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From Social Media to Ballot Box:Leveraging Location-Aware Sentiment Analysis for Election Predictions

Computers, Materials & Continua 2023年第12期77卷 3037-3055页

作者： asif khan Nada Boudjellal Huaping Zhang Arshad Ahmad Maqbool khan School of Computer Science and Technology Beijing Institute of TechnologyBeijing100081China The Faculty of New Information and Communication Technologies University Abdel-Hamid Mehri Constantine 2Constantine25000Algeria Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan

Predicting election outcomes is a crucial undertaking,and various methods are employed for this purpose,such as traditional opinion polling,and social media ***,traditional polling approaches often struggle to capture the intricate nuances of voter sentiment at local levels,resulting in a limited depth of analysis and *** light of this challenge,this study focuses on predicting elections at the state/regional level along with the country level,intending to offer a comprehensive analysis and deeper insights into the electoral *** achieve this,the study introduces the Location-Based Election Prediction Model(LEPM),which utilizes social media data,specifically Twitter,and integrates location-aware sentiment analysis techniques at both the state/region and country *** predicts the support and opposing strength of each political party/*** determine the location of users/voters who have not disclosed their location information in tweets,the model utilizes a Voter Location Detection(VotLocaDetect)approach,which leverages recent tweets/*** sentiment analysis techniques employed in this study include rule-based sentiment analysis,Valence Aware Dictionary and Sentiment Reasoner(VADER)as well as transformers-based sentiment analysis such as Bidirectional Encoder Representations from Transformers(BERT),BERTweet,and Election based BERT(ElecBERT).This study uses the 2020 United States(US)Presidential Election as a case *** applying the LEPM model to the election,the study demonstrates its ability to accurately predict outcomes in forty-one states,achieving an 0.84 accuracy rate at the state ***,at the country level,the LEPM model outperforms traditional polling *** a low Mean Absolute Error(MAE)of 0.87,the model exhibits more precise predictions and serves as a successful alternative to conventional polls and other *** the extensive social media data,the LEPM model provides nuanc

关键词： Sentiment analysis big data machine learning election predictions social media analysis

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Improving Sentiment Analysis in Election-Based Conversations on Twitter with ElecBERT Language Model

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Computers, Materials & Continua 2023年第9期76卷 3345-3361页

作者： asif khan Huaping Zhang Nada Boudjellal Arshad Ahmad Maqbool khan School of Computer Science and Technology Beijing Institute of TechnologyBeijing100081China The Faculty of New Information and Communication Technologies University Abdel-Hamid Mehri Constantine 2Constantine25000Algeria Department of IT and Computer Science Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripur22620Pakistan

Sentiment analysis plays a vital role in understanding public opinions and sentiments toward various *** recent years,the rise of social media platforms(SMPs)has provided a rich source of data for analyzing public opinions,particularly in the context of election-related ***,sentiment analysis of electionrelated tweets presents unique challenges due to the complex language used,including figurative expressions,sarcasm,and the spread of *** address these challenges,this paper proposes Election-focused Bidirectional Encoder Representations from Transformers(ElecBERT),a new model for sentiment analysis in the context of election-related ***-related tweets pose unique challenges for sentiment analysis due to their complex language,sarcasm,*** is based on the Bidirectional Encoder Representations from Transformers(BERT)language model and is fine-tuned on two datasets:Election-Related Sentiment-Annotated Tweets(ElecSent)-Multi-Languages,containing 5.31 million labeled tweets in multiple languages,and ElecSent-English,containing 4.75million labeled tweets in *** outperforms othermachine learning models such as Support Vector Machines(SVM),Na飗e Bayes(NB),and eXtreme Gradient Boosting(XGBoost),with an accuracy of 0.9905 and F1-score of 0.9816 on ElecSent-Multi-Languages,and an accuracy of 0.9930 and F1-score of 0.9899 on *** performance of differentmodels was compared using the 2020 United States(US)Presidential Election as a case *** ElecBERT-English and ElecBERT-Multi-Languages models outperformed BERTweet,with the ElecBERT-English model achieving aMean Absolute Error(MAE)of *** paper presents a valuable contribution to sentiment analysis in the context of election-related tweets,with potential applications in political analysis,social media management,and policymaking.

