A vehicular ad hoc network (VANET) is a mobile ad hoc network in which network nodes are vehicles-most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organized nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, information dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming-the lack of realistic vehicular channel modeling-is identified. The importance of a rigorous and standardized performance evaluation regime utilizing realistic vehicular channel models is demonstrated.

In this paper, we investigate antenna selection strategies for multiple-input-multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) wireless systems from an energy efficiency (EE) perspective. We first derive closed-form expressions of the EE and the energy efficiency-spectral efficiency (EE-SE) tradeoff in conventional antenna selection MIMO-OFDM systems. The obtained results show that these systems suffer from a significant loss in EE. To achieve a better EE performance, we propose an adaptive antenna selection method where both the number of active radio-frequency chains and the antenna indexes are selected depending on the channel condition. This selection scheme could be implemented by an exhaustive search technique for a small number of antennas. Moreover, we develop a greedy algorithm that achieves a near-optimal performance with much lower complexity compared with the (optimal) exhaustive search method when the number of antennas is large. In addition, the efficacy of power loading across subcarriers for improved EE in the conventional and proposed antenna selection MIMO-OFDM systems is considered. Monte Carlo simulation results are provided to validate our analyses.

Hybrid polypyrrole (PPy)–multi walled carbon nanotube (MWNT) yarns were obtained by chemical and electrochemical polymerization of pyrrole on the surface and within the porous interior of twisted MWNT yarns. The material was characterized by scanning electron microscopy, electrochemical, mechanical and electrical measurements. It was found that the hybrid PPy-MWNT yarns possessed significantly higher mechanical strength (over 740 MPa) and Young's modulus (over 54 GPa) than the pristine MWNT yarn. The hybrid yarns also exhibited substantially higher electrical conductivity (over 235 S cm⁻¹) and their specific capacitance was found to be in excess of 60 F g⁻¹. Measurements of temperature dependence of electrical conductivity revealed semiconducting behaviour, with a large increase of band gap near 100 K. The collected low temperature data are in good agreement with a three-dimensional variable range hopping model (3D-VRH). The improved durability of the yarns is important for electrical applications. The composite yarns can be produced in commercial quantities and used for applications where the electrical conductivity and good mechanical properties are of primary importance.

Multiplayer online games (MOGs) have become increasingly popular because of the opportunity they provide for collaboration, communication, and interaction. However, compared with ordinary human communication, MOG still has several limitations, especially in communication using facial expressions. Although detailed facial animation has already been achieved in a number of MOGs, players have to use text commands to control the expressions of avatars. In this paper, we propose an automatic expression recognition system that can be integrated into an MOG to control the facial expressions of avatars. To meet the specific requirements of such a system, a number of algorithms are studied, improved, and extended. In particular, Viola and Jones face‐detection method is extended to detect small‐scale key facial components; and fixed facial landmarks are used to reduce the computational load with little performance degradation in the recognition accuracy.

Fighting propagation delays in real-time interactive applications improves gameplay and fairness in networked games by trading off inconstencies and tuning decision points topology.

Conductive biomaterials have recently gained much attention, specifically owing to their application for electrical stimulation of electrically excitable cells. Herein, flexible, electrically conducting, robust fibers composed of both an alginate biopolymer and graphene components have been produced using a wet-spinning process. These nanocomposite fibers showed better mechanical, electrical, and electrochemical properties than did single fibers that were made solely from alginate. Furthermore, with the aim of evaluating the response of biological entities to these novel nanocomposite biofibers, in vitro studies were carried out using C2C12 myoblast cell lines. The obtained results from in vitro studies indicated that the developed electrically conducting biofibers are biocompatible to living cells. The developed hybrid conductive biofibers are likely to find applications as 3D scaffolding materials for tissue engineering applications.