Impact of Ultra Wide Band emission on WiMAX systems at 2.5 and 3.5 GHz

In this work, results of an analytical analysis to assess the effect of Ultra Wide Band (UWB) emissions on the Worldwide Interoperability for Microwave Access system (WiMAX) are presented. The WiMAX range is evaluated with and without the UWB interference. Free space propagation model is used to calculate the UWB signal power that interferes with WiMAX systems. It is shown that, for the case of single UWB transmitter, WiMAX system can easily tolerate UWB interference when the UWB EIRP is ?83 dBm/MHz or less for a distance between the UWB transmitter and the WiMAX receiver of 1 m or higher at 3.5 GHz frequency in order to have only 5% range reduction. To make this possible, multi band UWB should not transmit in the first and the second bands. This will have a detrimental effect on UWB technology. For 2.5 GHz WiMAX, the range reduction will be 5% when the UWB EIRP is ?87 dBm/MHz.     

Speech authentication system using digital watermarking and pattern recovery

The objective of this paper is to detect speech forgery using digital audio watermarking and pattern recovery techniques. A digital watermark pattern has been attached with the speech signal to detect three kinds of alterations or forgeries such as substitution, insertion, and removal. The watermark pattern will be modified if some changes have been made to the speech contents. Modification and forgery can be measured and detected by pattern recovery. The proposed method uses the cyclic pattern embedding to overcome synchronizing problems of previous detection techniques. In addition, pattern recovery enhances the robustness to compression. This method has been tested and verified using six recording devices, which was used for collecting verbal data. The speech signals were sampled at the rate of 8 kHz and digitized at 16 bits resolution. Randomly chosen regions were substituted, removed, and compressed in MP3 at the rate of 16 kbps as well as in CELP at the rate of 11.5 kbps. The experiment shows the perfect detection for three kinds of forgeries and it proved the validity of the proposed method.     

High resolution ambulatory holter ECG events detection-delineation via modified multi-lead wavelet-based features analysis: Detection and quantification of heart rate turbulence

The presented study describes a false-alarm probability-FAP bounded solution for detecting and quantifying Heart Rate Turbulence (HRT) major parameters including heart rate (HR) acceleration/deceleration, turbulence jump, compensatory pause value and HR recovery rate. To this end, first, high resolution multi-lead holter electrocardiogram (ECG) signal is appropriately pre-processed via Discrete Wavelet Transform (DWT) and then, a fixed sample size sliding window is moved on the pre-processed trend. In each slid, the area under the excerpted segment is multiplied by its curve-length to generate the Area Curve Length (ACL) metric to be used as the ECG events detection-delineation decision statistic (DS). The ECG events detection-delineation algorithm was applied to various existing databases and as a result, the average values of sensitivity and positive predictivity Se = 99.95% and P+ = 99.92% were obtained for the detection of QRS complexes, with the average maximum delineation error of 7.4 msec, 4.2 msec and 8.3 msec for P-wave, QRS complex and T-wave, respectively. Because the heart-rate time series might include fast fluctuations which don’t follow a premature ventricular contraction (PVC) causing high-level false alarm probability (false positive detections) of HRT detection, based on the binary two-dimensional Neyman-Pearson radius test (which is a FAP-bounded classifier), a new method for discrimination of PVCs from other beats using the geometrical-based features is proposed. The statistical performance of the proposed HRT detection-quantification algorithm was obtained as Se = 99.94% and P+ = 99.85% showing marginal improvement for the detection-quantification of this phenomenon. In summary, marginal performance improvement of ECG events detection-delineation process, high performance PVC detection and isolation from noisy holter data and reliable robustness against holter strong noise and artifacts can be mentioned as important merits and capabilities of the proposed HRT detection algorithm.     

