Influence of the Number of Channels and Classification Algorithm on the Performance Robustness to Electrode Shift in Steady-State Visual Evoked Potential-Based Brain-Computer Interfaces

There remains an active investigation on elevating the classification accuracy and information transfer rate of brain-computer interfaces based on steady-state visual evoked potential. However, it has often been ignored that the performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) can be affected through the minor displacement of the electrodes from their optimal locations in practical applications because of the mislocation of electrodes and/or concurrent use of electroencephalography (EEG) devices with external devices, such as virtual reality headsets. In this study, we evaluated the performance robustness of SSVEP-based BCIs with respect to the changes in electrode locations for various channel configurations and classification algorithms. Our experiments involved 21 participants, where EEG signals were recorded from the scalp electrodes densely attached to the occipital area of the participants. The classification accuracies for all the possible cases of electrode location shifts for various channel configurations (1–3 channels) were calculated using five training-free SSVEP classification algorithms, i.e., the canonical correlation analysis (CCA), extended CCA, filter bank CCA, multivariate synchronization index (MSI), and extended MSI (EMSI). Then, the performances of the BCIs were evaluated using two measures, i.e., the average classification accuracy (ACA) across the electrode shifts and robustness to the electrode shift (RES). Our results showed that the ACA increased with an increase in the number of channels regardless of the algorithm. However, the RES was enhanced with an increase in the number of channels only when MSI and EMSI were employed. While both ACA and RES values for the five algorithms were similar under the single-channel condition, both ACA and RES values for MSI and EMSI were higher than those of the other algorithms under the multichannel (i.e., two or three electrodes) conditions. In addition, EMSI outperformed MSI when comparing the ACA and RES values under the multichannel conditions. In conclusion, our results suggested that the use of multichannel configuration and employment of EMSI could make the performance of SSVEP-based BCIs more robust to the electrode shift from the optimal locations.

Comprior: facilitating the implementation and automated benchmarking of prior knowledge-based feature selection approaches on gene expression data sets

Background Reproducible benchmarking is important for assessing the effectiveness of novel feature selection approaches applied on gene expression data, especially for prior knowledge approaches that incorporate biological information from online knowledge bases. However, no full-fledged benchmarking system exists that is extensible, provides built-in feature selection approaches, and a comprehensive result assessment encompassing classification performance, robustness, and biological relevance. Moreover, the particular needs of prior knowledge feature selection approaches, i.e. uniform access to knowledge bases, are not addressed. As a consequence, prior knowledge approaches are not evaluated amongst each other, leaving open questions regarding their effectiveness. Results We present the Comprior benchmark tool, which facilitates the rapid development and effortless benchmarking of feature selection approaches, with a special focus on prior knowledge approaches. Comprior is extensible by custom approaches, offers built-in standard feature selection approaches, enables uniform access to multiple knowledge bases, and provides a customizable evaluation infrastructure to compare multiple feature selection approaches regarding their classification performance, robustness, runtime, and biological relevance. Conclusion Comprior allows reproducible benchmarking especially of prior knowledge approaches, which facilitates their applicability and for the first time enables a comprehensive assessment of their effectiveness.

Photodegradation of Brilliant Green Dye by a Zinc bioMOF and Crystallographic Visualization of Resulting CO2

We present a novel bio-friendly water-stable Zn-based MOF (1), derived from the natural amino acid L-serine, which was able to efficiently photodegrade water solutions of brilliant green dye in only 120 min. The total degradation was followed by UV-Vis spectroscopy and further confirmed by single-crystal X-ray crystallography, revealing the presence of CO2 within its channels. Reusability studies further demonstrate the structural and performance robustness of 1.

Thinking What One is Doing: Knowledge-how, Methods, and Reliability

There has been renewed interest over the last twenty years in Ryle's claims and arguments about knowledge-how. Elzinga (2018) and Löwenstein (2017) have both recently defended independent Ryle-inspired accounts of knowledge-how. In what follows, I will propose and defend an amendment to accounts of knowledge-how like those of Elzinga and Löwenstein. I argue that this amendment provides an additional needed distinction between the performance robustness provided by certain performance methods (or styles), and the robustness of an agent's ability to perform according to such methods (or styles). Additionally, the proposed amendment, if adopted, will make the amended views even more Rylean. I argue for this, in part, through original exegetical work on an under-discussed theme in Ryle's philosophy of mind: the relation between semi-hypothetical statements, methodological act-description, and knowledge-how.

Tolerance-Insensitive Design of the Magnet Shape for a Surface Permanent Magnet Synchronous Motor

Many studies have been conducted to reduce the cogging torque of electric power steering motors. However, in the mass production of such motors, it is essential to enhance performance robustness in relation to tolerances. For such motors, this work analyzes performance robustness in relation to tolerances by applying a cycloid curve to the surface magnet of the rotor. Applying a cycloid curve to the magnet surface of the rotor is one of several ways to reduce cogging torque. To evaluate the performance of the cycloid curve, we compare it with an eccentric curve. The two curves are compared for the same specifications and evaluated using the indicator, tolerance insensitivity rate, which is used to assess performance robustness in relation to tolerances. The cycloid curve was evaluated to be more robust in relation to tolerances, as compared with the eccentric curve. Finally, an experiment was conducted to validate the robustness of the cycloid curve.