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    A volume decomposition model to determine machining features for prismatic parts

    , Article Journal of Applied Sciences ; Volume 9, Issue 9 , 2009 , Pages 1703-1710 ; 18125654 (ISSN) Houshmand, M ; Imani, D. M ; Sharif University of Technology
    2009
    Abstract
    Selection and development of machining features are the core activity in process planning. Usually the machining features development is done by experts according to elementary volumes. Performing this process by experts develops a limited machining features and the optimum solution may be missed. In this study a new method is developed to generate machining features and analyzes them to extract feasible features. The feasible solution is based on technical limitation of parts without any expert's judgments. Also it uses a set covering optimization technique to extract optimum one. Finally, the numerical results are presented and performance of the proposed method is tested by some candidate... 

    Probabilistic dynamic multi-objective model for renewable and non-renewable distributed generation planning

    , Article IET Generation, Transmission and Distribution ; Volume 5, Issue 11 , 2011 , Pages 1173-1182 ; 17518687 (ISSN) Soroudi, A ; Caire, R ; Hadjsaid, N ; Ehsan, M ; Sharif University of Technology
    2011
    Abstract
    This study proposes a probabilistic dynamic model for multi-objective distributed generation (DG) planning, which also considers network reinforcement at presence of uncertainties associated with the load values, generated power of wind turbines and electricity market price. Monte Carlo simulation is used to deal with the mentioned uncertainties. The planning process is considered as a two-objective problem. The first objective is the minimisation of total cost including investment and operating cost of DG units, the cost paid to purchase energy from main grid and the network reinforcement costs. The second objective is defined as the minimisation of technical risk, including the probability... 

    Single image super resolution by adaptive K-means clustering

    , Article 10th Iranian Conference on Machine Vision and Image Processing, MVIP 2017, 22 November 2017 through 23 November 2017 ; Volume 2017-November , April , 2018 , Pages 209-214 ; 21666776 (ISSN) ; 9781538644041 (ISBN) Rahnama, J ; Shirpour, M ; Manzuri, M. T ; Sharif University of Technology
    IEEE Computer Society  2018
    Abstract
    In recent days imaging systems have seen considerable extended usage due to their ease of use and reasonable price. However, they have weaknesses lies in image resolution. In order to increase the quality of the images, due to the technical limitations and costs of hardware parts, software techniques like the super-resolution is used, which means increasing the density of pixels in the image. The super-resolution is broken down into two categories; super-resolution using a single image and super-resolution using multiple images. In this paper, a method for increasing image quality, based on the Dong method has been proposed. In the proposed method, which is based on only one image, tries to...