Shahriar Shirvani Moghaddam
P. Amiri; M. Kohestani; M. Seifouri
Abstract
In this paper, we investigate the parameters affecting Total Harmonic Distortion (THD) and Power Supply Rejection Ratio (PSRR) in PWM Class D Amplifiers (CDAs) on the basis of linear models with feedback. From our mathematical analysis, we show that the THD of a PWM Class D amplifier with feedback can ...
Read More
In this paper, we investigate the parameters affecting Total Harmonic Distortion (THD) and Power Supply Rejection Ratio (PSRR) in PWM Class D Amplifiers (CDAs) on the basis of linear models with feedback. From our mathematical analysis, we show that the THD of a PWM Class D amplifier with feedback can be improved by increasing the gain of the integrator through adding another amplifier at the output of the integrator. We also show that the THD can be further improved by means of two cascaded amplifiers with a single pole. We verify our analysis by means of PSPICE simulations. Simulation results show that the THD of the gain boosting and the two cascaded amplifiers with a single pole CDAs can be improved by as much as 1.4 times and 2 times, respectively.
M. Mansour Abadi; Z. Ghassemlooy; D. Smith; W. Pang Ng
Abstract
Studying Gaussian beam is a method to investigate laser beam propagation and ABCD matrix is a fast and simple method to simulate Gaussian beam propagation in different mediums. Of the ABCD matrices studied so far, reflection and refraction matrices at various surfaces have attracted a lot of researches. ...
Read More
Studying Gaussian beam is a method to investigate laser beam propagation and ABCD matrix is a fast and simple method to simulate Gaussian beam propagation in different mediums. Of the ABCD matrices studied so far, reflection and refraction matrices at various surfaces have attracted a lot of researches. However in previous work the incident beam and the principle axis of surface are in parallel. As an extension to those investigations, a general scheme that the incident beam is oblique is discussed here and the full analysis of the reflection and refraction of a Gaussian beam at the surface of a tilted concave/convex elliptic paraboloid surface is addressed. Based on the optical phase matching, analytic mathematical equations are derived for the spot size and the wavefront radius of a beam. Expressions are converted into the ABCD matrices, which are more convenient and practical to use. Finally, a practical case is analyzed by applying the obtained formulas. This analysis is important since paraboloid surfaces in optics or terahertz waves are used as mirrors or lenses.
V. Maihami; F. Yaghmaee
Abstract
With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers ...
Read More
With quick development of digital images and the availability of imaging tools, massive amounts of images are created. Therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. Automatic image annotation (AIA) or refers to attaching words, keywords or comments to an image or to a selected part of it. In this paper, we propose a novel image annotation algorithm based on neighbor voting which uses fuzzy system. The performance of the model depends on selecting the right neighbors and a fuzzy system with the right combination of features it offers.Experimental results on Corel5k and IAPR TC12 benchmark annotated datasets, demonstrate that using the proposed method leads to good performance.
Cognitive Radio Networks
M. Sadeghian Kerdabadi; R. Ghazizadeh; H. Farrokhi
Abstract
Background and Objectives: In an energy harvesting cognitive radio network, both energy efficiency and spectrum efficiency can be improved, simultaneously. In this paper, we consider an energy harvesting-based multi-antenna cognitive radio network to execute cooperative spectrum sensing, data transmission ...
Read More
Background and Objectives: In an energy harvesting cognitive radio network, both energy efficiency and spectrum efficiency can be improved, simultaneously. In this paper, we consider an energy harvesting-based multi-antenna cognitive radio network to execute cooperative spectrum sensing, data transmission and RF energy harvesting by secondary transmitter from PU’ signal and the ambient noise, simultaneously. Methods: In his paper, two novel models called Joint Power allocation and Energy Harvesting by Time switching and Antennas splitting (JPEHTA) and Joint Power allocation and Continuous Energy Harvesting (JPCEH) are proposed. We formulate the joint optimization problems of the sensing time, detection threshold, energy harvesting time, number of cooperative antennas for sensing and energy harvesting as well as power allocation for each antenna in both proposed models. The aim is for enhancing both the spectral and the energy efficiencies under constraints on the probabilities of global detection and false alarm, energy harvesting and transmission power budget. Then, the considered multi-variable problem is solved by using two convex-based iterative proposed algorithms having less computational complexity compared to baseline approaches to achieve the optimal parameters and goals of the problem. Results: The results present insights about the impact of the sensing time, detection threshold, power allocation and the number of antennas on the energy and spectrum efficiencies of cognitive radio network with an energy harvesting capability.Conclusion: Simulation results shown that the proposed schemes outperform the structures that have not optimized all the parameters considered in this paper, jointly or schemes in which single-antenna SU are participated in spectrum sensing, energy harvesting and data transmitting.
