Design and optimization of fully differential capacitive MEMS accelerometer based on surface micromachining

In this paper, design and simulation of a single-axial, capacitive, fully differential MEMS accelerometer based on surface micromachining with two proof masses is presented. So far, most surface micromachined capacitive accelerometers offered, employed differential interface circuits to measure capacitor variations. However, in the presented structure, the possibility of fully differential design is realized by dividing the proof mass to two electrically isolated parts that are located on a silicon nitride layer. By utilizing two proof masses and altering outputs and stimulation voltage, parasitic capacitor is reduced and the sensitivity is increased. Moreover, some sensor capacitors are embedded inside the proof mass, so that sensitivity could be increased in the limited area and electrode length could be reduced. Furthermore, analytic equations are derived to calculate the sensitivity, as well to optimize the sensor structure. The designed sensor has been simulated and optimized using COMSOL Multiphysics, where the simulation results show the mechanical and capacitive sensitivity of 29.8 nm/g and 15.8 fF/g, respectively. The sensor size is 1 mm × 1 mm that leads to excellent performance, regarding to the defined figure of merit.

     

Application of artificial neural networks and genetic programming in vapor–liquid equilibrium of C1 to C7 alkane binary mixtures

In this study, the capacity of artificial neural networks (ANNs) and genetic programming (GP) in making possible, fast and reliable predictions of equilibrium compositions of alkane binary mixtures is investigated. A data set comprising 847 data points was gathered and used in both training the proposed ANN and generating the closed-form expressions of the GP procedure. The results obtained demonstrate the relative precision of the proposed ANN, while, on the other hand, exhibit that the GP model, although less precise, affords high CPU time efficiency and simplicity. Concisely, the proposed models can serve the purpose of being close first estimates for more thermodynamically rigorous vapor–liquid equilibrium calculation procedures and do obviate the necessity for the availability of a large set of experimental binary interaction coefficients. Mean absolute errors of 0.0100 and 0.0404 for liquid compositions and of 0.0054 and 0.0254 for vapor-phase mole fractions, for the proposed ANN and GP models, respectively, are a testament to the reliability of the proposed models.

     

A Sliding Mode Approach to Enhance the Power Quality of Wind Turbines Under Unbalanced Voltage Conditions

An integral terminal sliding mode-based control design is proposed in this paper to enhance the power quality of wind turbines under unbalanced voltage conditions. The design combines the robustness, fast response, and high quality transient characteristics of the integral terminal sliding mode control with the estimation properties of disturbance observers. The controller gains were auto-tuned using a fuzzy logic approach. The effectiveness of the proposed design was assessed under deep voltage sag conditions and parameter variations. Its dynamic response was also compared to that of a standard SMC approach. The performance analysis and simulation results confirmed the ability of the proposed approach to maintain the active power, currents, DC-link voltage and electromagnetic torque within their acceptable ranges even under the most severe unbalanced voltage conditions. It was also shown to be robust to uncertainties and parameter variations, while effectively mitigating chattering in comparison with the standard SMC.      

Simple Short-Term Probabilistic Drought Prediction Using Mediterranean Teleconnection Information

Timely forecasts of the onset or possible evolution of droughts is an important contribution to mitigate their manifold negative effects; therefore, in this paper, we propose a mathematically-simple drought forecasting framework gaining Mediterranean Sea temperature information (SST-M) to predict droughts. Agro-metrological drought index addressing seasonality and autocorrelation (AMDI-SA) was used in a Markov model in Urmia lake basin, North West of Iran. Markov chain is adopted to model drought for joint occurrence of different classes of drought severity and sea surface temperature of Mediterranean Sea, which is called 2D Markov chain model. The proposed model, which benefits suitability of Markov chain models for modeling droughts, showed improvement results in prediction scores relative to classic Markov chain model not including SST-M information, additionally.     

Fault detection and isolation using viability theory and interval observers

This paper proposes the use of interval observers and viability theory in fault detection and isolation (FDI). Viability theory develops mathematical and algorithmic methods for investigating the viability constraints characterisation of dynamic evolutions of complex systems under uncertainty. These methods can be used for checking the consistency between observed and predicted behaviour by using simple sets that approximate the exact set of possible behaviour (in the parameter or state space). In this paper, FDI is based on checking for an inconsistency between the measured and predicted behaviours using viability theory concepts and sets. Finally, an example is provided in order to show the usefulness of the proposed approach.     

Application of the active learning method to the retrieval of pigment from spectral remote sensing reflectance data

Due to the noise that is present in remote sensing data, a robust method to retrieve information is needed. In this study, the active learning method (ALM) is applied to spectral remote sensing reflectance data to retrieve in‐water pigment. The heart of the ALM is a fuzzy interpolation method that is called the ink drop spread (IDS). Three datasets (SeaBAM, synthetic and NOMAD) are used for the evaluation of the selected ALM approach. Comparison of the ALM with the ocean colour 4 (OC4) algorithm and the artificial neural network (ANN) algorithm demonstrated the robustness of the ALM approach in retrieval of in‐water constituents from remote sensing reflectance data. In addition, the ALM identified and ranked the most relevant wavelengths for chlorophyll and pigment retrieval.     

