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    The effect of a training program on body composition, growth hormone, insulin and insulin-like growth factor 1 in overweight female college students

    , Article Gazzetta Medica Italiana Archivio per le Scienze Mediche ; Volume 171, Issue 4 , 2012 , Pages 409-416 ; 03933660 (ISSN) Gholipour, M ; Tabrizi, A ; Sharif University of Technology
    2012
    Abstract
    Aim. The aim of this study was to determine the effect of a training program on body composition, GH, IGF-1 and insulin in overweight and obese female college students. Methods. The 17 overweight college student females divided into 2 groups: Experimental group (E) with 3 sessions per week, 6 weeks duration (N=9,Age=18.9 ± 1.3,BMI= 28.8 ± 2.6), and non-exercising control group (C) (N=8, Age=19.3 ± 1.8, BMI=26.3 ± 0.9). All measures included Vo2max, body composition, IGF-1, GH and insulin were done at baseline and following the protocol. Results. The calorie intake increased in both groups when compared to the baseline. The Vo2max increased statistically significant in E, and decreased in C.... 

    Comparison of the effects of growth hormone on acylated ghrelin and following acute intermittent exercise in two levels of obesity

    , Article Tehran University Medical Journal ; Volume 71, Issue 5 , 2013 , Pages 330-339 ; 16831764 (ISSN) Gholipour, M ; Tabrizi, A ; Sharif University of Technology
    2013
    Abstract
    Background: The prevalence of obesity has risen enormously over the past few decad-es. Both food intake (Appetite) and energy expenditure can influence body weight. Acylated ghrelin enhances appetite, and its plasma level is suppressed by growth horm-one. The present study, examines the effects of an intermittent exercise with progress-ive intensities on acylated ghrelin, appetite, and growth hormone in inactive male students with two levels of obesity. Methods: Eleven inactive males were allocated into two groups on the basis of their body mass index (BMI). Six subjects in group one, BMI= 31.18±0.92 kg/m2, and five subjects in group two, BMI= 36.94±2.25 kg/m2, ran on the treadmill with... 

    Artificial neural networks to predict 3D spinal posture in reaching and lifting activities; Applications in biomechanical models

    , Article Journal of Biomechanics ; Volume 49, Issue 13 , Volume 49, Issue 13 , 2016 , Pages 2946-2952 ; 00219290 (ISSN) Gholipour, A ; Arjmand, N ; Sharif University of Technology
    Elsevier Ltd  2016
    Abstract
    Spinal posture is a crucial input in biomechanical models and an essential factor in ergonomics investigations to evaluate risk of low back injury. In vivo measurement of spinal posture through the common motion capture techniques is limited to equipped laboratories and thus impractical for workplace applications. Posture prediction models are therefore considered indispensable tools. This study aims to investigate the capability of artificial neural networks (ANNs) in predicting the three-dimensional posture of the spine (S1, T12 and T1 orientations) in various activities. Two ANNs were trained and tested using measurements from spinal postures of 40 male subjects by an inertial tracking... 

    The role of hippo signaling pathway in physiological cardiac hypertrophy

    , Article BioImpacts ; Volume 10, Issue 4 , 2020 , Pages 251-257 Gholipour, M ; Tabrizi, A ; Sharif University of Technology
    Tabriz University of Medical Sciences  2020
    Abstract
    Introduction: The role of Hippo signaling pathway, which was identified by genetic studies as a key regulator for tissue growth and organ size, in promoting physiological cardiac hypertrophy has not been investigated. Methods: Fourteen male Wistar rats were randomly assigned to the exercise and control groups. The exercise group ran 1 hour per day, 5 days/week, at about 65%-75% VO2max on the motor-driven treadmill with 15ºslope, and the control group ran 15 min/d, 2 days/ week at 9 m/min (0ºinclination), throughout the eight-week experimental period. Forty-eight hours after the last session, hearts were dissected and left ventricles were weighed and stored for subsequent RT-PCR analysis.... 

    Critical Behavior of Neuronal Systems: an Information Theory Viewpoint

    , M.Sc. Thesis Sharif University of Technology Soltani, Miaad (Author) ; Moghimi, Saman (Supervisor)
    Abstract
    Experiments conducted in recent two decades indicated critical behavior in neural activity at different scales. Theoretically occurrences of these critical and power-law behavior can significantly facilitate brain activities correspondent to computation and memory tasks, but attaining the critical point essentially demands externally fine-tuning which has not been established yet. This fine-tuning often lies with placing system at transition point. Recent studies of group showed that a transition from synchronous to asynchronous phase could be achievable by a change in external parameters. At the very transition point, neuronal avalanches statistically demonstrate a power-law behavior which... 

    Green supply chain network design considering inventory-location-routing problem: A fuzzy solution approach

    , Article International Journal of Logistics Systems and Management ; Volume 35, Issue 4 , 2020 , Pages 436-452 Gholipour, S ; Ashoftehfard, A ; Mina, H ; Sharif University of Technology
    Inderscience Publishers  2020
    Abstract
    The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be... 

