Sharif Digital Repository

We explore the dictionary learning problem for sparse representation when the signals are dependent. In this paper, a first-order Markovian model is considered for dependency of the signals, that has many applications especially in medical signals. It is shown that the considered dependency among the signals can degrade the performance of the existing dictionary learning algorithms. Hence, we propose a method using the Maximum Log-likelihood Estimator (MLE) and the Expectation Minimization (EM) algorithm to learn the dictionary from the signals generated under the first-order Markovian model. Simulation results show the efficiency of the proposed method in comparison with the... 

In this study a hybrid method of neural networks-genetic algorithms is proposed and applied in an economical case study. The results of this study show that the proposed hybrid algorithm is a more efficient modeling approach compared to either a single neural network method or a single genetic algorithm approach. Since modeling based on the observed data is also employed in other fields of science, the application of the proposed method is not restricted only to economics. © 2008 Asian Network for Scientific Information  

OTIS-based architectures appear to have the potential to be an interesting option for future generations of multiprocessing systems. In this paper, we propose a new adaptive unicast routing algorithm and four software-based (unicast-based) broadcast algorithms for the wormhole switched OTI S-hypercube. We then present an empirical performance evaluation of these algorithms in OTIS-hypercube for different topologies, message length and traffic loads. © 2008 IEEE  

In this paper with the use of fuzzy genetic algorithm combination with evolutionary algorithms, as a method for local searching, it has been tried to exploit high capabilities of genetic algorithm, as a search algorithm, beside to other evolutionary algorithms, as local search algorithms, in order to increase efficiency of a rule learning system. For this purpose three hybrid algorithms have been used for solving the intrusion detection problem. These three algorithms are combination of genetic algorithm and SFL and PSO as three evolutionary algorithms which try to introduce efficient solutions for complex optimization problems by patterning from natural treatments. © 2007 IEEE  

We introduce kernel smoothing method to extract the global trend of a time series and remove short time scales variations and fluctuations from it. A multifractal detrended fluctuation analysis (MF-DFA) shows that the multifractality nature of TEPIX returns time series is due to both fatness of the probability density function of returns and long range correlations between them. MF-DFA results help us to understand how genetic algorithm and kernel smoothing methods act. Then we utilize a recently developed genetic algorithm for carrying out successful forecasts of the trend in financial time series and deriving a functional form of Tehran price index (TEPIX) that best approximates the time... 

We have investigated different algorithms for the simulation of kinetics of small systems. We have simulated the first order reversible reaction with the Gillespie, Gibson and Brack time simulation as a function of Poisson distribution and compared the results of three algorithms. We have also simulated intracellular viral kinetics for a genome with Gillespie and Poisson distribution algorithms  

Cryptography algorithms are a fundamental part of a cryptographic system that is designed and implemented to increase information security. They are the center of attention of experts in the information technology domains. Although the cryptography algorithms are implemented to attain the goals such as confidentially, integrity, and authenticity of designing, but other matters that must be noticed by designers include speed, resource consumption, reliability, flexibility, usage type, and so on. For the useful allocation of hardware, software, and human resources, it is important to identify the role of each of the factors influencing the design of cryptographic algorithms to invest in the... 

The three-dimensional multiple bin-size bin packing problem (3D-MBSBPP) has many practical applications in the logistic problems such as warehouse management, transportation planning and container loading. An efficient solution to the problem can have significant effects on reducing the transportation costs, improving the status and increasing the productivity and profitability of the companies. The mathematical models proposed for this problem are few in number and can, therefore, be expanded and improved much further. In this paper, based on the needs of a spare-part company in Iran, we developed a mathematical model for 3D-MBSBPP. This model takes into account the rotation of the boxes... 

Zamin, which is a high level artificial life environment have been successfully used as a test bed for a number of cognitive and AI studies. Here we have tried to test the evolution of a pleasure computing mechanism in Zamin's artificial creatures and have extended their mental capabilities to cover uncertainty in action selection mechanism. The results show some improvements in both genetic evolution process and learning capabilities. More specifically, we have evolved an internal pleasure system in Zamin creatures for the first time, quite unsupervised. In addition creatures could learn much more efficient behavioral patterns than what they could before  

Over the past decade, the power industry in many countries around the world has been undergoing massive changes to introduce competition. In power systems under transmission open access, an optimal schedule of generation of units to satisfy the demand at the minimum production and transmission costs with consideration of system operation constraints is an important issue. In this paper, a method for centralized economic dispatch in deregulated power systems is presented. The considered constraints are minimum and maximum power generation of units, capacity of transmission lines and ramp rate limits. Genetic algorithm is used to solve a nonlinear objective function. Simulations are performed... 

