Sharif Digital Repository

This paper proposes a class of estimators for population correlation coefficient when information about the population mean and population variance of one of the variables is not available but information about these parameters of another variable (auxiliary) is available, in two phase sampling and analyzes its properties. Optimum estimator in the class is identified with its variance formula. The estimators of the class involve unknown constants whose optimum values depend on unknown population parameters. In earlier research it has been shown that when these population parameters are replaced by their consistent estimates the resulting class of estimators has the same asymptotic variance... 

The state estimation (SE) is a fundamental data processing algorithm used by the control centers of modern power networks. The most widely used state estimator is rooted to the weighted least squares (WLS) estimator which is not sufficiently robust to the gross errors in the measurements. This paper, presents a new robust algorithm for power system SE environments. The proposed approach not only has the comparative performance of the conventional loss function based on the estimator of the WLS additionally, it also considers loss function based on the quasi weighted least squares (QWLS) estimator. The performance analysis is evaluated on the ability of the state estimator for reducing the... 

The local oscillator phase noise can severely affect the performance of OFDM systems. In this paper a new method is presented for compensation of this phase noise. The method is based on the fact that the scattered pilots, which are used for channel estimation, are subject to the same phase error as the OFDM symbols. Least square approach is used to exploit the phase noise information that exists in the scattered pilots and compensate the phase noise on the OFDM symbols. Simulation results show that the method is very effective, especially in high SNR  

This work aims to propose a new technique that considerably helps enhance time and precision needed to identify "Inertia Parameters (IPs)" of a typical Autonomous Space-Robot (ASR). Operations might include, capturing an unknown Target Space-Object (TSO), "active space-debris removal" or "automated in-orbit assemblies". In these operations generating precise successive commands are essential to the success of the mission. We show how a generalized, repeatable estimation-process could play an effective role to manage the operation. With the help of the well-known Force-Based approach, a new "modular formulation" has been developed to simultaneously identify IPs of an ASR while it captures a... 

In this paper, a new multi-attribute T2 control chart is initially proposed to monitor multi-attribute processes based on a transformation technique. Then, the maximum likelihood estimator of a multivariate Poisson process change point is derived for unknown changes that are assumed to belong to a family of monotonic changes. Using extensive simulation experiments, the performance of the proposed change-point estimator is compared to the ones derived for step changes and linear-trend disturbances, when the true change types are step change, linear trends and multiple-step changes. We show when the type of the change is not known a priori, the proposed estimator is an appropriate choice,... 

Feature relevance estimation is one of the most successful techniques used for improving the retrieval results of a content-based image retrieval (CBIR) system based on users' feedbacks. In this class of approaches, the weights of the feature elements (FEs) are adjusted based on the relevance feedbacks (RFs) given by the users to reduce the so-called semantic gap in the underlying CBIR system. An analytical approach is proposed in this paper to convert the users' feedbacks to the appropriate FE weights by solving a constrained optimization problem. Experiments on a set of 11,000 images from the Corel database show that the proposed approach outperforms other existing short-term RF approaches... 

Since space diversity and frequency diversity are both efficient techniques in the radar applications, we propose in this paper a method for simultaneous usage of both techniques. On this basis, multi-frequency array radar in which all frequencies are used simultaneously to increase the number of targets that can be uniquely identified, is introduced and analyzed. First, the signal model for such a system is derived and then, it is shown how the use of multi-frequency signal can noticeably improve the parameter identifiability. Specifically, we show the maximum number of targets that can be uniquely identified by the multi-frequency array radar is L times that of its single-frequency array... 

Interfacial tension is one of the very important parameters in pharmacology science, chemical engineering and petroleum engineering. The interfacial tension between pure hydrocarbons and water is widely used in chemical and petroleum engineering and so that it is highly desirable to find its accurate values. In this study a new unique correlation has been developed based on a comprehensive database of pure hydrocarbons-water interfacial tension values which contained both aliphatic and aromatic compounds (32 different hydrocarbons) with pressure ranges of 0.1-300 MPa and temperature ranges of 252.44-550 K. The proposed correlation uses the density difference between pure hydrocarbon and... 

Multiple Discrete Continuous Extreme Value (MDCEV) has become popular in the past years. Yet, the model suffers from an ‘empirical identification’ issue that is mainly due to inter-relations between two of its parameters, α and γ. This paper presents a hybrid optimization paradigm (named HELPME) to address this issue in a basic MDCEV formulation and take full advantage of the model by estimating a ‘mixed-profile.’ HELPME benefits from a coarse-to-fine search strategy, in which a customized Electromagnetism-like meta-heuristic precedes a gradient-based approach. The Atlanta Regional Travel Survey (2011) is used to empirically analyze performance of HELPME as well as significance of the... 