F. Ghassemlooy; D. Wu; M.A. Khalighi; X. Tang
Abstract
For an indoor non-directed line of sight optical wireless communication (NLOS-OWC) system we investigate the optimized Lambertian order (OLO) of light-emitting diodes (LEDs). We firstly derive an expression for the OLO from a conventional Lambertian LED model. Then, we analyze the indoor multi-cell NLOS-OWC ...
Read More
For an indoor non-directed line of sight optical wireless communication (NLOS-OWC) system we investigate the optimized Lambertian order (OLO) of light-emitting diodes (LEDs). We firstly derive an expression for the OLO from a conventional Lambertian LED model. Then, we analyze the indoor multi-cell NLOS-OWC channel characteristics including the optical power distribution and the multipath time dispersion for two cases of one-cell and four-cell configurations. Furthermore, we estimate the transmission bandwidth by simulating the channel frequency response.Numerical results presented show that, by using OLO a significant improvement of the transmission bandwidth can be achieved for an indoor NLOS-OWC system, in particular, for multi-cell configurations.
Artificial Intelligence
N. Ghanbari; S. H. Zahiri; H. Shahraki
Abstract
Background and Objectives: In this paper, a new version of the particle swarm optimization (PSO) algorithm using a linear ranking function is proposed for clustering uncertain data. In the proposed Uncertain Particle Swarm Clustering method, called UPSC method, triangular fuzzy numbers (TFNs) are used ...
Read More
Background and Objectives: In this paper, a new version of the particle swarm optimization (PSO) algorithm using a linear ranking function is proposed for clustering uncertain data. In the proposed Uncertain Particle Swarm Clustering method, called UPSC method, triangular fuzzy numbers (TFNs) are used to represent uncertain data. Triangular fuzzy numbers are a good type of fuzzy numbers and have many applications in the real world.Methods: In the UPSC method input data are fuzzy numbers. Therefore, to upgrade the standard version of PSO, calculating the distance between the fuzzy numbers is necessary. For this purpose, a linear ranking function is applied in the fitness function of the PSO algorithm to describe the distance between fuzzy vectors. Results: The performance of the UPSC is tested on six artificial and nine benchmark datasets. The features of these datasets are represented by TFNs.Conclusion: The experimental results on fuzzy artificial datasets show that the proposed clustering method (UPSC) can cluster fuzzy datasets like or superior to other standard uncertain data clustering methods such as Uncertain K-Means Clustering (UK-means) and Uncertain K-Medoids Clustering (UK-medoids) algorithms. Also, the experimental results on fuzzy benchmark datasets demonstrate that in all datasets except Libras, the UPSC method provides better results in accuracy when compared to other methods. For example, in iris data, the clustering accuracy has increased by 2.67% compared to the UK-means method. In the case of wine data, the accuracy increased with the UPSC method is 1.69%. As another example, it can be said that the increase in accuracy for abalone data was 4%. Comparing the results with the rand index (RI) also shows the superiority of the proposed clustering method.
Computational Intelligence
Z. K. Pourtaheri
Abstract
Background and Objectives: According to this fact that a typical autonomous underwater vehicle consumes energy for rotating, smoothing the path in the process of path planning will be especially important. Moreover, given the inherent randomness of heuristic algorithms, stability analysis of heuristic ...
