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Enormous development as well as quickly movement throughout spin-crossover@polymer actuators.
To address the severe class imbalance issue in the CT volume and meanwhile improve the segmentation performance, a loss function consisting of weighted cross-entropy and jaccard distance is proposed. During the network training, the 2D and 3D contexts are learned jointly in an end-to-end way. The proposed network achieves competitive results on the Liver Tumor Segmentation Challenge (LiTS) and the 3D-IRCADB datasets. This method should be a new promising paradigm to explore the contexts for liver and tumor segmentation.When multiple speakers talk simultaneously, a hearing device cannot identify which of these speakers the listener intends to attend to. Auditory attention decoding (AAD) algorithms can provide this information by, for example, reconstructing the attended speech envelope from electroencephalography (EEG) signals. However, these stimulus reconstruction decoders are traditionally trained in a supervised manner, requiring a dedicated training stage during which the attended speaker is known. Pre-trained subject-independent decoders alleviate the need of having such a per-user training stage but perform substantially worse than supervised subject-specific decoders that are tailored to the user. This motivates the development of a new unsupervised self-adapting training/updating procedure for a subject-specific decoder, which iteratively improves itself on unlabeled EEG data using its own predicted labels. This iterative updating procedure enables a self-leveraging effect, of which we provide a mathematical analysis that reveals the underlying mechanics. The proposed unsupervised algorithm, starting from a random decoder, results in a decoder that outperforms a supervised subject-independent decoder. Starting from a subject-independent decoder, the unsupervised algorithm even closely approximates the performance of a supervised subject-specific decoder. The developed unsupervised AAD algorithm thus combines the two advantages of a supervised subject-specific and subject-independent decoder it approximates the performance of the former while retaining the `plug-and-play character of the latter. As the proposed algorithm can be used to automatically adapt to new users, as well as over time when new EEG data is being recorded, it contributes to more practical neuro-steered hearing devices.The size and shape of fingertips vary significantly across humans, making it challenging to design wearable fingertip interfaces suitable for everyone. Although deemed important, this issue has often been neglected due to the difficulty of customizing devices for each different user. This article presents an innovative approach for automatically adapting the hardware design of a wearable haptic interface for a given user. We consider a three-DoF fingertip cutaneous device, composed of a static body and a mobile platform linked by three articulated legs. The mobile platform is capable of making and breaking contact with the finger pulp and re-angle to replicate contacts with arbitrarily-oriented surfaces. We analyze the performance of this device as a function of its main geometrical dimensions. Then, starting from the user's fingertip characteristics, we define a numerical procedure that best adapts the dimension of the device to (i) maximize the range of renderable haptic stimuli; (ii) avoid unwanted contacts between the device and the skin; (iii) avoid singular configurations; and (iv) minimize the device encumbrance and weight. Together with the mechanical analysis and evaluation of the adapted design, we present a MATLAB script that calculates the device dimensions customized for a target fingertip as well as an online CAD utility for generating a ready-to-print STL file of the personalized design.The Bogus Finger is a remote-controllable tool for simulating vertical pressing forces of various magnitude as exerted by a human finger. Its main application is the characterization of haptic devices under realistic active touch conditions. The device is released as an open-source hardware and software DIY project that can be easily built using off-the-shelf components. We report the characterization of the quasi-static properties of the device, and validate its dynamic response to pressing on a vibrating surface by comparison with human fingers. Remdesivir molecular weight The present prototype configuration accurately reproduces the mechanical impedance of the human finger in the frequency range 200-400 Hz.We propose a film device that can be attached to flat surfaces, including touch panels, to remotely reduce surface friction by irradiating airborne ultrasound. In this article, we present a film-air resonance structure that produces large-amplitude surface vibrations excited by airborne ultrasound. We confirmed via simulation that the surface amplitude increases to a level sufficient to reduce friction at the designed frequency. It was also observed in an experiment using a prototype that the friction between a finger and film surface is sharply reduced, and the surface vibrates with sufficient amplitude when touched with a finger.This study seeks to understand conditions under which virtual gratings produced via vibrotaction and friction modulation are perceived as similar and to find physical origins in the results. To accomplish this, we developed two single-axis devices, one based on electroadhesion and one based on out-of-plane vibration. The two devices had identical touch surfaces, and the vibrotactile device used a novel closed-loop controller to achieve precise control of out-of-plane plate displacement under varying load conditions across a wide range of frequencies. A first study measured the perceptual intensity equivalence curve of gratings generated under electroadhesion and vibrotaction across the 20-400Hz frequency range. A second study assessed the perceptual similarity between two forms of skin excitation given the same driving frequency and same perceived intensity. Our results indicate that it is largely the out-of-plane velocity that predicts vibrotactile intensity relative to shear forces generated by friction modulation. A high degree of perceptual similarity between gratings generated through friction modulation and through vibrotaction is apparent and tends to scale with actuation frequency suggesting perceptual indifference to the manner of fingerpad actuation in the upper frequency range.
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