Evaluating the use of ECG signal in low frequencies as a biometry

Traditional strategies, such as fingerprinting and face recognition, are becoming more and more fraud susceptible. As a consequence, new and more fraud proof biometrics modalities have been considered, one of them being the heartbeat pattern acquired by an electrocardiogram (ECG). While methods for subject identification based on ECG signal work with signals sampled in high frequencies (>100 Hz), the main goal of this work is to evaluate the use of ECG signal in low frequencies for such aim. In this work, the ECG signal is sampled in low frequencies (30 Hz and 60 Hz) and represented by four feature extraction methods available in the literature, which are then feed to a Support Vector Machines (SVM) classifier to perform the identification. In addition, a classification approach based on majority voting using multiple samples per subject is employed and compared to the traditional classification based on the presentation of single samples per subject each time. Considering a database composed of 193 subjects, results show identification accuracies higher than 95% and near to optimality (i.e., 100%) when the ECG signal is sampled in 30 Hz and 60 Hz, respectively, being the last one very close to the ones obtained when the signal is sampled in 360 Hz (the maximum frequency existing in our database). We also evaluate the impact of: (1) the number of training and testing samples for learning and identification, respectively; (2) the scalability of the biometry (i.e., increment on the number of subjects); and (3) the use of multiple samples for person identification.     

Buffered DDA command generation in a CNC

In a computerized numerical controller (CNC), interpolating more than one block in a sampling interval, increases the feed rate. Some commands skipped by the generator are pre-saved in a circular buffer, to provide faster operation than that of a conventional digital differential analyzer. The feed rate can be increased when programmed distances are short. The high feed rate is confirmed by installing the buffered command generation algorithm in the motion board that includes a digital signal processor. The feed rate can reach 11.6 m/min, when minimal (1 μm) distance is programmed in all blocks.     

Mechanical design and characterization of a resonant magnetic field microsensor with linear response and high resolution

A resonant magnetic field microsensor based on Microelectromechanical Systems (MEMS) technology including a piezoresistive detection system has been designed, fabricated, and characterized. The mechanical design for the microsensor includes a symmetrical resonant structure integrated into a seesaw rectangular loop (700 μm × 450 μm) of 5 μm thick silicon beams. An analytical model for estimating the first resonant frequency and deflections of the resonant structure by means of Rayleigh and Macaulay's methods is developed. The microsensor exploits the Lorentz force and presents a linear response in the weak magnetic field range (40–2000 μT). It has a resonant frequency of 22.99 kHz, a sensitivity of 1.94 V T^?1, a quality factor of 96.6 at atmospheric pressure, and a resolution close to 43 nT for a frequency difference of 1 Hz. In addition, the microsensor has a compact structure, requires simple signal processing, has low power consumption (16 mW), as well as an uncomplicated fabrication process. This microsensor could be useful in applications such as the automotive sector, the telecommunications industry, in consumer electronic products, and in some medical applications.     

A traffic cellular automata model based on road network grids and its spatial and temporal resolution’s influences on simulation

Microscopic Traffic Simulation Model based on Cellular Automata (CA) has become more and more popular since it was firstly introduced by Creamer and Ludwig in 1986. Cellular automata are simpler to implement on computers, provide a simple physical picture of the system and can be easily modified to deal with different aspects of traffic. However, in a traditional traffic CA model, the spatial resolution of CA and temporal resolution of simulation are low. Take TRANSIMS for example. The size of cellular automata is 7.5 m and the time step equals 1 s. In such a case, if a vehicle drives at a speed of 4 cells per s, the speed difference between 95 km/h (3.5 1 7.5 m/s) and 121 km/h (4.4999 1 7.5 m/s) will not be distinguished by simulation models. And the temporal resolution of 1 s makes the system hard to model different drivers’ reaction time, which plays a very important role in vehicular movement models. In this paper, a microscopic traffic cellular automata model based on road network grids is proposed to overcome the low spatial and temporal resolutions of traditional traffic CA models. In our model, spatial resolution can be changed by setting different grid size for lanes and intersections before or during simulation and temporal resolution can be defined according to simulation needs to model different drivers’ reaction time, whereas the vehicular movement models are still traditional CA models. By doing so, the low spatial and temporal resolution of CA model can be overcome and the advantages of using CA to simulate traffic are preserved. The paper also presents analyses of the influences on simulation of different 1D lane grid size, 2D intersection grid size and different combinations of temporal resolution and mean drivers’ reaction time. The analysis results prove the existence of spatial and temporal resolution thresholds in traffic CA models. They also reveal that the size of grids, the combinations of different temporal resolutions and mean drivers’ reaction time do pose influences on the speed of vehicles and lane/intersection occupancy, but do not affect the volume of traffic greatly.     