Read More
Background and Objectives: According to this fact that a typical autonomous underwater vehicle consumes energy for rotating, smoothing the path in the process of path planning will be especially important. Moreover, given the inherent randomness of heuristic algorithms, stability analysis of heuristic path planners assumes paramount importance.Methods: The novelty of this paper is to provide an optimal and smooth path for autonomous underwater vehicles in two steps by using two heuristic optimization algorithms called Inclined Planes system Optimization algorithm and genetic algorithm; after finding the optimal path by Inclined Planes system Optimization algorithm in the first step, the genetic algorithm is employed to smooth the path in the second step. Another novelty of this paper is the stability analysis of the proposed heuristic path planner according to the stochastic nature of these algorithms. In this way, a two-level factorial design is employed to attain the stability goals of this research.Results: Utilizing a Genetic algorithm in the second step of path planning offers two advantages; it smooths the initially discovered path, which not only reduces the energy consumption of the autonomous underwater vehicle but also shortens the path length compared to the one obtained by the Inclined Planes system optimization algorithm. Moreover, stability analysis helps identify important factors and their interactions within the defined objective function.Conclusion: This proposed hybrid method has implemented for three different maps; 36.77%, 48.77%, and 50.17% improvements in the length of the path are observed in the three supposed maps while smoothing the path helps robots to save energy. These results confirm the advantage of the proposed process for finding optimal and smooth paths for autonomous underwater vehicles. Due to the stability results, one can discover the magnitude and direction of important factors and the regression model.
S. Jamali; N. Alipasandi; B. Alipasandi
Abstract
Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED ...
Read More
Random Early Detection (RED) is one of the most commonly used Active Queue Management (AQM) algorithms that is recommended by IETF for deployment in the network. Although RED provides low average queuing delay and high throughput at the same time, but effectiveness of RED is highly sensitive to the RED parameters setting. As network condition varies largely, setting RED's parameters with fixed values is not an efficient solution. We propose a new method to dynamically tuning RED's parameters. For this purpose, we compute the rate of which the queue is occupied and consider it as a congestion metric that will be forecasted when the queue is overloaded. This meter is used to dynamically setting RED parameters. The simulation results show the effectiveness of the proposed method. According to the results, we achieve a significantly higher utilization and less packet loss comparing to original RED algorithm in dynamic conditions of the network.
T. G. Arora; M. V. Aware; D. R. Tutakne
Abstract
Pulse-width modulated (PWM) adjustable frequency drives (AFDs) are extensively used in industries for control of induction motors. It has led to significant advantages in terms of the performance, size, and efficiency but the output voltage waveform no longer remains sinusoidal. Hence, overshoots, high ...
Read More
Pulse-width modulated (PWM) adjustable frequency drives (AFDs) are extensively used in industries for control of induction motors. It has led to significant advantages in terms of the performance, size, and efficiency but the output voltage waveform no longer remains sinusoidal. Hence, overshoots, high rate of rise, harmonics and transients are observed in the voltage wave. They increase voltage and thermal stresses; resulting into accelerated insulation aging. This paper presents the application of fuzzy logic to life estimation of PWM driven induction motors. Insulation stress parameters are experimentally computed for wide range of switching frequency and used in fuzzy logic based life estimation algorithms. The results obtained with the fuzzy expert system show a performance approaching that attainable for the life model based on the inverse power law.
J. Rostami Monfared; M. Fazeli; Y. Lotfi
Abstract
In this article, a speed control of DC motor is designed and illustrated using fuzzy logic-based programmable logic controller (PLC). The DC motor is an attractive part of electrical equipment in many industrial applications requiring variable speed and load specifications due to its ease of controllability. ...
Read More
In this article, a speed control of DC motor is designed and illustrated using fuzzy logic-based programmable logic controller (PLC). The DC motor is an attractive part of electrical equipment in many industrial applications requiring variable speed and load specifications due to its ease of controllability. The designed system is consisted of three main parts including programmable logic controller, pulse width modulation (PWM) bipolar drive and DC motor. In the control section, PLC is used as real time controller and fuzzy logic algorithm is designed based on nonlinear model of DC motor, and its parameters are optimized in MATLAB software. Then, it is implemented using rslogix5000 PLC and programming language ladder for speed control. Finally, with favorable results, the efficiency of the controller is successfully proved under different load conditions. The obtained results demonstrate the efficiency of the PLC intelligent controller in enhancing the accuracy and speed control of DC motor.
S. Roostaee; H.R Ghaffary
Abstract
Data analysis in cardiovascular diseases is difficult due to large massive of information. All of features are not impressive in the final results. So it is very important to identify more effective features. In this study, the method of feature selection with binary cuckoo optimization algorithm is ...
