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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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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 *** work is carried with the help of the Caputo operator of fractional *** analytical solutions of some numerical examples are presented to confirm the reliability of the proposed *** 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 ***,the solution in series form has the desired rate of convergence and provides the closed-form *** 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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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 usma. 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 *** electronic properties were studied using PBE GGA,TB-mBJ and hybrid(YS-PBE0)*** the structural parameters of optimized structures are in harmonious agreement to the available *** 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)*** 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 *** properties were studied by using BoltzTraP2 code employed to *** 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 *** memory parallel programming techniques using both OpenMP and PThreads libraries are developed to accelerate the code and improve the performance of the ASR *** 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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Insight into the dynamics of non-Newtonian Carreau fluid when viscous dissipation,entropy generation,convective heating and diffusion are significant

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Applied Mathematics(A Journal of Chinese Universities) 2024年第1期39卷 34-46页

作者： ZHOU Shuang-shuang Muhammad Ijaz khan Sami Ullah khan Sumaira Qayyum School of Science Hunan City UniversityYiyang 413000China Department of Mechanical Engineering Prince Mohammad Bin Fahd UniversityP.O.Box1664Al-Khobar 31952Kingdom of Saudi Arabia Department of Mathematics Namal UniversityMianwali 42250Pakistan Department of Mathematics Quaid-I-Azam University 45320Islamabad 44000Pakistan

The investigation endorsed the convective flow of Carreau nanofluid over a stretched surface in presence of entropy generation *** novel dynamic of viscous dissipation is utilized to analyze the thermal mechanism of magnetized *** convective boundary assumptions are directed in order to examine the heat and mass transportation of *** thermal concept of thermophoresis and Brownian movements has been re-called with the help of Buongiorno *** problem formulated in dimensionless form is solved by NDSolve *** graphical analysis for parameters governed by the problem is performed with physical *** affiliation of entropy generation and Bejan number for different parameters is inspected in *** numerical data for illustrating skin friction,heat and mass transfer rate is also *** motion of the fluid is highest for the viscosity ratio *** temperature of the fluid rises via thermal Biot *** generation rises for greater Brinkman number and diffusion parameter.

关键词： heat generation surface reaction CNTs based nano uid stretching/shrinking sheet thermal radiation

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Interpretable Detection of Malicious Behavior in Windows Portable Executables Using Multi-Head 2D Transformers

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Big Data Mining and Analytics 2024年第2期7卷 485-499页

作者： Sohail khan Mohammad Nauman Computer Science Department Effat College of EngineeringEffat UniversityJeddah 23341Kingdom of Saudi Arabia

Windows malware is becoming an increasingly pressing problem as the amount of malware continues to grow and more sensitive information is stored on *** of the major challenges in tackling this problem is the complexity of malware analysis,which requires expertise from human *** developments in machine learning have led to the creation of deep models for malware ***,these models often lack transparency,making it difficult to understand the reasoning behind the model’s decisions,otherwise known as the black-box *** address these limitations,this paper presents a novel model for malware detection,utilizing vision transformers to analyze the Operation Code(OpCode)sequences of more than 350000 Windows portable executable malware samples from real-world *** model achieves a high accuracy of 0.9864,not only surpassing the previous results but also providing valuable insights into the reasoning behind the *** model is able to pinpoint specific instructions that lead to malicious behavior in malware samples,aiding human experts in their analysis and driving further advancements in the *** report our findings and show how causality can be established between malicious code and actual classification by a deep learning model,thus opening up this black-box problem for deeper analysis.

关键词： machine learning malware vision transformers Windows Protable Executable(PE)

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Metabolic complications of psychotropic medications in psychiatric disorders:Emerging role of de novo lipogenesis and therapeutic consideration

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World Journal of Psychiatry 2024年第6期14卷 767-783页

作者： Mohammad M khan Zaw Ali khan Mohsin Ali khan Laboratory of Translational Neurology and Molecular Psychiatry Department of BiotechnologyEra’s Lucknow Medical College and Hospitaland Faculty of ScienceEra UniversityLucknow 226003India Era’s Lucknow Medical College and Hospital Era UniversityLucknow 226003India

Although significant advances have been made in understanding the pathophysiology of psychiatric disorders(PDs),therapeutic advances have not been very *** psychotropic medications can reduce classical symptoms in patients with PDs,their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes,obesity and non-alcoholic fatty liver disease(NAFLD).The mechanism(s)underlying these metabolic abnormalities is not clear;however,lipid/fatty acid accumulation due to enhanced de novo lipogenesis(DNL)has been shown to reduce membrane fluidity,increase oxidative stress and inflammation leading to the development of the aforementioned metabolic ***,emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity,diabetes and NAFLD after long-term treatment with psychotropic medications in patients with *** support of this,several adjunctive drugs comprising of anti-oxidants and antiinflammatory agents,that are used in treating PDs in combination with psychotropic medications,have been shown to reduce insulin resistance and development of *** conclusion,the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities,and a new avenue for translational research and therapeutic drug designing in PDs.

关键词： Psychotropic medications Metabolic complications De novo lipogenesis Obesity Diabetes Non-alcoholic fatty liver disease

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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 *** 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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Unsupervised Color Segmentation with Reconstructed Spatial Weighted Gaussian Mixture Model and Random Color Histogram

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Computers, Materials & Continua 2024年第3期78卷 3323-3348页

作者： Umer Sadiq khan Zhen Liu Fang Xu Muhib Ullah khan Lerui Chen Touseef Ahmed khan Muhammad Kashif Khattak Yuquan Zhang School of Computer and Information Science Hubei Engineering UniversityXiaogan432000China Institute for AI Industrial Technology Research Hubei Engineering UniversityXiaogan432000China Key Lab of Mountain Hazards and Surface Processes Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China University of Chinese Academy of Sciences Beijing100049China College of Aviation Zhongyuan University of TechnologyZhengzhou451191China Research Center of Digital Mountain and Remote Sensing Application Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu610041China School of Computer Science University of PoonchAzad Jammu Kashmir12350Pakistan School of Computer Science and Information Engineering Hubei UniversityWuhan430062China

Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture *** the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation *** this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter *** proposed model highlights the residual region with considerable information and constructs color ***,we incorporate the content-based color saliency as spatial information in the Gaussian mixture *** segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum ***,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic *** experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge *** the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.

关键词： Unsupervised segmentation color saliency spatial weighted GMM random color histogram

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

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

作者： usma. 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

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