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Sentiment Analysis in Social Media for Competitive Environment Using Content Analysis

Computers, Materials & Continua 2022年第6期71卷 5603-5618页

作者： shahid mehmood Imran Ahmad Muhammad Adnan Khan Faheem Khan T.Whangbo Riphah School of Computing&Innovation Faculty of ComputingRiphah International University Lahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Engineering Gachon UniversitySeongnam13557Korea

Education sector has witnessed several changes in the recent *** changes have forced private universities into fierce competition with each other to get more students *** competition has resulted in the adoption of marketing practices by private universities similar to commercial *** get competitive gain,universities must observe and examine the students’feedback on their own social media sites along with the social media sites of their *** study presents a novel framework which integrates numerous analytical approaches including statistical analysis,sentiment analysis,and text mining to accomplish a competitive analysis of social media sites of the *** techniques enable local universities to utilize social media for the identification of the most-discussed topics by students as well as based on the most unfavorable comments received,major areas for improvement.A comprehensive case study was conducted utilizing the proposed framework for competitive analysis of few top ranked international universities as well as local private universities in Lahore *** results show that diversity of shared content,frequency of posts,and schedule of updates,are the key areas for improvement for the local *** on the competitive intelligence gained several recommendations are included in this paper that would enable local universities generally and Riphah international university(RIU)Lahore specifically to promote their brand and increase their attractiveness for potential students using social media and launch successful marketing campaigns targeting a large number of audiences at significantly reduced cost resulting in an increased number of enrolments.

关键词： Social media higher education sentiment analysis content analysis competitive analysis text mining

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中华蜜蜂囊状幼虫病病毒系统发育关系与感染性克隆制备

中华蜜蜂囊状幼虫病病毒系统发育关系与感染性克隆制备

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作者： shahid mehmood 福建农林大学

学位级别：硕士

囊状幼虫病毒(SBV)广泛存在于西方蜜蜂(Apis mellifera)中,而在东方蜜蜂(Apis cerana)中独特演化出一 SBV毒株,中蜂囊状幼虫病(中囊病)病毒(Apis cerana SBV,AcSBV),导致幼虫在化蛹前死亡,常使蜂群群势下降蜂群崩溃,是中蜂生产中最严重... 详细信息

囊状幼虫病毒(SBV)广泛存在于西方蜜蜂(Apis mellifera)中,而在东方蜜蜂(Apis cerana)中独特演化出一 SBV毒株,中蜂囊状幼虫病(中囊病)病毒(Apis cerana SBV,AcSBV),导致幼虫在化蛹前死亡,常使蜂群群势下降蜂群崩溃,是中蜂生产中最严重的病害,几乎所有东方蜜蜂的自然栖息地都有AcSBV存在。台湾地区中蜂在2015年之前没有相关研究报道,当地蜂农也没有被囊状幼虫病毒影响过,直到2016年台湾中部饲养中蜂的蜂农发现了 SBV类似症状。我们用RT-PCR方法检测了该地区患病蜂群蜜蜂幼虫的样本,并对台湾北部地区没有发病症状的蜂场进行了调查。系统发育分析显示,从中国台湾中部蜂群中分离的AcSBV应为外源引入;所有分离得到的AcSBV的基因序列与在中国大陆、越南和韩国的AcSBV基因组序列具有高度的相似性,但与中国台湾鉴定出的SBV序列有明显的区别。患病蜂群中的总体流行性较低,在无症状的蜂群中未发现潜伏感染,AcSBV可能尚未达到其最高的流行病潜力。囊状幼虫病毒在蜜蜂中能造成致死疾病,它属于软腐病病毒科,是一种单链正股RNA病毒,仅编码一个开放阅读框(Open reading frame,ORF),翻译成一个多聚蛋白后在宿主细胞中再进行切割成单一有功能的蛋白。目前没有反向遗传学研究数据,很难在不影响单个ORF的前提下,创建具有人为引入突变或报告基因的感染性克隆。在本研究中,我们构建了一种模拟dicistrovirus基因组结构的双顺反子中囊病病毒克隆,两个ORFs由基因间区IRES(IGR-IRES)划分。黑王台病毒的基因间区IRES在克隆后整合到中囊病病毒基因组3’-端非编码区之后,后再接上EGFP基因与polyA区。转录后,将病毒RNA注射到蜜蜂幼虫体内,产生带蛋白壳的克隆病毒,并作为经口接种源两代以上。接种后的幼虫表现出典型的中囊病病状和EGFP荧光,证明了组建的双顺反子中囊病病毒克隆是稳定的,功能与野生型中囊病相同。此外,研究结果显示,表明SBV的3’端非编码区不影响IGR-IRES的功能以及其后人为引入序列的复制。我们的SBV克隆含有易于追踪的EGFP荧光表达可以有助于更好地理解中囊病病毒的反向遗传学、致病机理以及传染机制。中囊病病毒有典型软腐病毒基因组结构,与其他软腐病毒有高度相似的基因组序列,相同的方法能适用于其他蜜蜂或昆虫的软腐病毒可隆。

