-
61
Feature Graph Construction With Static Features for Malware Detection
Published 2025-01-01“…Malware can greatly compromise the integrity and trustworthiness of information and is in a constant state of evolution. Existing feature fusion-based detection methods generally overlook the correlation between features. …”
Get full text
Article -
62
-
63
Simulation-Based Electrothermal Feature Extraction and FCN–GBM Hybrid Model for Lithium-ion Battery Temperature Prediction
Published 2025-08-01“…This study proposes a hybrid temperature prediction model that integrates Fully Connected Networks (FCN) and Gradient Boosting Machines (GBM) to capture temperature evolution under varying discharge rates. …”
Get full text
Article -
64
AI-based tool wear prediction with feature selection from sound signal analysis
Published 2025-08-01“…Finally, an artificial neural network (ANN) model is designed to estimate tool wear levels. …”
Get full text
Article -
65
Financial Evolution and Interdisciplinary Research
Published 2023-03-01“…This paper (summary of the second chapter of the manuscript "quantum dance") talks about the multidimensionality of finance through evolution, philosophy with interdisciplinary features (interweaving of neuroscience, mathematics, quantum physics, biology and artificial intelligence). …”
Get full text
Article -
66
Spatiotemporal pattern evolution and quantitative prediction of electrical carbon emissions from a demand-side perspective in urban areas
Published 2025-07-01“…Utilizing high-frequency monitoring data from 3000 distribution network stations (May–Sept 2018), it creates an integrated ’spatiotemporal evolution-data driven prediction’ framework to reveal emission dynamics and enhance forecast accuracy. …”
Get full text
Article -
67
-
68
-
69
Hybrid Big Bang-Big crunch with cuckoo search for feature selection in credit card fraud detection
Published 2025-07-01“…Here, the CS algorithm uses the Levy flight attribute to help the BB-BC agents escape from stagnation and premature convergence. After feature selection, classification is performed using Deep Convolutional Neural Networks (DCNN) and Enhanced DCNN (EDCNN) to improve detection accuracy. …”
Get full text
Article -
70
-
71
Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification
Published 2025-01-01“…However, the complexity of urban areas and their surrounding structures makes it extremely difficult to capture correlations between features. This article proposes a novel multiscale attention feature fusion network, composed of hierarchical convolutional neural networks and transformer to enhance joint classification accuracy of hyperspectral image (HSI) and light detection and ranging (LiDAR) data. …”
Get full text
Article -
72
Deriving structure from evolution: metazoan segmentation
Published 2007-12-01“…Abstract Segmentation is a common feature of disparate clades of metazoans, and its evolution is a central problem of evolutionary developmental biology. …”
Get full text
Article -
73
DeepAptamer: Advancing high-affinity aptamer discovery with a hybrid deep learning model
Published 2025-03-01“…To address these challenges, we proposed DeepAptamer for identifying high-affinity sequences from unenriched early SELEX rounds. As a hybrid neural network model combining convolutional neural networks and bidirectional long short-term memory, DeepAptamer integrated sequence composition and structural features to predict aptamer binding affinities and potential binding motifs. …”
Get full text
Article -
74
Flow Field Reconstruction and Prediction of Powder Fuel Transport Based on Scattering Images and Deep Learning
Published 2025-07-01“…Based on the acquired scattering images, a prediction and reconstruction method was developed using a deep network framework composed of a Stacked Autoencoder (SAE), a Backpropagation Neural Network (BP), and a Long Short-Term Memory (LSTM) model. …”
Get full text
Article -
75
Modeling Upscaled Mass Discharge From Complex DNAPL Source Zones Using a Bayesian Neural Network: Prediction Accuracy, Uncertainty Quantification and Source Zone Feature Importance
Published 2024-07-01“…Instead, the BNN model chooses three physically meaningful SZ quantities related to mass discharge as input features. Then, we use the expected gradients method to identify the feature importance for mass‐discharge prediction. …”
Get full text
Article -
76
-
77
Evolution of the activities of states as reflected in legal and political Teachings
Published 2020-12-01Get full text
Article -
78
Artificial Intelligence-Powered Insights into Polyclonality and Tumor Evolution
Published 2025-01-01“…Recent studies have revealed that polyclonality—where multiple distinct subclones cooperate during early tumor development—is a critical feature of tumor evolution, as demonstrated by Sadien et al. and Lu et al. in Nature (October 2024). …”
Get full text
Article -
79
The role of learned song in the evolution and speciation of Eastern and Spotted towhees.
Published 2025-06-01Get full text
Article -
80
Viral evolution sustains a dengue outbreak of enhanced severity
Published 2021-01-01Get full text
Article