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An Implementation of Multiscale Line Detection and Mathematical Morphology for Efficient and Precise Blood Vessel Segmentation in Fundus Images

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Computers, Materials & Continua 2024年第5期79卷 2565-2583页

作者： Syed Ayaz Ali shah Aamir shahzad Musaed Alhussein Chuan Meng Goh Khursheed Aurangzeb Tong Boon Tang muhammad Awais Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusAbbottabad22060Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Faculty of Information and Communication Technology University Tunku Abdul RehmanKampar CampusKampar31900Malaysia Centre for Intelligent Signal and Imaging Research University Teknologi PETRONASBandar Seri IskandarPerak32610Malaysia School of Computing Sciences University of East AngliaNorwichNR47TJUK

Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood *** task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different ***,the speed of the retinal vessel segmentation system is of utmost *** the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the *** address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical *** algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)*** experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE ***,our algorithmexhibits competitive performance with state-of-the-art ***,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE *** is worth noting that these results were achieved using Matlab scripts containing multiple *** suggests that the processing time can be further reduced by replacing loops with *** the proposed algorithm can be deployed in real time *** summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.

关键词： Line detector vessel detection localization mathematical morphology image processing

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Bond-Slip Behavior of Steel Bar and Recycled Steel Fibre-Reinforced Concrete

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Journal of Renewable Materials 2024年第1期12卷 167-186页

作者： Ismail shah Jing Li Nauman Khan Hamad R.Almujibah muhammad Mudassar Rehman Ali Raza Yun Peng School of Architecture and Civil Engineering Yunnan Agricultural UniversityKunming650000China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu610041China Yunnan International Joint R&D Center of Smart Agriculture and Water Security Yunnan Agricultural UniversityKunming650201China School of Water Conservancy Yunnan Agricultural UniversityKunming650201China School of Civil Engineering Guizhou UniversityGuiyang550025China Department of Civil Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif City21974Saudi Arabia School of Civil Engineering Zhengzhou UniversityZhengzhou450001China

Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and *** is considered a sustainable material due to its low carbon footprint and environmental friendly *** study examines the key influencing factors that affect the behavior of this material,such as the steel fiber volume ratio,recycled aggregate replacement rate,concrete strength grade,anchorage length,and stirrup *** study investigates the bond failure morphology,bond-slip,and bond strength constitutive relationship of steel fiber recycled *** results show that the addition of steel fibers at 0.5%,1.0%,and 1.5%volume ratios can improve the ultimate bond strength of pull-out specimens by 9.05%,6.94%,and 5.52%,*** replacement rate of recycled aggregate has minimal effect on the typical bond strength of pull-out ***,the ultimate bond strengths of pull-out specimens with concrete strength grades C45 and C60 have improved compared to those with C30 *** specimens with longer anchorage lengths exhibit lower ultimate bond strength,with a reduction of 33.19%and 46.37%for anchorage lengths of 5D and 7D,respectively,compared to those without *** restraint of 1φ8 and 2φ8 improves the ultimate bond strength by 5.29%and 6.90%,*** fibers have a significant effect on the behavior of concrete after it cracks,especially during the stable expansion stage,crack instability expansion stage,and failure stage.

关键词： Recycled coarse aggregates(RCA) steel fiber bonding performance bond-slip environmental challenges

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融合乌尔都语词性序列预测的汉乌神经机器翻译

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计算机工程与科学 2024年第3期46卷 518-524页

作者：陈欢欢王剑 muhammad naeem Ul Hassan 昆明理工大学信息工程与自动化学院云南昆明650500 昆明理工大学云南省人工智能重点实验室云南昆明650500

面向南亚和东南亚的小语种机器翻译,目前已有不少研究团队开展了深入研究,但作为巴基斯坦官方语言的乌尔都语,由于稀缺的数据资源和与汉语之间的巨大差距,有针对性的汉乌机器翻译方法研究非常稀少。针对这种情况,提出了基于Transformer... 详细信息

面向南亚和东南亚的小语种机器翻译,目前已有不少研究团队开展了深入研究,但作为巴基斯坦官方语言的乌尔都语,由于稀缺的数据资源和与汉语之间的巨大差距,有针对性的汉乌机器翻译方法研究非常稀少。针对这种情况,提出了基于Transformer的融合乌尔都语词性序列的汉乌神经机器翻译模型。首先利用Transformer对目标语言乌尔都语的词性序列进行预测,然后将翻译模型的预测结果和词性序列模型的预测结果相结合进行联合预测,从而实现语言知识到翻译模型的融入。在现有小规模汉乌数据集上的实验表明,所提方法在数据集上的BLEU值相较于基准模型提升了0.13,取得了较为明显的效果。

