Toan, Trinh DinhLam, Soi HoiWong, Yiik DiewMeng, Meng...
18页查看更多>>摘要：This paper presents the development and validation of a driving simulator for ramp traffic control on expressways using a traffic simulator and control (TSC). The TSC consists of two main components: car-following model (CFM), and traffic controller (TC). The CFM simulates the car-following behavior and delivers aggregated traffic parameters to the TC to derive control actions. The CFM and TC are harmonized and integrated in a close-loop control manner, where the effects of the control by the TC are fed back as inputs for the CFM in real-time applications. Although the following behavior of individual vehicles is simulated, the aggregated outputs such as average speed and flow rate from the model are the parameters of interest. For simplicity in the model development and validation and to capture lane-changing effects, the traffic in the multi-lane expressway where the data were obtained was equivalently represented as a single-lane system. The validation of the CFM was performed at macroscopic level where aggregated outputs from the model were compared to observed data in a segment of the Pan Island Expressway of Singapore under various traffic conditions. The result shows that the simulated speed is not significantly different from the actual speed at 5% significance level, and the aggregated flow rate discrepancies fall in a small range, from 2.21% to 3.15%. This shows that the TSC model is a reliable model for traffic simulation and control applications. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:
NSTL
Elsevier
Pan, HaoBai, HaijianZheng, XiaoyanChen, Jin...
19页查看更多>>摘要：In the near future, connected and autonomous vehicles (CAVs) will share road space with human-driven vehicles (HVs). In this mixed vehicular traffic, effective following cooperation among multiple vehicles is an important basis for improving traffic efficiency and safety. However, CAVs are unable to communicate with HVs to acquire information. Therefore, how to obtain HV information and realize cooperative car-following has become an urgent problem for CAVs. This paper proposes a CAV driving strategy that considers multiple preceding vehicles, including HVs. The strategy first uses a large amount of real car-following data to build an upgraded Elman neural network (ENN) model optimized with the sparrow search algorithm (SSA), which is utilized to obtain HV information. Then, we combine the SSA-ENN with the classical car-following model and use a time-varying weighting model to analyze the impact of the different states of multiple preceding cars at various moments on the host car, so as to achieve car following driving control. Numerical simulations are carried out, and the results show that the driving strategy can improve road capacity and suppress traffic oscillations. With the increase in CAV penetration, traffic efficiency, safety, and driving comfort are improved accordingly. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Khalfaoui, FadhilaDilmi, SamiaBoumali, Abdelmalek
10页查看更多>>摘要：Electron-impact ionization (EII) can be important in dynamic systems where atoms are suddenly exposed to higher electron temperatures. EII can also have a significant effect on the charge state distribution for plasmas with a non-thermal electron energy distribution. In this paper, we present the effects of hot electrons on the calculation of ionization rates for neutral Helium using superstatistics. We also exchange the distribution function with the effective Boltzmann factor of superstatistics. The ionization rates of neutral Helium are obtained from cross sections obtained by FAC code, are weighted by a nonmaxwellian distribution function. The results are compared to those reported by Kato. et. al. We note that non-maxwellian energy distribution for different fractions of hot electrons showed the effects of these rates on the fractions of hot electrons and the forms of ionization rates.Published by Elsevier B.V.
原文链接:- NSTL
- Elsevier
Eftekhari, F.Tavassoly, M. K.Behjat, A.
17页查看更多>>摘要：In this paper we investigate the dynamics of f-deformed interaction (nonlinear atom field coupling) of a three-level atom in V-configuration with a two-mode quantized field in the presence and absence of Kerr medium as well as the phonon and photon dissipations in an optomechanical cavity. We solve the associated time-dependent Schrodinger equation and arrive at the corresponding state vector at arbitrary time. In the continuation, we evaluate several nonclassical properties including atomic von Neumann entropy, atomic information entropy squeezing, sub-Poissonian statistics and atomic squeezing, numerically. Our numerical results show that, with the parameters at our disposal, we can adjust the above-mentioned properties according to our purposes. For instance, significant amount of von Neumann entropy may be achieved, in the linear and nonlinear atom-field coupling, without or even with considered dissipations. However, atomic information entropy squeezing can be observed only in the presence of nonlinear atom-field coupling by tuning the proper values of Lamb-Dicke parameter. Atomic squeezing can be seen in the presence or absence of linear and nonlinear atom-field coupling. Negative values of Mandel parameter, showing the sub-Poissonian statistics as the nonclassicality of the field can be observed with and without nonlinear atom-field coupling, however, the presence of Lamb-Dicke nonlinearity can make this effect more visible. Unless the atomic information entropy squeezing, in all above mentioned physical phenomena stability of the evaluated parameters can be accessible via choosing appropriate parameters containing Lamb-Dicke parameter, Kerr effects, dissipation parameters, laser pumps and photon-phonon coupling. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Lima, A. I. A.Vasconcelos, M. S.Anselmo, D. H. A. L.
