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This work describes the algorithms used in a prototypical software system for automatic pronunciation assessment of Mandarin Chinese. The system uses Viterbi decoding to isolate each syllable and find the log probability of a given utterance based on HMM (hidden Markov models). The isolated syllables are then sent to a GMM (Gaussian mixture model) for tone(More)
Software test is a very important phase in software development, and an important means to ensure the software's reliability. Path-oriented testing is a main approach in software test. In this paper, an automated test data generation method for linear approximation of bifurcation function is proposed. Combined with predicate slice and definition-use-control(More)
An energy-efficient nonvolatile intelligent processor (NIP) is proposed for battery-less energy harvesting system. This NIP employs RRAM-based nonvolatile logics (NVL) with self-write-termination (SWT) scheme and low-power processing-in-memory (PIM) to achieve energy-efficient computing against frequent power-off situations. An NIP test chip was fabricated(More)
Fast image search with efficient additive kernels and kernel locality-sensitive hashing has been proposed. As to hold the kernel functions, recent work has probed methods to create locality-sensitive hashing, which guarantee our approach's linear time; however existing methods still do not solve the problem of locality-sensitive hashing (LSH) algorithm and(More)
This study aimed to determine the effects of fructooligosaccharide (FOS) levels and its feeding modes on growth, immune response, antioxidant capability and disease resistance of blunt snout bream (Megalobrama amblycephala). Fish (12.5 ± 0.5 g) were subjected to three FOS levels (0, 0.4% and 0.8%) and two feeding modes (supplementing FOS continuously and(More)
Approximate nearest neighbor search is a good method for large-scale image retrieval. We put forward an effective deep learning framework to generate binary hash codes for fast image retrieval after knowing the recent benefits of convolutional neural networks (CNNs). Our concept is that we can learn binary codes by using a hidden layer to present the latent(More)
This paper concentrates on the issue of finite-time controller design for periodic systems with random transmission delays over networked control systems. The definitions of stochastic finite-time stability and finite-time boundedness are respectively given at the beginning of this paper. Then, based on the Lyapunov function and the linear matrix(More)
Emerging memory devices enable performance improvements in memory applications and make possible chip designs using beyond von Neumann architectures. This paper explores the use of emerging memory devices in applications of nonvolatile logics and neuromorphic computing, and provides a review of several silicon examples of nonvolatile logics. This paper also(More)