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It is a fixed-length vector with L entries equal to the total number of slot values.
where (underline {mathbf {h}}_{p}) is the pth-order redundancy-removed coefficient vector, which is composed of coefficients (underline {h}_{p(m_{1},dots},m_{p}m_{p})}), and (underline {mathbf {x}}_{p}(n) = mathbf {L}_{p} [mathbf {x}_{p-1}(n) otimes mathbf {x}_{1}(n)] ) is the pth-order redundancy-removed input vector with L p denoting the pth-order elimination matrix [9].
Y i denotes the Gene Ontology terms which are assigned to X i, and Y i = [ y i,1,…, y i, L ] ∈ {0,1} L is a label vector with L labels, where y i, l = +1 if the lth label is positive for X i, and 0 otherwise.
Y i denotes the labels which are assigned to X i, and Y i = [ y i,1,…, y i, L ] ∈ {0,1} L is a label vector with L labels, where y i, l = +1 if the lth label is positive for X i, and 0 otherwise.
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According to the basic implementation of QIM, called binary dither modulation (DM), the watermark message m is first represented by a vector b with L binary components, i.e., b j ∈{0,1},⋯,1,⋯,L.
The first derivative of the scoring function is a one dimensional vector with 3 l elements.
[S] m is a syndrome vector with (l+ 1) values, in this class of codes (n - k) equal 1.
Each instance is then represented by a sequence of m sized vectors with length l, where m is the alphabet size and l is the length of the character sequences.
Moreover, b (x ) ∈ R d is a vector with b ∈ L ∞ (Ω ; R d ) and c (x ) ∈ R is a scalar with c ∈ L ∞.
Notation: Column vectors (matrices) are denoted using lower-case (upper-case) boldface letters; calligraphic letters are reserved for sets; T stands for transposition, N ( μ, σ 2 ) denotes the Gaussian probability density function with mean μ and variance σ2; ⊗ denotes the Kronecker product; 0 L is the L-dimensional column vector with all zeros, and I L is the L-dimensional identity matrix.
At the transmitter, the source S with binary values is a vector with the length L s, i.e., (phantom {dot {i}!}mathbf {S}=[S_{1}, cdot cdot cdot, S_{L_{s}}]).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com