesgue space and some classical fractional integral and differential operators are obtained as special *** properties of new operators like semi-group,inverse and certain others are discussed and its weighted Laplace transform is *** integro-differential freeelectron laser(FEL)and kinetic equations are *** solutions to these new equations are obtained by using the modified weighted Laplace *** Cauchy problem and a growth model are designed as applications along with graphical ***,the conclusion section indicates future directions to the readers.

关键词： Weighted fractional operators weighted laplace transform integro-differential free-electron laser equation kinetic differ-integral equation

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A Deep Learning Approach for Prediction of Protein Secondary Structure

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Computers, Materials & Continua 2022年第8期72卷 3705-3718页

作者： muhammad Zubair muhammad Kashif Hanif Eatedal Alabdulkreem Yazeed Ghadi muhammad Irfan Khan muhammad umer Sarwar Ayesha Hanif Department of Computer Science Government College UniversityFaisalabadPakistan Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Software Engineering/Computer Science Al Ain UniversityAbu DhabiUnited Arab Emirates

The secondary structure of a protein is critical for establishing a link between the protein primary and tertiary *** this reason,it is important to design methods for accurate protein secondary structure *** of the existing computational techniques for protein structural and functional prediction are based onmachine learning with *** deep learning architectures have already been applied to tackle protein secondary structure prediction *** this study,deep learning based models,i.e.,convolutional neural network and long short-term memory for protein secondary structure prediction were *** input to proposed models is amino acid sequences which were derived from CulledPDB *** tuning with cross validation was employed to attain best parameters for the proposed *** proposed models enables effective processing of amino acids and attain approximately 87.05%and 87.47%Q3 accuracy of protein secondary structure prediction for convolutional neural network and long short-term memory models,respectively.

关键词： Convolutional neural network machine learning protein secondary structure deep learning long short-term memory protein secondary structure prediction

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A Framework of Deep Learning and Selection-Based Breast Cancer Detection from Histopathology Images

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Computer Systems Science & Engineering 2023年第5期45卷 1001-1016页

作者： muhammad Junaid umer muhammad Sharif Majed Alhaisoni Usman Tariq Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadWah CampusWah CanttPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman University(PNU)P.O.BOX 84428Riyadh11671Saudi Arabia College of Computer Engineering and Science Prince Sattam Bin Abdulaziz UniversityAl-Kharaj11942Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

Breast cancer(BC)is a most spreading and deadly cancerous malady which is mostly diagnosed in middle-aged women worldwide and effecting beyond a half-million people every *** BC positive newly diagnosed cases in 2018 reached 2.1 million around the world with a death rate of 11.6%of total *** diagnosis and detection of breast cancer disease with proper treatment may reduce the number of *** gold standard for BC detection is biopsy analysis which needs an expert for correct *** diagnosis of BC is a complex and challenging *** work proposed a deep learning-based(DL)solution for the early detection of this deadly disease from histopathology *** evaluate the robustness of the proposed method a large publically available breast histopathology image database containing a total of 277524 histopathology images is *** proposed automatic diagnosis of BC detection and classification mainly involves three ***,a DL model is proposed for feature ***,the extracted feature vector(FV)is passed to the proposed novel feature selection(FS)framework for the best ***,for the classification of BC into invasive ductal carcinoma(IDC)and normal class different machine learning(ML)algorithms are *** outcomes of the proposed methodology achieved the highest accuracy of 92.7%which shows that the proposed technique can successfully be implemented for BC detection to aid the pathologists in the early and accurate diagnosis of BC.

关键词： Breast cancer deep learning FS IDC ML SVM

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