In this study, we used multivariate decoding methods to study processing differences between canonical (montring and count) and noncanonical finger numeral configurations (FNCs). While previous research investigated these processing differences using behavioral and event-related potentials (ERP) methods, conventional univariate ERP analyses focus on specific time intervals and electrode sites and fail to capture broader scalp distribution and EEG frequency patterns. To address this issue a supervised learning classifier—support vector machines (SVM)—was used to decode ERP scalp distributions and alpha-band power for montring, counting, and noncanonical FNCs (for integers 1 to 4). The SVM was used to test whether the numerical information presented in FNCs can be decoded from the EEG data. Differences in the magnitude and timing of accuracy rates were used to compare the three types of FNCs. Overall, the algorithm was able to predict numerical information presented in FNCs beyond the random chance level accuracy, with higher rates for ERP scalp distributions than alpha-power. Montring had lower peak accuracy compared to counting and noncanonical configurations, likely due to automaticity in processing montring configurations leading to less distinct scalp distributions for the four numerical magnitudes (1 to 4). Paralleling the response time data, the peak decoding accuracy time for montring was earlier for montring (472 ms), compared to counting (577 ms) and noncanonical FNCs (604 ms). The results provide support for montring configurations being processed automatically, somewhat similar to number symbols, and provide additional insights for processing differences across different forms of FNCs. This study also highlights the strengths of decoding methods in EEG/ERP research on numerical cognition.

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The uncertainties arising from the imperfection of the shared understanding during humanrobot collaboration (HRC) is a critical challenge in developing real-world robots, which has attracted attention in various fields, especially in the manufacturing sector. Many research efforts have explored several key components and elements of HRC to reduce uncertainties. However, these efforts are mostly isolated from each other and few attempts have been made to develop generic frameworks to combine them for better HRC frameworks. This article contributes to this issue by reviewing the components of HRC research and developing a generic framework of purposeful communication to better arrive at a common view of uncertainties and collaboratively deal with those required by the tasks at hand holistically. The aspects of HRC components that can affect the shared understanding of humans and robots include the type of collaborative task, communication modalities, and decision-making of robots. After examining these aspects, we re-positioned the central problem to the cause of these uncertainties and proposed a new categorization of the available HRC scenarios considering communication channels, because communication strategies should be the main focus for reducing these uncertainties. This categorization will help to design better HRC frameworks that will lead to improving shared understanding and task performance, reducing uncertainties, and establishing trust, transparency, and safety. This paper proposes a comprehensive literature review and a new categorization of the currently used communication approaches by analyzing forty-nine selected articles from a wide range of articles in various databases.

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A numerical parameter sensitivity analysis is performed on the bending and torsional vibrations of a flexural-torsional vibrating beam gyroscope model. The gyroscope analyzed in this work is comprised of a rotating cantilever beam with a point-mass attached to its free end and a piezoelectric actuator fixed to a portion of its length. The governing equations of motion are derived using extended Hamilton’s principle and the steady-state magnitude response of the system is obtained through frequency domain methods. A sensitivity analysis is then carried out for the parameters including rotational speed of the base, the length of the beam, the location of the piezoelectric patch, and the location of the added point mass along the beam’s length. It is observed that, in the region surrounding specific configurations, small variations in the rotation rate, beam length and the location of the piezoelectric patch will result in significant changes to the amplitudes of the coupled vibrations and produce peaks in the sensitivity curves. Further, the amplitude of vibration tends to increase as the location of the added point-mass is moved closer to the free end. Generally, the bending modes are more sensitive to all of these parameter variations than are the torsional modes.