    Automated Lip-Reading robotic system based on convolutional neural network and long short-term memory

    , Article 13th International Conference on Social Robotics, ICSR 2021, 10 November 2021 through 13 November 2021 ; Volume 13086 LNAI , 2021 , Pages 73-84 ; 03029743 (ISSN) ; 9783030905248 (ISBN) Gholipour, A ; Taheri, A ; Mohammadzade, H ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    In Iranian Sign Language (ISL), alongside the movement of fingers/arms, the dynamic movement of lips is also essential to perform/recognize a sign completely and correctly. In a follow up of our previous studies in empowering the RASA social robot to interact with individuals with hearing problems via sign language, we have proposed two automated lip-reading systems based on DNN architectures, a CNN-LSTM and a 3D-CNN, on the robotic system to recognize OuluVS2 database words. In the first network, CNN was used to extract static features, and LSTM was used to model temporal dynamics. In the second one, a 3D-CNN network was used to extract appropriate visual and temporal features from the... 

    Sandpiles and Surface Growth

    , M.Sc. Thesis Sharif University of Technology Shahoei, Rezvan (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    We study the Abelian Sandpile Model and its relation with surface growth. ese two models are related through their field theories and equations of motion. It has been shown that the different features of different sandpile models can be expressed in terms of the noise term in the surface growth equation. A mapping between the simplest sandpile model, the BTW model, and a surface growth has already been introduced. is surface growth has not been studied in details so far. In this thesis we study different features of this surface growth corresponding to the BTW model, continuous sandpile model and also massive abelian sandpile model. We also consider different boundary conditions  

    The Abelian Sand-pile Model (ASM) and Generalization to the Continuous State

    , M.Sc. Thesis Sharif University of Technology Lotfi, Ehsan (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    The four-page article by Bak, Tang and Wiesenfeld in 1987 was a beginning to a new wave of physicists’ efforts to explain and describe the concept of complexity; a not-so-well-defined concept that resists against the reductionist tools and methods of physics. The Self-organized Criticality theory presented in that article via a simple model, known as sandpile model, was first of all an effort to explain the numerous occurrence of power law distribution in nature. SOC was introduced to tell us why so many natural phenomena like Earthquakes, landslides, forest fires, extinction and other seemingly non-related catastrophic events, more or less obey the scale-less power law distribution; A... 

    Transition from Abelian Sandpile Model to Manna Model

    , M.Sc. Thesis Sharif University of Technology Asasi, Hamed (Author) ; Moghimi-Araghi, Saman (Supervisor)
    Abstract
    In this research, we want to address the question of universality classes in BTW and Manna sandpile models. So far, number of works has been devoted to this issue but the the answer remained unsolved. We will try another approach to study this question by perturbing the original models. To this end, we introduce three models that have evolution rules between BTW model and Manna model. By simulating this models, we observe that in the presence of perturbation, the probability dis- tribution has two regimes of behaviour which are separated by a new characteristic scale. The regime of small avalanches is described by the exponent of BTW model and the regime of large avalanches by the exponent... 

    Generalized Growth Models

    , M.Sc. Thesis Sharif University of Technology Imani, Shima (Author) ; Moghimi-Araghi, Saman (Supervisor)
    Abstract
    Edwards-Wilkinson’s equation can be achieved from a Hamiltonian. When we have the Hamiltonian for the system, there are common approaches that makes it out of critical. In other words,the ”mass” should be added to the system. In this study we have tried to simulate and solve analytically these models that are involved mass term. We try to onstruct these mass terms in a way that have a minimum impact on the system and we study the quantities that characterize the out of critical behaviors  

    Percolation on Small World Networks

    , M.Sc. Thesis Sharif University of Technology Masoomi, Razie (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    Percolation is a phenomenon that can be found in many physical problems. Additionally, as a statistical model, it has a very rich physics, since many fundamental concepts in the context of critical phenomena and complex systems-such as phase transition, scaling laws etc can be found in the model. Percolation phenomenon can be defined on different lattices. In this thesis we study percolation on small-world networks. In small-world networks, in addition to local bonds that connects the neighbouring sites, there exist some long-ranged bonds that connect cites far from each other. Social networks, some networks of internet or the gene networks are examples of such networks. Therefore, to study... 

    Chaos in Sandpile Models With and Without Bulk Dissipation

    , M.Sc. Thesis Sharif University of Technology Mollabashi, Ali (Author) ; Moghimi-Araghi, Saman (Supervisor)
    Abstract
    A complte set of characteristic parameters of the sandpile models is still unknown. We have studied the existence of ”weak chaos” critical exponent in different sandpile models and we have shown that it is a characteristic exponent of deterministic models. We have shown that BTW and Zhang models do not belong to the same universality class (contrary to Zhang’s previous conjecture and contrary to Ben-Hur & Biham’s results.) Also we have shown that directed models, specificly Ramaswamy-Dhar’s directed model form a different universality class. ”Weak chaos” exponent in also studied in massive models and we have shown that by increase of dissipation, the exponent decreases rapidly to an... 

