检索结果-南通市图书馆

Depositional and Bio-Sequence Stratigraphic Framework of Late Cretaceous Kawagarh Formation,Kala-Chitta Range,Pakistan:Equivalent of Gurpi Formation(Iran)

在线全文

学校读者我要写书评

暂无评论

Journal of Earth Science 2024年第2期35卷 332-348页

作者： muhammad Awais Bilal Wadood muhammad Ishaq muhammad Bilal Zeeshan Zafar Nasar Khan Aminullah Khan Department of Geology University of SwabiAnbar-SwabiKhyber PakhtunkhwaSwabi23561Pakistan Department of Earth Environmental and Resources SciencesUniversity of Naples FedericoⅡNaples80126Italy State Key Laboratory of Continental Dynamics Department of GeologyNorthwest UniversityXi’an710069China National Centre of Excellence in Geology University of PeshawarPeshawarKhyber Pakhtunkhwa25130Pakistan Department of Geological Engineering School of Earth Sciences and EngineeringXi’an Shiyou UniversityXi’an610500China Department of Petroleum Geology and Engineering School of Earth ResourcesChina University of GeosciencesWuhan430074China Department of Geology University of MalakandDir Lower18800ChakdaraPakistan Department of Earth and Environmental Sciences KU LeuvenLeuven3001Belgium

The present study is focused on evaluation of deep marine pelagic sediments of Late Cretaceous Kawagarh Formation of Kala-Chitta Range in the context of microfacies analysis,paleoenvironmental interpretation,planktonic foraminiferal biostratigraphy,sequence stratigraphy and diversification of species.A total of thirty three rock samples were collected from the measured *** microfacies are interpreted,namely planktonic foraminifera wackestone,planktonic foraminifera mudstone and sandy mudstone indicating low energy depositional environment i.e.,outer *** biostratigraphic studies show plentiful planktonic foraminifera species of Globotruncana,Heterohelix and ***,no association of benthic or siliceous organisms was *** the basis of available species assemblage,a single local planktonic foraminifera biozone i.e.,Globotruncana-Heterohelix-Globotruncanita Assemblage Biozone is *** biozone information is combined with published literature and Lower Santonian to Middle Maastrichtian age has been assigned to the Kawagarh *** trend of species occurrences evinces that species number decreases over time with pulsated rise in the Kawagarh *** Kawagarh Formation carbonates show an overall Transgressive Systems Tract(TST).The Kawagarh Formation of Pakistan evinces analogous characteristics to that of the Late Cretaceous Gurpi Formation of Iran based on the geologic age,outcrop lithology,microfacies,planktonic foraminiferal assemblages,depositional setting and sequence stratigraphy.

关键词： depositional fabric biostratigraphy sequence stratigraphy Late Cretaceous Kawagarh Formation Pakistan Gurpi Formation Iran

Cold plasma-induced effects on electromagnetic wave scattering in waveguides:a mode-matching analysis

在线全文

学校读者我要写书评

暂无评论

Communications in Theoretical Physics 2024年第3期76卷 144-156页

作者： Shahana Rizvi muhammad Afzal Department of Mathematics Capital University of Science and TechnologyIslamabadPakistan

This article presents advancements in an analytical mode-matching technique for studying electromagnetic wave propagation in a parallel-plate metallic rectangular *** technique involves projecting the solution onto basis functions and solving linear algebraic systems to determine scattering *** accuracy of this method is validated via numerical assessments,which involve the reconstruction of matching conditions and conservation *** study highlights the impact of geometric and material variations on reflection and transmission phenomena in the waveguide.

关键词： electromagnetic waves scattering cold plasma metallic conducting mode-matching technique

Predicting Age and Gender in Author Profiling: A Multi-Feature Exploration

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第5期79卷 3333-3353页

作者： Aiman muhammad Arshad Bilal Khan Sadique Ahmad muhammad Asim Department of Computer Science City University of Science and Information TechnologyPeshawar25000Pakistan EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia School of Computer Science and Technology Guangdong University of TechnologyGuangzhou510006China

Author Profiling (AP) is a subsection of digital forensics that focuses on the detection of the author’s personalinformation, such as age, gender, occupation, and education, based on various linguistic features, e.g., stylistic,semantic, and syntactic. The importance of AP lies in various fields, including forensics, security, medicine, andmarketing. In previous studies, many works have been done using different languages, e.g., English, Arabic, French,***, the research on RomanUrdu is not up to the ***, this study focuses on detecting the author’sage and gender based on Roman Urdu text messages. The dataset used in this study is Fire’18-MaponSMS. Thisstudy proposed an ensemble model based on AdaBoostM1 and Random Forest (AMBRF) for AP using multiplelinguistic features that are stylistic, character-based, word-based, and sentence-based. The proposed model iscontrasted with several of the well-known models fromthe literature, including J48-Decision Tree (J48),Na飗e Bays(NB), K Nearest Neighbor (KNN), and Composite Hypercube on Random Projection (CHIRP), NB-Updatable,RF, and AdaboostM1. The overall outcome shows the better performance of the proposed AdaboostM1 withRandom Forest (ABMRF) with an accuracy of 54.2857% for age prediction and 71.1429% for gender predictioncalculated on stylistic features. Regarding word-based features, age and gender were considered in 50.5714% and60%, respectively. On the other hand, KNN and CHIRP show the weakest performance using all the linguisticfeatures for age and gender prediction.

