Unpacking the underachievement of gifted students: A systematic review of internal and external factors.

In recent years, there has been a substantial research and numerous reviews on the subject of gifted students. The current systematic review is dedicated to explore the underachieving in gifted students, aiming to identify and classify the internal and external factors contributing to this phenomenon. In this study, 282 research articles published from 2010 to 2024 were reviewed using three databases including Google Scholar, ERIC, and Science Direct.

Hand Force Estimation from Acoustic Myography Using Deep Wavelet Scattering Transform and Long Short-Term Memory.

The ability to estimate user intention from surface electromyogram (sEMG) signals is a crucial aspect in the design of powered prosthetics. Recently, researchers have been using regression techniques to connect the user's intent, as expressed through sEMG signals, to the force applied at the fingertips in order to achieve a natural and accurate form of control. However, there are still challenges associated with processing sEMG signals that need to be overcome to allow for widespread and clinical implementation of upper limb prostheses.

Empirical Mode Decomposition-Based Feature Extraction for Environmental Sound Classification.

In environment sound classification, log Mel band energies (MBEs) are considered as the most successful and commonly used features for classification. The underlying algorithm, fast Fourier transform (FFT), is valid under certain restrictions. In this study, we address these limitations of Fourier transform and propose a new method to extract log Mel band energies using amplitude modulation and frequency modulation.

Acoustic Estimation of the Direction of Arrival of an Unmanned Aerial Vehicle Based on Frequency Tracking in the Time-Frequency Plane.

The development of unmanned aerial vehicles (UAVs) opens up a lot of opportunities but also brings some threats. Dealing with these threats is not easy and requires some good techniques. Knowing the location of the threat is essential to deal with an UAV that is displaying disturbing behavior.

Acoustic localization and tracking of a multi-rotor unmanned aerial vehicle using an array with few microphones.

In recent years, the current technological improvements of unmanned aerial vehicles (UAV) have made drones more difficult to locate using optical or radio-based systems. However, the sound emitted by UAV motorization and the aerodynamic whistling of the UAVs can be exploited using a microphone array and an adequate real time signal processing algorithm. The proposed method takes advantage of the characteristics of the sound emitted by the UAV.