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    Network and application-aware cloud service selection in peer-assisted environments

    , Article IEEE Transactions on Cloud Computing ; Volume 9, Issue 1 , 2021 , Pages 258-271 ; 21687161 (ISSN) Askarnejad, S ; Malekimajd, M ; Movaghar, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2021
    Abstract
    There are a vast number of cloud service providers, which offer virtual machines (VMs) with different configurations. From the companies perspective, an appropriate selection of VMs is an important issue, as the proper service selection leads to improved productivity, higher efficiency, and lower cost. An effective service selection cannot be done without a systematic approach due to the modularity of requests, the conflicts between requirements, and the impact of network parameters. In this paper, we introduce an innovative framework, called PCA, to solve service selection problem in the hybrid environment of peer-assisted, public, and private clouds. PCA detects the conflicts between the... 

    Integration of the intelligent optimisation algorithms with the artificial neural networks to predict the performance of a counter flow wet cooling tower with rotational packing

    , Article International Journal of Ambient Energy ; 2021 ; 01430750 (ISSN) Assari, N ; Assareh, E ; Alirahmi, M ; Hosseini, H ; Nedaei, M ; Rahimof, Y ; Fathi, A ; Behrang, M ; Jafarinejad, T ; Sharif University of Technology
    Taylor and Francis Ltd  2021
    Abstract
    The present study investigated a counter-flow cooling tower performance by integrating the Artificial Neural Networks and Intelligent Optimisation Algorithms (ANN-IOAs). For this purpose, two scenarios were evaluated. In the first scenario, inlet air wet-bulb temperature (T aw), inlet air dry bulb temperature (T ad), water to the air mass flow rate ratio (mw /ma), and rotor speed (υ) were the input parameters for the ANNs, while the output temperature (T wo) was the ANNs output. In the second scenario, the same input parameters applied for the first scenario were used as input variables and the tower efficiency (ε) was considered as an output parameter. The well-known IOAs methods, namely,... 

    Optimized integrated design of a high-frequency medical ultrasound transducer with genetic algorithm

    , Article SN Applied Sciences ; Volume 3, Issue 6 , 2021 ; 25233971 (ISSN) Babazadeh Khameneh, A ; Chabok, H. R ; Nejat Pishkenari, H ; Sharif University of Technology
    Springer Nature  2021
    Abstract
    Designing efficient acoustic stack and elements for high-frequency (HF) medical ultrasound (US) transducers involves various interrelated parameters. So far, optimizing spatial resolution and acoustic field intensity simultaneously has been a daunting task in the area of HF medical US imaging. Here, we introduce optimized design for a 50-MHz US probe for skin tissue imaging. We have developed an efficient design and simulation approach using Krimholtz, Leedom and Matthaei (KLM) equivalent circuit model and spatial impulse response method by means of Field II software. These KLM model and Field II software are integrated, and a GA algorithm is used to optimize the design of the US transducer... 

    Dynamic iranian sign language recognition using an optimized deep neural network: An implementation via a robotic-based architecture

    , Article International Journal of Social Robotics ; 2021 ; 18754791 (ISSN) Basiri, S ; Taheri, A ; Meghdari, A. F ; Boroushaki, M ; Alemi, M ; Sharif University of Technology
    Springer Science and Business Media B.V  2021
    Abstract
    Sign language is a non-verbal communication tool used by the deaf. A robust sign language recognition framework is needed to develop Human–Robot Interaction (HRI) platforms that are able to interact with humans via sign language. Iranian sign language (ISL) is composed of both static postures and dynamic gestures of the hand and fingers. In this paper, we present a robust framework using a Deep Neural Network (DNN) to recognize dynamic ISL gestures captured by motion capture gloves in Real-Time. To this end, first, a dataset of fifteen ISL classes was collected in time series; then, this dataset was virtually augmented and pre-processed using the “state-image” method to produce a unique... 

    Observation of stage position in a two-axis nano-positioner using hybrid Kalman filter

    , Article Scientia Iranica ; Volume 28, Issue 5 B , 2021 , Pages 2628-2638 ; 10263098 (ISSN) Bayat, S ; Nejat Pishkenari , H ; Salarieh, H ; Sharif University of Technology
    Sharif University of Technology  2021
    Abstract
    This study presents a novel method for observation of stage position in a 2D nano-positioning system based on a hybrid Kalman filter. The proposed method obviates the need to measure the stage position directly using complex and costly capacity sensors. Instead, traditional piezo actuators equipped with strain gauge sensors are utilized to measure the deection of the magnification system at the position of actuators. Then, a powerful estimation algorithm called Kalman filter was employed to observe stage displacements. The designed hybrid Kalman filter uses dynamical equations of motion in the prediction step. The piezo actuators deections are measured and exploited to correct the predicted... 

