Journal of Electrical and Computer Engineering Innovations
Volume:11 Issue: 1, Winter-Spring 2023

Several service identification methods have been proposed to identify services using a business process-based strategy. However, these methods are still not accurate enough and adequately automated and thus need improvements. The present study addresses this gap by proposing a new semi-automated combinational method that applies process mining techniques and simultaneously considers different aspects of the business domain (e.g., goal and data). We argue that this method facilitates service identification more comprehensively and accurately and helps enhance organizational performance and lower cost structure. Our method includes three Phases. In the first phase, the system log is inspected, and the running business process is extracted using process mining techniques. After validating this model, we create a goal and data model in the next phase. In the third phase, we establish connections between the introduced models by defining some matrices. These connections are of two types: structural and conceptual. Finally, we propose a couple of algorithms that lead to the identification of services. We evaluate the utility of our proposed method by conducting a case study and using the experts’ opinions from different perspectives as follows: (1) assessing the accuracy and reusability of the identified services, (2) appraising the efficiency of employing this method in more complex processes, (3) calculating the cohesion to coupling ratio, and (4) assessing the performance of the method and other service quality measures. The results indicate that the average accuracy of this method is about 12 % higher than the previously identified methods for both simple and complex processes. Additionally, it empirically proves that using the process mining techniques improves the service identification considerably (8%). Moreover, according to the experts’ opinions, the combination of goal and data model and process mining has increased the performance by 8%. In comparison, the cohesion to coupling ratio demonstrated a 7% increase compared to other methods. In sum, we conclude that this method is an advanced and reliable way of service identification regardless of the process size and the complexity. The findings reveal that considering different aspects of business processes together and using process mining techniques improves the ratio of cohesion to coupling and accuracy of the identified services. Adherence to this approach enables companies to mine their business processes, modify them, and quickly identify services with higher performance. Besides, using this method provides a semi-automated and more effective way of service identification

IP multimedia subsystems (IMS) have been introduced as the Next Generation Network (NGN) platform while considering Session Initiation Protocol (SIP) as the signaling protocol. SIP lacks a proper overload mechanism. Hence, this challenge causes decline in the multimedia QoS. The main propose of overload control mechanism is to keep the network throughput at the same network capacity with overload. NGN distributed with IMS is a complex innovative network consisting of interacting subsystems. Hence, multi-agent systems (MAS) receiving further attention for solving complex problems can solve the problem of overload in these networks. To this end, each IMS server is considered as an intelligent agent that can learn and negotiate with other agents while maintaining autonomy, thus eliminating the overload by communication and knowledge transfer between the agents. In the present research, using MAS and their properties, the intelligent hop by hop method is provided based on Q-learning and negotiation capability for the first time. In the proposed method, parameters of overload controller are obtained by reinforcement learning. In order to check the validity of controller performance, a comparison is made with the similar method in which the optimal parameters are achieved based on trial and error. The result of the comparison confirms the validity of the proposed method. In order to evaluate the efficiency of the learner method, it is compared with similar and standard methods, for which the results are compared to show performance. The results show, the proposed method has approximately improved the throughput by 13%, the delay by 49% and the number of rejected sessions by 17% compare with methods, passing control messages through the network such as CPU occupancy methods. While compare with external controller methods like holonic, throughput is improved by 1% and the number of rejected requests is decreased by 10%, but delay is increased by 6% due to the convergence time of the learning and negotiation process. To overcome overload, complex IMS servers are considered as learner and negotiator agents. This is a new method to achieve the required parameters without relying on expert knowledge or person as well as, heterogeneous IMS entities can be inserted into the problem to complete study in future.

The Field-effect Bipolar Junction Transistor (FEBJT) is a device with a bipolar junction transistor (BJT) characteristics except that it is designed with standard CMOS technology. Therefore, it can be implemented in nanometer dimensions without the usual restrictions in fabricating the nanoscale BJTs. In addition to the advantages that FEBJT has as a bipolar junction transistor in analog circuits, it can also be used to design digital circuits. Here, we have investigated the capability of FEBJT as the base of a new digital family in nanometer scales. To do this, we have designed and simulated an inverter logic gate based on FEBJT. We have presented this logic gate's static and dynamic assessment criteria and compared these characteristics with other technologies. Also, a three-stage ring oscillator circuit based on FEBJT is designed and presented. A three-dimensional TCAD Mixed-Mode simulator has been used for the simulations. The value of maximum frequency, PDP, dynamic power, and ring frequency are calculated 0.25THz, 38×10-17 J, 94uW, and 85GHz, respectively. The excellent function of the FEBJT-based inverter gate and oscillator demonstrates that this device can be used as the base of new digital circuits and can open a doorway to the nanoscale CMOS digital family.

