Nomenclature.

<div><p>Human-robot interaction has gained significant attention in various domains, including healthcare, customer service, and industrial automation. High computational cost, inefficient service matching, and elevated failure rates in dynamic service contexts are some primary disadvant...

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Main Author: Mohammed Albekairi (21615782) (author)
Other Authors: Meshari D. Alanazi (21615785) (author), Turki M. Alanazi (17990269) (author), Mohamed Vall O. Mohamed (21615788) (author), Khaled Kaaniche (21615791) (author), Anis Sahbani (21615794) (author), Ali Elrashidi (19712176) (author)
Published: 2025
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author Mohammed Albekairi (21615782)
author2 Meshari D. Alanazi (21615785)
Turki M. Alanazi (17990269)
Mohamed Vall O. Mohamed (21615788)
Khaled Kaaniche (21615791)
Anis Sahbani (21615794)
Ali Elrashidi (19712176)
author2_role author
author
author
author
author
author
author_facet Mohammed Albekairi (21615782)
Meshari D. Alanazi (21615785)
Turki M. Alanazi (17990269)
Mohamed Vall O. Mohamed (21615788)
Khaled Kaaniche (21615791)
Anis Sahbani (21615794)
Ali Elrashidi (19712176)
author_role author
dc.creator.none.fl_str_mv Mohammed Albekairi (21615782)
Meshari D. Alanazi (21615785)
Turki M. Alanazi (17990269)
Mohamed Vall O. Mohamed (21615788)
Khaled Kaaniche (21615791)
Anis Sahbani (21615794)
Ali Elrashidi (19712176)
dc.date.none.fl_str_mv 2025-06-27T17:43:02Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0324986.t001
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Nomenclature_/29427680
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Medicine
Sociology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
tabu search approaches
reliably provide end
process inquiries autonomously
organized computing approaches
high computational cost
gained significant attention
convergent optimization issue
dynamic service contexts
xlink "> human
model &# 8217
make robots better
proposed hicm incorporates
hicm fared better
provide timely services
inefficient service matching
elevated failure rates
robotic query processing
handle human questions
failure rates
customer service
time human
robots must
robotic agents
processing systems
model evaluates
matching ratio
human questions
existing query
services suited
appropriate services
accessible services
various domains
using self
support system
success factor
specific solutions
robot interaction
research introduces
primary disadvantages
making framework
industrial automation
including healthcare
important metrics
findings demonstrate
competing models
combining annealing
calculate quickly
autonomous nature
87 %.
09 %,
dc.title.none.fl_str_mv Nomenclature.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <div><p>Human-robot interaction has gained significant attention in various domains, including healthcare, customer service, and industrial automation. High computational cost, inefficient service matching, and elevated failure rates in dynamic service contexts are some primary disadvantages of existing query-processing systems. This research introduces a Hybrid Intelligent Computing Model (HICM) to improve robots’ ability to process inquiries autonomously. The goal is to make robots better at responding to human questions in real time with efficient, personalized, and context-specific solutions. Using self-organized computing approaches, robotic agents can reliably provide end-users with services suited to their demands. Due to their autonomous nature, robots must be able to calculate quickly and accurately to provide timely services. To meet these needs, the proposed HICM incorporates a sophisticated decision-support system to handle human questions and find the appropriate services. Within this decision-making framework, the model evaluates the characteristics and relevance of questions about accessible services by combining annealing and Tabu Search approaches. To avoid addressing queries incompatibly, the Tabu Search technique approaches query resolution as a non-convergent optimization issue. Comparing HICM’s performance to other models reveals significant improvements over CDS, DGTA, and CCS. In particular, HICM reduced calculation time by 8.67%, service time by 15.09%, and failure rates by 7.87%. In terms of important metrics, HICM fared better than the competing models. Its success factor was 11.8% higher, its matching ratio was 14.88% higher, and its failure rates were 6.22% lower. These findings demonstrate the model’s efficiency and reliability in terms of robotic query processing and real-time service delivery.</p></div>
eu_rights_str_mv openAccess
id Manara_6950008ea02b56903734fe3cb47c4e99
identifier_str_mv 10.1371/journal.pone.0324986.t001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/29427680
publishDate 2025