关键词： Transformer 神经机器翻译乌尔都语词性序列

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TMPRSS2 Polymorphism and Its Correlation with SARS-CoV-2 Susceptibility - A Secondary Publication

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Journal of Clinical and Nursing Research 2024年第5期8卷 329-335页

作者： Saleem Awan Anum Siraj Amber Khan Arifa Anwar muhammad naeem Kiani Saira Yahya Department of Biosciences Shaheed Zulfikar Ali Bhutto Institute of Science and Technology(SZABIST)UniversityKarachiPakistan Department of Plant Breeding and Genetics Sindh Agriculture UniversityTandojamPakistan Guangdong Key Laboratory of Biomedical Measurements and Ultrasound Imaging School of Biomedical EngineeringShenzhen University Medical SchoolShenzhen UniversityShenzhen 518060Guangdong ProvinceChina

Background:Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)virus affected more people than SARS-CoV-1 and related *** genetic factors,besides respiratory droplets and direct exposure to the virus,are found highly responsible for transmitting SARS-CoV-2 ***:The objective of this study was to determine the plasma levels of the TMPRSS2 gene and its role in SARS-CoV-2 ***:A total of 100 patients,i.e.50 SARS-CoV-2 positive patients as the case group and 50 SARS-CoV-2 negative samples as the control group,were selected randomly and included in this case-control study to determine the association between TMPRSS2 gene and susceptibility to SARS-CoV-2 infection and severity of coronavirus disease 2019(COVID-19).The TMPRSS2 levels of case and control samples were measured through an enzyme-linked immunosorbent assay(ELISA).Following the genomic DNA extraction,a set of reverse and forward primers of human TMPRSS2 gene primers were used for the amplification of the TMPRSS2 ***:In the control group,the ratio of men to women was more or less the same while in the case group 62%of the population were *** TMPRSS2 level was found to be 4.70±7.7 ng/ml in case samples while it was 4.73±5.7 ng/ml in control ***:The levels of TMPRSS2 in plasma samples of both controls and cases were found to be the same indicating that the entry of SARS-CoV-2 is not dependent on the plasma levels of this protein.

关键词： TMPRSS2 SARS-CoV-2 ACE2 Gene COVID-19 Expression

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Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

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Intelligent Automation & Soft Computing 2024年第3期39卷 545-566页

作者： Asad Raza shahzad Memon muhammad Ali Nizamani Mahmood Hussain shah Dr.AHS Bukhari Postgraduate Centre of Information and Communication Technology Faculty of Engineering and TechnologyUniversity of SindhJamshoro76060Pakistan Newcastle Business School Northumbria UniversityNewcastleNE1UK

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven ***,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the *** signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging ***,there is the need for an IDS which can learn from data and detect new *** Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking *** this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta *** proposed DSNN model was trained and evaluated with the next-generation dataset,TON_*** pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE ***,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble *** experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML *** addition,the model proposed for IDS has been compared with similar *** proposed DSNN achieved better performance metrics than the other *** proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

关键词： Industrial internet of things smart industrial environment cyber-attacks convolutional neural network ensemble learning

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The Influence of Depression on Different Age and Gender Groups in Bahawalpur

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Journal of Clinical and Nursing Research 2024年第7期8卷 196-207页

作者： Mehran Khan muhammad shahbaz Tooba Waris Shoaib Yaseen Iqra Afzal Emaan Khadim Sawera Usman muhammad Ismail shah Sulaiman Aslam Zafar Iqbal Bahawalpur College of Pharmacy BMDC Complex63100PunjabPakistan

In Bahawalpur,a cross-sectional study assessed depression prevalence across age and gender groups,involving 442 participants from diverse socioeconomic backgrounds and *** the PHQ9 questionnaire,84%were found to meet depression *** findings revealed a higher incidence in females(88%)than males(79%),with the greatest disparity among young adults,particularly young women,due to factors like academic pressure and financial *** children had the lowest depression rates(68%),possibly due to better *** individuals exhibited more severe depression,likely related to aging and domestic *** study’s findings highlight a significant variation in depression severity across different demographic groups,with an overall higher incidence in *** research underscores the necessity for targeted mental health resources and interventions tailored to the specific needs of each demographic *** also points to the importance of addressing academic and socioeconomic stressors to mitigate depression,particularly among young *** the study provides valuable insights,it relies on self-reported data,which may introduce ***,future research should include clinical assessments to validate these findings and ensure a more accurate representation of depression within the community.

