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    Investigation of Io's auroral hiss emissions due to its motion in Jupiter's magnetosphere

    , Article Research in Astronomy and Astrophysics ; Volume 12, Issue 6 , 2012 , Pages 693-702 ; 16744527 (ISSN) Moghimi, M. H ; Sharif University of Technology
    The left-hand side of the auroral hiss emission observed by Galileo has a frequency time profile shaped very similar to the funnel shape observed in the Earth's auroral region. This close similarity indicates that we can use the theory of whistler-mode propagation near the resonance cone to locate the emission source. The general characteristics of the whistler mode are discussed. Then the position of the emission source is investigated using a geometrical method that takes into account the trajectory of Galileo. Initially a point source is assumed. Then the possibility of a sheet source aligned along the magnetic field lines which are tangent to the surface of Io is investigated. Both types... 

    New modification on production data of gas condensate reservoirs for rate transient analysis

    , Article Petroleum Science and Technology ; Vol. 32, issue. 5 , Jan , 2014 , p. 543-554 ; ISSN: 10916466 Boogar, A. S ; Gerami, S ; Masihi, M ; Sharif University of Technology
    Techniques of production data analysis for single-phase oil and gas reservoirs have advanced significantly over the past few years. These techniques range from traditional (i.e., Arps, 1945; Fetkovich, 1980) to modern methods that account for the variation of operating conditions at the wellbore. However, the application of these later methods to gas condensate reservoirs is a challenge. The authors aimed to extend the applicability of modern production data analysis (single-phase flow) to analyze the production data of a gas condensate reservoir (two-phase flow). A single-phase production model consists of (a) a material balance equation, (b) the solution of diffusivity equation for gas... 

    New modification on production data of gas condensate reservoirs for rate transient analysis

    , Article Petroleum Science and Technology ; Vol. 32, issue. 5 , 2014 , Pages 543-554 ; ISSN: 10916466 Boogar, A. S ; Gerami, S ; Masihi, M ; Sharif University of Technology
    Techniques of production data analysis for single-phase oil and gas reservoirs have advanced significantly over the past few years. These techniques range from traditional (i.e., Arps, 1945; Fetkovich, 1980) to modern methods that account for the variation of operating conditions at the wellbore. However, the application of these later methods to gas condensate reservoirs is a challenge. The authors aimed to extend the applicability of modern production data analysis (single-phase flow) to analyze the production data of a gas condensate reservoir (two-phase flow). A single-phase production model consists of (a) a material balance equation, (b) the solution of diffusivity equation for gas... 

    Dark energy from fifth-dimensional brans-dicke theory

    , Article International Journal of Modern Physics D ; Volume 22, Issue 10 , 2013 ; 02182718 (ISSN) Bahrehbakhsh, A. F ; Farhoudi, M ; Vakili, H ; Sharif University of Technology
    Following the approach of the induced-matter theory, we investigate the cosmological implications of a five-dimensional Brans-Dicke (BD) theory, and propose to explain the acceleration of the universe. After inducing in a four-dimensional hypersurface, we classify the energy-momentum tensor into two parts in a way that, one part represents all kind of the matter (the baryonic and dark) and the other one contains every extra terms emerging from the scale factor of the fifth dimension and the scalar field, which we consider as the energy-momentum tensor of dark energy. We also separate the energy-momentum conservation equation into two conservation equations, one for matter and the other for... 

    High-precision photometry by telescope defocusing - I. the transiting planetary system WASP-5

    , Article Monthly Notices of the Royal Astronomical Society ; Volume 396, Issue 2 , 2009 , Pages 1023-1031 ; 00358711 (ISSN) Southworth, J ; Hinse, T. C ; Jørgensen, U. G ; Dominik, M ; Ricci, D ; Burgdorf, M. J ; Hornstrup, A ; Wheatley, P. J ; Anguita, T ; Bozza, V ; Novati, S. C ; Harpsøe, K ; Kjærgaard, P ; Liebig, C ; Mancini, L ; Masi, G ; Mathiasen, M ; Rahvar, S ; Scarpetta, G ; Snodgrass, C ; Surdej, J ; Thöne, C. C ; Zub, M ; Sharif University of Technology
    We present high-precision photometry of two transit events of the extrasolar planetary system WASP-5, obtained with the Danish 1.54-m telescope at European Southern Obseratory La Silla. In order to minimize both random and flat-fielding errors, we defocused the telescope so its point spread function approximated an annulus of diameter 40 pixel (16 arcsec). Data reduction was undertaken using standard aperture photometry plus an algorithm for optimally combining the ensemble of comparison stars. The resulting light curves have point-to-point scatters of 0.50 mmag for the first transit and 0.59 mmag for the second. We construct detailed signal-to-noise ratio calculations for defocused... 

