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    Designing a Video Search System Using Topic Models

    , M.Sc. Thesis Sharif University of Technology Kianpisheh, Mohammad (Author) ; Gholampoor, Iman (Supervisor) ; Sharif Khani, Mohammad (Supervisor)
    In this work we present a surveillance video retrieval system based on Topic Models. We’ve shown that employing Dynamic Programming improve the effectiveness of Topic Model based retrival. In the other hand proposed method has the accuracy near to the low-level features based methods. Lightweight database is the major advantageous of propsed method over the low-level features based methods. In our work storage space occupied by database decreases from 42 MB to only 0.4 MB for the mit dataset. Moreover lightweight database strikingly speeded up the retrieval process, for example retrieval process in proposed method is about 24 times faster than low-level features based systems. Furthermore in... 

    Vision-based Vehicle Detection in Intercity Roads for Intelligent Transportation Systems Applications

    , M.Sc. Thesis Sharif University of Technology Rostami, Peyman (Author) ; Marvasti, Farokh (Supervisor)
    This project aims to highlight vision related tasks centered around "car". First, we gathered a dataset of 4343 front view car images, captured from the streets of Iran and Syria during daylight, the images of which are all manually cropped around their corresponding accurately chosen bounding boxes. we also extracted seven parts (i.e. left and right front lights, left and right mirrors, bumper, plate, and air intake) from each car image in the dataset. Our dataset is suitable for developing and testing bounding box extraction algorithms, holistic and part based analyses, occlusion handling algorithms, etc. next, we utilized Viola-Jones Detector to develop a system for car detection, in... 

    Ontological Study of Metabolic Networks to Develop an Identification Software for Metabolic Networks

    , M.Sc. Thesis Sharif University of Technology Mohammadi Peyhani, Homa (Author) ; Bozorgmehry Boozarjomehry, Ramin (Supervisor)
    Simulation of biological behaviors as the pre requirement for control and optimization, especially for recognition and treating diseases, requires studying involved reactions which may or may not be accessible. In the other side, finding the correct network structures and related mathematical expressions to simulate biological behaviors is a complicated problem due to multi aspect interactions among biological reactions, which imply an approach that integrate the knowledge coming from multiple discipline including biological concepts, mathematical modelling, bioinformatics and advanced programming. In this study we aim to analyze this problem using ontological inference to develop a... 

    Geometrical Fracture Modeling Within Multiple-Point Statistics Framework

    , M.Sc. Thesis Sharif University of Technology Ahmadi, Rouhollah (Author) ; Masihi, Mohsen (Supervisor) ; Rasaei, Mohammad Reza (Supervisor) ; Eskandaridalvand, Kiomars (Supervisor) ; Shahalipour, Reza (Co-Advisor)
    Majority of the oil and gas reservoirs, in the main hydrocarbon production regions around the world, are naturally fractured reservoirs. Fractures play an important role in reservoir fluid flow either in the form of high permeable complex conduits or strong permeability anisotropies. Realistic characterization of naturally fractured reservoirs requires an exhaustive understanding of fracture connectivity and fracture pattern geometry. These subsequently demand description of many fracture parameters such as density (intensity), spacing, orientation, size and aperture. Therefore, a first step in fractured reservoirs characterization is the static geometric modeling of the subsurface fracture... 

    A Unified Approach to Modeling and Design of Semi-structured Databases

    , Ph.D. Dissertation Sharif University of Technology Jahangard Rafsanjani, Amir (Author) ; Mirian Hosseinabadi, Hassan (Supervisor)
    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. In this research we focus on semantic modeling for XML data and we propose a model-driven approach for modeling and designing XML databases. In the approach data is modeled without considering representation and implementation details in a platform independent model.
    We use Object-Role Modeling as the platform independent model. We specify a formal meta-model of this model in Alloy and we validate instance models by checking... 

    Speech-Driven Talking Face Synthesis based on True Articulatory Gestures

    , M.Sc. Thesis Sharif University of Technology Peyghan, Mohammad Reza (Author) ; Ghaemmaghami, Shahrokh (Supervisor) ; Behroozi, Hamid (Co-Supervisor)
    Talking face synthesis is a process in which is made using audio-visual data or its features. Because the face is the first output, face animation plays a crucial role in this process. A high-quality face, a balance between different facial regions, natural movements of facial organs, and the like are basic requirements to synthesize a relatively realistic talking face. There are a wide variety of applications for the photo-realistic talking face. For instance, as a teaching assistant, or reading emails and e-books are only two simple ones to mention. To reach a realistic talking face with mentioned necessary requirements, we set a goal to consider all face regions and their movements. To... 

    Encryption Aware Query Processing for Data Outsourcing

    , Ph.D. Dissertation Sharif University of Technology Ghareh Chamani, Javad (Author) ; Jalili, Rasool (Supervisor)
    Data outsourcing provides cost-saving and availability guarantees. However, privacy and confidentiality issues, disappoint owners from outsourcing their data. Although solutions such as CryptDB and SDB tried to provide secure and practical systems, their enforced limitations, made them useless in practice. Inability in search on encrypted data, is one of the most important existing challenges in such systems. Furthermore, the overhead of mechanisms such as FHEs, removes them from considering for any practical system. Indeed, special purpose encryptions would be the only usable mechanisms for such purposes. However, their limited functionality does not support some important required... 

