Showing 106 results for Ica
S. Mirzakuchaki, A. Heidari,
Volume 15, Issue 2 (6-2019)
Abstract
With the advent and development of the Internet of Things, new needs arose and more attention was paid to these needs. These needs include: low power consumption, low area consumption, low supply voltage, higher security and so on. Many solutions have been proposed to improve each one of these needs. In this paper, we try to reduce the power consumption and enhance the security by using SPGAL, a DPA-resistant Logic, and Carbon Nanotube FETs (CNTFETs) instead of conventional CMOS and MOSFET technology, for IoT devices. All simulations are done with HSPICE.
S. Mavaddati,
Volume 15, Issue 3 (9-2019)
Abstract
Blind voice separation refers to retrieve a set of independent sources combined by an unknown destructive system. The proposed separation procedure is based on processing of the observed sources without having any information about the combinational model or statistics of the source signals. Also, the number of combined sources is usually predefined and it is difficult to estimate based on the combined sources. In this paper, a new algorithm is introduced to resolve these issues using empirical mode decomposition technique as a pre-processing step. The proposed method can determine precisely the number of mixed voice signals based on the energy and kurtosis criteria of the captured intrinsic mode functions. Also, the separation procedure employs a grey wolf optimization algorithm with a new cost function in the optimization procedure. The experimental results show that the proposed separation algorithm performs prominently better than the earlier methods in this context. Moreover, the simulation results in the presence of white noise emphasize the proper performance of the presented method and the prominent role of the presented cost function especially when the number of sources is high.
N. Mansouri, M. M. Javidi,
Volume 15, Issue 3 (9-2019)
Abstract
As grow as the data-intensive applications in cloud computing day after day, data popularity in this environment becomes critical and important. Hence to improve data availability and efficient accesses to popular data, replication algorithms are now widely used in distributed systems. However, most of them only replicate the static number of replicas on some requested chosen sites and it is obviously not enough for more reasonable performance. In addition, the failure of request is one of the most common issue within the data centers. To compensate these problems, we, propose a new data replication strategy to provide cost-effective availability, minimize the response time of applications and make load balancing for cloud storage. The proposed replication strategy has three different steps which are the identification of data file to replicate, placing new replicas, and replacing replicas. In the first step, it finds the most requested files for replication. In the second step, it selects the best site by consideration of the frequency of requests for replica, the last time the replica was requested, failure probability, centrality factor and storage usage) for storing new replica to reduce access time. In the third step, the replacement decision is made in order to provide better resource usage. The proposed strategy can ascertain the importance of valuable replicas based on the number of accesses in future, the availability of the file, the last time the replica was requested, and size of replica. Our proposed algorithm evaluated by CloudSim simulator and results confirmed the better performance of hybrid replication strategy in terms of mean response time, effective network usages, replication frequency, degree of imbalance, and number of communications.As grow as the data-intensive applications in cloud computing day after day, data popularity in this environment becomes critical and important. Hence to improve data availability and efficient accesses to popular data, replication algorithms are now widely used in distributed systems. However, most of them only replicate the static number of replicas on some requested chosen sites and it is obviously not enough for more reasonable performance. In addition, the failure of request is one of the most common issue within the data centers. To compensate these problems, we, propose a new data replication strategy to provide cost-effective availability, minimize the response time of applications and make load balancing for cloud storage. The proposed replication strategy has three different steps which are the identification of data file to replicate, placing new replicas, and replacing replicas. In the first step, it finds the most requested files for replication. In the second step, it selects the best site by consideration of the frequency of requests for replica, the last time the replica was requested, failure probability, centrality factor and storage usage) for storing new replica to reduce access time. In the third step, the replacement decision is made in order to provide better resource usage. The proposed strategy can ascertain the importance of valuable replicas based on the number of accesses in future, the availability of the file, the last time the replica was requested, and size of replica. Our proposed algorithm evaluated by CloudSim simulator and results confirmed the better performance of hybrid replication strategy in terms of mean response time, effective network usages, replication frequency, degree of imbalance, and number of communications.
M. Ghayeni,
Volume 15, Issue 4 (12-2019)
Abstract
In this paper, the new approach for the transmission reliability cost allocation (TRCA) problem is proposed. In the conventional TRCA problem, for calculating the contribution of each user (generators & loads or contracts) in the reliability margin of each transmission line, the outage analysis is performed for all system contingencies. It is obvious that this analysis is very time-consuming for large power systems. This paper suggests that this calculation should be done only for major contingencies. To do this, at first, the contingency filtering technique (CFT) is introduced based on the new economic indices that quantify the severity of each contingency to determine the critical contingencies. Then the results of contingency filtering are used in the TRCA problem. The simulation results are reported for the IEEE 118-bus test system. The obtained results show that by application of CFT in TRCA problem, the simulation time is greatly reduced, but the percentage of error remains within an acceptable limit.