A moving horizon approach to input design for closed loop identification

The identification of high fidelity models is a critical element in the implementation of high performance model predictive control (MPC) applications in the industry. These controllers can vary in size with input–ouput dimensions ranging from 5 × 10 to 50 × 100. Identifying models of this scale accurately is a time consuming and demanding exercise. We present a novel approach wherein an information rich test signal is generated in closed loop by maximizing the MPC objective, as opposed to minimization that is done in the standard controller. We show that the proposed input design approach is similar to T-optimal (trace optimal) experiment design method. Our approach automatically accounts for the input and output constraints and is implemented in a moving horizon manner. It is demonstrated through simulation examples on both well and ill-conditioned processes.     

A statistical model for robust integration of narrowband cues in speech

We investigate a statistical model for integrating narrowband cues in speech. The model is inspired by two ideas in human speech perception: (i) Fletcher’s hypothesis (1953) that independent detectors, working in narrow frequency bands, account for the robustness of auditory strategies, and (ii) Miller and Nicely’s analysis (1955) that perceptual confusions in noisy bandlimited speech are correlated with phonetic features. We apply the model to detecting the phonetic feature [ +  /  − sonorant] that distinguishes vowels, approximants, and nasals (sonorants) from stops, fricatives, and affricates (obstruents). The model is represented by a multilayer probabilistic network whose binary hidden variables indicate sonorant cues from different parts of the frequency spectrum. We derive the Expectation-Maximization algorithm for estimating the model’s parameters and evaluate its performance on clean and corrupted speech.     

Experimental blood glucose interval identification of patients with type 1 diabetes

Many problems are confronted when characterizing a type 1 diabetic patient such as model mismatches, noisy inputs, measurement errors and huge variability in the glucose profiles. In this work we introduce a new identification method based on interval analysis where variability and model imprecisions are represented by an interval model as parametric uncertainty.The minimization of a composite cost index comprising: (1) the glucose envelope width predicted by the interval model, and (2) a Hausdorff-distance-based prediction error with respect to the envelope, is proposed. The method is evaluated with clinical data consisting in insulin and blood glucose reference measurements from 12 patients for four different lunchtime postprandial periods each.Following a “leave-one-day-out” cross-validation study, model prediction capabilities for validation days were encouraging (medians of: relative error = 5.45%, samples predicted = 57%, prediction width = 79.1 mg/dL). The consideration of the days with maximum patient variability represented as identification days, resulted in improved prediction capabilities for the identified model (medians of: relative error = 0.03%, samples predicted = 96.8%, prediction width = 101.3 mg/dL). Feasibility of interval models identification in the context of type 1 diabetes was demonstrated.     

Design of high speed gate driver employing IZO TFTs

This paper presents a new bi-side gate driver integrated by indium-zinc-oxide thin film transistors (IZO TFTs). Our optimized operate method can achieve high speed performance by employing a lower duty ratio (25%) CK2 with its pulse located in the middle of the pulse of CK2L to fully use the bootstrapped high voltage of node Q. In addition, the size of devices is optimized by calculation and simulation, and the function of the proposed gate driver is predicted by the circuit simulation. Furthermore, the proposed gate driver with 20 stages is fabricated by the IZO TFTs process. It is shown that a 2.6 μs width pulse with good noise-suppressed characteristic can be successfully output at the condition of R_load = 6 kΩ and C_load = 150 pF. The power consumption of the proposed gate driver with 20 stages is measured as 1 mW. Hence, the proposed gate driver may be applied to the display of 4K resolution (4096 × 2160) at a frame rate of 120 Hz. Moreover, there is a good stability for the proposed gate driver under 48 h operation.     