关键词： Digital forensics author profiling for security AdaBoostM1 random forest ensemble learning

Suppression and synchronization of chaos in uncertain time-delay physical system

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Applied Mathematics(A Journal of Chinese Universities) 2024年第3期39卷 416-437页

作者： Israr Ahmad muhammad Shafiq Department of Preparatory Studies Centre University of Technology and Applied SciencesNizwaOman Department of Electrical and Computer Engineering Sultan Qaboos UniversityOman

The mechanical horizontal platform(MHP)system exhibits a rich chaotic *** chaotic MHP system has applications in the earthquake and offshore *** article proposes a robust adaptive continuous control(RACC)*** investigates the control and synchronization of chaos in the uncertain MHP system with time-delay in the presence of unknown state-dependent and time-dependent *** closed-loop system contains most of the nonlinear terms that enhance the complexity of the dynamical system;it improves the efficiency of the *** proposed RACC approach(a)accomplishes faster convergence of the perturbed state variables(synchronization errors)to the desired steady-state,(b)eradicates the effect of unknown state-dependent and time-dependent disturbances,and(c)suppresses undesirable chattering in the feedback control *** paper describes a detailed closed-loop stability analysis based on the Lyapunov-Krasovskii functional theory and Lyapunov stability *** provides parameter adaptation laws that confirm the convergence of the uncertain parameters to some constant *** computer simulation results endorse the theoretical findings and provide a comparative performance.

关键词： chaotic horizontal platform system chaos suppression chaos synchronization robust adaptive control Lyapunov stability theory

A Systematic Literature Review of Machine Learning and Deep Learning Approaches for Spectral Image Classification in Agricultural Applications Using Aerial Photography

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第3期78卷 2967-3000页

作者： Usman Khan muhammad Khalid Khan muhammad Ayub Latif muhammad Naveed muhammad Mansoor alam Salman A.Khan Mazliham Mohd Su’ud College of Computing and Information Sciences Karachi Institute of Economics and TechnologyKarachi75190Pakistan Faculty of Computing and Informatics(FCI) Multimedia UniversityCyberjaya63100Malaysia Faculty of Computing Riphah International UniversityIslamabad46000Pakistan Faculty of Engineering and Information Technology School of Computer ScienceUniversity of Technology SydneySydneyAustralia

Recently,there has been a notable surge of interest in scientific research regarding spectral *** potential of these images to revolutionize the digital photography industry,like aerial photography through Unmanned Aerial Vehicles(UAVs),has captured considerable *** encouraging aspect is their combination with machine learning and deep learning algorithms,which have demonstrated remarkable outcomes in image *** a result of this powerful amalgamation,the adoption of spectral images has experienced exponential growth across various domains,with agriculture being one of the prominent *** paper presents an extensive survey encompassing multispectral and hyperspectral images,focusing on their applications for classification challenges in diverse agricultural areas,including plants,grains,fruits,and *** meticulously examining primary studies,we delve into the specific agricultural domains where multispectral and hyperspectral images have found practical ***,our attention is directed towards utilizing machine learning techniques for effectively classifying hyperspectral images within the agricultural *** findings of our investigation reveal that deep learning and support vector machines have emerged as widely employed methods for hyperspectral image classification in ***,we also shed light on the various issues and limitations of working with spectral *** comprehensive analysis aims to provide valuable insights into the current state of spectral imaging in agriculture and its potential for future advancements.

关键词： Machine learning deep learning unmanned aerial vehicles multi-spectral images image recognition object detection hyperspectral images aerial photography

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam Saleemallah almogadwy muhammad Adnan Khan muhammad Hasnain Azam Khan muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

RUSAS: Roman Urdu Sentiment Analysis System

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第4期79卷 1463-1480页

作者： Kazim Jawad muhammad Ahmad Majdah alvi muhammad Bux alvi Faculty of Computer Science and Engineering Frankfurt University of Applied SciencesFrankfurt am Main60318Germany Technical Writer and Researcher Proteus Technologies LLCIslamabad04405Pakistan Faculty of Engineering The Islamia University of BahawalpurBahawalpur63100Pakistan

