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A new framework based on recurrence quantification analysis for epileptic seizure detection
, Article IEEE Journal of Biomedical and Health Informatics ; Volume 17, Issue 3 , 2013 , Pages 572-578 ; 21682194 (ISSN) ; Mousavi, S. R ; Vosoughi Vahdat, B ; Sayyah, M ; Sharif University of Technology
2013
Abstract
This study presents applying recurrence quantification analysis (RQA) on EEG recordings and their subbands: delta, theta, alpha, beta, and gamma for epileptic seizure detection. RQA is adopted since it does not require assumptions about stationarity, length of signal, and noise. The decomposition of the original EEG into its five constituent subbands helps better identification of the dynamical system of EEG signal. This leads to better classification of the database into three groups: Healthy subjects, epileptic subjects during a seizure-free interval (Interictal) and epileptic subjects during a seizure course (Ictal). The proposed algorithm is applied to an epileptic EEG dataset provided...
A new category of relations: combinationally constrained relations
, Article Scientia Iranica ; Volume 16, Issue 1 D , 2009 , Pages 34-52 ; 10263098 (ISSN) ; Mirian Hosseinabadi, H ; Sharif University of Technology
2009
Abstract
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 new Bayesian classifier for skin detection
, Article 3rd International Conference on Innovative Computing Information and Control, ICICIC'08, Dalian, Liaoning, 18 June 2008 through 20 June 2008 ; 2008 ; 9780769531618 (ISBN) ; Mousavi, M. E ; Sharif University of Technology
2008
Abstract
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...
A new approach in object-oriented methodology for creating event-based simulator
, Article 2006 Canadian Conference on Electrical and Computer Engineering, CCECE'06, Ottawa, ON, 7 May 2006 through 10 May 2006 ; 2006 , Pages 2424-2427 ; 08407789 (ISSN); 1424400384 (ISBN); 9781424400386 (ISBN) ; Abdollahzadeh, A ; Jalali, L ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2006
Abstract
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...
A Neuro-Fuzzy model for prediction of liquefaction-induced lateral spreading
, Article 8th US National Conference on Earthquake Engineering 2006, San Francisco, CA, 18 April 2006 through 22 April 2006 ; Volume 13 , 2006 , Pages 8001-8008 ; 9781615670444 (ISBN) ; Khalili, A ; Sadati, N ; Sharif University of Technology
2006
Abstract
Lateral spreading generated by earthquake induced liquefaction, is a major cause for significant damage to the engineered structures, during earthquakes. Knowing the amount of displacement which is likely to occur due to the lateral spreading, will lead to better construction policies, and will reduce unexpected damages. A Neuro-Fuzzy model based on subtractive clustering is developed to predict the amount of lateral spreading expected to occur due to an earthquake. A large database containing the case histories of observed lateral spreading during seven major earthquakes of the past is used for training and evaluating the models. The results of this study show that Neuro-Fuzzy method serves...
Analyzing the supply chain using SCOR model in a steel producing company
, Article 40th International Conference on Computers and Industrial Engineering, 25 July 2010 through 28 July 2010 ; 2010 ; 9781424472956 (ISBN) ; Akbari, M. R ; Ssheikh Sajadieh, M ; Sharif University of Technology
Abstract
Supply Chain Operations Reference (SCOR) model is developed and maintained by the Supply Chain Council (SCC). The model is a reference model which can be used to map, benchmark and improve the supply chain operations. SCOR model provides companies with a basic process modeling tool, an extensive benchmark database and defines a set of supply chain metrics. Mobarakeh Steel Company (located in Isfahan, Iran) initiated the project of studying and analyzing its supply chain performance based on the SCOR model. This paper explains the steps and the results of the project. Interviews with the managers and considering the documents on the four major subjects of planning, logistics, information flow...
An access and inference control model for time series databases
, Article Future Generation Computer Systems ; Volume 92 , 2019 , Pages 93-108 ; 0167739X (ISSN) ; Amini, M ; Sharif University of Technology
Elsevier B.V
2019
Abstract
Today, many applications produce and use time series data. The data of this type may contain sensitive information. So they should be protected against unauthorized accesses. In this paper, security issues of time series data are identified and an access and inference control model for satisfying the identified security requirements is proposed. Using this model, administrators can define authorization rules based on various time-based granularities (e.g. day or month) and apply value-based constraints over the accessed times series data. Furthermore, they can define policy rules over the composition of multiple time-series other than the base time-series data. Detecting and resolving...
A model-driven approach to semi-structured database design
, Article Frontiers of Computer Science ; Volume 9, Issue 2 , 2015 , Pages 237-252 ; 20952228 (ISSN) ; Mirian Hosseinabadi, S ; Sharif University of Technology
Higher Education Press
2015
Abstract
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...
A location privacy-preserving method for spectrum sharing in database-driven cognitive radio networks
, Article Wireless Personal Communications ; Volume 95, Issue 4 , 2017 , Pages 3687-3711 ; 09296212 (ISSN) ; Ahmadian Attari, M ; Jannati, H ; Aref, M. R ; Sharif University of Technology
Springer New York LLC
2017
Abstract
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...