    Audio segmentation and classification based on a selective analysis scheme

    , Article Proceedings - 10th International Multimedia Modelling Conference, MMM 2004, Brisbana, 5 January 2004 through 7 January 2004 ; 2004 , Pages 42-48 ; 0769520847 (ISBN); 9780769520841 (ISBN) Ghaemmaghami, S ; Sharif University of Technology
    This paper addresses a new approach to segmentation and classification of audio through analysis of a smaller set of selective frames, which are identified by temporal decomposition (TD). These frames are located at the most steady instants, or event centroids, within a given block of the signal, which yield the maximal diversity over the set of selected features. Based on this selection scheme, the number of frames used in the analysis is reduced by at least 40%, while the temporal resolution is doubled as compared to that in typical audio classifiers. By constructing a classification system to segment audio into speech, music, speech-music, and others, it is shown that the proposed method... 

    Application Microarray Technology in Infectious Diseases

    , M.Sc. Thesis Sharif University of Technology Nazari Nodooshan, Khadijeh (Author) ; Mahdavi-Amiri, Nezameddin (Supervisor) ; Karami, Ali (Co-Advisor)
    DNA microarrays consist of DNA microscopic points that are attached to a solid surface such as glass, plastic or silicon chip and formed as an array. The fixed pieces of DNA are considered as searchers. In an experiment, we can use thousands of searchers. Therefore, any microarray consists of the same number of genetic tests as the experiment performed on all of them in parallel. Whit this ability, arrays have speeded up the biological investigations. Microarray technology can be seen as a continued development of southern blotting. However, the most important stage in this technology, analysis of data, requires reliable bioinformatics tools achieving high reliabilities. Infectious diseases,... 

    MAGIC: An open-source MATLAB toolbox for external control of transcranial magnetic stimulation devices

    , Article Brain Stimulation ; Volume 11, Issue 5 , 2018 , Pages 1189-1191 ; 1935861X (ISSN) Habibollahi Saatlou, F ; Rogasch, N. C ; McNair, N. A ; Biabani, M ; Pillen, S. D ; Marshall, T. R ; Bergmann, T. O ; Sharif University of Technology
    Elsevier Inc  2018

    RMet: An automated R based software for analyzing GC-MS and GC×GC-MS untargeted metabolomic data

    , Article Chemometrics and Intelligent Laboratory Systems ; Volume 194 , 2019 ; 01697439 (ISSN) Moayedpour, S ; Parastar, H ; Sharif University of Technology
    Elsevier B.V  2019
    Gas chromatography-mass spectrometry (GC-MS) and comprehensive two-dimensional gas chromatography-mass spectrometry (GC×GC-MS) are powerful techniques for measurement of all metabolites in complex metabolic samples. However, analyzing GC-MS and especially GC×GC-MS metabolomic data is a major challenge to the researchers in the field of metabolomics mainly due to the complexity and large data size. In this regard, an automated R based software entitled RMet has been developed to overcome the challenges in the metabolomic analysis workflow of GC-MS and GC×GC-MS data sets. Additionally, it is able to facilitate the complex process of extracting reliable and useful biological information from... 

    OGLE-2014-BLG-1186: Gravitational microlensing providing evidence for a planet orbiting the foreground star or for a close binary source?

    , Article Monthly Notices of the Royal Astronomical Society ; Volume 484, Issue 4 , 2019 , Pages 5608-5632 ; 00358711 (ISSN) Dominik, M ; Bachelet, E ; Bozza, V ; Street, R. A ; Han, C ; Hundertmark, M ; Udalski, A ; Bramich, D. M ; Alsubai, K. A ; Calchi Novati, S ; Ciceri, S ; D'Ago, G ; Figuera Jaimes, R ; Haugbølle, T ; Hinse, T. C ; Horne, K ; Jørgensen, U. G ; Juncher, D ; Kains, N ; Korhonen, H ; Mancini, L ; Menzies, J ; Popovas, A ; Rabus, M ; Rahvar, S ; Scarpetta, G ; Schmidt, R ; Skottfelt, J ; Snodgrass, C ; Southworth, J ; Starkey, D ; Steele, I. A ; Surdej, J ; Tsapras, Y ; Wambsganss, J ; Wertz, O ; Pietrukowicz, P ; Szymanski, M. K ; Mróz, P ; Skowron, J ; Soszynski, I ; Ulaczyk, K ; Poleski, R ; Wyrzykowski, Ł ; Kozłowski, S ; Sharif University of Technology
    Oxford University Press  2019
    Discussing the particularly long gravitational microlensing event OGLE-2014-BLG-1186 with a time-scale tE ∼ 300 d, we present a methodology for identifying the nature of localised deviations from single-lens point-source light curves, which ensures that (1) the claimed signal is substantially above the noise floor, (2) the inferred properties are robustly determined and their estimation is not subject to confusion with systematic noise in the photometry, (3) alternative viable solutions within the model framework are not missed. Annual parallax and binarity could be separated and robustly measured from the wing and the peak data, respectively. We find matching model light curves that involve... 

