Scientia Iranica
Volume:28 Issue: 6, Nov-Dec 2021

In recent years, Fisher linear discriminant analysis (FLDA) based classifi-cation is one of the most successful approaches and has been shown effectiveperformance in different classification tasks. However, when the learning data(source domain) have a different distribution against the testing data (tar-get domain), the FLDA-based models may not be optimal, and the perfor-mance will be degraded, dramatically. To face this problem, in this paper, wepropose an optimal domain adaptation via Bregman divergence minimization(DAB) approach, in which the discriminative features of source and target do-mains are simultaneously learned via domain invariant representation. DABis designed based on the constraints of FLDA, with the objective to adaptthe coupled marginal and conditional distribution mismatches with Breg-man divergence minimization. Thus, the resulting representation can havewell functionality like FLDA and simultaneously have better discriminationability. Moreover, our proposed approach can be easily kernelized to dealwith nonlinear tasks. Extensive experiments on various benchmark datasetsshow that our DAB can effectively deal with the cross domain divergence andoutperforms several state-of-the-art domain adaptation approaches on cross-distribution domains.

The optimization problems with more than three objectives are many-objective optimization problems exist in various scientific and engineering domains. The existing multi-objective evolutionary algorithmic approaches primarily developed to address problems up to three objectives. Such multi-objective evolutionary algorithms do not found effective to address the many-objective optimization problems. The limitations of existing multi-objective evolutionary algorithms initiated the need to develop a specific algorithm which efficiently solves the many-objective optimization problems. The proposed work presents the design of the MaOHDE to address MaOPs. Initially, NS-MODE & NS-MOPSO algorithms developed by incorporating the non-dominated sorting approach from NSGA-II, the ranking approach, weight vector, and reference points. The widely used Tchebycheff – a decomposition-based approach applied to decompose the MaOPs. The MaOHDE algorithm developed by hybridizing the NS-MODE with NS-MOPSO. The presented approach’s strength is revealed using 20 instances of DTLZ functions. The effectiveness and efficiency are verified by comparing with MaOJaya, RD-EMO, NSGA-III, MOEA/D, MOEA/DD, RVEA, and MOEA/D-M2M algorithms. From the results, it is observed that the hybridization of NS-MODE and NS-MOPSO as MaOHDE responds better than its competitors for most of the test instances or it is competitive. The convergence rate is also good as compared with other state-of-art algorithms.

The main goal of this paper is to present a new approximate analytical method called modified generalized Taylor fractional series method (MGTFSM) for solving general nonlinear time- fractionalpartial differential equations. The fractional derivative is considered in the Caputo sense. We establish the convergence results of the proposed method. The basic idea of the MGTFSM is to construct the solution in the form of infinite series which converges rapidly to the exact solution of the given problem. The main advantage of the proposed method compare to current methods is that method solves the nonlinear problems without using linearization, discretization, perturbation or anyother restriction. The efficiency and accuracy of the MGTFSM is tested by means of different numerical examples. The results prove that the proposed method is very effective and simple for solving the nonlinear fractional problems.

Let $S$ be a set of $n$ points in the plane that is in convex position. In this paper, using the well-known path-greedy spanner algorithm, we present an algorithm that constructs a plane $frac{3+4pi}{3}$-spanner $G$ of degree 3 on the point set $S$. Recently, Biniaz et al. ({it Towards plane spanners of degree 3, Journal of Computational Geometry, 8 (1), 2017}) have proposed an algorithm that constructs a degree 3 plane $frac{3+4pi}{3}$-spanner $G'$ for $S$. We show that there is no upper bound with a constant factor on the total weight of $G'$, but the total weight of $G$ is asymptotically equal to the total weight of the minimum spanning tree of $S$.

