We present a targeted, scaled-up comparison of incremental processing in humans and neural language models by collecting by-word reaction time data for sixteen different syntactic test suites across a range of structural phenomena. Human reaction time data comes from a novel online experimental paradigm called the Interpolated Maze task. We compare human reaction times to by-word probabilities for four contemporary language models, with different architectures and trained on a range of data set sizes. We find that across many phenomena, both humans and language models show increased processing difficulty in ungrammatical sentence regions with human and model 'accuracy' scores (à la Marvin and Linzen (2018)) about equal. However, although language model outputs match humans in direction, we show that models systematically under-predict the difference in magnitude of incremental processing difficulty between grammatical and ungrammatical sentences. Specifically, when models encounter syntactic violations they fail to accurately predict the longer reaction times observed in the human data. These results call into question whether contemporary language models are approaching human-like performance for sensitivity to syntactic violations.1. S d (was impressed) < Sc(was impressed) 2. S d (was impressed) < S b (was impressed)

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Fingerprint and Iris are significant biometric tools used for authentication. This paper proposes a novel methodology by which the biometric patterns can be visualized as a set of Bezier curves and hence represented by the corresponding Bezier points, resulting in considerable reduction in the file size. This scheme utilizes the Bezier curve representations for effective compression of all those images. Initially, the ridges and furrows present in the fingerprint and iris image are extracted along with their coordinate values. The control points are determined for all the ridges and furrows. The control points of all the ridges determined are stored and are used to represent the fingerprint and iris image. When needed, those can be reconstructed from the stored control points using Bezier curves. The quality of the reconstructed fingerprint and iris is also maintained. Thus the proposed scheme achieves considerable memory reduction in storing the biometric patterns.