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—Resilience to packet loss is a critical requirement in predictive video coding for transmission over packet-switched networks , since the prediction loop propagates errors and causes substantial degradation in video quality. This work proposes an algorithm to optimally estimate the overall distortion of decoder frame reconstruction due to quantization,(More)
With the widespread use of electronic health record (EHR), building a secure EHR sharing environment has attracted a lot of attention in both healthcare industry and academic community. Cloud computing paradigm is one of the popular healthIT infrastructure for facilitating EHR sharing and EHR integration. In this paper we discuss important concepts related(More)
— We propose an algorithm for efficient threshold network synthesis of arbitrary multi-output Boolean functions. Many nanotechnologies, such as resonant tunneling diodes (RTDs), quantum cellular automata (QCA), and single electron tunneling (SET), are capable of implementing threshold logic efficiently. The main purpose of this work is to bridge the current(More)
—Massive multiple-input multiple-output (MIMO) wireless communications refers to the idea equipping cellular base stations (BSs) with a very large number of antennas, and has been shown to potentially allow for orders of magnitude improvement in spectral and energy efficiency using relatively simple (linear) processing. In this paper, we present a(More)
Mobile payment is an emerging and important application of mobile commerce. The adoption and use of mobile payment services are critical for both service providers and investors to profit from such an innovation. The present study attempts to identify the determinants of pre-adoption of mobile payment services and explore the temporal evolution of these(More)
Extracting informative image features and learning effective approximate hashing functions are two crucial steps in image retrieval. Conventional methods often study these two steps separately, e.g., learning hash functions from a predefined hand-crafted feature space. Meanwhile, the bit lengths of output hashing codes are preset in the most previous(More)
Pattern matching in stock time series is an active research area in data mining. We propose a new real-time hybrid pattern-matching algorithm in this paper. The algorithm is based on the Spearman's rank correlation, rule sets and sliding window. The concept of sliding windows enables patterns matching to be performed only based on subsequence of stock data(More)
Distributed word representations have been widely used and proven to be useful in quite a few natural language processing and text mining tasks. Most of existing word embedding models aim at generating only one embedding vector for each individual word, which, however, limits their effectiveness because huge amounts of words are polysemous (such as bank and(More)