Residue number system (RNS) is considered as a prominent candidate for high-speed arithmetic applications due to its limited carry propagation, fault tolerance, and parallelism in “Addition”, “Subtraction”, and “Multiplication” operations. Whereas, “Comparison”, “Division”, “Scaling”, “Overflow Detection” and “Sign Detection” are considered as complicated operations in residue number systems, which have also received a surge of attention in a multitude of publications. Efficient realization of Comparators facilitates other hard-to-implement operations and extends the spectrum of RNS applications. Such comparators can substitute the straightforward method (i.e. converting the comparison operands to binary and comparing them with wide word binary comparators) to compare RNS numbers. Dynamic Range Partitioning (DRP) method has shown advantages for comparing unsigned RNS numbers in the 3-moduli sets {2^n,2^n±1} and {2^n,2^n-〖1,2〗^(n+1)-1}, in comparison with other methods. In this paper, we employed DRP components and designed a unified unit that detects the sign of operands and also compares numbers, for the 5-moduli set γ={2^2n,2^n±1,2^n±3}. This unit can be used for comparison of signed and also unsigned RNS numbers in the moduli set γ. Synthesized comparison results reveal 47% (54%) speed-up, 35% (32%) less area consumption, 25% (24%) lower power dissipation, and 60% (65%) less energy for n=8 (16) in comparison to the straightforward signed comparator. According to the results of this study, DRP method for sign detection and comparison operations outperforms other methods in different moduli sets including 5-moduli set γ={2^2n,2^n±1,2^n±3}.

Depth from defocus and defocus deblurring from a single image are two challenging problems caused by the finite depth of field in conventional cameras. Coded aperture imaging is a branch of computational imaging, which is used to overcome these two problems. Up to now, different methods have been proposed for improving the results of either defocus deblurring or depth estimation. In this paper, an asymmetric coded aperture is proposed which improves results of depth estimation and defocus deblurring from a single input image. To this aim, a multi-objective optimization function taking into consideration both deblurring results and depth discrimination ability is proposed. Since aperture throughput affects on image quality, our optimization function is defined based on illumination conditions and camera specifications which yields an optimized throughput aperture. Because the designed pattern is asymmetric, defocused objects on two sides of the focal plane can be distinguished. Depth estimation is performed using a new algorithm, which is based on perceptual image quality assessment criteria and can discern blurred objects lying in front or behind the focal plane. Extensive simulations as well as experiments on a variety of real scenes are conducted to compare the performance of our aperture with previously proposed ones. Our aperture has been designed for indoor illumination settings. However, the proposed method can be utilized for designing and evaluating appropriate aperture patterns for different imaging conditions.

The Hemispherical Resonator Gyroscope (HRG) is an inertial sensor that is a good choice for space missions and inertial navigation due to their low noise, low energy consumption, long life, and excellent accuracy and sensitivity. It consists of three main parts: the shell, the excitation and detection system, and the control circuits. In recent years, with using MEMS technology in the construction of HRG, vibrating shells with low volume and low price are made. The hemispherical shell is the main part and the beating heart of hemispherical resonator gyroscopes and is responsible for sensing. An optimized shell is required to implement the excitation and detection system and operate the gyroscope properly. In this research, the structure of a spherical shell with an environmental base that does not need to release the shell from its environment for its excitation and detection system is selected and the relationships governing this type of shell to improve the parameters of the glass blowing method will be investigated. Also, all sub-processes of this type method of fabrication to optimize the glass-blown spherical shell are implemented. The process of making spherical shell by glass blowing using the chemical foaming process is used to obtain shells with height to radius ratio greater than 1, and finally, a glass shell with an etched cavity with a radius of 562 μm and depth of 524 μm created by the CNC process, with height to radius ratio of approximately 1.8 Has been achieved. In this method, using direct transfer of calcium carbonate to the etched cavity, before anodic bonding, the glass shell volume has been increased from 0.602 nL to 1.04 nL. The result is that to achieve a glass shell with a height to radius ratio of more than 1, in addition to improving the fabrication process, it is necessary to transfer the solid foaming agent to the etched cavity. Finally, in the fabrication of the glass-blown spherical shell, we have used the chemical foaming process (CFP) to obtain shells with a height to radius ratio greater than 1.

