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Publication Forced vibration characteristics of embedded graphene oxide powder reinforced metal foam nanocomposite plate in thermal environment(Elsevier, 2021) Zheng, Jie; Zhang, Chunwei; Musharavati, Farayi; Khan, Afrasyab; Sebaey, Tamer A.; Eyvazian, AramehDynamic behavior of a new class of nanocomposites consisted of metal foam as matrix and graphene oxide powders as reinforcement is presented in this study in the framework of forced vibration. Graphene oxide powders are dispersed through the thickness of a plate made from metal foam material according to four various functionally graded patterns on the basis of the Halpin-Tsai micromechanical homogenization method. Also, three kinds of porosity distributions including two symmetric and one uniform patterns are considered for the metal foam matrix. As external effects, the plate is rested on the Winkler-Pasternak substrate and under uniform thermal and transverse dynamic loadings. By an incorporation of the refined higher order plate theory and Hamilton’s principle, the governing equations of the dynamically loaded graphene oxide powder reinforced metal foam nanocomposite plate are derived and then solved with Galerkin exact solution method to achieve the resonance frequencies and dynamic deflections of the structure. Moreover, the influence of different boundary conditions is taken into account. The results indicate that the forced vibrational response of the graphene oxide powder strengthened metal foam nanocomposite plate is dramatically dependent on various parameters such as graphene oxide powders’ weight fraction, different boundary conditions, various porosity distributions, foundation parameters and temperature change of uniform thermal loading.Publication Brain Connectivity Analysis Under Semantic Vigilance and Enhanced Mental States(MDPI, 2019) Yahya, Fares; Tariq, Usman; Hassanin, Omnia; Mir, Hasan; Babiloni, Fabio; Al-Nashash, HasanIn this paper, we present a method to quantify the coupling between brain regions under vigilance and enhanced mental states by utilizing partial directed coherence (PDC) and graph theory analysis (GTA). The vigilance state is induced using a modified version of stroop color-word task (SCWT) while the enhancement state is based on audio stimulation with a pure tone of 250 Hz. The audio stimulation was presented to the right and left ears simultaneously for one-hour while participants perform the SCWT. The quantification of mental states was performed by means of statistical analysis of indexes based on GTA, behavioral responses of time-on-task (TOT), and Brunel Mood Scale (BRMUS). The results show that PDC is very sensitive to vigilance decrement and shows that the brain connectivity network is significantly reduced with increasing TOT, p < 0.05. Meanwhile, during the enhanced state, the connectivity network maintains high connectivity as time passes and shows significant improvements compared to vigilance state. The audio stimulation enhances the connectivity network over the frontal and parietal regions and the right hemisphere. The increase in the connectivity network correlates with individual differences in the magnitude of the vigilance enhancement assessed by response time to stimuli. Our results provide evidence for enhancement of cognitive processing effciency with audio stimulation. The BRMUS was used to evaluate the emotional states of vigilance task before and after using the audio stimulation. BRMUS factors, such as fatigue, depression, and anger, significantly decrease in the enhancement group compared to vigilance group. On the other hand, happy and calmness factors increased with audio stimulation, p < 0.05.Publication Emotion Recognition Based on Fusion of Local Cortical Activations and Dynamic Functional Networks Connectivity: An EEG Study(IEEE Xplore Digital Library, 2019) Yahya, Fares; Tariq, Usman; Alex, Meera; Mir, Hasan; Al-Nashash, HasanIn this paper, we present a method to improve emotion recognition based on the fusion of local cortical activations and dynamic functional network patterns. We estimate the cortical activations using power spectral density (PSD) with the Burg autoregressive model. On the other hand, we estimate the functional connectivity networks by utilizing the phase locking value (PLV). The results of cortical activations and connectivity networks show different patterns across three emotions at all frequency bands. Similarly, the results of fusion significantly improve the classification rate in terms of accuracy, sensitivity, specificity and the area under the receiver operator characteristics curve (AROC), p < 0:05. The average improvement with fusion in all evaluation metrics are 6.84% and 4.1% when compared to PSD and PLV alone, respectively. The results clearly demonstrate the advantage of fusion of cortical activations with dynamic functional networks for developing human-computer interaction system in real-world applications.Publication Vigilance Decrement and Enhancement Techniques: A Review(MDPI, 2019) Yahya, Fares; Tariq, Usman; Mir, Hasan; Alawar, Hamad; Babiloni, Fabio; Al-Nashash, HasanThis paper presents the first comprehensive review on vigilance enhancement using both conventional and unconventional means, and further discusses the resulting contradictory findings. It highlights the key differences observed between the research findings and argues that variations of the experimental protocol could be a significant contributing factor towards such contradictory results. Furthermore, the paper reveals the effectiveness of unconventional means of enhancement in significant reduction of vigilance decrement compared to conventional means. Meanwhile, a discussion on the challenges of enhancement techniques is presented, with several suggested recommendations and alternative strategies to maintain an adequate level of vigilance for the task at hand. Additionally, this review provides evidence in support of the use of unconventional means of enhancement on vigilance studies, regardless of their practical challenges.