Sharif Digital Repository

The aim of the present study is to provide an Atlas of IRAN Offshore Renewable Energy Resources (hereafter called 'the Atlas') to map out wave and tidal resources at a national scale, extending over the area of the Persian Gulf and Sea of Oman. Such an Atlas can provide necessary tools to identify the areas with greatest resource potential and within reach of present technology development. To estimate available tidal energy resources at the site, a two-dimensional tidally driven hydrodynamic numerical model of Persian Gulf was developed using the hydrodynamic model in the MIKE 21 Flow Model (MIKE 21HD), with validation using tidal elevation measurements and tidal stream diamonds from... 

The goal of image segmentation is to find regions that represent objects or meaningful parts of objects. In this paper a new method is presented for color image segmentation which involves the ideas used for community detection in social networks. In the proposed method an initial segmentation is applied to partition input image into small homogeneous regions. Then a weighted network is constructed from the regions, and a community detection algorithm is applied to it. The detected communities represent segments of the image. A remarkable feature of the method is the ability to segments the image automatically by optimizing the modularity value in the constructed network. The performance of... 

A new face recognition method is proposed in this paper. The proposed method is based on fuzzy regularized linear discriminant analysis (FR-LDA) and combines the regularized linear discriminant analysis (R-LDA) and the fuzzy set theory. R-LDA is based on a new regularized Fisher's discriminant criterion, which is particularly robust against the small sample size problem compared to the traditional one used in LDA. In the proposed method, we calculate the membership degree matrix by Fuzzy K-nearest neighbor (FKNN) and then incorporate the membership degree into the definition of the between-class and within-class scatter matrices and get the fuzzy between-class and within-class scatter... 

Considering the wide spread locations of wind farms in Iran, it is important to develop a suitable decision support system (DSS) to fulfill proper management of wind farms. Extensive literature survey indicates that there are no integrated forms of DSS to manage a set of wind farms. The existing wind farms are performing independently, and there is no practical method for exchanging the online data. DSS can contribute to optimal operation of wind farms, operation and maintenance scheduling, pricing policy, etc. In this study, a geographic information system and RETSCREEN software were linked to the designed DSS to achieve a more suitable result. Also, a huge number of data are constantly... 

Considering the wide spread locations of wind farms in Iran, it is important to develop a suitable decision support system (DSS) to fulfill proper management of wind farms. Extensive literature survey indicates that there are no integrated forms of DSS to manage a set of wind farms. The existing wind farms are performing independently, and there is no practical method for exchanging the online data. DSS can contribute to optimal operation of wind farms, operation and maintenance scheduling, pricing policy, etc. In this study, a geographic information system and RETSCREEN software were linked to the designed DSS to achieve a more suitable result. Also, a huge number of data are constantly... 

In this paper, we propose a mapping from low level feature space to the semantic space drawn by the users through relevance feedback to enhance the performance of current content based image retrieval (CBIR) systems. The proposed approach makes a rule base for its inference and configures it using the feedbacks gathered from users during the life cycle of the system. Each rule makes a hypercube (HC) in the feature space corresponding to a semantic concept in the semantic space. Both short and long term strategies are taken to improve the accuracy of the system in response to each feedback of the user and gradually bridge the semantic gap. A scoring paradigm is designed to determine the... 

In this paper, we propose a novel method for extracting fiducial points (FPs) of electrocardiogram (ECG) signals. We propose the use of multi hidden Markov model (MultiHMM) as opposed to the traditional use of Classic HMM. In the MultiHMM method, each segment of an ECG beat is represented by a separate ergodic continuous density HMM. Each HMM has different state number and is trained separately. In the test step, the log-likelihood of two consecutive HMMs is compared and a path is estimated, which shows the correspondence of each part of the ECG signal to the HMM with the maximum log-likelihood. Fiducial points are estimated from the obtained path. For performance evaluation, the Physionet... 

In this paper, we propose a novel method for extracting fiducial points (FPs) of the beats in electrocardiogram (ECG) signals using switching Kalman filter (SKF). In this method, according to McSharry's model, ECG waveforms (P-wave, QRS complex and T-wave) are modeled with Gaussian functions and ECG baselines are modeled with first order auto regressive models. In the proposed method, a discrete state variable called “switch” is considered that affects only the observation equations. We denote a mode as a specific observation equation and switch changes between 7 modes and corresponds to different segments of an ECG beat. At each time instant, the probability of each mode is calculated and... 