The Effect of Temperature Adjustment on Reference Evapotranspiration and Reconnaissance Drought Index (RDI) in Iran

The reference evapotranspiration (ET₀) is necessary to calculate Reconnaissance Drought Index (RDI). To estimate ET₀, FAO56 Penman-Monteith method which needs reference stations data is commonly used. Most of the meteorological stations in Iran are classified as non-reference satations and The use of their data in ET₀ calculation can affect the RDI. The objective of the present study is to evaluate the effect of temperature adjustment based on the reference condition on ET₀ and RDI values in non-reference stations of Iran. For this purpose, the meteorological data, recorded during 1960–2014 in 27 non-reference stations located in arid and semi-arid regions, were used. First, the values of ET₀ were determined using observed values of temperature. Using these values, RDI were computed by Log-Normal and Gamma distributions at annual and 6-month scales. Then the values of minimum, maximum and dew point temperatures were adjusted on the basis of the reference condition. The values of ET₀ and consequently RDI were calculated using adjusted data. On the basis of obtained results, at annual and 6-month scales, using observed values of temperature instead of adjusted values in non-reference stations cause to overestimate the value of ET₀. Also, using observed data with no adjustment can change the drought class which was determined on the basis of RDI. According to these results, temperature adjustment based on reference condition can change the values of ET₀ and RDI which was calculated by using Log-Normal or Gamma distributions at annual and 6-month scales.     

A novel joint secret image sharing and robust steganography method using wavelet

In this paper a data hiding method is proposed based on the combination of a secret sharing technique and a novel steganography method using integer wavelet transform. In this method in encoding phase, first a secret image is shared into n shares, using a secret sharing technique. Then, the shares and Fletcher-16 checksum of shares are hidden into n cover images using proposed wavelet based steganography method. In decoding phase, t out of n stego images are required to recover the secret image. In this phase, first t shares and their checksums are extracted from t stego images. Then, by using the Lagrange interpolation the secret image is revealed from the t shares. The proposed method is stable against serious attacks, including RS and supervisory training steganalysis methods, it has the lowest detection rate under global feature extraction classifier examination compared to the state-of-the-art techniques. Experimental results on a set of benchmarks showed that this method outperforms conventional methods in offering a high secure and robust mechanism for joining secret image sharing and steganography.     

A dimensional description of the unconfined compressive strength of artificially cemented fine-grained soils

Abstract

This study aims at establishing a universal predictive model for the unconfined compressive strength (UCS) of artificially cemented fine-grained soils. Model development, its validation and calibration were carried out using a comprehensive database gathered from the research literature. The dimensional analysis concept was successfully extended to the soil–cement UCS problem, thereby leading to a practical dimensional model capable of simulating the UCS as a function of the blend’s index properties — that is, cement content, specific surface area, curing time, and the compaction state parameters (including water content and dry density). The predictive capability of the proposed model was examined and further validated using routine statistical tests, as well as conventional fit-measure indices which resulted in R²?>?0.95 and NRMSE < 5%. A sensitivity analysis was also carried out to quantify the relative impacts of cement content, curing time and soil plasticity on the UCS. The higher the soil plasticity, the higher the positive sensitivity to cement content, implying that soils of higher plasticity would require higher cement contents for stabilization. On the contrary, the higher the soil plasticity, the lower the positive sensitivity to curing time, indicating a more effective cement hydration in soils of lower plasticity. Finally, an explicit calibration procedure, involving a total of three UCS measurements for three recommended soil–cement mix designs, was proposed and validated, thus allowing for the proposed model to be implemented with confidence for predictive purposes, preliminary design assessments and/or soil–cement optimization studies.     

Designing a new standard structure for improving automatic processing of Persian handwritten bank cheques

Millions of handwritten bank cheques are processed manually every day in banks and other financial institutions all over the world. Substitution of manual cheque processing with automatic cheque reader system saves time and the cost of processing. In the recent years, systems such as A2iA have been made in order to automate processing of Latin cheques. Normally, these systems are based on the standard structures of cheques such as Check 21 in the USA or Check 006 in Canada. There are major problems in traditional (currently used) Persian bank cheques, which yield low accuracy and computational cost in their automatic processing. In this paper, in order to solve these problems, a novel structure for Persian handwritten bank cheques is presented. Importance and supremacy of this new structure for Persian handwritten bank cheques is shown by conducting several experiments on our created database of cheques based on the new structure. The created database includes 500 handwritten bank cheques based on the presented structure. Experimental results verify the usefulness and importance of the new structure in automatic processing of Persian handwritten bank cheques which provides a standard guideline for automatic processing of Persian handwritten bank cheques comparable to Check 21 or Check 006.