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Cognitive load, which alters neuronal activity, is essential to understanding how the brain reacts to stress. This work aims to classify electroencephalogram (EEG) signals to detect cognitive load by extracting features from intrinsic mode functions (IMFs). The variational mode decomposition (VMD) was used for the eight-level decomposition of each EEG channel data (4 s). Next, entropy-based features were extracted from each IMF. The extracted features were fed to supervised machine learning (ML) classifiers: light gradient boosting machine (LightGBM), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost) for classification. Experiments are conducted on two public EEG datasets, multi-arithmetic tasks (MAT) and simultaneous task EEG workload (STEW). The performance is measured via accuracy, specificity, sensitivity, positive predictive value, log-loss score, F1 score, and area under receiver operating curves (AUROC). The proposed LightGBM classifier technique demonstrates superior classification accuracy rates of 97.22% and 95.51% for the MAT and STEW datasets. The experiment results demonstrated that the proposed technique detects cognitive load more precisely than existing methods. The LightGBM classifier model enhanced accuracy and sensitivity in predicting outcomes through the utilization of ML and data mining methods. [ABSTRACT FROM AUTHOR]

This work investigates the complex dielectric spectroscopy of polymethyl methacrylate (PMMA) doped with non-functionalized, OH functionalized, and COOH functionalized multi-walled carbon nanotubes (MWCNTs) in a frequency range of 104 Hz to 2 MHz. Utilizing a 3D mixing technique, various MWCNT concentrations were reinforced in PMMA to create polymer nanocomposites, followed by injection compression. Extra tree regression analysis was then implemented to forecast properties such as dielectric constant, conductivity, loss tangent, and electric modulus at intermediate frequencies. To ensure robust model performance, training used subsets ranging from 50 to 70%, with the remaining 50 to 30% set aside for testing, respectively. Performance metrics such as adjusted R2 score, root mean square error, and mean absolute error were employed to evaluate the predictive accuracy of the models. Experimental data obtained from tests highlighted that the application of extra tree regression analysis resulted in a noteworthy 50% reduction in both analysis time and associated resource expenditures. Novel insights into the chemical interactions and structural changes in the synthesized PMMA nanocomposites were gained through Fourier-transform infrared spectroscopy and X-ray diffraction techniques. This study not only demonstrates the efficiency of advanced regression techniques in predicting dielectric properties but also introduces a cost-effective approach for developing high-performance polymer nanocomposites. These findings have significant potential applications in electronics, sensors, and advanced materials, underscoring the novelty and practical relevance of the research. [ABSTRACT FROM AUTHOR]

The synthesis and characterization of Dy3+-activated CaSi2O5 phosphor is reported. The phosphors were synthesized using a modified solid-state reaction method with variable concentrations of doping ions (0.1–2.5 mol.%) of Dy3+. The synthesized phosphors were characterized by X-ray diffraction (XRD) analysis and the field emission scanning electron microscopy (FESEM) technique. The XRD pattern revealed that the doped phosphors had a cubic structure. FESEM micrographs clearly indicated that the particles crystallized in inhomogeneous morphology on a micrometer scale with a sporadic and asymmetrical shape. Photoluminescence excitation and emission spectra were monitored for variable doping concentrations and the emission found at 485 and 576 nm (excited at 353 nm). The corresponding transitions of the doping ion and concentration quenching effect were studied in detail. The 1931 CIE (x, y) chromaticity coordinates (x = 0.30 and y = 0.31) showed the distribution of a spectral region calculated from PL emission spectra. On the basis of CIE analysis, the prepared phosphor is useful for white light emission in inorganic light-emitting diodes. As-synthesized phosphor was examined by thermoluminescence glow curve analysis with different doses of gamma and electron beam and corresponding kinetic parameters were calculated using the computerized glow curve deconvolution technique. [ABSTRACT FROM AUTHOR]

Epoxy nanocomposites exhibit remarkable characteristics by synergistically integrating the characteristics of epoxy resin with the unique properties of nanoparticles. This study focuses on the incorporation of ZnO and TiO2 nanoparticles into epoxy composites and investigates their impact on dielectric properties. A three-dimensional crosslinked structure was formed using Bisphenol-A epoxy resin and amine hardener. Dielectric spectroscopic assessments of the nanoparticle-doped epoxy composites were conducted over a frequency range of 20 Hz to 2 MHz and extended to 200 MHz to 20 GHz. The research provides a detailed analysis of the influence of ZnO and TiO2 nanoparticles on pristine, undoped epoxy resin. We present Regression analysis which is a useful tool for predicting the dielectric constant of intermediate frequency because it can save time and resources. Experiment data from tests show that using the XGBoost regression analysis can result in a 60% reduction in both time and resource requirements. [ABSTRACT FROM AUTHOR]