关键词： Influence Depression Different age Gender groups Bahawalpur

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Enhancing Secure Development in Globally Distributed Software Product Lines: A Machine Learning-Powered Framework for Cyber-Resilient Ecosystems

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Computers, Materials & Continua 2024年第6期79卷 5031-5049页

作者： Marya Iqbal Yaser Hafeez Nabil Almashfi Amjad Alsirhani Faeiz Alserhani Sadia Ali Mamoona Humayun muhammad Jamal University Institute of Information Technology PMAS-Arid Agriculture UniversityRawalpindiPakistan Department of Software Engineering College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Computer Science College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Computer Engineering&Networks College of Computer and Information SciencesJouf UniversityAl Jouf72388Saudi Arabia Department of Information Systems College of Computer and Information SciencesJouf UniversitySakakaAl Jouf72388Saudi Arabia Department of Mathematics Pir Mehr Ali Shah Arid Agriculture UniversityRawalpindiPakistan

Embracing software product lines(SPLs)is pivotal in the dynamic landscape of contemporary software ***,the flexibility and global distribution inherent in modern systems pose significant challenges to managing SPL variability,underscoring the critical importance of robust cybersecurity *** paper advocates for leveraging machine learning(ML)to address variability management issues and fortify the security of *** the context of the broader special issue theme on innovative cybersecurity approaches,our proposed ML-based framework offers an interdisciplinary perspective,blending insights from computing,social sciences,and ***,it employs ML for demand analysis,dynamic feature extraction,and enhanced feature selection in distributed settings,contributing to cyber-resilient *** experiments demonstrate the framework’s superiority,emphasizing its potential to boost productivity and security in *** digital threats evolve,this research catalyzes interdisciplinary collaborations,aligning with the special issue’s goal of breaking down academic barriers to strengthen digital ecosystems against sophisticated attacks while upholding ethics,privacy,and human values.

关键词： Machine Learning variability management cybersecurity digital ecosystems cyber-resilience

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Impact of frailty on endoscopic retrograde cholangiopancreatography outcomes in nonagenarians:A United States national experience

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World Journal of Gastrointestinal Endoscopy 2024年第3期16卷 148-156页

作者： Sanket Dhirubhai Basida Dushyant Singh Dahiya muhammad Nadeem Yousaf Brinda Basida Bhanu Siva Mohan Pinnam Manesh Kumar Gangwani Hassam Ali Sahib Singh Yash R shah Daksh Ahluwalia Mihir Prakash shah Saurabh Chandan Neil R Sharma Shyam Thakkar Department of Internal Medicine University of Missouri-ColumbiaColumbiaMO 65212United States Division of Gastroenterology Hepatology&MotilityThe University of Kansas School of MedicineKansas CityKS 66160United States Division of Gastroenterology and Hepatology University of MissouriColumbiaMO 65212United States Department of Rheumatology Medical College of GeorgiaAugusta UniversityNorth AugustaGA 30912United States Department of Internal Medicine John H.Stroger Hospital of Cook CountyChicagoIL 60612United States Department of Internal Medicine The University of ToledoToledoOH 43606United States Division of Gastroenterology and Hepatology East Carolina University/Brody School of MedicineGreenvilleNC 27858United States Department of Internal Medicine Sinai HospitalBaltimoreMD 21215United States Department of Internal Medicine Trinity Health Oakland/Wayne State UniversityPontiacMI 48341United States Division of Gastroenterology and Hepatology Creighton University School of MedicineOmahaNE 68131United States Division of Interventional Oncology&Surgical Endoscopy GI Oncology Tumor Site TeamParkview Cancer InstituteParkview HealthFort WayneIN 46845United States Section of Gastroenterology&Hepatology West Virginia University School of MedicineMorgantownWV 26505United States

