A 5 GHz LC-VCO frequency synthesizer for unlicensed band of WiMAX

This paper presents a low power and low phase noise CMOS integer-N frequency synthesizer based on the charge-pump Phase Locked Loop (PLL) topology. The frequency synthesizer can be used for IEEE 802.16 unlicensed band of WiMAX (World Interoperability for Microwave Access). The operation frequency of the proposed design is ranged from 5.13 to 5.22 GHz. The proposed Voltage-Controlled Oscillator (VCO) achieves low power consumption and low phase noise. The high speed divider is implemented by an optimal extended true single phase clock (E-TSPC) prescaler. It can achieve higher operating frequency and lower power consumption. A new frequency divider is also proposed to eliminate the hardware overhead of the S counter in the conventional programmable divider. The proposed frequency synthesizer consists of a phase-frequency detector (PFD), a charge pump, a low-pass loop filter, a VCO, and a frequency divider. The simulated phase noise of the proposed VCO is −121.6 dBc/Hz at 1 MHz offset from the carrier frequency. The proposed frequency synthesizer consumes 13.1 mW. The chip with an area of 1.048 × 1.076 mm² is fabricated in a TSMC 0.18 μm CMOS 1P6M technology process.     

Determination of optimal parameters for bilateral filter in brain MR image denoising

Noise elimination is an important pre-processing step in magnetic resonance (MR) images for clinical purposes. In the present study, as an edge-preserving method, bilateral filter (BF) was used for Rician noise removal in MR images. The choice of BF parameters affects the performance of denoising. Therefore, as a novel approach, the parameters of BF were optimized using genetic algorithm (GA). First, the Rician noise with different variances (σ = 10, 20, 30) was added to simulated T1-weighted brain MR images. To find the optimum filter parameters, GA was applied to the noisy images in searching regions of window size [3 × 3, 5 × 5, 7 × 7, 11 × 11, and 21 × 21], spatial sigma [0.1–10] and intensity sigma [1–60]. The peak signal-to-noise ratio (PSNR) was adjusted as fitness value for optimization.After determination of optimal parameters, we investigated the results of proposed BF parameters with both the simulated and clinical MR images. In order to understand the importance of parameter selection in BF, we compared the results of denoising with proposed parameters and other previously used BFs using the quality metrics such as mean squared error (MSE), PSNR, signal-to-noise ratio (SNR) and structural similarity index metric (SSIM). The quality of the denoised images with the proposed parameters was validated using both visual inspection and quantitative metrics. The experimental results showed that the BF with parameters proposed by us showed a better performance than BF with other previously proposed parameters in both the preservation of edges and removal of different level of Rician noise from MR images. It can be concluded that the performance of BF for denoising is highly dependent on optimal parameter selection.     

Multi-class fault diagnosis of induction motor using Hilbert and Wavelet Transform

The information extraction capability of two widely used signal processing tools, Hilbert Transform (HT) and Wavelet Transform (WT), is investigated to develop a multi-class fault diagnosis scheme for induction motor using radial vibration signals. The vibration signals are associated with unique predominant frequency components and instantaneous amplitudes depending on the motor condition. Using good systematic and analytical approach this fault frequencies can be identified. However, some faults either electrical or mechanical in nature are associated with same or similar vibration frequencies leading to erroneous conclusions. Genetic Algorithm (GA) is proposed and used successfully to find the most relevant fault frequencies in radial (vertical) frame vibration signal which can be used to diagnose the induction motor faults very effectively even in the presence of noise. The information obtained by Continuous Wavelet Transform (CWT) was found to be highly redundant compared to HT and thus by selecting the most relevant features using GA, the fault classification accuracy has considerably improved especially for CWT. Almost similar fault frequencies were found using CWT + GA and HT + GA for radial vibration signal.     

Design and fabrication of an alternating dielectric multi-layer device for surface plasmon resonance sensor

An alternating dielectric multi-layer device was fabricated and tested in the laboratory to show that dielectric mirrors of alternating high/low refractive index materials, based on the design of distributed Bragg reflector (DBR) for vertical cavity surface emission lasers (VCSELs), can be used in designing SPR biochemical sensors. The thickness, number of layers, and other design parameters of the device used were optimized using optical admittance loci analysis. The proof-of-concept device was fabricated with a symmetrical structure using Au/(SiO₂/TiO₂)₄/Au.Using a 632 nm-wavelength light source on a BK7 coupling prism, our laboratory tests showed that, under water, there was an 11.5° shift in resonant peak position towards the critical angle (from 74° in a conventional single-layer Au film), and a 3.25 times decrease in FWHM (the half-peak width). Our design also resulted in a wider dynamic range of up to a 1.50 refractive index unit (RIU), compared to 1.38 RIU in a conventional single-layer Au film. Using glucose solutions in ddH₂O, the calculated resolution was 1.28 × 10⁻⁵. The calculated intensity sensitivity was 10 000 a.u./RIU, about twice the improvement over the conventional single-layer Au film.     

