Results 201 to 210 of about 248,320 (248)

Single‐Cell Transcriptomic Analysis of Tumor Heterogeneity and the Microenvironment in Pseudomyxoma Peritonei

Advanced Science, EarlyView.
This study presents a single‐cell atlas of pseudomyxoma peritonei spanning primary and paired metastatic lesions. Distinct epithelial substates, stromal remodeling, immune exclusion, lipid metabolic reprogramming, and a candidate angiogenic network were identified in metastatic lesions.
Xi Li, Lei Wang, Lei Ai, Zimeng Li, Zhaochangci Chen, Yuchen Luo, Tianran Zhang, Mengjia Liao, Songhao Wang, Jiajia Cui, Ke Liu, Chengxian Guo, Guodong Liu, Jiye Yin, Wei Wu   +14 more
wiley   +1 more source

Performance–Complexity Trade‐Offs in Battery Lifetime Prediction with Task‐Aware Transformers

Advanced Science, EarlyView.
FAST‐BatPro integrates convolutional feature extraction, flash Attention, and sparse attention for efficient battery lifetime prediction. Using limited early‐cycle data across multiple chemistries and operating conditions, it achieves robust accuracy while reducing inference latency, computational cost, and energy consumption.
Jingyuan Zhao, Misheng Cai, Zhenghong Wang, Yan Wang, Yuqi Li, Bo Dong, Hewu Wang, Andrew F. Burke, Simona Onori, Stephen J. Harris   +9 more
wiley   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

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Data Preprocessing

2021
Abstract This chapter focuses on the process of cleaning data and preparing it for further processing. Specifically, the chapter discusses various techniques that you will use, including preprocessing, outlier identification, data consistency, and the normalization or standardization process, used to normalize your data.
Magy Seif El-Nasr, Truong Huy Nguyen Dinh, Alessandro Canossa, Anders Drachen   +3 more
openaire   +2 more sources

Automated preprocessing of environmental data

Future Generation Computer Systems, 2015
In this article we discuss automated preprocessing of environmental data for further use. Environmental data is by default heterogeneous, as it may consist of data from sources such as weather stations, weather radars, chemical sensors, acoustic sensors, and off-line laboratory analysis.
Mauno Rönkkö, Jani Heikkinen, Ville Kotovirta, Venkatachalam Chandrasekar   +3 more
openaire   +1 more source

Data Preprocessing

2018
Successful reconstruction of a shadow attractor provides preliminary empirical evidence that a signal isolated from observed time series data may be generated by deterministic dynamics. However, because we cannot reasonably expect signal processing to purge the signal of all noise in practice, and because noisy linear behavior can be visually ...
Ray Huffaker, Marco Bittelli, Rodolfo Rosa   +2 more
  +4 more sources

Preprocessing the Data

2010
In this book, we provide tools that are needed to investigate administrative and clinical databases that are routinely collected in the support of patient treatment. Often, these databases are large and require non-traditional methodology to investigate.
Patricia Cerrito, John Cerrito
openaire   +1 more source

Synchronized Preprocessing of Sensor Data

2020 IEEE International Conference on Big Data (Big Data), 2020
Sensor data whether collected for machine learning, deep learning or other applications must be preprocessed to fit input requirements or improve performance and accuracy. Data preparation is an expensive, resource consuming and complex phase often performed centrally on raw data for a specific application.
TAWAKULI, Amal, KAISER, Daniel, ENGEL, Thomas   +2 more
openaire   +2 more sources

Data Quality Visualization for Preprocessing

2016
Preprocessing is often the most time-consuming phase in data analysis and interdependent data quality issues a cause of suboptimal modelling results. The design problem addressed in this paper is: what kind of framework can support visualization of data quality issue interdependencies for faster and more effective preprocessing? An object framework was
openaire   +1 more source

Financial Data Preprocessing Issues

2021
Today the challenge facing every company is the enormous quantity of data being captured, at yearly, monthly, weekly, daily and hourly levels and how this data may be used. Despite the amount of data often this data is limited regarding company processes and their analysis.
Audrius Lopata, Rimantas Butleris, Saulius Gudas, Vytautas Rudzionis, Kristina Rudzioniene, Liutauras Zioba, Ilona Veitaite, Darius Dilijonas, Evaldas Grisius, Maarten Zwitserloot   +9 more
openaire   +1 more source