Generative Adversarial Networks Based Cognitive Feedback Analytics System for Integrated Cyber-Physical System and Industrial Iot Networks

In the modern era of technologies, the internet grows in the advancement of our day-to-day life like automation devices. The devices to set up industries with integrated cyber-physical systems and industrial IoT applications. Generative adversarial networks (GAN) can generate Cognitive feedback analysis with various data for both generator and discriminator in a supervised model. Neural networks are used for artificial intelligence algorithms, but in adversarial networks, feedback analytics is analyzed with the significance of data. The modern age of intelligent manufacturing will indeed be ushered in by Cyber-Physical Production Systems (CPPS). However, because of the connections between the virtual and physical worlds, CPPS would be subject to cross-domain assaults. Against Denial-of-Service (DoS) threats, this paper concentrates on complex performance feedback management of Cyber-Physical Systems (CPS). To begin, a swapping system modelling approach for the complex response feedback CPS is provided by analyzing the distinct effects of DoS assaults on the sensor-controller (S-C) and controller-to-actuator (C-A) channels, accordingly. Given the difference in bandwidth between the dual channels and the accused's energy cap, it is reasonable to conclude that an offender can only jam a single communication stream at a point and also that the possible number of successive DoS attacks is limited. Second, using a packet-based transfer scheme, a nested switching paradigm is built on the foundation of the switching mechanism, considering both the spatial heterogeneity and the temporal durability of DoS attacks. The probability of discriminator gets analyzed feedback data to check whether actual data or fake data is sampled, and it is generated. Cognitive feedback supports genetic algorithms to sample the feedback data in a system for advanced technologies.

SIMULATION AND PARAMETERS-IDENTIFICATION METHODS OF HETEROGENEOUS ABNORMAL NEUROLOGICAL MOVEMENTS IN MULTICOMPONENT NEURO-BIOSYSTEMS WITH COGNITIVE FEEDBACK

The foundations of mathematical modeling and identification of parameters of heterogeneous abnormal neurological movements (ANM) in multicomponent neuro-biosystems with cognitive feedback have been developed. Based on the methods of integral transformations and spectral analysis developed by the authors for heterogeneous media, a new approach to the construction of hybrid models of wave signal propagation is proposed that describes unwanted tremors of the patient's arm (T-object) as a result of an unconstrained contraction of skeletal muscles due to the cognitive effects of a certain group of neural nodes in the cortex cerebral (CC). A hybrid model of a neuro-biosystem is developed, which describes the state and behavior, namely, the segment-by-segment description of 3D elements of the ANM trajectories of the T-object, taking into account the matrix of cognitive influences of the groups of neuro nodes of the CC. On the basis of hybrid integral Fourier transforms a high-speed analytical vector solution of the model is obtained, which describes the elements of the trajectories on each AND-segment. A new method for calculating of hybrid spectral function, spectral values and matrix of cognitive influences of CC neuronodes is proposed, which determine hybrid integral transformation of solution construction. New non-classical problems of multi-parameter identification of neuro-feedback systems in heterogeneous media based on minimization of the residual functional between observation trajectories and their model analogs are formulated and solved. High-performance algorithms of the amplitude-frequency characteristics identifying of a feedback-system in analytical expressions for the gradients of the residual functional have been constructed, which allow parallel-computations on multicore computers. Computer modeling and identification of ANM trajectories of the studied neuro-feedback-system have been performed.

Give People What They Want, Feedback: Older Adult Perceptions on Cognitive Training Features to Increase Engagement

According to Temporal Self-Regulation Theory (TST; Hall & Fong, 2007), adherence motivation can be driven by both positive and negative emotional reactions in which adherence is viewed in relation to gains versus losses. In a sample of 100 older adults (ages 64+), we explored participant-provided feedback related to intervention and game elements participants perceived would increase their adherence across five domains: (1) ability to adjust difficulty; (2) ability to change game design (from the preprogrammed American Western theme); (3) cognitive performance feedback; (4) ability to unlock extra game features (e.g., more levels); and (5) other elements. Ranked in order of frequency of endorsement, 53% endorsed: cognitive performance feedback; 47%: ability to adjust difficulty; 28%: ability to unlock new features; 27%: the ‘Other’ option; and 20% endorsed changing the game’s theme. This work has implications for models of adherence, specifically, the role that expectations of later cognitive feedback might play.

Supportive Peer Feedback in Tertiary Education: Analysis of Pre-Service Teachers’ Perceptions

To acquire knowledge about student-mediated peer-to-peer collaborative activities, pre-service teachers’ perceptions of peer feedback are analyzed and categorized as receiver, provider, or cognitive feedback. A questionnaire of 15 survey questions concerning supportive feedback from peers was designed and validated using assessments from more than 200 pre-service teachers. The questionnaire was aligned with the activities promoting supportive feedback between pre-service teachers from three bachelor’s degrees at a tertiary education institution. Their perceptions were then quantified in terms of the peer feedback categories. While there were significant correlations between the scores for all 15 questions, real insights were produced when the highest correlations were analyzed. As such, being involved as both feedback providers and receivers was highly rated. The self-efficacy of pre-service teachers receiving feedback, (i.e., the extent to which peer instructional strategies and the selected learning tasks were cognitively challenging so as to improve receiver feedback), proved to be correlated with their perceptions of involvement, autonomy, and structure. Likewise, motivation for providing or receiving feedback was also closely correlated with the self-efficacy of pre-service teachers providing feedback. Finally, all three questions in the cognitive feedback category were highly correlated. The pre-service teachers were, thus, motivated to improve their learning and considered feedback as a useful task and as a way to strengthen their relationships with their peers.

Sustainable Peer Feedback in Higher Education: Category-Driven Analysis on Pre-Service Students’ Perceptions

Students who had been actively engaged in mediated collaborative activities, were asked for their perceptions about the sustainable peer feedback they had received and provided. Their views were then analyzed and categorized in terms of receiver and provider feedback, cognitive feedback and previously acquired feedback to further knowledge about sustainable education processes. A peer supported feedback questionnaire was created and validated, and its categories were correlated. The questionnaire was then aligned with the activities used to foster peer feedback between the pre-service students from the three bachelor’s degrees. The perceptions the students had of the feedback processes were analyzed using defined peer support feedback categories and the results showed a correlation between cognitive feedback and both provider and receiver self-efficacy feedback. In addition, there was a further correlation between both provider and receiver self-efficacy feedback as well as provider and receiver involvement and feedback structure. However, the results also revealed that neither receiver nor provider autonomy support were significant categories for supportive feedback.