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    Critique of Kuhns Histirical Perspective from Gadamerian Perspective

    , M.Sc. Thesis Sharif University of Technology Behzadi Moghaddam, Mohammad Reza (Author) ; Moeinzadeh, Mahdi (Supervisor) ; Taghavi, Mostafa (Supervisor)
    Abstract
    Truth and Method is one of the two or three most important works of this century on the philosophy of humanistic studies. The book is powerful, exciting, but undeniably difficult. Published when Gadamer was sixty, it gathers the ripe fruit of a lifetime's reading, teaching, and thinking. Because it is immersed in German philosophy and scholarship, the book is even more challenging for an American reader. An emerging body of commentary in English as well as the many shorter essays Gadamer has, happily, lived to write and which are increasingly available in translation provide additional means of access to his thought. Truth and Method, however, remains his magnum opus, the comprehensive and... 

    Neural network-based approaches, solving haplotype reconstruction in MEC and MEC/GI models

    , Article Neural Computing and Applications ; Volume 22, Issue 7-8 , 2013 , Pages 1397-1405 ; 09410643 (ISSN) Moeinzadeh, M. H ; Asgarian, E ; Sharifian-R. S ; Sharif University of Technology
    2013
    Abstract
    Single nucleotide polymorphism (SNP) in human genomes is considered to be highly associated with complex genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of recent studies on human genomics. The two sequences of SNPs in diploid human organisms are called haplotypes. In this paper, the problem of haplotype reconstruction from SNP fragments with and without genotype information is studied. Minimum error correction (MEC) is an important model for this problem but only effective when the error rate of the fragments is low. MEC/GI, as an extension to MEC model, employs the related genotype information besides the SNP fragments and,... 

    F.C.A: designing a fuzzy clustering algorithm for haplotype assembly

    , Article IEEE International Conference on Fuzzy Systems, 20 August 2009 through 24 August 2009 ; 2009 , Pages 1741-1744 ; 10987584 (ISSN) ; 9781424435975 (ISBN) Moeinzadeh, M. H ; Asgarian, E ; Noori, M. M ; Sadeghi, M ; Sharifian R., S ; Sharif University of Technology
    2009
    Abstract
    Reconstructing haplotype in MEC (Minimum Error Correction) model is an important clustering problem which focuses on inferring two haplotypes from SNP fragments (Single Nucleotide Polymorphism) containing gaps and errors. Mutated form of human genome is responsible for genetic diseases which mostly occur in SNP sites. In this paper, a fuzzy clustering approach is performed for haplotype reconstruction or haplotype assembly from a given sample Single Nucleotide Polymorphism (SNP). In the best previous approach based on reconstruction rate (Wang 2007[2]), all SNP-fragments are considered with equal values. In our proposed method the value of the fragments are based on the degree of membership... 

    MBBR and MBR Reactor Configuration for Better Performance

    , M.Sc. Thesis Sharif University of Technology (Author) ; Borgheei, Mahdi (Supervisor)
    Abstract
    Membrane bioreactors (MBRs) which are commonly understood as the combination of membrane filtration and biological treatment using activated sludge have several advantages, but membrane fouling reduces the membrane efficiency, permeability and lifetime. An alternative is replacing a moving bed biofilm reactor (MBBR) with the activated sludge system which may reduce the effect of membrane fouling. The sludge produced in MBBRs has poor settling characteristics, therefore, their efficiency is limited by the sedimentation tank performance and they require a larger settling surface. The combination of moving bed biofilm reactors and membrane bioreactors can compensate for the drawbacks of both of... 