The evolution of communication and its consequences on living objects is a challenging subject for many researches. Due to lack of our knowledge about the real trend of this evolution, artificial life simulations can shed light on many dark points of this process. In this paper, we have used Zamin artificial life environment to test the emergence of a very simple form of communication. The usability of this new capability is tested by a simple test of coping with new environment  

Conventional implementation of multi-dimensional wavelet transform (e.g. 3-D wavelet) requires whether a high amount of "in access" memory or a continual access to slow memory of a processor which makes it infeasible for most applications. In this paper, we proposed a novel algorithm for computation of an n-D discrete wavelet transform (DWT) based on lifting scheme. In addition to benefits of lifting scheme (which causes a major reduction in computational complexity and performs the total computations in time domain), our real-time approach computes the coefficients for all kinds of 1st and 2 nd generation wavelets with short delay and optimized utilization of the slow and fast memories of a... 

In this paper, a new approach for behavior based architecture in mobile robot navigation in unknown environments is presented. In this approach, the general actions of a mobile robot are classified into three thoroughly separated tasks. Then, an individual fuzzy controller is designed and implemented for each task (behavior). Finally, a behavior selector is designed to switch between the robot tasks (behavior patterns) and manage all separated fuzzy controllers to navigate a mobile robot in a fully unknown environment. Another case considered in this paper is to test and examine the proposed algorithm in an environment including the static and dynamic (moving) obstacles. The most difficult... 

This article investigates optimization of long-term operation of hydrothermal power systems consisting of cascaded reservoirs. Due to stochasticity of reservoir inflows, demand for energy, and unit forced outages, the uncertainty of this system is so significant that reliability of demand satisfaction becomes an indispensable component of the modelling process. On the other hand, existence of stochastic parameters, especially in the case of cascaded reservoirs, makes the problem very difficult to solve by applying existing optimization techniques. A hybrid genetic algorithm with dynamic tuning of its control parameters is developed that incorporates real number encoding and an analytical... 

Using the recently developed ABS algorithm for solving linear Diophantine equations we give a representation of the solutions of a system of m linear integer inequalities in n variables, m ≤ n, with full rank coefficient matrix. We apply this result to solve linear integer programming problems with m ≤ n inequalities. © 2001 OPA (Overseas Publishers Association) N.V. Published by license under the Gordon and Breach Science Publishers imprint, a member of the Taylor & Francis Group  

The authors consider the Multi-Skilled Project Scheduling Problem (MSPSP) as a version of the Multi-mode Resource-Constrained Project Scheduling Problem (MRCPSP), which extends the well-known NP-hard Resource-Constrained Project Scheduling Problem (RCPSP). In the MSPSP, it is made up of activities, which require specific skills to be done. Moreover, resources are staff members who master fixed skill(s). Thus, each resource requirement of an activity corresponds to the number of persons doing the corresponding skill that must be assigned to the activity during its whole processing time. The authors focus on taking into account the setup times when performing work, depending on the appointment... 

In this paper, a new algorithm for solving the shortest loop design problem is presented. The shortest loop design problem is to find the shortest loop for an automated guided vehicle covering at least one edge of each department of a block layout. In this paper, first it is shown that this problem can be represented as a graph model. The properties of the presented model enable us to design a meta-heuristic based on ant colony system algorithm for solving the shortest loop design problem. Computational results show the efficiency of our algorithm in compare to the other techniques  

This research considers a flexible flowshop sequence-dependent group scheduling problem with minimization of total completion time. A mixed integer linear mathematical model for the research problem is developed. Since the research problem is shown to be strongly NP-hard, a metaheuristic algorithm based on memetic algorithm (MA) is proposed. A lower bounding method based on the Branch and Price algorithm is also proposed to evaluate the quality of the MA. In order to evaluate the performance of the proposed algorithms, random test problems, ranging in size from small, medium, to large are generated and solved by the MA and the lower bounding method. The results show that the average...