This study aims to present a new structure based on coaxial waveguide, which can change the bandwidth, return losses, and input impedance by changing the plasma parameters of the coaxial waveguide. This structure consists of a metal body and a gas tube inside it, which uses a high voltage alternating current converter, can change the plasma parameters and, consequently the waveguide parameters. The input and output of the waveguide are also designed using the indirect capacitive coupling method. In the Field of plasma research and related emerging technologies, recently, it has achieved a special place in various industries such as radar and Aerospace industries. The creation of telecommunication structures such as antennas and Waveguides with plasma, has given features such as adaptability, the ability to reconfigure the characteristics of the structure, and improve the sensitivity of this type of structure. By applying and changing the plasma excitation parameters, a change in the bandwidth was observed in the frequency band range of 0.5-4 GHz and a maximum of 1.38 GHz. Also, increasing the intensity of the excitation current improved the return losses in the resonance frequencies and, on the other hand, increased the band ripple. According to the results, the change of Plasma parameters depends on the change of plasma excitation frequency, and the value of Excitation current applied. As the Value of excitation current increases, the matching to the resonance frequencies improves, but on the other hand, the passband ripple of the plasma waveguide filter increases. As the plasma excitation pulse frequency increases, the bandwidth and resonance frequencies change to higher frequencies, and the matching to the resonance frequencies improves. But on the other hand, the passband ripple increases. This new waveguide filter can be used in cognitive/ adaptive telecommunication systems due to the constant change of frequency band.

Big data is a combination of structured, semi-structured and unstructured data collected by organizations that must be stored and used for decision-making. Businesses that deal with the business intelligence system, as well as their data sources, have a major challenge in exploiting Big Data. The current architecture of business intelligence systems is not capable of incorporating and exploiting Big Data. In this paper, an architecture is developed to respond to this challenge. This paper focuses on the promotion of business intelligence to create an ability to exploit Big Data in business intelligence. In this regard, a new architecture is proposed to integrate both Business Intelligence and Big Data architectures. To evaluate the proposed architecture, we investigated business intelligence architecture and Big Data architecture. Then, we developed a Unified Modeling Language diagram for the proposed architecture. In addition, using the Colored Petri-Net, the proposed architecture is evaluated in a case study. The results show that our architectural system has a higher efficiency in performing all steps, average time, and maximum time compared to business intelligence architecture. The proposed architecture can help companies and organizations gain more value from their data sources and better support managers and organizations in their decision-making.

Cylindrical scanning technique is a well-established indirect measurement method to characterize a wide range of antenna patterns such as fan-beam antennas and phased array antennas with versatile radiation patterns. Cylindrical scanning technique which is based on the nearfield-to-far-field transformation based on cylindrical mode coefficients (CMCs), cannot predict the antenna radiation pattern with a very narrow beamwidth in the azimuth plane accurately, because a remarkable error occurs during the calculation of the derivative of high-order Hankel functions in the CMCs extraction. We aim to address this issue and introduce a simple yet rigorous technique namely the sequential sampling method (SSM) in conjunction with the two-dimensional Fast Fourier Transform (2D-FFT) to efficiently calculate the far-field radiation pattern of a super-directive antenna with a very narrow beamwidth in the azimuth plane. Briefly, the SSM offers several sequences of progressive azimuth angles and the corresponding order of Hankel functions in such a way that CMCs fully span 360 degrees of azimuth angles (φ) in the cylindrical coordinate system in each sequence. Afterward, by putting the far-field obtained by these sequences together, the final radiation pattern will have a high angular resolution. This technique can also be applied to determine the necessary criteria in the data acquisition step which should be satisfied to precisely measure the radiation pattern of super-directive antennas. These criteria are the maximum acceptable sampling resolution and the minimum value of the required azimuth angle (φ) in the data acquisition step if the far-field pattern is merely desired on the front side of the antenna. For verifications, the far-field radiation pattern of an electrically large slot array antenna including 81×15 slots is calculated at 8.75 GHz by the proposed technique and the results are compared with the array theory. The results show that the azimuth pattern can accurately be measured as small as 0.1° resolution by the SSM. By comparing the results obtained by the proposed method and the traditional cylindrical scanning method, it can be inferred that the far-field pattern of an antenna with narrow beamwidth in the azimuth plane can easily be characterized by a cylindrical scanning system without any huge computational burden