    Simulation of the Self-organized Critical Models on the
    Human’s Brain Network

    , M.Sc. Thesis Sharif University of Technology Shokouhi, Fatemeh (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    Self-organized critical phenomena are interesting phenomena which are ubiquitous in nature. Examples include mountain ranges , coastlines and also activities in the hu-man's brain. In these processes, without fine-tuning of any external parameter such as the temperature, the system exhibits critical behavior. In other words, the dynamics of the system, drives it towards an state in which long range correlations in space and scaling behaviors can be seen.The first successful model which could characterize such systems was BTW model, introduced by Bak , Tang and Wiesenfeld in 1987. This model, later named Abelian sandpile model, was very simple and because of this simplicity, a large amount of... 

    Fluctuations in the order of System Size in the Avalanche-Size Distribution of Sandpiles Model

    , M.Sc. Thesis Sharif University of Technology Saadat, Elaheh (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    Since the concept of Self-Organized Criticality was introduced in terms of BTW Sandpiles model, its major features have been known as broad power law distributions without any tuning parameters. In some selforganized critical systems like brain and neural networks, some evidences and experiments show a periodic or non-power law distribution of avalanches in addition to the power-law distributions of avalanches. In this thesis we try to observe the same phenomenon in the well-known SOC models, namely the BTW and Manna sandpile models. We have considered small lattice sizes with periodic boundary conditions and a small amount of dissipation. Within such conditions we observe a periodic-like... 

    Burridge-Knopoff Model with Nonuniform Parameters

    , M.Sc. Thesis Sharif University of Technology Shahin, Ali (Author) ; Moghimi-Araghi, Saman (Supervisor)
    Abstract
    Power law behavior of earthquakes has been a matter of interest for many scientists. One on these power laws known as Gutenberg-Richter law describes the magnitude distribution of earthquakes. The Burridge-Knopoff model of faults, produces the same power law distribution of events as the Gutenberg-Richter law for earthquakes. Olami, Feder and Christensen in 1992, introduced a 2-D, continues sand pile model Known as OFC that displays self-organized-criticality. They claimed that this model is equivalent to Burridge-Knopoff model. It means that criticality is the origin of power law behavior of the Burridge-Knopoff model. Nevertheless, there are some evidence against criticality in the... 

    Mullins-Herring Equation with Lateral Growth

    , M.Sc. Thesis Sharif University of Technology Ghamari, Danial (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    Surface growth have been one of the most interesting topics of research in non-equilibrium Statistical physics, due to their relevance in studying industrial growth processes. Many models such as Edwards-Wilkinson and KPZ have been proposed to study these systems where by incorporating renormalization group, numerical integration and computer simulations we can derive their critical exponents. In general, a thermal noise is implemented in these models, however, other types can be used as well. In particular for the case of Edwards-Wilkinson, it has been shown that a multiplicative noise changes the universality class of the model. In this thesis we want to investigate the effects of... 

    The Role of Simplified Models for Neurons in the Emergence of Collective Behaviors in Neuronal Populations

    , M.Sc. Thesis Sharif University of Technology Hosseini, Nafiseh (Author) ; Moghimi Araghi, Saman (Supervisor)
    Abstract
    The brain, as a complex system with various components working in concert, plays a fundamental role in many cognitive processes and human perception of the surrounding environment. Perception, in many cases, can differ from reality due to evolutionary processes, natural selection, or even flaws in any of the parameters within this complex intelligent system. One of the observed phenomena in perception is the heightened visibility of edges, often depicted with Mach bands. To describe this phenomenon, primarily, rate models are used, especially in regions where a linear approximation is suitable for neuronal responses. However, the response of neuronal populations in a range of external... 

    Production planning problem with pricing under random yield: CVAR criterion [electronic resource]

    , Article Journal of Systems Science and Systems Engineering ; 2014 Eskandarzadeh, S. (Saman) ; Eshghi, Kourosh ; Modarres Yazdi, Mohammad ; Bahramgiri, Mohsen ; Sharif University of Technology
    Abstract
    In this paper, we address a basic production planning problem with price dependent demand and stochastic yield of production. We use price and target quantity as decision variables to lower the risk of low yield. The value of risk control becomes more important especially for products with short life cycle. This is because, the profit implications of low yield might be unbearable in the short run. We apply Conditional Value at Risk (CVaR) to model the risk. CVaR measure is a coherent risk measure and thereby having nice conceptual and mathematical underpinnings. It is also widely used in practice. We consider the problem under general demand function and general distribution function of... 

    An adaptive regression tree for non-stationary data streams

    , Article Proceedings of the ACM Symposium on Applied Computing ; March , 2013 , Pages 815-816 ; 9781450316569 (ISBN) Gholipour, A ; Hosseini, M. J ; Beigy, H ; Sharif University of Technology
    2013
    Abstract
    Data streams are endless flow of data produced in high speed, large size and usually non-stationary environments. The main property of these streams is the occurrence of concept drifts. Using decision trees is shown to be a powerful approach for accurate and fast learning of data streams. In this paper, we present an incremental regression tree that can predict the target variable of newly incoming instances. The tree is updated in the case of occurring concept drifts either by altering its structure or updating its embedded models. Experimental results show the effectiveness of our algorithm in speed and accuracy aspects in comparison to the best state-of-the-art methods