Read More
Data analysis in cardiovascular diseases is difficult due to large massive of information. All of features are not impressive in the final results. So it is very important to identify more effective features. In this study, the method of feature selection with binary cuckoo optimization algorithm is implemented to reduce property. According to the results, the most appropriate classification for support vector machine is featured diagnoses heart disease. The main purpose of this article is feature reduction and providing a more precise diagnosis of the disease. The proposed method is evaluated using three measures: accuracy, sensitivity and specificity. For comparison, a data set of Machine Learning Repository database including information about 303 people with 14 features was used. In addition to the high accuracy of current methods, are expensive and time-consuming. The results indicate that the proposed method is superior on other algorithms in terms of Performance, accuracy and run time.
Nonlinear System
A.R. Ghomi Taheri; F. Setoudeh; M. B. Tavakoli
Abstract
Background and Objectives: The Differential transform method (DTM) is used in the analysis of ordinary, partial, and high-order differential equations. Recently, the DTM is used in the nonlinear analysis of physical nonlinear dynamic systems.Methods: The DTM method is used to analyze and analytically ...
Read More
Background and Objectives: The Differential transform method (DTM) is used in the analysis of ordinary, partial, and high-order differential equations. Recently, the DTM is used in the nonlinear analysis of physical nonlinear dynamic systems.Methods: The DTM method is used to analyze and analytically solve the nonlinear mathematical model of bias current-controlled Colpitts oscillator with variable coefficients. Intervals of the validity of the proposed method are evaluated by using the fourth order Runge-Kutta method (RK4M). In this note, the Lyapunov exponent (LE) can be used to analyze the Colpitts oscillator. By using DTM, the LEs are calculated analytically with unknown parameters in a short interval of time t[0, 3 Sec]. Results: In this paper, intervals of the validity of the proposed method are evaluated using RK4M. In addition, LEs are calculated using analytical and numerical methods based on DTM technique and Wolf method, respectively. LEs of the proposed system are presented as a function of the control parameter to confirm the applied technique’s usefulness. Conclusion: By comparing these two methods, the proposed DTM analytical technique is relatively more precise. Simulation results confirmed the impact of different parameters on LEs with two different initial conditions. The results show good accuracy of the DTM in short time intervals t[0, 3 Sec].
Network Security
M. Amiri; A. Barati
Abstract
Background and Objectives: Increasing usage of Internet and computer networks by individuals and organizations and also attackers’ usage of new methods and tools in an attempt to endanger network security, have led to the emergence of a wide range of threats to networks.Methods: A honeypot is one ...
Read More
Background and Objectives: Increasing usage of Internet and computer networks by individuals and organizations and also attackers’ usage of new methods and tools in an attempt to endanger network security, have led to the emergence of a wide range of threats to networks.Methods: A honeypot is one of the basic techniques employed for network security improvement. It is basically designed to be attacked so as to get the attackers’ information and trap them. By using a vulnerable scanner in this paper, we obtained the required network vulnerabilities and normalized them via the proposed method. Then, a dynamic hybrid honeypot has proposed by high and low interaction honeypots. Also, in the proposed method, by footprinting and scanning of an integrated network, a detailed picture of the production network and a honeypot configuration file are generated.Results: As a result, more devices could be detected via automated production by the proposed method.Conclusion: This method could accelerate honeypot production and reduce the users’ mistakes during their manual production. Monitoring network traffic, collecting the information of network machines, determining network operating systems, and storing data in a database are the specific features of this system that could be performed by using the selected network scanning tools and modules.
Wireless Sensor Network
S. Ashraf; T. Ahmed; Z. Aslam; D. Muhammad; A. Yahya; M. Shuaeeb
Abstract
Background and Objectives: The quick response time and the coverage range are the crucial factors by which the quality service of a wireless sensor network can be acknowledged. In some cases, even networks possess sufficient available bandwidth but due to coverage tribulations, the customer ...