This paper presents an ultra-low-voltage operational transconductance amplifier (OTA) and Gm-C filter, both working with 0.3V single supply voltage. Using pseudo-differential structure, the common mode rejection is the main challenge in low voltage condition which is overcome by a new common mode feedback circuit. The OTA can be tuned through the gate terminal of body-driven PMOS input transistors. Post-layout simulation shows 23.4 dB differential gain and 47.4 dB CMRR at low frequencies. By changing the tune voltage from 50mV to 0V, the OTA's transconductance can be tuned from 7.9 to 17.4 uA/V. By applying input voltages up to 0.36 Vpp, the THD of output current remains less than -60 dB. The proposed OTA is employed to implement a tunable low-pass Gm-C filter. The cutoff frequency of Gm-C filter can be tuned from 1.13 to 1.9 MHz that makes it applicable in the multi-standard direct conversion receivers as channel selection filter. The power consumption of filter is 111.3 uW and its input referred voltage noise is 168.7 nV/sqrt(Hz), as results of post-layout simulations. The post-layout simulation shows the IIP3 of 8.5 dBm for the cutoff frequency of 1.9 MHz.

This paper introduces a new active snubber cell for soft switched power factor correction (PFC) boost converters. In the new converter, the main switch turns on by zero voltage transition (ZVT) and turns off by zero voltage switching (ZVS). The main diode turns on by ZVS and turns off by zero current switching (ZCS). In the active snubber cell, the auxiliary switch turns on by ZCS and turns off by zero current transition (ZCT). Any semiconductor device does not expose the addition voltage stress. The theoretical analysis of the proposed converter is presented, and also verified with both simulation and experimental study at 100 kHz switching frequency and 600 W output power. Furthermore, the new converter has 95.7% efficiency and 0.99 power factor at soft switching operation.

This paper deals with the adaptive detection of radar target signal with unknown amplitude embedded in Gaussian interference which has been modelled as an AR process. Considering such model for the interference decreases the number of parameters that must be estimated and therefore less or even no secondary data is needed to obtain a detector with desired performance. Herein the detection is based on only the primary data. The authors resorting to the modern Kalman filtering technique develop the conventional GLRT-based detection in the presence of AR interference and propose two new detectors; AREKF based on extended Kalman filter and ARUKF based on unscented Kalman filter. The performance assessment conducted by Monte Carlo simulation compares the proposed detectors with the existing detectors based on generalised likelihood ratio test and Kalman filter. The results show that the ARUKF detector significantly has better detection performance than that of other detectors for the low number of primary data and high signal to noise ratio (SNR).

This study focuses on a special topology of Transvers Flux Permanent Magnet Generator which benefits from low PM cost due to using cheap Ferrite PMs. In this structure, only one PM per phase is used where leads to easy manufacturing process. In spite of the above mentioned advantages of the topology, there are some disadvantages such as unbalanced voltage, high demagnetisation risk of the PM, and high cogging torque. Aiming to solve these problems while maintaining the advantages of the topology, a new structure is proposed. The stator of this structure contains two series connected coils which eliminates all the even order harmonics and balances the voltage waveform. This trick reduces the armature reaction as well as demagnetisation of the PMs, significantly. Additionally, the rotor teeth of the proposed structure are skewed where leads to a noticeable reduction in cogging torque. The output results of the proposed structure are compared with the original one in terms of harmonic components, cogging torque profile, and PM demagnetisation.

Energy consumption plays a key role in economics development for all countries. Catching the future trend of energy consumption is very important for the governments and energy companies. In this paper, the primary energy consumption of Saudi Arabia, India, Philippines and Vietnam are systematically studied by various forecasting models. Based on the actual data from 2006 to 2016, a novel grey forecasting model termed NDGM_S (1,1,k,c) is proposed where the Simpson numerical integration formula is applied to construct the background value. The time response function and the restored value of the present model are deduced, and then the unbiased property is proved. As shown in the computational results, the NDGM_S (1,1,k,c) model can achieve better prediction accuracy than other forecasting models, and it is quite suitable for predicting sequence with homogeneous/non-homogeneous exponential law.

