Power Spectrum Density Analysis Research Articles

Investigating the Relationship between Noise Exposure and Human Cognitive Performance: Attention, Stress, and Mental Workload Based on EEG Signals Using Power Spectrum Density

A pervasive environmental stressor is one that damages mental and physical health as well as cognitive abilities by producing noise at a specific frequency and level. Current noise pollution levels pose a significant threat to public health, potentially leading to impaired cognitive function, increased stress, and other negative health consequences. This study aims to investigate the relationship between noise exposure and human cognitive abilities using a comprehensive analysis of power spectrum density (PSD) derived from EEG signals. Twenty-four participants completed the experiment to identify the effect of exposure to different noise levels (55 dB, 65 dB, 70 dB, 75 dB, 80 dB, and 85 dB) and two types of continuous and intermittent noise. The Stroop Color–Word Test and the Emotive Epoch EEG are cognitive task instruments used during experiments. Behavioral performance (accuracy and response time) and power spectrum electroencephalographic density were collected and analyzed. The methodology involved collecting EEG data from participants exposed to controlled noise stimuli and a subsequent PSD analysis to uncover frequency-specific patterns associated with cognitive processes. Attention levels were measured by examining beta wave activity, while stress responses were evaluated through an alpha wave analysis. Additionally, mental workload was assessed by considering the overall distribution of PSD through the theta-to-alpha ratio. The results revealed a significant relationship between the exposure to noise types and levels and human cognitive ability. The analysis of the power spectrum density on the cognitive aspects of attention and stress yielded results indicating that participants were in the best attention condition and in a relaxed or unstressed state when exposed to noise levels of 65 dB in both continuous and intermittent noise types. For the mental workload aspect, participants exposed to both continuous and intermittent noise types at a noise level of 70 dB began to indicate the presence of mental workload. These findings supported the importance of considering the impact of environmental noise on human cognitive well-being and demonstrated the potential of EEG monitoring as an objective tool for assessing the impact of noise on cognitive performance.

Ultraviolet Radiation Quasi-Periodicities and Their Possible Link with the Cosmic Ray and Solar Interplanetary Data

In this study, solar ultraviolet (UV) radiation data collected in Riyadh, Saudi Arabia, between 2015 and 2022 were analyzed to explore quasi-periodicities in the UV time series. The power spectrum density analysis revealed several local peaks that exceeded the 95% confidence interval. These peaks included periodicities of 483–490 days, 272 days, 157−162 days, 103−110 days, 64–72 days, 27 days, and 13 days. To investigate the potential influence of space weather parameters on UV radiation, data on cosmic rays, solar radio flux at 10.7 cm (F10.7 cm), the Kp index, and solar wind speed for the same time period were examined. The aim was to identify periodicities in these variables that aligned with those found in the UV radiation data. The analysis reveals that several periodicities observed in the UV radiation spectrum are also present in the spectra of the considered parameters. Prominent periodicities include a 270-day cycle in UV radiation and cosmic rays, as well as periodicities of 72 days, 27 days, and 13 days in all considered variables. Furthermore, 110-day peaks are observed in spectrum of the UV radiation, the Kp index, solar radio flux F10.7, and solar wind speed. Notably, consistent peaks at 157-day periodicity are identified in the UV spectrum, also present in the spectra of all the considered variables (cosmic rays ∼162 days, Kp index ∼162 days, solar radio flux ∼156 days, and solar wind speed ∼163 days). The identification of common periodicities between UV radiation and space weather parameters in this study provides compelling evidence of a potential direct or indirect influence of solar variations on UV radiation. This finding significantly enhances our understanding of the impact of extraterrestrial factors, particularly solar activity, on the Earth’s environment.