Silicon microphone development and application

This paper gives an overview of the development of Silicon microphones fabricated in a standard BiCMOS process line of Infineon. MEMS development results in reliable processes for high sensitivity poly-silicon membranes. Microphones with sensitivity up to −39 dB V/Pa at 2 V bias and a signal to noise ratio of up to 65 dB(A) are presented. The impact of packaging on the product design is described. As an example a directional microphone with cardioid response and backward noise suppression of 19 dB is described.     

Exploitation of aeroelastic effects for drift reduction,in an all-polymer air flow sensor

This paper presents a vibration amplitude measurement method that greatly reduces the effects of baseline resistance drift in an all-polymer piezoresistive flow sensor or microtuft. The sensor fabrication is based on flexible printed circuit board (flex-PCB) technology to enable the potential for low-cost and scalable manufacture. Drift reduction is accomplished by discriminating the flow-induced vibration (‘flutter’) amplitude of the microtuft-based sensor as a function of flow velocity. Flutter peak-to-peak amplitude is measured using a microcontroller-based custom readout circuit. The fabricated sensor with the readout circuitry demonstrated a drift error of 2.8 mV/h, which corresponds to a flow-referenced drift error of 0.2 m/s of wind velocity per hour. The sensor has a sensitivity of 14.5 mV/(m/s) with less than 1% non-linearity over the velocity range of 5–16 m/s. The proposed vibration amplitude measurement method is also applied to a sensor array with a modified structure and a reduced dimension, which demonstrated a sensitivity of 13.2 mV/(m/s) with a flow-referenced drift error of 0.03 m/s of wind velocity per hour.     

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.     

Development of SAW based gyroscope with high shock and thermal stability

A novel surface acoustic wave (SAW)-based gyroscope with an 80 MHz central frequency was developed on a 128° YX LiNbO₃ piezoelectric substrate. The developed sensor was composed of a SAW resonator, metallic dots, and two SAW delay lines. A SAW resonator was employed to generate a stable standing wave with a large amplitude, metallic dots were used to induce a Coriolis force and to form a secondary SAW, and two delay lines were formed to extract the Coriolis effect by comparing the resonance frequencies between these two delay lines. Coupling of modes (COM) modeling was conducted to determine the optimal device parameters prior to fabrication. According to the simulation results, the device was fabricated and then measured on a rate table. When the device was subjected to an angular rotation, resonant frequency differences between the two oscillators were observed because of the secondary wave, generated by the Coriolis force, perturbed the propagation of the SAW in the sense element. Depending on the angular velocity, the difference of the resonance frequency was linearly modulated. The obtained sensitivity was approximately 172 Hz deg^?1 s^?1 at an angular rate range of 0–500 deg/s. Device performances depending on different mass weights and temperatures were also characterized. Good thermal and shock stabilities were observed during the evaluation process.     

Modal analysis and modified cascade neural networks in identification of geometrical parameters of circular arches

A hybrid computational system, composed of the finite element method (FEM) and cascade neural network system (CNNs), is applied to the identification of three geometrical parameters of elastic arches, i.e. span l, height f and cross-sectional thickness h. FEM is used in the direct (forward) analysis, which corresponds to the mapping α = {l, f, h} → {ω_j}, where: α – vector of control parameters, ω_j – arch eigenfrequencies. The reverse analysis is related to the identification procedure in which the reverse mapping is performed {ω_j} → {α_i}. For the identification purposes a recurrent, three level CNNs of structure (D^k-H^k-1)_s was formulated, where: k – recurrence step, s = I, II, III-levels of cascade system. The Semi-Bayesian approach is introduced for the design of CNNs applying the MML Maximum Marginal Likelihood) criterion. The computation of hyperparameters is performed by means of the Bayesian procedure evidence. The numerical analysis proves a great numerical efficiency of the proposed hybrid approach for both the perfect (noiseless) values of eigenfrequencies and noisy ones simulated by an added artificial noise.     

