44,961 research outputs found
Repetition Detection in a Dynamic String
A string UU for a non-empty string U is called a square. Squares have been well-studied both from a combinatorial and an algorithmic perspective. In this paper, we are the first to consider the problem of maintaining a representation of the squares in a dynamic string S of length at most n. We present an algorithm that updates this representation in n^o(1) time. This representation allows us to report a longest square-substring of S in O(1) time and all square-substrings of S in O(output) time. We achieve this by introducing a novel tool - maintaining prefix-suffix matches of two dynamic strings.
We extend the above result to address the problem of maintaining a representation of all runs (maximal repetitions) of the string. Runs are known to capture the periodic structure of a string, and, as an application, we show that our representation of runs allows us to efficiently answer periodicity queries for substrings of a dynamic string. These queries have proven useful in static pattern matching problems and our techniques have the potential of offering solutions to these problems in a dynamic text setting
Understanding maximal repetitions in strings
The cornerstone of any algorithm computing all repetitions in a string of
length n in O(n) time is the fact that the number of runs (or maximal
repetitions) is O(n). We give a simple proof of this result. As a consequence
of our approach, the stronger result concerning the linearity of the sum of
exponents of all runs follows easily
COMPARISON OF CONCENTRIC MOVEMENT VELOCITY WITH PUSH BAND 2.0 AND VICON MOTION CAPTURE DURING RESISTANCE EXERCISES
We compared concentric movement velocity (CMV) measured with PUSH Bands (v.2.0) and a Vicon motion capture system (MC) during back squat (SQ) and bench press (BP) resistance exercises (RE) completed using a 2-dimensional smith machine. Twelve experienced resistance-trained males completed 10 repetitions at 50% of 1-repetiton maximum (1RM), and 6 repetitions at 75% 1RM for both BP and SQ. Use of Least-squares means contrasts suggests CMV measures did not differ between measurement technologies. Also, there is no indication of systematic bias between PUSH and MC. PUSH provides an accurate and reliable measurement of CMV during moderate and high intensity SQ and BP as compared with MC
A Minimal Periods Algorithm with Applications
Kosaraju in ``Computation of squares in a string'' briefly described a
linear-time algorithm for computing the minimal squares starting at each
position in a word. Using the same construction of suffix trees, we generalize
his result and describe in detail how to compute in O(k|w|)-time the minimal
k-th power, with period of length larger than s, starting at each position in a
word w for arbitrary exponent and integer . We provide the
complete proof of correctness of the algorithm, which is somehow not completely
clear in Kosaraju's original paper. The algorithm can be used as a sub-routine
to detect certain types of pseudo-patterns in words, which is our original
intention to study the generalization.Comment: 14 page
Fewest repetitions in infinite binary words
A square is the concatenation of a nonempty word with itself. A word has
period p if its letters at distance p match. The exponent of a nonempty word is
the quotient of its length over its smallest period.
In this article we give a proof of the fact that there exists an infinite
binary word which contains finitely many squares and simultaneously avoids
words of exponent larger than 7/3. Our infinite word contains 12 squares, which
is the smallest possible number of squares to get the property, and 2 factors
of exponent 7/3. These are the only factors of exponent larger than 2. The
value 7/3 introduces what we call the finite-repetition threshold of the binary
alphabet. We conjecture it is 7/4 for the ternary alphabet, like its repetitive
threshold
On the maximal number of cubic subwords in a string
We investigate the problem of the maximum number of cubic subwords (of the
form ) in a given word. We also consider square subwords (of the form
). The problem of the maximum number of squares in a word is not well
understood. Several new results related to this problem are produced in the
paper. We consider two simple problems related to the maximum number of
subwords which are squares or which are highly repetitive; then we provide a
nontrivial estimation for the number of cubes. We show that the maximum number
of squares such that is not a primitive word (nonprimitive squares) in
a word of length is exactly , and the
maximum number of subwords of the form , for , is exactly .
In particular, the maximum number of cubes in a word is not greater than
either. Using very technical properties of occurrences of cubes, we improve
this bound significantly. We show that the maximum number of cubes in a word of
length is between and . (In particular, we improve the
lower bound from the conference version of the paper.)Comment: 14 page
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