Adaptive beamforming algorithm with increased speed and improved reliability for smart antennas

In this paper, a novel adaptive beamforming algorithm has been proposed which can be used for tracking the subscribers of a smart antenna in a wide angle spread environment. It can be adapted for arbitrary variations in both eigenvalues and eigenvectors of the autocorrelation matrix of received signal which is mostly the case for moving subscribers’ environment. Moreover, it uses one adaptive module which is less than two adaptive modules of previous works and leads to a high speed at least two times more than previous works.     

Performance analysis of secure communications over correlated slow‐fading additive white Gaussian noise channels

The broadcast nature of communications in wireless communication networks makes it vulnerable to some attacks, particularly eavesdrop attack. Hence, information security can have a key role to protect privacy and avoid identity theft in these networks, especially in distributed networks. In the wireless systems, the signal propagation is affected by path loss, slow fading (shadowing), and fast fading (multi‐path fading). As we know, there is a correlation between communication channels in the real radio environments. This correlation is defined by the correlation between their shadowing and/or multipath fading factors. So when there are several channels in the wireless systems, there is certainly a correlation between the channels. In this paper, we assume that the transmitter knows the full channel state information (CSI), it means the transmitter knows both the channel gains of the illegitimate (ie, eavesdropper) and the legitimate receivers and study the performance of secure communications of single‐input single‐output (SISO) systems consisting of single antenna devices, in the presence of a single antenna passive eavesdropper over correlated slow fading channels, where the main (transmitter to legitimate receiver) and eavesdropper (transmitter to illegitimate receiver) channels are correlated. Finally, we present numerical results and verify the accuracy of our analysis by Monte‐Carlo simulations.     

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.

     

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.     

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.     

A lightweight anonymous two‐factor authentication protocol for wireless sensor networks in Internet of Vehicles

Internet of Vehicles (IoV), as the next generation of transportation systems, tries to make highway and public transportation more secure than used to be. In this system, users use public channels for their communication so they can be the victims of passive or active attacks. Therefore, a secure authentication protocol is essential for IoV; consequently, many protocols are presented to provide secure authentication for IoV. In 2018, Yu et al proposed a secure authentication protocol for WSNs in vehicular communications and claimed that their protocol could satisfy all crucial security features of a secure authentication protocol. Unfortunately, we found that their protocol is susceptible to sensor capture attack, user traceability attack, user impersonation attack, and offline sink node's secret key guessing attack. In this paper, we propose a new authentication protocol for IoV which can solve the weaknesses of Yu et al's protocol. Our protocol not only provides anonymous user registration phase and revocation smart card phase but also uses the biometric template in place of the password. We use both Burrow‐Abadi‐Needham (BAN) logic and real‐or‐random (ROR) model to present the formal analysis of our protocol. Finally, we compare our protocol with other existing related protocols in terms of security features and computation overhead. The results prove that our protocol can provide more security features and it is usable for IoV system.     

Dielectrophoresis-based microfluidic platform to sort micro-particles in continuous flow

Non-invasive separation of particles with different sizes and sensitivities has been a challenge and interest for point-of-care diagnostics and personalized treatment. Dielectrophoresis is widely known as a powerful technique to sort the particles and (most importantly to) distinguish cells and monitor their state without the need for biochemical tags. In this paper, a dielectrophoresis-based microchannel design is proposed which allows for continuous particle sorting and separation under the applied AC field. It is also practical to implement the platform for monitoring cell behavior irregularities caused by certain diseases toward diagnosis and treatment. In this regard, the device employs dielectrophoretic (DEP) force exerted on the particles by only two electrodes with oblique arrangement in the channel. The electrodes are arranged with a bevel angle to the fluid flow direction but they are not parallel and therefore a gradually decreasing electric field is achieved along the channel’s width. As a result, the dielectrophoretic force, acting on the particles of different sizes, would also gradually decrease along channels width which renders the necessary distinguishing lateral displacements of particles for separation. Therefore, the particles with different sizes can be sorted in a continuous-flow regime and be received at multiple outlet reservoirs with no need to turn the electric field on/off. The presented device is fabricated and evaluated in the experiment to prove its feasibility. Afterward, using numerical simulations, we investigate the optimum design parameters in the presented device to enhance device efficiency for separating particles with different size ranges.