Analysis of PAPR reduction of optical-OTFS for 256-QAM using companding and clipping–filtering algorithms

Abstract The article presents an investigation into Peak-to-Average Power Ratio (PAPR) reduction techniques in Optical Orthogonal Time Frequency Space (O-OTFS) modulation. Focusing on clipping and filtering as well as companding methods, the study explores their efficacy in mitigating PAPR challenges inherent in O-OTFS waveforms. The research evaluates the impact of these techniques on signal quality, particularly in the context of a Rician channel. Clipping and filtering (C&F) are examined for their ability to control amplitude peaks, while companding is analyzed for its role in optimizing dynamic range. The study conducts a comprehensive analysis of Bit Error Rate (BER) and power spectrum density (PSD) under varying conditions, shedding light on how these methods influence the reliability and robustness of OTFS communication. The investigation considers the interplay of these PAPR reduction methods with the unique characteristics of the Rician and Rayleigh channel, which includes a dominant line-of-sight component. The findings contribute valuable insights into designing efficient OTFS modulation systems for real-world scenarios. Ultimately, this research aims to provide a deeper understanding of PAPR reduction strategies in OTFS, offering guidance for optimizing signal processing techniques in communication systems where mitigating PAPR is crucial for achieving high performance and reliable data transmission. It is noted that the proposed C&F and companding algorithms outperform the conventional methods and achieved a PAPR gain of 1–3 dB and BER gain of 10.6–2 dB.

Hydrological complexity analysis using multiscale entropy: Methodological explorations and insights

Multiscale entropy is a popular and valuable methodology for analyzing hydrological complexity. However, some errors and limitations remain in its use and interpretation. This study identified three key issues, incorrect mapping of entropy values with frequency signals, an insufficient time scale range, and an unclear relationship between features in the multiscale entropy curve and hydrological interpretation. To address these issues, we focused on the sediment concentration and runoff in the Yanhe Watershed and conducted in-depth explorations using refined composite multiscale entropy (RCMFE) and three other methods, power spectrum density analysis, wavelet transform, and surrogate analysis.The results indicate that the entropy at each scale is influenced by signals with time scales equal to or greater than its own scale and that its variation is controlled by the overall signal dispersion. The RCMFE method demonstrated suitability for the complexity analysis of sediment and runoff sequences with short-length data. To effectively capture hydrological complexity, attention to the scale range issue is crucial, ensuring that the richness of complex features at larger scales in multiscale entropy curves is not overlooked. Interpretation of the local minima and maxima in the multiscale entropy curve is highlighted. Local minima signify high periodic patterns and predictability, whereas the first peak, typically occurring at approximately 2–3 months, is a valuable indicator of the overall complexity of the hydrological series. Linear characteristics were found to contribute significantly to the hydrological complexity, with stronger linear correlations resulting in an overall increase, lower local minima, and increased volatility in the multiscale entropy curve. The notable reduction in the hydrological complexity of the Yanhe Watershed calls for ecological sustainability and sustainable soil and water conservation efforts.

High-resolution experiments for mixing in large enclosures

To support further model development and validation for mixing in large enclosures, the MiGaDome facility that is 1/12th scaled from the Modular High-Temperature Gas Reactor (MHTGR) upper plenum has recently been built at the University of Michigan. In this paper, 2D PIV measurements have been conducted on two jets discharging into the MiGaDome facility. Two twin-jet cases of Re=4097 and Re=6021, and an asymmetrical case (Re=6021 v.s. 4097) have been investigated. Intense turbulent mixing with spanwise vortices of various sizes is observed in the instantaneous vector field for all cases. A power spectrum density analysis with a 7.5 Hz cutoff frequency has shown low-frequency fluctuations of St=0.0144 and St=0.0120 in the middle of the two jets for the two uniform injection cases. Besides, the time-averaged flow field shows that a down-wash fountain flow has formed due to wall jet impingement for the two cases, while a clockwise recirculation is created for the asymmetrical case. High-resolution 2D velocity and turbulent statistics fields have been obtained from the time-averaged measurements. In addition, the integral length scales are also calculated based on the two-point spatial cross-correlation.

A new variability pattern in GRS 1915+105 with NICER and Insight-HXMT observations

ABSTRACT We explore the timing and spectral properties of GRS 1915+105 based on X-ray observations of NICER and Insight-HXMT during the long outburst from 2017 to 2021. We find a new class of variability in the rising stage of the outburst that differs from the formerly reported patterns of light curves. This new variability pattern, which we name class ψ, is characterized by several periodic mini pulses superposed on another longer periodic pulse. The periods are ∼130 and ∼10 s for the main pulses and mini pulses, respectively, based on the analysis of power spectrum density and step-wise filter correlation (SFC), where the SFC method has an advantage in finding the superimposed periodic components. The mini pulses become weak or disappear when the luminosity increases and the light curves change into the classical class κ. The class ψ shows a softer spectrum with lower count rates compared to the class κ during the main pulse. The new class ψ shows peculiar timing and spectral properties compared to those of classic class κ, which can help us to explore the class transition mechanism in GRS 1915+105.

