In this paper, a coherent perfect absorption-type NOR gate based on plasmonic nano particles is proposed. It consists of two plasmonic nanorod arrays on top of two serial arms with quartz substrate. The operation prin...
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In this paper, a coherent perfect absorption-type NOR gate based on plasmonic nano particles is proposed. It consists of two plasmonic nanorod arrays on top of two serial arms with quartz substrate. The operation principle is based on the absorbable formation of a conductive path in the dielectric layer of a plasmonic nanoparticle waveguide. Because the coherent perfect absorption efficiency depends strongly on the number of plasmonic nanorods and the locations of nanorods, an efficient binary optimization method based the Particle Swarm optimization algorithm is used to design an optimized array of the plasmonic nanorods in order to achieve the maximum absorption coefficient in the off' state and the minimum absorption coefficient in the on' state. In Binary Particle Swarm optimization, a group of birds consists a matrix with binary entries, control the presence (1') or the absence (0') of nanorods in the array. Copyright (c) 2016 John Wiley & Sons, Ltd.
With increasing importance being attached to big data mining, analysis, and forecasting in the field of wind energy, how to select an optimization model to improve the forecasting accuracy of the wind speed time serie...
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With increasing importance being attached to big data mining, analysis, and forecasting in the field of wind energy, how to select an optimization model to improve the forecasting accuracy of the wind speed time series is not only an extremely challenging problem, but also a problem of concern for economic forecasting. The artificial intelligence model is widely used in forecasting and data processing, but the individual back-propagation artificial neural network cannot always satisfy the time series forecasting needs. Thus, a hybrid forecasting approach has been proposed in this study, which consists of data preprocessing, parameter optimization and a neural network for advancing the accuracy of short-term wind speed forecasting. According to the case study, in which the data are collected from Peng Lai, a city located in China, the simulation results indicate that the hybrid forecasting method yields better predictions compared to the individual BP, which indicates that the hybrid method exhibits stronger forecasting ability.
The pump structure greatly influences the characteristics of a diode side-pumped laser. To achieve high absorption efficiency and a homogeneous pump-beam distribution simultaneously, a systemic algorithm has been esta...
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ISBN:
(纸本)9780819483737
The pump structure greatly influences the characteristics of a diode side-pumped laser. To achieve high absorption efficiency and a homogeneous pump-beam distribution simultaneously, a systemic algorithm has been established to optimize the pump structure, where multiple reflections occur on the internal wall of the reflector inside the pump chamber. A novel design of an efficient, highly reliable, and good beam quality diode side-pumped solid-state laser is presented. Effort has been done to obtain a highly uniform pumping intensity in the active area, which simultaneously reduces the effects of thermal gradient. In this design a novel lens duct configuration is used. By this way a uniform power distribution and a maximum absorption of pump power is resulted. Numerical analysis also indicates the superiority of the design to other methods such as direct and diffusive pumping techniques.
Cloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. To give secure and reliable services in cloud computing environment is an important i...
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Cloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. To give secure and reliable services in cloud computing environment is an important issue. Providing security requires more than user authentication with passwords or digital certificates and confidentiality in data transmission, because it is vulnerable and prone to network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To detect DoS attack and other network level malicious activities in Cloud, use of only traditional firewall is not an efficient solution. In this paper, we propose a cooperative and hybrid network intrusion detection system (CH-NIDS) to detect network attacks in the Cloud environment by monitoring network traffic, while maintaining performance and service quality. In our NIDS framework, we use Snort as a signature based detection to detect known attacks, while for detecting network anomaly, we use Back-Propagation Neural network (BPN). By applying snort prior to the BPN classifier, BPN has to detect only unknown attacks. So, detection time is reduced. To solve the problem of slow convergence of BPN and being easy to fall into local optimum, we propose to optimize the parameters of it by using an optimization algorithm in order to ensure high detection rate, high accuracy, low false positives and low false negatives with affordable computational cost. In addition, in this framework, the IDSs operate in cooperative way to oppose the DoS and DDoS attacks by sharing alerts stored in central log. In this way, unknown attacks that were detected by any IDS can easily be detected by others IDSs. This also helps to reduce computational cost for detecting intrusions at others IDS, and improve detection rate in overall the Cloud environment.
Combining the characteristics of wireless sensor network, the ant colony algorithm is applied to a wireless sensor network, and a wireless sensor network route algorithm based on energy equilibrium is proposed in this...
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Combining the characteristics of wireless sensor network, the ant colony algorithm is applied to a wireless sensor network, and a wireless sensor network route algorithm based on energy equilibrium is proposed in this paper. This algorithm takes the energy factor into the consideration of selection of route based on probability and enhanced calculation of information so as to find out the optimal route from the source node to the target node with low cost and balanced energy, and it prolongs the life cycle of the whole network.