Sentiment analysis, the meta field of Natural Language Processing (NLP), attempts to analyze and identify thesentiments in the opinionated text data. People share their judgments, reactions, and feedback on the internetusing various languages. Urdu is one of them, and it is frequently used worldwide. Urdu-speaking people prefer tocommunicate on social media in Roman Urdu (RU), an English scripting style with the Urdu language *** have developed versatile lexical resources for features-rich comprehensive languages, but limitedlinguistic resources are available to facilitate the sentiment classification of Roman Urdu. This effort encompassesextracting subjective expressions in Roman Urdu and determining the implied opinionated text polarity. Theprimary sources of the dataset are Daraz (an e-commerce platform), Google Maps, and the manual effort. Thecontributions of this study include a Bilingual Roman Urdu Language Detector (BRULD) and a Roman UrduSpelling Checker (RUSC). These integrated modules accept the user input, detect the text language, correct thespellings, categorize the sentiments, and return the input sentence’s orientation with a sentiment intensity *** developed system gains strength with each input experience gradually. The results show that the languagedetector gives an accuracy of 97.1% on a close domain dataset, with an overall sentiment classification accuracy of94.3%.

关键词： Roman Urdu sentiment analysis Roman Urdu language detector Roman Urdu spelling checker flask

An indicator model for assessing community resilience to the COVID-19 pandemic and its validation: A case study in Hong Kong

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Safety Science and Resilience 2024年第2期5卷 222-234页

作者： Nan Liao muhammad Nawaz Departnent of Geography Faculty Art and Social SciencesSingapore 65166666Singapore

The COVID-19 outbreak had a significant negative impact on the world,and the fifth wave of COVID-19 in Hong Kong brought a considerable shock to Chinese *** is a growing call for more resilient ***,empirical evidence and validation of modeling studies of resilience indicators for urban community responses to the COVID-19 pandemic still need to be *** this study,a resilience assessment indicator model comprising 4 subsystems,7 indicators,and 12 variables was developed to assess the resilience of Hong Kong communities in response to COVID-19(i.e.,Resilience Index).Furthermore,this study utilized regression models such as geographically weighted regression(GWR)and multiscale GWR(MGWR)to validate the resilience model proposed in this study at the model and variable *** the regression model,the Resilience Index and the individual variables in the resilience model are explanatory variables,and the outcomes of the COVID-19 pandemic(confirmed cases,confirmation rate,discharged cases,discharge rate)are dependent *** results showed that:(i)the resilience of Hong Kong communities to the COvID-19 pandemic was not strong in general and showed some clustered spatial distribution characteristics;(i)the validation results at the model level showed that the Resilience Index did not explain the consequences of the COvID-19 pandemic to a high degree;(ii)the validation results at the variable level showed that the MGWR model was the best at identifying the relationships between explanatory variables and the dependent variable;and(iv)compared with the model-level assessment results,the variable-level assessment explained the consequences of the COvID-19 pandemic better than the model level assessment *** above analysis and the spatial distribution maps of the resilience variables can provide empirically based and targeted insights for policymakers.

关键词： Resilience Community resilience CoVID-19pandemic Resilience assessment indicator model Resilience model validation MGWR

Novel Fractal-Based Features for Low-Power Appliances in Non-Intrusive Load Monitoring

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第7期80卷 507-526页

作者： Anam Mughees muhammad Kamran Department of Electrical Engineering University of Engineering and Technology(UET)Lahore54890Pakistan Department of Electrical Engineering Government College UniversityFaisalabad38000Pakistan Department of Electrical Engineering and Technology Muhammad Nawaz Sharif University of Engineering&Technology(MNS UET)Multan60000Pakistan

Non-intrusive load monitoring is a method that disaggregates the overall energy consumption of a building to estimate the electric power usage and operating status of each appliance *** studies have mostly concentrated on the identification of high-power appliances like HVAC systems while overlooking the existence of low-power ***-power consumer appliances have comparable power consumption patterns,which can complicate the detection task and can be mistaken as *** research tackles the problem of classification of low-power appliances and uses turn-on current transients to extract novel features and develop unique appliance signatures.A hybrid feature extraction method based on mono-fractal and multi-fractal analysis is proposed for identifying low-power *** dimension,Hurst exponent,multifractal spectrum and the Hölder exponents of switching current transient signals are extracted to develop various‘turn-on’appliance signatures for *** classifiers,i.e.,deep neural network,support vector machine,decision trees,and K-nearest neighbours have been optimized using Bayesian optimization and trained using the extracted *** simulated results showed that the proposed method consistently outperforms state-of-the-art feature extraction methods across all optimized classifiers,achieving an accuracy of up to 96%in classifying low-power appliances.

关键词： Nonintrusive load monitoring multi-fractal analysis appliance classification switching transients