Results 31 to 40 of about 7,040 (158)
, 2017 New social and economic activities massively exploit big data and machine learning algorithms to do inference on people's lives. Applications include automatic curricula evaluation, wage determination, and risk assessment for credits and loans. Recently,
Camps-Valls, Gustau +5 more
core +1 more source
Protein Science, Volume 35, Issue 1, January 2026.Abstract Intrinsically disordered proteins (IDPs) lack stable tertiary structure and instead exist as dynamic ensembles of conformations, playing essential roles in cellular regulation, signaling, and disease. As structural ensembles of IDPs become increasingly available through databases such as the Protein Ensemble Database (PED) and various ...
Hamidreza Ghafouri +3 more
wiley +1 more source
Imagined Chinese Speech Decoding Based on Initials and Finals From EEG Activity
IET Signal Processing, Volume 2026, Issue 1, 2026.Brain‐computer interface (BCI) plays an important role in various fields, such as neuroscience, rehabilitation, and machine learning. The silent BCI, which can reconstruct inner speech from neural activity, holds great promise for aphasia patients. In this paper, we design an imagined Chinese speech experimental paradigm based on initials and finals ...
Jingyu Gu +4 more
wiley +1 more source
Exploring the Power of Machine Learning in Analysing Protein–Protein Sequences
IET Systems Biology, Volume 20, Issue 1, January/December 2026.Figure 2 depicts the structure of a peptide bond formed between amino acids to form a polypeptide chain. ABSTRACT Proteins are fundamental biological macromolecules responsible for regulating nearly all cellular processes, and their functions are largely determined by the underlying amino acid sequences.
Anindya Nag +8 more
wiley +1 more source
, 2014 We consider the image classification problem via kernel collaborative representation classification with locality constrained dictionary (KCRC-LCD). Specifically, we propose a kernel collaborative representation classification (KCRC) approach in which ...
Li, Hui +5 more
core +1 more source
The Journal of Engineering, Volume 2026, Issue 1, January/December 2026.This study proposes a digital twin‐enabled hybrid deep learning approach for tool wear monitoring in CNC milling. A four‐layer digital twin architecture is established to enable bidirectional real‐time interaction between the physical machine and its virtual model.
Shuo Wang +3 more
wiley +1 more source
Semi-Supervised Kernel PCA [PDF]
, 2010 We present three generalisations of Kernel Principal Components Analysis (KPCA) which incorporate knowledge of the class labels of a subset of the data points.
Christian Walder +4 more
core +2 more sources
, 2013 Feature extraction and dimensionality reduction are important tasks in many fields of science dealing with signal processing and analysis. The relevance of these techniques is increasing as current sensory devices are developed with ever higher ...
Arenas-García, Jerónimo +3 more
core +1 more source
Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.Intrusion detection systems (IDS) play an important role as a frontline defense in the ongoing effort to secure our networks. But how can we be sure they are effective? It all comes down to the data they were tested on. The review takes a close look at the research landscape by breaking down studies based on five of the most widely used datasets: NSL ...
H. A. El Shenbary +5 more
wiley +1 more source
Lightweight Deep Learning Approach for Intelligent Intrusion Detection in IoT Networks
International Journal of Distributed Sensor Networks, Volume 2026, Issue 1, 2026.Intrusion detection system (IDS) is designed to analyze and monitor the network traffic to identify unauthorized access or attacks in an Internet of Things (IoT). IDS assists in protecting IoT devices and networks by recognizing malicious activities and preventing potential breaches.
Srikanth Mudiyanuru Sriramappa +5 more
wiley +1 more source