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In this study, we present a new 64-channel mobile EEG system (NeusenW, Neuracle Inc.), and compare it to a state-of-the-art wired laboratory EEG system and evaluate the EEG signal quality. Previous studies were only performed on seated participants in laboratory environments, and only a very limited number focus on motion conditions. In this study, we instead implemented experiments in standing, walking and running conditions.

Assistive technologies such as wheelchairs, canes, and walkers have significantly improved the mobility, function, and quality of life for individuals with spinal cord injury (SCI). In this article, we propose a framework which combines machine learning algorithms with wearable sensors to capture and track mobility in individuals with SCI. Pilot testing in two individuals without SCI indicated that four to seven features obtained from sensors worn on the body or placed on the assistive technology could successfully detect mobility and mobility modes.

Target re-identification across non-overlapping camera views is a challenging task due to variations in target appearance, illumination, viewpoint and intrinsic parameters of cameras. Brightness transfer function (BTF) was introduced for inter-camera color calibration, and to improve the performance of target re-identification methods. There have been several works based on BTFs, more specifically using weighted BTFs (WBTF), cumulative BTF (CBTF) and mean BTF (MBTF). In this paper, we present a novel method to model the ap-pearance variation across different camera views.

Automatic question-answering is a classical problem in natural language processing, which aims at designing systems that can automatically answer a question, in the same way as human does. In this work, we propose a deep learning based model for automatic question-answering. First the questions and answers are embedded using neural probabilistic modeling. Then a deep similarity neural network is trained to find the similarity score of a pair of answer and question. Then for each question, the best answer is found as the one with the highest similarity score.