The presence of long-range interactions is crucial in distinguishing between abstract complex networks and wave *** photonics,because electromagnetic interactions between optical elements generally decay rapidly with ...
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The presence of long-range interactions is crucial in distinguishing between abstract complex networks and wave *** photonics,because electromagnetic interactions between optical elements generally decay rapidly with spatial distance,most wave phenomena are modeled with neighboring interactions,which account for only a small part of conceptually possible ***,we explore the impact of substantial long-range interactions in topological *** demonstrate that a crystalline structure,characterized by long-range interactions in the absence of neighboring ones,can be interpreted as an overlapped *** overlap model facilitates the realization of higher values of topological invariants while maintaining bandgap width in photonic topological *** breaking of topology-bandgap tradeoff enables topologically protected multichannel signal processing with broad *** practically accessible system parameters,the result paves the way to the extension of topological physics to network science.
Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency *** charge-based or emerging memory technologies such as memris...
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Advancements in neuromorphic computing have given an impetus to the development of systems with adaptive behavior,dynamic responses,and energy efficiency *** charge-based or emerging memory technologies such as memristors have been developed to emulate synaptic plasticity,replicating the key functionality of neurons—integrating diverse presynaptic inputs to fire electrical impulses—has remained *** this study,we developed reconfigurable metal-oxide-semiconductor capacitors(MOSCaps)based on hafnium diselenide(HfSe2).The proposed devices exhibit(1)optoelectronic synaptic features and perform separate stimulus-associated learning,indicating considerable adaptive neuron emulation,(2)dual light-enabled charge-trapping and memcapacitive behavior within the same MOSCap device,whose threshold voltage and capacitance vary based on the light intensity across the visible spectrum,(3)memcapacitor volatility tuning based on the biasing conditions,enabling the transition from volatile light sensing to non-volatile optical data *** reconfigurability and multifunctionality of MOSCap were used to integrate the device into a leaky integrate-and-fire neuron model within a spiking neural network to dynamically adjust firing patterns based on light stimuli and detect exoplanets through variations in light intensity.
We consider a power system whose electric demand pertaining to freshwater production is high(high freshwater electric demand),as in the Middle East,and investigate the tradeoff of storing freshwater in tanks versus st...
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We consider a power system whose electric demand pertaining to freshwater production is high(high freshwater electric demand),as in the Middle East,and investigate the tradeoff of storing freshwater in tanks versus storing electricity in batteries at the day-ahead operation *** storing freshwater and storing electricity increase the actual electric demand at valley hours and decrease it at peak hours,which is generally beneficial in term of cost and ***,to what extent?We analyze this question considering three power systems with different generation-mix configurations,i.e.,a thermal-dominated mix,a renewable-dominated one,and a fully renewable *** generation-mix configurations are inspired by how power systems may evolve in different countries in the Middle *** production uncertainty is compactly modeled using chance *** draw conclusions on how both storage facilities(freshwater and electricity)complement each other to render an optimal operation of the power system.
Safe, socially compliant, and efficient navigation of low-speed autonomous vehicles (AVs) in pedestrian-rich environments necessitates considering pedestrians' future positions and interactions with the vehicle an...
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Safe, socially compliant, and efficient navigation of low-speed autonomous vehicles (AVs) in pedestrian-rich environments necessitates considering pedestrians' future positions and interactions with the vehicle and others. Despite the inevitable uncertainties associated with pedestrians' predicted trajectories due to their unobserved states (e.g., intent), existing deep reinforcement learning (DRL) algorithms for crowd navigation often neglect these uncertainties when using predicted trajectories to guide policy learning. This omission limits the usability of predictions when diverging from ground truth. This work introduces an integrated prediction and planning approach that incorporates the uncertainties of predicted pedestrian states in the training of a model-free DRL algorithm. A novel reward function encourages the AV to respect pedestrians' personal space, decrease speed during close approaches, and minimize the collision probability with their predicted paths. Unlike previous DRL methods, our model, designed for AV operation in crowded spaces, is trained in a novel simulation environment that reflects realistic pedestrian behaviour in a shared space with vehicles. Results show a 40% decrease in collision rate and a 15% increase in minimum distance to pedestrians compared to the state of the art model that does not account for prediction uncertainty. Additionally, the approach outperforms model predictive control methods that incorporate the same prediction uncertainties in terms of both performance and computational time, while producing trajectories closer to human drivers in similar scenarios. IEEE
Under perfect competition,marginal pricing results in short-term efficiency and the subsequent right short-term price ***,the main reason for the adoption of marginal pricing is not the above,but investment cost *** i...
