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Intelligent modulation Recognition of Communication Signal for Next-Generation 6G Networks

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Computers, materials & Continua 2023年第3期74卷 5723-5740页

作者： mrim m.a.nfia. Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

In recent years,the need for a fast,efficient and a reliable wireless network has increased *** 5G networks have already been tested while a few are in the early stages of *** noncooperative communication scenarios,the recognition of digital signal modulations assists people in identifying the communication targets and ensures an effective management over *** recent advancements in both machine Learning(mL)and Deep Learning(DL)models demand the development of effective modulation recognition models with self-learning *** this background,the current research article designs aDeep Learning enabled Intelligent modulation Recognition of Communication Signal(DLImR-CS)technique for next-generation *** aim of the proposed DLImR-CS technique is to classify different kinds of digitally-modulated *** addition,the fractal feature extraction process is appliedwith the help of the Sevcik Fractal Dimension(SFD)***,the extracted features are fed into the Deep Variational Autoencoder(DVAE)model for the classification of the modulated *** order to improve the classification performance of the DVAE model,the Tunicate Swarm Algorithm(TSA)is used to finetune the hyperparameters involved in DVAE model.A wide range of simulations was conducted to establish the enhanced performance of the proposed DLImR-CS *** experimental outcomes confirmed the superior recognition rate of the DLImR-CS model over recent state-of-the-art methods under different evaluation parameters.

关键词： 6G networks communication signal modulation recognition deep learning machine learning parameter optimization

Lightning Search Algorithm with Deep Transfer Learning-Based Vehicle Classification

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Computers, materials & Continua 2023年第3期74卷 6505-6521页

作者： mrim m.a.nfia. Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

There is a drastic increase experienced in the production of vehicles in recent years across the *** this scenario,vehicle classification system plays a vital part in designing Intelligent Transportation Systems(ITS)for automatic highway toll collection,autonomous driving,and traffic ***,computer vision and pattern recognition models are useful in designing effective vehicle classification *** these models are trained using a small number of hand-engineered features derived fromsmall ***,such models cannot be applied for real-time road traffic *** developments in Deep Learning(DL)-enabled vehicle classification models are highly helpful in resolving the issues that exist in traditional *** this background,the current study develops a Lightning Search Algorithm with Deep Transfer Learning-based Vehicle Classification model for ITS,named LSADTL-VCITS *** key objective of the presented LSADTL-VCITS model is to automatically detect and classify the types of *** accomplish this,the presented LSADTL-VCITS model initially employs You Only Look Once(YOLO)-v5 object detector with Capsule Network(CapsNet)as baseline *** addition,the proposed LSADTL-VCITS model applies LSA with multilayer Perceptron(mLP)for detection and classification of the *** performance of the proposed LSADTL-VCITS model was experimentally validated using benchmark dataset and the outcomes were examined under several *** experimental outcomes established the superiority of the proposed LSADTL-VCITS model compared to existing approaches.

关键词： Intelligent transportation system object detection vehicle classification deep learning machine learning

Deep Learning-Based Sign Language Recognition for Hearing and Speaking Impaired People

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Intelligent Automation & Soft Computing 2023年第5期36卷 1653-1669页

作者： mrim m.a.nfia. Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Sign language is mainly utilized in communication with people who have hearing *** language is used to communicate with people hav-ing developmental impairments who have some or no interaction *** inter-action via Sign language becomes a fruitful means of communication for hearing and speech impaired persons.A Hand gesture recognition systemﬁnds helpful for deaf and dumb people by making use of human computer interface(HCI)and convolutional neural networks(CNN)for identifying the static indications of Indian Sign Language(ISL).This study introduces a shark smell optimization with deep learning based automated sign language recognition(SSODL-ASLR)model for hearing and speaking impaired *** presented SSODL-ASLR technique majorly concentrates on the recognition and classiﬁcation of sign lan-guage provided by deaf and dumb *** presented SSODL-ASLR model encompasses a two stage process namely sign language detection and sign lan-guage classiﬁ*** theﬁrst stage,the mask Region based Convolution Neural Network(mask RCNN)model is exploited for sign language ***-ondly,SSO algorithm with soft margin support vector machine(Sm-SVm)model can be utilized for sign language classiﬁ*** assure the enhanced classiﬁca-tion performance of the SSODL-ASLR model,a brief set of simulations was car-ried *** extensive results portrayed the supremacy of the SSODL-ASLR model over other techniques.

