Sharif Digital Repository

This study proposes an approach for improving service reliability in the distribution network based on establishing competition among electric distribution utilities. The idea behind this approach is to categorise the utilities and compare the performance of utilities located in one cluster with the other members of the same cluster. The reward/penalty mechanism (RPM) as a quality regulating instrument is designed for each cluster and used to penalise the utilities with a performance worse than the benchmark and to reward them for providing a performance better than the benchmark. Based on the RPM, utilities located in one cluster compete to make more profit by serving customers in better... 

This paper presents a new inference algorithm for active learning method (ALM). ALM is a pattern-based algorithm for soft computing, which uses the ink drop spread (IDS) algorithm as its main engine for feature extraction. In this paper, a fuzzy number is extracted from each IDS plane rather than from the narrow path and the spread, as in previous approaches. This leads to a significant reduction in the hardware required to implement the inference part of the algorithm and real-time computation of the implemented hardware. A modified version of the memristor crossbar structure is used to solve the problem of varying shapes of the ink drops, as reported in previous studies. In order to... 

Recommender systems have become an important issue in network science. Collaborative filtering and its variants are the most widely used approaches for building recommender systems, which have received great attention in both academia and industry. In this paper, we studied the relationship between recommender systems and connectivity of users-items bipartite network. This results in a novel recommendation algorithm. In our method recommended items are selected based on the eigenvector corresponding to the algebraic connectivity of the graph - the second smallest eigenvalue of the Laplacian matrix. Since recommending an item to a user equals to adding a new link to the users-items bipartite... 

Performance evaluation and efficiency analysis is considered to be one of the critical responsibilities of the management department. This paper investigates and assesses the efficiency and performance of Iranian insurance companies through nonparametric frontier analysis (FA) models. The two well-known nonparametric FA models, data envelopment analysis (DEA) and free disposal hull, are utilized to separate the efficient companies from the inefficient companies, and two well-known super-efficiency analysis models are utilized to rank the efficient units. For the further analysis, critical inputs are also identified for inefficient companies using DEA sensitivity analysis which is a powerful... 

While the transistor density continues to grow exponentially in Field-Programmable Gate Arrays (FPGAs), the increased leakage current of CMOS transistors act as a power wall for the aggressive integration of transistors in a single die. One recently trend to alleviate the power wall in FPGAs is to turn off inactive regions of the silicon die, referred to as dark silicon. This paper presents a reconfigurable architecture to enable effective fine-grained power gating of unused Logic Blocks (LBs) in FPGAs. In the proposed architecture, the traditional soft logic is replaced with Mega Cells (MCs), each consists of a set of complementary Generic Reconfigurable Hard Logic (GRHL) and a conventional... 

A novel bi-objective multi-server location-allocation (LA) model is developed in this paper, in which the facilities are modeled as an M/M/m queuing system. Further, capacity and budget limitations are provided to make the LA problem more realistic. The two objective functions include (1) minimizing aggregate waiting times and (2) minimizing the maximum idle time of all facilities. Since the proposed model is NP-hard, a meta-heuristic algorithm called multi-objective harmony search algorithm (MOHA) is developed to solve it. In this algorithm, a new presentation scheme that satisfies most of the model constraints is proposed. Since there is no benchmark available in the literature to validate... 

An information system network (ISN) can be modeled as a stochastic-flow network (SFN). There are several algorithms to evaluate reliability of an SFN in terms of Minimal Cuts (MCs). The existing algorithms commonly first find all the upper boundary points (called d-MCs) in an SFN, and then determine the reliability of the network using some approaches such as inclusion-exclusion method, sum of disjoint products, etc. However, most of the algorithms have been compared via complexity results or through one or two benchmark networks. Thus, comparing those algorithms through random test problems can be desired. Here, the authors first state a simple improved algorithm. Then, by generating a... 

