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Custom emoji based emotion recognition system for dynamic business webpages

International Journal of Intelligent Computing and Cybernetics 2022年第4期15卷 497-509页

作者： Fatima Isiaka zainab Adamu Computer Science Sheffield Hallam UniversitySheffieldUK Ahmadu Bello University ZariaNigeria

Purpose-One of the contributions of artificial intelligent(AI)in modern technology is emotion recognition which is mostly based on facial expression and modification of its inference *** facial recognition scheme is mostly built to understand user expression in an online business webpage on a marketing site but has limited abilities to recognise elusive *** basic emotions are expressed when interrelating and socialising with other personnel *** most times,studying how to understand user expression is often a most tedious task,especially the subtle *** emotion recognition system can be used to optimise and reduce complexity in understanding users’subconscious thoughts and reasoning through their pupil ***/methodology/approach-This paper demonstrates the use of personal computer(PC)webcam to read in eye movement data that includes pupil changes as part of distinct user attributes.A custom eye movement algorithm(CEMA)is used to capture users’activity and record the data which is served as an input model to an inference engine(artificial neural network(ANN))that helps to predict user emotional response conveyed as emoticons on the ***-The result from the error in performance shows that ANN is most adaptable to user behaviour prediction and can be used for the system’s modification *** limitations/implications-One of the drawbacks of the analytical tool is its inability in some cases to set some of the emoticons within the boundaries of the visual field,this is a limitation to be tackled within subsequent runs with standard ***/value-The originality of the proposed model is its ability to predict basic user emotional response based on changes in pupil size between average recorded baseline boundaries and convey the emoticons chronologically with the gaze points.

关键词： AI Static business webpages Artificial neural network Emotion recognition system Pupil changes User expression Eye movement behaviour

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Lacunary Generating Functions of Hybrid Type Polynomials in Viewpoint of Symbolic Approach

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Computer Modeling in Engineering & Sciences 2022年第2期130卷 903-921页

作者： Nusrat Raza Umme zainab Serkan Araci Mathematics Section Women’s CollegeAligarh Muslim UniversityAligarh202002India Department of Mathematics AligarhMuslim UniversityAligarh202002India Department of Economics Faculty of EconomicsAdministrative of Social SciencesHasan Kalyoncu UniversityGaziantepTR-27410Turkey

In this paper,we introduce mon-symbolic method to obtain the generating functions of the hybrid class of Hermite-associated Laguerre and its associated *** obtain the series definitions of these hybrid special ***,we derive the double lacunary generating functions of the Hermite-Laguerre polynomials and the Hermite-Laguerre-Wright ***,we find multiplicative and derivative operators for the Hermite-Laguerre-Wright polynomials which helps to find the symbolic differential equation of the Hermite-Laguerre-Wright *** concluding remarks are also given.

关键词： Hermite-laguerre polynomials laguerre-wright polynomials hermite-laguerre-wright polynomials hermite-mittag-leffler functions

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Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

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Computers, Materials & Continua 2022年第8期72卷 3719-3749页

作者： Mousa Al-Akhras zainab Darwish Samer Atawneh Mohamed Habib College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia King Abdullah II School for Information Technology The University of JordanAmman11942Jordan Faculty of Engineering Port Said UniversityPort Said42523Egypt

Association rules’learning is a machine learning method used in finding underlying associations in large *** intentionally or unintentionally present,noise in training instances causes overfitting while building the classifier and negatively impacts classification *** paper uses instance reduction techniques for the datasets before mining the association rules and building the *** reduction techniques were originally developed to reduce memory requirements in instance-based *** paper utilizes them to remove noise from the dataset before training the association rules *** experiments were conducted to assess the accuracy of association rules with different instance reduction techniques,namely:DecrementalReduction Optimization Procedure(DROP)3,DROP5,ALL K-Nearest Neighbors(ALLKNN),Edited Nearest Neighbor(ENN),and Repeated Edited Nearest Neighbor(RENN)in different noise *** show that instance reduction techniques substantially improved the average classification accuracy on three different noise levels:0%,5%,and 10%.The RENN algorithm achieved the highest levels of accuracy with a significant improvement on seven out of eight used datasets from the University of California Irvine(UCI)machine learning *** improvements were more apparent in the 5%and the 10%noise *** RENN was applied,the average classification accuracy for the eight datasets in the zero-noise test enhanced from 70.47%to 76.65%compared to the original *** average accuracy was improved from 66.08%to 77.47%for the 5%-noise case and from 59.89%to 77.59%in the 10%-noise *** confidence was also reported in building the association rules when RENN was *** above results indicate that RENN is a good solution in removing noise and avoiding overfitting during the construction of the association rules classifier,especially in noisy domains.