关键词： Sign language recognition deep learning shark smell optimization mask rcnn model disabled people

Fire Hawk Optimizer with Deep Learning Enabled Human Activity Recognition

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Computer Systems Science & Engineering 2023年第6期45卷 3135-3150页

作者： mohammed Alonazi mrim m.a.nfia. Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia

Human-Computer Interaction(HCI)is a sub-area within computer science focused on the study of the communication between people(users)and computers and the evaluation,implementation,and design of user interfaces for computer *** has accomplished effective incorporation of the human factors and software engineering of computing systems through the methods and concepts of cognitive *** is an aspect of HCI dedicated to guar-anteeing that human–computer communication is,amongst other things,efficient,effective,and sustaining for the ***,Human activity recognition(HAR)aim is to identify actions from a sequence of observations on the activities of subjects and the environmental *** vision-based HAR study is the basis of several applications involving health care,HCI,and video *** article develops a Fire Hawk Optimizer with Deep Learning Enabled Activ-ity Recognition(FHODL-AR)on HCI driven *** the presented FHODL-AR technique,the input images are investigated for the identification of different human *** feature extraction,a modified SqueezeNet model is intro-duced by the inclusion of few bypass connections to the SqueezeNet among Fire ***,the FHO algorithm is utilized as a hyperparameter optimization algorithm,which in turn boosts the classification *** detect and cate-gorize different kinds of activities,probabilistic neural network(PNN)classifier is *** experimental validation of the FHODL-AR technique is tested using benchmark datasets,and the outcomes reported the improvements of the FHODL-AR technique over other recent approaches.

关键词： Activity recognition fire hawks optimizer deep learning usability human computer interaction

Evaluation of NFC-Guidable System to manage Polypharmacy in Elderly Patients

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Computer Systems Science & Engineering 2022年第5期41卷 445-460页

作者： Khalid Alzahrani mrim.a.nfia. Department of Clinical Laboratories Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia

A complete and thorough understanding by patients of their prescriptions is one of the most critical components of a successful treatment *** unfamiliar with the intricacies of prescribed medication can cause serious health risks due to not adhering to prescription instructions or noting potential drug interactions,which can lead to life-threatening *** face communication barriers(including non-English speaking patients),lack of time,lack of knowledge,workload,and frequent interruption when dispensing medicines often preventing them from providing the necessary guidance to their *** minimize this risk,an NFC-Guidable polypharmacy system was developed integrating Near Field Technology(NFC)into prescription *** intention being,to automate prescription identification for elderly patients in hospitals and primary health care(PHC)centers where Arabic is their native language and patients have five or more prescriptions at a *** system provides prescription information such as name,expiration date based on the Islamic calendar,appropriate dosage,the correct time for a dose,contraindication,and other relevant instructions in *** objectives of the system are to improve patient safety and enhance the quality of prescription dispensing for elderly and non-English speaking *** evaluation study with polypharmacy elderly patients and pharmacists is conducted to understand the perception and acceptance of the system by both *** strengths and weaknesses of the system as well as suggestions for improvement from participants were also *** study results indicate that the system helps patients to avoid misuse of sensitive medication and authenticates their prescribed prescription drugs before taking *** system also assists pharmacists in improving the efficiency of dispensing medication and streamline ***,the application was well received by both patients and ***,NFC technol

关键词： NFC health elder patients pharmacists language

Bayes-Q-Learning Algorithm in Edge Computing for Waste Tracking

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Intelligent Automation & Soft Computing 2023年第5期36卷 2425-2440页

作者： D.Palanikkumar R.Ramesh Kumar mehedi masud mrim m.a.nfia. mohamed Abouhawwash Department of Computer Science and Engineering Dr.NGP Institute of TechnologyCoimbatore641048India Department of Information Technology Sri Krishna College of TechnologyCoimbatore641042India Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Department of mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

The major environmental hazard in this pandemic is the unhygienic dis-posal of medical *** wastage is not properly managed it will become a hazard to the environment and *** medical wastage is a major issue in the city,municipalities in the aspects of the environment,and *** efﬁcient supply chain with edge computing technology is used in managing medical *** supply chain operations include processing of waste collec-tion,transportation,and disposal of *** research works have been applied to improve the management of *** main issues in the existing techniques are ineffective and expensive and centralized edge computing which leads to failure in providing security,trustworthiness,and *** over-come these issues,in this paper we implement an efﬁcient Naive Bayes classiﬁer algorithm and Q-Learning algorithm in decentralized edge computing technology with a binary bat optimization algorithm(NBQ-BBOA).This proposed work is used to track,detect,and manage medical *** minimize the transferring cost of medical wastage from various nodes,the Q-Learning algorithm is *** accuracy obtained for the Naïve Bayes algorithm is 88%,the Q-Learning algo-rithm is 82%and NBQ-BBOA is 98%.The error rate of Root mean Square Error(RmSE)and mean Error(mAE)for the proposed work NBQ-BBOA are 0.012 and 0.045.