The possibility of using C20 fullerene and graphene as semiconductor segments for detection,and destruction of cyanogen-chloride chemical agent

Detection of hazardous chemical species by changing the electrical conductivity of a semiconductor matter is a proposed and applied way for decreasing their subsequent unpleasant effects. Recently, many examples of using inorganic or organic materials, polymeric, and also nano-sized species as sensors were reported in which, in some cases, those matters were strongly affective and suitable.In this project, we have made an assessment on whether the graphene segment or C₂₀ fullerene, able to sense the existence of cyanogen chloride NCCl? In order to gain trustable results, the possible reaction pathways along with the adsorption kinetics were investigated. Moreover, the electronic density of states DOS showed that C₂₀ fullerene senses the existence of cyanogen chloride agent with a clearer signal (ΔE_g = 0.0110 eV) compared to the graphene segment (ΔE_g = 0.0001 eV). Also the adsorption energy calculations showed that cyanogen chloride could be adsorbed by the fullerene in a multi-step process (E_ads1 = −0.852 kcal mol⁻¹; E_ads2 = −0.446 kcal mol⁻¹; E_ads3 = −2.330 kcal mol⁻¹).     

Remote sensing of canopy light use efficiency in temperate and boreal forests of North America using MODIS imagery

Light use efficiency (LUE) is an important variable characterizing plant eco-physiological functions and refers to the efficiency at which absorbed solar radiation is converted into photosynthates. The estimation of LUE at regional to global scales would be a significant advantage for global carbon cycle research. Traditional methods for canopy level LUE determination require meteorological inputs which cannot be easily obtained by remote sensing. Here we propose a new algorithm that incorporates the enhanced vegetation index (EVI) and a modified form of land surface temperature (T_m) for the estimation of monthly forest LUE based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Results demonstrate that a model based on EVI × T_m parameterized from ten forest sites can provide reasonable estimates of monthly LUE for temperate and boreal forest ecosystems in North America with an R² of 0.51 (p < 0.001) for the overall dataset. The regression coefficients (a, b) of the LUE–EVI × T_m correlation for these ten sites have been found to be closely correlated with the average EVI (EVI_ave, R² = 0.68, p = 0.003) and the minimum land surface temperature (LST_min, R² = 0.81, p = 0.009), providing a possible approach for model calibration. The calibrated model shows comparably good estimates of LUE for another ten independent forest ecosystems with an overall root mean square error (RMSE) of 0.055 g C per mol photosynthetically active radiation. These results are especially important for the evergreen species due to their limited variability in canopy greenness. The usefulness of this new LUE algorithm is further validated for the estimation of gross primary production (GPP) at these sites with an RMSE of 37.6 g C m^? 2 month^? 1 for all observations, which reflects a 28% improvement over the standard MODIS GPP products. These analyses should be helpful in the further development of ecosystem remote sensing methods and improving our understanding of the responses of various ecosystems to climate change.     

Classification of modulation signals using statistical signal characterization and artificial neural networks

Modulation recognition systems have to be able to correctly classify the incoming signal modulation scheme in the presence of noise. A new method for classification of analogue and digital modulated signals at low signal-to-noise ratio (SNR) is introduced in this paper. This method uses the statistical signal characterization (SSC) to extract parameters to classify the different modulation signals. The SSC technique produces a set of four numerical parameters for a specific modulated signal. Subsequent comparison of these parameters to those of other waveforms provides the basis for our classification system. The results of SSC technique are applied to an artificial neural network (ANN) to have a robust classification system in the presence of noise down to SNR of 3 dB. No a priori information is required by this technique about the set of input waveforms. The input to the classification system can be analogue or digital signals or a combination of both. The proposed technique shows a 100% efficiency of classification of analogue signals or digital signals at SNR of 7 dB. This classification efficiency reduces to 83% and 86% for analogue or digital signals at SNR of 3 dB. The SSC technique shows better classification results in comparison with other techniques with an important advantage over other methods, which is the simplicity of the neural network needed with this technique due to the small number of features used in the classification.     