A. P. Hutomo, I. P. Buditomo, A. P. Putra, S. Suhariningsih, S. D. Astuti,
Volume 15, Issue 4 (12-2019)
Abstract
The Functional Electrical Stimulator design using monophasic spike-exponential waveform was proposed and described in this study. The monophasic square waveform has benefit in generating an action potential, but it could cause side effects such as toxic caused by the electrode polarization. The square waveform signal which the frequency and pulse width could be modulated was manipulated to be the monophasic spike-exponential waveform. Transformer OT240 was applied at the end of the FES system part and functioned as a voltage amplifier and DC signal isolator. On every frequency range between 5–100 Hz, the 16 peak voltage stages with the lower limit of 45 Volt and an upper limit of 400 Volt was arranged to obtain VRMS value in each stage. Characterization result shows that the produced waveform was monophasic spike-exponential with the narrow pulse width (t1/2 = 7 µs) and VRMS in the maximum frequency and peak voltage was 8.99 Volt. This study showed that the designed FES had high VP and low VRMS, thus, it could be concluded that this FES system design could be a candidate for its application.
S. Juneja, R. Sharma,
Volume 15, Issue 4 (12-2019)
Abstract
Design of Global Positioning System (GPS) receiver with a low noise amplifier (LNA) in the front end remains a major design requirement for the success of modern day navigation and communication system. Any LNA is expected to meet the requirements like its ability to add the least amount of noise while providing sufficient gain, perfect input and output matching, and high linearity. However, most of the reported designs of LNAs present the need for striking a trade-off between these design parameters in order to obtain the desired performance for a particular RF receiver. This paper presents high gain (21dB), high input matched (-29dB), high reverse isolation (-41dB) and low noise figure (< 2dB) narrowband LNA for extremely low power level GPS L1 band signals broadcasting at 1.57GHz with a channel bandwidth of 10MHz. Inductive source degeneration topology is employed for the design and all the matching inductors in the circuit are used with fixed quality factor (Q) to model the losses for better tuning and matching. The design is carried out on Cadence Virtuoso Tool version IC6.1.6 and Spectre version MMSIM13.1 at 0.18µm technology node using a generic process development kit. Detailed mathematical analysis of the design is done and all the DC parameters like values of transconductance, gate source capacitance, drain source voltage, drain current, etc. are reported. Graphical analysis using Smith chart is carried out to present the results and to bring forth the trade-offs involved in the design. LNA draws 5mA current from 1.2V supply voltage and offers good linearity that is sufficient for GPS application and is measured by input intercept point 3 (IIP3 < ‑4dBm).
A. Jabbari, F. Dubas,
Volume 16, Issue 1 (3-2020)
Abstract
In this research work, an improved two-dimensional semi-analytical subdomain based method for performance computation in IPM machine considering infinite-/finite-magnetic material permeability in pseudo-Cartesian coordinates by using hyperbolic functions has been presented. In the developed technique, all subdomains are divided into periodic or non-periodic regions with homogeneous or non-homogeneous boundary conditions (BCs), respectively. Taking into account the appropriate interfaces conditions in the presented coordinates system, the machine performances including magnetic flux density, cogging/electromagnetic torque, back-EMF, and self-/mutual induction have been calculated for three distinct values of soft-magnetic material relative permeability (viz, 200, 800 and ∞). The semi-analytical results are compared and confirmed by the FEA results.
M. H. Refan, A. Dameshghi,
Volume 16, Issue 2 (6-2020)
Abstract
Geometric Dilution of Precision (GDOP) is a coefficient for constellations of Global Positioning System (GPS) satellites. These satellites are organized geometrically. Traditionally, GPS GDOP computation is based on the inversion matrix with complicated measurement equations. A new strategy for calculation of GPS GDOP is construction of time series problem; it employs machine learning and artificial intelligence methods for problem-solving. In this paper, the Time Delay Neural Network (TDNN) is introduced to the GPS satellite DOP classification. The TDNN has a memory for archiving past event that is critical in GDOP approximation. The TDNN approach is evaluated all subsets of satellites with the less computational burden. Therefore, the use of the inverse matrix method is not required. The proposed approach is conducted for approximation or classification of the GDOP. The experiments show that the approximate total RMS error of TDNN is less than 0.00022 and total performance of satellite classification is 99.48%.