    Observation of EGRET gamma-ray sources by an extensive air shower experiment

    , Article Astronomy and Astrophysics ; Volume 434, Issue 2 , 2005 , Pages 459-467 ; 00046361 (ISSN) Khakian Ghomi, M ; Bahmanabadi, M ; Samimi, J ; Sharif University of Technology
    Ultra-high-energy (E > 100 TeV) Extensive Air Showers (EASs) have been monitored for a period of five years (1997-2003), using a small array of scintillator detectors in Tehran, Iran. The data have been analyzed taking into account the dependence of source counts on zenith angle. During a calendar year different sources come into the field of view of the detector at varying zenith angles. Because of varying thickness of the overlaying atmosphere, the shower count rate is extremely dependent on zenith angle, which has been carefully analyzed over time (Bahmanabadi et al. 2002, Exp. Astron., 13, 39). High energy gamma-ray sources from the EGRET third catalogue where observed and the data were... 

    A Data Mining Approach to Efficiently Improve Data Analysis in Energy Management Systems

    , M.Sc. Thesis Sharif University of Technology Joshaghani, Mohammad (Author) ; Bagheri Shouraki, Saeed (Supervisor)
    In Energy Management Systems, data analysis is done based on the information gathered from the electricity utility. The closer the information is to its real value, the better the data analysis in EMS becomes. Hence, improving the accuracy of the collected information leads to an improvement in data analysis in EMS. The information collected from the network consists of the measured values of voltage phasor at each bus, the generation or load power at each bus, and the power flow in branches. Since the total number of sensors are usually less than the total network’s parameters, it is not possible to precisely determine the values of Network’s parameters, and only an estimation of them can... 

    A Reactive Architecture for Big Data Streaming Analytics Platform in IoT

    , M.Sc. Thesis Sharif University of Technology Mirvakili, Esmaeil (Author) ; Habibi, Jafar (Supervisor) ; Fazli, Mohammad Amin (Supervisor)
    Today’s biggest IoT companies are built on the extraction of insight from data of sensors, and data processing has become crucial in IoT businesses. Nevertheless, the size of data which should be processed is growing significantly fast. The pace of the data growing has changed the nature of data processing in IoT. Today, IoT industries demand highly scalable and fault tolerant data processing architectures which can handle the massive amount of data. In this research, we presented a distributed architecture for scalable and resilient data processing based on the Liquid which is a nearline and offline big data architecture. We used the Reactive Manifesto to design the architecture highly... 

    Searches for New Physics with Opposite-Sign Di-Leptons(Using the CMS Experiment at the Large Hadron Collider)

    , Ph.D. Dissertation Sharif University of Technology Fahim, Ali (Author) ; Arfaei, Hessamaddin (Supervisor) ; Pape, Luc ($item.subfieldsMap.e)
    Among the proposals for new physics, Supersymmetry is the most popular to gradually appear at a yet unreached center-of-mass energy at the Large Hadron Collider (LHC). However, that doesn’t seem very likely. This thesis represents a search for any evidence of a minimal supergravity inspired scenario (mSUGRA) of R-parity conserving supersymmetry at the Compact Muon Solenoid (CMS) experiment. The analysis employs an event topology , which consists primarily of opposite-sign di-leptons accompanied by hadronic jets and missing transverse energy. The search utilizes data produced by the proton-proton collision of the LHC at a center-of-mass energy p s = 7 TeV and recorded by the CMS detector in... 

