Sharif Digital Repository

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated with the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson channel with memory (under peak-power and total-power constraints). The outputs of a discrete Poisson channel with memory are Poisson distributed random variables with a mean comprising of a fixed additive noise and a linear combination of past input symbols. Assuming a maximum-likelihood (ML) decoder, we search for a codebook that has the smallest possible error probability. This problem is challenging because error probability of a code does not have a... 

A coding scheme for transmission of a bit maps a given bit to a sequence of channel inputs (called the codeword associated to the transmitted bit). In this paper, we study the problem of designing the best code for a discrete Poisson channel with memory (under peak-power and total-power constraints). The outputs of a discrete Poisson channel with memory are Poisson distributed random variables with a mean comprising a fixed additive noise and a linear combination of past input symbols. Assuming a maximum-likelihood (ML) decoder, we find the best codebook design by minimizing the error probability of the decoder over all codebooks. For the case of having only a total-power constraint, the... 

Active components in amplifiers generate noise. Thus, amplifiers too, produce noise at their output and, therefore, increase the input signal to noise ratio. This is an undesirable feature, more particularly when one is dealing with weak input signals already combined with noise. Thus, reducing amplifiers' noise becomes a necessity for some applications. To overcome this problem, one approach consists of improving electronic device technology. Another approach is the use of advanced techniques in designing low noise amplifiers by taking advantage of pulse shapers. Pulse shapers generally consist of calculated filters made of integrator(s) and differentiator(s) that limit properly the... 

The optimal design of complex systems in engineering requires pursuing rigorous mathematical modeling of the system's behavior as a function of a set of design variables to achieve goal-oriented design. Despite the success of current knee implants, the limited life span remains the main concern of this complex system. The mismatch between the properties of engineered biomaterials and those of biological materials leads to insufficient bonding with bone, stress shielding effects and wear problems (i.e. aseptic loosening). The use of a functionally graded material (FGM) for the femoral component of knee implants is attractive because the properties can be designed to vary in a certain pattern... 

In this paper, two different hybrid intelligent systems are applied to develop practical soft identifiers for modeling the tool-tissue force as well as the resulted maximum local stress in laparoscopic surgery. To conduct the system identification process, a 2D model of an in vivo porcine liver was built for different probing tasks. Based on the simulation, three different geometric features, i.e. maximum deformation angle, maximum deformation depth and width of displacement constraint of the reconstructed shape of the deformed body are extracted. Thereafter, two different fuzzy inference paradigms are proposed for the identification task. The first identifier is an adaptive co-evolutionary... 

Optimal control of large-scale uncertain dynamic systems with time delays in states is considered in this paper. For this purpose, a two-level strategy is proposed to decompose the large-scale system into several interconnected subsystems at the first level. Then optimal control inputs are obtained by minimization of convex performance indices in presence of uncertainties, in the form of states and interactions feedback. The solution is achieved by bounded data uncertainty problems, where the uncertainties are only needed to be bounded and it is not required to satisfy the so-called 'matching conditions'. At the second level, a simple substitution-type interaction prediction method is used... 

In this paper, the problem of scheduling commercial messages during the peak of viewing time of a TV channel is formulated as a combinatorial auction-based mathematical programming model. Through this model, a profitable and efficient mechanism for allocating the advertising time to advertisers is developed by which the revenue of TV channels is maximised while the effectiveness of advertising is increased. We developed a steady-state genetic algorithm to find an optimal or a near optimal solution for the proposed problem. A computational experiment was conducted for evaluating the efficiency of the proposed algorithm. A set of test problems with different sizes were generated, using the... 

In large-scale power systems, classical centralized control approaches may fail due to geographically distribution of information and decentralized controllers result in sub-optimal solution for load-frequency control (LFC) problems. In this paper, a two-level structure is presented to obtain optimal solution for LFC problems and also reduce the computational complexity of centralized controllers. In this approach, an interconnected multi-area power system is decomposed into several sub-systems (areas) at the first-level. Then an optimization problem in each area is solved separately, with respect to its local information and interaction signals coming from other areas. At the second-level,... 

The present study was aimed at developing a model to optimize the sizing parameters and farm layout of wind turbines according to the wind resource and economic aspects. The proposed model, including aerodynamic, economic and optimization sub-models, is used to achieve minimum levelized cost of electricity. The blade element momentum theory is utilized for aerodynamic modeling of pitch-regulated horizontal axis wind turbines. Also, a comprehensive cost model including capital costs of all turbine components is considered. An iterative approach is used to develop the optimization model. The modeling results are presented for three potential regions in Iran: Khaf, Ahar and Manjil. The optimum... 

The earned value is a leading technique in monitoring and analyzing project performance and project progress. Although, it allows exact measurement of project progress, and can uncover any time and cost deviations from the plan, its capability in reporting accepted level of deviation is not well studied. This study presented an approach to overcome this limitation by applying statistical quality control charts to monitor earned value indices. For this purpose, project time and cost performance indices of a real construction project were monitored regularly on individual control charts. The results were quite promising, and not only competed well against traditional approaches, but also... 