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Under perfect competition,marginal pricing results in short-term efficiency and the subsequent right short-term price ***,the main reason for the adoption of marginal pricing is not the above,but investment cost *** is,the fact that the profits obtained by infra-marginal technologies(technologies whose production cost is below the marginal price)allow them just to recover their investment *** the other hand,if the perfect competition assumption is removed,investment over-recovery or under-recovery generally occurs for infra-marginal technologies.
This paper proposes an empirical wavelet transform(EWT)based method for identification and analysis of sub-synchronous oscillation(SSO)modes in the power system using phasor measurement unit(PMU)*** phasors from PMUs ...
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This paper proposes an empirical wavelet transform(EWT)based method for identification and analysis of sub-synchronous oscillation(SSO)modes in the power system using phasor measurement unit(PMU)*** phasors from PMUs are preprocessed to check for the presence of *** the presence is established,the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida *** superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest *** show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.
作者：
Arian AziziMona GhassemiZero Emission
Realization of Optimized Energy Systems(ZEROES)LaboratoryDepartment of Electrical and Computer EngineeringThe University of Texas at DallasRichardsonTexasUSA
The next generation of aircraft,including more electric aircraft and all-electric aircraft(AEA),requires electric power systems with high power density and low system mass *** the voltage of the system to the range of...
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The next generation of aircraft,including more electric aircraft and all-electric aircraft(AEA),requires electric power systems with high power density and low system mass *** the voltage of the system to the range of a few kV,medium voltage(MV),is a reasonable approach to achieving high-power-density and low-system-mass EPSs for aircraft *** voltages,however,pose many challenges for aviation MV power cables such as arcs and arc tracking,partial discharges(PDs),and thermal *** this regard,thermal management is more challenging since heat transfer by convection is greatly reduced at wide-body aircraft's cruising altitudes due to the reduced air *** this paper,a finite element method(FEM)model is devel-oped in COMSOL Multiphysics for an aircraft bipolar MVDC(5 kV)power *** the model,the maximum permissible cable current at a low pressure of 18.8 kPa(at an altitude of 12.2 km from sea level,the usual cruising altitude for wide-body aircraft)is ***,an analytical model is developed based on analytical and proven empirical correlations governing conductive,radiative,and convective heat transfers at the steady state to estimate the ampacity of the bipolar cable system at reduced *** was shown that the proposed analytical model can be used for atmospheric pressure and systems with a larger number of poles,expanding its range of *** results of the FEM and analytical models correlate at wide ranges of parameters such as ambient temperature,duct size,distance between the positive and negative pole cables,and the overall diameter of the *** influence of horizontal and vertical arrangement of poles is included in the analytical *** results of this study can be used to design bipolar MVDC power cable systems for the envisaged wide-body AEA.
High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation lear...
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High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable ***, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational ***, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices.
The permanent magnet (PM) Vernier machines enhance torque density and decrease cogging torque compared to conventional permanent magnet synchronous motor. This paper presents a novel fractional-slot H-shaped PM Vernie...
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With 5G and beyond promises to realize massive machine-type communications, a wide range of applications have driven interest in complex heterogeneous networked systems, including multi-agent optimization, large-scale...
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ISBN:
(纸本)9798350371000;9798350370997
With 5G and beyond promises to realize massive machine-type communications, a wide range of applications have driven interest in complex heterogeneous networked systems, including multi-agent optimization, large-scale distributed learning, 5G service provisioning, etc. This trend highlights the essence of seamless control, management, and security mechanisms to be in place for the next-generation networked cyber-physical systems (CPS). In this paper, we interpret trust as a relation among networked collaborating entities that can set forth a measure for evaluating the status of network components and secure the execution of the collaborative protocol. In this paper, we will first elaborate on the importance of trust as a metric and then present a mathematical framework for trust computation and aggregation within a network. We consider two use-case examples where trust can be incorporated into the next-generation networked CPS and improve the security of decision-making, i.e. i) federated learning (FL), and ii) network resource provisioning. Finally, we explain the challenges associated with aggregating the trust evidence and briefly explain our ideas to tackle them.
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