The improved multiband-structured subband adaptive filter (IMSAF) applies the input regressors at each subband to speed up the convergence rate of MSAF. When the projection order is increased, the convergence rate of the IMSAF algorithm improves at the cost of increased complexity. The present research introduces two new IMSAF algorithms with low computational complexity feature. In the first algorithm, the selective partial update approach (SPU) is extended to IMSAF algorithms and SPU-IMSAF is established. In SPU-IMSAF, the filter coefficients are partially updated at each subband for every adaptation. In the second algorithm, the set-membership (SM) strategy is utilized in IMSAF and SM-IMSAF is established. The SM-IMSAF has fast convergence rate, low steady-state error and low computational complexity features at the same time. Also, by combining SM and SPU methods, the SM-SPU-IMSAF is introduced. Simulation results demonstrate the good performance of the proposed algorithms.

Classical vehicle routing problems (VRP) involves supply of goods/services from a central depot to geographically scattered customers. Besides the classical objective of minimizing the total travelled distance, the present work also considers simultaneous optimization of two additional objectives namely minimizing make span and minimizing distance imbalance. A mathematical model for this multi-objective version of VRP (MO-VRPTW) has been developed. A meta-heuristic based on multiple ant colony system for solving this MO-VRPTW has also been proposed. Firefly algorithm (FA) has also been applied to avoid local optima. Two new migration operators named Migration-I and Migration-II and multi-pheromone matrices have been developed to further improve the solution set. The proposed algorithm has been tested on a number of benchmark problems and its superiority over other state of art approaches and NSGA-II one of the commonly used method for multi-objective optimization problems is demonstrated.

Wound-rotor (WR) resolvers are the most commercially used resolvers in industrial applications. In this paper, the effect of different winding arrangements on the accuracy of WR resolvers is discussed. Three windings are proposed for the stator of the resolver that are involved on-tooth overlapping winding, distributed lap winding and distributed concentric winding. Those windings are also applied to the rotor. All the rotor windings are assumed to be single phase and two-phase. Therefore, the effect of damper winding is also studied in the paper. The analysis is done using time stepping finite element method and the most accurate resolver is built and tested. Close agreement between the experimental measurements and the finite element results confirms the obtained results.

Estimation of solar energy generation in the integrated power systems must be performed for power system the long-term planning and the short-term control. Irradiation is one of the main factors affecting the out coming energy of solar system. Hence, investigation of solar irradiation on the horizontal surface helps in proper and efficient implementation of solar energy system. Capturing much more energy from the irradiation, by the Photovoltaic (PV) cells, results in enhancement of out coming energy of PV station. This paper is going to study the impact of implementation two topologies for energy harvesting in PV stations. The topologies are as follows: (a) PV station with multilevel boost converters and inverters, (b) PV station with only multilevel inverters. Studies have been performed on 80 KW PV test station, located in Kabudrahang, Iran. The comparison between the results demonstrates much more solar energy harvesting in the case of applying multilevel converters in the output of PV arrays. Simulation results show the promising result of the proposed topology in harvesting maximum power from a PV station.

In this paper, a single synchronous reference-frame based control method is proposed to improve the performance of AC-DC interlink converters feeding DC loads under unbalanced AC grid conditions. Unbalanced grid voltages cause undesirable double frequency (2ω0) oscillations on the DC link voltage in AC-DC converters. In the medium/high power applications, low switching frequency, and the oscillatory power of the input filter considerably degrade the functionality of the existing methods for removing 2ω0 ripples from DC link voltage. In this paper, an analytical equation for the terminal active power is derived considering the input filter inductance. Accordingly, suitable current references are proposed to eliminate the undesirable 2ω0 ripples from DC-link voltage considering low switching frequency. It is shown that the filter inductance adds a non-linear term to the active power equation which complicates the current reference calculation. Accordingly, a real-time recursive method is proposed to solve the equations and find the current references. To evaluate the performance of the proposed method, different grid unbalanced conditions, including asymmetrical short circuit faults, are applied to a test system in the PSCAD/EMTDC environment. Furthermore, the functionality of the proposed method is compared with that of the existing method for unbalanced conditions in the literature.