关键词：囊状幼虫病东方蜜蜂囊状幼虫病毒克隆病毒双顺反子 IGR-IRES

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A single-step synthesis of nitrogen-doped graphene sheets decorated with cobalt hydroxide nanoflakes for the determination of dopamine

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Progress in Natural Science:Materials International 2017年第5期27卷 582-587页

作者： Muhammad mehmood shahid Ahmad H.Ismail Ali MA.Abdul Amir AL-Mokaram R.Vikneswaran Sohail Ahmad Amir Hamza Arshid Numan Department of Physics Faculty of ScienceUniversity of Malaya Department of Chemistry College of ScienceMustansiriyah University Department of Chemistry Faculty of ScienceUniversity of Malaya Nanotechnology & Catalysis Research Centre University of Malaya 5. Faculty of ScienceUniversity of Haripur

Nitrogen-doped reduced graphene oxide（NrGO）sheets decorated with Co（OH）;nanoflakes were prepared by a single-step hydrothermal *** morphological and structural characterizations of as synthesized Nr GO@Co（OH）;nanoflakes were performed by field emission scanning electron microscopy（FESEM）,EDX-mapping and X-ray diffraction（XRD）.Nr GO@Co（OH）;nanoflakes modified glassy carbon electrode（GCE）was used for electrochemical sensing of dopamine in neutral *** nanocomposite modified electrode showed enhanced electrochemical sensing ability for the detection of dopamine and the limit of detection（Lo D）was found to be 0.201μM with a sensitivity value of 0.0286±0.002 m A m M;.Interference studies revealed that Nr GO@Co（OH）;─GCE endow excellent selectivity for DA detection even in the presence of higher concentration of common co-existing physiological interfering ***,proposed sensor demonstrated excellent performance in urine samples with promising reproducibility and stability.

关键词： Nitrogen doped graphene Dopamine Electrochemical sensor Amperometric detection

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Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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Computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah shahid shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

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ASLP-DL—A Novel Approach Employing Lightweight Deep Learning Framework for Optimizing Accident Severity Level Prediction

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Computers, Materials & Continua 2024年第2期78卷 2535-2555页

作者： Saba Awan Zahid mehmood Department of Software Engineering University of Engineering and TechnologyTaxila47050Pakistan Department of Computer Engineering University of Engineering and TechnologyTaxila47050Pakistan

Highway safety researchers focus on crash injury severity,utilizing deep learning—specifically,deep neural networks(DNN),deep convolutional neural networks(D-CNN),and deep recurrent neural networks(D-RNN)—as the preferred method for modeling accident *** learning’s strength lies in handling intricate relation-ships within extensive datasets,making it popular for accident severity level(ASL)prediction and *** prior success,there is a need for an efficient system recognizing ASL in diverse road *** address this,we present an innovative Accident Severity Level Prediction Deep Learning(ASLP-DL)framework,incorporating DNN,D-CNN,and D-RNN models fine-tuned through iterative hyperparameter selection with Stochastic Gradient *** framework optimizes hidden layers and integrates data augmentation,Gaussian noise,and dropout regularization for improved *** and factor contribution analyses identify influential *** on three diverse crash record databases—NCDB 2018–2019,UK 2015–2020,and US 2016–2021—the D-RNN model excels with an ACC score of 89.0281%,a Roc Area of 0.751,an F-estimate of 0.941,and a Kappa score of 0.0629 over the NCDB *** proposed framework consistently outperforms traditional methods,existing machine learning,and deep learning techniques.