A hepta-band terahertz metamaterial absorber (MMA) with modified dual T-shaped resonators deposited on polyimide is presented for sensing applications. The proposed polarization sensitive MMA is ultra-thin (0.061 λ) and compact (0.21 λ) at its lowest operational frequency, with multiple absorption peaks at 1.89, 4.15, 5.32, 5.84, 7.04, 8.02, and 8.13 THz. The impedance matching theory and electric field distribution are investigated to understand the physical mechanism of hepta-band absorption. The sensing functionality is evaluated using a surrounding medium with a refractive index between 1 and 1.1, resulting in good Quality factor (Q) value of 117. The proposed sensor has the highest sensitivity of 4.72 THz/RIU for glucose detection. Extreme randomized tree (ERT) model is utilized to predict absorptivities for intermediate frequencies with unit cell dimensions, substrate thickness, angle variation, and refractive index values to reduce simulation time. The effectiveness of the ERT model in predicting absorption values is evaluated using the Adjusted R2 score, which is close to 1.0 for nmin = 2, demonstrating the prediction efficiency in various test cases. The experimental results show that 60% of simulation time and resources can be saved by simulating absorber design using the ERT model. The proposed MMA sensor with an ERT model has potential applications in biomedical fields such as bacterial infections, malaria, and other diseases. [ABSTRACT FROM AUTHOR]

An ultra-thin metamaterial absorber (MMA) comprises of a split-ring-cross (SRC)-shaped resonator coupled with graphene and dielectric layer backed by metallic ground plane is presented theoretically and numerically for hepta-band applications. The proposed absorber demonstrates multiple absorption peaks at 2.33, 5.24, 7.74, 8.25, 10.05, 10.97, and 12.61 THz with average absorption of more than 96%. The physical mechanism of the hepta-band absorption is analyzing by electric field distribution and attributed to the combination of dipolar and LC resonance. Furthermore, the effect of geometric parameters is analyzed to validate the optimal selection of the structural parameters. In addition, the proposed MMA is analyzed for different incident and polarization angles suggesting that absorption response is insensitive to polarization angles. Compared with the previously reported MMAs, the proposed design is ultra-thin (0.036λ) and compact (0.21λ) at the lowest operational frequency. The absorptivity at 12.61 THz is 99.81% and the corresponding quality (Q) factor is 31.52 for a bandwidth of 0.40 THz. The proposed absorber can be potentially utilized in detection, sensing, and imaging. Moreover, the sensing performance of the proposed MMA has been investigated using overlayer thickness and overlayer permittivity. [ABSTRACT FROM AUTHOR]

A four-terminal ballistic rectifier demonstrating voltage rectification for both electrical (AC/DC) as well as thermal (temperature gradient) inputs is presented. The thermoelectric behavior of the graphene triangular ballistic rectifier (G-TBR) is based on its nonlinear electrical response. The responsivity and noise equivalent power of the device are calculated to be 8870 mV/W and 1.59 nW/Hz1/2, respectively, at a back-gate voltage of 5 V. The rectified thermal voltage between two isothermal output (lower and upper) terminals is estimated to be 2.8 µV at a temperature gradient of 150 K. Further, the electric and thermoelectric output of the proposed G-TBR is validated by analytical modeling. Such G-TBRs could be used in the future in energy harvesting application to use heat produced by electronic circuitry, integrated circuits (ICs), etc. [ABSTRACT FROM AUTHOR]

In this study, an ultra-compact metamaterial absorber (MMA) has been proposed for microwave applications comprising two modified square-shaped resonators printed on a dielectric substrate and terminated by a metallic plane. The proposed MMA exhibits perfect absorption at 3.36 GHz, 3.95 GHz and 10.48 GHz, covering S- and X-band applications. The absorber is ultra-compact (0.112 λ) in size and ultra-thin (0.018 λ) in thickness at the lowest resonating frequency. The normalized impedance, constitutive electromagnetic parameters, electric field and surface current distribution have been studied to understand the physical mechanism of the triple-band absorption. Furthermore, the absorber is analyzed with different polarization and incident angles for transverse electric waves. The proposed MMA has been experimentally demonstrated to verify the results obtained from simulations. Moreover, the effect of over-layer thickness is investigated to examine the sensing application of the absorber. [ABSTRACT FROM AUTHOR]

This paper presents a graphene-based tunable polarization-insensitive metamaterial absorber (MMA) at terahertz (THz) frequencies. The absorber consists of top patterned gold (Au) layer followed by single layer of graphene, dielectric spacer, and Au layer at bottom. The proposed MMA demonstrates multi-band absorption with the characteristics of both broad- and dual-band absorption by optimizing dimensions (parametric analysis). Broad-band absorption reaches over 90% for the range of 4.57–6.45 THz with the relative absorption bandwidth of 34%, and the absorption peak at 6.86 and 7.20 THz having 98.9 and 95.2% absorption. The normalized impedance and constitutive electromagnetic parameters of the MMA are calculated using the Nicolson–Ross–Weir (NRW) method to validate the absorption rate. Furthermore, proposed absorber is polarization-insensitive upto 90° for transverse electric wave. The tunable characteristic of MMA is achieved by tuning the Fermi energy of graphene with the application of bias voltage. Accordingly, the proposed multi- and broad-band absorbers find its potential applications in spectroscopy detection, imaging, and sensing. [ABSTRACT FROM AUTHOR]