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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 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

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Comparison of resistive index and shear-wave elastography in the evaluation of chronic kidney allograft dysfunction

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World Journal of Transplantation 2024年第1期14卷 154-163页

作者： Ameet Kumar Jesrani Syed M Faiq Rahma Rashid Tariq Ali Kalwar rehan Mohsin Tahir Aziz Nida Amin khan Muhammed Mubarak Department of Radiology Sindh Institute of Urology and TransplantationKarachi 74200SindhPakistan Department of Pathology Sindh Institute of Urology and TransplantationKarachi 74200SindhPakistan Department of Transplantation Sindh Institute of Urology and TransplantationKarachi 74200SindhPakistan Department of Urology Sindh Institute of Urology and TransplantationKarachi 74200SindhPakistan

BACKGROUND Detection of early chronic changes in the kidney allograft is important for timely intervention and long-term survival.Conventional and novel ultrasound-based investigations are being increasingly used for this purpose with variable results.AIM To compare the diagnostic performance of resistive index(RI)and shear wave elastography(SWE)in the diagnosis of chronic fibrosing changes of kidney allograft with histopathological results.METHODS This is a cross-sectional and comparative study.A total of 154 kidney transplant recipients were included in this study,which was conducted at the Departments of Transplantation and Radiology,Sindh Institute of Urology and Transplantation,Karachi,Pakistan,from August 2022 to February 2023.All consecutive patients with increased serum creatinine levels and reduced glomerular filtration rate(GFR)after three months of transplantation were enrolled in this study.SWE and RI were performed and the findings of these were evaluated against the kidney allograft biopsy results to determine their diagnostic utility.RESULTS The mean age of all patients was 35.32±11.08 years.Among these,126(81.8%)were males and 28(18.2%)were females.The mean serum creatinine in all patients was 2.86±1.68 mg/dL and the mean estimated GFR was 35.38±17.27 mL/min/1.73 m2.Kidney allograft biopsy results showed chronic changes in 55(37.66%)biopsies.The sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NPV)of SWE for the detection of chronic allograft damage were 93.10%,96.87%%,94.73%,and 95.87%,respectively,and the diagnostic accuracy was 95.45%.For RI,the sensitivity,specificity,PPV,and NPV were 76.92%,83.33%,70.17%,and 87.62%,respectively,and the diagnostic accuracy was 81.16%.CONCLUSION The results from this study show that SWE is more sensitive and specific as compared to RI in the evaluation of chronic allograft damage.It can be of great help during the routine follow-up of kidney transplant recipients for screening and early detection of chronic changes and select

关键词： Shear wave Sonoelastography Resistive index Chronic allograft changes Biopsy Histopathology

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Association Rule Analysis-Based Identification of Influential Users in the Social Media

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Computers, Materials & Continua 2022年第12期73卷 6479-6493页

作者： Saqib Iqbal rehan khan Hikmat Ullah khan Fawaz Khaled Alarfaj Abdullah Mohammed Alomair Muzamil Ahmed College of Engineering Al Ain UniversityAl AinUnited Arab Emirates Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science and Information Sciences Imam Mohammad Ibn Saud Islamic University(IMSIU)Al-HoufufSaudi Arabia

The exchange of information is an innate and natural process that assist in content dispersal.Social networking sites emerge to enrich their users by providing the facility for sharing information and social interaction.The extensive adoption of social networking sites also resulted in user content generation.There are diverse research areas explored by the researchers to investigate the influence of social media on users and confirmed that social media sites have a significant impact on markets,politics and social life.Facebook is extensively used platform to share information,thoughts and opinions through posts and comments.The identification of influential users on the social web has grown as hot research field because of vast applications in diverse areas for instance political campaigns marketing,e-commerce,commercial and,etc.Prior research studies either uses linguistic content or graph-based representation of social network for the detection of influential users.In this article,we incorporate association rule mining algorithms to identify the top influential users through frequent patterns.The association rules have been computed using the standard evaluation measures such as support,confidence,lift,and conviction.To verify the results,we also involve conventional metrics for example accuracy,precision,recall and F1-measure according to the association rules perspective.The detailed experiments are carried out using the benchmark College-Msg dataset extracted by Facebook.The obtained results validate the quality and visibility of the proposed approach.The outcome of propose model verify that the association rule mining is able to generate rules to identify the temporal influential users on Facebook who are consistent on regular basis.The preparation of rule set help to create knowledge-based systems which are efficient and widely used in recent era for decision making to solve real-world problems.

