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

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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 languages.While 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 effectiveness of the models. The research findings revea

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

A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

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Computers, Materials & Continua 2024年第3期78卷 3805-3823页

作者： Shaha Al-Otaibi Rahim khan Hashim ali Aftab Ahmed khan Amir Saeed Jehad ali Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Abdul Wali Khan University MardanMardan23200Pakistan Department of Computer Science and IT UET PeshawarJalozai Campus PeshawarPeshawar24240Pakistan Department of AI Convergence Network Ajou UniversitySuwon16499South Korea

The Internet of Things(IoT)is a smart networking infrastructure of physical devices,i.e.,things,that are embedded with sensors,actuators,software,and other technologies,to connect and share data with the respective server module.Although IoTs are cornerstones in different application domains,the device’s authenticity,i.e.,of server(s)and ordinary devices,is the most crucial issue and must be resolved on a priority basis.Therefore,various field-proven methodologies were presented to streamline the verification process of the communicating devices;however,location-aware authentication has not been reported as per our knowledge,which is a crucial metric,especially in scenarios where devices are mobile.This paper presents a lightweight and location-aware device-to-server authentication technique where the device’s membership with the nearest server is subjected to its location information along with other measures.Initially,Media Access Control(MAC)address and Advance Encryption Scheme(AES)along with a secret shared key,i.e.,λ_(i) of 128 bits,have been utilized by Trusted Authority(TA)to generate MaskIDs,which are used instead of the original ID,for every device,i.e.,server and member,and are shared in the offline phase.Secondly,TA shares a list of authentic devices,i.e.,server S_(j) and members C_(i),with every device in the IoT for the onward verification process,which is required to be executed before the initialization of the actual communication process.Additionally,every device should be located such that it lies within the coverage area of a server,and this location information is used in the authentication process.A thorough analytical analysis was carried out to check the susceptibility of the proposed and existing authentication approaches against well-known intruder attacks,i.e.,man-in-the-middle,masquerading,device,and server impersonations,etc.,especially in the IoT domain.Moreover,proposed authentication and existing state-of-the-art approaches have been simulated in the real environment of IoT to verif

关键词： Internet of things authenticity security location communication

Development of anti-corrosive coating on AZ31 Mg alloy modified by MOF/LDH/PEO hybrids

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Journal of Magnesium and Alloys 2024年第2期12卷 586-607页

作者： Muhammad ali khan Ananda Repycha Safira Mohammad Aadil Mosab Kaseem Corrosion and Electrochemistry Laboratory Department of Nanotechnology and Advanced Materials EngineeringSejong UniversitySeoul 05006Republic of Korea

The self-assembly of hybrid inorganic-organic materials on stationary platforms plays a critical role in improving their structural stability and wide usability.In this work,a novel two-step hydrothermal approach is proposed for synthesizing stable and advanced hybrid coatings on metal-oxide platforms through the surface modification of layered double hydroxide(LDH)films using novel metal-organic frameworks(MOFs).Initially,Mg-Al LDH nanocontainers,grown on a magnesium oxide layer produced through plasma electrolytic oxidation(PEO)of AZ31 Mg alloy substrate,were intercalated with cobalt via an oxidation route,providing the metallic coordination center for the MOF formation.In the subsequent step,a pioneering technique is introduced,utilizing tryptophan as the organic linker for the first time at a pH of 10.The self-assembly of cobalt-tryptophan complex,driven by the strong bonding between electrophilic sites of monomers and nucleophilic sites,facilitated the formation of a MOF network having a cloud-like structure on the surface of MgAl LDH's film.The resulting MOF-LDH encapsulation containers demonstrate exceptional electrochemical stability when exposed to a 3.5 wt.%NaCl solution,surpassing the performance of PEO and pure LDH coatings.This enhanced stability is attributed to the development of a dense top layer and a stable composition within the self-assembled MOF,effectively sealing flaws and preventing the infiltration of corrosive ions into the underlying metallic substrate.The formation mechanism of MOFs on LDH galleries is investigated using density functional theory calculations.

