Guo YF, Li J, Bonham AJ, Wang YP, Deng HW (2009) Gains in power for exhaustive analyses of haplotypes using variable-sized sliding window strategy: a comparison of association-mapping strategies. Eur J Hum Genet 17:785–792 Central
With decreasing grain sizes,its crystal structure、ferroelectricity and phase transition temperature all indicated the character of size effect. 随着晶粒尺寸的减小,它的晶体结构、铁电性和相变温度等都表现出尺寸效应。 更多例句>> 4) phase change temperature 相变温度 1. The text prepared a kind of co...
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An apparatus and method for turbo decoding using a variable window size. A control logic block receives information about a code rate of received data bits and a data block size, ad
Initially, the speech signal is considered as input and the FMPM features are extracted using FDLP, MHEC and PNCC including MFCC based on the variable size of a sliding window. Here, the sliding window size is optimized by Modified Grey Wolf Optimization (MGWO) algorithm which is also used ...
sliding windows in adapting to evolving data streams, we propose a variable sliding window frequent pattern mining algorithm, which dynamically adjusts the window size to adapt to new concept drifts and detect them in a timely manner. Furthermore, considering the challenge of existing concept drift...
sliding window of size \(\ln (120)=5\) within each row; (3) a per-column-average time series with 60 entries, each representing the average expression level within the corresponding column; and (4) a within-column-window-average time series with \(60\times \frac{120}{\ln (60)}=...
In dictionary coding, LZ77 refers to the Sliding Window Lempel-Ziv algorithm created in 1977 by Abraham Lempel and Jacob Ziv. LZW (Lempel-Ziv-Welch) refers to the universal lossless data compression algorithm created by Abraham Lempel, Jacob Ziv, and Terry Welch. LZ77 algorithms achieve compressio...
(2) a within-row-window-average time series with\(120\times \frac{60}{\ln (120)}=1440\)entries, where each entry is derived from averaging expression levels within a non-overlapping sliding window of size\(\ln (120)=5\)within each row; (3) a per-column-average time series with ...
Presented in Algorithm 1 is the fundamental framework. Algorithm 1. The framework of MFPSO. Input: Population size N, Random matching probability rmp Output: Population P, the optimal solution pgk,gen for task Tk. 1. Initialize to generate a population of size N denoted as P; 2. Calculate...