    Water-energy nexus approach for optimal design of hybrid cooling system in direct reduction of iron plant

    , Article Journal of Cleaner Production ; Volume 287 , 2021 ; 09596526 (ISSN) Hashemi Beni, M ; Morad Bazofti, M ; Akbari Mohammadi, A ; Mokhtari, H ; Saboohi, Y ; Golkar, B ; Ghandi, A. H ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    Direct reduction of iron process in steel industry has special production conditions. Low quality cooling water, low cold and high hot cooling water temperature, space limitation for new equipment installation, high value-added of product and severe effect of cooling water temperature on production rate are of these conditions. Considering technical and economic constraints and limitations, this situation makes this process an attractive case study for converting the existing wet cooling tower to hybrid cooling system. In this paper, based on integration of process, dry and wet cooling system and ambient conditions profiles, a new method for designing hybrid cooling system has been proposed.... 

    Minimization of Non-repeatable Runout (NRRO) in High-Speed Spindle Bearings

    , Article SAE 2021 Automotive Technical Papers, WONLYAUTO 2021, 1 January 2021 ; Issue 2021 , 2021 ; 01487191 (ISSN) Farahani, M. R ; Khodaygan, S ; Sharif University of Technology
    SAE International  2021
    Abstract
    The production with high quality at the lowest production time can be a key means to success in the competitive environment of manufacturing companies. Therefore, in recent years, the need for extra precise and high-speed machine tools has been impressively increased in manufacturing applications. One of the main sources of errors in the motion of high-speed spindles is the occurrence of non-repetitive runouts (NRRO) in the bearing. The NRRO can be caused by some factors such as the form of balls, the waviness of rings, the number of balls, and the permutation of one or two balls in the ball bearing. In this paper, a Taguchi-based approach is proposed for the optimal design of high-speed... 

    Machine learning approach for carrier surface design in carrier-based dry powder inhalation

    , Article Computers and Chemical Engineering ; Volume 151 , 2021 ; 00981354 (ISSN) Kazemzadeh Farizhandi, A. A ; Alishiri, M ; Lau, R ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    In this study, a machine learning approach was applied to evaluate the impact of operating and design variables on dry powder inhalation efficiency. Emitted dose and fine particle fraction data were extracted from the literature for a variety of drug and carrier combinations. Carrier surface properties are obtained by image analysis of SEM images reported. Models combining artificial neural network and genetic algorithm were developed to determine the emitted dose and fine particle fraction. Design strategies for the carrier surface were also proposed to enhance the fine particle fractions. © 2021 Elsevier Ltd  

    Prediction of seismic damage spectra using computational intelligence methods

    , Article Computers and Structures ; Volume 253 , 2021 ; 00457949 (ISSN) Gharehbaghi, S ; Gandomi, M ; Plevris, V ; Gandomi, A. H ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    Predicting seismic damage spectra, capturing both structural and earthquake features, is useful in performance-based seismic design and quantifying the potential seismic damage of structures. The objective of this paper is to accurately predict the seismic damage spectra using computational intelligence methods. For this purpose, an inelastic single-degree-of-freedom system subjected to a set of earthquake ground motion records is used to compute the (exact) spectral damage. The Park-Ang damage index is used to quantify the seismic damage. Both structural and earthquake features are involved in the prediction models where multi-gene genetic programming (MGGP) and artificial neural networks... 

    Pressuremeter test in unsaturated soils: a numerical study

    , Article SN Applied Sciences ; Volume 3, Issue 4 , 2021 ; 25233971 (ISSN) Keshmiri, E ; Ahmadi, M. M ; Sharif University of Technology
    Springer Nature  2021
    Abstract
    The paper presents a numerical analysis of pressuremeter test in unsaturated cohesive soils. In practice, pressuremeter is commonly expanded up to 10–15% cavity strains. At these strains, limit pressure is not usually reached, and its value is estimated by extrapolation. Accordingly, authors suggest using cavity pressure at 10% strain (P10) for the interpretation of pressuremeter test rather than limit pressure. At this strain, it is also assured that plastic strain occurs around the cavity, which is crucial for the interpretations. In unsaturated soils, the moisture at which a soil is tested has a noticeable influence on the pressuremeter cavity pressure, and consequently, on the magnitude... 

