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This paper presents a power-efficient low-phase noise digitally controlled oscillator (DCO) implemented in a 65 nm CMOS technology. The DCO is designed for a 12 GHz frequency synthesizer covering up to 1GHz of frequency sweep range demanded by the frequency modulated continuous wave (FMCW) radar. The realized DCO circuit is designed to meet the stringent phase noise specifications of less than −110dBc/Hz...
This paper revisits visual saliency prediction by evaluating the recent advancements in this field such as crowd-sourced mouse tracking-based databases and contextual annotations. We pursue a critical and quantitative approach towards some of the new challenges including the quality of mouse tracking versus eye tracking for model training and evaluation. We extend quantitative evaluation of models...
This paper presents a framework for saliency estimation and fixation prediction in videos. The proposed framework is based on a hierarchical feature representation obtained by stacking convolutional layers of independent subspace analysis (ISA) filters. The feature learning is thus unsupervised and independent of the task. To compute the saliency, we then employ a multiresolution saliency architecture...
This paper presents our efforts towards a framework for video annotation using gaze. In computer vision, video annotation (VA) is an essential step in providing a ground truth for the evaluation of object detection and tracking techniques. VA is a demanding element in the development of video processing algorithms, where each object of interest should be manually labelled. Although the community has...
This paper studies the performance of recorded eye movements and computational visual attention models (i.e. saliency models) in the recognition of emotional valence of an image. In the first part of this study, it employs eye movement data (fixation & saccade) to build image content descriptors and use them with support vector machines to classify the emotional valence. In the second part,...
This paper presents a novel control method for an induction machine (IM) connected to the network through the Static Synchronous Series Compensator (SSSC) and parallel capacitor at the IM's terminals. By segregating the operational states into three sequential operational zones namely, normal (0), during-fault (1), and after-fault recovery (2). Each state provides an appropriate controlling process...
This paper studies the effects of eccentricities faults (EFs) on sensorless operation of Switched Reluctance motors (SRMs). EFs are among widespread faults in SRMs which make machine airgap uneven and consequently change SRM characteristics such as phase and mutual inductances. One of the most common methods for indirect rotor position estimation is to apply high frequency pulses to idle phases. As...
This paper presents an extra freewheeling mode in bifilar Switched Reluctance Generators (SRG) to enhance the Energy Conversion Ratio (ECR). Freewheeling possibility is accomplished through some modifications in conventional structure of bifilar converters requiring only one more MOSFET and diode for each phase. The proposed BiFilar with FreeWheeling (BFFW) mode converter lets the machine increase...
In this paper an adaptive harmonic elimination method is proposed for 5-level Z-source inverter (ZSI). The main objective of harmonic elimination method is to eliminate low order harmonics and satisfies fundamental component by solving nonlinear equations. For any DC voltages variation, this nonlinear equation must be solved to obtain switching angles and shoot through duty cycle of inverter. Genetic...
In this paper a novel converter is presented to improve the excitation process in Switched Reluctance Generators (SRGs). This converter is accomplished through a singular scheme of flyback converter which first in an initial phase charge a dumping capacitor up to a high certain voltage and during the magnetizing period discharge this stored energy into machine's coils. In this paper, the required...
In this paper a comprehensive method is introduced to redress Eccentricity Faults consequences. Two main effects of EFs include considerable increase in Unbalanced Magnetic Force (UMF) and torque ripple. Dependency of UMF and torque ripple on EF level is shown and the possibility of compensating them via controlling currents in facing poles is proved. These objectives are accomplished through a novel...
This paper presents a novel approach to increase the excitation flux in magnetizing state and prolong stored energy discharge in a Switched Reluctance Generator (SRG). This purpose is achieved by using a multi-winding SRG in which the coils in every phase can be paralleled in magnetization period and then shift to series connection in demagnetizing time. It's demonstrated that faster phase charging...
Significant recent progress has been made in developing high-quality saliency models. However, less effort has been undertaken on fair assessment of these models, over large standardized datasets and correctly addressing confounding factors. In this study, we pursue a critical and quantitative look at challenges (e.g., center-bias, map smoothing) in saliency modeling and the way they affect model...
This paper presents a novel hybrid algorithm, named bacterial foraging Nelder-Mead (BF-NM), to determine the optimal values for the proportional-integral (PI) controller parameters in load frequency control (LFC) of a two-area thermal power system including governor dead-band and generation rate constraint (GRC) nonlinearities. In order to have the best optimization procedure, a local search algorithm...
The fire and smoke monitoring systems are useful in different industry such as military, social security and economical. The recent methods for fire and smoke detection are used only motion and color characteristics thus many wrong alarms are happening and this is decrease the performance of the systems. This research presents a new method for fire and smoke detection through image processing. In...
A texture based object tracking algorithm is presented. The algorithm is an extension to famous mean-shift tracking method. It does not rely on color histogram. It incorporates both color histogram and texture histogram information to model tracking target. In order to extract textural information a novel similarity operator is introduced. It is fast to compute and gray-scale invariant. It would be...
Customer knowledge has been increasingly recognized as a key strategic knowledge resource in organizations. This knowledge can be extracted from the customers' gathered information. For different customers the gathered information has different value and should be considered based on its value. In this paper we represent a method for customer knowledge management by considering the value of information...
This study presents an integrated genetic algorithm (GA) and artificial neural network (ANN) to estimate and predict electricity demand using stochastic procedures. The considered sector is the energy intensive sector and the economic indicators used in this paper are price, value added, number of customer, price of the substitute fuel and electricity intensity. The chosen models are linear-logarithmic,...
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