Results 61 to 70 of about 53,359 (288)

Unsupervised Feature Selection by Pareto Optimization

Proceedings of the AAAI Conference on Artificial Intelligence, 2019
Dimensionality reduction is often employed to deal with the data with a huge number of features, which can be generally divided into two categories: feature transformation and feature selection. Due to the interpretability, the efficiency during inference and the abundance of unlabeled data, unsupervised feature selection has attracted much attention ...
Chao Feng 0006, Chao Qian 0001, Ke Tang 0001   +2 more
openaire   +2 more sources

Filter feature selection for unsupervised clustering of designer drugs using DFT simulated IR spectra data

, 2021
The rapid emergence of novel psychoactive substances (NPS) poses new challenges and requirements for forensic testing/analysis techniques. This paper aims to explore the application of unsupervised clustering of NPS compounds\u27 infrared spectra.
Kedan, He
core   +1 more source

PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science

Advanced Engineering Materials, EarlyView.
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley   +1 more source

An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials

Advanced Engineering Materials, EarlyView.
An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

Unsupervised Minimum Redundancy Maximum Relevance Feature Selection for Predictive Maintenance: Application to a Rotating Machine

International Journal of Prognostics and Health Management, 2021
Identifying and selecting optimal prognostic health indicators in the context of predictive maintenance is essential to obtain a good model and make accurate predictions.
Valentin Hamaide , François Glineur
doaj   +1 more source

Unsupervised Streaming Feature Selection in Social Media

, 2015
The explosive growth of social media sites brings about mas-sive amounts of high-dimensional data. Feature selection is effective in preparing high-dimensional data for data an-alytics.
Xia Hu, Huan Liu, Jiliang Tang, Jundong Li   +3 more
core   +1 more source

Printed Integrated Logic Circuits Based on Chitosan‐Gated Organic Transistors for Future Edible Systems

Advanced Functional Materials, EarlyView.
Edible electronics needs integrated logic circuits for computation and control. This work presents a potentially edible printed chitosan‐gated transistor with a design optimized for integration in circuits. Its implementation in integrated logic gates and circuits operating at low voltage (0.7 V) is demonstrated, as well as the compatibility with an ...
Giulia Coco, Valerio Francesco Annese, Valerio Galli, Ilaria Penna, Debora Russo, Marina Veronesi, Rita Scarpelli, Stefania Sabella, Mario Caironi   +8 more
wiley   +1 more source

Pull‐and‐Push Nanotherapeutic Hydrogels: Scavenging Inflammatory Triggers While Driving Tissue Regeneration in Burn Wounds

Advanced Functional Materials, EarlyView.
A nanounit‐assembled hydrogel employing a “pull‐and‐push” strategy simultaneously scavenges pro‐inflammatory cell‐free DNA (cfDNA) and delivers regenerative therapeutics in response to burn‐induced hyperthermia. By repolarizing macrophages and promoting angiogenesis, this multifunctional platform accelerates burn wound healing, offering a blueprint for
Han‐Sem Kim, Seong‐Jin Shin, Sak Lee, Nandin Mandakhbayar, Ji‐Hye Kang, Da‐Young Kong, Seong‐Doo Hong, Ueon Sang Shin, Hae‐Won Kim, Jung‐Hwan Lee   +9 more
wiley   +1 more source

Application of Unsupervised Feature Selection in Cashmere and Wool Fiber Recognition

Journal of Natural Fibers
Suitable features are the key to identifying cashmere and wool fibers, and feature selection is an important step in classification. Existing supervised feature selection methods need to consider the information between fiber features and class labels ...
Yaolin Zhu, Xingze Wang, Meihua Gu, Gang Hu, Wenya Li   +4 more
doaj   +1 more source

Bi-Sparse Unsupervised Feature Selection

IEEE Transactions on Image Processing
To deal with high-dimensional unlabeled datasets in many areas, principal component analysis (PCA) has become a rising technique for unsupervised feature selection (UFS). However, most existing PCA-based methods only consider the structure of datasets by embedding a single sparse regularization or constraint on the transformation matrix. In this paper,
Xianchao Xiu, Chenyi Huang, Pan Shang, Wanquan Liu   +3 more
openaire   +3 more sources