Sharif Digital Repository

Optical character recognition of cursive scripts present a number of challenging problems in both segmentation and recognition processes and this attracts many researches in the field of machine learning. This paper presents a novel approach based on a combination of MLP and SVM to design a trainable OCR for Persian/Arabic cursive documents. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use. © Springer-Verlag Berlin Heidelberg 2005  

In content based image retrieval similarity measurement is one of the most important aspects in a large image database for efficient search and retrieval to find the best answer for a user query. Color and texture are among the more expressive of the visual features. Considerable work has been done in designing efficient descriptors for these features for applications such as similarity retrieval. The MPEG-7 specifies a standard set of descriptors for color, texture and shape. In the Human Vision System (HVS), visual information is not perceived equally; some information may be more important than other information. The purpose of this paper is to show how the MPEG-7 descriptor based on... 

Researchers have been studying security challenges of database outsourcing for almost a decade. Privacy of outsourced data is one of the main challenges when the "Database As a Service" model is adopted in the service oriented trend of the cloud computing paradigm. This is due to the insecurity of the network environment or even the untrustworthiness of the service providers. This paper proposes a method to preserve privacy of outsourced data based on Shamir's secret sharing scheme. We split attribute values into several parts and distribute them among untrusted servers. The problem of using secret sharing in data outsourcing scenario is how to search efficiently within the randomly... 

Graph Matching (GM) plays an essential role in computer vision and machine learning. The ability of using pairwise agreement in GM makes it a powerful approach in feature matching. In this paper, a new formulation is proposed which is more robust when it faces with outlier points. We add weights to the one-to-one constraints, and modify them in the process of optimization in order to diminish the effect of outlier points in the matching procedure. We execute our proposed method on different real and synthetic databases to show both robustness and accuracy in contrast to several conventional GM methods  

Background: Long reads provide valuable information regarding the sequence composition of genomes. Long reads are usually very noisy which renders their alignments on the reference genome a daunting task. It may take days to process datasets enough to sequence a human genome on a single node. Hence, it is of primary importance to have an aligner which can operate on distributed clusters of computers with high performance in accuracy and speed. Results: In this paper, we presented IMOS, an aligner for mapping noisy long reads to the reference genome. It can be used on a single node as well as on distributed nodes. In its single-node mode, IMOS is an Improved version of Meta-aligner (IM)... 

The choice of technology to transport passengers in large metropolitan areas is an important issue everywhere. There are many factors involved in this choice. This paper deals with the possibility of the objective use of available information in the analysis of the suitability of a rail public transport system for a city. A database has been made from publications on public city transportation and country level information. Logit models of choice have been calibrated by the maximum likelihood and nonlinear least square methods based on the acquired information. Each city is treated as an "individual", choosing rail or non-rail modes for its trips. Only cities with a population of more than... 

In this paper, two different statistical approaches are used for duration prediction of the Farsi language. These two statistical models are Neural Networks (NN) and Classification And Regression Trees (CART). The first step in this work was to create a database and develop a flexible feature extraction and selection module. In the next step, the output of the feature selection module was used to train both models. The results of the trained models are further studied to determine the most important parameters affecting the syllable duration in Farsi, The model accuracy is evaluated by using separate training and test data. In the third step of this work, ah automatic rule generator module... 

Security of database outsourcing, due to the untrustworthiness of service provider, is a basic challenge to have Database As a Service in a cloud computing environment. Having disparate assumptions to solve different aspects of security such as confidentiality and integrity is an obstacle for an integrated secure solution through the combination of existing approaches. Concentrating on confidentiality and integrity aspects of database outsourcing, this paper proposes an approach in which each attribute value is split up between several data servers using a customized threshold secret sharing scheme. Our approach preserves data confidentiality and at the same time provides the correctness... 

In this paper, we proposed a method based on time-frequency dependent features extracted from Intrinsic Mode Functions (IMFs) and physiological feature such as the number of premature beats (PBs) to predict the onset of Paroxysmal Atrial Fibrillation (PAF) by using electrocardiogram (ECG) signal. To extract IMFs, we used Empirical Mode Decomposition (EMD). In order to predict PAF, we used variance of IMFs of signals, the area under the absolute of IMF curves and the number of PBs, since increasing of all of these parameters are a clear sign of PAF occurrence. We used clinical database which was provided for the 2001 Computer in Cardiology Challenge (CinC). The test set of this database... 

