Sharif Digital Repository

Automatic image annotation is a challenging problem in the field of image retrieval. Dealing with large databases makes the annotation problem more difficult and therefore an effective approach is needed to manage such databases. In this work, an annotation system has been developed which considers images in separate categories and constructs a profiling model for each category. To describe an image, we propose a new feature extraction method based on color and texture information that describes image content using discrete distribution signatures. Image signatures of one category are partitioned using spectral clustering and a prototype is determined for each cluster by solving an... 

Computational intelligence (CI) as an offshoot of artificial intelligence (AI), is becoming more and more widespread nowadays for solving different engineering problems. Especially by embracing Swarm Intelligence techniques such as ant colony optimization (ACO), CI is known as a good alternative to classical AI for dealing with practical problems which are not easy to solve by traditional methods. Besides, electricity load forecasting is one of the most important concerns of power systems, consequently; developing intelligent methods in order to perform accurate forecasts is vital for such systems. This study presents a hybrid CI methodology (called ACO-GA) by integration of ant colony... 

The mathematical techniques of decision making are among the most valuable outcomes of this research activity, which is generally referred to as realization in the operations, operational research or quantitative methods of decision making. Over time, with the increase in the complexity and the variety of decision making problems, the methods of decision making become more varied and will have more capability of problem solving. Multi-Criteria Decision Making (MCDM) is a collection of methodologies to compare, select, or rank multiple alternatives that involve incommensurate attributes. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is a multiple criteria... 

A Hub Location Problem (HLP) deals with finding the locations of hub facilities and assignment of demand nodes to established facilities. Hubs play a central role in many networks such as telecommunication networks and their unavailability may lead to network breakdown or poor service levels. An objective in design of a hub-and-spoke network is maximization of reliability to transfer flows. This paper puts forward design of a reliable single-allocation hub-and-spoke network using an interactive fuzzy goal programming. To model and solve the problem, a fuzzy goal programming approach was developed for design of network in an interactive manner between decision maker and the model. To validate... 

In general, decomposition methods can facilitate the process of solving sophisticated and heterogonous problems in the area of software development and engineering. These approaches are assisting to decompose problems based on different disciplines, characteristics and functionalities that is results into increasing the computational efficiency (e.g. parallel processing/computing) and accelerate the software changing process, software modifications and error tracking. Essentially, these approaches contribute to the degree of modularity to decompose a complex problem into different sub-problems and to focus on local objectives. There are different approaches that are used to decompose a... 

The flowshop sequence dependent group scheduling problem with minimization of makespan as the objective (F m |fmls, S plk, prmu|C max ) is considered in this paper. It is assumed that several groups with different number of jobs are assigned to a flow shop cell that has m machines. The goal is to find the best sequence of processing the jobs in each group and the groups themselves with minimization of makespan as the objective. A mathematical model for the research problem is developed in this paper. As the research problem is shown to be NP-hard, a hybrid ant colony optimization (HACO) algorithm is developed to solve the problem. A lower bounding technique based on relaxing a few... 

This study presents a motion planning algorithm to generate a feasible periodic solution for a hybrid system describing running by a three-dimensional (3-D), three-link, three-actuator, monopedal robot. In order to obtain a symmetric running gait along a straight line, the hybrid system consists of two stance phases and two flight phases. The motion planning algorithm is developed on the basis of a finite-dimensional optimisation problem with equality and inequality constraints. By extending the concept of hybrid zero dynamics to running, the authors propose a time-invariant control scheme that is employed at two levels to locally exponentially stabilise the generated periodic solution for... 

Constrained clustering methods (that usually use must-link and/or cannot-link constraints) have been received much attention in the last decade. Recently, kernel adaptation or kernel learning has been considered as a powerful approach for constrained clustering. However, these methods usually either allow only special forms of kernels or learn non-parametric kernel matrices and scale very poorly. Therefore, they either learn a metric that has low flexibility or are applicable only on small data sets due to their high computational complexity. In this paper, we propose a more efficient non-linear metric learning method that learns a low-rank kernel matrix from must-link and cannot-link... 

The friction drive principle, which is based on the superposition of two synchronized perpendicular vibrations at the interface of the robot and the work floor, plays a fundamental role in the locomotion of miniaturized robots. In this paper, the iteration perturbation method proposed by He is used to generate a periodic solution for this type of friction drive microrobot. The equation of motion for the system reveals a parametrically excited oscillator with discontinuity, the elastic force term for which is proportional to a signum function. The obtained solutions are in excellent agreement with those achieved from numerical integration and experiments reported in the literature. Results... 

Instead of charging tolls on individual links, this paper considers doing the same on paths. Path and link tolls are "valid" if they encourage motorists to use routes that collectively lead to a target distribution, e.g., one that minimizes travel delay. Because the numbers of valid link and path tolls are typically infinite, an objective in pricing tolls is to find a set of valid tolls that yields the least revenue to lessen the financial burden on motorists.Path tolls are generally more flexible than link tolls and this paper shows that this flexibility can substantially reduce the financial burden on motorists. Additionally, valid path tolls yielding the least revenue possess... 