关键词： Association rule mining ranking social web influential users social media

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ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

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Intelligent Automation & Soft Computing 2024年第2期39卷 301-317页

作者： Aiman Muhammad Arshad Bilal khan Khalil khan Ali Mustafa Qamar rehan Ullah khan Department of Computer Science City University of Science and Information TechnologyPeshawarPakistan Department of Computer Science School of Engineering and Digital SciencesNazarbayev UniversityAstanaKazakhstan Department of Computer Science College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and genders.To improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and assessment.To evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are compared.The findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,respectively.Additional metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling tasks.This study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and education.The results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

关键词： Machine learning author profiling AdaBoostM1 random forest ensemble learning text classification

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Exhumation History and Exploration Potential of Gold Deposits in the NE Jiaodong Peninsula,North China:Evidence from Apatite and Zircon Fission Track Thermochronology

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Journal of Earth Science 2023年第3期34卷 776-789页

作者： Yuanlin Chen Huan Li Chaoyang Zheng Safiyanu Muhammad Elatikpo Liu’an Duan Bo Feng Dadou Li rehan khan Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring Ministry of EducationSchool of Geosciences and Info-PhysicsCentral South UniversityChangsha 410083China College of Resources and Environmental Engineering Guizhou UniversityGuiyang 550025China Department of Geology Ahmadu Bello University ZariaNigeria Yantai Geological Survey Center of Coastal Zone China Geological SurveyYantai 264004China Xintai Gold and Mining Industry Co.Ltd Yantai 265147China No.1 Institute of Geology and Mineral Resources of Shangdong Province Jinan 250100China

As the most important gold producer in China,the Northwest Jiaodong Peninsula is famous for its large gold deposits.In recent years,the discovery of gold mineralization has reached a depth of 4000 m below the surface in this region.It has attracted significant interest from explorers about the prospecting potential at greater depths.Besides,the current deep drilling shows that the prospecting effect in the west portion is better than the region to the east.Does it imply that there is a difference in prospecting potential between the east and the west?This paper seeks to address the issue through fission track thermochronology on apatite and zircon to reveal the temperature-time evolution relationship of rock mass and to inverts their thermal evolution history.In addition,this study analyzes the transformation of ore deposits after mineralization,quantitatively calculates the uplift-erosion rate of rock mass,and summarizes the preservation law of ore deposits.Based on the thermal history simulation of the apatite fission track,our results show that the Guocheng gold belt has experienced three stages of thermal evolution:108-74,74-27,and 27-0 Ma.The uplift and cooling processes of the threestage tectonic uplift events are the results of multi-stage Pacific plate accretion.The calculated total denudation depth of the gold deposit in the Guocheng gold belt from Cretaceous to the present is about 3.4-5.3 km.The metallogenic depth of the ore body in the gold belt is 5.6-8.0 km,which indicates that the ore body in the Guocheng gold belt has suffered a significant degree of denudation.It is speculated that the location with less denudation in the southwest has greater prospecting potential.Our results quantitatively identify the uplift and denudation of the deposit after mineralization,which provides a new theoretical reference for regional mineralization,deep prospecting and exploration.

关键词： Queshan pluton Muniushan pluton thermal history simulation apatite zircon exhumation magnitude exploration potential gold deposits Guocheng gold belt

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Can NogoA Be a Suitable Target to Treat Ischemic Stroke?

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Neuroscience Bulletin 2024年第4期40卷 557-560页

作者： Suliman khan Abdul Nasir Medical Research Center The Second Affiliated Hospital of Zhengzhou UniversityZhengzhou540014China

Treating stroke or restoring brain function after stroke remains challenging for clinicians[1,2].Researchers have largely focused on developing neuroprotective strategies and translating these discoveries from rodent experiments to the clinical setting;however,these have been typified by several failures[2].It is known that astrocytes play a crucial role in the pathogenesis of ischemic stroke[3,4].They are activated in response to stimuli arising from injury,characterized by drastic changes to their morphology and function-associated gene expression.Reactive astrocytes exacerbate secondary neurodegeneration(repair of nervous tissue by the generation of new neurons,glial cells,axons,myelin,or synapses)[5]as well as provide neuroprotection during CNS pathologies[6].It is worth noting that myelin-related neurite growth inhibitors induce the suppression of axon regeneration after stroke[7].

关键词： protective NogoA clinical

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A novel fractional case study of nonlinear dynamics via analytical approach

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Applied Mathematics(A Journal of Chinese Universities) 2024年第2期39卷 276-290页

作者： Hassan khan Adnan khan Rasool Shah Dumitru Baleanu Department of Mathematics Abdul Wali khan UniversityMardan 23200Pakistan Department of Mathematics Faculty of Arts and SciencesCankaya UniversityAnkara 06530Turkey Institute of Space Sciences Magurele-BucharestRomania

The present work describes the fractional view analysis of Newell-Whitehead-Segal equations,using an innovative technique.The work is carried with the help of the Caputo operator of fractional derivative.The analytical solutions of some numerical examples are presented to confirm the reliability of the proposed method.The derived results are very consistent with the actual solutions to the problems.A graphical representation has been done for the solution of the problems at various fractional-order derivatives.Moreover,the solution in series form has the desired rate of convergence and provides the closed-form solutions.It is noted that the procedure can be modified in other directions for fractional order problems.

