Loss functions between PCA-DNN model and PCA-LSTM model. by Cihun-Siyong Alex Gong (11874066)

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …”

Performance of PCA and Joint Autoencoder (JAE) denoising algorithms. by Ege Altan (11768156)

Testing function diagram of QIMPN-PCA-DC. by Jun Zhao (59250)

The loss function of network structures, LPC-DNN, LPC-PCA-DNN, LPC-LSTM, LPC-PCA-LSTM, MFCC-DNN, MFCC-PCA-DNN, MFCC-LSTM and MFCC-PCA-LSTM, as the epoch increases. by Cihun-Siyong Alex Gong (11874066)

Reconstructing <i>sparse</i>, binary patterns using message passing algorithms and PCA. by Sebastian Goldt (14522594)

“…<p>We plot the mse per pattern obtained by the AMP algorithm, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e072" target="_blank">Eq (32)</a>, as a function of the effective noise Δ (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e032" target="_blank">9</a>), for random (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e044" target="_blank">15</a>) and informed (<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010813#pcbi.1010813.e045" target="_blank">16</a>) initialisations. …”

A parabolic relationship between prediction errors and learning rates obtained by a cubic learning algorithm. by Boluwatife Ikwunne (22238697)

Multi-functional liquid crystal devices based on random binary matrix algorithm by Tibin Zeng (10890697)

“…<p>Multi-functional diffraction gratings have found broad applications in laser processing, medicine, beam manipulation, etc. …”

Genes that contribute to PCA and GO terms of enriched and differentially expressed genes. GO, gene ontology; PCA, principal component analysis. by Tomokatsu Udagawa (11675636)

Subjects:

PCA2GO Functional Annotation of Immune biological functions significantly enriched p<10E-10) in Stage 1 and stage 2 r-HAT cases. by Peter Nambala (7245215)

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PCA of full simulated repertoire using sequence descriptors. by Katharina Waury (14203284)

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PCA calculation FRHGs score. by Lixia Chen (614030)

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Comparison of UACI among different algorithms. by Feixian Liu (22477943)

“…Based on the 2D-SQSM, this paper further designs a highly robust color image encryption algorithm. First, by introducing different hash functions multiple times, the correlation between the key and plaintext is enhanced, significantly improving resistance against brute-force attacks; second, cyclic shifting and segmentation-recombination operations are applied separately to the three RGB channels to effectively disrupt pixel distribution and significantly reduce spatial correlation between pixels; finally, the chaotic sequence generated by the 2D-SQSM is utilized for XOR diffusion, further enhancing the randomness and diffusion capability of the ciphertext. …”

Comparison of NPCR among different algorithms. by Feixian Liu (22477943)

“…Based on the 2D-SQSM, this paper further designs a highly robust color image encryption algorithm. First, by introducing different hash functions multiple times, the correlation between the key and plaintext is enhanced, significantly improving resistance against brute-force attacks; second, cyclic shifting and segmentation-recombination operations are applied separately to the three RGB channels to effectively disrupt pixel distribution and significantly reduce spatial correlation between pixels; finally, the chaotic sequence generated by the 2D-SQSM is utilized for XOR diffusion, further enhancing the randomness and diffusion capability of the ciphertext. …”

Infrared Spectroscopy Coupled with Machine Learning Algorithms to Investigate Vascular Dysfunction in Ovariectomy: An Animal Model Study by Tháfanys S. Travezani (20609398)

Iteration versus fitness function. by B. Venkatesh (17202747)

Functional PCA With Covariate-Dependent Mean and Covariance Structure by Fei Ding (134577)

“…However, many existing functional PCA methods do not make use of covariates, and those that do often have high computational cost or make overly simplistic assumptions that are violated in practice. …”

Principal Component Analysis (PCA) of the independent dataset from the HPC cohort. by Erica A. K. DePasquale (11851483)

Principal component analysis (PCA) of sub-layer mean intensities. by Maëlle Vilbert (17101954)

Algorithm used for important sampling of the likelihood function. by Zhiyong Huang (3620000)