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Designing a LQR controller for an electro-hydraulic-actuated-clutch model
, Article Proceedings of 2016 2nd International Conference on Control Science and Systems Engineering, ICCSSE 2016, 27 July 2016 through 29 July 2016 ; 2016 , Pages 82-87 ; 9781467398725 (ISBN) ; Selk Ghafari, A ; Pourebrahim, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
Abstract
During the past decade, Electro-Hydraulic system has performed a significant role in industrial engineering as an actuator for high performance and precision positioning applications. In this case, many control methods have been developed for an electro-hydraulic actuated clutch. In this paper a Linear Quadratic Regulators (LQR) is proposed to trajectory control of a wet clutch actuated by a hydraulic servo valve mechanism. Simulation study was performed using linearized mathematical model of the system implemented in MATLAB software. Based on the simulation results performance of the proposed controller was evaluated and discussed
Heat and Cooling Load Management through Minimizing the Heat Transfer and Utilizing the Storage Potential of Materials and Equipment Inside a Building
, M.Sc. Thesis Sharif University of Technology ; Saboohi, Yadollah (Supervisor)
Abstract
Buildings are responsible for 40% of total energy consumption worldwide. A significant portion of this energy contributes to building temperature control, and energy storage is an effective way to reduce energy consumption and to levelize the supply of heat load. A solution for reducing energy consumption in the building is to increase the thermal inertia of the building and to store energy using smart materials in the building components. Materials with phase change can stabilize the internal temperature of the building.In the present study, model is exmined with the help of modeling the thermal behavior of a room in Tehran in summer, using MATLAB software. The problem is solved by the...
Design and Implementat of a Navigating Procedure for Robotic-assisted Fracture Reduction of Long Bones
, M.Sc. Thesis Sharif University of Technology ; Farahmand, Farzam (Supervisor)
Abstract
During femur fracture reduction surgery, both patients and surgeons are exposed to a great amount of radiation, which is harmful to their health. Computer-assisted orthopaedic surgery (CAOS) is a less invasive approach for its ability to reduce the usage of image intensifiers. Various robots have been developed for femur fracture reduction surgery. Most of these robots are based on serial architectures. Both low load-carrying capacity and poor accuracy are inherent to serial robots, which makes them inappropriate for femur fracture reduction. Some parallel robots using the “Stewart platform” have also been developed for femur fracture reduction, but their restricted workspace limits their...
Semi-supervised parallel shared encoders for speech emotion recognition
, Article Digital Signal Processing: A Review Journal ; Volume 118 , 2021 ; 10512004 (ISSN) ; Razzazi, F ; Sameti, H ; Sharif University of Technology
Elsevier Inc
2021
Abstract
Supervised speech emotion recognition requires a large number of labeled samples that limit its use in practice. Due to easy access to unlabeled samples, a new semi-supervised method based on auto-encoders is proposed in this paper for speech emotion recognition. The proposed method performed the classification operation by extracting the information contained in unlabeled samples and combining it with the information in labeled samples. In addition, it employed maximum mean discrepancy cost function to reduce the distribution difference when the labeled and unlabeled samples were gathered from different datasets. Experimental results obtained on different emotional speech datasets...
Fairness in Machine Learning
, M.Sc. Thesis Sharif University of Technology ; Foroughmand Araabi, Mohammad Hadi (Supervisor)
Abstract
As machine learning continues to be used extensively in all aspects of human life, especially social and legal decision making; Concerns have been raised about data-driven software and services biasing against certain demographic groups. Machine learning fairness, which refers to methods for correcting algorithmic bias in automated decision-making systems, is not only a social concern but also an industry need for developing human-centered tools.The study reviews studies on bias, fairness definitions, and attempts to reduce bias in machine learning models. Eventually, we suggest a method for reducing bias in imbalanced datasets
On the use of compressive sensing for image enhancement
, Article Proceedings - 2016 UKSim-AMSS 18th International Conference on Computer Modelling and Simulation, UKSim 2016, 6 April 2016 through 8 April 2016 ; 2016 , Pages 167-171 ; 9781509008889 (ISBN) ; Ghorshi, S ; Khoshnevis, S. A ; Pourebrahim, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2016
Abstract
Compressed Sensing (CS), as a new rapidly growing research field, promises to effectively recover a sparse signal at the rate of below Nyquist rate. This revolutionary technology strongly relies on the sparsity of the signal and incoherency between sensing basis and representation basis. Exact recovery of a sparse signal will be occurred in a situation that the signal of interest sensed randomly and the measurements are also taken based on sparsity level and log factor of the signal dimension. In this paper, compressed sensing method is proposed to reduce the noise and reconstruct the image signal. Noise reduction and image reconstruction are formulated in the theoretical framework of...