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We examined the relation between maternal responsiveness and children's acquisition of mental and non-mental state vocabulary in 59 pairs of mothers and children aged 10 to 26 months as they engaged in a free-play episode. Children wore a head camera and responsiveness was defined as maternal talk that commented on the child's actions (e.g., when the child reached for or manipulated an object visible in the head camera). As hypothesized, maternal responsiveness correlated with both mental and non-mental state vocabulary acquisition in younger children (approximately 18 months and younger) but not older children. We posit a diminishing role for maternal responsiveness in language acquisition as children grow older.

A comprehensive and effective parallel airborne synthetic aperture radar (SAR) processing system using the architecture of central processing units (CPU) and graphical processing units (GPU) is proposed first in this paper. By using the techniques of Compute Unified Device Architecture, the SAR processing system is much more efficient and robust, thereby enabling it to work with high efficiency. This paper focuses on the optimizations of motion compensation, subaperture chirp scaling algorithm, phase gradient autofocus (PGA), and even visualization with Open Source Computer Vision Library. Apart from this, it is also the first time the PGA has been run on the architecture of CPU and GPU. Experimental results show a speedup of ∼37 times compared with a nonoptimized CPU-based approach.

In intelligent traffic monitoring, speed measuring millimeter waves (MMW) radar is one of the most commonly used tools for traffic enforcement. In traffic enforcement field, the radar must provide the evidence of each vehicle belongs to which lane. In this paper, we propose a novel kernel line segment adaptive possibilistic c-means clustering algorithm (KLSAPCM) for lane determination of vehicles. Firstly, the raw measurement data is preprocessed using the extracting method of data adjacent lane centerlines. Secondly, according to the improved minimum radius data search method, outliers are removed and the proposed KLSAPCM algorithm is initialized. Finally, the accuracy of lane determination has been improved by the proposed KLSAPCM clustering algorithm based on adaptive kernel line segment that conforms to the shape features of the measurement data in the actual scene. The experiment results for multiple scenes were: the KLSAPCM algorithm is compared with the DBSCAN, the k-means, the FCM, the PCM, the AMPCM, and the APCM algorithms on real measurement datasets, and the results highlight the classification rate of the proposed algorithm. Meanwhile, the proposed algorithm gets a good real-time performance and strong robustness for some sparse moving vehicle scene applications. INDEX TERMS MMW radar, radar measurements, lane determination, clustering algorithms. The associate editor coordinating the review of this manuscript and approving it for publication was Chao Tong.

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