Defining a suitable similarity measure is a crucial step in (medical) image registration tasks. A common problem with frequently used intensity-based image registration algorithms is that they assume intensities of different pixels are independent of each other that could lead to low registration performance especially in the presence of spatially-varying intensity distortions, because they ignore the complex interactions between the pixel intensities. Motivated by this problem, in this paper we present a novel similarity measure which takes into account nonstationarity of the pixels intensity and complex spatially varying intensity distortions in mono-modal settings. Experimental results on... 

Accurate description of wall-bounded turbulent flows requires a fine grid near walls to fully resolve the boundary layers. We consider a locally simplified transport model using an assumed near-wall viscosity profile to project the wall boundary conditions using the boundary transfer method. Related coefficients are obtained numerically. By choosing a near-wall viscosity profile, we derive an analytic wall function, which significantly reduces the CPU costs. The performance of this wall function is compared to other near-wall treatments proposed in the literature for two frequently used benchmark cases: near-equilibrium channel flow and flow over a backward-facing step with separation and... 

Ensemble Kalman filter, EnKF, as a Monte Carlo sequential data assimilation method has emerged promisingly for subsurface media characterization during past decade. Due to high computational cost of large ensemble size, EnKF is limited to small ensemble set in practice. This results in appearance of spurious correlation in covariance structure leading to incorrect or probable divergence of updated realizations. In this paper, a universal/adaptive thresholding method is presented to remove and/or mitigate spurious correlation problem in the forecast covariance matrix. This method is, then, extended to regularize Kalman gain directly. Four different thresholding functions have been considered... 

This paper presents an improved firefly algorithm (FA) for fast optimization of truss structures with discrete variables. The enhanced accelerated firefly algorithm (AFA) is a simple, but very effective modification of FA. In order to investigate the performance and robustness of the proposed algorithm, some benchmark (structural optimization) problems are solved and the results are compared with FA and other algorithms. The results show that in some test cases, AFA not only finds lighter structures compared to other algorithms, but also converges faster. In the rest test cases, the optimal solutions are found with very less computational effort. The study also shows that the proposed AFA... 

The secure hash algorithm (SHA)-3 has been selected in 2012 and will be used to provide security to any application which requires hashing, pseudo-random number generation, and integrity checking. This algorithm has been selected based on various benchmarks such as security, performance, and complexity. In this paper, in order to provide reliable architectures for this algorithm, an efficient concurrent error detection scheme for the selected SHA-3 algorithm, i.e., Keccak, is proposed. To the best of our knowledge, effective countermeasures for potential reliability issues in the hardware implementations of this algorithm have not been presented to date. In proposing the error detection... 

A wide range of scheduling algorithms used in the data centers have traditionally concentrated on enhancement of performance metrics. Recently, with the rapid growth of data centers in terms of both size and number, the power consumption has become a major challenge for both industry and society. At the software level, energy-aware task scheduling is an effective technique for power reduction in the data centers. However, most of the currently proposed energy-aware scheduling approaches are only paying attention to computation cost. In the other words, they ignore the energy consumed by the network equipment, namely communication cost. In this paper, the problem of scheduling... 

We propose a graph-based data clustering algorithm which is based on exact clustering of a minimum spanning tree in terms of a minimum isoperimetry criteria. We show that our basic clustering algorithm runs in O(nlogn) and with post-processing in almost O(nlogn) (average case) and O(n2) (worst case) time where n is the size of the data-set. It is also shown that our generalized graph model, which also allows the use of potentials at vertices, can be used to extract an extra piece of information related to anomalous data patterns and outliers. In this regard, we propose an algorithm that extracts outliers in parallel to data clustering. We also provide a comparative performance analysis of... 

This paper introduces an alternative Fault-Tolerant Power-Aware Hybrid Adder (or simply FARHAD). FARHAD is a highly power efficient protection solution against errors in application with high number of additions. FARHAD, similar to earlier studies, relies on performing add operations twice to detect errors. Unlike previous studies, FARHAD uses an aggressive adder to produce the initial outcome and a low-power adder to generate the second outcome, referred to as the checker. FARHAD uses checkpointing, a feature already available to high-performance processors, to recover from errors. FARHAD achieves the high energy-efficiency of timeredundant solutions and the high performance of...