A hybrid deep model for automatic arrhythmia classification based on LSTM recurrent networks
, Article 15th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2020, 1 June 2020 through 3 June 2020 ; 2020 ; Amini, A ; Baghshah, M. S ; Khodajou Chokami, H ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
Electrocardiogram (ECG) recording of electrical heart activities has a vital diagnostic role in heart diseases. We propose to tackle the problem of arrhythmia detection from ECG signals totally by a deep model that does not need any hand-designed feature or heuristic segmentation (e.g., ad-hoc R-peak detection). In this work, we first segment ECG signals by detecting R-peaks automatically via a convolutional network, including dilated convolutions and residual connections. Next, all beats are aligned around their R-peaks as the most informative section of the heartbeat in detecting arrhythmia. After that, a deep learning model, including both dilated convolution layers and a Long-Short Term...
A hybrid computational approach to estimate solar global radiation: An empirical evidence from Iran
, Article Energy ; Volume 49, Issue 1 , 2013 , Pages 204-210 ; 03605442 (ISSN) ; Ramiyani, S. S ; Sarvar, R ; Moud, H. I ; Mousavi, S. M ; Sharif University of Technology
2013
Abstract
This paper presents an innovative hybrid approach for the estimation of the solar global radiation. New prediction equations were developed for the global radiation using an integrated search method of genetic programming (GP) and simulated annealing (SA), called GP/SA. The solar radiation was formulated in terms of several climatological and meteorological parameters. Comprehensive databases containing monthly data collected for 6 years in two cities of Iran were used to develop GP/SA-based models. Separate models were established for each city. The generalization of the models was verified using a separate testing database. A sensitivity analysis was conducted to investigate the...
A fundamental tradeoff between computation and communication in distributed computing
, Article IEEE Transactions on Information Theory ; 2017 ; 00189448 (ISSN) ; Maddah Ali, M. A ; Yu, Q ; Avestimehr, A. S ; Sharif University of Technology
Abstract
How can we optimally trade extra computing power to reduce the communication load in distributed computing? We answer this question by characterizing a fundamental tradeoff between computation and communication in distributed computing, i.e., the two are inversely proportional to each other. More specifically, a general distributed computing framework, motivated by commonly used structures like MapReduce, is considered, where the overall computation is decomposed into computing a set of “Map” and “Reduce” functions distributedly across multiple computing nodes. A coded scheme, named “Coded Distributed Computing” (CDC), is proposed to demonstrate that increasing the computation load of the...
A fundamental tradeoff between computation and communication in distributed computing
, Article IEEE Transactions on Information Theory ; Volume 64, Issue 1 , 2018 , Pages 109-128 ; 00189448 (ISSN) ; Maddah Ali, M. A ; Yu, Q ; Salman Avestimehr, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2018
Abstract
How can we optimally trade extra computing power to reduce the communication load in distributed computing? We answer this question by characterizing a fundamental tradeoff between computation and communication in distributed computing, i.e., the two are inversely proportional to each other. More specifically, a general distributed computing framework, motivated by commonly used structures like MapReduce, is considered, where the overall computation is decomposed into computing a set of “Map” and “Reduce” functions distributedly across multiple computing nodes. A coded scheme, named “coded distributed computing” (CDC), is proposed to demonstrate that increasing the computation load of the...
A front-end OCR for omni-font Persian/Arabic cursive printed documents
, Article Digital Imaging Computing: Techniques and Applications, DICTA 2005, Cairns, 6 December 2005 through 8 December 2005 ; Volume 2005 , 2005 , Pages 385-392 ; 0769524672 (ISBN); 9780769524672 (ISBN) ; Pirsiavash, H ; Razzazi, F ; Sharif University of Technology
2005
Abstract
Compared to non-cursive scripts, optical character recognition of cursive documents comprises extra challenges in layout analysis as well as recognition of the printed scripts. This paper presents a front-end OCR for Persian/Arabic cursive documents, which utilizes an adaptive layout analysis system in addition to a combined MLP-SVM recognition process. The implementation results on a comprehensive database show a high degree of accuracy which meets the requirements of commercial use. © 2005 IEEE
Advanced nastaliq CAPTCHA
, Article 2008 7th IEEE International Conference on Cybernetic Intelligent Systems, CIS 2008, London, 9 September 2008 through 10 September 2008 ; 2008 ; 9781424429141 (ISBN) ; Shirali Shahreza, M ; Sharif University of Technology
2008
Abstract
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...
A data mining approach for diagnosis of coronary artery disease
, Article Computer Methods and Programs in Biomedicine ; Volume 111, Issue 1 , 2013 , Pages 52-61 ; 01692607 (ISSN) ; Habibi, J ; Hosseini, M. J ; Mashayekhi, H ; Boghrati, R ; Ghandeharioun, A ; Bahadorian, B ; Sani, Z. A ; Sharif University of Technology
2013
Abstract
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...
A content-based approach to medical images retrieval
, Article International Journal of Healthcare Information Systems and Informatics ; Volume 8, Issue 2 , 2013 , Pages 15-27 ; 15553396 (ISSN) ; Fatemizadeh, E ; Badie, K ; Sharif University of Technology
2013
Abstract
Content-based image retrieval (CBIR) makes use of image features, such as color, texture or shape, to index images with minimal human intervention. Content-based image retrieval can be used to locate medical images in large databases. In this paper, the fundamentals of the key components of content-based image retrieval systems are introduced first to give an overview of this area. Then, a case study which describes the methodology of a CBIR system for retrieving human brain magnetic resonance images, is presented. The proposed method is based on Adaptive Neuro-fuzzy Inference System (ANFIS) learning and could classify an image as normal and tumoral. This research uses the knowledge of CBIR...