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    Combination of wavelet and PCA for face recognition

    , Article 2006 IEEE GCC Conference, GCC 2006, Manama, 20 March 2006 through 22 March 2006 ; 2006 ; 9780780395909 (ISBN) Mazloom, M ; Kasaei, S ; Sharif University of Technology
    This work presents a method to increase the face recognition accuracy using a combination of Wavelet, PCA, and Neural Networks. Preprocessing, feature extraction and classification rules are three crucial issues for face recognition. This paper presents a hybrid approach to employ these issues. For preprocessing and feature extraction steps, we apply a combination of wavelet transform and PCA. During the classification stage, the Neural Network (MLP) is explored to achieve a robust decision in presence of wide facial variations. The computational load of the proposed method is greatly reduced as comparing with the original PCA based method on the Yale and ORL face databases. Moreover, the... 

    Seizure detection in EEG signals: a comparison of different approaches

    , Article 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'06, New York, NY, 30 August 2006 through 3 September 2006 ; 2006 , Pages 6724-6727 ; 05891019 (ISSN); 1424400325 (ISBN); 9781424400324 (ISBN) Mohseni, H. R ; Maghsoudi, A ; Shamsollahi, M. B ; Sharif University of Technology
    In this paper, the performance of traditional variance-based method for detection of epileptic seizures in EEG signals are compared with various methods based on nonlinear time series analysis, entropies, logistic regression, discrete wavelet transform and time frequency distributions. We noted that variance-based method in compare to the mentioned methods had the best result (100%) applied on the same database. © 2006 IEEE  

    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) Haeri, S. M ; Khalili, A ; Sadati, N ; Sharif University of Technology
    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... 

    The knowledge map of energy security

    , Article Energy Reports ; Volume 7 , 2021 , Pages 3570-3589 ; 23524847 (ISSN) Nasr Esfahani, A ; Bagheri Moghaddam, N ; Maleki, A ; Nazemi, A ; Sharif University of Technology
    Elsevier Ltd  2021
    Much efforts have been made in the area of energy security in recent years, but due to its wide scope, it is necessary to review relevant knowledge activities and to analyze the state of knowledge of the field of energy security measurement. The purpose of this article is to present a comprehensive map of knowledge in the field of energy security. For this reason, many documents and articles have been collected during the period 2002–2019 using 7 large and reputable scientific databases as well as 53 different journals, 90% white Q1 quality. There is employed meta-synthesis, scientometrics and network analysis. In the initial survey stage where 1290 articles were found, after analyzing 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) Mehran, R ; Pirsiavash, H ; Razzazi, F ; Sharif University of Technology
    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  

    SkipTree: A Scalable range-queryable distributed data structure for multidimensional data

    , Article 16th International Symposium on Algorithms and Computation, ISAAC 2005, Hainan, 19 December 2005 through 21 December 2005 ; Volume 3827 LNCS , 2005 , Pages 298-307 ; 03029743 (ISSN); 3540309357 (ISBN); 9783540309352 (ISBN) Alaei, S ; Toossi, M ; Ghodsi, M ; Sharif University of Technology
    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  

    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) Niknazar, M ; Mousavi, S. R ; Vosoughi Vahdat, B ; Sayyah, M ; Sharif University of Technology
    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 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) Tarjoman, M ; Fatemizadeh, E ; Badie, K ; Sharif University of Technology
    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... 

    Unsupervised estimation of conceptual classes for semantic image annotation

    , Article 2011 19th Iranian Conference on Electrical Engineering, ICEE 2011, 17 May 2011 through 19 May 2011 ; May , 2011 ; 9789644634284 (ISBN) Teimoori, F ; Esmaili, H ; Shirazi, A. A. B ; Sharif University of Technology
    A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as the group of database images labeled with a common semantic label. It is shown that, by establishing this one-to-one correspondence between semantic labels and semantic classes, a minimum probability of error annotation and retrieval are feasible with algorithms that are 1) conceptually simple and 2) computationally efficient. In this article, a content-based image retrieval and annotation architecture is proposed. Its attitude is decreasing the semantic gap by partitioning the image to its semantic regions and using... 