In general, traditional salt farmers determine the time to harvest salt by visiting and monitoring their salt ponds. Therefore, to assist salt farmers in determining the right time to harvest salt and determine the quality of the harvested salt, a wireless-based electronic device is needed that can monitor the salt content and viscosity of the brine. An electronic device that is made to measure salt content (salinity) with a conductivity sensor and to measure fluid viscosity using a data processing method from sensor readings which is first converted to digital data with a program on the microcontroller. To find out whether the brine is ready to be harvested or not, the data obtained in the form of conductivity and stress are converted into percentages of NaCl and degrees of Baume. Then the data is sent to the ESP8266 wifi module to be stored in a database and displayed on the Web. The results of the data obtained are based on testing in salt ponds for young water but it has been quite a long time the results have approached old water of around 64% and 14o Be. The results of the old water test that had just been moved to the last reservoir were close to harvest time of around 94% and 21o Be. If it has reached 25o Be then it is enough to be moved to the crystallization site. To determine the harvest period based on two parameters, namely the salt content and the viscosity of the liquid is 86-90% and the viscosity of the liquid is 20-24o Be. If you have reached both of these parameters, the salt can be harvested in about 7-10 days to make the water crystallize. Equipment Indicators for determining salt harvest time based on salinity and liquid viscosity using a microcontroller that has been made have been successfully used to determine salt harvest time properly. The salt quality of this indicator tool is the salt content including the K-3 quality or the lowest quality of the 3 existing qualities.

This paper proposes a new Model Order ‎Reduction (MOR) method based on the Bilinear Balanced Truncation ‎‎(BBT) approach. In the BBT method, solving the generalized Lyapunov ‎equations is necessary to determine the bilinear system's controllability ‎and observability Gramians. Since the bilinear systems are generally of ‎high order, the computation of the Gramians of controllability and ‎observability have huge computational volumes. In addition, the accuracy ‎of reduced-order model obtained by BT is relatively low. In fact, the ‎balanced truncation method is only available for local energy bands due ‎to the use of type I Gramians. In this paper, BBT based on type II ‎controllability and observability Gramians would be considered to fix ‎these drawbacks.‎ At first, a new iterative method is proposed for determining ‎the proper order for the reduced-order bilinear model, which is related to ‎the number of Hankel singular values of the bilinear system whose real ‎parts are closest to origin and have the most significant amount of ‎energy. Then, the problem of determining of type II controllability and ‎observability Gramians of the high-order bilinear system have been ‎formulated as a constrained optimization problem with some Linear ‎Matrix Inequality (LMI) constraints for an intermediate middle-order ‎system. Then, the achieved Gramians are applied to the BBT method to ‎determine the reduced-order model of the bilinear system. Next, the ‎steady state accuracy of the reduced model would be improved via ‎employing a tuning factor.‎ Using the concept of type II Gramians and via the proposed ‎method, the accuracy of the proposed bilinear BT method is increased. ‎For validation of the proposed method, three high-order bilinear models ‎are approximated. The achieved results are compared with some well-‎known MOR approaches such as bilinear BT, bilinear Proper Orthogonal ‎Decomposition (POD) and Bilinear Iterative Rational Krylov subspace ‎Algorithm (BIRKA) methods.‎ According to the obtained results, the proposed MOR ‎method is superior to classical bilinear MOR methods, but is almost ‎equivalent to BIRKA. It is out-performance respecting to BIRKA is its ‎guaranteed stability and convergence. ‎

Intelligent receivers, automatically detect the digital modulation type of the received signals for demodulation purposes where is well known as Automatic Modulation Classification (AMC) module. The performance of AMC algorithms depends on the channel conditions where for example, in fading channel its performance gets worse than the AWGN channel. We propose a new algorithm for improving the AMC classification accuracy in flat fading channels. The proposed algorithm consists of an optimizable nonlinear preprocess followed by Linear Discriminant Analysis (LDA) technique. Two Lemmas have been found for extracting the optimization rule. And an optimization algorithm has been built based on the previous Lemmas. The simulation results show that the proposed algorithm improves the classification accuracy between 8-Phase Shift Keying (8PSK) and 16PSK (as an example of M-array PSK (MPSK) inter-class) for Signal-to-noise ratio (SNR) values greater than 13 dB, and between 16- quadrature amplitude shift modulation (16QAM) and 64QAM (as an example of M-array QAM (MQAM) inter-class) for SNR values greater than 4 dB. By using the proposed optimization algorithm, the AMC classification accuracy has been improved. Other classification problems can use this algorithm. And other nonlinear preprocess functions or optimization algorithms may be found in future work.