    Presentation and Modeling of a New Nanocomposite Shield Against Gamma Radiation Based on Simulation and Computational Tools

    , M.Sc. Thesis Sharif University of Technology Arvaneh, Ali (Author) ; Hosseini, Abolfazl (Supervisor)
    In this study, using the MCNPX computer code based on the Monte Carlo method, the properties of protection against gamma-rays of the glass system with the combination of (55-x)Bi2O3-15Pb3O4-20Al2O3-10ZnO-xTiO2 with certain concentrations (x= 0, 5, 10, 15, 20, 25, 30 and 35 mol percent) and in nano and micro dimensions by calculating several parameters related to photon attenuation such as half value layer (HVL), Tenth value layer (TVL), mean free range (MFP), mass attenuation coefficient (m), linear attenuation coefficient (l), effective atomic number (Zeff) and buildup factor (BF) for We investigated different energy levels in the range of 1500-100 keV. To verify the simulation results,... 

    Formal process algebraic modeling, verification, and analysis of an abstract Fuzzy Inference Cloud Service

    , Article Journal of Supercomputing ; Vol. 67, issue. 2 , February , 2014 , pp. 345-383 ; Online ISSN: 1573-0484 Rezaee, A ; Rahmani, A. M ; Movaghar, A ; Teshnehlab, M
    In cloud computing, services play key roles. Services are well defined and autonomous components. Nowadays, the demand of using Fuzzy inference as a service is increasing in the domain of complex and critical systems. In such systems, along with the development of the software, the cost of detecting and fixing software defects increases. Therefore, using formal methods, which provide clear, concise, and mathematical interpretation of the system, is crucial for the design of these Fuzzy systems. To obtain this goal, we introduce the Fuzzy Inference Cloud Service (FICS) and propose a novel discipline for formal modeling of the FICS. The FICS provides the service of Fuzzy inference to the... 

    KNNDIST: A non-parametric distance measure for speaker segmentation

    , Article 13th Annual Conference of the International Speech Communication Association 2012, INTERSPEECH 2012 ; Volume 3 , 2012 , Pages 2279-2282 ; 9781622767595 (ISBN) Mohammadi, S. H ; Sameti, H ; Langarani, M. S. E ; Tavanaei, A ; Sharif University of Technology
    A novel distance measure for distance-based speaker segmentation is proposed. This distance measure is nonparametric, in contrast to common distance measures used in speaker segmentation systems, which often assume a Gaussian distribution when measuring the distance between two audio segments. This distance measure is essentially a k-nearest-neighbor distance measure. Non-vowel segment removal in preprocessing stage is also proposed. Speaker segmentation performance is tested on artificially created conversations from the TIMIT database and two AMI conversations. For short window lengths, Missed Detection Rated is decreased significantly. For moderate window lengths, a decrease in both... 

    HBIR: Hypercube-based image retrieval

    , Article Journal of Computer Science and Technology ; Volume 27, Issue 1 , January , 2012 , Pages 147-162 ; 10009000 (ISSN) Ajorloo, H ; Lakdashti, A ; Sharif University of Technology
    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... 

    Image steganalysis based on SVD and noise estimation: Improve sensitivity to spatial LSB embedding families

    , Article IEEE Region 10 Annual International Conference, Proceedings/TENCON, 21 November 2011 through 24 November 2011, Bali ; 2011 , Pages 1266-1270 ; 9781457702556 (ISBN) Diyanat, A ; Farhat, F ; Ghaemmaghami, S ; Sharif University of Technology
    We propose a novel image steganalysis method, based on singular value decomposition and noise estimation, for the spatial domain LSB embedding families. We first define a content independence parameter, DS, that is calculated for each LSB embedding rate. Next, we estimate the DS curve and use noise estimation to improve the curve approximation accuracy. It is shown that the proposed approach gives an estimate of the LSB embedding rate, as well as information about the existence of the embedded message (if any). The proposed method can effectively be applied to a wide range of the image LSB steganography families in spatial domain. To evaluate the proposed scheme, we applied the method to a... 

    Three-dimensional modular discriminant analysis (3DMDA): A new feature extraction approach for face recognition

    , Article Computers and Electrical Engineering ; Volume 37, Issue 5 , 2011 , Pages 811-823 ; 00457906 (ISSN) Safayani, M ; Manzuri Shalmani, M. T ; Sharif University of Technology
    In this paper, we present a novel multilinear algebra based feature extraction approach for face recognition which preserves some implicit structural or locally-spatial information among elements of the original images. We call this method three-dimensional modular discriminant analysis (3DMDA). Our approach uses a new data model called third-order tensor model (3TM) for representing the face images. In this model, each image is partitioned into the several equal size local blocks, and the local blocks are combined to represent the image as a third-order tensor. Then, a new optimization algorithm called direct mode (d-mode) is introduced for learning three optimal projection axes. Extensive... 

