AIMC Topic: Algorithms

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Electrocardiogram Biometrics Using Transformer's Self-Attention Mechanism for Sequence Pair Feature Extractor and Flexible Enrollment Scope Identification.

Sensors (Basel, Switzerland)
The existing electrocardiogram (ECG) biometrics do not perform well when ECG changes after the enrollment phase because the feature extraction is not able to relate ECG collected during enrollment and ECG collected during classification. In this rese...

Pattern Recognition of EMG Signals by Machine Learning for the Control of a Manipulator Robot.

Sensors (Basel, Switzerland)
Human Machine Interfaces (HMI) principles are for the development of interfaces for assistance or support systems in physiotherapy or rehabilitation processes. One of the main problems is the degree of customization when applying some rehabilitation ...

Establishment of Economic Forecasting Model of High-tech Industry Based on Genetic Optimization Neural Network.

Computational intelligence and neuroscience
Scientific and accurate prediction of high-tech industries is of great practical significance for government departments to grasp the future economic operation and formulate development strategies. In this paper, aiming at some shortcomings of neural...

Computer Vision-Based Medical Cloud Data System for Back Muscle Image Detection.

Computational intelligence and neuroscience
The fast development of image recognition and information technology has influenced people's life and industry management mode not only in some common fields such as information management, but also has very much improved the working efficiency of va...

Detection of Dental Diseases through X-Ray Images Using Neural Search Architecture Network.

Computational intelligence and neuroscience
An important aspect of the diagnosis procedure in daily clinical practice is the analysis of dental radiographs. This is because the dentist must interpret different types of problems related to teeth, including the tooth numbers and related diseases...

A novel remaining useful life prediction method based on multi-support vector regression fusion and adaptive weight updating.

ISA transactions
Remaining useful life prediction is of huge significance in preventing equipment malfunctions and reducing maintenance costs. Currently, machine learning algorithms have become hotspots in remaining useful life prediction due to their high flexibilit...

In silico prediction of potential drug-induced nephrotoxicity with machine learning methods.

Journal of applied toxicology : JAT
In recent years, drug-induced nephrotoxicity has been one of the main reasons for the failure of drug development. Early prediction of the nephrotoxicity for drug candidates is critical to the success of clinical trials. Therefore, it is very importa...

Double hierarchy hesitant fuzzy linguistic information based framework for personalized ranking of sustainable suppliers.

Environmental science and pollution research international
With the growing appetite for reducing carbon footprint, organizations are tirelessly working towards green practices and one such crucial practice is purchasing raw materials from sustainable suppliers (SSs). Inspired by the drift in purchase habits...

An integrated network representation of multiple cancer-specific data for graph-based machine learning.

NPJ systems biology and applications
Genomic profiles of cancer cells provide valuable information on genetic alterations in cancer. Several recent studies employed these data to predict the response of cancer cell lines to drug treatment. Nonetheless, due to the multifactorial phenotyp...

A novel short-term carbon emission prediction model based on secondary decomposition method and long short-term memory network.

Environmental science and pollution research international
Grasping the dynamics of carbon emission in time plays a key role in formulating carbon emission reduction policies. In order to provide more accurate carbon emission prediction results for planners, a novel short-term carbon emission prediction mode...