Modelling the fate and transport of negatively buoyant storm–river water in small multi-basin lakes

The dynamics of negatively buoyant river plumes in a small multi-basin kettle lake with steep bathymetry (Toolik Lake, AK) are simulated using a Cartesian hydrodynamic model based on the solution of the three-dimensional shallow water equations. To validate the model, model predictions are compared with results from previous analytical and laboratory studies and with field observations. The grid resolution adopted for the Toolik Lake model is 0.5 m (= Δz) in the vertical and 20 m (= Δx) in the horizontal, so that the ratio of the bottom slope S₀ to Δz/Δx is lower than 4 in 99% of the computational domain. With that resolution, the model represents correctly the rate of mixing between lake and river water and the speed of propagation of downslope gravity currents. The model provides accurate predictions of the temperature structure (RMSE = 0.25 °C) and of eddy diffusivities at the depths of the intrusions of incoming water. Measurements and modelling show similar fractions and depth distribution of river water on a cross-basin transect, which suggests that the mixing dynamics of the plume as it transits between basins are well resolved. Thus, the stage is set to quantify the ecological consequences of storm events in small lakes with several interconnected basins using coupled biological measurements and 3D modelling.     

Compressive sensing based sub-mm accuracy UWB positioning systems: A space–time approach

A key challenge to achieve very high positioning accuracy (such as sub-mm accuracy) in Ultra-Wideband (UWB) positioning systems is how to obtain ultra-high resolution UWB echo pulses, which requires ADCs with a prohibitively high sampling rate. The theory of Compressed Sensing (CS) has been applied to UWB systems to acquire UWB pulses below the Nyquist sampling rate. This paper proposes a front-end optimized scheme for the CS-based UWB positioning system. A Space–Time Bayesian Compressed Sensing (STBCS) algorithm is developed for joint signal reconstruction by transferring mutual a priori information, which can dramatically decrease ADC sampling rate and improve noise tolerance. Moreover, the STBCS and time difference of arrival (TDOA) algorithms are integrated in a pipelined mode for fast tracking of the target through an incremental optimization method. Simulation results show the proposed STBCS algorithm can significantly reduce the number of measurements and has better noise tolerance than the traditional BCS, OMP, and multi-task BCS (MBCS) algorithms. The sub-mm accurate CS-based UWB positioning system using the proposed STBCS–TDOA algorithm requires only 15% of the original sampling rate compared with the UWB positioning system using a sequential sampling method.     

A two-dimensional nano-positioner: Design,modelling and experiments

In this paper, an X-Y nano-positioner driven by the shear piezoelectric actuators (SPAs) is proposed based on the friction-inertial theory. The nano-positioner can output a two-dimensional motion at a maximum speed of 0.187 mm/s within a 5 mm×5 mm workspace. In order to solve the contradiction between the motion velocity and the motion resolution, the coarse and the fine motion modes are first proposed on the SPAs application. The coarse motion and the fine motion are realized based on the power-function-shaped signal and the combined piecewise-curve signal respectively. The performance of the nano-positioner, e.g. the resolution, the velocity and the fluctuation, are analyzed and discussed based on different driving signals. Compared with other nano-positioners, the proposed system in this paper is superior in respect of compact size, high resolution, high velocity and two switchable motion modes. Furthermore, a prototype system of the proposed nano-positioner has been developed, which is evaluated by using a capacitive sensor based measurement system. Experiment results validate the effectiveness of the proposed methodology that can be employed and extended to a variety of SPA involved systems.     

