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Sentiment Analysis of Low-Resource Language Literature Using Data Processing and Deep Learning

Computers, Materials & Continua 2024年第4期79卷 713-733页

作者： Aizaz Ali maqbool khan.khalil khan.rehan ullah khan.abdulrahman aloraini Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan Software Competence Center Hagenberg Softwarepark 32aHagenberg4232Austria Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstana010000Kazakhstan Department of Information Technology College of ComputerQassim UniversityP.O.Box 1162BuraydahSaudi Arabia

Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse *** numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiv

关键词： Urdu sentiment analysis convolutional neural networks recurrent neural network deep learning natural language processing neural networks

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Design of Machine Learning Based Smart Irrigation System for Precision Agriculture

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Computers, Materials & Continua 2022年第7期72卷 109-124页

作者： khalil Ibrahim Mohammad Abuzanouneh Fahd N.Al-Wesabi Amani abdulrahman Albraikan Mesfer Al Duhayyim M.Al-Shabi Anwer Mustafa Hilal Manar Ahmed Hamza Abu Sarwar Zamani K.Muthulakshmi Department of Information Technology College of ComputerQassim UniversityAl-Bukairiyah52571Saudi Arabia Department of Computer Science King Khalid UniversityMuhayel Aseer62529Saudi Arabia&Faculty of Computer and ITSana’a UniversitySana’a61101Yemen Department of Computer Science College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11564Saudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Management Information System College of Business and AdministrativeTaibah UniversityMedina42353Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Department of Electronics and Communication Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India

Agriculture 4.0,as the future of farming technology,comprises numerous key enabling technologies towards sustainable *** use of state-of-the-art technologies,such as the Internet of Things,transform traditional cultivation practices,like irrigation,to modern solutions of precision *** achieve effectivewater resource usage and automated irrigation in precision agriculture,recent technologies like machine learning(ML)can be *** this motivation,this paper design an IoT andML enabled smart irrigation system(IoTML-SIS)for precision *** proposed IoTML-SIS technique allows to sense the parameters of the farmland and make appropriate decisions for *** proposed IoTML-SIS model involves different IoT based sensors for soil moisture,humidity,temperature sensor,and ***,the sensed data are transmitted to the cloud server for processing and decision ***,artificial algae algorithm(AAA)with least squares-support vector machine(LS-SVM)model is employed for the classification process to determine the need for ***,the AAA is applied to optimally tune the parameters involved in the LS-SVM model,and thereby the classification efficiency is significantly *** performance validation of the proposed IoTML-SIS technique ensured better performance over the compared methods with the maximum accuracy of 0.975.

关键词： Automatic irrigation precision agriculture smart farming machine learning cloud computing decision making internet of things

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Unique Solution of Integral Equations via Intuitionistic Extended Fuzzy b-Metric-Like Spaces

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Computer Modeling in Engineering & Sciences 2023年第4期135卷 109-131页

作者： Naeem Saleem khalil Javed Fahim Uddin Umar Ishtiaq khalil Ahmed Thabet Abdeljawad Manar A.Alqudah Department of Mathematics University of Management and TechnologyLahore54770Pakistan Department of Math&Stats International Islamic University IslamabadIslamabad44000Pakistan Abdus Salam School of Mathematical Sciences Government College UniversityLahore54600Pakistan Office of Research Innovation and CommercializationUniversity of Management and TechnologyLahore54770Pakistan Department of Mathematics and Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Medical Research China Medical UniversityTaichung40402Taiwan Department of Mathematical Sciences Faculty of SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

In this manuscript,our goal is to introduce the notion of intuitionistic extended fuzzy b-metric-like *** establish some fixed point theorems in this ***,we plot some graphs of an example of obtained result for better *** use the concepts of continuous triangular norms and continuous triangular conorms in an intuitionistic fuzzy metric-like *** norms are used to generalize with the probability distribution of triangle inequality in metric space *** conorms are known as dual operations of triangular *** obtained results boost the approaches of existing ones in the literature and are supported by some examples and applications.