Investigation of Methodologies for Extracting Individual Brain Oscillations: Comparisons & Insights.

There is increasing evidence that the effects of non-invasive brain stimulation can be maximized when the applied intervention matches internal brain oscillations. Extracting individual brain oscillations is thus a necessary step for implementing personalized brain stimulation. In this context, different methods have been proposed for obtaining subject-specific spectral peaks from electrophysiological recordings. However, comparing the results obtained using different approaches is still lacking. Therefore, in the present work, we examined the following methodologies in terms of obtaining individual motor-related EEG spectral peaks: fast Fourier Transform analysis, power spectrum density analysis, wavelet analysis, and a principal component based time-frequency analysis. We used EEG data obtained when performing two different motor tasks - a hand grip task and a hand opening- and-closing task. Our results showed that both the motor task type and the specific method for performing the analysis had considerable impact on the extraction of subject-specific oscillation spectral peaks.Clinical Relevance-This exploratory study provides insights into the potential effects of using different methods to extract individual brain oscillations, which is important for designing personalized brain-machine-interfaces.

The nonlinearity of pupil diameter fluctuations in an insight task as criteria for detecting children who solve the problem from those who do not.

Insights, characterized by sudden discoveries following unsuccessful problem-solving attempts, are fascinating phenomena. Dynamic systems perspectives argue that insight arises from self-organizing perceptual and motor processes. Entropy and fractal scaling are potential markers for emerging new and effective solutions. This study investigated whether specific features associated with self-organization in dynamical systems can distinguish between individuals who succeed and those who fail in solving insight tasks. To achieve this, we analyzed pupillary diameter fluctuations of children aged 6 to 12 during the 8-coin task, a well-established insight task. The participants were divided into two groups: successful (n = 24) and unsuccessful (n = 43) task completion. Entropy, determinism, recurrence ratio, and the β scaling exponent were estimated using Recurrence Quantification and Power Spectrum Density analyses. The results indicated that the solver group exhibited more significant uncertainty and lower predictability in pupillary diameter fluctuations before finding the solution. Recurrence Quantification Analysis revealed changes that went unnoticed by mean and standard deviation measures. However, the β scaling exponent did not differentiate between the two groups. These findings suggest that entropy and determinism in pupillary diameter fluctuations can identify early differences in problem-solving success. Further research is needed to determine the exclusive role of perceptual and motor activity in generating insights and investigate these results' generalizability to other tasks and populations.

Experimental mode decomposition investigation on 3-stage axial flow compressor stall phenomena using aeroacoustics measurements

Safely operating compressors is quite critical. Rotating stall is highly undesirable and affects negatively the performance and stability of aero-engine compressors. It is important to identify a precursor of such rotating stalling phenomena observed on the compressor. In this work, we conduct experimental measurements on a 3-stage axial flow compressor by using 8 acoustic pressure sensors. Emphasis is being placed on applying different mode decomposition methods such as Proper Orthogonal Decomposition (POD) and Empirical Mode Decomposition (EMD) on these acoustics data to shed lights on the stall phenomena. Comparison is then made between these methods and conventional means like continuous wavelet (CWA), and PSD (Power Spectrum Density) analyses to achieve a timely detection of stall inception and the energy distribution before and after stall occurred. It is found from POD that the dominant acoustic modes contributing to more than 90% of the total fluctuation energy are changed from 3 to 4, when the stall occurred. The EMD investigation shows that the compressor stall is associated with a few low-frequency IMFs (intrinsic mode function). Time evolutions of such IMFs are observed to grow from negligible amplitude disturbances into limit cycles. Additionally, applying CWA reveals that the stall cell is originated from the first stage and then propagates circumferentially and axially to the second and third stage. Finally, PSD analysis shows that the stall frequency related to the spike-type stall cell exists only on the first stage. This is different from the blade passing frequency as observed on all stages of the compressor. In summary, the present work offers alternative acoustic measurements to examine the dynamic instability of a compressor stall with advanced signal-processing techniques applied.