M. Mozaffari Legha, E. Farjah,
Volume 16, Issue 2 (6-2020)
Abstract
This paper aims to establish an Arduino and IoT-based Hierarchical Multi-Agent System (HMAS) for management of loads’ side with incentive approach in a micro-grid. In this study, the performance of the proposed algorithm in a micro-grid has been verified. The micro-grid contains a battery energy storage system (BESS) and different types of loads known as residential consumer (RC), commercial consumer (CC), and industrial consumer (IC). The user interface on a smartphone directly communicates with the load management system via an integrated Ethernet Shield server which uses Wi-Fi communication protocol. Also, the communication between the Ethernet Shield and the Arduino microcontroller is based on Wi-Fi communication. A simulation model is developed in Java Agent Development Environment (JADE) for dynamic and effective energy administration, which takes an informed decision and chooses the most feasible action to stabilize, sustain, and enhance the micro-grid. Further, the environment variable is sensed through the Arduino microcontroller and sensors, and then given to the MAS agents in the IoT environment. The test results indicated that the system was able to effectively control and regulate the energy in the micro-grid.
M. Dodangeh, N. Ghaffarzadeh,
Volume 16, Issue 2 (6-2020)
Abstract
In this paper, a new fast and accurate method for fault detection, location, and classification on multi-terminal DC (MTDC) distribution networks connected to renewable energy and energy storages presented. MTDC networks develop due to some issues such as DC resources and loads expanding, and try to the power quality increasing. It is important to recognize the fault type and location in order to continue service and prevent further damages. In this method, a circuit kit is connected to the network. Fault detection is performed with the measurement of the current of the connected kits and the traveling-waves of the derivative of the fault current and applying to a mathematical morphology filter, in the Fault time. The type and location of faults determinate using circuit equations and current calculations. DC series and ground arc faults are considered as DC distribution network disturbances. The presented method was tested in an MTDC network with many faults. The results illustrate the validity of the proposed method. The main advantages of the proposed fault location and classification strategy are higher accuracy and speed than conventional approaches. This method robustly operates to changing in sampling frequency, fault resistance, and works very well in high impedance fault.
M. Sedighizadeh, S. M. M. Alavi, A. Mohammadpour,
Volume 16, Issue 3 (9-2020)
Abstract
Regarding the advances in technology and anxieties around high and growing prices of fossil fuels, government incentives increase to produce cleaner and sustainable energy through distributed generations. This makes trends in the using microgrids which consist of electric demands and different distributed generations and energy storage systems. The optimum operation of microgrids with considering demand-side management increases efficiency and reliability and maximize the advantages of using distributed generations. In this paper, the optimal operation scheduling and unit commitment of generation units installed in a microgrid are investigated. The microgrid consists of technologies based on natural gas that are microturbine and phosphoric acid fuel cell and technologies based on renewable energy, including wind turbine and photovoltaic unit along with battery energy storage system and plug-in electric vehicle commercial parking lot. The goal of the paper is to solve a multi-objective problem of maximizing revenues of microgrid operator and minimizing emissions. This paper uses an augmented epsilon constraint method for solving the multi-objective problem in a stochastic framework and also implements a fuzzy-based decision-maker for choosing the suitable optimal solution amid Pareto front solutions. This new model implements the three type of the price-based and incentive-based demand response program. It also considers the generation reserve in order to enhance the flexibility of operations. The presented model is tested on a microgrid and the results demonstrate the efficacy of the proposed model economically and environmentally compared to other methods.
Z. Kazemi, A. A. Safavi,
Volume 16, Issue 3 (9-2020)
Abstract
Kalman filtering has been widely considered for dynamic state estimation in smart grids. Despite its unique merits, the Kalman Filter (KF)-based dynamic state estimation can be undesirably influenced by cyber adversarial attacks that can potentially be launched against the communication links in the Cyber-Physical System (CPS). To enhance the security of KF-based state estimation, in this paper, the basic KF-based method is enhanced by incorporating the dynamics of the attack vector into the system state-space model using an observer-based preprocessing stage. The proposed technique not only immunizes the state estimation against cyber-attacks but also effectively handles the issues relevant to the modeling uncertainties and measurement noises/errors. The effectiveness of the proposed approach is demonstrated by detailed mathematical analysis and testing it on two well-known IEEE cyber-physical test systems.