关键词： Mg alloy Layered double hydroxide Metal-organic frameworks Corrosion DFT

The role of green industrial transformation in mitigating carbon emissions:Exploring the channels of technological innovation and environmental regulation

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Energy and Built Environment

Energy and Built Environment 2024年第3期5卷 464-479页

作者： Saima Mehmood Khalid Zaman Shiraz khan Zohaib ali Haroon ur Rashid khan Department of Economics The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Management Sciences The University of HaripurHaripurKhyber Pakhtunkhwa 22620Pakistan Department of Energy and Process Engineering(EPT) Norwegian University of Science and TechnologyHøgskoleringen 1Trondheim 7034Norway Faculty of Business The University of Wollongong in DubaiDubai 20183United Arab Emirates

The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic concerns.The purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and 2020.Carbon emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible mediators.The association between variables is assessed using the robust least-squares approach.Green industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon emissions.The findings support the pollution haven hypothesis in a country.The causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental standards.According to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 forward.Additionally,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over time.Green industrial transitions are projected to result in a ten-year reduction in carbon emissions.The variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over time.Pakistan’s economy should foster a green industrial revolution to avoid pollution and increase environmental sustainability to meet its environmental g

关键词： Carbon intensity Industrial green transformation Environmental regulations Technological innovations Robust least squares regression

Acoustofluidic separation of prolate and spherical micro-objects

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Microsystems & Nanoengineering 2024年第1期10卷 217-230页

作者： Muhammad Soban khan Mushtaq ali Song Ha Lee Keun Young Jang Seong Jae Lee Jinsoo Park Department of Mechanical Engineering Chonnam National University77 Yongbong-roBuk-guGwangju 61186Republic of Korea Department of Polymer Engineering The University of Suwon17 Wauan-gilBongdam-eupHwaseongGyeonggi 18323Republic of Korea

Most microfluidic separation techniques rely largely on object size as a separation marker.The ability to separate micro-objects based on their shape is crucial in various biomedical and chemical assays.Here,we develop an ondemand,label-free acoustofluidic method to separate prolate ellipsoids from spherical microparticles based on traveling surface acoustic wave-induced acoustic radiation force and torque.The freely rotating non-spherical microobjects were aligned under the progressive acoustic field by the counterrotating radiation torque,and the major axis of the prolate ellipsoids was parallel to the progressive wave propagation.The specific alignment of the ellipsoidal particles resulted in a reduction in the cross-sectional area perpendicular to the wave propagation.As a consequence,the acoustic backscattering decreased,resulting in a decreased magnitude of the radiation force.Through the variation in radiation force,which depended on the micro-object morphology enabled the acoustofluidic shape-based separation.We conducted numerical simulations for the wave scattering of spherical and prolate objects to elucidate the working mechanism underlying the proposed method.A series of experiments with polystyrene microspheres,prolate ellipsoids,and peanut-shaped microparticles were performed for validation.Through quantitative analysis of the separation efficiency,we confirmed the high purity and high recovery rate of the proposed acoustofluidic shapebased separation of micro-objects.As a bioparticle,we utilize Thalassiosira eccentrica to perform shape-based separation,as the species has a variety of potential applications in drug delivery,biosensing,nanofabrication,bioencapsulation and immunoisolation.

关键词： separation spherical rotating

Optimal Bidding Strategies of Microgrid with Demand Side Management for Economic Emission Dispatch Incorporating Uncertainty and Outage of Renewable Energy Sources

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Energy Engineering 2024年第4期121卷 849-867页

作者： Mousumi Basu Chitralekha Jena Baseem khan Ahmed ali Department of Power Engineering Jadavpur UniversityJadavpurIndia School of Electrical Engineering KIIT UniversityBhubaneswarIndia Department of Electrical and Computer Engineering Hawassa UniversityHawassaEthiopia Department of Electrical and Electronic Engineering Technology Faculty of Engineering and the Built EnvironmentUniversity of JohannesburgJohannesburgSouth Africa

In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity provider.DER consists of gas turbines and renewable energy sources such as photovoltaic systems and wind turbines.Better bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage rate.To solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy sources.The uncertainty related to solar and wind units is modeled using lognormal and Weibull probability distributions.TOU-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.

关键词： Micro-grid distributed energy resources demand response program uncertainty outage

Expansion of human umbilical cord derived mesenchymal stem cells in regenerative medicine

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World Journal of Stem Cells 2024年第4期16卷 410-433页

作者： Shafiqa Naeem Rajput Bushra Kiran Naeem Anwar ali Asmat Salim Irfan khan Dr.Panjwani Center for Molecular Medicine and Drug Research International Center for Chemical and Biological SciencesUniversity of KarachiKarachi 75270SindhPakistan Surgical Unit 4 Dr.Ruth KM Pfau Civil HospitalKarachi 74400Pakistan Department of Physiology University of KarachiKarachi 75270Pakistan Center for Regenerative Medicine and Stem Cells Research and Department of Ophthalmology and Visual SciencesThe Aga Khan UniversityKarachi 74800SindhPakistan

