Sharif Digital Repository

Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in... 

k-medoids algorithm is a partitional, centroid-based clustering algorithm which uses pairwise distances of data points and tries to directly decompose the dataset with n points into a set of k disjoint clusters. However, k-medoids itself requires all distances between data points that are not so easy to get in many applications. In this paper, we introduce a new method which requires only a small proportion of the whole set of distances and makes an effort to estimate an upperbound for unknown distances using the inquired ones. This algorithm makes use of the triangle inequality to calculate an upper-bound estimation of the unknown distances. Our method is built upon a recursive approach to... 

Recently, the problem of integrating side information about classes has emerged in the learning settings like zero-shot learning. Although using multiple sources of information about the input space has been investigated in the last decade and many multi-view and multi-modal learning methods have already been introduced, the attribute learning for classes (output space) is a new problem that has been attended in the last few years. In this paper, we propose an attribute learning method that can use different sources of descriptions for classes to find new attributes that are more proper to be used as class signatures. Experimental results show that the learned attributes by the proposed... 

In this study, biocompatible ceramic layers containing TiO2 and hydroxyapatite (HA) nanoparticles (TiO2/HA) were deposited on pure commercial titanium (Grade 2) by using plasma electrolytic oxidation and AC power supply. The coating process was carried out in five different solutions for various times at a current density of 500 mA cm−2. To achieve the optimum conditions for thickness and microstructure, the coating process was conducted in solutions with a 3 g L−1 concentration of HA nanoparticles. FESEM, XRD, and FTIR results showed that HA nanoparticles were successfully incorporated into the pores of the layer. Furthermore, the corrosion behavior of the coating layers in the simulated... 

Although GAN-based methods have received many achievements in the last few years, they have not been entirely successful in generating discrete data. The most crucial challenge of these methods is the difficulty of passing the gradient from the discriminator to the generator when the generator outputs are discrete. Despite the fact that several attempts have been made to alleviate this problem, none of the existing GAN-based methods have improved the performance of text generation compared with the maximum likelihood approach in terms of both the quality and the diversity. In this paper, we proposed a new framework for generating discrete data by an adversarial approach in which there is no... 

Background: We developed transformer-based deep learning models based on natural language processing for early risk assessment of Alzheimer’s disease from the picture description test. Methods: The lack of large datasets poses the most important limitation for using complex models that do not require feature engineering. Transformer-based pre-trained deep language models have recently made a large leap in NLP research and application. These models are pre-trained on available large datasets to understand natural language texts appropriately, and are shown to subsequently perform well on classification tasks with small training sets. The overall classification model is a simple classifier on... 

There is a global tendency towards using Distributed Generation (DG) and renewable energy resources. Considering low utilization cost and low undesirable environmental effects, wind farms have become a considerable resource for producing electrical energy in many countries. Since Wind farms are not programmable and their power output which depends on weather and wind speed is uncertain, they create problems for utilizing electricity system. There are different methods for preserving system stability against the uncertainty of wind power plants. Optimal utilization of pumped storage and gas resources is one of the approaches for reducing production risk of wind farms. In this paper, it is... 

In many real-world applications, data contain heterogeneous input modalities (e.g., web pages include images, text, etc.). Moreover, data such as images are usually described using different views (i.e. different sets of features). Learning a distance metric or similarity measure that originates from all input modalities or views is essential for many tasks such as content-based retrieval ones. In these cases, similar and dissimilar pairs of data can be used to find a better representation of data in which similarity and dissimilarity constraints are better satisfied. In this paper, we incorporate supervision in the form of pairwise similarity and/or dissimilarity constraints into... 

One of the most studied problems in machine learning is finding reasonable constraints that guarantee the generalization of a learning algorithm. These constraints are usually expressed as some simplicity assumptions on the target. For instance, in the Vapnik–Chervonenkis (VC) theory the space of possible hypotheses is considered to have a limited VC dimension One way to formulate the simplicity assumption is via information theoretic concepts. In this paper, the constraint on the entropy H(X) of the input variable X is studied as a simplicity assumption. It is proven that the sample complexity to achieve an ∊-δ Probably Approximately Correct (PAC) hypothesis is bounded by [Formula... 

In restructured and de-regulated power systems, generating companies (Gencos) are responsible for supplying electricity for both energy and reserve markets, which usually operate simultaneously. In this condition, the question is how much and for what price must each Genco generate for each market to maximize its profit, so this paper intends to answer to this question. In this paper, first, the combined energy and reserve markets are considered, and the Nash equilibrium points are determined. Then, the bidding strategies for each Genco at these points will be presented. The bids for the energy and 10 min spinning reserve (TMSR) markets are separated in the second stage, and again, the... 

