Search Results (6)

New probability models of inherently embodied cognition derived from the asymptotic limit theorems of information and control theories show, where the Weber–Fechner, Stevens, Hick–Hyman, and Pieron’s psychophysics laws—and analogous processes of sensory data rate compression—operate, that sufficient arousal will engender the classic Yerkes–Dodson effect responses for ‘easy’ and ‘difficult’ challenges, depending on the level of ‘noise’ impeding the cognition rate. A ‘hallucination’ mode is found to arise at low arousal, and, in the face of sufficient noise, a ‘panic’ mode at high arousal. Systems that are ‘ductile’ in a formal sense, however, are not afflicted by such hallucination, although panic remains for difficult challenges. Similar dynamics that surround organized conflict on ‘Clausewitz landscapes’ of fog, friction, and deadly adversarial intent have long been studied. We find a central mechanism for cognitive failure under increasing stress across a very broad range of modalities to be enough—usually badly needed—compression of sensory/intelligence and internal information transmission rates. It seems possible, with some effort, to convert the probability models developed here into robust statistical tools for the study and limited control of critical real-time, real-world embodied cognitive phenomena associated with cellular, neural, individual, machine, and institutional systems and their many composites. Full article

When an organism is exposed to environmental stimuli of varying intensity, the adaptive changes in the CNS can be explained by several conceptual provisions: the law of motivation–activation by Yerkes and Dodson, the laws of force and pessimal protective inhibition, and the theory of emotion activation. Later, reinforcement sensitivity theory was developed in the fields of psychology and psychophysics. At the same time, cortical prepulse inhibition (PPI), the prepulse inhibition of perceived stimulus intensity (PPIPSI), and the augmentation/reduction phenomenon were proposed in sensory neurophysiology, which expanded our understanding of consciousness. The aim of this study was to identify markers of levels of activity of cognitive processes under normal and in psychopathological conditions while amplifying the information stimulus. For this purpose, we changed the contrast level of reversible checkerboard patterns and mapped the visual evoked potentials (VEPs) in 19 monopolar channels among 52 healthy subjects and 39 patients with a mental illness without an active productive pathology. Their cognitive functions were assessed by presenting visual tests to assess invariant pattern recognition, short-term visual memory, and Gestalt perception. The personalities of the healthy subjects were assessed according to Cattell’s 16-factor questionnaire, linking the data from neurophysiological and cognitive studies to factors Q4 (relaxation/tension) and C (emotional stability). According to the N₇₀ and N₁₅₀ VEP waves, the healthy subjects and the patients were divided into two groups. In some, there was a direct relationship between VEP amplitude and contrast intensity (21 patients and 29 healthy persons), while in the others, there was an inverse relationship, with a reduction in VEP amplitude (18 patients and 23 healthy persons). The relationship and mechanisms of subjects’ cognitive abilities and personality traits are discussed based on the data acquired from the responses to information stimuli of varied intensity. Full article

Social awareness and relationship management components can be seen as a form of emotional intelligence. In the present work, we propose task-related adaptation on the machine side that accounts for a person’s momentous cognitive and emotional state. We validate the practical significance of the proposed approach in person-specific and person-independent setups. The analysis of results in the person-specific setup shows that the individual optimal performance curves for that person, according to the Yerkes–Dodson law, are displaced. Awareness of these curves allows for automated recognition of specific user profiles, real-time monitoring of the momentous condition, and activating a particular relationship management strategy. This is especially important when a deviation is detected caused by a change in the person’s state of mind under the influence of known or unknown factors. Full article

The application of information technology provides technical support for achieving the requirements of reducing burden and improving quality in the Chinese “Double Reduction” Policy. Based on the analysis of the mechanism and path of “Smart Homework” (an educational tool that applies artificial intelligence technology) to reduce the burden and improve the quality of Chinese Jiangxi Province by using the literature, this paper investigates 78 counties and cities of this province and finds that this tool can reduce the burden of primary and secondary school students’ homework, improve the completion of homework, reduce the willingness to participate in after-school tutoring, and improve the self-efficacy and learning investment, so as to achieve the goal of the Chinese “Double Reduction” Policy, but at the same time, the lack of convenience in using intelligent products has caused psychological anxiety for a small number of students. The psychological mechanism of reducing burden and improving quality is in line with the principle revealed by the Yerkes–Dodson law; that is, as learning anxiety decreases, the impact of psychological stress on learning efficiency increases. The appropriate psychological stress enhanced the impact of psychological pressure on learning efficacy and engagement, and improved learning efficiency. The article believes that, first, based on the principle of a three-layer structure of homework burden, the use of “Smart Homework” achieves the reduction of homework burden from three aspects: surface layer, inner layer, and core layer. Second, “Smart Homework” reduces the willingness to participate in extracurricular tutoring and, to some extent, reduces the burden of extracurricular tutoring. Third, “Smart Homework” can help students better complete homework and improve learning efficiency. Full article

Given the COVID-19 pandemic and the resulting social distancing measures with inevitable telecommuting, capturing user emotions is essential as it affects both satisfaction and task performance. Therefore, the purpose of this study was to analyze emotions and task performance in terms of dislike and personalized decision-making in indoor spaces. To facilitate experiments with participants, a mixed-reality environment was utilized with the Pleasure, Arousal, Dominance (PAD) test and cognitive tests. The results of the experiment conducted on 30 subjects identified that aroused and discontented emotions dominated in non-preferred spaces, but pleased, important, and autonomous emotions arose in personalized spaces, as determined through sentimental analysis and statistical methods. Although negative emotions were present in the aversion space, attention and execution abilities were high compared to the personalized space, but working memory was low. By conducting stepwise regression analysis, it was found that working in a visually unfavorable space, which caused an increase in controlled or controlling emotions, improved short-term work efficiency. In addition, important emotions did not have a positive effect on any task performance. However, with pleased and contented emotions in a personalized indoor space, long-term work efficiency was increased, as explained by the Yerkes-Dodson law. Full article

Work-induced stress is widely acknowledged as harming physical and psychosocial health and has been linked with adverse outcomes such as a decrease in productivity. Recently, workplace stressors have increased due to the COVID-19 pandemic. This study aims to contribute to the literature base in a couple of areas. First, it extends the current knowledge base by utilising generative additive modelling (GAMs) to uncover the nature of the relationship between workload (a key workplace stressor) and productivity based on real-world event logs. Additionally, it uses recursive partitioning modelling to shed light on the factors that drive the relationship between these variables. Secondly, it utilises a simulation-based approach to investigate the diffusion of workload-induced stress in the workplace. Simulation is a valuable tool for exploring the effect of changes in a risk-free manner as it provides the ability to run multiple scenarios in a safe and virtual environment with a view to making recommendations to stakeholders. However, there are several recognised issues with traditional simulation approaches, such as inadequate resource modelling and the limited use of simulations for operational decision making. In this study, we propose an approach which extracts the required parameters from an event log and subsequently utilises them to initialise a workload-induced stress diffusion simulation model accurately. We also explore the effects of varying the parameters to control the spread of workload-induced stress within the network. With suitable amendments, this approach can be extended to model the spread of disease (e.g., COVID-19), diffusion of ideas, among other things, in the workplace. Full article