Results 61 to 70 of about 72,703 (318)

ProSiteHunter: A Unified Framework for Sequence‐Based Prediction of Protein‐Nucleic Acid and Protein‐Protein Binding Sites

Advanced Science, EarlyView.
This study proposed a unified sequence‐based framework for protein binding site prediction, which adopted a tri‐track semantic multi‐source feature fusion strategy to effectively capture diverse macromolecular interaction sites and further improved the accuracy of antibody‐antigen interaction prediction.
Dongliang Hou, Qihang Zhen, Zexin Lv, Xinyue Cui, Suhui Wang, Minghua Hou, Zhan Zhou, Xiaogen Zhou, Guijun Zhang   +8 more
wiley   +1 more source

A Distributed Sensor-Based Recursive Framework for DoA Estimation and Geolocation

IEEE Access
This paper proposes a distributed sensor-based RECursive Subspace and Factor Graph (REC-SaFG) framework for direction-of-arrival (DoA) estimation and geolocation of a fast-moving target.
Lei Jiang, Nopphon Keerativoranan, Tad Matsumoto, Jun-Ichi Takada   +3 more
doaj   +1 more source

An Efficient Algorithm for Direction Finding against Unknown Mutual Coupling

Sensors, 2014
In this paper, an algorithm of direction finding is proposed in the presence of unknown mutual coupling. The preliminary direction of arrival (DOA) is estimated using the whole array for high resolution.
Weijiang Wang, Shiwei Ren, Yingtao Ding, Haoyu Wang   +3 more
doaj   +1 more source

Subspace Approximation with Outliers [PDF]

, 2020
The subspace approximation problem with outliers, for given $n$ points in $d$ dimensions $x_{1},\ldots, x_{n} \in R^{d}$, an integer $1 \leq k \leq d$, and an outlier parameter $0 \leq α\leq 1$, is to find a $k$-dimensional linear subspace of $R^{d}$ that minimizes the sum of squared distances to its nearest $(1-α)n$ points.
Amit Deshpande 0001, Rameshwar Pratap
openaire   +2 more sources

Matched direction detectors and estimators for array processing with subspace steering vector uncertainties [PDF]

, 2005
In this paper, we consider the problem of estimating and detecting a signal whose associated spatial signature is known to lie in a given linear subspace but whose coordinates in this subspace are otherwise unknown, in the presence of subspace ...
Besson, Olivier, Scharf, Louis, Vincent, François   +2 more
core  

A Phase‐Resolved Geometric Deep Learning Framework Maps Structural Determinants of Disease‐Associated Protein Aggregation and Guides Suppressor Design

Advanced Science, EarlyView.
SKALE 2.0 maps disease‐associated protein aggregation as a phase‐resolved structural process, linking mutation‐induced geometric perturbations to nucleation, elongation, and suppressor design. Across neurodegenerative proteins, the framework reveals cryptic aggregation vulnerabilities, separates phase‐concordant and phase‐switching mutations, and ...
Jia Shen Sio, Wei Xuan Wilson Loo, Yan Shan Loo, Wen Xin Tan, Hui Xuan Lim, Huitao Liu, Chen Seng Ng   +6 more
wiley   +1 more source

Substation Equipment 3D Identification Based on KNN Classification of Subspace Feature Vector

Journal of Intelligent Systems, 2017
Aiming to realize rapid and efficient three-dimensional (3D) identification of substation equipment, this article proposes a new method in which the 3D identification of substation equipment is based on K-nearest neighbor (KNN) classification of subspace
Guo Weiying, Ji Yong, Luo Yong, Zhou Yan
doaj   +1 more source

Higgledy-piggledy subspaces and uniform subspace designs [PDF]

Designs, Codes and Cryptography, 2016
In this article, we investigate collections of `well-spread-out' projective (and linear) subspaces. Projective $k$-subspaces in $\mathsf{PG}(d,\mathbb{F})$ are in `higgledy-piggledy arrangement' if they meet each projective subspace of co-dimension $k$ in a generator set of points.
Fancsali, Szabolcs, Sziklai, Péter
openaire   +4 more sources

Discriminative Semantic Subspace Analysis for Relevance Feedback

, 2016
Content-based image retrieval (CBIR) has attracted much attention during the past decades for its potential practical applications to image database management. A variety of relevance feedback (RF) schemes have been designed to bridge the gap between low-
Zhang, Lining, Lining Zhang, Shao, Ling, Shum, Hubert P. H., Ling Shao, Hubert P. H. Shum, Shum, Hubert   +6 more
core   +1 more source

Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates

Advanced Science, EarlyView.
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao, Yufei Liu, Ruixi Huang, Zhongxue Gan, Siyang Leng   +4 more
wiley   +1 more source