Read More
Background and Objectives: The quick response time and the coverage range are the crucial factors by which the quality service of a wireless sensor network can be acknowledged. In some cases, even networks possess sufficient available bandwidth but due to coverage tribulations, the customer satisfaction gets down suddenly. The increasing number of nodes directly is neither a canny solution to overcome the coverage problem nor a cost-effective. In fact, by changing the positions of the deployed node sagaciously can resolve the coverage issue and seems a cost-effective solution. Therefore, keeping all circumstances, a Depuration based Efficient Coverage Mechanism (DECM) has been developed. This algorithm suggests the new shifting positions for previously deployed sensor nodes to fill the coverage gap.Methods: It is a redeployment process and accomplished in two rounds. The first round avails the Dissimilitude Enhancement Scheme (DES), which searches the node to be shifted at new positions. The second round controls the unnecessary movement of the sensor nodes by the Depuration mechanism thereby the distance between previous and new positions is reduced. Results: The factors like loudness, pulse emission rate, maximum frequency, and sensing radius are meticulously explored during simulation rounds conducted by MATLAB. The performance of DECM has been compared with superlative algorithms i.e., Fruit Fly Optimization Algorithm (FOA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) in terms of mean coverage range, computation time, standard deviation, and network energy diminution.Conclusion: According to the simulation results, the DECM has achieved more than 98% coverage range, with a trivial computation time of nearly 0.016 seconds as compared to FOA, PSO, and ACO.
Hardware
M. Hosseini Shirvani; A. Akbarifar
Abstract
Background and Objectives: Among miscellaneous networks, onion-based routing network technologies such as The Onion-based Routing (ToR), Invisible Internet Project (I2P), and Riffle networks are used to communicate anonymously by different worldwide users for security, privacy, and safety requirements. ...
Read More
Background and Objectives: Among miscellaneous networks, onion-based routing network technologies such as The Onion-based Routing (ToR), Invisible Internet Project (I2P), and Riffle networks are used to communicate anonymously by different worldwide users for security, privacy, and safety requirements. Sometimes, these types of networks sacrifice anonymity for the sake of efficient communication or vice-versa. This paper surveys aforementioned networks for investigating their potential and challenges.Methods: Onion-routing networks encapsulate messages in several layers of encryption similar to layers of an onion. The anonymous communication networks are involved dining cryptographers (DC) problem so-called DC-nets, which need sending anonymous message with unconditional sender and untraceable receipt. So, DC-nets must be resistant against traffic analysis attacks although they will attenuate the network bandwidth. In this line, ToR is a free software that provides anonymous communication, I2P networks are based on hidden internet service project which uses tunnelling for anonymous communications, and Riffle networks include a small set of camouflaging servers that provide anonymity for authorized users. This paper presents a comparative study on anonymizing ToR, I2P, and Riffle networks in terms of associated prominent parameters in this vein.Results: The comparison is based on similarities, differences, and challenges in network behaviors. This comparison is beneficial for further researches and future improvements.Conclusion: The review of the current paper reveals that the Riffle networks are more resilient and have great confidentiality and integrity against other onion-based routing networks.
Artificial Intelligence
S. H. Zahiri; R. Iranpoor; N. Mehrshad
Abstract
Background and Objectives: Person re-identification is an important application in computer vision, enabling the recognition of individuals across non-overlapping camera views. However, the large number of pedestrians with varying appearances, poses, and environmental conditions makes this task particularly ...
Read More
Background and Objectives: Person re-identification is an important application in computer vision, enabling the recognition of individuals across non-overlapping camera views. However, the large number of pedestrians with varying appearances, poses, and environmental conditions makes this task particularly challenging. To address these challenges, various learning approaches have been employed. Achieving a balance between speed and accuracy is a key focus of this research. Recently introduced transformer-based models have made significant strides in machine vision, though they have limitations in terms of time and input data. This research aims to balance these models by reducing the input information, focusing attention solely on features extracted from a convolutional neural network model. Methods: This research integrates convolutional neural network (CNN) and Transformer architectures. A CNN extracts important features of a person in an image, and these features are then processed by the attention mechanism in a Transformer model. The primary objective of this work is to enhance computational speed and accuracy in Transformer architectures. Results: The results obtained demonstrate an improvement in the performance of the architectures under consistent conditions. In summary, for the Market-1501 dataset, the mAP metric increased from approximately 30% in the downsized Transformer model to around 74% after applying the desired modifications. Similarly, the Rank-1 metric improved from 48% to approximately 89%.Conclusion: Indeed, although it still has limitations compared to larger Transformer models, the downsized Transformer architecture has proven to be much more computationally efficient. Applying similar modifications to larger models could also yield positive effects. Balancing computational costs while improving detection accuracy remains a relative goal, dependent on specific domains and priorities. Choosing the appropriate method may emphasize one aspect over another.
