Sharif Digital Repository

Minimum entropy control technique, an approach for controlling chaos without using the dynamical model of the system, can be improved by being combined with a nature-based optimization technique. In this paper, an ACO-based optimization algorithm is employed to minimize the entropy function of the chaotic system. The feedback gain of a delayed feedback controller is adjusted in the ACO algorithm. The effectiveness of the idea is investigated on suppressing chaos in the tapping-mode atomic force microscope equations. Results show a good performance. The PSO-based version of the minimum entropy control technique is also used to control the chaotic behavior of the AFM, and corresponding results... 

A new computational algorithm is introduced in the present study to solve multimaterial topology optimization problems. It is based on the penalization of the objective functional by the multiphase volume constrained Ginzburg-Landau energy functional. The update procedure is based on the gradient flow of the objective functional by a fractional step projected steepest descent method. In the first step, the new design is found based on the projected steepest descent method to ensure the reduction in the objective functional, simultaneously satisfying the control constraints. In the second step, regularization step, an H1 regularity of the solution is ensured while keeping the feasibility of... 

We propose an algorithm based on mutual information to address the problem of online reconstruction of dynamic MRI from partial k-space measurements. Most of previous compressed sensing (CS) based methods successfully leverage sparsity constraint for offline reconstruction of MR images, yet they are not used in online applications due to their complexities. In this paper, we formulate the reconstruction as a constraint optimization problem and try to maximize the mutual information between the current and the previous time frames. Conjugate gradient method is used to solve the optimization problem. Using Cartesian mask to undersample k-space measurements, the proposed method reduces... 

Smartening of contemporaneous power delivery systems in conjunction with increased penetration of vehicle to grid (V2G) technology, changes the way market participants play their role in the market operation to maximize their profit. In V2G technology, plug-in electric vehicles (PEV) have bidirectional power flows i.e. they can either inject power to the grid or draw power from it. In recent years, the V2G technology has found a world wild attention due to its important advantages such as the peak load reduction and providing system reserve, to name a few. The unit commitment (UC) is a power system operation problem which is used to find the optimal operation schedule of generation units.... 

In this paper, the problem of optimal tracking control for a container ship is addressed. The multi-input-multi-output nonlinear model of the S175 container ship is well established in the literature and represents a challenging problem for control design, where the design requirement is to follow a commanded maneuver at a desired speed. To satisfy the constraints on the states and the control inputs of the vessel nonlinear dynamics and minimize the heading error, a nonlinear optimal controller is formed. To solve the resulted nonlinear constrained optimal control problem, the Gauss Pseudospectral Method (GPM) is used to transcribe the optimal control problem into a Nonlinear Programming... 

Numerical modeling of the fully coupled phenomena of solid deformation-fluid flow in partially saturated porous media is of great interest in many branches of science and engineering. In this study, a new formulation based on one of the famous mesh-less methods, called Element-Free Galerkin (EFG), is developed to simulate the water and air movement through variably saturated soils. For this purpose, the governing partial differential equations including the equilibrium equation and mass conservation laws for each fluid phase are discretized in space using the same EFG shape functions. To enforce the essential boundary conditions, penalty method is employed. Temporal discretization is... 

A number of challenges including instability, nonconvergence, nonuniqueness, nonoptimality, and lack of a general guideline for inverse modelling have limited the application of automatic calibration by generic inversion codes in solving the saltwater intrusion problem in real-world cases. A systematic parameter selection procedure for the selection of a small number of independent parameters is applied to a real case of saltwater intrusion in a small island aquifer system in the semiarid region of the Persian Gulf. The methodology aims at reducing parameter nonuniqueness and uncertainty and the time spent on inverse modelling computations. Subsequent to the automatic calibration of the... 

The multivariate exponentially weighted moving average, MEWMA, control chart is an effective statistical tool for detecting small shifts in process mean vectors. On the one hand, the economic design process of a MEWMA control chart involves determining the main parameters of the chart, namely, the sample size n, the sampling interval h, the smoothing constant r, and the control limit L such that a quality cost function is minimized. On the other hand, the statistically constrained economic design of MEWMA chart is to determine the chart parameters such that a cost function is minimized while the statistical performance of the chart is maintained at a desire level. In this paper, the... 

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... 

Unit Commitment is the optimization process for minimizing the total cost of real power generation meeting the generating units and the system constraints. With the restructuring in power systems, the matter of great concern is the fuel cost and consequently electricity price increase in some hours of the day. Accordingly, the optimum performance of Demand Side Management (DSM) has been gaining great attention recently. In this paper, the effect of the optimum performance of Emergency Demand Response Program (EDRP) on the cost of the unit commitment problem considering the line flow constrains is scrutinized. Due to the fact that the simultaneous adoption of the unit commitment and demand... 