    Designing an Intelligent System to Analyze Electrograms of Induced Pluripotent Stem Cell-Derived Cardiomyocytes

    , M.Sc. Thesis Sharif University of Technology Golgooni, Zeinab (Author) ; Rabiee, Hamid Reza (Supervisor) ; Soleymani, Mahdieh (Supervisor) ; Pahlavan, Sara (Co-Advisor)
    Ability to differentiate induced pluripotent stem cells to cardiomycocytes has attracted attentions,considering crucial role of the heart in the human body and great potential applications of these cells like disease modeling, new treatment methods and basic research. We are able to analyze the performance of beating cells through recording extracellular field potentials of cardiomyocytes using multi-electrode array (MEA) technology. This analysis is an essential step to use cardiac cells in any future development and experiment. Currently, the electrophysiology experts analyze recorded extracellular field potentials of induced cardiomyocytes by observing all the episodes of each record.... 

    Architecture-aware Implementation of Graph Algorithms based on Linear Algebra in GPUs

    , M.Sc. Thesis Sharif University of Technology Barkhordar, Marzieh (Author) ; Sarbazi Azad, Hamid (Supervisor)
    Processing of large graphs is the key component in many data analytics applications.We model the relationship of entities in different applications, such as web page ranking, social networks and tracking drug interaction with cells, using graphs. Graphics processing unit (GPU) is a well-known accelerator used for graph processing. Unfortunately, there are many challenges for mapping graph applications to GPUs efficiently. As graph applications have more kernel invocations and data transfers, using caches in these applications would be ineffective. Since vertices’ degrees of a graph are different, load distribution in many graph applications is not well balanced.Recently, matrix algebra has... 

    Stock Market Prediction Based on Analysis of Textual and Numerical Data

    , M.Sc. Thesis Sharif University of Technology Taleb, Mohsen (Author) ; Akhavan Niaki, Taghi (Supervisor)
    Unstructured data is an important resource in data mining which In spite of their large volume, they haven’t been analyzed so much. Natural language data are a typical kind of unstructured data which humans can easily understand them but normally it is not possible for machines to process these kind of data. To make these data usable for prediction, pre-processing is required to prepare them for feeding into machine learning algorithms. Therefore, feature extraction is needed for texts in order to make presentative features from them that can unveil the hidden pattern. In this study, in addition to the variables that extracted from the technical indicators, the texts from telegram channels... 

    Machine Learning Based Modeling of Cognitive Performance from Life-style Data

    , M.Sc. Thesis Sharif University of Technology Jazayeri, Farnaz (Author) ; Razvan, Mohammad Reza (Supervisor) ; Khaligh Razavi, Mahdi (Supervisor)
    For neurodegenerative diseases like Multiple Sclerosis, Alzheimer’s, or Parkinson’s disease early detection is required to slow progression and prevent disease onset. To do so, identifying early signs and symptoms of the disease as well as modifying lifestyle can play a crucial role. Nowadays, the increasing use of smart gadgets and sensors has paved the way for collecting behavioral data and therefore analyzing and extracting meaningful patterns. In this study, lifestyle and cognitive performance data have been collected via a platform called OptiMind. Previous studies have shown that the Integrated Cognitive Assessment (ICA) can identify patients with neurodegenerative disorders (such as... 

    Hyperspectral Imaging Combined with Chemometric Techniques for Diagnosis of Breast Cancer

    , M.Sc. Thesis Sharif University of Technology Roshandel, Pegah (Author) ; Parastar Shahri, Hadi (Supervisor)
    Breast cancer is one of the most known types of cancer. About every eight women, one woman will suffer from one of the types of malignant tissues during her life. Diagnosing this type of cancer in the early stages is an important matter and can lead to full recovery. Therefore, one of the challenges in this field is the emergence of a fast method with high sensitivity to diagnose this disease in its early stages. Currently, biopsy is the standard method for breast cancer diagnosis. However, there are some drawbacks to this method. For instance, in order to detect the tumor margin, all breast tissue must be removed, which causes all breast tissue, including healthy tissues, to be removed.... 

    Persistent Homology and its Applications in Machine Learning

    , M.Sc. Thesis Sharif University of Technology Kiani, Amir (Author) ; Ranjbar, Alireza (Supervisor)
    Persistent homology is one of the main tools in Topological Data Analysis. Indeed, to deal with a huge dataset while noise sensitivity is important, persistent homology can reflect some information about data in the form of persistent homology groups and persistence diagrams. Note that statistical or linear algebraic tools are not suitable to work with huge datasets with very high dimensions. In this thesis, we discuss the concept of persistent homology and investigate some of its properties such as the stability of the persistence diagrams. Indeed, persistence diagrams are obtained from the generating sets of the persistent homology groups. Further, we discuss an application of persistent...