The speed sensor is one of the main components of the control and monitoring systems of rotational machines which is widely used in the aviation industry, railway, and automotive applications. Variable Reluctance Speed sensor (VRS) is a kind of magnetic sensor that has been traditionally employed for many different industrial measurements because of several well-known advantages, such as passive nature, non-contact operations, robustness, low cost, low sensitivity to dirt, and large-signal output. In this paper, a variable reluctance speed sensor is proposed. The design process of the proposed sensor is presented and both the magnetic and electrical models of this sensor are derived by assuming the effect of magnetomotive force caused by eddy current formed on the outer edge of the target gear at high frequencies. As a result, the proposed model can demonstrate the performance of the variable reluctance speed sensor at high frequencies very well. The proposed VRS is designed and simulated using MATLAB and Ansys Maxwell software to verify the theoretical results is constructed and tested. In this paper, a variable reluctance speed sensor is proposed and studied. The magnetic and electrical models of the proposed sensor are derived and the output voltage equation has been calculated as a function of the air gap length. The proposed VR sensor is simulated using 2D Finite Element Analysis software to identify the main parameters that influence the sensor output and also to verify the accuracy of the model. According to the simulation results, the output waveform quality will be affected by parameters such as air gap length, target gear material, the self-inductance of the VR sensor, and the load component values. In terms of the electrical model, we were able to simulate the effect of load resistance and capacitance on the sensor output.

Non-orthogonal multiple access (NOMA) is a promising solution to meet a high data rate demand in the new generation of cellular networks. Moreover, simultaneous wireless information and power transfer (SWIPT) was introduced to enhance the performance in terms of energy efficiency. In this paper, a single-cell cooperative NOMA system with energy harvesting full-duplex (FD) relaying is proposed to improve the sum rate and energy efficiency. A downlink model consisting of a base station (BS), two cell-center users (nearly located users), and two cell-edge users (far located users) are considered. In each signalling interval, the BS transmits a superposition signal of cell-center and cell-edge users based on the power domain (PD) NOMA strategy. Employing a relay selection criterion, a cell-center user is paired with a cell-edge user and acts as an FD decode and forward (DF) relay to improve the cell-edge user performance. An energy harvesting (EH) model is considered where a power splitting (PS) protocol is adopted at the relay node. The other cell-center user saves the harvested energy from the BS to exploit in the subsequent signalling intervals. Two problems of power allocation for sum rate and energy efficiency maximization in constraints of the minimum required data rate for each user and maximum transmit power at the BS are formulated for the proposed scheme. Due to the non-convexity, the optimization problems are transformed and approximated to the convex optimization problems and solved by iterative algorithms. Difference of convex (DC) programming is employed for solving the sum rate maximization problem where an effective combination of DC programming, bisection method, and Dinkelbach algorithm is utilized for dealing with the energy efficiency maximization problem. The sum rate and energy efficiency over maximum available power at the BS are presented. Also, the effects of the power splitting factor and the cell radius on the sum rate and energy efficiency are investigated. Moreover, a comparison with the OMA and NOMA schemes is studied for the different minimum required data rates. Simulation results validate that the proposed scheme outperforms the OMA and NOMA schemes in terms of sum rate in all SNR regimes. Moreover, the energy efficiency of the proposed scheme achieves considerably better performance than OMA for all SNR values and obtains remarkable better performance than NOMA in most SNR values.

 Object detection has been a fundamental issue in computer vision. Research findings indicate that object detection aided by convolutional neural networks (CNNs)‌ is still in its infancy despite -having outpaced other methods.