A survey on wireless sensor network infrastructure for agriculture

The hybrid wireless sensor network is a promising application of wireless sensor networking techniques. The main difference between a hybrid WSN and a terrestrial wireless sensor network is the wireless underground sensor network, which communicates in the soil. In this paper, a hybrid wireless sensor network architecture is introduced. The framework to deploy and operate a hybrid WSN is developed. Experiments were conducted using a soil that was 50% sand, 35% silt, and 15% clay; it had a bulk density of 1.5 g/cm³ and a specific density of 2.6 cm^? 3. The experiment was conducted for several soil moistures (5, 10, 15, 20 and 25%) and three signal frequencies (433, 868 and 915 MHz). The results show that the radio signal path loss is smallest for low frequency signals and low moisture soils. Furthermore, the node deployment depth affected signal attenuation for the 433 MHz signal. The best node deployment depth for effective transmission in a wireless underground sensor network was determined.     

A DFT study on the central-ring doped HBC nanographenes

Nanographenes (NGs) are a segment of graphene whose dangling bonds are saturated with hydrogen atoms, introducing different properties and promising applications. Here we investigate the electronic, thermodynamic, optical, and structural properties of four C₃₆X₃Y₃H₁₈ NGs (X = B, and Al; and Y = N, and P) based on the density functional theory calculations. It was mainly found that 1) BN-NG is planar molecule and the others are buckybowl-shaped ones, 2) The bowl-to-bowl inversion Gibbs free energies (ΔG^#) of buckybowl shaped NGs are very huge and the rate constant is very small, hindering the inversion, 3) The relative energetic stability order based on the standard enthalpy of formation (ΔH_f^°) is as BN > AlN > BP > AlP, which the BN, and AlN doped NGs are stable at room temperature but the BP and AlP doped ones are instable, 4) The electrical conductivity order of magnitude is inverse of that of stability, 5) An exciton binding energy is predicted in the range of 0.57–0.75 eV for the NGs which corresponds to Frenkel exciton type, 6) the NGs are not soluble in organic solvent in agreement with the experimental results and is partially soluble in water solvent with Gibbs free energy of solvation (ΔG_solv) in the range of −6.1 to −10.1 kcal/mol.     

Development of wireless compressive/relaxation-stress measurement system integrated with pressure-sensitive carbon black-filled silicone rubber-based sensors

In order to detect the installation compressive stress and monitor the stress relaxation between two bending surfaces on a defensive furnishment, a wireless compressive-stress/relaxation-stress measurement system based on pressure-sensitive sensors is developed. The flexible pressure-sensitive stress sensor array is fabricated by using carbon black-filled silicone rubber-based composite. The wireless stress measurement system integrated with this sensor array is tested with compressive stress in the range from 0 MPa to 3 MPa for performance evaluation. Experimental results indicate that the fractional change in electrical resistance of the pressure-sensitive stress sensor changes linearly and reversibly with the compressive stress, and its fractional change goes up to 355% under uniaxial compression; the change rate of the electrical resistance can track the relaxation stress and give out a credible measurement in the process of stress relaxation. The relationship between input (compressive stress) and output (the fractional change in electrical resistance) of the pressure-sensitive sensor is ΔR/R₀ = σ × 1.2 MPa^?1. The wireless compressive stress measurement system can be used to achieve sensitivity of 1.33 V/MPa to the stress at stress resolution of 920.3 Pa. The newly developed wireless stress measurement system integrated with pressure-sensitive carbon black-filled silicone rubber-based sensors has advantages such as high sensitivity to stress, high stress resolution, simple circuit and low energy consumption.     