BACKGROUND Stem cells are undifferentiated cells that possess the potential for self-renewal with the capacity to differentiate into multiple lineages.In humans,their limited numbers pose a challenge in fulfilling the necessary demands for the regeneration and repair of damaged tissues or organs.Studies suggested that mesenchymal stem cells(MSCs),necessary for repair and regeneration via transplantation,require doses ranging from 10 to 400 million cells.Furthermore,the limited expansion of MSCs restricts their therapeutic application.AIM To optimize a novel protocol to achieve qualitative and quantitative expansion of MSCs to reach the targeted number of cells for cellular transplantation and minimize the limitations in stem cell therapy protocols.METHODS Human umbilical cord(hUC)tissue derived MSCs were obtained and re-cultured.These cultured cells were subjected to the following evaluation pro-cedures:Immunophenotyping,immunocytochemical staining,trilineage differentiation,population doubling time and number,gene expression markers for proliferation,cell cycle progression,senescence-associatedβ-galactosidase assay,human telomerase reverse transcriptase(hTERT)expression,mycoplasma,cytomegalovirus and endotoxin detection.RESULTS Analysis of pluripotent gene markers Oct4,Sox2,and Nanog in recultured hUC-MSC revealed no significant differences.The immunophenotypic markers CD90,CD73,CD105,CD44,vimentin,CD29,Stro-1,and Lin28 were positively expressed by these recultured expanded MSCs,and were found negative for CD34,CD11b,CD19,CD45,and HLA-DR.The recultured hUC-MSC population continued to expand through passage 15.Proliferative gene expression of Pax6,BMP2,and TGFb1 showed no significant variation between recultured hUC-MSC groups.Nevertheless,a significant increase(Pality control assessments co

关键词： Human umbilical cord Mesenchymal stem cells Expansion Cell proliferation In vitro expansion Senescence

Performance Enhancement of XML Parsing Using Regression and Parallelism

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Computer Systems Science & Engineering 2024年第2期48卷 287-303页

作者： Muhammad ali Minhaj Ahmad khan Department of Computer Science Bahauddin Zakariya UniversityMultan60000Pakistan

The Extensible Markup Language(XML)files,widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications.With the existing Document Object Model(DOM)based parsing,the performance degrades due to sequential processing and large memory requirements,thereby requiring an efficient XML parser to mitigate these issues.In this paper,we propose a Parallel XML Tree Generator(PXTG)algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework(RXPF)that analyzes and predicts performance through profiling,regression,and code generation for efficient parsing.The PXTG algorithm is based on dividing the XML file into n parts and producing n trees in parallel.The profiling phase of the RXPF framework produces a dataset by measuring the performance of various parsing models including StAX,SAX,DOM,JDOM,and PXTG on different cores by using multiple file sizes.The regression phase produces the prediction model,based on which the final code for efficient parsing of XML files is produced through the code generation phase.The RXPF framework has shown a significant improvement in performance varying from 9.54%to 32.34%over other existing models used for parsing XML files.

关键词： Regression parallel parsing multi-cores XML

Enhanced electrochemical and photocatalytic performance achieved through dual incorporation of SnO2 and WO3 nanoparticles into LDH layer fabricated on PEO-coated AZ31 Mg alloy

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Journal of Magnesium and Alloys 2024年第5期12卷 1880-1898页

作者： Muhammad ali khan Ananda Repycha Safira Mosab Kaseem Arash Fattah-alhosseini Corrosion and Electrochemistry Laboratory Department of Nanotechnology and Advanced Materials Engineering Sejong University Department of Materials Engineering Faculty of Engineering Bu-Ali Sina University

This study explores the potential of LDH flakes decorated with metallic oxide nanoparticles to function as both anti-corrosion barriers against chloride anions and heterogeneous photocatalysts for tetracycline degradation under visible light. The process involves modifying the primarily MgO-based inorganic porous film by growing a MgFe LDH film, followed by the individual and dual incorporation of SnO2and WO3nanoparticles. The dual incorporation of these nanoparticles into the LDH matrix leads to synergistic interactions, effectively sealing pre-existing defects within LDH flakes and facilitating the in-situ formation of catalytic sites through oxidation and the induction of surface oxygen vacancy defects, which synergistically contribute to the enhancement of both electrochemical and photocatalytic activities. The enhanced electrochemical stability is reflected in a significant reduction in corrosion current density by 4 orders of magnitude compared to unmodified porous film. Additionally, the decorated film demonstrates sustained photocatalytic functionality, achieving significant degradation（95.5%） of tetracycline within two hours. This study presents a novel approach, highlighting the dual effectiveness of LDHs decorated by dual metal oxides as an anti-corrosive agent and photocatalyst, with promising implications for environmental remediation and wastewater purification.

关键词： Porous film LDH film Anti corrosive Photocatalysis Oxygen vacancy Tetracycline