Sharif Digital Repository

Computational intelligence (CI) as an offshoot of artificial intelligence (AI), is becoming more and more widespread nowadays for solving different engineering problems. Especially by embracing Swarm Intelligence techniques such as ant colony optimization (ACO), CI is known as a good alternative to classical AI for dealing with practical problems which are not easy to solve by traditional methods. Besides, electricity load forecasting is one of the most important concerns of power systems, consequently; developing intelligent methods in order to perform accurate forecasts is vital for such systems. This study presents a hybrid CI methodology (called ACO-GA) by integration of ant colony... 

The past few years have witnessed a growing rate of attraction in adoption of Artificial Intelligence (AI) techniques to solve different engineering problems. Besides, Short Term Electrical Load Forecasting (STLF) is one of the important concerns of power systems and accurate load forecasting is vital for managing supply and demand of electricity. This study estimates short term electricity loads of Iran by means of Adaptive Neuro-Fuzzy Inference System (ANFIS), Artificial Neural Networks (ANN) and Genetic Algorithm (GA) which are the most successful AI techniques in this field. In order to improve forecasting accuracy, all AI techniques are equipped with preprocessing concept, and effects... 

Recognition and correction of inhomogeneous displacement caused by patient's movement has been recently discussed as an interesting topic in medical image processing. Considering consistency in general structure of the image during distortion, histogram could be employed as a fast implementation method in feature domain. Accordingly, attribute vectors could be defined for each pixel based on spatial features to find corresponding points in two images. Consequently a point-based and non-rigid transformation approach will be designed. A B-spline image registration has been applied to match those pairs with a defined smoothness factor. This algorithm is a step-by-step registration process... 

La0.3Sr0.7FeO3-δ (LSF) perovskite was prepared according to two methods: (1) applying new phenolic derivative of serine amino acid (L) as chelating agent, and (2) in absence of L as ligand-free perovskite (LFP). The newly prepared aminophenolic ligand L was fully characterized by 1H and 13C NMR, IR as well as elemental analysis while the LSF perovskite samples were characterized using the IR spectra, powder x-ray diffraction (PXRD) patterns, and SEM micrographs. The PXRD pattern obtained for the perovskite prepared by L (PPP) indicated on the presence of pure perovskite phase. The hydrogen permeation through PPP and LFP membranes with thickness of 1.0mm were measured as a function of... 

This paper presents a lossless data hiding method using coefficients of integer wavelet domain. The modification of selected small coefficients of the high frequency subbands are used to embed data. We use the histogram modification to intelligently select the proper coefficients for data hiding. Data embedding is done by processing these selected coefficients. We show that at low payload data hiding our method has comparable PSNR than the best known reversible data hiding techniques, while at higher payloads it has significant superiority on image quality. ©2007 IEEE  

Let G be a graph, and λ the smallest integer for which G has a nowherezero λ-flow, i.e., an integer λ for which G admits a nowhere-zero λ-flow, but it does not admit a (λ − 1)-flow. We denote the minimum flow number of G by Λ(G). In this paper we show that if G and H are two arbitrary graphs and G has no isolated vertex, then Λ(G ∨ H) ⩽ 3 except two cases: (i) One of the graphs G and H is K2 and the other is 1-regular. (ii) H = K1 and G is a graph with at least one isolated vertex or a component whose every block is an odd cycle. Among other results, we prove that for every two graphs G and H with at least 4 vertices, Λ(G ∨ H) ⩽ 3  

A systematic change of HZSM-5 (HZ5) as a catalyst of the methanol to aromatics (MTA) reaction was undertaken by employing a fixed-bed tubular-type reactor under ambient pressure, applying a weight hourly space velocity (WHSV) of 2 h-1 at 375 °C, as the first report on the application of low-Si/Al-ratio alkaline-[Mo,Na]-HZSM-5 in the MTA process. To characterize the surface and textural properties of the catalysts, powder X-ray diffraction (PXRD), nitrogen adsorption/desorption, temperature-programmed desorption of ammonia (NH3-TPD), pyridine-infrared spectroscopy (Py-IR), thermogravimetric analysis (TGA), and energy-dispersive X-ray (EDX) methods were employed. Gas chromatography (GC) and... 

Multiple Attribute Decision Making (MADM) addresses the problem of choosing an optimum choice containing the highest degree of satisfaction from a set of alternatives which are characterized in terms of their attributes. In order to make a decision or choose a best alternative, a decision maker (DM) is often asked to provide his/her preferences either on alternatives or on the relative weights of attributes or on both of them. In this paper some basic principles from data envelopment analysis (DEA) is used in order to extract the necessary information for solving an MADM problem. We will introduce a comprehensive yet efficient approach for accountable and understandable MADM. For obtaining... 

Intelligent solutions, based on artificial intelligence (AI) technologies, to solve complicated practical problems in various sectors are becoming more and more widespread nowadays. On the other hand, electrical load prediction is one of the important concerns of power systems so development of intelligent prediction tools for performing accurate predictions is essential. This study presents an intelligent hybrid approach called ACO-SA by hybridization of Ant Colony Optimization (ACO) and Simulated Annealing (SA). The hybrid approach consists of two general stages. At the first stage time series inputs will be fed into ACO and it performs a global search to find a globally optimum solution.... 