关键词： Injury severity prediction deep learning feature

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Ion-acoustic waves with non-planar wavefronts

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Plasma Science and Technology 2024年第1期26卷 1-7页

作者： Shujaht BUKHARI Muhammad shahid Ata-ur RAHMAN Department of Physics The University of Azad Jummu and KashmirMuzaffarabad 13100Azad Kashmir Department of Physics Women University of Azad Jammu&KashmirBagh 12500Pakistan Department of Physics Islamia College PeshawerPeshawar 25120Pakistan

The ion-acoustic(IA) mode exhibiting various orbital angular momentum(OAM) states is examined in a plasma with drifting *** constituent plasma species are modeled with a non-gyrotropic Maxwellian distribution and discussion of dispersion relation and growth rate of twisted IA waves under various conditions is *** the domain of kinetic model,the twisted IA waves are characterized by Laguerre-Gaussian(LG) solutions,where plasma distribution function and electric field are decomposed into axial and azimuthal *** plasma response function is obtained under paraxial approximations and investigated for threshold condition of instability growth rate with helical electric field *** impact of an extra electron specie on the instability is demonstrated through a comparison of twisted waves for single and double electron species.

关键词： instability twist parameter wave excitation orbital angular momentum threshold limit

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Gravity-driven powder flow and the influence of external vibration on flow characteristics

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Particuology 2024年第5期88卷 201-209页

作者： Muhammad shahid Ansari Ratna Kumar Annabattula Sathyan Subbiah Department of Mechanical Engineering Indian Institute of Technology MadrasChennai 600036India

The controlled and homogeneous flow of dry granular powders through hoppers is essential for applications,namely,packaging of food grains,fertilizers and additive manufacturing processes such as directed energy deposition for better product *** of the major issues encountered in the granular flows through hoppers is flow stagnation due to the well-known arching ***-assisted granular flow through hoppers is one of the mechanisms used for better mass flow *** this work,the influence of external mechanical vibration on the powder flow is investigated experimentally and using discrete element ***,the mass flow rate through the hopper increases with an increase in vibration amplitude and then decreases,signifying the existence of an optimal amplitude of *** DEM simulations explained the underlying mechanisms for the existence of an optimal amplitude of vibration corresponding to the maximum mass flow rate.A range of vibration amplitudes from 0 mm to 3.5 mm is used to study the flow behaviour;the maximum flow of around 33 g/s to 35 g/s is observed for 0.75 mm to 1.25 mm vibration amplitude for the hopper-particle combination studied in this *** work also reports the influence of vibration frequency,hopper,and particle dimension on the flow *** research facilitates the effective use of mechanical vibration to enhance powder flow that can further be extended to non-spherical and multi-material particles.

关键词： Discrete element method Flow rate Granular flow Path tracking Vibration intensity

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Web GIS-Based Temporal Analysis of Climatic Factors Impacting Heat Stroke in Karachi

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Journal of Geographic Information System 2024年第1期16卷 61-69页

作者： Ali Atif Mahnoor Rehman Muhammad Butt Syed Mahmood shahid Ghazi Rashid mehmood Department of Management Victoria University Sydney Australia Department of Geography Government College University Lahore Pakistan Department of Space Science University of the Punjab Lahore Pakistan Centre of Geographic Information System University of The Punjab Lahore Pakistan

This study focuses on the impact of climate change, specifically the increasing threat of heatwaves, in Pakistan, with a particular emphasis on the city of Karachi. The Pakistan Meteorological Department (PMD) analysed a century of climatic data to reveal warming trends, attributing them to human-induced factors. The vulnerability of Pakistan to climate change is highlighted, given its warm climate and location in a region where temperature increases are expected to surpass global averages. The study examines the past three decades, noting a significant rise in the frequency of hot days, especially in Karachi, where heatwaves have become more prevalent. The aims and objectives of the study involve identifying temporal changes in temperature, rainfall, humidity, and wind speed from 1984 to 2014 in Karachi. The literature review emphasizes the health implications of heatwaves, citing increased mortality during such events globally. The study incorporates a comprehensive temporal analysis, addressing gaps in previous research by considering multiple climate indicators responsible for heatwaves. The methodology involves statistical analyses, including linear regression and Pearson correlation, applied to temperature data and urbanization parameters. Results indicate an increasing trend in heat index temperature, with heatwave vulnerability peaking in the last three decades. Heat Index Temperature Anomalies show a clear surge, emphasizing the need for new indices to control critical heat stress conditions. The study concludes that tropical climate variability, particularly heat index, is linked to extreme hot days, urging measures to reduce population vulnerability. The findings underscore the importance of policy strategies, such as integrated coastal zone management, to mitigate the adverse health effects of heatwaves in Karachi’s vulnerable population.