Tunable Adhesion of Shape Memory Polymer Dry Adhesive Soft Robotic Gripper via Stiffness Control

A shape memory polymer (SMP) has been intensively researched in terms of its exceptional reversible dry adhesive characteristics and related smart adhesive applications over the last decade. However, its unique adhesive properties have rarely been taken into account for other potential applications, such as robotic pick-and-place, which might otherwise improve robotic manipulation and contribute to the related fields. This work explores the use of an SMP to design an adhesive gripper that picks and places a target solid object employing the reversible dry adhesion of an SMP. The numerical and experimental results reveal that an ideal compositional and topological SMP adhesive design can significantly improve its adhesion strength and reversibility, leading to a strong grip force and a minimal release force. Next, a radially averaged power spectrum density (RAPSD) analysis proves that active heating and cooling with a thermoelectric Peltier module (TEC) substantially enhances the conformal adhesive contact of an SMP. Based on these findings, an adhesive gripper is designed, fabricated, and tested. Remarkably, the SMP adhesive gripper interacts not only with flat and smooth dry surfaces, but also moderately rough and even wet surfaces for pick-and-place, showing high adhesion strength (>2 standard atmospheres) which is comparable to or exceeds those of other single-surface contact grippers, such as vacuum, electromagnetic, electroadhesion, and gecko grippers. Lastly, the versatility and utility of the SMP adhesive gripper are highlighted through diverse pick-and-place demonstrations. Associated studies on physical mechanisms, SMP adhesive mechanics, and thermal conditions are also presented.

Experimental investigation on flow field around a flapping plate with single degree of freedom

Undesirable flapping motion of discs can cause the failure of swing check valves in nuclear passive safety systems. Time-resolved particle image velocimetry (PIV) was employed to investigate the flow characteristics around a free-to-rotate plate and the motion response, with the Reynolds numbers, based on the hydraulic diameter of the channel, from 1.32 × 104 to 3.95 × 104. Appreciable flapping motion (±3.52°) appeared at the Reynolds number of 2.6 × 104 with the frequency of 5.08 Hz. In the low-Reynolds-number case, the plate showed negligible flapping. In the high-Reynolds-number case, the deflection angle increased with reduced flapping amplitude. The torque from the fluid determined the flapping amplitude. In the low-Reynolds-number case, Karman vortices were absent. With increasing Reynolds numbers, Karman vortices developed behind the plate with larger deflection angles. Strong interaction between the wake flow from the leading and trailing edge of the plate was observed. Based on power spectrum density (PSD) analysis, the vortex shedding frequency coincided with the flapping frequency, and the amplitude was positively correlated to the strength of the vortices. Proper orthogonal decomposition (POD) modes evince that, in the case of appreciable motion, coherent structures exhibited a larger spatial scale, enhancing the magnitude of the external torque on the plate.

Numerical Investigations on Unsteady Features of Rounded Trailing Edge Airfoils

As a practical rounded trailing edge airfoil for coaxial rotors, DBLN-526 is a fore and aft symmetrical airfoil with two steps on its lower side. This airfoil has been used at the inboard section of the coaxial rotor system. As there are always two eddies behind the airfoil because of its rounded trailing edge, the interaction between the separation and transition should be considered. Thus, the unsteady Reynolds-averaged Navier-Stokes- (RANS-) based γ − Re ¯ θ t model was used to analyze the unsteady transition and separation features. Three different rounded trailing-edge airfoils were compared with DBLN-526. Power spectrum density analysis and Δ Cl calculations demonstrated that the lift coefficient fluctuation of DBLN-526 was smaller than that of other rounded airfoils with different angles. Further investigation indicated that the locations of transition for DBLN-526 can be fixed at a wide range of angles by the unique design on its lower side. Because of this settled transition location, the size of separation is decreased, and the position of separation is settled as well, which leads to a lower lift coefficient fluctuation. The turbulent kinetic energy after the transition was higher, which injected a lot of energy into the boundary layer, and the separation zone near the transition position was relatively smaller. This study provides an indication for controlling separation and reducing unsteady fluctuations for rounded trailing edge airfoils.