We consider a single-processor firm real-time (FRT) system with exponential interarrival and execution times for jobs with relative deadlines following a general distribution. The scheduling policy of the system is first-come first-served (FCFS) and the capacity of the system is arbitrary. This system is subject to an arbitrary-shaped time/utility function (TUF), which determines the accrued utility of each job according to its completion time. It is considered that the system power consumption at different working states is predetermined for each processor speed. We have proposed an exact analytical method for the calculation of specific performance and power-related measures of the system.... 

We consider nonlinear optimization problems constrained by a system of fuzzy relation equations. The solution set of the fuzzy relation equations being nonconvex, in general, conventional nonlinear programming methods are not practical. Here, we propose a genetic algorithm with max-product composition to obtain a near optimal solution for convex or nonconvex solution set. Test problems are constructed to evaluate the performance of the proposed algorithm showing alternative solutions obtained by our proposed model  

This paper examines the problem of determining optimal sensors trajectories for localization of a moving radio source based on Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) measurements in situations in which sensors are constrained both in their movements and regions of operation. By considering the movement of the source and constrained movement of the sensors, a constraint problem is formed which is solved to determine optimal trajectories of the sensors for source tracking. The validity of the proposed algorithm is assessed by two different simulation scenarios and the results verify its proper operation with estimation error decreasing in consecutive steps... 

In this paper, an Uzawa-type augmented Lagrangian contact formulation is presented for modeling frictional discontinuities in the framework of the X-FEM technique. The kinematically nonlinear contact problem is resolved based on an active set strategy to fulfill the Kuhn-Tucker inequalities in the normal direction of contact. The Coulomb's friction rule is employed to address the stick-slip behavior on the contact interface through a return mapping algorithm in conjunction with a symmetrized (nested) augmented Lagrangian approach. A stabilization algorithm is proposed for the robust imposition of the frictional contact constraints within the proposed augmented Lagrangian framework. Several... 

Due to the tight power envelope, in the future technology nodes it is envisaged that not all cores in a many-core chip can be simultaneously powered-on (at full performance level). The power-gated cores are referred to as Dark Silicon. At the same time, growing reliability issues due to process variations and soft errors challenge the cost-effective deployment of future technology nodes. This paper presents a reliability management system for Dark Silicon chips (dsReliM) that optimizes for reliability of on-chip systems while jointly accounting for soft errors, process variations and the thermal design power (TDP) constraint. Towards the TDP-constrained reliability optimization, dsReliM... 

In a MIMO (Multiple Input Multiple Output) radar system, proper design of transmit signal and receive filter is an advantageous tool to improve the detection performance. Thus, in this paper, we consider the problem of transmit code and receive filter design, in order to maximize the Signal to Noise Ratio (SNR) at the receiver while enforcing a similarity constraint between the transmit space-time code (STC) and a reference STC which has a desirable ambiguity function. We will show that by solving such constrained optimization problem through successive iterations, our proposed method leads to satisfactory results  

This paper presents a formulation of fuzzy optimization for uncertainties in natural gas in fuel constraints for hourly individual unit and total unit fuel consumptions. Security Constrained Unit Commitment (SCUC) is usually a mixed integer programming and gas load flow has a non-linear equation a genetic algorithm is proposed to solve natural gas transmission network. A fuzzy mixed integer programming optimization is briefly discussed and adapted to deal with security constrained unit commitment schedule. Finally, two case studies are investigated (IEEE 6-bus system with 7-node natural gas transmission grid and the IEEE 118-bus power system linked with 14-node gas transmission test system)... 

In this paper, we propose an optimized parameter selection procedure for rainbow table Time Memory Trade-Off (TMTO) attack with sequential online search. Unlike previous works that mainly deal with minimizing required memory in the rainbow table TMTO attack we simultaneously focus on the required memory and online search time. Our parameter selection technique is optimized regarding the minimization of the required memory subject to a certain success probability and a maximum online search time. Obtained results are two compact mathematical expressions for determining rainbow table TMTO attack parameters, number and length of chains. The application of our optimized parameter selection... 

Most lattice-based cryptographic schemes with a security proof suffer from large key sizes and heavy computations. This is also true for the simpler case of authentication protocols that are used on smart cards as a very-constrained computing environment. Recent progress on ideal lattices has significantly improved the efficiency and made it possible to implement practical lattice-based cryptography on constrained devices. However, to the best of our knowledge, no previous attempts have been made to implement lattice-based schemes on smart cards. In this article, we provide the results of our implementation of several state-of-the art lattice-based authentication protocols on smart cards and... 

We present a combined trust region-line search structured algorithm for solving constrained nonlinear least-squares problems. The approach is based on adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method of Coleman and Conn for nonlinearly constrained optimization problems. The structured adaptation also makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians. For robustness, we propose a new penalty parameter updating strategy and a specific line search strategy within the trust region, taking account of the least-squares objective and special structured considerations for the approximate projected...