关键词： Fixed point extended fuzzy b-metric like space intuitionistic extended fuzzy b-metric-like space integral equation

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Dose-dependent relationship between serum metformin levels and glycemic control, insulin resistance and leptin levels in females newly diagnosed with type 2 diabetes mellitus

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Journal of Diabetes Mellitus 2012年第2期2卷 179-185页

作者： Kadhim Ali Kadhim Dowser khalil Ismael Ban Hoshi Khalaf Khalid Ibrahim Hussein Munaf Hashim Zalzala Saad abdulrahman Hussain Department of Pharmacology and Therapeutics College of Pharmacy Al-Mustansriya University Baghdad Iraq Departments of Pharmacology and Toxicology College of Pharmacy University of Baghdad Baghdad Iraq Specialized Center for Endocrinology and Diabetes Baghdad Iraq

Despite the extensive clinical experience with the use of metformin worldwide, no formal dose-ranging study has been conducted because the current dosing strategy of metformin was determined empirically, rather than by an understanding of its dose-response relationship in patients with type 2 diabetes. The present study was designed to evaluate the correlation between serum metformin levels and glycemic control, insulin resistance and leptin levels in females newly diagnosed with type 2 diabetes. Sixty type 2 diabetic females were recruited for the study and were allocated into 3 groups;each receiving metformin 1000, 1500 and 2000 mg/day respectively for 3 months. Blood samples withdrawn from each patient at zero time and after 3 months is used to evaluate serum levels of HbA1c, glucose, leptin and insulin, in addition, the measurement of serum level of metformin in blood after 3 months by HPLC. The results demonstrated that all the treated groups with different doses of metformin showed significant improve in all parameters;the use of increased metformin doses was only correlated with plasma leptin levels in the highest dose. In conclusion, serum metformin levels are not good predictors for correlating improvement in clinical and biochemical parameters with increasing the dose in newly diagnosed non-insulin resistant females with type 2 diabetes.

关键词： Type2 Diabetes Mellitus Leptin BMI Serum Metformin Glycemic Control

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Irritable Bowel Syndrome and Dietary Habits in Northern Saudi Arabia

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Health 2019年第3期11卷 289-297页

作者： Saleh Hadi Alharbi Fahad A. Alateeq khalil Ibrahim Alshammari Abdulaziz Saad Sharea Alshammri Naif Abdulmohsen Naif Alabdali Motab Ali Saud Alsulaiman Sami Mamdouh Ibrahim Algothi abdulrahman Sulaiman Altoraifi Maha Qasem Almutairi Hussain Gadelkarim Ahmed Faculty of Medicine Al-Imam Mohammad Ibn Saud Islamic University Riyadh KSA College of Medicine University of Hail Hail KSA Department of Histopathology and Cytology FMLS University of Khartoum Khartoum Sudan

Background: dietary habit is one of the most universally recounted initiators of irritable bowel syndrome (IBS). The objective of the present study was to determine the role of some dietary habits in the etiology of IBS in Northern Saudi Arabia. Methodology: In this community based cross-sectional survey, data about IBS were obtained from 930 Saudi volunteers living in the city of Hail, Northern Saudi Arabia. IBS was diagnosed using Rome IV criteria. Results: The prevalence of IBS was 11% among males vs. 12.5% among females. The prevalence of IBS symptoms among males was 30% vs. 36.5% females. IBS was significantly associated with reduced water intake, the RR (95% CI) = 1.1800 (1.0146 to 1.3722), P = 0.0316. In the present study, the majority of the study population 904/929 (97.3%) didn’t accustom to vegetables/fruits intake. Conclusion: IBS is prevalent in Northern Saudi Arabia, both among males and females with relatively increasing among females. Low water intake and insufficient fibers intake (particularly, in vegetables and fruits) might be behind the growing prevalence of IBS in Saudi Arabia.

关键词： Irritable Bowel Syndrome Dietary Habits Saudi Arabia

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