Sharif Digital Repository

Hub location problem arises where the flow has to be routed between a set of origins and destinations, but direct links between all nodes are impossible or too costly. In these situations, e.g. transportation and communication systems, hubs serve as transshipment points to collect, transfer, and distribute the flow. In hub location allocation problem, hubs are located and non-hub nodes are allocated to them. In this thesis, two different models of capacitated multiple allocation hub location problem are discussed. In the first model, flow collection of hubs from non-hub nodes and in the second model, sum of flow collection and distribution of hubs from/to non-hub nodes is addressed. The... 

Image segmentation has a huge amount of applications in machine vision, target detection, medical image processing, etc. In many medical researches such as Organ and Gland Volume Specification, Analysis of Anatomical Structures and Multimodal Image Registration, Organ
Segmentation is the first step of preprocessing.Since detection of diseases out of medical images depends on organ segmentation results,the segmentation process is done by experts which has a lot of disadvantages such as high time computation, high cost, etc. Hence, designing algorithms that can segment images with high accuracy and need minimum user interaction are desirable. So, in this thesis, a new
knowledge based... 

In parallel to the growing of population in Tehran metropolitan, air pollution in this city has become to a major problem. From which high concentration of pollutants have adverse effects on public health, accurate estimating and forecasting of concentrations for several days ahead, can provide the possibility to implement the management measures to reduce hazard and risks. Among the air pollution models, application of statistic models based on neural network in comparison to the traditional deterministic models are easier and less costly. In most studies, static models use a classical single MLP to predict one step ahead. For this purpose ANN models are required to estimate next value of... 

The objective of OCR systems is to retrieve machine-encoded text from a raster image. Despite the abundance of powerful OCR algorithms for English, there are not many for Farsi. Our proposed algorithm is comprised of pre-processing, line detection, sub-word detection and segmentation, feature extraction and classification. Furthermore, hardware implementation and acceleration of this system on a GPGPU is presented. This algorithm was tested on 5 fonts including Titr, Lotus,Yekan, Koodak and Nazanin and an average accuracy above 90% was achieved