关键词： Sentiment analysis social media election prediction machine learning transformers

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Modified approximation and error estimation for King’s type(p,q)-BBH operators

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Applied Mathematics(A Journal of Chinese Universities) 2022年第2期37卷 199-212页

作者： M.Mursaleen Mohd.Ahasan asif khan Department of Medical Research China Medical University HospitalChina Medical University(Taiwan)TaichungTaiwanChina Department of Mathematics Aligarh Muslim UniversityAligarh 202002India Department of Mathematics School of Basic and Applied SciencesGalgotias UniversityGreater Noida-203201India

In this paper,the King’s type modification of(p,q)-Bleimann-Butzer and Hahn operators is *** results based on Korovkin’s approximation theorem for these new operators are *** the help of modulus of continuity and the Lipschitz type maximal functions,the rate of convergence for these new operators are *** is shown that the King’s type modification have better rate of convergence,flexibility than classical(p,q)-BBH operators on some ***,for comparisons of the operators,we presented some graphical examples and the error estimation in the form of tables through MATLAB(R2015a)

关键词： (p,q)-integers (p,q)-Bleimann-Butzer and Hahn operators King's type modi cation modulus of continuity Holder inequality and Lipschitz functions

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Expression profiling of transgenes(Cry1Ac and Cry2A) in cotton genotypes under different genetic backgrounds

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Journal of Integrative Agriculture 2022年第10期21卷 2818-2832页

作者： Kashif NOOR Hafiza Masooma Naseer CHEEMA asif Ali khan Rao Sohail Ahmad khan Department of Plant Breeding and Genetics University of AgricultureFaisalabad 38040Pakistan Institute of Plant Breeding and Biotechnology Muhammad Nawaz Shareef University of AgricultureMultan 60000Pakistan Center of Agricultural Biochemistry and Biotechnology University of AgricultureFaisalabad 38040Pakistan

Transgenic cotton carrying the CrylAc gene has revolutionized insect pest control since its adoption,although the development of resistance in insect pests has reduced its *** 10 years of cultivating Bacillus thuringiensis(Bt)cotton with a single Cry1 Ac gene,growers are on the verge of adopting Bt cotton that carries the double gene(Cry1 Ac+Cry2 A)due to its better effectiveness against insect ***,the current study was designed to evaluate the role of each gene in the effectiveness of Bt cotton carrying the double *** expression levels of the Cry1 Ac and Cry2 A genes were evaluated in the leaves of 10 genotypes(2 parents and 8 Fhybrids)at 30 days after sowing(DAS),while samples of leaves,bolls and flowers were taken from the upper and lower canopies at 70 and 110 *** Fhybrids were developed through reciprocal crosses between two Bt(CKC-1,CKC-2)and two non-Bt(MNH-786,FH-942)*** differential expression of transgenes was evaluated through Enzyme Linked Immuno-Sorbent Assay(ELISA).The results showed that the MNH786 xCKC-1 hybrid had the highest concentrations of Cry1 Ac gene at30 DAS(3.08μg g^(-1))and 110 DAS(1.01μg g^(-1))in *** contrast,the CKC-2 xMNH-786 hybrid showed the lowest concentrations of Cry1 Ac gene at 30 DAS(2.30μg g^(-1))and 110 DAS(0.86μg g^(-1)).The Fhybrid FH-942×CKC-2 showed the highest concentrations of Cry2 A gene at 30 DAS(8.39μg g^(-1))and 110 DAS(7.74μg g^(-1))in leaves,while the CKC-1 xMNH-786 hybrid expressed the lowest concentrations of Cry2 A gene at 30 DAS(7.10μg g^(-1))and 110 DAS(8.31μg g^(-1)).A comparison between the two stages of plant growth showed that leaves had the highest concentrations at 30 DAS,whereas the lowest concentrations were observed at 110 DAS for both genes in *** the expression pattern was compared between various plant parts in genotype CKC-2,it was found that leaves had higher concentrations of Cry1 Ac(3.12μg g^(-1))and Cry2 A(8.31μg g^(-1))at 70 DAS,followed by bolls

关键词： transgenic cotton breeding transgene expression double gene insect resistance

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A spatial regression modeling framework for examining relationships between the built environment and pedestrian crash occurrences at macroscopic level:A study in a developing country context

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Geography and Sustainability 2022年第4期3卷 312-324页

作者： Niaz Mahmud Zafri asif khan Department of Urban and Regional Planning Bangladesh University of Engineering and Technology(BUET)-1000Bangladesh