Z. Rafiee, M. Rafiee, M. R. Aghamohammadi,
Volume 16, Issue 3 (9-2020)
Abstract
Improving transient voltage stability is one of the most important issues that must be provided by doubly fed induction generator (DFIG)-based wind farms (WFs) according to the grid code requirement. This paper proposes adjusted DC-link chopper based passive voltage compensator and modified transient voltage controller (MTVC) based active voltage compensator for improving transient voltage stability. MTVC is a controller-based approach, in which by following a voltage dip (VD) condition, the voltage stability for the WF can be improved. In this approach, a voltage dip index (VDI) is proposed to activate/deactivate the control strategy, in which, two threshold values are used. In the active mode, the active and reactive power are changed to decrease the rotor current and boost the PCC voltage, respectively. Based on the control strategy, in a faulty grid, DFIG not only will be able to smooth DC-link voltage fluctuations and reduces rotor overcurrents but also it will increase the voltage of point of common coupling (PCC). Therefore, it improves transient voltage stability. The simulation results show the effectiveness of the proposed strategy for improving voltage stability in the DFIG.
S. Shadpey, M. Sarlak,
Volume 16, Issue 4 (12-2020)
Abstract
This paper presents a pattern recognition-based scheme for detection of islanding conditions in synchronous- based distributed generation (DG) systems. The main idea behind the proposed scheme is the use of spatial features of system parameters such as the frequency, magnitude of positive sequence voltage, etc. In this study, the system parameters sampled at the point of common coupling (PCC) were analyzed using reduced-noise morphological gradient (RNMG) tool, first. Then, the spatial features of the RNMG magnitudes were calculated. Next, to optimize and increase the ability of the proposed scheme for islanding detection, the best features with a much discriminating power were selected based on separability index (SI) calculation. Finally, to distinguish the islanding conditions from the other normal operation conditions, a support vector machine (SVM) classifier was trained based on the selected features. To investigate the power of the proposed scheme for islanding detection, the results of examinations on the various islanding conditions including system loading and grid operating state were presented. These results show that the proposed algorithm reliably detect the islanding condition within 32.7 ms.
A. Jabbari,
Volume 17, Issue 1 (3-2021)
Abstract
In this paper, we present a semi-analytical model for determining the magnetic and electromagnetic characteristics of spoke-type permanent magnet (STPM) machine considering magnet segmentation and finite soft-material relative permeability. The proposed model is based on the resolution of the Laplace’s and Poisson’s equations in a Cartesian pseudo-coordinate system with respect to the relative permeability effect of iron core in a subdomain model. Two different magnet-segmented STPM machine was studied analytically and numerically. The effect of the iron core relative permeability on the STPM machine performances was investigated at no-load and on-load conditions with respect to certain values of iron core relative permeability by comparing cogging torque, electromagnetic torque ripple, and reluctance torque ripple waveforms. In order to validate the results of the proposed analytical model, the analytical and numerical results were compared. It can be seen that the analytical modeling results are consistent with the results of numerical analysis.
M. Petrov,
Volume 17, Issue 1 (3-2021)
Abstract
The noise in reconstructed slices of X-ray Computed Tomography (CT) is of unknown distribution, non-stationary, oriented and difficult to distinguish from main structural information. This requires the development of special post-processing methods based on the local statistical evaluation of the noise component. This paper presents an adaptive method of reducing noise in CT images employing the shearlet domain in order to obtain such an estimate. The algorithm for statistical noise assessment takes into account the distribution of signal energy in different scales and directions. The method efficiently uses the strong targeted sensitivity of shearlet systems in order to reflect more accurately the anisotropic information in the image. Because of the complex characteristics of the noise in these images, the threshold constant is determined by means of the relative entropy change criterion. The comparative analysis, which has been conducted, shows that the proposed method achieves higher values for the Peak Signal-to-Noise Ratio (PSNR), as well as lower values for the Mean Squared Error (MSE), in comparison with the other methods considered. For the MATLAB’S Shepp Logan Phantom test image, the numerical value of this superiority is on average more than 23% for the first quantitative measure, and 37% for the second. Its efficiency, which is greater than that of the wavelet-based method, is confirmed by the results obtained – the edges have been preserved during noise reduction in real CT images.
