Trust identification through cognitive correlates with emphasizing attention in cloud robotics
Attention and Trust remain the crux of robotic sensory perception when associated with cloud robotics. It involves tasks that compete for attention from several stimuli taken by the robot itself upon its selective attention mode, focuses its attention on the task with higher precedence, and filters...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-07-01
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| Series: | Egyptian Informatics Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110866522000032 |
| _version_ | 1811341675762548736 |
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| author | Wasim Ahmad Khan Fahad Ahmad Saad Awadh Alanazi Tayyabah Hasan Shahid Naseem Kottakkaran Sooppy Nisar |
| author_facet | Wasim Ahmad Khan Fahad Ahmad Saad Awadh Alanazi Tayyabah Hasan Shahid Naseem Kottakkaran Sooppy Nisar |
| author_sort | Wasim Ahmad Khan |
| collection | DOAJ |
| description | Attention and Trust remain the crux of robotic sensory perception when associated with cloud robotics. It involves tasks that compete for attention from several stimuli taken by the robot itself upon its selective attention mode, focuses its attention on the task with higher precedence, and filters out the rest to be performed later. The robot could unload storage-extensive and computation extensive jobs towards the cloud while keeping trust establishment in control. Factors leading to these robots' availability, confidentiality, data protection, and isolation security trigger attention. Trust involving suppliers and users is intended to attain safety measures that endorse various cloud suppliers' status and accessible services. It takes several input stimuli from the robot, i.e., confidence, experience, and emotion, and gives output as trust level to pay attention during social interactions among robots. Input parameters are mapped into fuzzy sets, taking a range of input and output membership functions. The fuzzifier and defuzzifier are designed according to the proposed scheme. The developed system, named Trust Annotator, is tested and analyzed using MATLAB R2021a. Mamdani model is conferred, which yielded some unusual yet promising outcomes. These outcomes show conformity between the designed and simulated systems. |
| first_indexed | 2024-04-13T18:58:29Z |
| format | Article |
| id | doaj.art-ab512e4a0fb44136a76953da26363285 |
| institution | Directory Open Access Journal |
| issn | 1110-8665 |
| language | English |
| last_indexed | 2024-04-13T18:58:29Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Egyptian Informatics Journal |
| spelling | doaj.art-ab512e4a0fb44136a76953da263632852022-12-22T02:34:10ZengElsevierEgyptian Informatics Journal1110-86652022-07-01232259269Trust identification through cognitive correlates with emphasizing attention in cloud roboticsWasim Ahmad Khan0Fahad Ahmad1Saad Awadh Alanazi2Tayyabah Hasan3Shahid Naseem4Kottakkaran Sooppy Nisar5School of Computer Science, National College of Business Administration & Economics, Lahore, PakistanDepartment of Basic Sciences, Deanship of Common First Year, Jouf University, Sakaka, Aljouf 72341, Saudi ArabiaDepartment of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka, Aljouf 72341, Saudi ArabiaDepartment of Computer Sciences, Kinnaird College for Women, Lahore, PakistanDepartment of Information Sciences, University of Education, Lahore, Punjab 54700, PakistanDepartment of Mathematics, College Arts and Science, Prince Sattam Bin Abdulaziz University, Wadi Aldawaser 11991, Saudi Arabia; Corresponding author.Attention and Trust remain the crux of robotic sensory perception when associated with cloud robotics. It involves tasks that compete for attention from several stimuli taken by the robot itself upon its selective attention mode, focuses its attention on the task with higher precedence, and filters out the rest to be performed later. The robot could unload storage-extensive and computation extensive jobs towards the cloud while keeping trust establishment in control. Factors leading to these robots' availability, confidentiality, data protection, and isolation security trigger attention. Trust involving suppliers and users is intended to attain safety measures that endorse various cloud suppliers' status and accessible services. It takes several input stimuli from the robot, i.e., confidence, experience, and emotion, and gives output as trust level to pay attention during social interactions among robots. Input parameters are mapped into fuzzy sets, taking a range of input and output membership functions. The fuzzifier and defuzzifier are designed according to the proposed scheme. The developed system, named Trust Annotator, is tested and analyzed using MATLAB R2021a. Mamdani model is conferred, which yielded some unusual yet promising outcomes. These outcomes show conformity between the designed and simulated systems.http://www.sciencedirect.com/science/article/pii/S1110866522000032Artificial IntelligenceStimuliSelective AttentionMamdani ModelFuzzy LogicConfidence |
| spellingShingle | Wasim Ahmad Khan Fahad Ahmad Saad Awadh Alanazi Tayyabah Hasan Shahid Naseem Kottakkaran Sooppy Nisar Trust identification through cognitive correlates with emphasizing attention in cloud robotics Egyptian Informatics Journal Artificial Intelligence Stimuli Selective Attention Mamdani Model Fuzzy Logic Confidence |
| title | Trust identification through cognitive correlates with emphasizing attention in cloud robotics |
| title_full | Trust identification through cognitive correlates with emphasizing attention in cloud robotics |
| title_fullStr | Trust identification through cognitive correlates with emphasizing attention in cloud robotics |
| title_full_unstemmed | Trust identification through cognitive correlates with emphasizing attention in cloud robotics |
| title_short | Trust identification through cognitive correlates with emphasizing attention in cloud robotics |
| title_sort | trust identification through cognitive correlates with emphasizing attention in cloud robotics |
| topic | Artificial Intelligence Stimuli Selective Attention Mamdani Model Fuzzy Logic Confidence |
| url | http://www.sciencedirect.com/science/article/pii/S1110866522000032 |
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