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Nomenclature.Mohammed Albekairi (21615782)Meshari D. Alanazi (21615785)Turki M. Alanazi (17990269)Mohamed Vall O. Mohamed (21615788)Khaled Kaaniche (21615791)Anis Sahbani (21615794)Ali Elrashidi (19712176)MedicineSociologyCancerInfectious DiseasesBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedtabu search approachesreliably provide endprocess inquiries autonomouslyorganized computing approacheshigh computational costgained significant attentionconvergent optimization issuedynamic service contextsxlink "> humanmodel &# 8217make robots betterproposed hicm incorporateshicm fared betterprovide timely servicesinefficient service matchingelevated failure ratesrobotic query processinghandle human questionsfailure ratescustomer servicetime humanrobots mustrobotic agentsprocessing systemsmodel evaluatesmatching ratiohuman questionsexisting queryservices suitedappropriate servicesaccessible servicesvarious domainsusing selfsupport systemsuccess factorspecific solutionsrobot interactionresearch introducesprimary disadvantagesmaking frameworkindustrial automationincluding healthcareimportant metricsfindings demonstratecompeting modelscombining annealingcalculate quicklyautonomous nature87 %.09 %,<div><p>Human-robot interaction has gained significant attention in various domains, including healthcare, customer service, and industrial automation. High computational cost, inefficient service matching, and elevated failure rates in dynamic service contexts are some primary disadvantages of existing query-processing systems. This research introduces a Hybrid Intelligent Computing Model (HICM) to improve robots’ ability to process inquiries autonomously. The goal is to make robots better at responding to human questions in real time with efficient, personalized, and context-specific solutions. Using self-organized computing approaches, robotic agents can reliably provide end-users with services suited to their demands. Due to their autonomous nature, robots must be able to calculate quickly and accurately to provide timely services. To meet these needs, the proposed HICM incorporates a sophisticated decision-support system to handle human questions and find the appropriate services. Within this decision-making framework, the model evaluates the characteristics and relevance of questions about accessible services by combining annealing and Tabu Search approaches. To avoid addressing queries incompatibly, the Tabu Search technique approaches query resolution as a non-convergent optimization issue. Comparing HICM’s performance to other models reveals significant improvements over CDS, DGTA, and CCS. In particular, HICM reduced calculation time by 8.67%, service time by 15.09%, and failure rates by 7.87%. In terms of important metrics, HICM fared better than the competing models. Its success factor was 11.8% higher, its matching ratio was 14.88% higher, and its failure rates were 6.22% lower. These findings demonstrate the model’s efficiency and reliability in terms of robotic query processing and real-time service delivery.</p></div>2025-06-27T17:43:02ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0324986.t001https://figshare.com/articles/dataset/Nomenclature_/29427680CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/294276802025-06-27T17:43:02Z
spellingShingle Nomenclature.
Mohammed Albekairi (21615782)
Medicine
Sociology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
tabu search approaches
reliably provide end
process inquiries autonomously
organized computing approaches
high computational cost
gained significant attention
convergent optimization issue
dynamic service contexts
xlink "> human
model &# 8217
make robots better
proposed hicm incorporates
hicm fared better
provide timely services
inefficient service matching
elevated failure rates
robotic query processing
handle human questions
failure rates
customer service
time human
robots must
robotic agents
processing systems
model evaluates
matching ratio
human questions
existing query
services suited
appropriate services
accessible services
various domains
using self
support system
success factor
specific solutions
robot interaction
research introduces
primary disadvantages
making framework
industrial automation
including healthcare
important metrics
findings demonstrate
competing models
combining annealing
calculate quickly
autonomous nature
87 %.
09 %,
status_str publishedVersion
title Nomenclature.
title_full Nomenclature.
title_fullStr Nomenclature.
title_full_unstemmed Nomenclature.
title_short Nomenclature.
title_sort Nomenclature.
topic Medicine
Sociology
Cancer
Infectious Diseases
Biological Sciences not elsewhere classified
Information Systems not elsewhere classified
tabu search approaches
reliably provide end
process inquiries autonomously
organized computing approaches
high computational cost
gained significant attention
convergent optimization issue
dynamic service contexts
xlink "> human
model &# 8217
make robots better
proposed hicm incorporates
hicm fared better
provide timely services
inefficient service matching
elevated failure rates
robotic query processing
handle human questions
failure rates
customer service
time human
robots must
robotic agents
processing systems
model evaluates
matching ratio
human questions
existing query
services suited
appropriate services
accessible services
various domains
using self
support system
success factor
specific solutions
robot interaction
research introduces
primary disadvantages
making framework
industrial automation
including healthcare
important metrics
findings demonstrate
competing models
combining annealing
calculate quickly
autonomous nature
87 %.
09 %,