Sharif Digital Repository

Evaluating architectures and choosing the correct one is a critical issue in software engineering domain, in accordance with extremely extension of architecturedriven designs. In the first years of defining architecture styles, some special quality attributes were introduced as their basic attributes. After a moment, by utilizing them in practice, some results were obtained confirming some of attributes; some others meanwhile were not witnessed. As software architecture construction process is dependent on and addressed by both usage conditions and quality attributes, in this paper a framework has been proposed to provide an environment and a platform that can cover evaluation of... 

This paper presents a new interpretable fuzzy classification system. Simulated annealing heuristic is employed to effectively investigate the large search space usually associated with classification problem. Here, two criteria are used to evaluate the proposed method. The first criterion is accuracy of extracted fuzzy if-then rules, and the other is comprehensibility of obtained rules. Experiments are performed with some data sets from UCI machine learning repository. Results are compared with several well-known classification algorithms, and show that the proposed approach provides more accurate and interpretable classification system. © 2009 IEEE  

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... 

The growth of database application usage requires DataBase Management Systems (DBMS) that are accessible, reliable, and dependable. One approach to handle these requirements is replication mechanism. Replication mechanism can be divided into various categories. Some related works consider two categories for replication mechanisms: heterogeneous and homogenous however majority of them classify them in three groups: physical, trigger-based and log based schema. Log-based replication mechanisms are the most widely used category among DBMS vendors. Adapting such approach for heterogeneous systems is a complex task, because of lack of log understanding in the other end. Semantic technologies... 

Today, communication science is advancing very rapidly; one of these advances is mobile location determination which means finding position of a mobile station. There are some methods to location determination; one of these methods is Signal Strength (Power of Arrivals). In this research, Mobile Location Determination using enhanced signature database method in a Location grid will be introduced; several ways for positioning error reduction will also be described. © 2009 IEEE  

The normalization theory in relational database design is a classical subject investigated in different papers. The results of these research works are the stronger normal forms such as 5NF, DKNF and 6NF. In these normal forms, there are less anomalies and redundancies, but it does not mean that these stronger normal forms are free of anomalies and redundancies. Each normal form discussion is based on a particular constraint. In this paper, we introduce relations which contain a new kind of constraint called "combinational constraint". We. distinguish two important kinds of this constraints, namely Strong and Weak. Also we classify the. Combinationally Constrained Relations as Single and... 

A discussion regarding speech accents will be given while describing a set of statistical signal processing methods for the modeling, analysis, synthesis, and morphing of English language accents. Accent morphing deals with the changing of the accent of a speech to a different accent. Accent itself is a distinctive pattern of pronunciation of speech within a community of people who belong to a national, geographic, or socioeconomic grouping. Then, the signal processing methodology for speech accent processing will be reviewed while the concept of an accent profile has been presented  

In this paper a new method for automatic word clustering is presented. We used this method for building n-gram language models for Persian continuous speech recognition (CSR) systems. In this method, each word is specified by a feature vector that represents the statistics of parts of speech (POS) of that word. The feature vectors are clustered by k-means algorithm. Using this method causes a reduction in time complexity which is a defect in other automatic clustering methods. Also, the problem of high perplexity in manual clustering methods is abated. The experimental results are based on "Persian Text Corpus" which contains about 9 million words. The extracted language models are evaluated... 

XML has emerged as a common standard for data exchange over the World Wide Web. One way to manage XML data is to use the power of relational databases for storing and querying them. So the hierarchical XML data should be mapped into flat relational structure. In this paper we propose an algorithm which maps DTD to relational schema and as well as content and structure it preserves the functional dependencies during the mapping process in order to produce relations with less redundancy. This is done by categorizing functional dependencies and introducing four rules to be applied to the relations created by the hybrid inlining algorithm according to each category. These rules will reduce... 

In this paper a novel method called Extended Two-Dimensional PCA (E2DPCA) is proposed which is an extension to the original 2DPCA. We state that the covariance matrix of 2DPCA is equivalent to the average of the main diagonal of the covariance matrix of PCA. This implies that 2DPCA eliminates some covariance information that can be useful for recognition. E2DPCA instead of just using the main diagonal considers a radius of r diagonals around it and expands the averaging so as to include the covariance information within those diagonals. The parameter r unifies PCA and 2DPCA. r=1 produces the covariance of 2DPCA, r=n that of PCA. Hence, by controlling r it is possible to control the... 

Spectral Subtraction (SS), as a speech enhancement technique, originally designed for improving quality of speech signal judged by human listeners. it usually improve the quality and intelligibility of speech signals, while the speech recognition systems need compensation techniques capable of reducing the mismatch between the noisy speech features and the clean models. This paper proposes a novel approach for solving this problem by considering the SS and the speech recognizer as two interconnected components, sharing the common goal of improved speech recognition accuracy. The experimental evaluations on a real recorded database and the TIMIT database show that the proposed method can... 