 This study proposes a straightforward, easily implementable, and high-precision object detection method that can detect objects ‌‌‌with minimum least error. ‌Object detectors generally fall into one-stage ‌‌and two-stage‌ detectors‌. Unlike one-stage detectors, two-stage detectors ‌are often more precise, despite performing at a lower speed. In this study, a one-stage‌ detector is proposed, and the results indicated its sufficient precision. The proposed method uses a feature pyramid network ‌(FPN) to detect objects on multiple scales. This network is combined with the ResNet 50 deep neural network.

 The proposed method is trained and tested on ‌Pascal VOC 2007 and COCO datasets. It yields a mean average precision (mAP) of 41.91 in Pascal Voc2007 and 60.07% in MS COCO. The proposed method is tested under additive noise. The test images of the datasets are combined with the salt and pepper noise to obtain the value of mAP for different noise levels up to 50% for Pascal VOC and MS COCO datasets. The investigations show that the proposed method provides acceptable results.

 It can be concluded that using deep learning algorithms and CNNs and combining them with a feature network can significantly enhance object detection precision.

The displacement of molecules is one of the major fabrication faults in manufacturing molecular electronic devices. In this paper, we profoundly study the effect of displacement on the current-voltage, and conductance-voltage characteristics of the Au-Benzenedithiol-Au single-molecule device. The ab-initio calculations on the isolated molecules were performed to obtain the basic single-level quantum-dot model parameters. These parameters were then used within the self-consistent field algorithm to calculate the electrical characteristics of the device. The maximum conductance occurs when the molecule is placed exactly in the midpoint of the distance between the two electrodes, where the electrostatic capacitance reaches its minimum. When the molecule deviates from this point, and approaches one electrode, the conductance is decreased, and asymmetric behavior emerges. A molecular rectifier can be manufactured by placing the molecule close to one electrode. Although modern software packages may employ advanced and complicated models including the combination of the density functional theory (DFT) and non-equilibrium Green’s function (NEGF) methods to obtain accurate results, they are demanding in computer memory and time. Moreover, understanding the physical quantities of the systems from large-scale matrices is often difficult. The single-level model is a computationally light method, which provides a profound understanding of the device characteristics since all quantities are presented by numbers.

This paper introduces a novel low-power and low-delay multi-digit ternary adder in carbon nanotube field effect transistor (CNTFET) technology. In the proposed design, reducing the power consumption is the main priority. In this multi valued logic design, geometry-dependent threshold voltage of the CNTFET is the design code. At each stage, a half adder is applied to generate the intermediate binary signals called half-sum (HS) and half-carry (HC). For the binary operations, the gate diffusion input (GDI) method is used to significantly reduce the power consumption as in the proposed decoder design. In this work a GDI based sum generator and a low-power encoder are used to calculate the final sum value of each stage. Furthermore, the proposed carry generation/propagation block results in a significant reduction in the overall propagation delay time. The simulation reveals a significant improvement in terms of power consumption (up to 27%), PDP (up to 41%) and FO4 delay (up to 20%). A CNTFET based power and delay efficient multi-digit ternary adder has been presented in this paper. The simulation is performed by the Synopsis HSPICE simulator with Stanford 32 nm CNTFET technology. According to the results, a significant saving in average power consumption is achieved where the power-delay product (PDP) is improved by 41% compared to the best existing design.

Development of intermittent wind generation has necessitated the inclusion of several creative approaches in modeling the deregulated power market with presence of wind sources. The uncertain nature of wind resources will cause the private companies meet several risk in their medium and long term planning in a restructured power market. In addition to considering the uncertainties such as load, fuel costs, wind power generation and technical actions of rivals for modeling the restructured power market, the regulatory policies i.e incentive policy for wind resources and Carbon tax should be assumed in this approach. The first contribution of this article is to propose a developed mathematical model in order to evaluate the medium term deregulated power market by assuming the hybrid wind-thermal power plants. The second contribution is to evaluate the impact of different types of Feed in Tariff supports on Market Clearing Price, Expected Cost for Government, profits and contribution of each firm in electricity generation in the restructured power market. Also the scenario based method has been used to generate the scenarios for wind uncertainties and then their reliability validate based on the statistical methods. The proposed mathematical model in the first contribution is calculated for each season and load levels based on the proposed wind scenarios. The functionality and feasibility of this model is demonstrated by simulation studies. The proposed model in this article can be so useful for evaluating the different types of incentive policies for renewable energies. Moreover, this study confirms the previous researches that selected the Feed in Tariff as an efficient approach for developing the wind resources.

