Results 81 to 90 of about 5,787,304 (258)

Another Look at Measures of Forecast Accuracy [PDF]

We discuss and compare measures of accuracy of univariate time series forecasts. The methods used in the M-competition and the M3-competition, and many of the measures recommended by previous authors on this topic, are found to be inadequate, and many of
Anne B. Koehler, Rob J. Hyndman
core  

DDSurfer: A Weakly‐Supervised Dual‐Stream Deep Learning Framework for Cortical Surface Reconstruction From Diffusion MRI

Advanced Science, EarlyView.
DDSurfer reconstructs cortical surfaces directly from diffusion MRI without requiring T1‐weighted scans. By fusing complementary microstructural features and learning diffeomorphic deformations, it efficiently generates accurate white matter and pial surfaces, improving geometric fidelity and morphometric reliability across datasets for robust surface ...
Chengjin Li, Wei Zhang, Xi Zhu, Yuqian Chen, Nir A. Sochen, Jarrett Rushmore, Carl‐Fredrik Westin, Yogesh Rathi, Lauren J. O'Donnell, Ofer Pasternak, Fan Zhang   +10 more
wiley   +1 more source

Quantitative Assessment of Brix in Grafted Melon Cultivars: A Machine Learning and Regression-Based Approach

Foods
The article demonstrates the Brix content of melon fruits grafted with different varieties of rootstock using Support Vector Regression (SVR) and Multiple Linear Regression (MLR) model approaches.
Uğur Ercan, Ilker Sonmez, Aylin Kabaş, Onder Kabas, Buşra Calık Zyambo, Muharrem Gölükcü, Gigel Paraschiv   +6 more
doaj   +1 more source

MMSE-based waveform design for the distributed MIMO radar in spectrally crowded environments

The Journal of Engineering, 2019
This study investigates the waveform design problem for a distributed multiple-input-multiple-output (MIMO) radar operating in spectrally crowded environments.
Bo Tang, Ning Zhang, Shuo Zhang, Zhongrui Huang   +3 more
doaj   +1 more source

Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning

Advanced Science, EarlyView.
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley   +1 more source

Nonlinear Equalization for Optical Communications Based on Entropy-Regularized Mean Square Error [PDF]

, 2022
An entropy-regularized mean square error (MSE-X) cost function is proposed for nonlinear equalization of short-reach optical channels. For a coherent optical transmission experiment, MSE-X achieves the same bit error rate as the standard MSE cost ...
Diedolo, Francesca, Schädler, Maximilian, Calabró, Stefano, Böcherer, Georg   +3 more
core  

Cancer‐Associated BCL‐2 Mutants Reveal Mechanisms Towards Venetoclax Resistance

Advanced Science, EarlyView.
Venetoclax (VEN) resistance in chronic lymphocytic leukemia arises from diverse BCL2 mutations. We map mechanisms contributing to VEN resistance across common BCL‐2 variants. G101V and D103Y reduce drug binding and increase sequestration of pro‐apoptotic proteins. V156D blocks VEN allosterically.
Jonas Aufdermauer, Ian de Ridder, Mahjoobeh Ehsani, Marasim Khan, Justin Kale, Lukas P. Frenzel, David Andrews, Spyridoula Karamanou, Ana J. Garcia‐Saez, Geert Bultynck   +9 more
wiley   +1 more source

NbOx Mott Memristor‐Based Oscillatory P‐trit for Ternary Potts Machine

Advanced Science, EarlyView.
A ternary Potts machine utilizing NbOx‐based probabilistic trits (p‐trits) is demonstrated for efficient combinatorial optimization. By leveraging the electro‐thermal switching dynamics of NbOx memristors, this architecture generates three‐state stochastic fluctuations.
Hakseung Rhee, Seoeun Jang, Tae Wook Go, Woojoon Park, Gwangmin Kim, Do Hoon Kim, Hanchan Song, Younghyun Lee, Junmo Kang, Daehee Kim, Kyung Min Kim   +10 more
wiley   +1 more source

A neural network prediction analysis of breakout continuous casting based on differential evolution (DE)

Metalurgija, 2020
In order to predict the breakout of continuous casting accurately and timely, a breakout prediction neural network (BPNN) model based on differential evolution algorithm was proposed. Differential evolutionary algorithm is introduced to solve the problem
Y. R. Li, C. N. Zhang
doaj  

Deep Learning Prediction of O‐Glycopeptide Tandem Mass Spectra Enhances O‐Glycoproteomics

Advanced Science, EarlyView.
DeepGPO integrates Transformer and graph neural networks with tailored training strategies, including data augmentation, loss re‐weighting, and pre‐training, to achieve high‐quality O‐glycopeptide MS/MS spectra prediction. The predicted MS/MS spectra are used to localize O‐glycosylation sites from HCD MS/MS data, enhancing O‐glycoproteomics analysis ...
Yu Zong, Yuxin Wang, Liang Qiao
wiley   +1 more source