- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Risk assessment in a central concentrating solar power plant
摘要： In this paper, optimal scheduling of a central concentrating solar power (CSP) plant which is one of the most promising technologies in the solar energy is investigated in the presence of different uncertainties. Thermal energy storage is integrated with the CSP plant in order to allow the plant to be independent from the instantaneous solar radiation. In order to model different uncertainty such as power market price and solar irradiation, a new hybrid information gap decision theory (IGDT)-stochastic method is introduced which is a mixed-integer linear programming method and presents more reliable results in a suitable computation time. In the proposed method the uncertainty of the solar irradiation is modeled by IGDT method while power market price uncertainty is considered by a set of fifty scenarios. Three different strategies as risk-averse, risk-neutral and risk-taker are introduced to analyze the operation of the CSP plant. In the risk-neutral strategy, obtained profit is equal to $3895 which is reduced in the risk-averse strategy by increasing robustness value indicating increased uncertainty of the solar irradiation. In the risk-taker strategy, the CSP operating profit will be equal to $4245 by 15% of increase in solar radiation, comparing with the risk-neutral case shows almost 8.2% increase in profit.
关键词： Information gap decision theory (IGDT),Solar thermal energy storage,Stochastic optimization,Concentrating solar power (CSP) plant
更新于2025-09-19 17:15:36
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Joint Optimization of FeICIC and Spectrum Allocation for Spectral and Energy Efficient Heterogeneous Networks
摘要： Cellular heterogeneous networks (HetNets) with densely deployed small cells can effectively boost network capacity. The co-channel interference and the prominent energy consumption are two crucial issues in HetNets which need to be addressed. Taking the traffic variations into account, this paper proposes a theoretical framework to analyze spectral efficiency (SE) and energy efficiency (EE) considering jointly further-enhanced inter-cell interference coordination (FeICIC) and spectrum allocation (SA) via a stochastic geometric approach for a two-tier downlink HetNet. SE and EE are respectively derived and validated by Monte Carlo simulations. To create spectrum and energy efficient HetNets that can adapt to traffic demands, a non-convex optimization problem with the power control factor, resource partitioning fraction and number of subchannels for the SE and EE tradeoff is formulated, based on which, an iterative algorithm with low complexity is proposed to achieve the sub-optimal solution. Numerical results confirm the effectiveness of the joint FeICIC and SA scheme in HetNets. Meanwhile, a system design insight on resource allocation for the SE and EE tradeoff is provided.
关键词： sleep mode,stochastic geometry,spectral efficiency,spectrum allocation,FeICIC,heterogeneous networks,energy efficiency
更新于2025-09-19 17:15:36
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[IEEE 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Sydney, Australia (2018.11.10-2018.11.17)] 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC) - Laser-Based Scintillator Crystal Emulator for Optical Testing of SiPM Readout Technologies
摘要： Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms.
关键词： winner-take-all,probabilistic learning,stochastic computing,Neuromorphic systems,probabilistic inference,spiking neurons,stochastic memristors
更新于2025-09-19 17:13:59
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[IEEE 2019 Device Research Conference (DRC) - Ann Arbor, MI, USA (2019.6.23-2019.6.26)] 2019 Device Research Conference (DRC) - Waveguide Uni-Traveling-Carrier Photodiodes for mmW Signal Generation: Space-Charge Impedance and Efficiency Limitations
摘要： Recent theoretical studies have shown that probabilistic spiking can be interpreted as learning and inference in cortical microcircuits. This interpretation creates new opportunities for building neuromorphic systems driven by probabilistic learning algorithms. However, such systems must have two crucial features: 1) the neurons should follow a specific behavioral model, and 2) stochastic spiking should be implemented efficiently for it to be scalable. This paper proposes a memristor-based stochastically spiking neuron that fulfills these requirements. First, the analytical model of the memristor is enhanced so it can capture the behavioral stochasticity consistent with experimentally observed phenomena. The switching behavior of the memristor model is demonstrated to be akin to the firing of the stochastic spike response neuron model, the primary building block for probabilistic algorithms in spiking neural networks. Furthermore, the paper proposes a neural soma circuit that utilizes the intrinsic nondeterminism of memristive switching for efficient spike generation. The simulations and analysis of the behavior of a single stochastic neuron and a winner-take-all network built of such neurons and trained on handwritten digits confirm that the circuit can be used for building probabilistic sampling and pattern adaptation machinery in spiking networks. The findings constitute an important step towards scalable and efficient probabilistic neuromorphic platforms.
关键词： Neuromorphic systems,winner-take-all,stochastic computing,probabilistic learning,probabilistic inference,spiking neurons,stochastic memristors
更新于2025-09-19 17:13:59
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Radial Nanowire Assemblies under Rotating Magnetic Field Enabled Efficient Charge Separation
摘要： Developing efficient charge separation strategies is essential to achieve high power conversion efficiency in fields of chemistry, biology and material science. Herein, we develop a facile strategy for fabrication of unique wafer-scale radial nanowire assemblies by exploiting shear force in rotary solution. The assembling mechanism can be well revealed by the large-scale stochastic dynamics simulation. Free electrons can be rapidly generated to produce quantitatively tunable current output when the radial nanowire assemblies rotating under the magnetic field. Moreover, the photoconductive performance of the radial semiconductor nanowire assemblies can be remarkably enhanced as the electron-hole recombination was retrained by the efficient charge separation under the rotating magnetic field. Such large-scale unique nanowire assemblies will facilitate the design of efficient charge separation process in bio-system, sensors and photocatalysis.
