Results 91 to 100 of about 4,055 (251)

Porous Carbon Materials for Carbon Dioxide Capture

Carbon Energy, EarlyView.
This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu, Chuhan Fu, Tao Qi, Hui Zhou, Guangping Hao, Yalou Guo, Guoping Hu   +6 more
wiley   +1 more source

Artificial intelligence in enzyme catalysis: Emerging trends and applications in biocatalyst engineering

The Canadian Journal of Chemical Engineering, EarlyView.
Schematic representation of artificial intelligence approaches in enzyme catalysis, integrating bibliometric analysis, emerging research trends, and machine learning tools for enzyme design, prediction, and industrial biocatalytic applications. Abstract This study systematically explores the applications of artificial intelligence (AI) in enzyme ...
Misael Bessa Sales, Francisco Izaias da Silva Aires, Paulo Gonçalves de Sousa Junior, Calebe Da Rocha Silva, Emanuel Lino Rodrigues, Maria Cristiane Martins de Souza, José C. S. dos Santos   +6 more
wiley   +1 more source

Vine copula knockoffs for variable selection in gene expression studies

Canadian Journal of Statistics, EarlyView.
Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina, Alejandro Román Vásquez, Graciela González Farías, Gabriel Escarela   +3 more
wiley   +1 more source

On the Trail of Creativity: Dimensionality of Divergent Thinking and Its Relation With Cognitive Abilities, Personality, and Insight

European Journal of Personality, EarlyView., 2020
Abstract Divergent thinking (DT) is an important constituent of creativity that captures aspects of fluency and originality. The literature lacks multivariate studies that report relationships between DT and its aspects with relevant covariates, such as cognitive abilities, personality traits (e.g. openness), and insight. In two multivariate studies (N 
S. Weiss, D. Steger, Y. Kaur, A. Hildebrandt, U. Schroeders, O. Wilhelm, Christian Kandler   +6 more
wiley   +1 more source

Multivariate fault classification in electrical distribution systems using empirical mode decomposition and machine learning

Discover Artificial Intelligence
The reliability and efficiency of electrical distribution systems are critical for maintaining uninterrupted power supply and minimizing disruptions caused by faults, which can lead to extensive outages and safety hazards.
Mihir Sinha, Mayukha Pal
doaj   +1 more source

Advances and applications of empirical mode decomposition and its variants in hydrology: A review

Guan'gai paishui xuebao
Hydrological series are influenced by climate change, ecological succession, and human activities, containing complex, multi-layered, and interactive information that reflects highly non-linear and non-stationary characteristics.
CHEN Yunfei, LIU Zuyu, LIU Xiuhua, HE Junqi, ZHENG Ce, MA Yandong   +5 more
doaj   +1 more source

Optimal subsampling for regression with mixed‐type predictors

Canadian Journal of Statistics, EarlyView.
Abstract Subsampling has emerged as an appealing strategy to mitigate the computational and storage challenges imposed by large datasets. Recent subsampling techniques have shown notable computational gains for data dominated by numerical predictors. However, real‐world datasets frequently contain both numerical and categorical predictors.
Jiaqing Zhu, Lin Wang, Fasheng Sun
wiley   +1 more source

Homophily‐adjusted social influence estimation

Canadian Journal of Statistics, EarlyView.
Abstract Homophily and social influence are two key concepts of social network analysis. Distinguishing between these phenomena is difficult, and approaches to disambiguate the two have been primarily limited to longitudinal data analyses. In this study, we provide sufficient conditions for valid estimation of social influence through cross‐sectional ...
Hanh T.D. Pham, Daniel K. Sewell
wiley   +1 more source

Large parameter asymptotic analysis for homogeneous normalized random measures with independent increments

Canadian Journal of Statistics, EarlyView.
Abstract Homogeneous normalized random measures with independent increments represent a broad class of Bayesian nonparametric priors and thus are widely used. In this article, we obtain the strong law of large numbers, the central limit theorem (CLT), and the functional central limit theorem (fCLT) of such measures when the concentration parameter a ...
Junxi Zhang, Shui Feng, Yaozhong Hu
wiley   +1 more source

Aplikasi Filter Multivariate Empirical Mode Decomposition (MEMD) Untuk Mereduksi Noise Pada Data VLF-EM

Jurnal Teknik ITS, 2017
Alat VLF-EM menangkap gelombang elektromagnetik dari medium-medium disekitarnya. Sehingga, alat VLF-EM ini sangat sensitif terhadap benda-benda yang memiliki komponen listrik dan magnet yang besar.
Muhammad Shafran Shofyan
doaj