BACKGROUND Endoscopic retrograde cholangiopancreatography(ERCP)is an essential therapeutic tool for biliary and pancreatic *** and elderly patients,especially those aged≥90 years are generally considered a higher-risk population for ERCP-related *** To investigate outcomes of ERCP in the Non-agenarian population(≥90 years)concerning *** This is a cohort study using the 2018-2020 National Readmission *** aged≥90 were identified who underwent ERCP,using the international classification of diseases-10 code with clinical *** Hopkins’s adjusted clinical groups frailty indicator was used to classify patients as frail and *** primary outcome was mortality,and the secondary outcomes were morbidity and the 30 d readmission rate related to *** used univariate and multivariate regression models for *** A total of 9448 patients were admitted for any indications of *** and non-frail patients were 3445(36.46%)and 6003(63.53%)*** for ERCP were Choledocholithiasis(74.84%),Biliary pancreatitis(9.19%),Pancreatico-biliary cancer(7.6%),Biliary stricture(4.84%),and Cholangitis(1.51%).Mortality rates were higher in frail group[adjusted odds ratio(aOR)=1.68,P=0.02].The Intra-procedural complications were insigni-ficant between the two groups which included bleeding(aOR=0.72,P=0.67),accidental punctures/lacerations(aOR=0.77,P=0.5),and mechanical ventilation rates(aOR=1.19,P=0.6).Post-ERCP complication rate was similar for bleeding(aOR=0.72,P=0.41)and post-ERCP pancreatitis(aOR=1.4,P=0.44).Frail patients had a longer length of stay(6.7 d vs 5.5 d)and higher mean total charges of hospitalization($78807 vs$71392)compared to controls(P<0.001).The 30 d all-cause readmission rates between frail and non-frail patients were similar(P=0.96).CONCLUSION There was a significantly higher mortality risk and healthcare burden amongst nonagenarian frail patients undergoing ERCP compared

关键词： Endoscopic retrograde cholangiopancreatography Nonagenarians Frailty Mortality Healthcare burden

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Aggregation operators and CRITIC-VIKOR method for confidence complex q-rung orthopair normal fuzzy information and their applications

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CAAI Transactions on Intelligence Technology 2023年第1期8卷 40-63页

作者： Tahir Mahmood Zeeshan Ali muhammad naeem Department of Mathematics and Statistics International Islamic University IslamabadIslamabadPakistan Umm Al-Qura University MakkahSaudi Arabia

Supply chain management is an essential part of an organisation's sustainable *** the concentration of natural environment,public,and economic influence and feasibility of your suppliers and purchasers is becoming progressively familiar as all industries are moving towards a massive sustainable *** handle such sort of developments in supply chain management the involvement of fuzzy settings and their generalisations is playing an important *** in mind this role,the aim of this study is to analyse the role and involvement of complex q-rung orthopair normal fuzzy(CQRONF)information in supply chain *** major impact of this theory is to analyse the notion of confidence CQRONF weighted averaging,confidence CQRONF ordered weighted averaging,confidence CQRONF hybrid averaging,confidence CQRONF weighted geometric,confidence CQRONF ordered weighted geometric,confidence CQRONF hybrid geometric operators and try to diagnose various properties and ***,with the help of the CRITIC and VIKOR models,we diagnosed the novel theory of the CQRONF-CRITIC-VIKOR model to check the sensitivity analysis of the initiated ***,in the availability of diagnosed operators,we constructed a multi-attribute decision-making tool for finding a beneficial sustainable supplier to handle complex ***,the initiated operator's efficiency is proved by comparative analysis.

关键词： averaging/geometric aggregation operators complex q-rung orthopair normal fuzzy information confidence levels strategic decision-making methods

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A Double-Branch Xception Architecture for Acute Hemorrhage Detection and Subtype Classification

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Computers, Materials & Continua 2023年第9期76卷 3727-3744页

作者： muhammad naeem Akram muhammad Usman Yaseen muhammad Waqar muhammad Imran Aftab Hussain Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Software Engineering Capital University of Science&TechnologyIslamabad44000Pakistan

This study presents a deep learning model for efficient intracranial hemorrhage(ICH)detection and subtype classification on non-contrast head computed tomography(CT)*** refers to bleeding in the skull,leading to the most critical life-threatening health condition requiring rapid and accurate *** is classified as intra-axial hemorrhage(intraventricular,intraparenchymal)and extra-axial hemorrhage(subdural,epidural,subarachnoid)based on the bleeding location inside the *** computer-aided diagnoses(CAD)-based schemes have been proposed for ICH detection and classification at both slice and scan ***,these approaches performonly binary classification and suffer from a large number of parameters,which increase storage ***,the accuracy of brain hemorrhage detection in existing models is significantly low for medically critical *** overcome these problems,a fast and efficient system for the automatic detection of ICH is *** designed a double-branch model based on xception architecture that extracts spatial and instant features,concatenates them,and creates the 3D spatial context(common feature vectors)fed to a decision tree classifier for final *** data employed for the experimentation was gathered during the 2019 Radiologist Society of North America(RSNA)brain hemorrhage detection *** model outperformed benchmark models and achieved better accuracy in intraventricular(99.49%),subarachnoid(99.49%),intraparenchymal(99.10%),and subdural(98.09%)categories,thereby justifying the performance of the proposed double-branch xception architecture for ICH detection and classification.

关键词： Computed tomography convolutional neural networks intracranial hemorrhage xception architecture

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