关键词： Association rules classification instance reduction techniques classification overfitting noise data cleansing

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Intrusion Detection System Through Deep Learning in Routing MANET Networks

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Intelligent Automation & Soft Computing 2023年第7期37卷 269-281页

作者： zainab Ali Abbood DoguÇagdaşAtilla Çagatay Aydin Department Electrical and Computer Engineering Altinbas UniversityIstanbulTurkey Department Computer Technology Engineering Al-Esraa UniversityBaghdadIraq Electric Autonomous and Unmanned Vehicles Application and Research CentreAltinbas UniversityIstanbulTurkey Faculty of Engineering and Architecture Altinbas UniversityIstanbulTurkey Department Electrical and Electronics Engineering Ege UniversityIzmirTurkey

Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in *** reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security *** protecting MANETs from attack,encryption and authentication schemes have their ***,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the *** are a secondary deﬁance system for mobile ad-hoc networks *** since they monitor network trafﬁc and report anything ***,many scientists have employed deep neural networks(DNNs)to address intrusion detection *** paper used MANET to recognize com-plex patterns by focusing on security standards through efﬁciency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent *** with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)*** results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the ti

关键词： ARP CBPNN CNN DNN DL E2E FFNN IDS ML MANET security

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Numerical Investigation of the Pulsatile Flow of Viscous Fluid in Constricted Wall Channel with Thermal Radiation

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Advances in Applied Mathematics and Mechanics 2023年第4期15卷 1001-1022页

作者： Amjad Ali zainab Bukhari Hamayun Farooq Zaheer Abbas Centre for Advanced Studies in Pure and Applied Mathematics(CASPAM) Bahauddin Zakariya UniversityMultan 60800Pakistan Department of Mathematics Islamia University of BahawalpurBahawalpur 63100Pakistan

The main theme of the current article is to investigate the heat transfer in the pulsatile flow of an electrically conducting viscous fluid in a constricted channel under the effect of the magnetic field and thermal *** unsteady governing equations simplified for low conducting fluids are solved numerically by finite difference method using stream-vorticity function *** influence of the flow parameters such as the Hartmann number(magnetic parameter),Strouhal number(flow pulsation parameter),Prandtl number,and radiation parameter is studied on the relevant flow *** influence of different emerging parameters on the skin friction coefficient and Nusselt number are examined,as *** general,the profiles are observed to exhibit a relatively more regular pattern upstream of the construction than that downstream of the constriction.

关键词： Constricted channel pulsatileflow thermal radiation magneticﬁeld Strouhal number Prandtl number

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Emotion detection on webpages using biosensors integrated to a window-based dynamic control system

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International Journal of Intelligent Computing and Cybernetics 2022年第2期15卷 277-301页

作者： Fatima Isiaka Salihu Aish Abdulkarim Kassim Mwitondi zainab Adamu Computer Science Sheffield Hallam UniversitySheffieldUK Federal University Dutse DutseNigeria Computing Department Sheffield Hallam UniversitySheffieldUK Ahmadu Bello University ZariaNigeria

Purpose-Detecting emotion on user experience of web applications and browsing is important in many *** designers and developers find such approach quite useful in enhancing navigational features of webpages,and biomedical personnel regularly use computer simulations to monitor and control the behaviour of *** the other hand,law enforcement agents rely on human physiological functions to determine the likelihood of falsehood in *** often,online user experience is studied via tangible measures such as task completion time,surveys and comprehensive tests from which data attributes are *** of users’emotion and behaviour in some of these cases depends mostly on task completion time and number of clicks per given time ***,such approaches are generally subjective and rely heavily on distributional assumptions making the results prone to recording ***/methodology/approach-The authors propose a novel method-a window dynamic control system that addresses the foregoing *** data were obtained from laboratory experiments during which forty-four volunteers had their synchronised physiological readings,skin conductance response(SCR),skin temperature(ST),eye movement behaviour and users’activity attributes taken using *** windowbased dynamic control system(PHYCOB I)is integrated to the biosensor which collects secondary data attributes from these synchronised physiological readings and uses them for two *** both detection of optimal emotional responses and users’stress *** method’s novelty derives from its ability to integrate physiological readings and eye movement records to identify hidden correlates on a ***-Results show that the control system detects basic emotions and outperforms other conventional models in terms of both accuracy and reliability,when subjected to model comparison that is,the average recoverable natural structures for the three models with

关键词： Skin conductance response Skin temperature Eye tracker sensors Human physiological functions Online behaviour Dynamic control system

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The flow behavior of powder stearin-based methyl ester sulfonates and the effect of glidant

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Particuology 2023年第9期80卷 148-156页