An Improved Altimeter in-Orbit Range Noise-Level Estimation Approach Based on Along-Track Differential Method

Satellite radar altimeters are advanced remote sensing devices that play an important role in observing the global marine environment. Accurately estimating the noise level of altimeter in-orbit ranging data is crucial for evaluating the payload performance, analyzing sea conditions, and monitoring data quality. In this study, we propose an approach based on the differential processing of along-track odd–even data sequences for altimeter in-orbit range noise-level estimation. Using the long-term along-track data sequence can notably improve the issue in the existing method in that the noise level is underestimated owing to the utilization of a relatively short data segment. On the basis of an analysis of the influence of low-frequency components on noise-level estimation, the mathematical formulas of the above differential method were deduced, and the efficacy of the approach in assessing the noise level of altimeter in-orbit data was demonstrated by simulation experiments. This method was used to estimate the noise levels of the 20 Hz datasets of Jason-3 and Sentinel-6, and the idea of the time-domain difference was extended to the frequency domain. The statistical results showed that the 20 Hz noise levels at the significant wave height (SWH) = 2 m were 7.41 cm (Jason-3 low-resolution (LR) mode), 6.66 cm (Sentinel-6 LR mode), and 3.13 cm (Sentinel-6 high-resolution (HR) mode). The power spectrum density analysis further verified its accuracy. By reprocessing the 20 Hz data of Sentinel-6 into 10, 5, and 1 Hz, the effectiveness of the along-track odd–even differential method to directly evaluate the noise level of 1 Hz data was explored, and the impact of ocean signals such as swells on noise-level estimation in synthetic aperture mode was discussed.

Psychophysiological effect according to restoration factors of audio-visual environment

This study investigated the effects of psychophysiological restoration due to environmental factors while experiencing the city, waterfront, and green space using various psychological scales and physiological measurement tools. The environment was experienced using virtual reality technology, and the subjects' responses were collected through surveys and EEG (electroencephalography) and HRV (heart rate variability) measurement. HRV responses were carried out by parameters such as total power (TP), SDNN and TSI. In case of EEG, PSD (power spectrum density) analysis indicated a relatively high restoration effect in the natural environment and increase of alpha-beta ratio. Based on functional connectivity, graph theory analysis showed that the limbic system network of non-restoration group was hyperactive. When comparing HRV responses (increase of TP, SDNN and reduction of TSI), from the resilience group, it was found to have higher global network efficiency. In fact, in urban space, there were fewer psychological restoration responses in the group with high noise sensitivity.

Sub-regional polishing and machining trajectory selection of complex surface based on K9 optical glass

With the rapid progress of science and technology, complex optical surfaces have been widely used in various devices. Due to the complexity of their geometric features, machining with a single trajectory inevitably has an impact on the accuracy of the machined surface. Sub-regional milling has been studied intensively by researchers worldwide. However, few studies have focused on sub-region polishing. Therefore, sub-regional polishing is not widely used in the machining field. This paper investigates the method of sub-regional polishing of complex surfaces and focuses on the selection of polishing trajectories for different processing areas. The method takes into account the curvature characteristics of each point on the surface and combines the Freeman code method to divide the surface into multiple processing regions. The selection of polishing trajectories for each processing area is analyzed from the viewpoint of surface roughness and power spectrum density analysis. The correctness of the trajectory selection is verified by polishing experiments on K9 optical glass. The results show that all three trajectories used in the experiments can reduce the surface roughness of the workpiece by more than 90%. Using the Hilbert trajectory can effectively reduce the medium-frequency and high-frequency errors of the machined surface and improve the optical properties of the surface. This work is expected to provide significant guidance for efficient and high-quality processing of complex optical surfaces compared with traditional machining methods using a single trajectory.

Optical variability of quasars with 20-yr photometric light curves

ABSTRACT We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998−2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping time-scale τDRW continues to rise with increased baseline, reaching a median value of ∼750 d (g band) in the rest frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20 per cent of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades time-scales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping time-scales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on time-scales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping time-scale.

Corrosion resistance and surface microstructure of Mg3 N2 /SS thin films by plasma focus instrument.

