Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

A citation-based review of study on image retrieval

Driven by the development of the information retrieval technologies, image retrieval has been studied for more than several decades. This study centers on revealing the current status and future directions of image retrieval based on reviewing previous related studies. The citation-based analysis was applied to 2243 articles retrieved from Web of Science database. The time series plots of the citation relationships between the retrieved articles reveal a fundamental research article that lay the foundation for the image retrieval field. Co-citation analysis identifies that the existing studies formed two clusters. Each cluster represents one of the two major areas in the field of image retrieval: the text-based image retrieval and the content-based image retrieval. The visualization map shows that the research of content-based image retrieval has received more attention than the area of text-based image retrieval. Relevance feedback was identified as a promising research direction for the future study

Highly tunable spin-dependent electron transport through carbon atomic chains connecting two zigzag graphene nanoribbons

Motivated by recent experiments of successfully carving out stable carbon atomic chains from graphene, we investigate a device structure of a carbon chain connecting two zigzag graphene nanoribbons with highly tunable spin-dependent transport properties. Our calculation based on the non-equilibrium Green's function approach combined with the density functional theory shows that the transport behavior is sensitive to the spin configuration of the leads and the bridge position in the gap. A bridge in the middle gives an overall good coupling except for around the Fermi energy where the leads with anti-parallel spins create a small transport gap while the leads with parallel spins give a finite density of states and induce an even-odd oscillation in conductance in terms of the number of atoms in the carbon chain. On the other hand, a bridge at the edge shows a transport behavior associated with the spin-polarized edge states, presenting sharp pure $\alpha$-spin and $\beta$-spin peaks beside the Fermi energy in the transmission function. This makes it possible to realize on-chip interconnects or spintronic devices by tuning the spin state of the leads and the bridge position.Comment: 7 pages, 9 figure

Empirical Likelihood Ratio Tests for Coe cients in High Dimensional Heteroscedastic Linear Models

This paper considers hypothesis testing problems for a low-dimensional coefficient vector in a high-dimensional linear model with heteroscedastic variance. Heteroscedasticity is a commonly observed phenomenon in many applications, including finance and genomic studies. Several statistical inference procedures have been proposed for low-dimensional coefficients in a high-dimensional linear model with homoscedastic variance, which are not applicable for models with heteroscedastic variance. The heterscedasticity issue has been rarely investigated and studied. We propose a simple inference procedure based on empirical likelihood to overcome the heteroscedasticity issue. The proposed method is able to make valid inference even when the conditional variance of random error is an unknown function of high-dimensional predictors. We apply our inference procedure to three recently proposed estimating equations and establish the asymptotic distributions of the proposed methods. Simulation studies and real data applications are conducted to demonstrate the proposed methods

Photoelectric Properties of DSSCs Sensitized by Phloxine B and Bromophenol Blue

Phloxine B and bromophenol blue as the sensitizers of dye-sensitized solar cells were investigated via UV-Vis spectra, FT-IR spectra, fluorescence spectra, and current-voltage characteristics. The frontier molecular orbital, vibration analysis, and the first hyperpolarizability were calculated with DFT/6-31G(d). The dipole moment, light harvesting efficiency (LHE), and larger absolute value of driving force of electron injection (ΔGinject) were also discussed. The calculated results were compared with the experimental results of phloxine B and bromophenol blue. It was found that, compared with bromophenol blue, bigger dipole moment of phloxine B results in larger open circuit voltage (Voc) according to the correlation between dipole moment and Voc. At the same time, for configuration of phloxine B, it has higher LHE and ΔGinject, which are helpful to enhance the abilities of absorbing sunlight and electron injection. Therefore, higher LHE and ΔGinject for phloxine B produced a larger value of Jsc

Effect of fibers on the temperature field and radialdeformation behavior of self-compacting concrete pipesunder cyclic fire condition

In this paper, the radial deformation of fiber reinforced self-compacting con-crete (SCC) pipes under cyclic fire conditions is studied. A series of experimen-tal study on the temperature fields and radial deformation properties of steelmesh, polypropylene fiber (PP fiber), and macro steel fiber (SF) reinforcedSCC pipes subjected to fire is carried out. A novel method for measuring thedeformation of pipes under high temperature has been proposed. The resultsindicate that both micro PP fiber and macro SF are effective in decreasing thetemperature difference and reducing the radial deformation in each thermalcycle. A significant positive synergistic effect on decreasing the residual radialdeformation can be achieved by combined use of macro SF and micro PP fiber.The elastic theory is used to estimate the elastic portion in the total radialdeformation, and the elastic radial deformation is about 22.3% of the maxi-mum radial deformation in the first thermal cycle. Based on the elastic calcula-tion and observed experimental results, a simplified method for estimating themaximum radial deformation in the first thermal cycle is proposed.National Natural Science Foundation of China, Grant/Award Number: 5157810