关键词： IPCC Heat Wave Heat Index PMD

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DeBERTa-GRU: Sentiment Analysis for Large Language Model

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Computers, Materials & Continua 2024年第6期79卷 4219-4236页

作者： Adel Assiri Abdu Gumaei Faisal mehmood Touqeer Abbas Sami Ullah Department of Informatics for Business College of BusinessKing Khalid UniversityAbha61421Saudi Arabia Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou450001China Department of Computer Science and Technology Beijing University of Chemical TechnologyBeijing100029China Department of Computer Science Government College University FaisalabadFaisalabadPunjab38000Pakistan

Modern technological advancements have made social media an essential component of daily *** media allow individuals to share thoughts,emotions,and *** analysis plays the function of evaluating whether the sentiment of the text is positive,negative,neutral,or any other personal emotion to understand the sentiment context of the *** analysis is essential in business and society because it impacts strategic *** analysis involves challenges due to lexical variation,an unlabeled dataset,and text distance *** execution time increases due to the sequential processing of the sequence ***,the calculation times for the Transformer models are reduced because of the parallel *** study uses a hybrid deep learning strategy to combine the strengths of the Transformer and Sequence models while ignoring their *** particular,the proposed model integrates the Decoding-enhanced with Bidirectional Encoder Representations from Transformers(BERT)attention(DeBERTa)and the Gated Recurrent Unit(GRU)for sentiment *** the Decoding-enhanced BERT technique,the words are mapped into a compact,semantic word embedding space,and the Gated Recurrent Unit model can capture the distance contextual semantics *** proposed hybrid model achieves F1-scores of 97%on the Twitter Large Language Model(LLM)dataset,which is much higher than the performance of new techniques.

关键词： DeBERTa GRU Naive Bayes LSTM sentiment analysis large language model

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Leveraging Augmented Reality,Semantic-Segmentation,and VANETs for Enhanced Driver’s Safety Assistance

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Computers, Materials & Continua 2024年第1期78卷 1443-1460页

作者： Sitara Afzal Imran Ullah Khan Irfan mehmood Jong Weon Lee Mixed Reality and Interaction Lab Department of SoftwareSejong UniversitySeoul05006Korea Faculty of Engineering and Digital Technologies School of Computer ScienceAI and ElectronicsUniversity of BradfordBradfordUK

Overtaking is a crucial maneuver in road transportation that requires a clear view of the road ***,limited visibility of ahead vehicles can often make it challenging for drivers to assess the safety of overtaking maneuvers,leading to accidents and *** this paper,we consider atrous convolution,a powerful tool for explicitly adjusting the field-of-view of a filter as well as controlling the resolution of feature responses generated by Deep Convolutional Neural Networks in the context of semantic image *** article explores the potential of seeing-through vehicles as a solution to enhance overtaking ***-through vehicles leverage advanced technologies such as cameras,sensors,and displays to provide drivers with a real-time view of the vehicle ahead,including the areas hidden from their direct line of *** address the problems of safe passing and occlusion by huge vehicles,we designed a see-through vehicle system in this study,we employed a windshield display in the back car together with cameras in both *** server within the back car was used to segment the car,and the segmented portion of the car displayed the video from the front *** see-through system improves the driver’s field of vision and helps him change lanes,cross a large car that is blocking their view,and safely overtake other *** network was trained and tested on the Cityscape dataset using semantic *** transparent technique will instruct the driver on the concealed traffic situation that the front vehicle has *** our findings,we have achieved 97.1% *** article also discusses the challenges and opportunities of implementing see-through vehicles in real-world scenarios,including technical,regulatory,and user acceptance factors.

关键词： Overtaking safety augmented reality VANET V2V deep learning

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