Sharif Digital Repository

This study deals with the problem of outlier censoring from the secondary data in a radar scenario, where the number of outliers is unknown. To this end, a procedure consisting of joint likelihood estimation and statistical model order selection (MOS) is proposed. Since the maximum likelihood (ML) estimation of the outlier subset requires to solve a combinatorial problem, an approximate ML (AML) method is employed to reduce the complexity. Therefore, to determine the number of outliers, different MOS criteria based on likelihood function are applied. At the analysis stage, the performance of the proposed methods is assessed based on simulated data. The results highlight that the devised... 

Modeling the mechanical behavior of asphalt binders and mixtures has been the subject of intensified research in recent decades. Master curves of the norm of the complex modulus |G*| in the linear viscoelastic domain are frequently used for modeling, while phase angle master curves are less frequently considered for this purpose. Therefore in this research, an empirical model is introduced for phase angle master curves of modified and neat bituminous binders. The model is based on a general form of a double-logistic (DL) mathematical function. The |GG*| master curve was then modeled using a mutual relationship between the phase angle and |GG*|. Master curves of three neat and seven modified... 

We study learning algorithms when there is a mismatch between the distributions of the training and test datasets of a learning algorithm. The effect of this mismatch on the generalization error and model misspecification are quantified. Moreover, we provide a connection between the generalization error and the rate-distortion theory, which allows one to utilize bounds from the rate-distortion theory to derive new bounds on the generalization error and vice versa. In particular, the rate-distortion-based bound strictly improves over the earlier bound by Xu and Raginsky even when there is no mismatch. We also discuss how 'auxiliary loss functions' can be utilized to obtain upper bounds on the... 

Reconfigurability in software has many advantages such as updating, bug fixing and adding new services. Dynamic reconfiguration is more useful for mission critical systems that need to change in run time. Reconfiguration of a system in network may result to reconfiguring its dependent systems, which we call reconfiguration propagation. In this paper, we present a model for reconfiguration propagation for systems in a network  

In this paper, a wide area measurement, centralized, load frequency control using model predictive control (MPC) is presented for multi-area power systems. A multivariable constrained MPC was used to calculate optimal control actions including generation rate constraints. To alleviate computational effort and to reduce numerical problems, particularly in large prediction horizon, an exponentially weighted functional MPC was employed. Time-based simulation studies were performed on a three-area power system, and the results were then compared with decentralized MPC and classical PI controller. The results show that the proposed MPC scheme offers significantly better performance against load... 

Background: Codon degeneracy and codon usage by organisms is an interesting and challenging problem. Researchers demonstrated the relation between codon usage and various functions or properties of genes and proteins, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Researchers usually represent segments of proteins responsible for specific functions or structures in a family of proteins as sequence patterns or motifs. We asked the question if organisms use the same codons in pattern segments as compared to the rest of the sequence. Methods. We used the likelihood ratio test, Pearson's chi-squared test, and mutual information... 

Miniaturized culture systems of hepatic cells are emerging as a strong tool facilitating studies related to liver diseases and drug discovery. However, the experimental optimization of various parameters involved in the operation of these systems is time-consuming and expensive. Hence, developing numerical tools predicting the function of such systems can significantly reduce the associated cost. In this paper, a perfusion-based three dimensional (3D) bioreactor comprising encapsulated human liver hepatocellular carcinoma (HepG2) spheroids are analyzed. The flow and mass transfer equations for oxygen as well as different metabolites such as albumin, glucose, glutamine, ammonia, and urea were... 

System Identification is a key technology for the development and integration of modern engineering systems including gas turbines. These systems are highly parametric with complex dynamics and nonlinearities. Small turbojet engines are special class of gas turbines that are suitable for scientific purposes and researches in the area of stability, performance, simulation and fuel control design. The motivation behind the presented study is to improve the speed, quality and cost of engine testing and to gain insight into alternatives to traditional identification methods for gas turbines. It discusses the identification of small turbojet engine dynamics by validating the thermodynamic model... 

In This paper detailed frequency-domain system identification method is applied to identify steering dynamics of a naval coastal patrol vessel using a data analysis software tool, called CIFER. Advanced features such as Chirp-Z transform and composite windowing techniques are used to extract high quality frequency responses. An accurate, linear and robust transfer function models are derived for yaw and roll dynamics of the vessel. In addition, to evaluate the accuracy of the identified model, time-domain responses from a 45-45 zig-zag test are compared with the responses predicted by the identified model. The model shows excellent predictive capability that is well suited for simulation... 

In this paper, a new model reference adaptive controller (MRAC) for uncertain switched linear systems is developed. A class of uncertain switched linear systems with parametric mismatched and input matched uncertainties, control input effectiveness and unmodeled dynamics is studied in this paper. The difference in input matrix for different switching modes which means the input channel degradation is investigated through this paper. By using common Lyapunov function method and developing new linear matrix inequality based sufficient conditions, uniform ultimate boundedness of the reference tracking error is guaranteed by switched MRAC and by using a novel nonlinear controller term, the size... 

Water quality is one of the most important factors contributing to a healthy life. From the water quality management point of view, TDS (total dissolved solids) is the most important factor and many water developing plans have been implemented in recognition of this factor. However, these plans have not been perfect and very successful in overcoming the poor water quality problem, so there are a good volume of related studies in the literature. We study TDS and the water flow of the Karoun river in southwest Iran. We collected the necessary time series data from the Harmaleh station located in the river. We present two Univariate Seasonal Autoregressive Integrated Movement Average (ARIMA)... 

A probabilistic method is presented for identifying the dynamic soil-foundation stiffnesses of building structures. It is based on model updating of a Timoshenko beam resting on sway and rocking springs, which respectively represent the superstructure and the soil-foundation system. Unlike those previously employed for this particular problem, the proposed method is a Bayesian one, which accounts for the prevailing uncertainties due to modeling and measurement errors. As such, it yields the probability distribution of the system parameters as opposed to average/deterministic values. In this approach, the joint probability density function of the parameters that control the flexible-base... 

In this paper, a distributed model predictive control is proposed to control Lipschitz nonlinear systems. The cooperative distributed scheme is considered where a global infinite horizon objective function is optimized for each subsystem, exploiting the state and input information of other subsystems. Thus, each control law is obtained separately as a state feedback of all system's states by solving a set of linear matrix inequalities. Due to convexity of the design, convergence properties at each iteration are established. Additionally, the proposed algorithm is modified to optimize only one control input at a time, which leads to a further reduction in the computation load. Finally, two... 

In this paper, a study is conducted to determine the influences of perforated anchors on heat transfer intensification of turbulence nanofluid flow in a pipe. Six different turbulence models are used, and the results obtained by these models are benchmarked with the existing theoretical data to select the best turbulence model. The outputs showed that the k–ε–RNG–scalable wall function model has higher accuracy and so it is selected to simulate this problem. The influences of various parameters including the addition of perforation on the anchors, the perforation diameter (in the range of 1–5 mm), the Re number (in the range of 5000–25,000), and the volumetric concentration of nanoparticles...