Sharif Digital Repository

Recently, tree structures have become a popular way for storing and manipulating huge amount of data. Classification of these data can facilitate storage, retrieval, indexing, query answering and different processing operations. In this paper, we present C-Classifier and M-Classifier algorithms for rule based classification of tree structured data. These algorithms are based on extracting especial tree patterns from training dataset. These tree patterns, i.e. closed tree patterns and maximal tree patterns are capable of extracting characteristics of training trees completely and non-redundantly. Our experiments show that M-Classifier significantly reduces running time and complexity. As... 

This paper addresses the issue of finding and accessing desired items when a large amount of data items are concerned, by proposing some concepts based on Tree Search Structure -a hierarchical structure for information retrieval. The proposed concepts are applicable to several environments such as File Managers on PCs, help tree views, site maps, taxonomies, and cell phones. A software tool, FTS (File Tree Search), that is developed to utilize the proposed concepts is also presented  

Content base image retrieval is an important research field with many applications. In this paper we presents a new approach for finding similar images to a given query, in a general-purpose image database using content-based image retrieval. Color and texture are used as basic features to describe images. In addition, a binary tree structure is used to describe higher level features of an image. It has been used to keep information about separate segments of the images. The performance of the proposed system has been compared with the SIMPLIcity system using COREL image database. Our experimental results showed that among 10 image categories available in COREL database, our system had a... 

Epistemic uncertainty in seismic hazard analysis is traditionally addressed by utilizing a logic-tree structure with subjective probabilities for branches. However, many studies have argued that probability is not a suitable choice for addressing epistemic uncertainties; in particular in addressing the background knowledge supporting the probabilities. In this regard, the application of imprecise probability (IP) is investigated. It is discussed that IP could provide a flexible tool for a more objective presentation of experts' knowledge. Moreover, the importance of addressing the strength of knowledge and surprises relative to knowledge in seismic hazard analysis along with methods to do... 

In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes... 

One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement... 

One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameters were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement... 

In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes... 

One important problem proposed recently in the field of web mining is website classification problem. The complexity together with the necessity to have accurate and fast algorithms yield to many attempts in this field, but there is a long way to solve these problems efficiently, yet. The importance of the problem encouraged us to work on a new approach as a solution. We use the content of web pages together with the link structure between them to improve the accuracy of results. In this work we use Naïve-bayes models for each predefined webpage class and an extended version of Hidden Markov Model is used as website class models. A few sample websites are adopted as seeds to calculate... 

This paper introduces a novel scalable speech coding scheme based on embedded matrix quantization of LSF parameters in an LPC model. In the proposed quantizer, codewords are organized based on a tree structure through a cell-merging process, which leads to a fine-grain scalable coder at rates below 900 bps. Near natural sounding is achieved at very low rates by employing an efficient adaptive dual-band scheme to approximate the LPC excitation signals. Evaluation results, obtained from both overall quality measurement and intelligibility assessment, show that the proposed coder could be a reasonable choice for improving the bottom-line speech quality in low bit rates. © 2008 IEEE  

Overlay multicast has gained much attention in recent years as an alternative method to network layer multicast, especially for mobile ad hoc networks (MANETs). In this paper, we propose a new overlay multicast protocol to achieve simplicity of deployment, rapid adaptation of overlay structure when nodes move, and reduced delay. In our algorithm, to join or leave a multicast group, it is only sufficient for a member node to inform its first upstream member node. This updates the tree structure more rapidly when nodes move. In addition, join and leave delays are reduced and this makes the protocol suitable for multimedia multicasting in MANETs. Simulation results compared to that of ODMRP and... 

Epistemic uncertainty in seismic hazard analysis is traditionally addressed by utilizing a logic-tree structure with subjective probabilities for branches. However, many studies have argued that probability is not a suitable choice for addressing epistemic uncertainties; in particular in addressing the background knowledge supporting the probabilities. In this regard, the application of imprecise probability (IP) is investigated. It is discussed that IP could provide a flexible tool for a more objective presentation of experts' knowledge. Moreover, the importance of addressing the strength of knowledge and surprises relative to knowledge in seismic hazard analysis along with methods to do...