Category: 7. Maths

Datasets collection

The data used for note recognition in this study came from the Camera-Processed Instrumental Music Scores (Camera-PrIMuS) dataset. This dataset contains images of the musical spectrum of an instrument processed by a camera and…

Modified signed-digit representation

Modified Signed-Digit (MSD) redundancy representation was first proposed by Avizienis etc. in 1961²⁹. In 1986 MSD was applied to optical computing by Drake etc.³⁰. Now MSD representation is widely used in…

Data acquisition

A total of 114 diabetic patients aged between 50-77 years old (mean: 66; SD: 5.7) have been recruited for this study, including 50 males and 64 females with the presence of either Type 1 or Type 2 diabetes mellitus in the early…

Problem description

Let the source point cloud be \(P = \left\{ p _ { 1 } , p _ { 2 } , \ldots , p _ { n } \right\}\) and the reference point cloud be \(Q = \left\{ q _ { 1 } , q _ { 2 } , \ldots , q _ { m } \right\}\) representing the point sets…

This study utilizes a balanced dataset of 11,000 tomato leaf images categorized into 10 disease classes and a healthy class, with 1,100 images per class. A deep learning-based ensemble model combining ResNet50 and MobileNetV2 was employed, where…

Stochastic dynamical systems

The application of stochastic dynamical systems has a long history in ecological and environmental science^53,54. The study of tipping points, in particular, also references seminal works by²⁹ and others that separated…

Using PTR-ToF-MS we identified 111 different signal compounds within the coffee samples, all of which have been previously identified in coffee studies. Since each compound has its own perceived threshold concentration, it is possible that not…

Performance evaluation metrics

To ascertain the validity of the model, three accuracy estimators were employed for objective evaluation: mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (\({R^2}\)). The…

Variational mode decomposition algorithm

To better handle the multimodal characteristics of stress time series data, this paper employs the Variational Mode Decomposition (VMD) method. By formulating a variational optimization problem, VMD…