Researchers have been trying to identify the contributory factors behind pedestrian crash occurrences through studies at both microscopic and macroscopic ***,built environment-related factors have primarily been examined in developed countries,resulting in a limited understanding of the phenomenon in the context of developing ***,these studies mostly used global regression models,which failed to incorporate spatial autocorrelation and spatial ***,some of these studies applied spatial regression models randomly without following a comprehensive logical framework behind their *** study aimed to develop a comprehensive spatial regression modeling framework to examine the relationships between pedestrian crash occurrences and the built environment at the macroscopic level in a megacity,Dhaka,the capital of a developing country:*** secondary pedestrian crash data,the study applied one global non-spatial model,two global spatial regression models,and two local spatial regression models following a comprehensive spatial regression modeling *** factors which significantly contributed to pedestrian crash occurrences in Dhaka were employed person density,mixed and recreational land use density,primary road density,major intersection density,and share of non-motorized *** for the last factor,all the other ones were positively related to pedestrian crash *** the five models used in this study,the multiscale geographically weighted regression(MGWR)performed the best as it calibrated each local relationship with a distant spatial scale *** findings and recommendations presented in this study would be useful for reducing pedestrian crashes and choosing the appropriate modeling technique for crash analysis.

关键词： Built environment Geographically weighted regression Spatial autocorrelation Spatial heterogeneity MGWR

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Evaluating Security of Big Data Through Fuzzy Based Decision-Making Technique

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Computer Systems Science & Engineering 2023年第1期44卷 859-872页

作者： Fawaz Alassery Ahmed Alzahrani asif Irshad khan Kanika Sharma Masood Ahmad Raees Ahmad khan Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Applications Mangalmay Institute of Engineering&TechnologyGreater Noida201310Uttar PradeshIndia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia

In recent years,it has been observed that the disclosure of information increases the risk of *** restricting the accessibility of information,providing security is ***,there is a demand for time tofill the gap between security and accessibility of *** fact,security tools should be usable for improving the security as well as the accessibility of *** security and accessibility are not directly influenced,some of their factors are indirectly influenced by each *** play an important role in bridging the gap between security and *** this paper,we identify the key attributes of accessibility and security that impact directly and indirectly on each other,such as confidentiality,integrity,availability,and *** significance of every attribute on the basis of obtained weight is important for its effect on security during the big data security life cycle *** calculate the proposed work,researchers utilised the Fuzzy Analytic Hierarchy Process(Fuzzy AHP).Thefindings show that the Fuzzy AHP is a very accurate mechanism for determining the best security solution in a real-time healthcare *** study also looks at the rapidly evolving security technologies in healthcare that could help improve healthcare services and the future prospects in this area.

关键词： Information security big data big data security life cycle fuzzy AHP

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Condition Monitoring and Maintenance Management with Grid-Connected Renewable Energy Systems

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Computers, Materials & Continua 2022年第8期72卷 3999-4017页

作者： Md.Mottahir Alam Ahteshamul Haque Mohammed Ali khan Nebras M.Sobahi Ibrahim Mustafa Mehedi asif Irshad khan Department of Electrical and Computer Engineering(ECE) King Abdulaziz UniversityJeddah 21589Saudi Arabia Advance Power Electronics Research Lab Department of Electrical EngineeringJamia Millia IslamiaNew Delhi 110025India Department of Electrical Power Engineering Faculty of Electrical Engineering and CommunicationBrno University of TechnologyBrno 61600Czech Republic Center of Excellence in Intelligent Engineering Systems(CEIES) King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia

The shift towards the renewable energy market for carbon-neutral power generation has encouraged different governments to come up with a plan of *** with the endorsement of renewable energy for harsh environmental conditions like sand dust and snow,monitoring and maintenance are a few of the prime *** problems were addressed widely in the literature,but most of the research has drawbacks due to long detection time,and high misclassification *** to overcome these drawbacks,and to develop an accurate monitoring approach,this paper is motivated toward the understanding of primary failure concerning a grid-connected photovoltaic(PV)system and highlighted along with a brief overview on existing fault detection *** on the drawback a data-driven machine learning approach has been used for the identification of fault and indicating the maintenance unit regarding the operation and maintenance ***,the system was tested with a 4 kWp grid-connected PV system,and a decision tree-based algorithm was developed for the identification of a *** results identified 94.7%training accuracy and 14000 observations/sec prediction speed for the trained classifier and improved the reliability of fault detection nature of the grid-connected PV operation.