关键词： Binary bat algorithm naïve bayes supply chain edge medical wastage

Deep Transfer Learning Driven Automated Fall Detection for Quality of Living of Disabled Persons

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Computers, materials & Continua 2023年第3期74卷 6719-6736页

作者： Nabil Almalki mrim m.a.nfia. Fahd N.Al-Wesabi mesfer Alduhayyem Anwer mustafa Hilal manar Ahmed Hamza King Salman Center for Disability Research RiyadhSaudi Arabia Department of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of Science&ArtsKing Khaled UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

mobile communication and the Internet of Things(IoT)technologies have recently been established to collect data from human beings and the *** data collected can be leveraged to provide intelligent services through different *** is an extreme challenge to monitor disabled people from remote *** is because day-to-day events like falls heavily result in *** a person with disabilities,a fall event is an important cause of mortality and post-traumatic ***,detecting the fall events of disabled persons in smart homes at early stages is essential to provide the necessary support and increase their survival *** current study introduces a Whale Optimization Algorithm Deep Transfer Learning-DrivenAutomated Fall Detection(WOADTL-AFD)technique to improve the Quality of Life for persons with *** primary aim of the presented WOADTL-AFD technique is to identify and classify the fall events to help disabled *** attain this,the proposed WOADTL-AFDmodel initially uses amodified SqueezeNet feature extractor which proficiently extracts the feature *** addition,the WOADTLAFD technique classifies the fall events using an extreme Gradient Boosting(XGBoost)*** the presented WOADTL-AFD technique,the WOA approach is used to fine-tune the hyperparameters involved in the modified SqueezeNet *** proposedWOADTL-AFD technique was experimentally validated using the benchmark datasets,and the results confirmed the superior performance of the proposedWOADTL-AFD method compared to other recent approaches.

关键词： Quality of living disabled persons intelligent models deep learning fall detection whale optimization algorithm

IoT-Driven Optimal Lightweight RetinaNet-Based Object Detection for Visually Impaired People

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Computer Systems Science & Engineering 2023年第7期46卷 475-489页

作者： mesfer Alduhayyem mrim m.a.nfia. Nabil Almalki Fahd N.Al-Wesabi Anwer mustafa Hilal manar Ahmed Hamza Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia King Salman Center for Disability Research RiyadhAl-Hayātim 16273Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Department of Computer Science College of Science&ArtsKing Khaled UniversityAr-Riyad 12372Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Visual impairment is one of the major problems among people of all age groups across the *** Impaired Persons(VIPs)require help from others to carry out their day-to-day *** they experience several problems in their daily lives,technical intervention can help them resolve the *** this background,an automatic object detection tool is the need of the hour to empower VIPs with safe *** recent advances in the Internet of Things(IoT)and Deep Learning(DL)techniques make it *** current study proposes IoT-assisted Transient Search Optimization with a Lightweight RetinaNetbased object detection(TSOLWR-ODVIP)model to help *** primary aim of the presented TSOLWR-ODVIP technique is to identify different objects surrounding VIPs and to convey the information via audio message to *** data acquisition,IoT devices are used in this ***,the Lightweight RetinaNet(LWR)model is applied to detect objects ***,the TSO algorithm is employed for fine-tuning the hyperparameters involved in the LWR ***,the Long Short-Term memory(LSTm)model is exploited for classifying *** performance of the proposed TSOLWR-ODVIP technique was evaluated using a set of objects,and the results were examined under distinct *** comparison study outcomes confirmed that the TSOLWR-ODVIP model could effectually detect and classify the objects,enhancing the quality of life of VIPs.

关键词： Visually impaired people deep learning object detection computer vision long short-term memory transient search optimization

A Novel Approximate message Passing Detection for massive mImO 5G System

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Computer Systems Science & Engineering 2023年第6期45卷 2827-2835页

作者： Nidhi Gour Rajneesh Pareek Karthikeyan Rajagopal Himanshu Sharma mrim m.a.nfia. mohammed A.AlZain mehedi masud Arun Kumar Department of Computer Science&Engineering JECRC UniversityJaipurIndia Centre for Nonlinear Systems Chennai Institute of TechnologyChennaiIndia Department of Electronics and Communication Engineering and University Centre for Research&Development Chandigarh UniversityMohaliIndia Department of Information Technology College of Computer and Information TechnologyTaif UniversityP.O.Box 11099Taif21994Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099TaifSaudi Arabia Department of Electronics and Communication Engineering JECRC UniversityJaipurIndia

massive-multiple Inputs and multiple Outputs(m-mImO)is considered as one of the standard techniques in improving the performance of Fifth Generation(5G)radio.5G signal detection with low propagation delay and high throughput with minimum computational intricacy are some of the serious concerns in the deployment of *** evaluation of 5G promises a high quality of service(QoS),a high data rate,low latency,and spectral efficiency,ensuring several applications that will improve the services in every *** existing detection techniques cannot be utilised in 5G and beyond 5G due to the high complexity issues in their *** the proposed article,the Approximation message Passing(AmP)is implemented and compared with the existing minimum mean Square Error(mmSE)and message Passing Detector(mPD)*** outcomes of the work show that the performance of Bit Error Rate(BER)is improved with minimal complexity.

关键词： AmP mmSE mPD 5G