关键词： Homotopy Perturbation method Shehu transform Newell-Whitehead-Segel Equation Caputo operator

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Room and cryogenic deformation behavior of AZ61 and AZ61-xCaO(x = 0.5, 1 wt.%) alloy

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Journal of Magnesium and Alloys 2024年第5期12卷 1996-2009页

作者： Umer Masood Chaudry Hafiz Muhammad rehan Tariq Nooruddin Ansari Soo Yeol Lee Tea-Sung Jun Department of Mechanical Engineering Incheon National University Research Institute for Engineering and Technology Incheon National University Department of Materials Science&Engineering Chungnam National University

This study investigates the influence of CaO(0.5, 1(wt.%)) alloying on the microstructural evolution, texture development and deformation behavior of AZ61 magnesium alloy. The uniaxial tension tests at room(RT) and cryogenic(CT,-150 ℃) temperature were performed to investigate the twinability and dislocation behavior and its consequent effect on flow stress, ductility and strain hardening rate. The results showed that the AZ61-1CaO exhibited superior strength/ductility synergy at RT with a yield strength(YS) of 223 MPa and a ductility of 23% as compared to AZ61(178 MPa, 18.5%) and AZ61-0.5CaO(198 MPa, 21%). Similar trend was witnessed for all the samples during CT deformation, where increase in the YS and decrease in ductility were observed. The Mtex tools based in-grain misorientation axis(IGMA) analysis of RT deformed samples revealed the higher activities of prismaticslip in AZ61-CaO, which led to superior ductility.Moreover, subsequent EBSD analysis of CT deformed samples showed the increased fraction of fine {10-12} tension twins and nucleation of multiple {10-12} twin variants caused by higher local stress concentration at the grain boundaries, which imposed the strengthening by twin-twin interaction. Lastly, the detailed investigations on strengthening contributors showed that the dislocation strengthening has the highest contribution towards strength in all samples.

关键词： Magnesium Twinning Twinning variant EBSD Cryogenic deformation

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Electronic and thermoelectric properties of YbMg_(2)X_(2)(X=P,As,Sb,Bi)zintl compounds by first-principles method

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Journal of Rare Earths 2024年第1期42卷 147-154,I0006页

作者： Sajid khan Dil Faraz khan R.Neffati Tariq Usman Muhammad Waqar Ahsraf Shamim khan Saeed Ullah Jan G.Murtaza Department of Physics University of Science&Technology BannuBannu28100Pakistan Department of Physics Faculty of ScienceKing Khalid UniversityP.O.Box 9004AbhaSaudi Arabia Laboratoire de Physique de La Matiere Condensee Departement de PhysiqueFaculte des Sciences de TunisUniversite Tunis El ManarCampus Universitaire1060TunisTunisia Department of Physics Shaoxing UniversityShaoxing312000China Department of Mathematics&Natural Sciences Prince Mohammad Bin Fahd UniversityAlkhobar31952Saudi Arabia Materials Modeling Lab Department of PhysicsIslamia College Peshawar25120KhyberPakhtunkhwaPakistan

In this work the structural,electronic and thermoelectric properties of YbMg_(2)X_(2)(X=P,As,Sb,Bi)zintl compounds were investigated comprehensively using first principles study.The electronic properties were studied using PBE GGA,TB-mBJ and hybrid(YS-PBE0)potentials.All the structural parameters of optimized structures are in harmonious agreement to the available data.The band structure study illustrates that the titled materials manifest metallic and semi metallic nature using PBE and TB-mBJ potentials while they show wide band gap semiconducting behavior by following hybrid(YS-PBE0)potential.Total density of states(TDOS)and partial density of states(PDOS)were also calculated to glimpse the contribution of orbitals of atoms in the formation of bands.Transport properties were studied by using BoltzTraP2 code employed to WIEN2k.We get enormous values of Seebeck coefficient(S),power factor(PF)and thermoelectric figure of merit(ZT)for all the samples YbMg_(2)X_(2)(X=P,As,Sb,Bi),Moreover,the overwhelming transport properties for the titled compounds indicate the optimum level of carriers’concentration which pinpoints these materials to be better thermoelectrics in the 1-2-2 zintl family.

关键词： Zintl compounds Hybrid functional Band structure Thermoelectrics Rare earths

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Performance of Text-Independent Automatic Speaker Recognition on a Multicore System

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Tsinghua Science and Technology 2024年第2期29卷 447-456页

作者： Rand Kouatly Talha Ali khan Faculty of Tech and Software Engineering University of Europe for Applied SciencesPotsdam 14469Germany

This paper studies a high-speed text-independent Automatic Speaker Recognition(ASR)algorithm based on a multicore system's Gaussian Mixture Model(GMM).The high speech is achieved using parallel implementation of the feature's extraction and aggregation methods during training and testing procedures.Shared memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR algorithm.The experimental results show speed-up improvements of around 3.2 on a personal laptop with Intel i5-6300HQ(2.3 GHz,four cores without hyper-threading,and 8 GB of RAM).In addition,a remarkable 100%speaker recognition accuracy is achieved.

关键词： Automatic Speaker Recognition(ASR) Gaussian Mixture Model(GMM) shared memory parallel programming PThreads OpenMP

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