    Switching kalman filter based methods for apnea bradycardia detection from ECG signals

    , Article Physiological Measurement ; Volume 36, Issue 9 , 2015 , Pages 1763-1783 ; 09673334 (ISSN) Ghahjaverestan, N. M ; Shamsollahi, M. B ; Ge, D ; Hernandez, A. I ; Sharif University of Technology
    Apnea bradycardia (AB) is an outcome of apnea occurrence in preterm infants and is an observable phenomenon in cardiovascular signals. Early detection of apnea in infants under monitoring is a critical challenge for the early intervention of nurses. In this paper, we introduce two switching Kalman filter (SKF) based methods for AB detection using electrocardiogram (ECG) signal. The first SKF model uses McSharry's ECG dynamical model integrated in two Kalman filter (KF) models trained for normal and AB intervals. Whereas the second SKF model is established by using only the RR sequence extracted from ECG and two AR models to be fitted in normal and AB intervals. In both SKF approaches, a... 

    User adaptive clustering for large image databases

    , Article Proceedings - International Conference on Pattern Recognition, 23 August 2010 through 26 August 2010, Istanbul ; 2010 , Pages 4271-4274 ; 10514651 (ISSN) ; 9780769541099 (ISBN) Saboorian, M. M ; Jamzad, M ; Rabiee, H. R ; Sharif University of Technology
    Searching large image databases is a time consuming process when done manually. Current CBIR methods mostly rely on training data in specific domains. When source and domain of images are unknown, unsupervised methods provide better solutions. In this work, we use a hierarchical clustering scheme to group images in an unknown and large image database. In addition, the user should provide the current class assignment of a small number of images as a feedback to the system. The proposed method uses this feedback to guess the number of required clusters, and optimizes the weight vector in an iterative manner. In each step, after modification of the weight vector, the images are reclustered. We... 

    A fundamental tradeoff between computation and communication in distributed computing

    , Article IEEE Transactions on Information Theory ; 2017 ; 00189448 (ISSN) Li, S ; Maddah Ali, M. A ; Yu, Q ; Avestimehr, A. S ; Sharif University of Technology
    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... 

    Introducing a framework to create telephony speech databases from direct ones

    , Article 14th International Conference on Systems Signals and Image Processing, IWSSIP 2007 and 6th EURASIP Conference Focused on Speech and Image Processing, Multimedia Communications and Services, EC-SIPMCS 2007, Maribor, 27 June 2007 through 30 June 2007 ; November , 2007 , Pages 327-330 ; 9789612480295 (ISBN) Momtazi, S ; Sameti, H ; Vaisipour, S ; Tefagh, M ; Sharif University of Technology
    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... 

    An implementation of a CBIR system based on SVM learning scheme

    , Article Journal of Medical Engineering and Technology ; Volume 37, Issue 1 , 2013 , Pages 43-47 ; 03091902 (ISSN) Tarjoman, M ; Fatemizadeh, E ; Badie, K ; Sharif University of Technology
    Content-based image retrieval (CBIR) has been one of the most active areas of research. The retrieval principle of CBIR systems is based on visual features such as colour, texture and shape or the semantic meaning of the images. A CBIR system can be used to locate medical images in large databases. This paper presents a CBIR system for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the support vector machine (SVM) learning method. This system can retrieve similar images from the database in two groups: normal and tumoural. This research uses the knowledge of the CBIR approach to the application of medical decision support and discrimination... 