All-optical hydrogen sensor based on a high alloy content palladium thin film

Optical reflectance measurements were performed to determine the hydrogen response characteristics of 20 nm thick Pd_0.6Au_0.4 films. The response time and signal change characteristics were determined as a function of hydrogen concentrations ranging from 0.05% to 4% in a balance of dry CO₂ free air. The detection limit was determined to be 0.05%, with a corresponding response time of 130 s, while at 4% hydrogen concentrations the response time was 5 s at ambient temperatures. A linear decrease of both the signal change and response time was measured within an operating temperature range between 25 °C and 100 °C for a 1% hydrogen in air gas mixture. The sensor response dependence of the Pd_0.6Au_0.4 film with a change in humidity was determined between ambient levels and 95% relative humidity (RH). While the signal change was independent of humidity the response time increased due to water adsorption on the Pd alloy sensing layer. A similar increase in response time was shown for 100 ppm of background CO mixed with 1% hydrogen in nitrogen at room temperature. At an elevated operating temperature of 80 °C, 100 ppm of CO did not affect the sensor response towards 1% hydrogen in a balance of nitrogen. Reliability tests have been performed over a 1-year time period and the sensing specifications have not drifted beyond 2% and 13% of the calibrated signal change and response time, respectively. A response time on the order of seconds and the proven stability of the high alloy content Pd thin film demonstrate the promising attributes of this material for use in an all-optical hydrogen sensor.     

Dynamically modulated intensity interrogation scheme using waveguide coupled surface plasmon resonance sensors

An electro-optically modulated intensity interrogation method based on tunable waveguide coupled surface plasmon resonance sensors has been proposed. It has been theoretically and experimentally demonstrated that the proposed scheme can enable sensitive measurement of measurand variations. By modulating the refractive index in the waveguide layer, this interrogation method yields modulated signal whose amplitude is related to measurand's refractive index. This amplitude modulated signal offers a higher signal to noise ratio and eliminates additive noise in the sensor system. A preliminary investigation using saline buffers with different NaCl concentrations shows a resolution of 2.3 × 10^?6 refractive index unit by our approach. Resolution can be controlled by the amplitude of the applied modulation voltage and can be further enhanced by optimizing the device structure or improving the electro-optical (E-O) coefficient of the E-O material. This approach is simple, stable, and promising for low-cost or multi-channel SPR biosensor applications.     

Statistical shape model for manifold regularization: Gleason grading of prostate histology

Gleason patterns of prostate cancer histopathology, characterized primarily by morphological and architectural attributes of histological structures (glands and nuclei), have been found to be highly correlated with disease aggressiveness and patient outcome. Gleason patterns 4 and 5 are highly correlated with more aggressive disease and poorer patient outcome, while Gleason patterns 1–3 tend to reflect more favorable patient outcome. Because Gleason grading is done manually by a pathologist visually examining glass (or digital) slides subtle morphologic and architectural differences of histological attributes, in addition to other factors, may result in grading errors and hence cause high inter-observer variability. Recently some researchers have proposed computerized decision support systems to automatically grade Gleason patterns by using features pertaining to nuclear architecture, gland morphology, as well as tissue texture. Automated characterization of gland morphology has been shown to distinguish between intermediate Gleason patterns 3 and 4 with high accuracy. Manifold learning (ML) schemes attempt to generate a low dimensional manifold representation of a higher dimensional feature space while simultaneously preserving nonlinear relationships between object instances. Classification can then be performed in the low dimensional space with high accuracy. However ML is sensitive to the samples contained in the dataset; changes in the dataset may alter the manifold structure. In this paper we present a manifold regularization technique to constrain the low dimensional manifold to a specific range of possible manifold shapes, the range being determined via a statistical shape model of manifolds (SSMM). In this work we demonstrate applications of the SSMM in (1) identifying samples on the manifold which contain noise, defined as those samples which deviate from the SSMM, and (2) accurate out-of-sample extrapolation (OSE) of newly acquired samples onto a manifold constrained by the SSMM. We demonstrate these applications of the SSMM in the context of distinguish between Gleason patterns 3 and 4 using glandular morphologic features in a prostate histopathology dataset of 58 patient studies. Identifying and eliminating noisy samples from the manifold via the SSMM results in a statistically significant improvement in area under the receiver operator characteristic curve (AUC), 0.832 ± 0.048 with removal of noisy samples compared to a AUC of 0.779 ± 0.075 without removal of samples. The use of the SSMM for OSE of newly acquired glands also shows statistically significant improvement in AUC, 0.834 ± 0.051 with the SSMM compared to 0.779 ± 0.054 without the SSMM. Similar results were observed for the synthetic Swiss Roll and Helix datasets.