Artificial Intelligence
M. Soluki; Z. Askarinejadamiri; N. Zanjani
Abstract
Background and Objectives: This article explores a method for generating Persian texts using the GPT-2 language model and the Hazm library. Researchers and writers often require tools that can assist them in the writing process and even think on their behalf in various domains. By leveraging the GPT-2 ...
Read More
Background and Objectives: This article explores a method for generating Persian texts using the GPT-2 language model and the Hazm library. Researchers and writers often require tools that can assist them in the writing process and even think on their behalf in various domains. By leveraging the GPT-2 model, it becomes possible to generate acceptable and creative texts, which increases writing speed and efficiency, thus mitigating the high costs associated with article writing.Methods: In this research, the GPT-2 model is employed to generate and predict Persian texts. The Hazm library is utilized for natural language processing and automated text generation. The results of this study are evaluated using different datasets and output representations, demonstrating that employing the Hazm library with input data exceeding 1000 yields superior outcomes compared to other text generation methodsResults: Through extensive experimentation and analysis, the study demonstrates the effectiveness of this combination in generating coherent and contextually appropriate text in the Persian language. The results highlight the potential of leveraging advanced language models and linguistic processing tools for enhancing natural language generation tasks in Persian. The findings of this research contribute to the growing field of Persian language processing and provide valuable insights for researchers and practitioners working on text generation applications in similar languages.Conclusion: Overall, this study showcases the promising capabilities of the GPT-2 model and Hazm library in Persian text generation, underscoring their potential for future advancements in the field This research serves as a valuable guide and tool for generating Persian texts in the field of research and scientific writing, contributing to cost and time reduction in article writing
M. Zahiry; S.M. Hashemi; J. Ghalibafan
Abstract
In this paper, a new method for designing an active dual-band dipole antenna is proposed. The operating frequencies of the proposed antenna are 150 and 450 MHz that are usually used in military applications. Using a series stub is the main idea in the proposed dual-band antenna, where it makes an independent ...
Read More
In this paper, a new method for designing an active dual-band dipole antenna is proposed. The operating frequencies of the proposed antenna are 150 and 450 MHz that are usually used in military applications. Using a series stub is the main idea in the proposed dual-band antenna, where it makes an independent resonance frequency higher than the main resonance frequency of a conventional dipole. To make appropriate matching impedance in the two frequency bands, the technique of creating an internal coaxial cable is used. Furthermore, to improve the antenna gain, an amplifier is in series part connected to the proposed dipole antenna. The simulated and measured results of the return loss, radiation patterns and antenna gain show that this antenna has a good operation in both resonance frequencies.
Electronics
S. Ranjbaran; A. Roudbari; S. Ebadollahi
Abstract
Background and Objectives: Using field calibration methods without precision laboratory equipment, systematic faults of inertial sensors can be reduced and measurement accuracy can be increased. Methods: In this paper, a simple and fast method called improved least squares is used to find calibration ...
Read More
Background and Objectives: Using field calibration methods without precision laboratory equipment, systematic faults of inertial sensors can be reduced and measurement accuracy can be increased. Methods: In this paper, a simple and fast method called improved least squares is used to find calibration coefficients of an accelerometer including bias, scale factor and non-orthogonality. In this method, this principal is used that the magnitude of acceleration measured by accelerometer in static condition is equal to the magnitude of gravity vector and a cost function is then defined. Also, in gyroscope field calibration, sensor is rotated manually around all three axes separately and then it is put in the static mode. Changes in the angle obtained from gyroscope at each movement are compared with the ones obtained from the calibrated accelerometer. Calibration coefficients including bias and scale factor are obtained using least squares method. Results: Simulation results in MATLAB show that the measurement accuracy of accelerometer after calibration has improved by about 60% and the accuracy of the gyroscope has increased by about 40%. Also, comparison with the other methods proves that the proposed method performs well in the accuracy, speed, time required, and the effect of noise changes. Conclusion: This paper by finding a fast, simple, and low-cost field calibration method to calibrate MEMS accelerometer and gyroscope without using accurate laboratory equipment can help a wide range of industries that use advanced and expensive sensors or use expensive laboratory equipment to calibrate their sensors, to decrease their costs.======================================================================================================Copyrights©2018 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.======================================================================================================
Power
H. Amiri; G. Arab Markadeh; N. Mahdian
Abstract
Background and Objectives: Increasing DC loads along with DC nature of distributed energy resources (DERs) raises interest to DC microgrids. Conventional droop/non-droop power-sharing in microgrids suffers from load dependent voltage deviation, slow transient response, and requires the parameters of ...