In recent years, IWR (Isolated Word Recognition) was one of the main concerns of speech processing. The challenging problems in this field appear when the database become so large or when we have a lot of word with similarly pronounce in the database. This paper introduces a general solution for a traditional problem in isolated similarly pronounced word recognition, especially in large databases. One the important problem of traditional IWR is referred to their segmentation algorithm, their methods were lacking in efficiency due to the following reasons: First, using equal segmentation is not at all intelligent at all and as a result, cannot produce accurate results; besides, utilizing... 

Recently XML has become a standard for data representation and the preferred method of encoding structured data for exchange over the Internet. Moreover it is frequently used as a logical format to store structured and semi-structured data in databases. We propose a model-driven and configurable approach for modeling hierarchical XML data using object role modeling (ORM) as a flat conceptual model. First a non-hierarchical conceptual schema of the problem domain is built using ORM and then different hierarchical views of the conceptual schema or parts of it are specified by the designer using transformation rules. A hierarchical modeling notation called H-ORM is proposed to show these... 

The great attention to cognitive radio networks (CRNs) in recent years, as a revolutionary communication paradigm that aims to solve the problem of spectrum scarcity, prompts serious investigation on security issues of these networks. One important security concern in CRNs is the preservation of users location privacy, which is under the shadow of threat, especially in database-driven CRNs. To this end, in this paper, we propose a Location Privacy Preserving Database-Driven Spectrum-Sharing (L-PDS 2) protocol for sharing the spectrum between PUs and SUs in a database-driven CRN, while protecting location privacy of both primary and secondary users, simultaneously. We also present two... 

One of the organizations’ main concerns is to protect sensitive data in database systems, especially the ones outsourced to untrusted service providers. An effective solution for this issue is to employ database encryption methods. Among different encryption approaches, Bucket-based method has the advantage of balancing security and performance of database operations. However, generating false-positive results in executing queries is the main drawback of this method. On the other hand, multi-join queries are one of the most critical operations executed on these stored sensitive data. Hence, acceptable processing and response time in executing multi-join queries is required. In this paper, we... 

The essential oil components of geranium oil cultivated in center of Iran were identified and determined using gas chromatography-mass spectrometry data combined with the chemometric resolution techniques. A total of 61 components accounting for 91.51% were identified using similarity searches between the mass spectra and MS database. This number was extended to 85 components using chemometric techniques. Various chemometric methods such as morphological scores, simplified Borgen method (SBM) and fixed size moving window evolving factor analysis (FSMWEFA) were used for determining the number of components, pure variables, zero concentration and selective regions. Then the overlapping peak... 

The COVID-19 epidemic is spreading day by day. Early diagnosis of this disease is essential to provide effective preventive and therapeutic measures. This process can be used by a computer-aided methodology to improve accuracy. In this study, a new and optimal method has been utilized for the diagnosis of COVID-19. Here, a method based on fuzzy C-ordered means (FCOM) along with an improved version of the enhanced capsule network (ECN) has been proposed for this purpose. The proposed ECN method is improved based on mayfly optimization (MFO) algorithm. The suggested technique is then implemented on the chest X-ray COVID-19 images from publicly available datasets. Simulation results are... 

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... 

Trip attraction has long been considered as a major element in trip demand estimation. Many models have been presented for this purpose. Models use socio-economic variables in order to predict trip attraction. Neural networks and neuro-fuzzy systems are suitable approaches to establish proper models. This paper develops neural and fuzzy-neural models to predict school trip attraction. Neural networks are organized in different architectures and the results have been compared in order to determine the best fitting one. Then an adaptive neural fuzzy inference system (ANFIS) is used to estimate number of school trip attraction. Different models were trained, validated and tested with a real... 

This paper addresses the problem of finding the nearest neighbor (or one of the R-nearest neighbors) of a query object q in a database of n objects, when we can only use a comparison oracle. The comparison oracle, given two reference objects and a query object, returns the reference object most similar to the query object. The main problem we study is how to search the database for the nearest neighbor (NN) of a query, while minimizing the questions. The difficulty of this problem depends on properties of the underlying database. We show the importance of a characterization: combinatorial disorder D which defines approximate triangle inequalities on ranks. We present a lower bound of Ω(Dlog...