    Finding feasible timetables with particle swarm optimization

    , Article Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, 18 November 2007 through 20 November 2007 ; 2007 , Pages 387-391 ; 9781424418411 (ISBN) Qarouni Fard, D ; Najafi Ardabifi, A ; Moeinzadeh, M. H ; Sharifian R, S ; Asgarian, E ; Mohammadzadeh, J ; Sharif University of Technology
    IEEE Computer Society  2007
    Abstract
    A Timetabling problem is usually defined as assigning a set of events to a number of rooms and timeslots such that they satisfy a number of constraints. Particle swarm optimization (PSO) is a stochastic, population-based computer problem-solving algorithm; it is a kind of swarm intelligence that is based on social-psychological principles and provides insights into social behavior, as well as contributing to engineering applications. This paper applies the Particle Swarm Optimization algorithm to the classic Timetabling problem. This is inspired by similar attempts belonging to the evolutionary paradigm in which the metaheuristic involved is tweaked to suit the grouping nature of problems... 

    Three heuristic clustering methods for haplotype reconstruction problem with genotype information

    , Article Innovations'07: 4th International Conference on Innovations in Information Technology, IIT, Dubai, 18 November 2007 through 20 November 2007 ; 2007 , Pages 402-406 ; 9781424418411 (ISBN) Moeinzadeh, M. H ; Asgarian, E ; Najafi Ardabili, A ; Sharifian R, S ; Sheikhaei, M. S ; Mohammadzadeh, J ; Sharif University of Technology
    IEEE Computer Society  2007
    Abstract
    Most positions of the human genome are typically invariant (99%) and only some positions (1%) are commonly variant which are associated with complex genetic diseases. Haplotype reconstruction is to divide aligned SNP fragments, which is the most frequent form of difference to address genetic diseases, into two classes, and thus inferring a pair of haplotypes from them. Minimum error correction (MEC) is an important model for this problem but only effective when the error rate of the fragments is low. MEC/GI as an extension to MEC employs the related genotype information besides the SNP fragments and so results in a more accurate inference. The haplotyping problem, due to its NP-hardness, may... 

    Forecasting the effects of a Canada-US currency union on output and prices: A counterfactual analysis

    , Article Journal of Forecasting ; Volume 32, Issue 7 , 2013 , Pages 639-653 ; 02776693 (ISSN) Mahdi Barakchian, S ; Sharif University of Technology
    2013
    Abstract
    This paper is a counterfactual analysis investigating the consequences of the formation of a currency union for Canada and the USA: whether outputs increase and prices decrease if these countries form a currency union. We use a two-country cointegrated model to conduct the counterfactual analysis, where the conditional forecasts are generated based on the Gaussian assumption. To deal with structural breaks and model uncertainty, conditional forecasts are generated from different models/estimation windows and the model-averaging technique is used to combine the forecasts. We also examine the robustness of our results to parameter uncertainty using the wild bootstrap method. The results show... 

    Evaluation of Non-linear Combination Method (Neural Network) For Value-at-Risk Forecasting in Market

    , M.Sc. Thesis Sharif University of Technology Rashnavadi, Leila (Author) ; Barakchian, Mahdi (Supervisor)
    Abstract
    Value at risk of an asset, is the asset’s expected maximum loss for a certain period of time and at a specified confidence level. Value-at-Risk can be calculated in the bank with its inter-nal method or standardized method. when a method have more violation number then bank need to keep more daily capital requirements. under the Basel 2 agreement if the violation of method more than 10 times in year, the Bank uses the standardized method.
    There are trade off Between daily capital charge and violations. Therefore, existing methods for calculating the value at risk, usually lead to much daily capital charge or many violations. Studies show with combination of different methods to calculate... 

    Using Complex Network Metrics for Evaluating the Influence of Conference and Journal Papers in Computer Science

    , M.Sc. Thesis Sharif University of Technology Habibi, Fatemeh (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    Journals and conferences in computer science are the major venue for publishing new achievement in the field. It is an expert opinion that a number of top conferences in computer science are even more important than journals. In this work we aim at studying this in terms of citation analysis. To this end, we took 100 top journals and 63 top conferences and extracted their citation graph through Scopus dataset. We then constructed the citation graph in which the nodes were the journals and conferences and the links corresponded to the citations of the papers. We used various measures to rank the nodes in the graph. The ranking methods included Prestige, PageRank, Eigenfactor, HITS and SALSA.... 

