String-based (or viewpoint) models of tonal harmony often struggle with data sparsity in pattern discovery and prediction tasks, particularly when modeling composite events like triads and seventh chords, since the number of distinct n-note combinations in polyphonic textures is potentially enormous. To address this problem, this study examines the efficacy of skip-grams in music research, an a...

BACKGROUND Proposed variations to Nutrition Facts Labels (NFL) have included the display of added sugars (AS) content, but its impact on consumer understanding is poorly understood. OBJECTIVE To examine the degree to which different formats for displaying AS influence consumer understanding, perceptions, and purchase intentions. DESIGN Randomized-controlled online experiment. PARTICIPANTS...

X-grams are a generalization of the n-grams, where the number of previous conditioning words is different for each case and decided from the training data. X-grams reduce perplexity with respect to trigrams and need less number of parameters. In this paper, the representation of the x-grams using finite state automata is considered. This representation leads to a new model, the non-deterministi...

In this prospective study, birth weight of 304 babies born at Kamla Nehru Hospital Pune during study period was recorded. From these 304 babies, babies with birth weight above 2000 grams were selected (260 babies) to prepare growth velocity curves. Daily weight of these 260 babies was recorded for 30 days. The mean birth weight of study population was 2742.5 grams. Among the daily weight record...

In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem in small amount of training data. The Multi-Class Composite Ngram maintains an accurate word prediction capability and reliability for sparse data with a compact model size based on multiple word clusters, so-called Multi-Classes. In the Multi-Class, the statistical connectivity...

In this paper, a new language model, the Multi-Class Composite N-gram, is proposed to avoid a data sparseness problem for spoken language in that it is difficult to collect training data. The Multi-Class Composite N-gram maintains an accurate word prediction capability and reliability for sparse data with a compact model size based on multiple word clusters, called MultiClasses. In the Multi-Cl...

Two grams of Kahlbaum’s alanine dissolved in 50 cc. of water were oxidized with 500 cc. of a solution containing 10.8 grams of potassium permanganate and 37.0 grams of potassium hydroxide (30 molecules). Vigorous oxidation took place at once and the temperature of the mixture rose to 37” C. After standing for forty-eight hours at room temperature complete decolorization had taken place; the pro...

We present a shallow linguistic approach to subjectivity classification. Using multinomial kernel machines, we demonstrate that a data representation based on counting character n-grams is able to improve on results previously attained on the MPQA corpus using word-based n-grams and syntactic information. We compare two types of string-based representations: key substring groups and character n...