Abstract Several researchers have worked on transmitting a given amount of flow through a network flow within fastest possible time, allowing flow to be transmitted through one or more paths. Extending this problem to the system reliability problem, the quickest path reliability problem has been introduced. The problem evaluates the probability of transmitting some given amount of flow from a source node to a sink node through a single minimal path in a stochastic-flow network within some specified units of time. Later, the problem has been extended to allow flow to be transmitted through two or more separate minimal paths (SMPs). Here, we consider the problem of sending flow through two... 

This paper presents an optimisation model for polymer electrolyte membrane fuel cell system based on simultaneous power maximisation and cost minimisation. The results show that, by employing appropriate relation between the objectives, the innovative design could be proposed. Genetic algorithm is applied to solve the optimisation problem. Power maximisation results reveal that at maximum amount of power (1.95 kW), unit cost of energy is $0.64. In contrast, minimisation of cost decreases unit cost of energy to $0.33. In this condition, output power is reduced approximately to 0.93 kW. To consider both optimisation problems concurrently, weighting method and Pareto set are employed. Our... 

In this paper a new model is proposed for the integrated problem of supply chain network designing and assembly line balancing under demand uncertainty. In this problem there are three types of entities: manufacturers, assemblers and customers. Manufacturers provide assemblers with components and assemblers use these components to produce the final products and satisfy the demand of the customers. This problem involves determining the location of manufacturers and assemblers in the network, balancing the assembly lines, and transportation of materials and products throughout the network. A mixed integer nonlinear programming formulation based on two stage stochastic programming method is... 

In this paper, a multiproduct single vendor-single buyer supply chain problem is investigated based on the economic production quantity model developed for the buyer to minimize the inventory cost. The model to be more applicable for real-world supply chain problems contains five stochastic constraints including backordering cost, space, ordering, procurement, and available budget. The objective is to find the optimal order quantities of the products such that the total inventory cost is minimized while the constraints are satisfied. The recently-developed sequential quadratic programming (SQP), as one of the best optimization methods available in the literature, is used to solve the... 

Bi-objective optimization of a multi-product multi-period three-echelon supply-chain-network problem is aimed in this paper. The network consists of manufacturing plants, distribution centers (DCs), and customer nodes. To bring the problem closer to reality, the majority of the parameters in this network including fixed and variable costs, customer demand, available production time, set-up and production times, all are considered stochastic. The goal is to determine the quantities of the products produced by the manufacturing plants in different periods, the number and locations of the warehouses, the quantities of products transported between the supply chain entities, the inventory of... 

This article proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs swarm intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate. The main contribution of this article is to extend swarm intelligence algorithms to build a routing tree in such a way that it can be utilized to maximize efficiency, thereby rectifying the delay problem of compressive sensing theory and improving the network lifetime. In addition, our approach offers accurate data recovery from small amounts of compressed data. Simulation results show that our approach can effectively extend the... 

Forecasting stock price time series is very important and challenging in the real world because they are affected by many highly interrelated economic, social, political and even psychological factors, and these factors interact with each other in a very complicated manner. This article presents an approach based on Genetic Fuzzy Systems (GFS) for constructing a stock price forecasting expert system. We use a GFS model with the ability of rule base extraction and data base tuning for next day stock price prediction to extract useful patterns of information with a descriptive rule induction approach. We evaluate capability of the proposed approach by applying it on stock price forecasting... 

In this paper, the nonlinear dynamic response of an inclined pinned-pinned beam with a constant cross section, finite length subjected to a concentrated vertical force traveling with a constant velocity is investigated. The study is focused on the mode summation method and also on frequency analysis of the governing PDEs equations of motion. Furthermore, the steady-state response is studied by applying the multiple scales method. The nonlinear response of the beam is obtained by solving two coupled nonlinear PDEs governing equations of planar motion for both longitudinal and transverse oscillations of the beam. The dynamic magnification factor and normalized time histories of mid-pint of the... 

In this paper, we follow two control tasks in a leader following frame with undirected network and local communications. As the first goal, distributed behavioral imitation, which is necessary to fit agents with complicated motion equations in kinematic frames, is discussed. Providing real agents with behavioral controller makes them capable to act as a kinematic particle. The second goal is to design an active leading strategy for the LA to move the group on a predefined path. Both problems can be mathematically modeled in an affine form, which is the reason behind using a unique adaptive controller to solve them. The controller is based on a neuro-fuzzy structure with critic-based leaning... 

Some periodic and quasi-periodic pulse trains are emitted by different sources in the environment and a number of sensors receive them through a single channel simultaneously. We are often interested in separating these pulse trains for source identification at sensors. This identification process is termed as deinterleaving pulse trains. Deinterleaving pulse trains has wide applications in communications, radar systems, neural systems, biomedical engineering, and so on. This paper studies the deinterleaving problem with the assumption that both sources and sensors are fixed. In this study, the problem of deinterleaving pulse trains is modeled as a blind source separation (BSS) problem. To...