A new approach for estimation of obstructive sleep apnea syndrome

Obstructive sleep apnea syndrome (OSAS) is a situation where repeatedly upper airway stops off while the respiratory effort continues during sleep at least for 10 s. Apart from polysomnography, many researchers have concentrated on exploring alternative methods for OSAS detection. However, not much work has been done on using non-Gaussian and nonlinear behavior of the electroencephalogram (EEG) signals. Bispectral analysis is an advanced signal processing technique particularly used for exhibiting quadratic phase-coupling that may arise between signal components with different frequencies. From this perspective, in this study, a new technique for recognizing patients with OSAS was introduced using bispectral characteristics of EEG signal and an artificial neural network (ANN). The amount of Quadratic phase coupling (QPC) in each subband of EEG (namely; delta, theta, alpha, beta and gamma) was calculated over bispectral density of EEG. Then, these QPCs were fed to the input of the designed ANN. The neural network was configured with two outputs: one for OSAS and one for estimation of normal situation. With this technique a global accuracy of 96.15% was achieved. The proposed technique could be used in designing automatic OSAS identification systems which will improve medical service.     

Capacity achieving high rate space-time block codes

It is well known, that the Alamouti scheme is the only space-time code from orthogonal design achieving the capacity of multiple-input multiple-output (MIMO) wireless communication system with n/sub T/=2 transmit antennas and n/sub R/=1 receive antenna. In this work, we propose the n-times stacked Alamouti scheme for n/sub T/=2n transmit antennas and show that this scheme achieves the capacity in the case of n/sub R/=1 receive antenna. For the more general case of more than one receive antenna, we show that if the number of transmit antennas is higher than the number of receive antennas we achieve a high portion of the capacity with this scheme.     

First-principles calculations of elemental crystalline boron phases under high pressure: Orthorhombic B28 and tetragonal B48

The structural, electronic, mechanical properties and hardness of orthorhombic B₂₈ and tetragonal B₄₈ boron phases have been studied by first-principles of pseudopotential calculations. The results indicated that both boron phases are energetically and also mechanically stable. In addition to electronic properties of highly directional covalent bonds, mechanical properties, and also the Debye temperatures of structures support that both are superhard materials. Calculated electronic band structures and density of states revealed that orthorhombic B₂₈ crystal is a semiconductor, and the tetragonal B₄₈ is metallic. The pressure-dependent behaviors of both structures are different, and both are ultra-incompressible and anisotropic materials. The physical parameters of the structures such as lattice parameters, bond lengths, and also energy gaps between valance and conduction bands are closely sensitive to applied external pressures. By means of pressure-volume graphs, obtained EOSs for α-rhombohedral B₁₂, orthorhombic B₂₈ and tetragonal B₄₈ boron phases are compared with available data. However, energetically possible pressure-induced phase transitions among the purposed structures are predicted on the pressure range of 0-460 GPa. Furthermore, our calculations showed that for the pressures from 0 GPa to 24 GPa energetically the more stable elemental boron phase is α-rhombohedral B₁₂, and from 24 GPa to 106 GPa is orthorhombic B₂₈, and from 106 GPa to 460 GPa is α-Ga-type boron.     

Estimating vigilance level by using EEG and EMG signals

We developed a new method for estimation of vigilance level by using both EEG and EMG signals recorded during transition from wakefulness to sleep. Previous studies used only EEG signals for estimating the vigilance levels. In this study, it was aimed to estimate vigilance level by using both EEG and EMG signals for increasing the accuracy of the estimation rate. In our work, EEG and EMG signals were obtained from 30 subjects. In data preparation stage, EEG signals were separated to its subbands using wavelet transform for efficient discrimination, and chin EMG was used to verify and eliminate the movement artifacts. The changes in EEG and EMG were diagnosed while transition from wakefulness to sleep by using developed artificial neural network (ANN). Training and testing data sets consist of the subbanded components of EEG and power density of EMG signals were applied to the ANN for training and testing the system which gives three situations for the vigilance level of the subject: awake, drowsy, and sleep. The accuracy of estimation was about 98–99% while the accuracy of the previous study, which uses only EEG, was 95–96%.     

Ranking kinematics for revising by contextual information

Annals of Mathematics and Artificial Intelligence - Probability kinematics is a leading paradigm in probabilistic belief change. It is based on the idea that conditional beliefs should be...     

Stacked OSTBC: Error Performance and Rate Analysis

It is well known that the Alamouti scheme is the only space-time code from orthogonal designs achieving the capacity of a multiple-input multiple-output (MIMO) wireless communication system with n_T=2 transmit antennas and n_R=1 receive antenna. In this paper, we propose the n-times stacked Alamouti scheme for n_T=2n transmit antennas and show that this scheme achieves the capacity in the case of n_R=1 receive antenna. This result may regarded as an extension of the Alamouti case. For the more general case of more than one receive antenna, we show that if the number of transmit antennas is higher than the number of receive antennas, we achieve a high portion of the capacity with this scheme. Further, we show that the MIMO capacity is at most twice the rate achieved with the proposed scheme for all signal-to-noise ratio (SNR). We derive lower and upper bounds for the rate achieved with this scheme and compare it with upper and lower bounds for the capacity. In addition to the capacity analysis based on the assumption of a coherent channel, we analyze the error rate performance of the stacked orthogonal space-time block code (OSTBC) with the optimal maximum-likelihood (ML) detector and with the suboptimal lattice-reduction (LR)-aided zero-forcing detector. We compare the error rate performance of the stacked OSTBC with spatial multiplexing (SM) and full-diversity achieving schemes. Finally, we illustrate the theoretical results by numerical simulations.     

The Effect of Deposition Conditions on Adhesion Strength of Ti and Ti6Al4V Cold Spray Splats

Cold spray is a complex process where many parameters have to be considered in order to achieve optimized material deposition and properties. In the cold spray process, deposition velocity influences the degree of material deformation and material adhesion. While most materials can be easily deposited at relatively low deposition velocity (<700 m/s), this is not the case for high yield strength materials like Ti and its alloys. In the present study, we evaluate the effects of deposition velocity, powder size, particle position in the gas jet, gas temperature, and substrate temperature on the adhesion strength of cold spayed Ti and Ti6Al4V splats. A micromechanical test technique was used to shear individual splats of Ti or Ti6Al4V and measure their adhesion strength. The splats were deposited onto Ti or Ti6Al4V substrates over a range of deposition conditions with either nitrogen or helium as the propelling gas. The splat adhesion testing coupled with microstructural characterization was used to define the strength, the type and the continuity of the bonded interface between splat and substrate material. The results demonstrated that optimization of spray conditions makes it possible to obtain splats with continuous bonding along the splat/substrate interface and measured adhesion strengths approaching the shear strength of bulk material. The parameters shown to improve the splat adhesion included the increase of the splat deposition velocity well above the critical deposition velocity of the tested material, increase in the temperature of both powder and the substrate material, decrease in the powder size, and optimization of the flow dynamics for the cold spray gun nozzle. Through comparisons to the literature, the adhesion strength of Ti splats measured with the splat adhesion technique correlated well with the cohesion strength of Ti coatings deposited under similar conditions and measured with tubular coating tensile (TCT) test.