Sharif Digital Repository

As Big Data processing often takes a long time and needs a lot of resources, sampling and approximate computing techniques may be used to generate a desired Quality of Result. On the other hand, due to not considering data variety, available sample-based approximation approaches suffer from poor accuracy. Data variety is one of the key features of Big Data which causes various parts of data to have different impact on the final result. To address this problem, we develop a data variety aware approximation approach called Gapprox. Our idea is to use a kind of cluster sampling to improve the accuracy of estimation. Our approach can decrease the amount of data to be processed to achieve the... 

A new architecture for analog sampled-data filters is presented. This architecture is based on implementing the difference equation of the filter using a neural network. It results in lower sensitivity of filter coefficients to hardware nonidealities. Different tradeoffs in the hardware implementation of the filter are discussed. A design example is also presented. © 2005 IEEE  

This paper investigates a new algorithm for flocking of multi-Agent systems with virtual leader. In this algorithm, unlike the existing algorithms, receiving of information by agents are not continuous and it is assumed that each agents receives information of neighbors and virtual leader as sampled data in fixed time intervals. A sufficient condition on sampling period is derived to guarantee the velocity convergence of agents to that of virtual leader, preserve network connectivity, and ensure collision avoidance. Finally, a numerical simulation is provided to illustrate the theoretical results. © 2017 IEEE  

A new family of sampled-data filters in which accuracy is a function of the ratio of the resistors is introduced. It is shown that this structure is suitable for low-voltage high-speed applications. A biquad filter with a quality factor of 10 and a clock frequency of 60MHz consuming only 2mW power is also presented  

The multidimensional Discrete Wavelet Transform (DWT) has been widely used in signal and image processing for regularly sampled data. For irregularly sampled data, however, other techniques should be used including the Least Square Wavelet Decomposition (LSWD). The commonly used level by level (sequential) wavelet decomposition, which calculates the wavelet coefficients in each resolution separately, may result in a gross interpolation error. To overcome this drawback, a different approach called the Simultaneous Least Square Wavelet Decomposition, which computes all wavelet coefficients simultaneously, have been proposed by the authors. In this paper, we extend the simultaneous LSWD... 

Partially-observed data collected by sampling methods is often being studied to obtain the characteristics of information diffusion networks. However, these methods usually do not consider the behavior of diffusion process. In this paper, we propose a novel two-step (sampling/estimation) measurement framework by utilizing the diffusion process characteristics. To this end, we propose a link-tracing based sampling design which uses the infection times as local information without any knowledge about the latent structure of diffusion network. To correct the bias of sampled data, we introduce three estimators for different categories, link-based, node-based, and cascade-based. To the best of... 

In this paper a holistic method and a local method based on decision template ensemble are investigated. In addition by combining both methods, a new hybrid method for boosting the performance of the system is proposed and evaluated with respect to robustness against small sample size problem in face recognition. Inadequate and substantial variations in the available training samples are the two challenging obstacles in classification of an unknown face image. At first in this novel multi learner framework, a decision template is designed for the global face and a set of decision templates is constructed for each local part of the face as a complement to the previous part. The prominent... 

This paper introduces "switched-resistor" circuits as a new family of current-mode sampled-data circuits with improved accuracy and linearity. Advantages of the switched-resistor circuits for high-speed and low-voltage applications are demonstrated. A switched-resistor biquad band-pass filter with a quality factor of 10 and clock frequency of 100 MHz, fabricated in a 0.18 μ m CMOS process, is also presented. The filter consumes 9 mW from 1.8 V supply. © 2008 Elsevier GmbH. All rights reserved  

This paper introduces how to incorporate fuzzy set theory with discrete-event simulation in order to model uncertain activity duration in simulating a real-world system, especially when insufficient or no sample data are available. A case study is developed to apply this method to select a scenario to implement the maintenance program in a constant work in process (CONWIP) system. The maintenance activities directly or indirectly affect on production system performance such as response time production costs and etc. so we used the fuzzy simulation to determine the maintenance affects on the system performance. Finally we used the fuzzy simulation result to develop a fuzzy multi attribute... 

This article introduces a methodology to integrate fuzzy multiattribute decision making (FMADM) and fuzzy simulation. According to this method, a fuzzy simulation method is applied to study the effect of different alternative on system's performance and decision criteria taking into account fuzzy inputs. Using a fuzzy analytical hierarchy process (FAHP) and the results of fuzzy simulation, a FMADM is conducted to select the best alternative. This article introduces how to incorporate fuzzy set theory with discrete-event simulation in order to model uncertain activity duration in simulating a realworld system, especially when insufficient or no sample data are available. A case study is... 

Needle insertion simulation and planning systems (SPSs) will play an important role in diminishing inappropriate insertions into soft tissues and resultant complications. Difficulties in SPS development are due in large part to the computational requirements of the extensive calculations in finite element (FE) models of tissue. For clinical feasibility, the computational speed of SPSs must be improved. At the same time, a realistic model of tissue properties that reflects large and velocity-dependent deformations must be employed. The purpose of this study is to address the aforementioned difficulties by presenting a cost-effective SPS platform for needle insertions into the liver. The study...