The sampling rate plays a key role in wireless applications at very high-frequency range. Flash analog-to-digital converter (ADC) betters the slow converter counterparts in this regard but bulky at inevitable high resolutions. A state-of-the-art Divide and Collate (DnC) algorithm is proposed to design the flash ADC at subranging levels. The offset voltage is kept at a minimum through the comparators used for coarse and fine conversion separately. The kick-back noise is also reduced by using sample and hold switches at the input. The 10-bit ADC architecture is designed with 45-nm CMOS technology and analyzed in the SPECTRE environment. A trivial variation in the transconductance with temperature is observed and consequently the offset drift with temperature is found to be 0.015 mV/'C. The design improves the INL by 0.42 LSB and DNL by 0.3 LSB. Signal-to-noise-and-distortion (SNDR) ratio and spurious-free dynamic range (SFDR) are 51.8 dB and 62 dB respectively at a frequency range near the Nyquist rate with a supply voltage of 1 V and input frequency of 500 MHz. Subranging scheme minimizes the comparator requirements which is reflected in the 44% reduction in the power dissipation.

Microgrids (MGs) are designed to be able to serve hosting critical load in island-mode during major events. However, during normal condition when they are in grid-connected mode, MGs may have opportunity to achieve monetary profits through optimizing operation of energy resources and their participation in wholesale markets. This paper proposes a model to optimize MGs participation in the markets and operation of energy resources. Since MGs usually host renewable energy resources, making decision without considering the uncertainties may prone MGs to risk. So, the model considers uncertainties associated with generation of renewable DGs, demand, and market prices via robust optimization technique. The model is a max-min problem which is modelled as a bi-level optimization problem. The problem is solved in two iterative steps. In the first step, a genetic algorithm (GA) is applied to obtain the worst case wherein uncertain parameters are determined such that MG profit is minimized. Then, a mixed-integer linear problem is solved to maximize the profit over MG decision variables considering the values determined in the first step. The steps are iterated to converge to the best solution. To verify performance of the approach, it is applied to a typical MG and the results are reported.

A reward and penalty scheme (RPS) is used for setting up the service quality which exposes the distribution companies to financial benefits caused by demand for the reliability of customers. In this paper, an algorithm for the optimal switch number and placement in distribution networks in the presence of RPS is presented. The primary objective is reliability improvement and minimization of the cost of sectionalizing switches (SS) and tie switches (TS) for a given regulatory period considering acceptable financial risk. In this algorithm, the uncertainty in the reliability is appeared as financial risk. A genetic algorithm is adopted to solve the optimization problem. The number and location of SS and TS is found while financial incentives of RPS, capital investment and annual operation and maintenance costs are considered. The performance of the proposed approach is assessed and illustrated on a real distribution network. The results show the efficiency of the proposed algorithm.

This study describes an experimental power generation system based on piezoelectric energy conversion for low power applications such as wireless sensor nodes. Piezoelectric transducers (PZTs) are especially suitable for energy harvesting from ambiance. A PZT is able to produce an open circuit voltage at hundreds volt level. But acquired current may be achieved at nano – micro scale. Therefore, PZT energy harvesters (PEH) have a very limited power generation capability. In order to generate higher output power, a series of PZT should be used in a PEH with proper electrical connection. In this paper, PEH is presented with a novel circuit topology for increase output power. The experimental system uses 20 diaphragm type PZTs with a 15 cm spring mounted at the center of each transducer. Necessary vibration is produced via a spring – mass structure of each PZT. Mass – spring structure is vibrated by the effect of wind. The maximum output power of the presented experimental generator for a nominal wind speed of 12 m/s is around 10.8 mJ. Results shows that proposed experimental generator is suitable for low power applications and output power of generator can be increased by using more PTZ is connected used circuit topology.