Flow-injection determination of iron(III) in soil by biamperometry using two independent redox couples

A flow-injection biamperometric method for the determination of iron(III) has been described. The detector consists of two chambers separated by a salt bridge, and one platinum wire working electrode is embedded in each chamber, respectively. When iron(III) solution and hydrogen peroxide solution simultaneously flow through two chambers, the reduction of iron(III) at one platinum electrode is associated with the oxidation of hydrogen peroxide at the other platinum electrode, forming such a system as similar to a reversible couple one. The biamperometric system can perform the determination of iron(III) without any external potential difference. The linear relationship is obtained from 1.0 × 10⁻⁶ to 1.0 × 10⁻⁴ mol l⁻¹ with a detection limit of 6.0 × 10⁻⁷ mol l⁻¹. The proposed method exhibits the satisfactory reproducibility with a relative standard derivation (R.S.D.) of 1.4% for 17 successive determinations of 2.0 × 10⁻⁵ mol l⁻¹ iron(III) and is applied to the determination of iron(III) in soil.     

Spin-valve planar Hall sensor for single bead detection

The planar Hall effect (PHE) sensor with a junction size of 3 μm × 3 μm for a single micro-bead detection has been fabricated successfully using a typical spin-valve thin film Ta(5)/NiFe(16)/Cu(1.2)/NiFe(2)/IrMn(15)/Ta(5) nm. The PHE sensor exhibits a sensitivity of about 7.2 μV Oe^?1 in the magnetic field range of ±7 Oe approximately. We have performed an experiment to illustrated the possibility of single micro-bead detection by using a PHE sensor. A single micro-bead of 2.8 μm diameter size is secluded from 0.1% dilute solution of the Dynabeads^® M-280 dropped on the sensor surface and is located on the sensor junction by using a micro magnetic needle. The comparison of the PHE voltage profiles in the field range from 0 to 20 Oe in the absence and presence of a single micro-bead identifies a single Dynabeads^® M-280, the maximal signal change as large as ΔV ～ 1.1 μV can be obtained at the field ～6.6 Oe. The results are well described in terms of the reversal of a basic single domain structure.     

A distance-based aggregation approach for group decision making with interval preference orderings

Xu (2013) proposed a nonlinear programming model to derive an exact formula to determine the experts’ relative importance weights for the group decision making (GDM) with interval preference orderings. However, in this study, we show that the exact formula to determine the weight vector which always equals to w = (1/m, 1/m, … , 1/m)^T (m is the number of experts). In this paper, we propose a distance-based aggregation approach to assess the relative importance weights for GDM with interval preference orderings. Relevant theorems are offered to support the proposed approach. After that, by using the weighted arithmetic averaging operator, we obtain the aggregated virtual interval preference orderings. We propose a possibility degree formula to compare two virtual interval preference orderings, then rank and select the alternatives. The proposed method is tested by two numerical examples. Comparative analysis are provided to show the advantages and effectiveness 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.     

Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content,leaf mass per area,leaf area index and leaf canopy biomass

This article aims at finding efficient hyperspectral indices for the estimation of forest sun leaf chlorophyll content (CHL, µg cm_leaf^? 2), sun leaf mass per area (LMA, g_{dry matter} m_leaf^? 2), canopy leaf area index (LAI, m²_leaf m_soil^? 2) and leaf canopy biomass (B_leaf, g_{dry matter} m_soil^? 2). These parameters are useful inputs for forest ecosystem simulations at landscape scale. The method is based on the determination of the best vegetation indices (index form and wavelengths) using the radiative transfer model PROSAIL (formed by the newly-calibrated leaf reflectance model PROSPECT coupled with the multi-layer version of the canopy radiative transfer model SAIL). The results are tested on experimental measurements at both leaf and canopy scales. At the leaf scale, it is possible to estimate CHL with high precision using a two wavelength vegetation index after a simulation based calibration. At the leaf scale, the LMA is more difficult to estimate with indices. At the canopy scale, efficient indices were determined on a generic simulated database to estimate CHL, LMA, LAI and Bleaf in a general way. These indices were then applied to two Hyperion images (50 plots) on the Fontainebleau and Fougères forests and portable spectroradiometer measurements. They showed good results with an RMSE of 8.2 µg cm^? 2 for CHL, 9.1 g m^? 2 for LMA, 1.7 m² m^? 2 for LAI and 50.6 g m^? 2 for Bleaf. However, at the canopy scale, even if the wavelengths of the calibrated indices were accurately determined with the simulated database, the regressions between the indices and the biophysical characteristics still had to be calibrated on measurements. At the canopy scale, the best indices were: for leaf chlorophyll content: ND_chl = (ρ₉₂₅ ? ρ₇₁₀)/(ρ₉₂₅ + ρ₇₁₀), for leaf mass per area: ND_LMA = (ρ₂₂₆₀ ? ρ₁₄₉₀)/(ρ₂₂₆₀ + ρ₁₄₉₀), for leaf area index: D_LAI = ρ₁₇₂₅ ? ρ₉₇₀, and for canopy leaf biomass: ND_Bleaf = (ρ₂₁₆₀ ? ρ₁₅₄₀)/(ρ₂₁₆₀ + ρ₁₅₄₀).     

