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The EmoReIQ (Emotion Recognition for Iraqi Autism Individuals) dataset is a specialized EEG dataset designed to capture emotional responses in individuals with Autism Spectrum Disorder (ASD) and Typically Developed (TD). It focuses on five core emotions: calm, happy, anger, fear, and sad. The dataset is gathered through an experimental setup using video stimuli to elicit these emotions and records corresponding EEG signals from participants.
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539 Views
This paper addresses the problem of dynamic multi-objective optimization problems (DMOPs), by demonstrating new approaches to change prediction strategies within an evolutionary algorithm paradigm. Because the objectives of such problems change over time, the Pareto optimal set (PS) and Pareto optimal front (PF) are also dynamic.
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Ultra-wideband radar (UWB) is capable of perceiving the surroundings irrespective of the visibility due to its broad frequency spectrum. Therefore, UWB technology can be employed in mobile robots to perform simultaneous localization and mapping (SLAM) in vision-denied environments (e.g. smoke, fog, walls with reflective surfaces). We chose four different environments to teleoperate a TurtleBot2 nonholonomic robot equipped with Novelda X4M300 monostatic radar modules and RPLIDAR-A2 laser range scanner(s).
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This dataset is utilized for the research of blind identification of CPM signal modulation order. The signal parameters in the dataset range as follows: modulation index from 0.125 to 1, modulation order of 2, 4, 8, pulse types including REC, RC, SRC, TFM, and GMSK, and correlation lengths of 1 to 8. The signals are oversampled by a factor of 10, transmitted through an additive white Gaussian noise (AWGN) channel, and the signal-to-noise ratio (SNR) ranges from 0 to 30dB.
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The file “marine_data.mat” is the data from the marine experiment, including data from different navigation and positioning sensors. The file “lake_data.mat” is the data from the lake experiment, including data from different navigation and positioning sensors.
The meaning and explanation for each column in the file “lake_data.mat” is shown as below:
Acc_x is the x-axis acceleration of the surface vehicle.
Acc_y is the y-axis accelerationof the surface vehicle.
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159 Views
While functional near-infrared spectroscopy (fNIRS) had previously been suggested for major depressive disorder (MDD) diagnosis, the clinical application to predict antidepressant treatment response (ATR) is still unclear. To address this, the aim of the current study is to investigate MDD ATR using fNIRS and micro-ribonucleic acids (miRNAs). Our proposed algorithm includes a custom inter-subject variability reduction based on the Principal Component Analysis (PCA).
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151 Views
This letter presents an effective digital passive intermodulation (PIM) cancellation technique for multi-band multiple-input multiple-output frequency-division duplexing radios for 5G and beyond. We begin by introducing a universal PIM signal model for multi-band radios with an arbitrary number of transmit--receive antennas, which enables the calculation of basis functions at all intermodulation frequencies. After establishing this signal model, a comparative analysis of state-of-the-art behavioral models is conducted in the context of PIM modeling.
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This radar raw datasets are collected with the FMCW radar system --- PARSAX in Delft University of Technology, the Netherlands. Two datasets are included, in which one is the echo scattered from a stationary industrial chimney and the other one is the echo of rain droplets. The radar echo of chimney was acquired in one FMCW signal sweep. And the echo of the rain droplets was measured over 512 sweeps, which can be used for both range profile and range-Doppler processing. In both radar datasets, the echoes of targets were contaminated by interferences.
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319 Views
This dataset acompanies our article titled "Insights into traditional Large Deformation Diffeomorphic Metric Mapping and unsupervised deep-learning for diffeomorphic registration and their evaluation", Computers in Biology and Medicine, 2024. This paper explores the connections between traditional Large Deformation Diffeomorphic Metric Mapping methods and unsupervised deep-learning approaches for non-rigid registration, particularly emphasizing diffeomorphic registration.
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259 Views
Traditional authentication models are vulnerable to security breaches when personal data is exposed. This study introduces novel hybrid visual stimuli protocols integrating event-related potentials (ERP) and steady-state visually evoked potentials (SSVEP) to develop an authentication system that enhances both performance and personalization in neural interfaces. Our model utilizes distinctive neural patterns elicited by a range of visual stimuli based on 4-digit numbers, such as familiar numbers (personal birthdates, excluding targets), standard targets, and non-targets.
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13 Views