In this paper, a novel structure as a Folded-Mirror (FM) Trans-impedance Amplifier (TIA) is designed and introduced for the first time based on the combination of the current-mirror and the folded-cascade topologies. The trans-impedance amplifier stage is the most critical building block in a receiver system. This novel proposed topology is based on the combination of the current mirror topology and the folded-cascade topology, which is designed using active elements. The idea is to use a current mirror topology at the input node. In the proposed circuit, unlike many other reported designs, the signal current (and not the voltage) is being amplified till it reaches the output node. The proposed TIA benefits from a low input resistance, due to the use of a diode-connected transistor, as part of the current mirror topology, which helps to isolate the dominant input capacitance. So, as a result, the data rate of 5Gbps is obtained by consuming considerably low power. Also, the designed circuit employs only six active elements, which yields a small occupied chip area, while providing 40.6dBΩ of trans-impedance gain, 3.55GHz frequency bandwidth, and 664nArms input-referred noise by consuming only 315µW power using a 1V supply. Results justify the proper performance of the proposed circuit structure as a low-power TIA stage. The proposed topology is based on the combination of the current mirror topology and the folded-cascade topology. The circuit performance of the proposed folded-mirror TIA is simulated using 90nm CMOS technology parameters in the Hspice software. Furthermore, the Monte-Carlo analysis over the size of widths and lengths of the transistors is performed for 200runs, to analyze the fabrication process. The proposed FM TIA circuit provides 40.6dBΩ trans-impedance gain and 3.55GHz frequency bandwidth, while, consuming only 315µW power using a 1V supply. Besides, as analyzing the quality of the output signal in the receiver circuits for communication applications is vital, the eye-diagram of the proposed FM TIA for a 50µA input signal is opened about 5mV, while, for a 100µA input signal the eye is opened vertically about 10mV. So, the vertical and horizontal opening of the eye is clearly shown. Furthermore, Monte-Carlo analysis over the trans-impedance gain represents a normal distribution with the mean value of 40.6dBΩ and standard deviation of 0.4dBΩ. Also, the value of the input resistance of the FM TIA is equal to 84.4Ω at low frequencies and reaches the value of 75Ω at -3dB frequency. The analysis of the effect of the feedback network on the value of the input resistance demonstrates the input resistance in the absence of the feedback network reaches up to 1.4MΩ, which yields the importance of the existence of the feedback network to obtain a broadband system. In this paper, a trans-impedance amplifier based on a combination of the current-mirror topology and the folded-cascade topology is presented, which amplifies the current signal and converts it to the voltage at the output node. Due to the existence of a diode-connected transistor at the input node, the input resistance of the TIA is comparatively small. Furthermore, four out of six transistors are PMOS transistors, which represent less thermal noise in comparison with NMOS transistors. Also, the proposed Folded-Mirror topology occupies a relatively small area on-chip, due to the fact that no passive element is used in the feedforward network. Results using 90nm CMOS technology parameters show 40.6dBΩ trans-impedance gain, 3.55GHz frequency bandwidth, 664nArms input-referred noise, and only 315µW power dissipation using a 1volt supply, which indicates the proper performance of the proposed circuit as a low-power building block.

In this paper, a novel linear parameter varying (LPV) model of a wind turbine is developed based on a benchmark model presented by Aalborg University and KK-electronic a/c. The observability and validity of the model are investigated using real aerodynamic data. In addition, a robust fault detection and reconstruction method for linear parameter varying systems using second-order sliding mode observer is developed and implemented on the linear parameter varying model. The fault signal is reconstructed using a nonlinear term named equivalent output error injection during sliding motion and a proper transformation. The effect of uncertainties and incorrect measurements are minimized by employing an oriented method that requires solving a nonlinear matrix inequality. During numerical simulations, an actuator fault in the pitch system is considered and the performance of the method in fault reconstruction is investigated. Wind speed range is considered from 14 m/s to 16  and it is regarded as a stochastic input exerting aerodynamic torque. Fast and accurate fault reconstruction happens in 0.6 seconds with less than one percent error. The observer performance is not affected by the fault and fault is estimated in 2.5 seconds with an error smaller than 2.48 percent. Results illustrate fast and accurate fault reconstruction and accurate state estimations in the presence of actuator fault.