    Security and searchability in secret sharing-based data outsourcing

    , Article International Journal of Information Security ; Volume 14, Issue 6 , November , 2015 , Pages 513-529 ; 16155262 (ISSN) Hadavi, M. A ; Jalili, R ; Damiani, E ; Cimato, S ; Sharif University of Technology
    Springer Verlag  2015
    A major challenge organizations face when hosting or moving their data to the Cloud is how to support complex queries over outsourced data while preserving their confidentiality. In principle, encryption-based systems can support querying encrypted data, but their high complexity has severely limited their practical use. In this paper, we propose an efficient yet secure secret sharing-based approach for outsourcing relational data to honest-but-curious data servers. The problem with using secret sharing in a data outsourcing scenario is how to efficiently search within randomly generated shares. We present multiple partitioning methods that enable clients to efficiently search among shared... 

    Speech driven lips animation for the Farsi language

    , Article Proceedings of the International Symposium on Artificial Intelligence and Signal Processing, AISP 2015, 3 March 2015 through 5 March 2015 ; 2015 , Pages 201-205 ; 9781479988174 (ISBN) Naraghi, Z ; Jamzad, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    With the growing presence of computers in everyday life, communication improvement between human and machines is inevitable. Talking faces are the faces whose movements are synchronized to speech. They have an effective role in many applications. Lip is the most important part of a talking face. The main goal of this project is implementing a natural and human-like lip movement synthesis system for the Farsi language. For this purpose, a comprehensive audio visual database called SFAVD1 was designed and used. After extracting the sufficient features and designing a parallel Hidden Markov Model, the speech driven lip movement sequence generator system for Farsi input speech was implemented.... 

    Face recognition using boosted regularized linear discriminant analysis

    , Article ICCMS 2010 - 2010 International Conference on Computer Modeling and Simulation, 22 January 2010 through 24 January 2010, Sanya ; Volume 2 , 2010 , Pages 89-93 ; 9780769539416 (ISBN) Baseri Salehi, N ; Kasaei, S ; Alizadeh, S ; Sharif University of Technology
    Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper, we have proposed the boosting method for face recognition (FR) that improves the linear discriminant analysis (LDA)-based technique. The improvement is achieved by incorporating the regularized LDA (R-LDA) technique into the boosting framework. 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. The AdaBoost technique is utilized within this framework to generalize a set of simple FR subproblems and their corresponding LDA solutions and combines the results from... 

    Towards a knowledge-based approach for creating software architecture patterns ontology

    , Article 2016 International Conference on Engineering and MIS, ICEMIS 2016, 22 September 2016 through 24 September 2016 ; 2016 ; 9781509055791 (ISBN) Rabinia, Z ; Moaven, S ; Habibi, J ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2016
    Software architecture patterns present solutions for software architecture problems and help to document architectural design decisions. Complexity and variability of patterns, and the required expertise for selecting an appropriate pattern, would cause some difficulties in utilizing architectural patterns. Using an ontology for registering architectural patterns is an efficient step in solving those problems. However, the mentioned difficulties make the process of constructing the architectural patterns ontology even more complicated. This paper proposes an approach that considers the construction of the architectural patterns ontology from four perspectives in order to overcome this... 

    Finding an unknown object by using piezeoelectric material: A finite element approach

    , Article 2nd International Conference on Environmental and Computer Science, ICECS 2009, 28 December 2009 through 30 December 2009, Dubai ; 2009 , Pages 156-160 ; 9780769539379 (ISBN) Azizi, A ; Durali, L ; Zareie, S ; Parvari Rad, F ; Sharif University of Technology
    IEEE  2009
    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... 

    Flat-Start single-stage discriminatively trained hmm-based models for asr

    , Article IEEE/ACM Transactions on Audio Speech and Language Processing ; Volume 26, Issue 11 , 2018 , Pages 1949-1961 ; 23299290 (ISSN) Hadian, H ; Sameti, H ; Povey, D ; Khudanpur, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    In recent years, end-to-end approaches to automatic speech recognition have received considerable attention as they are much faster in terms of preparing resources. However, conventional multistage approaches, which rely on a pipeline of training hidden Markov models (HMM)-GMM models and tree-building steps still give the state-of-the-art results on most databases. In this study, we investigate flat-start one-stage training of neural networks using lattice-free maximum mutual information (LF-MMI) objective function with HMM for large vocabulary continuous speech recognition. We thoroughly look into different issues that arise in such a setup and propose a standalone system, which achieves... 

    Improvements on the k-center problem for uncertain data extended abstract

    , Article Proceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems ; 27 May , 2018 , Pages 425-433 ; 9781450347068 (ISBN) Alipour, S ; Jafari, A ; Sharif University of Technology
    Association for Computing Machinery  2018
    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...