Many websites on the Internet offer services to people. They usually ask the users to fill the registration forms for using their services. Unfortunately, some vandalistic persons write programs which make automatic fake registration. For solving this problem, CAPTCHA (Completely Automated Public Turing test to tell Computers and Human Apart) systems are invented. These systems distinguish human users from computer programs. One of the CAPTCHA methods which is designed for Persian and Arabic users is Nastaliq CAPTCHA. In this method, the image of a Persian or Arabic word which is written in Nastaliq font is chosen from a dictionary, and it is shown to the users, then they are asked to type... 

Skin detection has different applications in computer vision such as face detection, human tracking and adult content filtering. One of the major approaches in pixel based skin detection is using Bayesian classifiers. Bayesian classifiers performance is highly related to their training set. In this paper, we introduce a new Bayesian classifier skin detection method. The main contribution of this paper is creating a huge database to create color probability tables and new method for creating skin pixels data set. Our database consists of about 80000 images containing more than 5 billions pixels. Our tests shows that the performance of Bayesian classifier trained on our data set is better than... 

The main concern of steganography (image hiding) methods is to embed a secret image into a host image in such a way that it causes minimum distortion to the host; to make it possible to extract a version of secret image from the host in such a way that the extracted version of secret image be as similar as possible to its original version (this should be possible even after usual attacks on the host image), and to provide ways of embedding secret images with larger size into a given host image. In this paper we propose a method that covers all above mentioned concerns by suggesting the idea of finding from an image data base, the most suitable host for a given secret image. In our method,... 

Background: It has been previously shown that palindromic sequences are frequently observed in proteins. However, our knowledge about their evolutionary origin and their possible importance is incomplete. Results: In this work, we tried to revisit this relatively neglected phenomenon. Several questions are addressed in this work. (1) It is known that there is a large chance of finding a palindrome in low complexity sequences (i.e. sequences with extreme amino acid usage bias). What is the role of sequence complexity in the evolution of palindromic sequences in proteins? (2) Do palindromes coincide with conserved protein sequences? If yes, what are the functions of these conserved segments?... 

In this paper, we present new adaptive linear discriminant analysis (LDA) algorithm and apply them for adaptive facial feature extraction. Adaptive nature of the proposed algorithm is advantageous for real world applications in which one confronts with a sequence of data such as online face recognition and mobile robotics. Application of the new algorithm on feature extraction from facial image sequences is given in three steps: i) adaptive image preprocessing, ii) adaptive dimension reduction and iii) adaptive LDA feature estimation. Steps 1 and 2 are done simultaneously and outputs of stage 2 are used as a sequence of inputs for stage3. The proposed system was tested on Yale and PIE face... 

A Comprehensive speech database is one of the important tools for developing speech recognition systems; these tools are necessary for telephony recognition, too. Although adequate databases for direct speech recognizers exist, there is not an appropriate database for telephony speech recognizers. Most methods suggested for solving this problem are based on building new databases which tends to consume much time and many resources; or they used a filter which simulates circuit switch behavior to transform direct databases to telephony ones, in this case resulted databases have many differences with real telephony databases. In this paper we introduce a framework for creating telephony speech... 

This study tries to characterize national transportation modes to assess balancing and sustainability. Using a pioneer measure for sustainable development (SD), and based on the conformity of the growths of all sectors with transportation modes, the countries are comparatively studied. The proposed measure, elasticity, for each pair of variables indicates the extent to which the two variables have been changing consistently. Indeed the elasticity values are measures of "harmonic development" reflecting sustainability. The study database consisted of key aspects of transportation sustainability in the form of national variables including transportation, economic, social and environmental... 

The mechanism of flow around a pier structure is so complicated that it is difficult to establish a general empirical model to provide accurate estimation for scour. Interestingly, each of the proposed empirical formula yields good results for a particular data set. Hence, in this study, alternative approaches, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), are proposed to estimate the equilibrium and time-dependent scour depth with numerous reliable data base. Two ANN models, multi-layer perception using back-propagation algorithm (MLP/BP) and radial basis using orthogonal least-squares algorithm (RBF/OLS), were used. The equilibrium scour depth was... 

Fuzzy systems have demonstrated their ability to solve different kinds of problems in various applications domains. Currently, there is an increasing interest to augment fuzzy systems with learning and adaptation capabilities. Two of the most successful approaches to hybridize fuzzy systems with learning and adaptation methods have been made in the realm of soft computing. Neural fuzzy systems and genetic fuzzy systems hybridize the approximate reasoning method of fuzzy systems with the learning capabilities of neural networks and evolutionary algorithms. The objective of this paper is to describe a fuzzy genetics-based learning algorithm and discuss its usage to detect intrusion in a...