Traffic on highways has increased significantly in the past few years. Consequently, this has caused delays for the drivers in reaching their final destination and increased the highway's congestion level. Many op...
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In this paper we consider the motion planning problem in an n-dimensional Euclidean space, n ≥q 2, containing finitely many obstacles with boundaries possessing a smooth structure. Obstacle boundaries are assumed to ...
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This work proposes a distributed estimation and control approach in which a team of aerial agents equipped with radio jamming devices collaborate in order to intercept and concurrently track-and-jam a malicious target...
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Roads are an important part of transporting goods and products from one place to another. In developing countries, the main challenge is to maintain road conditions regularly. Roads can deteriorate from time to time. ...
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Despite considerable research into information diffusion, most models focus on static networks. Networks in the real world change over time and information is lost when a node disappears. We sought to resolve the prob...
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Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first prop...
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Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.
Recently,intelligent reflecting surfaces(IRSs)have emerged as potential candidates for overcoming the line-of-sight issue in 5 G/6 G wireless *** IRSs can manipulate the direction of reflected beams,enabling efficient...
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Recently,intelligent reflecting surfaces(IRSs)have emerged as potential candidates for overcoming the line-of-sight issue in 5 G/6 G wireless *** IRSs can manipulate the direction of reflected beams,enabling efficient beam steering to enhance the performance of wireless *** unit cell(or unit structure)of an IRS commonly consists of electrical elements for phase ***,by employing phase modulation alone,an IRS can steer the reflected electromagnetic waves toward only discrete and specific angles,leaving a wide range of out-of-beam *** this work,an IRS that uses both phase modulation and space modulation is presented to improve the beam resolution and continuously cover out-of-beam areas that phase modulation alone cannot address.A positive-intrinsic-negative diode is mounted on a unit cell for phase modulation,and a 4D-printed reconfigured structure is fabricated to demonstrate space *** beam-steering function is achieved by alternating the states of the diodes in the same columns,while the beam resolution is improved by controlling the gaps between the *** functions are frst theoretically and numerically analyzed and then experimentally verified,demonstrating that additional angles of-46°/+50°,-22°/+14°,and -16°/+12°are achieved with space modulation and -60°/+62°,-30°/+22°,and±16°are achieved by phase modulation *** proposed IRS offers the possibility of functional integration in a variety of indoor applications within the wireless communication field.
In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a sma...
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In the restructured electricity market,microgrid(MG),with the incorporation of smart grid technologies,distributed energy resources(DERs),a pumped-storage-hydraulic(PSH)unit,and a demand response program(DRP),is a smarter and more reliable electricity *** consists of gas turbines and renewable energy sources such as photovoltaic systems and wind *** bidding strategies,prepared by MG operators,decrease the electricity cost and emissions from upstream grid and conventional and renewable energy sources(RES).But it is inefficient due to the very high sporadic characteristics of RES and the very high outage *** solve these issues,this study suggests non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)for an optimal bidding strategy considering pumped hydroelectric energy storage and DRP based on outage conditions and uncertainties of renewable energy *** uncertainty related to solar and wind units is modeled using lognormal and Weibull probability ***-based DRP is used,especially considering the time of outages along with the time of peak loads and prices,to enhance the reliability of MG and reduce costs and emissions.
Scalable coordination of photovoltaic(PV)inverters,considering the uncertainty in PV and load in distribution networks(DNs),is challenging due to the lack of real-time *** PV inverter setpoints can be achieved to addr...
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Scalable coordination of photovoltaic(PV)inverters,considering the uncertainty in PV and load in distribution networks(DNs),is challenging due to the lack of real-time *** PV inverter setpoints can be achieved to address this issue by capitalizing on the abundance of data from smart utility meters and the scalable architecture of artificial neural networks(ANNs).To this end,we first use an offline,centralized data-driven conservative convex approximation of chance-constrained optimal power flow(CVaR-OPF)in which conditional value-at-risk(CVaR)is used to compute reactive power setpoints of PV inverter,taking into account PV and load uncertainties in *** that,an artificial neural network(ANN)controller is trained for each PV inverter to emulate the optimal behavior of the centralized control setpoints of PV inverter in a decentralized ***,the voltage regulation performance of the developed ANN controllers is compared with other decentralized designs(local controllers)developed using model-based learning(regressionbased controller),optimization(affine feedback controller),and case-based learning(mapping)*** tests using real-world feeders corroborate the effectiveness of ANN controllers in voltage regulation and loss minimization.
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