AIMC Topic: Algorithms

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TP-RotatE: A knowledge graph representation learning method combining path information and rules to capture complex relational patterns.

PloS one
Representation learning on a knowledge graph (KG) aims to map entities and relationships into a low-dimensional vector space. Traditional methods for representation learning have predominantly focused on the structural aspects of triples within the K...

Research on emotion recognition using sparse EEG channels and cross-subject modeling based on CNN-KAN-[Formula: see text] model.

PloS one
Emotion recognition plays a significant role in artificial intelligence and human-computer interaction. Electroencephalography (EEG) signals, due to their ability to directly reflect brain activity, have become an essential tool in emotion recognitio...

Cyber security Enhancements with reinforcement learning: A zero-day vulnerabilityu identification perspective.

PloS one
A zero-day vulnerability is a critical security weakness of software or hardware that has not yet been found and, for that reason, neither the vendor nor the users are informed about it. These vulnerabilities may be taken advantage of by malicious pe...

Predicting central lymph node metastasis in papillary thyroid microcarcinoma: a breakthrough with interpretable machine learning.

Frontiers in endocrinology
OBJECTIVE: To develop and validate an interpretable machine learning (ML) model for the preoperative prediction of central lymph node metastasis (CLNM) in papillary thyroid microcarcinoma (PTMC).

Interpretable noninvasive diagnosis of tuberculous pleural effusion using LGBM and SHAP: development and clinical application of a machine learning model.

PeerJ
BACKGROUND: Tuberculous pleural effusion (TPE) is a prevalent tuberculosis complication, with diagnosis presenting considerable challenges. Timely and precise identification of TPE is vital for effective patient management and prognosis, yet existing...

Improved generative adversarial networks model for movie dance generation.

PloS one
To address the challenges of innovation and efficiency in film choreography, this study proposes a dance generation model based on the generative adversarial networks. The model is trained using the AIST++ dance motion dataset, incorporating data fro...

A lithium-ion batteries SOH estimation method based on extracting new features during the constant voltage charging stage and improving BPNN.

PloS one
Existing state of health (SOH) estimation methods for lithium-ion batteries predominantly extract health features (HF) from constant current (CC) and constant voltage (CV) charging phases. Nevertheless, CC charging phase feature extraction is suscept...

A lightweight hyperspectral image multi-layer feature fusion classification method based on spatial and channel reconstruction.

PloS one
Hyperspectral Image (HSI) classification tasks are usually impacted by Convolutional Neural Networks (CNN). Specifically, the majority of models using traditional convolutions for HSI classification tasks extract redundant information due to the conv...

Leveraging transformers and explainable AI for Alzheimer's disease interpretability.

PloS one
Alzheimer's disease (AD) is a progressive brain ailment that causes memory loss, cognitive decline, and behavioral changes. It is quite concerning that one in nine adults over the age of 65 have AD. Currently there is almost no cure for AD except ver...

The role of product art design based on a fuzzy decision support system in improving user interaction experience.

PloS one
User interaction for product selection relies on its design and technical support to improve the quality of the experience. Decision support systems are incorporated to leverage user experience through product interactions. This article introduces an...