    An exergetic model for the ambient air temperature impacts on the combined power plants and its management using the genetic algorithm

    , Article International Journal of Air-Conditioning and Refrigeration ; Volume 29, Issue 1 , 2021 ; 20101325 (ISSN) Khajehpour, H ; Norouzi, N ; Fani, M ; Sharif University of Technology
    World Scientific  2021
    Abstract
    4E analysis is used on a Brayton-Rankine combined cycle power plant (CCPP) with a dual pressure heat recovery steam generation (HRSG) system. A multi-objective genetic-based evolutionary optimization has been used to estimate the most optimal exergy efficiency status, exergy cost reduction, carbon emission reduction, and NOx emission reduction. For the validation of the data, the simulation results are compared with the plant's data. This study investigates the effect of every decisive parameter on the objective performance parameters of the CCPP. The primary estimated results are the emission rates, efficiencies, and the exergoeconomic cost of the system. At the optimum operational state,... 

    A framework for preemptive multi-skilled project scheduling problem with time-of-use energy tariffs

    , Article Energy Systems ; Volume 12, Issue 2 , 2021 , Pages 431-458 ; 18683967 (ISSN) Maghsoudlou, H ; Afshar Nadjafi, B ; Akhavan Niaki, S. T ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    The growing importance of energy consumption has become an integral part of many decision-making processes in various organizations. In this paper, a framework is proposed for an organization where the undertaken project is implemented by multi-skilled workforce and energy tariffs depending on the time-of-use. This is a real-life situation where energy tariffs are significantly high during the peak demand compared to the one in off peak demand in order to control overloaded consumption of energy. A formulation is developed for the problem to minimize the total cost of consuming required energy. The proposed formulation is validated using several small-scale instances solved by GAMS software.... 

    Optimized age dependent clustering algorithm for prognosis: A case study on gas turbines

    , Article Scientia Iranica ; Volume 28, Issue 3 B , 2021 , Pages 1245-1258 ; 10263098 (ISSN) Mahmoodian, A ; Durali, M ; Abbasian Najafabadi, T ; Saadat Foumani, M ; Sharif University of Technology
    Sharif University of Technology  2021
    Abstract
    This paper proposes an Age-Dependent Clustering (ADC) structure to be used for prognostics. To achieve this aim, a step-by-step methodology is introduced, that includes clustering, reproduction, mapping, and finally estimation of Remaining Useful Life (RUL). In the mapping step, a neural fitting tool is used. To clarify the age-based clustering concept, the main elements of the ADC model is discussed. A Genetic algorithm (GA) is used to find the elements of the optimal model. Lastly, the fuzzy technique is applied to modify the clustering. By investigating a case study on the health monitoring of some turbofan engines, the efficacy of the proposed method is demonstrated. The results showed... 

    A k-NN method for lung cancer prognosis with the use of a genetic algorithm for feature selection

    , Article Expert Systems with Applications ; Volume 164 , 2021 ; 09574174 (ISSN) Maleki, N ; Zeinali, Y ; Akhavan Niaki, S. T ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    Lung cancer is one of the most common diseases for human beings everywhere throughout the world. Early identification of this disease is the main conceivable approach to enhance the possibility of patients’ survival. In this paper, a k-Nearest-Neighbors technique, for which a genetic algorithm is applied for the efficient feature selection to reduce the dataset dimensions and enhance the classifier pace, is employed for diagnosing the stage of patients’ disease. To improve the accuracy of the proposed algorithm, the best value for k is determined using an experimental procedure. The implementation of the proposed approach on a lung cancer database reveals 100% accuracy. This implies that one... 

    A geomechanical approach to casing collapse prediction in oil and gas wells aided by machine learning

    , Article Journal of Petroleum Science and Engineering ; Volume 196 , 2021 ; 09204105 (ISSN) Mohamadian, N ; Ghorbani, H ; Wood, D. A ; Mehrad, M ; Davoodi, S ; Rashidi, S ; Soleimanian, A ; Shahvand, A. K ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    The casing-collapse hazard is one that drilling engineers seek to mitigate with careful well design and operating procedures. However, certain rock formations and their fluid pressure and stress conditions are more prone to casing-collapse risks than others. The Gachsaran Formation in south west Iran, is one such formation, central to oil and gas resource exploration and development in the Zagros region and consisting of complex alternations of anhydrite, marl and salt. The casing-collapse incidents in this formation have resulted over decades in substantial lost production and remedial costs to mitigate the issues surrounding wells with failed casing string. High and vertically-varying... 