Utilizing a plasma focus (PF) instrument, magnesium nitride (Mg3 N2 ) thin films were synthesized on stainless steel substrates. Twenty five optimum focus shots at 8 cm distance from the anode tip were used to deposit the films at different angular positions regarded to the anode axis. Scanning electron microscopy (SEM), atomic force microscopy (AFM), and X-ray diffraction (XRD) analyses were performed to assess the surface morphology and structural characteristics of Mg3 N2 films. Based on AFM images, these films were studied to understand the effect of angular position variation on their surfaces through morphological and fractal parameters. By increasing the angle, we verify that the grain size decreased from 130(0) nm to 75(5) nm and also the mean quadratic surface roughness of the films reduced in its average values from (28.97 ± 3.24) nm to (23.10 ± 1.34) nm. Power spectrum density analysis indicated that films become more self-affine at larger angles. Furthermore, the corrosion behavior of the films was investigated through a potentiodynamic polarization test in H2 SO4 solution. It was found that the ion energy and flux, varying with the angular positions from the anode tip, directly affected the nanostructured roughness and surface morphology of the samples. The electrochemical studies of films show that the uncoated sample presented the lowest corrosion resistance. The highest corrosion resistance was obtained for the sample deposited with 25 optimum shots and at 0° angular position reaching a reduction in the corrosion current density of almost 800 times compared to the pure stainless steel-304 substrate. HIGHLIGHTS: Mg3 N2 /SS films have been deposited at different angles by plasma focus (PF) instruments. The effect of angular position on the surface microtexture, morphological parameters, and corrosion features of the films was studied. The RBS measurement and X-ray diffraction are utilized to identify the crystalline phases and thickness of films.

Optical Variability of Quasars with 20-Year Photometric Light Curves

We study the optical $gri$ photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during $\sim 1998-2020$ with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average $\sim 200$ nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10-15 yr baselines and $\lesssim 100$ epochs. We find that the average damping timescale $\tau_{\rm DRW}$ continues to rise with increased baseline, reaching a median value of $\sim 750$ days ($g$ band) in the rest-frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained $\tau_{\rm DRW}$ (less than 20\% of the baseline), we confirm a weak wavelength dependence of $\tau_{\rm DRW}\propto \lambda^{0.51\pm0.20}$. We further quantify optical variability of these quasars over days to decades timescales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping timescales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on timescales less than $\sim$ a month for these luminous quasars, and this second break point correlates with the longer DRW damping timescale.

Reinforcement Learning-Based Mobile AR/VR Multipath Transmission With Streaming Power Spectrum Density Analysis

Multi-path transmission control protocol (MPTCP) is an extension of TCP that enables the concurrent transmission of information through different network interfaces (e.g., Cellular, Wi-Fi, 802.11p, and so on) available at terminal side. It is well known that MPTCP can provide significant advantages in bandwidth aggregation and transmission stability. Unfortunately, path diversity can limit bandwidth aggregation efficiency and incur higher delays. These issues become critical when in presence of emerging mobile AR and VR applications, which are bandwidth hungry, time-sensitive and exhibit abrupt variations of the bitrate. To address these issues, we propose the <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</u> einforcement <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">L</u> earning-based mobile AR/VR multipath transmission with streaming <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</u> ower <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</u> pectrum <underline xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D</u> ensity analysis (RL-PSD). RL-PSD analyses the Power Spectrum Density (PSD) of the AR/VR input stream to extract its features. Then, both the input stream and network features are considered to model the MPTCP congestion control as an reinforcement learning process. Finally, a two-stage reinforcement algorithm is proposed to optimize transmission performance. RL-PSD has been tested in both single-terminal and multi-terminal scenarios: results show that it outperforms the other advanced solutions conceived to support the multipath transmission of AR/VR streams.

Prediction of REM (Rapid Eye Movement) Sleep Behaviour Disorder using EEG Signal applied EMG1 and EMG2 Channel

This sleep disorder is reflected as the changes in the electrical activities and chemical activities in the brain that can be observed by capturing the brain signals and the images. In this research, Short Time-frequency analysis of Power Spectrum Density (STFAPSD) approach applied on Electroencephalogram (EEG) Signals for prediction of RBD sleep disorder. Collection of Electroencephalogram (EEG) of normal subjects &amp; different type of sleep disordered subjects &amp; application of signal processing on EEG data for development the algorithm for detection of sleep disorder and implementation in MATLAB.