DisCo P-ad: Distance-Correlation-Based <i><b>p</b></i>-Value Adjustment Enhances Multiple Testing Corrections for Metabolomics by Debmalya Nandy, Debashis Ghosh, Katerina Kechris

“…We propose a modification to the <i>p</i>-value adjustment based on a more general measure of association between two predictors, the <i>distance correlation</i>, with a specific focus on MWAS. …”
Get full text

Anomaly Usage Behavior Detection Based on Multi-Source Water and Electricity Consumption Information by Wenqing Zhou, Chaoqiang Chen, Qin Yan, Bin Li, Kang Liu, Yingjun Zheng, Hongming Yang, Hui Xiao, Sheng Su

Subjects: Get full text

Comparative study of power analysis attacks based on template and KNN algorithm by Jifang JIN, Chengyuan LIU, Xiaohong FAN, Xiaoyi DUAN, Jiayu LIU

“…Power analysis attack is still the most threatening type of side channel attack on cryptographic hardware.The template analysis attack with the attack of KNN algorithm was compared.Firstly, three dimensionality reduction methods of Pearson correlation coefficient, mutual information and maximum information coefficient and distance correlation coefficient were studied.Then, the effects of the number of feature points on the attack success rate of the two power analysis attacks under the same number of power consumption curves were compared.At the same time, the effects of different dimensionality reduction techniques on the two power analysis attacks when the number of power curves is the same and different.The results show that the template attack is better than the KNN algorithm attack in running speed, memory occupation and robustness, and the KNN algorithm attack has better performance in attack success rate.…”
Get full text

A social media geolocation method based on comparative learning by Yongchang XU, Shiduo HUANG, Haojun AI

“…Previous work on social media text-based geolocation focused on mapping language semantic space to geospatial space, which ignores the semantic correlation between social media texts and the distance correlation between geographical locations.To take advantage of these correlations, mCLF, a new unsupervised multiple-level contrastive learning framework was proposed, three contrastive learning modules were designed: a semantic learning module, a location learning module, and a cross-learning module.Transformer encoder was used to obtain semantic representation of posts, utilizing unsupervised contrastive learning method to decrease the distance of semantic representations and location representations of posts with near locations, and then fine-tuned the model with supervised method for geographic location regression or classification outputs.Compared with five baseline methods, extensive experiments based on four datasets demonstrate the effectiveness of the proposed framework.…”
Get full text

Nonlinear-Model-Based Analysis Methods for Time-Course Gene Expression Data by Li-Ping Tian, Li-Zhi Liu, Fang-Xiang Wu

“…Many statistic-based significance analysis methods and distance/correlation-based clustering analysis methods have been applied to time-course expression data. …”
Get full text

OSFS‐Vague: Online streaming feature selection algorithm based on vague set by Jie Yang, Zhijun Wang, Guoyin Wang, Yanmin Liu, Yi He, Di Wu

“…Moreover, OSFS‐Vague uses the distance correlation coefficient to classify streaming features into relevant features, weakly redundant features, and redundant features. …”
Get full text

Data-Driven Methodology for the Prediction of Fluid Flow in Ultrasonic Production Logging Data Processing by Hongwei Song, Ming Li, Chaoquan Wu, Qingchuan Wang, Shunke Wei, Mingxing Wang, Wenhui Ma

“…Then, the transducer signal is preprocessed by distance correlation analysis (DCA), and independent features are extracted by principal component analysis (PCA). …”
Get full text

Dual-stream disentangled model for microvascular extraction in five datasets from multiple OCTA instruments by Xiaoyang Hu, Xiaoyang Hu, Jinkui Hao, Quanyong Yi, Yitian Zhao, Jiong Zhang

“…The introduced vascular structure prior includes low-dimensional neighborhood energy from the Distance Correlation Energy (DCE) module, which helps to better perceive the structural information of continuous vessels.Results and discussionTo precisely evaluate our method on small vessels, we delicately establish OCTA microvascular labels by performing comprehensive and detailed annotations on the FOCA dataset, which includes data collected from different instruments, and evaluated the proposed D2Net effectively mitigates the challenges of microvasculature region recognition caused by noise and artifacts. …”
Get full text

Stochastic renormalization group and gradient flow by Andrea Carosso

“…The result implies a new approach to Monte Carlo RG that is amenable to lattice simulation. Long-distance correlations of the effective theory are shown to approach gradient-flowed correlations, which are simpler to measure. …”
Get full text

Two-dimensional stationary soliton gas by Thibault Bonnemain, Gino Biondini, Benjamin Doyon, Giacomo Roberti, Gennady A. El

“…We also explicitly evaluate the long-distance correlations for the two-component interference configurations. …”
Get full text

Phenotypic plasticity vs. local genetic adaptation: essential oil diversity of natural immortelle (Helichrysum italicum (Roth.) G.Don) populations along eastern Adriatic coast by Tonka Ninčević Runjić, Dejan Pljevljakušić, Marko Runjić, Martina Grdiša, Martina Grdiša, Zlatko Šatović, Zlatko Šatović

“…Results showed a significant and strong correlation between biochemical and bioclimatic distance, with 22.4% of biochemical differentiation between populations explained by bioclimatic distance. Correlations between the 18 main compounds and the bioclimatic variables of the populations’ native environment revealed that BIO14 Precipitation of driest month and BIO15 Precipitation seasonality, were the most informative. …”
Get full text