AIMC Topic: Electric Power Supplies

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LSTM-DGWO-Based Sentiment Analysis Framework for Analyzing Online Customer Reviews.

Computational intelligence and neuroscience
Sentiment analysis furnishes consumer concerns regarding products, enabling product enhancement development. Existing sentiment analysis using machine learning techniques is computationally intensive and less reliable. Deep learning in sentiment anal...

HyFormer: Hybrid Transformer and CNN for Pixel-Level Multispectral Image Land Cover Classification.

International journal of environmental research and public health
To effectively solve the problems that most convolutional neural networks cannot be applied to the pixelwise input in remote sensing (RS) classification and cannot adequately represent the spectral sequence information, we propose a new multispectral...

High-performance and low-power source-gated transistors enabled by a solution-processed metal oxide homojunction.

Proceedings of the National Academy of Sciences of the United States of America
Cost-effective fabrication of mechanically flexible low-power electronics is important for emerging applications including wearable electronics, artificial intelligence, and the Internet of Things. Here, solution-processed source-gated transistors (S...

Vision-Based Efficient Robotic Manipulation with a Dual-Streaming Compact Convolutional Transformer.

Sensors (Basel, Switzerland)
Learning from visual observation for efficient robotic manipulation is a hitherto significant challenge in Reinforcement Learning (RL). Although the collocation of RL policies and convolution neural network (CNN) visual encoder achieves high efficien...

A BERT Framework to Sentiment Analysis of Tweets.

Sensors (Basel, Switzerland)
Sentiment analysis has been widely used in microblogging sites such as Twitter in recent decades, where millions of users express their opinions and thoughts because of its short and simple manner of expression. Several studies reveal the state of se...

A study on pharmaceutical text relationship extraction based on heterogeneous graph neural networks.

Mathematical biosciences and engineering : MBE
Effective information extraction of pharmaceutical texts is of great significance for clinical research. The ancient Chinese medicine text has streamlined sentences and complex semantic relationships, and the textual relationships may exist between h...

Data Valuation Algorithm for Inertial Measurement Unit-Based Human Activity Recognition.

Sensors (Basel, Switzerland)
This paper proposes a data valuation algorithm for inertial measurement unit-based human activity recognition (IMU-based HAR) data based on meta reinforcement learning. Unlike previous studies that received feature-level input, the algorithm in this ...

An Efficient Dehazing Algorithm Based on the Fusion of Transformer and Convolutional Neural Network.

Sensors (Basel, Switzerland)
The purpose of image dehazing is to remove the interference from weather factors in degraded images and enhance the clarity and color saturation of images to maximize the restoration of useful features. Single image dehazing is one of the most import...

Application of Transformer Models to Landslide Susceptibility Mapping.

Sensors (Basel, Switzerland)
Landslide susceptibility mapping (LSM) is of great significance for the identification and prevention of geological hazards. LSM is based on convolutional neural networks (CNNs); CNNs use fixed convolutional kernels, focus more on local information a...

Towards Online Ageing Detection in Transformer Oil: A Review.

Sensors (Basel, Switzerland)
Transformers play an essential role in power networks, ensuring that generated power gets to consumers at the safest voltage level. However, they are prone to insulation failure from ageing, which has fatal and economic consequences if left undetecte...