关键词： Fault detection machine learning fault ride through

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Cyber Security Analysis and Evaluation for Intrusion Detection Systems

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Computers, Materials & Continua 2022年第7期72卷 1765-1783页

作者： Yoosef B.Abushark asif Irshad khan Fawaz Alsolami Abdulmohsen Almalawi Md Mottahir Alam Alka Agrawal Rajeev Kumar Raees Ahmad khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028India

Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the *** learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security *** is crucial in offering a proactive security system in the field of *** real time,cybersecurity protects information,information systems,and networks from *** the recent decade,several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity *** an increasing rate,intruders are breaching information *** detection,software vulnerability diagnosis,phishing page identification,denial of service assaults,and malware identification are the foremost cyber-security concerns that require efficient *** have tried a variety of approaches to address the present cybersecurity obstacles and *** a similar vein,the goal of this research is to assess the idealness of machine learning-based intrusion detection systems under fuzzy conditions using a Multi-Criteria Decision Making(MCDM)-based Analytical Hierarchy Process(AHP)and a Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS).Fuzzy sets are ideal for dealing with decision-making scenarios in which experts are unsure of the best course of *** projected work would support practitioners in identifying,prioritising,and selecting cybersecurityrelated attributes for intrusion detection systems,allowing them to design more optimal and effective intrusion detection systems.

关键词： Cybersecurity machine learning AHP-TOPSIS fuzzy logic intrusion detection systems

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A Novel Krill Herd Based Random Forest Algorithm for Monitoring Patient Health

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Computers, Materials & Continua 2023年第5期75卷 4553-4571页

作者： Md.Moddassir Alam Md Mottahir Alam Muhammad Moinuddin Mohammad Tauheed Ahmad Jabir Hakami Anis Ahmad Chaudhary asif Irshad khan Tauheed khan Mohd Department of Health Information Management and Technology University of Hafr Al-BatinSaudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing AbdulazizJeddah21589Saudi Arabia Center of Excellence in Intelligent Engineering Systems King Abdul Aziz UniversityJeddahSaudi Arabia College of Medicine King Khalid UniversityAbhaSaudi Arabia Department of Physics College of ScienceJazan UniversityP.O.Box.114Jazan45142Saudi Arabia Department of Biology College of ScienceImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11623Saudi Arabia Computer Science Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Math and Computer Science Augustana CollegeIL61201United States

Artificial Intelligence(AI)is finding increasing application in healthcare *** learning systems are utilized for monitoring patient health through the use of IoT sensor,which keep track of the physiological state by way of various health ***,early detection of any disease or derangement can aid doctors in saving patients’***,there are some challenges associated with predicting health status using the common algorithms,such as time requirements,chances of errors,and improper *** propose an Artificial Krill Herd based on the Random Forest(AKHRF)technique for monitoring patients’health and eliciting an optimal prescription based on their health *** begin with,various patient datasets were collected and trained into the system using IoT *** a result,the framework developed includes four processes:preprocessing,feature extraction,classification,and result ***,preprocessing removes errors,noise,and missing values from the dataset,whereas feature extraction extracts the relevant ***,in the classification layer,we updated the fitness function of the krill herd to classify the patient’s health status and also generate a *** found that the results fromthe proposed framework are comparable to the results from other state-of-the-art techniques in terms of sensitivity,specificity,Area under the Curve(AUC),accuracy,precision,recall,and F-measure.

关键词： Healthcare system health monitoring clinical decision support internet of things artificial intelligence machine learning diagnosis

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A Preliminary Study and Characterization of Nasir Abad Hunza Marble Deposit Gilgit Baltistan

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International Journal of Geosciences 2023年第5期14卷 467-479页

作者： Shahid khan asif khan Karakoram International University Gilgit-Baltistan Pakistan

Marble is widely used in construction industry mainly in interior & exterior design of buildings due to its resilient physical, chemical & mechanical properties. The diverse geology of Gilgit Baltistan has naturally endowed this region with different varieties of marble deposits. These marble deposits need proper characterization to ensure their proper use in the construction industry. This research aims to conduct a preliminary study for the characterization of the Nasir Abad Hunza marble deposit. Samples from said deposit were subjected to different tests to study its chemical, physical and mechanical properties. Results of XRF analysis reveal that the deposit under study is dolomitic. The comparison of different physical properties of deposits with standard values confirms its originality. However, high variation in the strength of core samples was observed, which could result from incomplete crystallization by metamorphism. This variation in the strength of samples suggests strength-based definitions of deposit domains to propose the use of each domain separately.

关键词： Hunza Gilgit Baltistan Marble Compressive Strength (U.C.S.)

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