This paper presents a novel opposition-based self-adaptive modified gravitational search algorithm (OSAMGSA) for optimal reactive power dispatch and voltage control in power-system operation. The problem is formulated as a mixed integer, nonlinear optimization problem, which has both continuous and discrete control variables. In order to achieve the optimal value of loss, voltage deviation, and voltage stability index, it is necessary to find the optimal value of control variables such as the tap positions of tap changing transformers, generator voltages, and compensation capacitor. Therefore, this complicated problem needs to be solved by an accurate optimization algorithm. This paper... 

In this paper a replacement-repair model is developed to study a renewing free replacement warranty (RFRW) for a class of multi-state deteriorating repairable products. After a replacement, the product warranty is renewed. Two parameters affect the manufacturer's decision to minimally repair or replace a failed item: the product deterioration level at the time of failure and the remaining warranty time. We derive an optimal replacement-repair policy to minimise the expected warranty servicing cost per item sold. In the case of a product with two different working states, we are able to explicitly find the optimal values of the replacement-repair parameters using the Adomian decomposition... 

In this research, application of the Endurance Time (ET) method in performance-based design of structures with and without consideration of uncertainties is investigated and a practical optimum design procedure is proposed. The ET method is used as an analytical assessment tool because of its capabilities in response estimation with an affordable computational demand. In the first step of the proposed method, ET analysis is implemented in a multi-objective optimum design procedure in order to achieve a set of Pareto optimal designs. Optimization is conducted with respect to initial cost and expected life cycle cost using a deterministic approach. For each design alternative the median... 

In this paper, a generalized intelligent water drops algorithm (IWD) for solving robot path planning problem is proposed. The authors want to reduce the time of reaching the optimal solution as much as possible. To do this, some new heuristic operators and a multi section graph model of environment is introduced. The authors divide graph to equal sections and compare behaviour of the solutions (paths) in each section with behaviour of them in other sections. This comparison uses a fuzzy inference system. Base on this comparison, a fuzzy number is assigned to each part of solutions. This fuzzy number determines the worth of a solution in a section. Less worth solutions need more improvement.... 

In this paper, an optimal design is performed for powder die-pressing process based on the genetic algorithm approach. It includes the shape optimization of powder component, the optimal design of punch movements, and the friction optimization of powdertool interface. The genetic algorithm is employed to perform an optimal design based on a fixed-length vector of design variables. The technique is used to obtain the desired optimal compacted component by verifying the prescribed constraints. The numerical modeling of powder compaction simulation is applied based on a large deformation formulation, powder plasticity behavior, and frictional contact algorithm. A Lagrangian finite element... 

In this study, an inventory system consisting of a single product, one supplier, and multiple identical retailers is considered. Each retailer replenishes inventory from the supplier according to the well known (R,Q) policy. Transit times are constant and retailers face independent Poisson demand. The supplier utilizing the retailers' information in decision making for replenishment policy with a given order size starts with m initial batches (of size Q) and places an order in a batch of size Q to an outside source when a new order is placed. In this inventory system, excess demand is backordered, delayed orders are satisfied on a first-come first-serve basis, and no partial shipment is... 

As a cost-effective and reliable alternative to supply remote areas, standalone hybrid energy systems (HESs) are recently under investigation to address various concerns associated with technical, financial, and environmental issues. This paper presents a comprehensive algorithm that can simultaneously optimize the component size, operation strategy, and slope of the photovoltaic panels of a standalone HES using an improved variant of particle swarm optimization (PSO), designated as the passive congregation PSO. A new operation strategy is proposed based on the set points of the control system. The optimization algorithm determines the optimal values of the set points to efficiently optimize... 

The purpose of this paper is to develop a global optimization model, simplification schemes, and a heuristic procedure for the design of a shortcut-enhanced unidirectional loop aisle-network with pick-up and drop-off stations. The objective is to minimize the total loaded and empty trip distances. This objective is the main determinant for the fleet size of the vehicles, which in turn is the driver of the total life-cycle cost of vehicle-based unit-load transport systems. The shortcut considerably reduces the length of the trips while maintaining the simplicity of the system. The global model solves simultaneously for the loop design, stations' locations and shortcut design. We then develop... 

In this communication, a hybrid model based on Least Square Support Vector Machine (LSSVM) was constructed to predict CO2 corrosion rate. The input parameters of the model are temperature, CO2 partial pressure, flow velocity and pH. The data used for training and testing of the developed model are 612 and 109 data, respectively. In order to benefit LSSVM from Kernel learning, we compared three kernel functions to select the most efficient one. Furthermore, Coupled Simulated Annealing (CSA) optimization technique was adapted to choose the best optimal values of the model parameters. The results elucidate that Gaussian Kernel functions is the desired function which can afford high accuracy for... 

The aim of this study is to couple molten carbonate fuel cell (MCFC) stack with integrated gasification combined cycle fed by refinery residues, to remove CO2 from gas turbine exhaust gases that have CO2 emission rate of 14,200 ton/year. By applying multi-objective optimisation (MOO) using genetic algorithm, the optimal values of operating load and the corresponding values of objective functions are obtained. The MOO of the MCFC system regarding two scenarios is performed. The first scenario is minimisation of cost of electricity (COE) and CO2 emission rate. Objective functions of the second scenario are the same as in the first scenario while CO2 tax is taken into account. Results show that...