9页查看更多>>摘要：In this work, we study the power laws and fractal properties of the energy spectrum in single-strand DNA stretches composed of pure GAs (Adenines and Guanines) sequences found in human chromosome 7. We have used the transfer matrix method for the tightbinding Hamiltonian to find the electronic energy distribution of this one-dimensional system. We obtain the energy spectra and calculate total energy as a function of site index n in the single-strand chain to characterize the fractality of the energy distribution. To investigate the multifractal behavior of energy bands, we have determined the singularity spectrum f (alpha) using an algorithm based on Shannon, Eggelston, and Billingsley theorems. Our results show that the energy spectra exhibit a double power law. It is revealed a fractal behavior similar to the random Cantor set, with the formation of energy minibands, when n increases.
原文链接:- NSTL
- Elsevier
Sun, Peng GangWu, XunlianQuan, YiningMiao, Qiguang...
14页查看更多>>摘要：Communities in social networks represent social circles, and people within same circles often highly interact and strongly influence one another, and hence individual behaviors percolate quickly, and tend to invoke a resonance phenomenon, i.e., collective behaviors. Nowadays, boundaries between circles are more and more indistinct because people probably involve more than one circle. This paper develops an influence percolation method (IPM) for identifying overlapping communities. In IPM, we first determine the influenced area of each node through many times of simulations for influence percolation so that activated nodes with a frequency belong to the area, and those as clusters can initialize a cover for a network. Then, the cover is further refined through three stages, i.e., filtration, absorbtion and selection to determine communities. We systematically evaluate our method on plenty of artificial networks with various network characteristics as well as real-world networks. The results indicate that our method achieves the best performance on the networks with stronger overlaps, e.g., up to 50% overlapping nodes, each of which belongs to more than four communities, compared with the state of the art algorithms. An interesting finding is that two nodes tend to be indivisible if one is a seed, influence percolates into the other exceeding a certain frequency, and this threshold is mainly determined by the networks' density. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Liang, BoWang, LinWang, Xiaofan
12页查看更多>>摘要：Network embedding or graph representation learning has recently attracted more researchers' attention and achieved state-of-the-art performance in many areas and tasks. Nevertheless, most of these methods are targeted for monolayer networks and ignore the multiplexity property of nodes which refers to the multifaceted relationships between two elements. Multiplexity provides multiple types of auxiliary information to refine the characteristics of nodes and can be modeled as a multiplex network. In this study, we propose a multiplex network embedding algorithm to learn a unique embedding for each node in each layer or each relation type. A biased path-dependency random walk strategy is adopted to generate node sequences for integrating different types of relations between nodes, which pays more attention to overlapping links and makes neighbor nodes in the sampling sequence more similar to each other. Then the skip-gram model is used to learn an overall embedding over node sequences. To strengthen the expressive power of the embedding in a specific layer, a fine tuning strategy with low time cost is employed to make the embedding comprise information of nodes at this particular layer and preserve their distinctive properties, and the unique embedding is achieved ultimately. To verify the effectiveness of our algorithms, we validate the performance of our algorithm and other baseline methods in the link prediction task. The results demonstrate that the learned embedding can capture the interlayer relationships and preserve the specific characteristics of nodes, and our algorithms can stably obtain better or comparable performance compared with other methods.(C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Zhou, ShiruiLing, ShuaiZhu, ChenqiangTian, Junfang...
14页查看更多>>摘要：As the important spatiotemporal state of traffic flow discovered by Kerner's three-phase traffic theory, the synchronized traffic flow describes a new traffic phase in congested traffic. However, until now most models within the standard traffic theories cannot reproduce it. The average space gap model (ASGM) is a simple cellular automaton model aimed to reproduce various empirical findings discovered by Kerner's three-phase traffic theory by incorporating the influence of the multi-anticipative effect on vehicle's deceleration. However, this paper shows that the simulated synchronized flow by ASGM is not consistent with the reality. To this end, the Multi-Anticipative Model (MAM) based on ASGM is proposed, which describes the influence of the multi-anticipative effect on both the accelerations and the decelerations. Simulations indicate that the empirical consistent synchronized flow and related congested patterns can be well reproduced by MAM. Moreover, MAM can reproduce the speed drop in the car following vehicle platoons reported by the empirical observations. Generally, MAM indicates that the multi-anticipative effect can shed light on the understanding and capturing the complex characteristics of traffic flow especially reported by Kerner's three-phase traffic theory. (c) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
Schmidt, M.Kohlrausch, G. L.Zimmer, F. M.
8页查看更多>>摘要：We investigate phase transitions and thermodynamics of the Ising model with first neighbor (J1) and second-neighbor (J2) antiferromagetic (AF) interactions on the body centered cubic (bcc) lattice within a cluster mean-field approach. In this lattice, tuning g = J(2)/J(1) leads to a ground-state transition between AF and superantiferromagnetic (SAF) phases at the maximum of frustration g = 2/3. Although the ordering temperature is reduced as -> 2/3, our findings suggest the absence of strong frustration effects on the model, in good agreement with Monte Carlo simulations. We also find first-order phase transitions between AF and SAF phases at finite temperatures. Furthermore, the cluster mean-field outcomes support a scenario with only continuous phase transitions between the paramagnetic state and the low-temperature long-range orders. Therefore, our results indicate that frustration is unable to change the nature of the order-disorder phase transitions, which can be ascribed to the higher dimensionality of the bcc lattice.(C) 2022 Elsevier B.V. All rights reserved.
原文链接:- NSTL
- Elsevier