    Particle swarm optimization with an enhanced learning strategy and crossover operator

    , Article Knowledge-Based Systems ; Volume 215 , 2021 ; 09507051 (ISSN) Molaei, S ; Moazen, H ; Najjar Ghabel, S ; Farzinvash, L ; Sharif University of Technology
    Elsevier B.V  2021
    Abstract
    Particle Swarm Optimization (PSO) is a well-known swarm intelligence (SI) algorithm employed for solving various optimization problems. This algorithm suffers from premature convergence to local optima. Accordingly, a number of PSO variants have been proposed in the literature. These algorithms exploited different schemes to improve performance. In this paper, we propose a new variant of PSO with an enhanced Learning strategy and Crossover operator (PSOLC). This algorithm applies three strategies, comprising altering the exemplar particles, updating the PSO parameters, and integrating PSO with Genetic Algorithm (GA). In the proposed learning strategy, each particle is guided by the best... 

    Identification of the appropriate architecture of multilayer feed-forward neural network for estimation of NPPs parameters using the GA in combination with the LM and the BR learning algorithms

    , Article Annals of Nuclear Energy ; Volume 156 , 2021 ; 03064549 (ISSN) Moshkbar Bakhshayesh, K ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    In this study, accurate estimation of nuclear power plant (NPP) parameters is done using the new and simple technique. The proposed technique using the genetic algorithm (GA) in combination with the Bayesian regularization (BR) and Levenberg- Marquardt (LM) learning algorithms identifies the appropriate architecture for estimation of the target parameters. In the first step, the input patterns features are selected using the features selection (FS) technique. In the second step, the appropriate number of hidden neurons and hidden layers are investigated to provide a more efficient initial population of the architectures. In the third step, the estimation of the target parameter is done using... 

    Modeling and optimization of a multiple (cascading) phase change material solar storage system

    , Article Thermal Science and Engineering Progress ; Volume 23 , 2021 ; 24519049 (ISSN) Nekoonam, S ; Roshandel, R ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    Utilization of heat storage units in solar energy systems can resolve the challenge of fluctuation and uncertainty of the solar energy. Phase change materials (PCMs) are used as the storage media for solar energy storage systems. In this research, a system including of a solar collector and a PCM-based cascaded energy storage unit was numerically investigated. Air was used as the heat transfer fluid (HTF) and three paraffin-based materials (RT50, RT65, and RT80) were used as PCM for the energy storage unit. The investigated system mainly operates between 15 °C and 90 °C and considering different PCMs, the selected PCMs were appropriate. Paraffin-based PCMs also present acceptable thermal... 

    Estimation of higher heating values (HHVs) of biomass fuels based on ultimate analysis using machine learning techniques and improved equation

    , Article Renewable Energy ; Volume 179 , 2021 , Pages 550-562 ; 09601481 (ISSN) Noushabadi, A.S ; Dashti, A ; Ahmadijokani, F ; Hu, J ; Mohammadi, A. H ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    To have a sustainable economy and environment, several countries have widely inclined to the utilization of non-fossil fuels like biomass fuels to produce heat and electricity. The advantage of employing biomass for combustion is emerging as a potential renewable energy, which is regarded as a cheap fuel. Chemical constituents or elements are essential properties in biomass applications, which would be costly and labor-intensive to experimentally estimate them. One of the criteria to evaluate the energy of biomass from an economic perspective is the higher heating value (HHV). In the present work, we have applied multilayer perceptron artificial neural network (MLP-ANN), least-squares... 

    Critical temperature evaluation of moment frames by means of plastic analysis theory and genetic algorithm

    , Article Iranian Journal of Science and Technology - Transactions of Civil Engineering ; 2021 ; 22286160 (ISSN) Palizi, S ; Saedi Daryan, A ; Sharif University of Technology
    Springer Science and Business Media Deutschland GmbH  2021
    Abstract
    Nowadays, deliberate or unwanted fire incidents have created much attention to the behavior of structures against these types of events. Since the properties of structural members are influenced by the increase in the temperature of the members, it is more difficult to predict the general and local behavior of the structures during the fire. In this research, a method has been proposed to calculate the critical temperature in two-dimensional structures at its collapse with desirable accuracy. In this process, the upper-bound theory of plastic analysis is used. The plastic analysis is performed by applying the initial fire scenario to the structure, and its collapse load factor with the...