Robust modeling of epistemic mental states

Rahman, A K M Mahbubur; Anam, Asm Iftekhar; Yeasin, Mohammed

doi:10.1007/s11042-020-09145-5

Cited by 4 publications

(2 citation statements)

References 41 publications

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“…On the other hand, the fair atmosphere can effectively regulate the degree of psychological contract destruction. For example, it is positively related to job satisfaction, role performance, and organizational citizenship behavior but negatively related to turnover intention [10]. The leader-member relationship in the interpersonal relationship atmosphere has also been proved to regulate the degree of psychological contract destruction effectively.…”

Section: Determination Of the Quantitative Relationship Between Param...mentioning

confidence: 99%

Response Model of Teachers’ Psychological Education in Colleges and Universities Based on Nonlinear Finite Element Equations

Guo

Aldulaimi

2022

Applied Mathematics and Nonlinear Sciences

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This article proposes a nonlinear mental health evaluation model after combining the nonlinear finite element equation with the mental health education of teachers in colleges and universities. We take the “self-concept” in psychology as an order parameter to judge mental health. At the same time, logical thinking is used to guide college teachers to rethink the process of their psychological activities. Research has found that the nature of human psychology is nonlinear. It is feasible to use nonlinear analysis methods to improve the status quo of original data analysis in psychological and behavioral control research.

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Section: Determination Of the Quantitative Relationship Between Param...mentioning

confidence: 99%

Response Model of Teachers’ Psychological Education in Colleges and Universities Based on Nonlinear Finite Element Equations

Guo

Aldulaimi

2022

Applied Mathematics and Nonlinear Sciences

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“…The paper by Rahman et al, "Robust modeling of epistemic mental states" pursued the individual dimension by considering several communicative modalities with high prevalence of the face [24]. The paper analyzes facial features and their temporal dynamics with epistemic mental states like Agreement, Concentration, Thoughtful, Certain, and Interest in dyadic conversations.…”

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confidence: 99%

Socio-affective technologies [SI 1156 T]

Carolis

D’Errico

Rossano

2020

Multimed Tools Appl

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Affective Computing is the science of creating emotionally aware systems, including the automatic analysis of affect and expressive behaviors [19]. Social computing is an interdisciplinary area that is concerned with the intersection of social behavior and computational systems [26]. Affective and social computing are two research fields that involve human and computer sciences defining them as featured by an interdisciplinary nature. In this perspective, a growing need within research concerning affective and social technologies is to combine and integrate psychological and computer sciences in order to make the technologies aware of human emotions and behaviors and able to interact with humans as well. The main purpose of this special issue is to advance emotion and social behavior recognition in order to understand their psychological features but also implement multimodal interaction with applications. The idea is to set the state of the scientific research on socioaffective technologies by integrating both the computational and psychological approaches in understanding, recognizing and shaping affective processes in the real and new social environments (social media, virtual reality) even in educational contexts. In psychological sciences, affective processes can be focused on individual, interactional and social dimensions [6, 21, 22]. All three dimensions can be explored by means of the analysis of verbal, physiological and expressive aspects which generally use one or more communicative modalities [20]: linguistic or rhetorical [3, 5, 16, 17], voice [25], facial [13], head [23] gestural or touching [20], postural modality [1]. In this context, from a computational point of view it is necessary to cope with real-time recognition of the meaning of human behaviors in contextual situations both from the cognitive and affective points of view. Especially in domains such as education [2, 4, 7, 9,

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ERBFV-Net: An Emotion Recognizer Based on Face Video for MAHNOB-HCI

Kuang

Liu

et al. 2023

2023 IEEE 6th Information Technology,Networking,Electronic and Automation Control Conference (ITNEC)

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Robust modeling of epistemic mental states

Cited by 4 publications

References 41 publications

Response Model of Teachers’ Psychological Education in Colleges and Universities Based on Nonlinear Finite Element Equations

Response Model of Teachers’ Psychological Education in Colleges and Universities Based on Nonlinear Finite Element Equations

Socio-affective technologies [SI 1156 T]

ERBFV-Net: An Emotion Recognizer Based on Face Video for MAHNOB-HCI

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