The interaction of [60]fullerene with a newly synthesized series of 17-to 21-membered macrocyclic ligands containing an O2N3-donor set has been investigated. The formation constants (K) arising from their complexation with [60]fullerene macrocycles, having various ring size, were measured in CHCl3 media by UV-visible spectroscopy applying Benesi-Hildebrand (BH) equation and their stoichiometries were also determined by the Job method. The best K value was measured for 20-membered ring macrocycle in which a 1:1 complexation stoichiometry with [60]fullerene was dominant. Furthermore, 1H NMR spectroscopy data reveled that the macrocylic ligand coordinates [60]fullerene via the nitrogen-donor... 

The voluminous of the e-mails are spam. Several algorithms are represented for spam detection based on batch learning. In this paper, a new algorithm based on incremental learning is introduced. The algorithm composes new knowledge from new training data with previous knowledge by combining classifiers based on weighted majority voting. The experiment results show that the proposed algorithm outperforms other related incremental algorithms and non-incremental algorithms  

This paper deals with estimation of fractional order and pole locator in fractional order systems. The estimation is based on Bode diagram of the system that is obtained using input and output measurements. Here the magnitude diagram is approximated with number of straight lines depending on the level of complexity and in consequence a very good estimation of fractional order and acceptable approximations of pole locators are determined. Relying on the proposed method, complexity of fractional order system identification which is mostly due to the estimation of fractional order is substantially resolved. Some example simulation results are provided to explain the work and show its... 

The present paper reports the spectroscopic investigations on the complexation of Cu(II) with two macrocyclic ligands bonded to [60]Fullerene (L1 and L2) measured in N-methylpyrrolidone (NMP) as solvent. On the basis of UV–vis-NIR spectroscopy applying Jobs method of continuous variation, typical 1:1 stoichiometries were established for the complexes of Cu(II) with L1, and L2. DFT calculations suggested that superior HOMO distributions spread over the nitrogen-donor (as well as somehow oxygen- donor in L2) groups of L1 and L2 macrocycles were the key factor for the observed Kb value enhancement. Thermodynamic stabilities for these complexes have also been determined employing... 

Incremental learning is a learning algorithm that can get new information from new training sets without forgetting the acquired knowledge from the previously used training sets. In this paper, an incremental learning algorithm based on ensemble learning is proposed. Then, an application of the proposed algorithm for spam filtering is discussed. The proposed algorithm called incremental RotBoost, assumes the environment is stationary. It trains new weak classifiers for newly arriving data, which are added to the ensemble of classifiers. To evaluate the performance of the proposed algorithm, several computer experiments are conducted. The results of computer experiments show the ability of... 

This paper deals with the identification of fractional-order systems through orthogonal rational functions. Fractional systems are characterized by their non-exponential aperiodic multimodes; therefore, fractional orthogonal rational functions provide better approximating models with fewer parameters. In spite of the fact that the Laguerre-based model is simple, it is, to some extent, deficient at high frequencies. Motivated by this objective, the use of a Legendre basis which has progressive pole locations and can be expected to perform better at high frequencies is studied  

A comparative investigation of the interaction of Cu(II) with a series of 15- to 19-membered mixed-donor dibenzo-substituted macrocyclic ligands, each incorporating an O2N2-donor set, has been carried out using UV-Visible studies in methanol. Although a ring size effect has been reported for a related series of Ni(II) complexes, no such metal ion discrimination has been reported for Cu(II) in terms of its binding constants with 14- to 17-membered macrocycles. Employing Job's method of continuous variation established 1:1 stoichiometry for the interaction between Cu(II) and 1-5. From UV-Visible studies applying the Benesi-Hildebrand equation, the binding constants (K) of Cu(II) with 1-5 were... 

Continuum-based modeling of nanostructures is an efficient and suitable method to study the behavior of these structures when the deformation can be considered homogeneous. This paper is concerned about multiscale nonlinear tensorial constitutive modeling of carbon nanostructures based on the interatomic potentials. The proposed constitutive model is a tensorial equation relating the second Piola-Kirchhoff stress tensor to Green-Lagrange strain tensor. For carbon nanotubes, some modifications are made on the planar representative volume element (RVE) to account for the curved atomic structure resulting a non-planar RVE. Using the proposed constitutive model, the elastic behavior of the... 

We have used a hierarchical multiscale modeling scheme for the analysis of cortical bone considering it as a nanocomposite. This scheme consists of definition of two boundary value problems, one for macroscale, and another for microscale. The coupling between these scales is done by using the homogenization technique. At every material point in which the constitutive model is needed, a microscale boundary value problem is defined using a macroscopic kinematical quantity and solved. Using the described scheme, we have studied elastic properties of cortical bone considering its nanoscale microstructural constituents with various mineral volume fractions. Since the microstructure of bone... 

A finite element-based hierarchical multiscale modeling scheme is presented and used for the analysis of nanotube-reinforced polymer composites. The scheme presented here consists of micro- and macroscale boundary value problems linked together using a computational homogenization scheme. Using the presented hierarchical multiscale scheme, we have studied nanotube-reinforced polymer composites, and the elastic properties are determined. Using different representative volume elements (RVEs) representing different volume fractions of aligned nanotubes, the effect of the nanotube volume fraction and the existence of an interphase layer on the effective elastic modulus of the nanocomposite are...