The influence of word size and tonal sequence probability on Mandarin well-formedness judgments

2019 ◽  
Vol 146 (4) ◽  
pp. 3053-3053
Author(s):  
Amy LaCross ◽  
Jordan Sandoval ◽  
Julie Liss
Keyword(s):  
2018 ◽  
Vol 144 (3) ◽  
pp. 1801-1801
Author(s):  
Amy LaCross ◽  
Jordan Sandoval ◽  
Julie Liss
Keyword(s):  

1994 ◽  
Vol 04 (04) ◽  
pp. 429-436 ◽  
Author(s):  
SANJEEV SAXENA ◽  
P.C.P. BHATT ◽  
V.C. PRASAD

We prove that prefix sums of n integers of at most b bits can be found on a COMMON CRCW PRAM in [Formula: see text] time with a linear time-processor product. The algorithm is optimally fast, for any polynomial number of processors. In particular, if [Formula: see text] the time taken is [Formula: see text]. This is a generalisation of previous result. The previous [Formula: see text] time algorithm was valid only for O(log n)-bit numbers. Application of this algorithm to r-way parallel merge sort algorithm is also considered. We also consider a more realistic PRAM variant, in which the word size, m, may be smaller than b (m≥log n). On this model, prefix sums can be found in [Formula: see text] optimal time.


2013 ◽  
Vol 756-759 ◽  
pp. 1387-1391
Author(s):  
Xiao Dong Wang ◽  
Jun Tian

Building an efficient data structure for range selection problems is considered. While there are several theoretical solutions to the problem, only a few have been tried out, and there is little idea on how the others would perform. The computation model used in this paper is the RAM model with word-size . Our data structure is a practical linear space data structure that supports range selection queries in time with preprocessing time.


Author(s):  
Martin H. Weik
Keyword(s):  

1996 ◽  
Vol 39 (1) ◽  
pp. 76-92 ◽  
Author(s):  
Pascal H.H.M. van Lieshout ◽  
Wouter Hulstijn ◽  
Herman F.M. Peters

The main purpose of the present study was to test the hypothesis that persons who stutter, when compared to persons who do not stutter, are less able to assemble abstract motor plans for short verbal responses. Subjects were adult males who stutter and age- and sex-matched control speakers, who were tested on naming pictures and words, using a choice-reaction time paradigm for both tasks. Words varied in the number of syllables (1, 2, and 3 syllables) and, for the bisyllabic words, also in the number of consonants (one or more) at the onset of the second syllable. Measurements consisted of speech reaction times, word durations, and measures of relative timing of specific motor events in the respiratory, phonatory, and articulatory subsystems. Results indicated that, in spite of longer speech reaction times for persons who stutter in comparison to control speakers, there was no interaction with word size, a finding that does not lend support to the abovementioned hypothesis. Word durations were found to be longer for persons who stutter, and, in addition, there was an interaction of group with word size. Both findings were associated with longer delays for persons who stutter in the onset of upper lip integrated electromyographic (IEMG) activity and thoracic compression, and a group effect on the order of upper lip and lower lip IEMG onset. Findings are taken to suggest the possibility that persons who stutter may use different motor control strategies to compensate for a reduced verbal motor skill, and although the nature of this reduced skill is unknown, it is speculated that it relates to the processes involved in the integration of sensory-motor information.


1979 ◽  
Vol 17 (5) ◽  
pp. 539-542 ◽  
Author(s):  
Brian Byrne ◽  
Judith Sinclair
Keyword(s):  

2000 ◽  
Vol 7 (4) ◽  
Author(s):  
Rasmus Pagh

We consider dictionaries over the universe U = {0, 1}^w on a unit-cost<br />RAM with word size w and a standard instruction set. We present<br />a linear space deterministic dictionary with membership queries in<br />time (log log n)^O(1) and updates in time (log n)^O(1), where n is the size<br />of the set stored. This is the first such data structure to simultaneously<br />achieve query time (log n)^o(1) and update time O(2 ^sqrt log n) ).


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