Developing new energy such as wind power and photovoltaic power is the main way to solve our energy problems. However, the volatility of wind power and photovoltaicpowerwill impact the grid. The changes of wind power ...
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Developing new energy such as wind power and photovoltaic power is the main way to solve our energy problems. However, the volatility of wind power and photovoltaicpowerwill impact the grid. The changes of wind power and photovoltaic power have complementary characteristics. It can effectively reduce the impact to the grid by combining them. This paper studies the optimal dispatch modeling problem with combination of wind power and photovoltaic power systems,establishes the optimal scheduling model of a power system including wind power and photovoltaic power considering the environmental benefits and spare capacity changing,and conducts a simulation calculation to verify the validity of the method.
The aim of this paper is to model and simulate a cantilever beam as energy harvester to expose to wind vibrations. A mathematical model describes the behavior of cantilever beam and the electromechanical coupling, usi...
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ISBN:
(纸本)9781479999828
The aim of this paper is to model and simulate a cantilever beam as energy harvester to expose to wind vibrations. A mathematical model describes the behavior of cantilever beam and the electromechanical coupling, using piezoelectric constitutive equations. An experimental setup of a fixed configuration (dimensions, materials, boundaries and shape) is performed by means of such device and the effects caused by the wind force on the cantilever are analyzed. The same device is used for a simulation, implemented with Comsol Multiphysics, in which wind force is simulated like a pressure acting on the cantilever. The comparison between simulation and experimental results validates the simulation method and allows an appropriate choice of the most suitable shape for this kind of cantilever: the choice is carried out using the optimization platform KIMEME.
Direct estimation of physiologically or biochemically important parameters from raw projection data is challenging in dynamic positron emission tomography ( PET) due to the coupling between tomographic image reconstru...
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ISBN:
(纸本)9781479923748
Direct estimation of physiologically or biochemically important parameters from raw projection data is challenging in dynamic positron emission tomography ( PET) due to the coupling between tomographic image reconstruction and nonlinear kinetic parameter estimation. optimization transfer algorithms have been previously developed to solve the complex optimization problem. These algorithms, however, can suffer from slow convergence rate. This paper proposes an accelerated iterative algorithm for direct reconstruction of kinetic parameters through variable splitting under the framework of augmented Lagrangian optimization. Similar to the optimization transfer algorithms, the proposed algorithm splits each iteration of direct reconstruction into two separate steps: dynamic image reconstruction and pixel-wise nonlinear least squares kinetic fitting. The unique advantage of the new algorithm is its flexibility to employ any existing reconstruction algorithms in the reconstruction step, which can substantially accelerate the convergence speed. Computer simulations show that the proposed direct algorithm can be efficiently implemented and achieve much faster convergence speed than the optimization transfer algorithm.
Optimally locating a transportation facility and automotive service enterprise is an interesting and important problem. In practice, many related factors, e.g., customer demands, allocations, and locations of customer...
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ISBN:
(纸本)9781467379960
Optimally locating a transportation facility and automotive service enterprise is an interesting and important problem. In practice, many related factors, e.g., customer demands, allocations, and locations of customers and facilities, are changing, and thus the problem features with uncertainty. To account for this uncertainty, some researchers have addressed its stochastic time and cost issues. A new research issue arises when a) decision-makers want to minimize the transportation time of customers while minimizing their transpiration cost when locating a facility;and b) users prefer to arrive at the destination within the specific time and cost. By taking a vehicle inspection station as a typical automotive service enterprise example, this work proposes a novel stochastic multi-objective optimization approach to address it. Moreover, some regional constraints can greatly influence its solution;while vehicle velocity is an uncertain variable due to the influence of some unpredictable factors in a location process. This work builds a practical stochastic expected value multi-objective programming model of its location with regional constraints and varying velocity. A hybrid algorithm integrating stochastic simulation and Genetic algorithms (GA), namely a random weight based multi-objective GA, is proposed to solve the proposed models. A numerical example is given to illustrate the proposed models and the effectiveness of the proposed algorithm.
This paper presents a comparative study on the optimization methods in fractional PID controller design for induction motor. Choosing the best optimization algorithm for tuning fractional order controllers is crucial ...
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ISBN:
(纸本)9781467377973
This paper presents a comparative study on the optimization methods in fractional PID controller design for induction motor. Choosing the best optimization algorithm for tuning fractional order controllers is crucial in order obtain best system response. In this study genetic algorithm, local search, nonlinear sequential quadratic programming, and particle swarm optimization algorithms are used to tune a fractional PI controller for induction motors. A model of a real motor is used to design and test the controllers. The resulted fractional controllers are approximated using refined Oustaloup's recursive filter in order to be implemented using digital controllers. The controllers' speed tracking performance is tested in simulation and a comparative analysis has been conducted.
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