This paper presents the SkipTree, a new balanced, distributed data structure for storing data with multidimensional keys in a peer-to-peer network. The SkipTree supports range queries as well as single point queries which are routed in O(log n) hops. SkipTree is fully decentralized with each node being connected to O(logn) other nodes. The memory usage for maintaining the links at each node is O(log n log log n) on average and O(log2 n) in the worst case. Load balance is also guaranteed to be within a constant factor. © Springer-Verlag Berlin Heidelberg 2005  

This paper explores software design methodologies in the context of creating a simulator and proposes a methodology to design and implement an event-based simulator namely Sim Met. SimMet is explored in the context of the development of a complex simulator for simulating real world conditions to use in science, technology and medicine and other simulations. In this paper we interested in event-based approach to create a real world with variety range of event possibilities. The paper first discusses the role of time concept as the cornerstone of a methodical analysis and design phase. In Sim Met we use an adaptation of object-oriented methodology to meet time and event concepts in creating a... 

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly... 

In real applications, there are situations where we need to model some problems based on uncertain data. This leads us to define an uncertain model for some classical geometric optimization problems and propose algorithms to solve them. The assigned version of the k-center problem for n uncertain points in a metric space is studied in this paper. The main approach is to replace each uncertain point with a clever choice of a certain point. We argue that the k-center solution for these certain replacements of our uncertain points, is a good constant approximation factor for the original uncertain k-center problem. This approach enables us to present fast and simple algorithms that give... 

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... 

Cardiovascular diseases are very common and are one of the main reasons of death. Being among the major types of these diseases, correct and in-time diagnosis of coronary artery disease (CAD) is very important. Angiography is the most accurate CAD diagnosis method; however, it has many side effects and is costly. Existing studies have used several features in collecting data from patients, while applying different data mining algorithms to achieve methods with high accuracy and less side effects and costs. In this paper, a dataset called Z-Alizadeh Sani with 303 patients and 54 features, is introduced which utilizes several effective features. Also, a feature creation method is proposed to... 

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... 

Identifying and measuring the impact and value of scientific output plays an important role in today's world of information overload. On one side, governments are trying to distribute research funds in ways that support research in strategically important fields, on the other side, researchers and scientists are seeking to access only relevant and quality information that have mainly worthy of their attention. Nowadays, countries are evaluated not only by their national products, military power, geographical area, etc., but also by such factors as the production and consumption of scientific information. Scientometric approaches are used to provide appropriate tools for evaluating scientific... 

There are a vast number of cloud service providers, which offer virtual machines (VMs) with different configurations. From the companies perspective, an appropriate selection of VMs is an important issue, as the proper service selection leads to improved productivity, higher efficiency, and lower cost. An effective service selection cannot be done without a systematic approach due to the modularity of requests, the conflicts between requirements, and the impact of network parameters. In this paper, we introduce an innovative framework, called PCA, to solve service selection problem in the hybrid environment of peer-assisted, public, and private clouds. PCA detects the conflicts between the... 

Labeling vertebral discs from MRI scans is important for the proper diagnosis of spinal related diseases, including multiple sclerosis, amyotrophic lateral sclerosis, degenerative cervical myelopathy and cancer. Automatic labeling of the vertebral discs in MRI data is a difficult task because of the similarity between discs and bone area, the variability in the geometry of the spine and surrounding tissues across individuals, and the variability across scans (manufacturers, pulse sequence, image contrast, resolution and artefacts). In previous studies, vertebral disc labeling is often done after a disc detection step and mostly fails when the localization algorithm misses discs or has false... 

This paper presents a method to determine material of an unknown sample object. The main objective of this study is to design a database for specifying material of an object. We produce the database for different materials which is subjected to different forces. For this purpose we use a Polyvinidilene Fluoride (PVDF) sensor which is a piezoelectric material. Also we study the effect of changing place of sensor on our study. The detailed design was performed using finite element method analysis. Furthermore, if we have an object which we do not know its material by use of this database we can find out what this object is and how much its Yanoung's modules is. This study will be suitable for... 

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...