关键词： nanowires,charge separation,stochastic dynamics simulation,assembly,magnetic field
更新于2025-09-19 17:13:59
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Production of relativistic electrons at subrelativistic laser intensities
摘要： Relativistic electron temperatures were measured from kilojoule, subrelativistic laser-plasma interactions. Experiments show an order of magnitude higher temperatures than expected from a ponderomotive scaling, where temperatures of up to 2.2 MeV were generated using an intensity of 1 × 1018 W/cm2. Two-dimensional particle-in-cell simulations suggest that electrons gain superponderomotive energies by stochastic acceleration as they sample a large area of rapidly changing laser phase. We demonstrate that such high temperatures are possible from subrelativistic intensities by using lasers with long pulse durations and large spatial scales.
关键词： particle-in-cell simulations,relativistic electrons,stochastic acceleration,laser-plasma interactions,subrelativistic laser intensities
更新于2025-09-19 17:13:59
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Near-Field Radio Holography of Slant-Axis Terahertz Antennas
摘要： Principal component analysis (PCA) and independent component analysis (ICA) for radiated emissions from printed circuits are critically intercompared, revealing similarities and differences of the extracted components between both methods. The input data in this analysis are measured wideband complex-valued magnetic radiated and evanescent fields with quasi-Gaussian spatial distributions. PCA and ICA lead to similar maps of their components when considered as spatial eigenmodes, but independent components exhibit simpler field structure than principal components.
关键词： stochastic fields,principal component analysis (PCA),uncertainty quantification,Independent component analysis (ICA),radiated emissions
更新于2025-09-19 17:13:59
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[IEEE 2019 Workshop on Recent Advances in Photonics (WRAP) - Guwahati, India (2019.12.13-2019.12.14)] 2019 Workshop on Recent Advances in Photonics (WRAP) - Photonic Crystal Fiber based Surface Plasmon Resonance Bio- Sensors with bimetallic selectively filled metal layers
摘要： The performance of cellular system significantly depends on its network topology, while cellular networks are undergoing a heterogeneous evolution. This promising trend introduces the unplanned deployment of smaller base stations (BSs), thus complicating the performance evaluation even further. In this paper, based on large amount of real BS locations data, we present a comprehensive analysis on the spatial modeling of a cellular network structure. Unlike the related works, we divide the BSs into different subsets according to geographical factor (e.g., urban or rural) and functional type (e.g., macrocells or microcells), and perform a detailed spatial analysis to each subset. After discovering the inaccuracy of the Poisson point process in BS locations modeling, we consider the Gibbs point processes as well as Neyman–Scott point processes and compare their performance in the view of a large-scale modeling test, and finally reveal the general clustering nature of BSs deployment. This paper carries out the first large-scale identification regarding available literature, and provides more realistic and general results to contribute to the performance analysis for the forthcoming heterogeneous cellular networks.
关键词： Cellular networks,base station (BS) locations,large-scale identification,Poisson point process,stochastic geometry
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech) - St. Petersburg, Russia (2019.10.17-2019.10.18)] 2019 IEEE International Conference on Electrical Engineering and Photonics (EExPolytech) - Effective Mode Volume Evolution in the He-Ne Laser
摘要： How isogenic cell populations maintain size homeostasis, i.e., a narrow distribution of cell size, is an intriguing fundamental problem. We model cell size using a stochastic hybrid system, where a cell grows exponentially in size (volume) over time and probabilistic division events are triggered at discrete-time intervals. Moreover, whenever division occurs, size is randomly partitioned among daughter cells. We first consider a scenario where a timer (cell-cycle clock) that measures the time elapsed since the last division event regulates both the cellular growth and division rates. The analysis reveals that such a timer-controlled system cannot achieve size homeostasis, in the sense that the cell-to-cell size variation grows unboundedly with time. To explore biologically meaningful mechanisms for controlling size, we consider two classes of regulation: a size-dependent growth rate and a size-dependent division rate. Our results show that these strategies can provide bounded intercellular variation in cell size and exact mathematical conditions on the form of regulation needed for size homeostasis are derived. Different known forms of size control strategies, such as the adder and the sizer, are shown to be consistent with these results. Finally, we discuss how organisms ranging from bacteria to mammalian cells have adopted different control approaches for maintaining size homeostasis.
关键词： cell size homeostasis,stochastic hybrid systems,sizer,moment dynamics,moment closure,Adder
更新于2025-09-19 17:13:59
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Ultrafast Light Source at 1.8 ??m Based on Thulium-Doped Fibers for Three-Photon Microscopy
摘要： Optical tomographic imaging requires an accurate forward model as well as regularization to mitigate missing-data artifacts and to suppress noise. Nonlinear forward models can provide more accurate interpretation of the measured data than their linear counterparts, but they generally result in computationally prohibitive reconstruction algorithms. Although sparsity-driven regularizers significantly improve the quality of reconstructed image, they further increase the computational burden of imaging. In this paper, we present a novel iterative imaging method for optical tomography that combines a nonlinear forward model based on the beam propagation method (BPM) with an edge-preserving three-dimensional (3-D) total variation (TV) regularizer. The central element of our approach is a time-reversal scheme, which allows for an efficient computation of the derivative of the transmitted wave-field with respect to the distribution of the refractive index. This time-reversal scheme together with our stochastic proximal-gradient algorithm makes it possible to optimize under a nonlinear forward model in a computationally tractable way, thus enabling a high-quality imaging of the refractive index throughout the object. We demonstrate the effectiveness of our method through several experiments on simulated and experimentally measured data.
关键词： Optical phase tomography,beam propagation method,compressive sensing,total variation regularization,stochastic proximal-gradient,sparse reconstruction
更新于2025-09-19 17:13:59