In the restructured power systems, generating companies (Genco) are responsible for selling their product in the energy market. In this condition, the question is how much and for what price must each Genco generate to maximize its profit. Therefore, this paper intends to propose a rational method to answer this question. In the proposed methodology, the hourly forecasted market clearing price (FMCP) is used as a reference to model the possible and probable price strategies of Gencos. The forecasted price is the basis of the bidding strategies of each Genco, which can be achieved by solving a bi-level optimization problem using GAMS (general algebraic modeling system) language. The first... 

In the restructured power systems, they are typically scheduled based on the offers and bids to buy and sell energy and ancillary services (AS) subject to operational and security constraints. Generally, no account is taken of unit reliability when scheduling it. Therefore generating units have no incentive to improve their reliability. This paper proposes a new method to obtain the equilibrium points for reliability and price bidding strategy of units when the unit reliability is considered in the scheduling problem. The proposed methodology employs the supply function equilibrium (SFE) for modeling a unit's bidding strategy. Units change their bidding strategies and improve their... 

On pool market structure, the generating units are typically dispatched in order of lowest to highest bid as needed to meet demand requirement as well as considering network constraints. Generally, no account is taken of generating unit's reliability when scheduling them. This paper proposes a new structure for electricity market to consider generating unit's reliability in the scheduling problem. GAMS (General Algebraic Modeling System) language has been used to solve the social welfare maximization problem using CPLEX optimization software with mixed integer programming. ©2006 IEEE  

This paper presents a new method to analyze the bidding strategies of Generating Companies (GENCOs) with regard to demand elasticity. It is assumed that the available information of each GENCO about its opponents is incomplete and only the minimum and maximum generation levels of their opponents, as well as their fuel type, are known. In the proposed methodology, GENCOs prepare their strategic bids according to a Supply Function Equilibrium (SFE) model. GENCOs will change their bidding strategies until Nash equilibrium points are obtained. The general Algebraic Modeling System (GAMS) has been used to solve the maximization modules using the MINOS optimization software with non Linear... 

Multicarrier energy systems have provided the opportunity for users who are experiencing only must-run loads to participate in demand response programs by using self-generation units. In this paper, a bilevel game between so-called energy retailers and consumers with firm loads (as subsystems) is formulated in a multicarrier energy system. In the first level of this game, energy retailers offer selling prices for different energy carriers to maximize their profit. Consequently, consumers react to the offered prices by managing their purchasing power from the retail market to minimize their energy bill in the second level. The proposed approach leads to a mixed integer nonlinear programming... 

Colloidal gas aphron (CGA) based fluids have recently been introduced to develop depleted hydrocarbon reservoirs due to their ability in controlling fluid losses. Bubbles size of CGAs plays an important role in pore blockage ability as the controlling mechanism in fluid invasion reduction. However, fundamental understanding of how bubble size distribution is controlled by polymer and surfactant concentrations is not well discussed in the available literature. Almost all reported experiences on CGAs sizing were conducted on single bubble behavior, and little attention has been given to the variation of bubble size distribution (BSD) of CGAs at different levels of polymer/surfactant... 

Recently, Colloidal Gas Aphron (CGA) based fluids have been introduced to further develop depleted hydrocarbon reservoirs. This fluid system has been employed in an attempt to control drilling fluid invasion and, thus, reducing formation damage occurred during drilling operations. Understanding the mechanisms of fluid invasion control is of great importance for successful design and application of CGA-based fluids in drilling operations. Although fluid flow of conventional foams has been studied extensively in the available literature, little attention has been paid to CGA fluids flow, especially in heterogeneous fractured porous media. Here, an experimental study was conducted to achieve... 

Multicarrier energy systems have provided the opportunity for users who are experiencing only must-run loads to participate in demand response programs by using self-generation units. In this paper, a bilevel game between so-called energy retailers and consumers with firm loads (as subsystems) is formulated in a multicarrier energy system. In the first level of this game, energy retailers offer selling prices for different energy carriers to maximize their profit. Consequently, consumers react to the offered prices by managing their purchasing power from the retail market to minimize their energy bill in the second level. The proposed approach leads to a mixed integer nonlinear programming... 

Recently, colloidal gas aphron (CGA) fluids technology has been employed to drill depleted oil and gas reservoirs. Almost all reported experience on CGA fluids were conducted at ambient conditions, and little attention has been paid on the behavior of CGAs at high pressures which is more close to real conditions. In this study, high pressure experiments were conducted by using High Pressure Microscope cell to visualize/monitor the behavior of CGAs at elevated pressures. Single bubble behavior and bubble size distribution (BSD) of CGAs were investigated under different scenarios of pressure change. Results of experiments revealed that BSD of CGAs is controlled by the path of pressure changes,...