In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and... 

Purpose: The purpose of this study is to determine why female labor force participation in Iran has been less than 20 percent. Design/methodology/approach: The authors estimate a structural dynamic matching model of female participation using individual panel data in Iran. The study incorporates many factors such as wage, child cost, education, spouse employment and job market search parameters. Findings: The study finds that gender discrimination in job finding has the biggest effect in reducing the rate of women's participation. If all market differences disappear, the female participation rate will increase by 12 percentage points to almost 27 percent, which is still much lower than that... 

This paper presents a hierarchically distributed algorithm for the execution of distribution state estimation function in active networks equipped with some phasor measurement units. The proposed algorithm employs voltage-based state estimation in rectangular form and is well-designed for large-scale active distribution networks. For this purpose, as the first step, the distribution network is supposed to be divided into some overlapped zones and local state estimations are executed in parallel for extracting operating states of these zones. Then, using coordinators in the feeders and the substation, the estimated local voltage profiles of all zones are coordinated with the local state... 

This paper illustrates the control of chaos using a fuzzy estimating system based on batch training and recursive least square methods for a continuous time dynamic system. The fuzzy estimator system is trained on both Ott-Geobogi-Yorke (OGY) control algorithm and Pyragas's delayed feedback control algorithm. The system, considered for this study, is a Bonhoeffer-van der Pol (BVP) oscillator. It is found that the implemented fuzzy control system constructed on OGY algorithm results in smaller control transient response than that of the OGY control algorithm itself. The transient response of Pyragas fuzzy control does not show a significant improvement in compare to the Pyragas control... 

A simple optimization methodology is applied to estimate the intrinsic kinetic parameters for both reversible and irreversible unireactant immobilized enzyme systems that follow the Michaelis-Menten mechanism. The method utilizes a direct-search optimization algorithm along with the numerical solution of the governing differential equations. The usefulness and validity of the method is demonstrated by comparing the predicted values of the intrinsic kinetic constants using the proposed method with a series of experimental values reported in the literature for different immobilized enzyme systems with irreversible and reversible reactions  

This paper deals with integral based methods to estimate the order and parameters of simple fractional order models from the extracted noisy step response data of a process. This data can be obtained from both open-loop and closed-loop tests. Numerical simulation results are presented to verify the robustness of these proposed methods in the presence of the measurement noise  

The goal of robust parameter estimation is developing a model which can properly fit to data. Parameter estimation of a geometric model, in presence of noise and error, is an important step in many image processing and computer vision applications. As the random sample consensus (RANSAC) algorithm is one of the most well-known algorithms in this field, there have been several attempts to improve its performance. In this paper, after giving a short review on existing methods, a robust and efficient method that detects the gross outliers to increase the inlier to outlier ratio in a reduced set of corresponding image points is proposed. It has a new hypothesis and verification scheme which... 

The goal of robust parameter estimation is developing a model which can properly fit to data. Parameter estimation of a geometric model, in presence of noise and error, is an important step in many image processing and computer vision applications. As the random sample consensus (RANSAC) algorithm is one of the most well-known algorithms in this field, there have been several attempts to improve its performance. In this paper, after giving a short review on existing methods, a robust and efficient method that detects the gross outliers to increase the inlier to outlier ratio in a reduced set of corresponding image points is proposed. It has a new hypothesis and verification scheme which... 

This paper explores the transferability of the Multiple Discrete-Continuous Extreme Value (MDCEV) model for activity type and duration using various transfer methods and sample sizes. This study employs the data of travel demand studies in two major cities, Shiraz and Mashhad in Iran. The model is first developed for Shiraz and then transferred to Mashhad. The adopted transfer methods are transfer scaling, Bayesian updating, combined transfer estimation, and joint context estimation. Aggregate and disaggregate transfer measures are adopted to examine the transferred models' general prediction and policy predictability. The results indicate the joint context estimation method's superiority in... 

Harmonic State Estimation (HSE) is a technique for identifying harmonic distributions in power systems with limited measurements. The main problem in HSE is the optimal placement of measurement meters such that the estimation error is minimized, while making the system fully observable. The second issue is the HSE method. This method must be accurate and fast enough in order to have an accurate HSE. This paper presents a new algorithm that uses minimum variance criterion (MVC) and a sequential method for optimal meters placement, SVD method for observability analysis and finally WLS method for harmonic estimation. The proposed method minimizes the number of measurement devices and the error...