Simultaneous determination of epinephrine and ascorbic acid at the electrochemical sensor of triazole SAM modified gold electrode

The electrochemical sensor of triazole (TA) self-assembled monolayer (SAM) modified gold electrode (TA SAM/Au) was fabricated. The electrochemical behaviors of epinephrine (EP) at TA SAM/Au have been studied. The TA SAM/Au shows an excellent electrocatalytic activity for the oxidation of EP and accelerates electron transfer rate. The diffusion coefficient is 1.135 × 10⁻⁶ cm² s⁻¹. Under the optimum experiment conditions (i.e. 0.1 mol L⁻¹, pH 4.4, sodium borate buffer, accumulation time: 180 s, accumulation potential: 0.6 V, scan rate: 0.1 Vs⁻¹), the cathodic peak current of EP versus its concentration has a good linear relation in the ranges of 1.0 × 10⁻⁷ to 1.0 × 10⁻⁵ mol L⁻¹ and 1.0 × 10⁻⁵ to 6.0 × 10⁻⁴ mol L⁻¹ by square wave adsorptive stripping voltammetry (SWASV), with the correlation coefficient of 0.9985 and 0.9996, respectively. Detection limit is down to 1.0 × 10⁻⁸ mol L⁻¹. The TA SAM/Au can be used for the determination of EP in practical injection. Meantime, the oxidative peak potentials of EP and ascorbic acid (AA) are well separated about 200 ± 10 mV at TA SAM/Au, the oxidation peak current increases approximately linearly with increasing concentration of both EP and AA in the concentration range of 2.0 × 10⁻⁵ to 1.6 × 10⁻⁴ mol L⁻¹. It can be used for simultaneous determination of EP and AA.     

Investigation of Ni-based thermal bimaterial structure for sensor and actuator application

Thermal bimaterial structures made of Ni and Ni-diamond nanocomposite for sensor and actuator application are proposed, fabricated, and tested. Two deflection types of thermal bimaterial structures, including upward and downward bending types, can be easily fabricated by controlling electroplating sequence of Ni and Ni-diamond nanocomposite. According to thermal performance measurement, the tip deflection of upward and downward types can reach about 82.5 μm and ?22.5 μm for a temperature change of 200 °C, respectively. In the condition, the thermomechanical sensitivity and output force are 412.5 nm/K and 97.0 μN for upward type thermal bimaterial structure; and ?112.5 nm/K and ?26.5 μN for downward type one. Due to the low electroplating process temperature (～50 °C) for both Ni-based layers, diminutive pre-deformation of as-fabricated structure and strong interlaminar bonding strength are verified by SEM and vibrational test. The resonant frequency of the structure remains unchanged after 10⁹ cycles.     

Using of hydrogen ion-selective poly(vinyl chloride) membrane electrode based on calix[4]arene as thiocyanate ion-selective electrode

A hydrogen ion-selective electrode (ISE) is prepared by using 5,11,17,23-tetra-tert-butyl-25,26,27,28-tetracyanometoxy-calix[4]arene and an investigation about whether it could be used as a thiocyanate ion-selective electrode is made by using its characteristic of becoming thiocyanate sensitive in acidic regions. The electrode of the optimum characteristic has a composition of 1% ionophore, 66% 2-NPOE and 33% poly(vinyl chloride) (PVC). This electrode exhibits a linear response over the range 1.0 × 10⁻¹ to 3.0 × 10⁻⁵ M of thiocyanate with a slope of 52.0 ± 0.2 mV/pSCN. The effects of the pH and the membrane composition are also investigated. The lifetime of the electrode is at least 4 months and its response time is found to be 10–15 s. The selectivity coefficients of some anions are calculated by using mixed solution interference method. Application of the electrode to the potentiometric titration of thiocyanate ion with silver nitrate is reported. There is a good agreement between the results obtained by the proposed electrode and the Mohr method at 95% confidence level.