    Design and Implementation of a VLSI Architecture for Time and Frequency Synchronization in the LTE

    , M.Sc. Thesis Sharif University of Technology Golnari, Amene (Author) ; Shabany, Mahdi (Supervisor)
    Abstract
    The long term evolution (LTE) standard is introduced and developed by the 3rd generation partnership project (3GPP) based on orthogonal frequency division multiplexing (OFDM). OFDM systems, in spite of having many advantages such high performance in bandwidth usage, are very sensitive to inter carrier interference (ICI) as a drawback. In order to prevent ICI, the frequency offset, mainly caused by the miss-match between oscillators' frequency and also between the sampling frequency of the transmitter and the receiver, should be estimated and compensated. Frequency synchronization is a part of the tasks of a synchronizer. In this thesis, main tasks of a synchronizer are illustrated and... 

    A New Approach in Value-at-Risk (VaR) Estimation by Forecast Combination Methods

    , M.Sc. Thesis Sharif University of Technology Seraj, Mostafa (Author) ; Barakchian, Mahdi (Supervisor)
    Abstract
    Value-at-Risk (VaR) is the most commontool for risk management. This tool is used to measure market risk and also used as a basis in determining financial standards for international financial institutions. VaR is the maximum loss of the asset portfolio at the specified confidence level and certain time horizon. Many parametric, nonparametric and semi parametric methods have been invented for VaR estimation. Each one of these methods has its advantages and disadvantages and different methods may perform better in differnet situations.When estimating VaR, we can choose one of these methods or we can combine the VaRs estimated by different methods. There are few researches conducted on VaR... 

    EEG Brain Functional Network Analysis in Cortex Level

    , M.Sc. Thesis Sharif University of Technology Pedrood, Bahman (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    Complex networks science have received tremendous attention in recent years and the brain is one of the systems to which graph theoretical tools have been applied. Alzheimer’s disease (AD) is a neurodegenerative disease affecting many of elderly population. AD changes the anatomy of the brain, which subsequently results in changes in its functions. These changes have been frequently reported in signals recorded from the brain (such as MEG, fMRI and EEG). Among these neuroimaging techniques EEG is one of the most aproprate methods for extracting functional connectivites according to high temporal resolution. In this thesis, we aimed at analyzing the properties of EEG-based functional networks... 

    Learning Improvement in Phase Oscillator Models

    , M.Sc. Thesis Sharif University of Technology Aghighi, Meysam (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    In the recent years, the problem of modeling a cognitive task using phase oscillators has been receiving a significant attention. In this view, single neurons are no longer elementary computational units. Rather, coherent oscillating groups of neurons are seen as nodes of networks performing cognitive tasks. From this assumption, we develop a model of stimulus-response learning and recognition. The most significant part of our work is defining learning methods for natural frequencies and coupling weights in a coupled phase oscillator network under Kuramoto conditions. In this thesis, we improved the previous models by not only emphasizing on the frequency of the oscillators but also taking... 

    Evaluation of Caviar Models Incorporated with Intraday Information ,the Case Study:Estimation Value at Risk of Gold

    , M.Sc. Thesis Sharif University of Technology Karimi, Parvane (Author) ; Barakchian, Mahdi (Supervisor)
    Abstract
    Value at risk (VaR) is the maximum loss of the asset portfolio at the specified confidence level and certain time horizon. This tool is used to measure market risk and also used as a basis in determining financial standards for international financial instituation. Conditional Autoregressive Value at Risk models or CAViaR models introduced by Engle and Manganelli (2004). This models calculate VaR base on quantile regession approach and show some promising performance properties.
    In order to propose a more accurate model for calcutating VaR , we develop CAViaR models by incorporating them with intraday information then we calculate VaR with this kind of models and CAViaR... 