作者： Zulina Abd Maurad Luqman Chuah Abdullah Mohd Shamsul Anuar Nor Nadiah Abdul Karim Shah zainab Idris Malaysian Palm Oil Board 6Persiaran InstitusiBandar Baru Bangi43000SelangorMalaysia Department of Chemical and Environmental Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdangSelangor43400Malaysia Department of Process and Food Technology Faculty of EngineeringUniversiti Putra MalaysiaSerdangSelangor43400Malaysia

The preparation and behavior of powder stearin-based methyl ester sulfonates(MES)with the addition of builder as a glidant agent was *** is an anionic surfactant and its performance is equivalent to petroleum-based linear alkylbenzene sulfonates(LAS),the workhorses of the detergent *** the same time,zeolites or soda ash were the alternative builders for non-phosphate-based *** behavior of powder MES properties was measured in terms of morphology,particle size,cohesion,caking,and *** that,these palm stearin-based MES of carbon chain 16–18 with ratios of 98:2,80:20,and 60:40 in flakes were ground using a high shear mixer by 23,000 rpm to produce powder *** the particle size of MES powder can reduce the powder's cohesion,caking,and *** addition of zeolite or soda ash as a glidant in powdered MES can improve the caking *** high stearic in MES greatly influenced getting fine particle powders and required more glidant *** powder MES with excellent powder characteristics can perform well as a bio-based cleaning product.

关键词： Methyl ester sulfonates Caking Compaction Cohesion Glidant

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Improved Transient Search Optimization with Machine Learning Based Behavior Recognition on Body Sensor Data

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Computers, Materials & Continua 2023年第5期75卷 4593-4609页

作者： Baraa Wasfi Salim Bzar Khidir Hussan zainab Salih Ageed Subhi R.M.Zeebaree ITM Department Technical College of AdministrationDuhok Polytechnic UniversityDuhokIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Recently,human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare *** though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs,physical human action recognition(HAR)through body sensors gives useful information about the lifestyle and functionality of an *** article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based BehaviorRecognition(ITSOMLBR)technique using body sensor *** presented ITSOML-BR technique collects data from different body sensors namely electrocardiography(ECG),accelerometer,and *** addition,the ITSOML-BR technique extract features like variance,mean,skewness,and standard ***,the presented ITSOML-BR technique executes a micro neural network(MNN)which can be employed for long term healthcare monitoring and ***,the parameters related to the MNN model are optimally selected via the ITSO *** experimental result analysis of the ITSOML-BR technique is tested on the MHEALTH *** comprehensive comparison study reported a higher result for the ITSOMLBR approach over other existing approaches with maximum accuracy of 99.60%.

关键词： Behavior recognition transient search optimization machine learning healthcare sensors wearables

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Modified Wild Horse Optimization with Deep Learning Enabled Symmetric Human Activity Recognition Model

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Computers, Materials & Continua 2023年第5期75卷 4009-4024页

作者： Bareen Shamsaldeen Tahir zainab Salih Ageed Sheren Sadiq Hasan Subhi R.M.Zeebaree Accounting Department College of Administration and EconomicsUniversity of DuhokDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Traditional indoor human activity recognition(HAR)is a timeseries data classification problem and needs feature ***,considerable attention has been given to the domain ofHARdue to the enormous amount of its real-time uses in real-time applications,namely surveillance by authorities,biometric user identification,and health monitoring of older *** extensive usage of the Internet of Things(IoT)and wearable sensor devices has made the topic of HAR a vital subject in ubiquitous and mobile *** more commonly utilized inference and problemsolving technique in the HAR system have recently been deep learning(DL).The study develops aModifiedWild Horse Optimization withDLAided Symmetric Human Activity Recognition(MWHODL-SHAR)*** major intention of the MWHODL-SHAR model lies in recognition of symmetric activities,namely jogging,walking,standing,sitting,*** the presented MWHODL-SHAR technique,the human activities data is pre-processed in various stages to make it compatible for further processing.A convolution neural network with an attention-based long short-term memory(CNNALSTM)model is applied for activity *** MWHO algorithm is utilized as a hyperparameter tuning strategy to improve the detection rate of the CNN-ALSTM *** experimental validation of the MWHODL-SHAR technique is simulated using a benchmark *** extensive comparison study revealed the betterment of theMWHODL-SHAR technique over other recent approaches.

关键词： Human activity recognition symmetry deep learning machine learning pattern recognition time series classification

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Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3677-3693页

作者： Mohammed Jasim Mohammed Jasim Bzar Khidir Hussan Subhi R.M.Zeebaree zainab Salih Ageed Engineering College Al-Kitab UniversityKirkukIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq

The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various *** specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer *** is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss *** automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical ***,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative *** manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)*** NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp *** accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing ***,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO ***,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC *** comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.

关键词： Biomedical imaging artificial intelligence colonic polyp classification medical image classification computer-aided diagnosis

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