Read More
Background and Objectives: Increasing DC loads along with DC nature of distributed energy resources (DERs) raises interest to DC microgrids. Conventional droop/non-droop power-sharing in microgrids suffers from load dependent voltage deviation, slow transient response, and requires the parameters of the loads, system and DERs connection status.Methods: In this paper, a new nonlinear decentralized back-stepping control strategy for voltage control and load sharing of DC islanded microgrids is proposed. The proposed method is robust against the load variations and uncertainty in microgrid parameters and has excellent dynamic and steady-state performance under different operating conditions. The major purpose of the proposed controller is to improve the transient performance of MG with load variations and constant power loads (CPLs). The local controller regulates the terminal voltage of DC-DC converter regarding the local quantities without needs to additional data of other system components.Results: For simplicity, the proposed method is simulated with PSIM software on a DC microgrid with two DGs. Different scenarios are studied to present the performance of the proposed method under different operating conditions.Conclusion: The results indicate the capability of the proposed method for voltage control and load sharing in DC microgrids.
S. SamadiGorji; B. Zakeri; M.R. Zahabi
Abstract
The aim of this paper is to minimize output phase noise for the pure signal synthesis in the frequency synthesizers. For this purpose, first, an exact mathematical model of phase locked loop (PLL) based frequency synthesizer is described and analyzed. Then, an exact closed-form formula in terms of synthesizer ...
Read More
The aim of this paper is to minimize output phase noise for the pure signal synthesis in the frequency synthesizers. For this purpose, first, an exact mathematical model of phase locked loop (PLL) based frequency synthesizer is described and analyzed. Then, an exact closed-form formula in terms of synthesizer bandwidth and total output phase noise is extracted. Based on this formula, the phase noise diagram as a function of bandwidth is plotted. From the analysis and simulation results, it is observed that the synthesizer has a minimum phase noise at a particular bandwidth.
S. Taghipour; R. Niaraki Asli
Abstract
Due to the expected increase of defects in circuits based on deep submicron technologies, reliability has become an important design criterion. Although different approaches have been developed to estimate reliability in digital circuits and some measuring concepts have been separately presented to reveal ...
Read More
Due to the expected increase of defects in circuits based on deep submicron technologies, reliability has become an important design criterion. Although different approaches have been developed to estimate reliability in digital circuits and some measuring concepts have been separately presented to reveal the quality of analog circuit reliability in the literature, there is a gap to estimate reliability when circuit includes analog and digital structures. In this paper, we propose a new classification method using Monte Carlo analysis to calculate the reliability of analog circuits and show its efficacy when it is used for a combination of analog and digital circuits. Our method is based on signal reliability concepts and measures the probability of passing correct or faulty values. Furthermore, we compare our reliability measurements with the reliability definitions come from other failure mechanisms in sub-micron technologies. Simulation results show the reliability measurement presented here which provides key information for reliability improvement and monitoring.
A. Safaei; M. Jahed
Abstract
Gesture and motion recognition are needed for a variety of applications. The use of human hand motions as a natural interface tool has motivated researchers to conduct research in the modeling, analysis and recognition of various hand movements. In particular, human-computer intelligent interaction has ...
Read More
Gesture and motion recognition are needed for a variety of applications. The use of human hand motions as a natural interface tool has motivated researchers to conduct research in the modeling, analysis and recognition of various hand movements. In particular, human-computer intelligent interaction has been a focus of research in vision-based gesture recognition. In this work, we introduce a 3-D hand model recognition method that offers flexible and elaborate representation of hand motion. We used landmark points on the tips and joints of the fingers and calculated the 3-D coordinates of these points through a stereo vision system followed by a Hidden Markov Model (HMM) to recognize hand motions. Experimentally, in an effort to evaluate the formation of hand gestures similar to those used in rehabilitation sessions, we studied three evolving motions. Given the natural hand features and uncontrolled environment, we were able to classify and differentiate unnatural slowness or rapidness in the performance of such motions, ranging from 45% to 93%.