    A Secure DBMS Architecture to Preserve Data Privacy, Confidentiality, and Integrity

    , M.Sc. Thesis Sharif University of Technology Halvachi, Hadi (Author) ; Jalili, Rasool (Supervisor)
    While data outsourcing provides some benefits, it suffers from new privacy and security concerns, mainly about the confidentiality and integrity of the stored sensitive data, as well as enforcing access control policies. Current solutions to these aims are not comprehensive and consider only one aspect of security requirements. A secure DBMS architecture is introduced that simultaneously considers confidentiality, integrity and access control enforcement requirements. The transparency of security functions from data owner, service providers, and applications facilitates the operationality of the solution.Additionally, a new indexing technique for character encrypted data is proposed that... 

    Using Functional Encryption to Manage Encrypted Data

    , M.Sc. Thesis Sharif University of Technology Mahfoozi, Rohollah (Author) ; Jalili, Rasool (Supervisor)
    Recently, many organizations outsource their data on an external server to rescue the trouble of data maintenance. But, data owners do not trust in the external server to enforce defined access control policies. In recent years, many researches was dedicated to cryptographic access control on outsourced data, in order to solve this problem. We introduce a method based on Attribute-based Encryption to enforce access control on outsourced data. In this method we consider policy updating and administrative access control. As a result The owner is not only able to change access control policies on outsourced data but also to define administrative rights (grant/revoke) for some admin users. Our... 

    Confidential Access to the Outsourced Relational Data

    , M.Sc. Thesis Sharif University of Technology NajmAbadi, Elahe Sadat (Author) ; Jalili, Rasool (Supervisor)
    In recent years, there has been a trend toward outsourcing data to the cloud provider. These companies must tackle the data security challenges. Generally these parties are assumed to be honest but curious. In past years, the research communities have been investigating different solution to ensure confidentiality.
    In addition to data confidentiality access and pattern confidentiality is a high-priority issue in some cases so. potential adversary should be unable to drive information from the observed access pattern to the outsourced data. Despite the fact that there are more investigation in the field of data confidentiality, concern over data security are the rise in outsourcing data,... 

    Query Optimization in Encrypted Database Systems

    , M.Sc. Thesis Sharif University of Technology Jafarinejad, Mahmoud (Author) ; Amini, Morteza (Supervisor)
    Protecting sensitive data stored in database systems, especially in outsourced ones, has become a major concern in many organizations. One of the main possible solutions is to encrypt data before storing them on databases. Bucket-based encryption is among different approaches proposed to accomplish this goal which besides its various benefits, suffers from generating false-positive results. Multi-join queries are one of the most important operations in database systems and their usage grows rapidly in comparison to other types of queries by increasing the size of stored information. While using the decision support systems and data mining solutions are growing continuously, executing... 

    Multi-Query Optimization in Distributed Databases Using an Ants Colony-Based Algorithm

    , M.Sc. Thesis Sharif University of Technology Abazari Torghabeh, Reza (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    One important problem in query optimization in centralized and decentralized databases is optimizing queries containing common sub-expressions, known as multi-query optimization. In processing these queries, the goal is to process a group of queries together and find a global execution plan with minimum cost for the query set. In most of researches which have approached this problem the focus were on exhaustive algorithms. Since size of the problem space for these algorithms grows exponential with query set size, these approaches are impractical. In this research we have presented six algorithms based on Ant Colony Optimization metaheuristic. We have compared the efficiency of these methods... 

    Component Based Translation of Z Specifications to Executable Code

    , M.Sc. Thesis Sharif University of Technology Khalafinejad, Saeed (Author) ; Mirian-Hosseinabadi, Hassan (Supervisor)
    Automatic translation of a high-level specification language to an executable implementation would be highly useful in maximizing the benefits of formal methods. We will introduce a set of translation functions to fill the specification-implementation gap in the domain of database applications. We chose Z, SQL and Delphi languages to illustrate our methodology. We extend Delphi libraries to support mathematical objects exist in Z. Then, based on the extended libraries, we extract the translation functions from Z to Delphi. The translation functions from Z to SQL are more easily extracted, because the mathematical foundation of Z has many properties in common with SQL. Based on the extracted...