    Design and Implementation of a Spectrum Sensor for Cognitive Radio

    , M.Sc. Thesis Sharif University of Technology Safavi, Mahya (Author) ; Shabani, Mahdi (Supervisor)
    Abstract
    Frequency scarcity has emerged the necessity of opportunistic utilization of frequency bands, which can be realized through a cognitive radio system. During an agile communication between unlicensed users, a cognitive radio system must avoid collision with licensed users. Hence it should continuously observe the band of interest and report the presence of licensed user signals. This task is fulfilled by a vital part of a cognitive radio system, called the spectrum sensing core. Recently several techniques have been proposed for the spectrum sensing in literature. Some of them like matched filtering, cyclostationarity based detection are based on primary user signal features. However energy... 

    VLSI Architecture of Turbo Decoder for LTE

    , M.Sc. Thesis Sharif University of Technology Ardakani, Arash (Author) ; Shabany, Mahdi (Supervisor)
    Abstract
    Long Term Evolution (LTE) aims the peak data rates in excess of 300 Mb/s, which may appear to be challenging to achieve due to the existence of some blocks such as the turbo decoder. One efficient approach to achieve this throughput is by parallelizing the Log Maximum a Posteriori (MAP) algorithm in the turbo decoder. In fact, the interleaver is known to be a major challenging part of the turbo decoder due to its need to the parallel interleaved memory access. LTE uses Quadratic Permutation Polynomial (QPP) interleaver, which makes it suitable for the parallel decoding. In this thesis, first, we propose an efficient architecture for the QPP interleaver, called the Add-Compare-Select (ACS)... 

    Efficient Hardware Implementation of ECG Derived Respiration (EDR) System, Applied to Body Area Network (BAN)

    , M.Sc. Thesis Sharif University of Technology Shayei, Ali (Author) ; Shabany, Mahdi (Supervisor)
    Abstract
    The rapid growth in the health care technology, has made the Body Area Network (BAN) as an attracting topic for research and design development. BAN devices have restrictions on their size and power consumption. Monitoring the respiratory signal is crucial in many medical applications and is normally part of a BAN system. Traditional methods for the respiration measurement are normally based on measuring the volume of air inhaled and exhaled by lungs (like a spirometer) or oxygen saturation in blood. However, these methods have numerous drawbacks including their high cost and limited accessibility. In this thesis, a novel scheme is proposed to derive the respiratory signal from the... 

    Dynamic Security Assessment in Restructured Power Systems

    , Ph.D. Dissertation Sharif University of Technology Kheradmandi, Morteza (Author) ; Ehsan, Mahdi (Supervisor)
    Abstract
    This thesis addresses the problem of dynamic security assessment in power sys-tems with an emphasis on its application in restructured power systems and issues arising in its applications. The new electric utility environment has an immedi-ate consequence of emphasis on reliability and secure operation of power systems. This requires faster and more precise methods to assess the dynamic aspect of se-curity. On the other hand, this issue is becoming challenging when the determined dispatch might not be accommodated due to violation of the limits.This thesis addresses the problem of dynamic security assessment in power sys-tems with an emphasis on its application in restructured power systems... 

    Incommensurability Problems: Feyerabend’s Linguistic Solution

    , M.Sc. Thesis Sharif University of Technology Shafah, Alireza (Author) ; Nasrin, Mahdi (Supervisor)

    Constructing EEG-Based Brain Functional Connectome Using Network-based Statistics

    , M.Sc. Thesis Sharif University of Technology Barzegaran, Elham (Author) ; Jalili, Mahdi (Supervisor)
    Abstract
    In recent years, there have been increasing attempts to study brain connectivity. Among a number of brain mapping techniques, Electroencephalography is an easy to use and cheap method that can be used in the study of brain function. One way of understanding the intricate wiring pattern and functions of brain is to consider it as a complex network. In this approach, a graph of brain functions, based on the functional relation of recorded electric signals, is constructed and then the network is evaluated with a number of network metrics that measure its different aspect of structure. Different neurological and psychological diseases can affect the connectivity power within the brain; as a...