A. Jabbari, F. Dubas,
Volume 17, Issue 2 (6-2021)
Abstract
In this paper, we present a mathematical model for determining the optimal radius of the iron pole shape in spoke-type permanent-magnet (PM) machines (STPMM) in order to minimize the pulsating torque components. The proposed method is based on the formal resolution of the Laplace’s and Poisson’s equations in a Cartesian pseudo-coordinate system with respect to the relative permeability effect of iron core in a subdomain model. The effect of PM width on the optimal radius of the iron pole has been investigated. In addition, for initial and optimal machines, the effect of the iron core relative permeability on the STPMM performances was studied at no-load and on-load conditions considering three certain PM widths. Moreover, the effect of iron pole shape on pulsating torque components with respect to certain values of iron core relative permeability was studied by comparing cogging torque, ripple and reluctance torque waveforms. In order to validate the results of the proposed analytical model, three motors with different PM widths were considered as case studies and their performance results were compared analytically and numerically. Two prototype spoke-type machines were fabricated and the experimental results were compared to analytical results. It can be seen that the analytical modeling results are consistent with the numerical analysis and experimental results.
S. K. Gudey, S. Andavarapu,
Volume 17, Issue 3 (9-2021)
Abstract
A three-phase dual-port T-type asymmetrical multilevel inverter (ASMLI) using two sources, solar forming the high voltage level and the battery forming the low voltage level, is considered for grid interconnection. A vertical shifted SPWM is used for the ASMLI circuit. A transformerless system for grid interconnection is achieved for a 100-kW power range. A well-designed boost converter and a Buck/Boost converter is used on the front side of the inverter. Design of battery charge controller and its controlling logic are done and its SOC is found to be efficient during charging and discharging conditions. A closed-loop control using PQ theory is implemented for obtaining power balance at 0.7 modulation index. The THD of the current harmonics in the system is observed to be 0.01% and voltage harmonics is 0.029% which are well within the permissible limits of IEEE-519 standard. The power balance is found to be good between the inverter, load, and the grid during load disconnection for a period of 0.15s. A comparison of THD’s, voltage, current stresses on the switches, and conduction losses is also presented for a single-phase system with respect to a two-level inverter which shows improved efficiency and low THD. Hence this system can be proposed for use in grid interconnection with renewable energy sources.
F. Bahmanzadeh, F. Mohajeri,
Volume 18, Issue 1 (3-2022)
Abstract
In this article, a very small flexible antenna with dual-band rejection specifications is proposed for operating in both wearable and ultra-wideband (UWB) applications. The overall size of this antenna is about 18×18×0.508 mm3 and by etching out two rectangular slot type single split-ring resonators (SRRs) of different dimensions from the radiating patch, dual band-notched specifications are obtained in WiMAX (3.3 GHz to 3.7 GHz) and WLAN (5.15 GHz to 5.825 GHz) wireless communication bands. The designed antenna operates over a wide impedance bandwidth (|S11| < –10 dB) from 2.1 GHz to 12 GHz which can cover the whole UWB band from 3.1 GHz to 10.6 GHz and reject the two mentioned bands. An asymmetrical partial ground plane and a beveled radiating patch are utilized to achieve 140% fractional bandwidth. Also, due to the good wearable radiation characteristics, this antenna can operate in industrial scientific medical (ISM) band from 2.4 GHz to 2.5 GHz. Meanwhile, the specific absorption ratio (SAR) value of the proposed antenna is less than the standard limit of 1.6 W/kg.
A. Saffari, S. H. Zahiri, M. Khishe,
Volume 18, Issue 1 (3-2022)
Abstract
In this paper, multilayer perceptron neural network (MLP-NN) training is used by the grasshopper optimization algorithm with the tuning of control parameters using a fuzzy system for the big data sonar classification problem. With proper tuning of these parameters, the two stages of exploration and exploitation are balanced, and the boundary between them is determined correctly. Therefore, the algorithm does not get stuck in the local optimization, and the degree of convergence increases. So the main aim is to get a set of real sonar data and then classify real sonar targets from unrealistic targets, including noise, clutter, and reverberation, using GOA-trained MLP-NN developed by the fuzzy system. To have accurate comparisons and prove the GOA performance developed with fuzzy logic (called FGOA), nine benchmark algorithms GOA, GA, PSO, GSA, GWO, BBO, PBIL, ES, ACO, and the standard backpropagation (BP) algorithm were used. The measured criteria are concurrency speed, ability to avoid local optimization, and accuracy. The results show that FGOA has the best performance for training datasets and generalized datasets with 96.43% and 92.03% accuracy, respectively.
