Muhammad Waqas^{1, 2}, Shanshan Tu^{1, 3, *}, Sadaqat Ur Rehman¹, Zahid Halim², Sajid Anwar², Ghulam Abbas², Ziaul Haq Abbas⁴, Obaid Ur Rehman⁵

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821

Abstract Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state… More >

M. G. RÍOS-DURÁN*, A. R. HERNÁNDEZ-TÉLLEZ**, C. A. MARTÍNEZ-PALACIOS**, L. G. ROSS***

BIOCELL, Vol.30, Suppl.S, pp. 149-155, 2006

Abstract This article has no abstract. More >

Hideaki Uchida^*, Hideki Fujii, Shinobu Yoshimura

The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.3, pp. 67-67, 2019, DOI:10.32604/icces.2019.05902

Abstract In recent years, EVs (Electric Vehicles) with high environmental performance has been popularized. To realize a low-carbon and sustainable society, EVs are expected to play major roles, and it is essential to use renewable energy for their charging effectively. Interactions between the transportation network and the electric power system have not been considered so far. However, the interactions are supposed to occur via EVs, which will popularize in the near future. Most of the previous studies about EVs’ popularization focused on either the transportation or the electric power system, and no sufficient simulation model has been studied. In this research,… More >

Weiwei Liu^{1, *}, Yang Tang², Fei Yang², Jin Wang³

Journal on Internet of Things, Vol.1, No.2, pp. 71-76, 2019, DOI:10.32604/jiot.2019.05946

Abstract Carbon monoxide (CO) is harmful to our health, and even causes death. The main source of CO is automobile exhaust. Therefore, this article determines that CO is the emission factor, and finally the evaluation model is established. The model provides an important basis for the highway construction project design, traffic management, environmental pollution control, energy saving, environmental evaluation and so on. Compared with the traditional method that calculates the road traffic volume through the air emissions model, according to the total amount of air pollution control, this paper builds the emission diffusion model, which calculates the road traffic volume by… More >

Chen X.Y.^∗,†, Liu Y.^2,‡, Fu B.M.^§, Fan J.T.^¶, Yang J.M.¹

Molecular & Cellular Biomechanics, Vol.5, No.4, pp. 275-284, 2008, DOI:10.3970/mcb.2008.005.275

Abstract Surface glycocalyx, as a barrier to material exchange between circulating blood and body tissues, can be treated as a periodic square array of cylindrical fibers. Previous study treated the glycocalyx as porous media and simulated by continuum theory. However, it has recently been found that a relatively hexagonal fibre-matrix structure may be responsible for the ultrafiltration properties of microvascular walls. The fibre-matrix is an underlaying three-dimensional meshwork with a fibre diameter of 10$\sim$12 nm and characteristic spacing of about 20 nm. The porous medium model does not consider the particle size, when the particle size is comparable to the fibre… More >

G.S. Li¹, D. Yao², Y.Z. Wang³, H.Y. Jiang²

CMES-Computer Modeling in Engineering & Sciences, Vol.51, No.1, pp. 53-72, 2009, DOI:10.3970/cmes.2009.051.053

Abstract In this paper, an undisturbed soil-column infiltrating experiment is investigated, and a mathematical model describing multi-components solutes transport behaviors in the column is put forward by combing hydro-chemical analysis with advection dispersion mechanisms, which is a group of advection-dispersion-reaction partial differential equations. Since the model involving six reaction coefficients which can not be obtained directly, an optimal perturbation regularization algorithm of determining these parameters is performed, and numerical simulations under different conditions are carried out. Furthermore, the inversion algorithm is applied to solve the real inverse problem by utilizing the measured breakthrough data. The reconstruction data basically coincide with the… More >

M.J. Galán Moreno, J.J. Sánchez Medina, L. Álvarez Álvarez E. Rubio Royo¹

CMES-Computer Modeling in Engineering & Sciences, Vol.50, No.3, pp. 191-226, 2009, DOI:10.3970/cmes.2009.050.191

Abstract Urban traffic is a key factor for the development of a city. There exist many different approaches facing traffic optimization. In our case we have focused on traffic lights optimization. We have designed and tested a new architecture to optimize traffic light cycle times. The purpose of this research is to demonstrate the good performance of our architecture in a congested scenario. We have simulated several congestion situations for a very large real world traffic network - "La Almozara" in Zaragoza, Spain. Our results seem encouraging in this extreme situation. As we increase the load in the network we get… More >

Shuren Zhou^1,2,*, Wenlong Liang^1,2, Junguo Li^1,2, Jeong-Uk Kim³

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 11-24, 2018, DOI:10.32604/cmc.2018.02617

Abstract Road traffic sign recognition is an important task in intelligent transportation system. Convolutional neural networks (CNNs) have achieved a breakthrough in computer vision tasks and made great success in traffic sign classification. In this paper, it presents a road traffic sign recognition algorithm based on a convolutional neural network. In natural scenes, traffic signs are disturbed by factors such as illumination, occlusion, missing and deformation, and the accuracy of recognition decreases, this paper proposes a model called Improved VGG (IVGG) inspired by VGG model. The IVGG model includes 9 layers, compared with the original VGG model, it is added max-pooling… More >

Huiyu Sun^1,*, Suzanne McIntosh¹

CMC-Computers, Materials & Continua, Vol.57, No.1, pp. 1-9, 2018, DOI:10.32604/cmc.2018.03684

Abstract The majority of big data analytics applied to transportation datasets suffer from being too domain-specific, that is, they draw conclusions for a dataset based on analytics on the same dataset. This makes models trained from one domain (e.g. taxi data) applies badly to a different domain (e.g. Uber data). To achieve accurate analyses on a new domain, substantial amounts of data must be available, which limits practical applications. To remedy this, we propose to use semi-supervised and active learning of big data to accomplish the domain adaptation task: Selectively choosing a small amount of datapoints from a new domain while… More >