Directional routing and scheduling for green vehicular delay tolerant networks

The vehicle delay tolerant networks (DTNs) make opportunistic communications by utilizing the mobility of vehicles, where the node makes delay-tolerant based “carry and forward” mechanism to deliver the packets. The routing schemes for vehicle networks are challenging for varied network environment. Most of the existing DTN routing including routing for vehicular DTNs mainly focus on metrics such as delay, hop count and bandwidth, etc. A new focus in green communications is with the goal of saving energy by optimizing network performance and ultimately protecting the natural climate. The energy–efficient communication schemes designed for vehicular networks are imminent because of the pollution, energy consumption and heat dissipation. In this paper, we present a directional routing and scheduling scheme (DRSS) for green vehicle DTNs by using Nash Q-learning approach that can optimize the energy efficiency with the considerations of congestion, buffer and delay. Our scheme solves the routing and scheduling problem as a learning process by geographic routing and flow control toward the optimal direction. To speed up the learning process, our scheme uses a hybrid method with forwarding and replication according to traffic pattern. The DRSS algorithm explores the possible strategies, and then exploits the knowledge obtained to adapt its strategy and achieve the desired overall objective when considering the stochastic non-cooperative game in on-line multi-commodity routing situations. The simulation results of a vehicular DTN with predetermined mobility model show DRSS achieves good energy efficiency with learning ability, which can guarantee the delivery ratio within the delay bound.     

End-to-End Performance Analysis of Millimeter Wave Triple-Hop Backhaul Transmission Systems

Frequencies above 10 GHz nowadays may be employed either for backhaul networks of mobile communication access networks or for broadband fixed wireless access networks. Millimeter wave networks can afford large bandwidth by carrying the aggregate traffic through different network nodes. Consequently, many line-of-sight multi-hop transmissions may occur. At these frequency bands, rain attenuation is the dominant fading mechanism that aggravates the outage performance of these networks. The objective of this paper is the presentation of analytical models for the calculation of the end-to-end performance analysis of a triple-hop system with non-regenerative and regenerative relays using the trivariate lognormal distribution along with a physical model for the calculation of the correlation coefficients among the rain fading channels. Moreover, an accurate rain attenuation time series synthesizer based on multi-dimensional first order Stochastic Differential eqnarrays is employed in order to validate the analytical results. Finally, extended numerical results investigate the impact of various operational and geographical parameters, as well as the influence of the arbitrary position of the relays on the outage system performance.     

Speech and Video Telephony Quality Characterization and Prediction of Live Contemporary Mobile Communication Networks

Quality of Service (QoS) characterization and prediction is of utmost importance in contemporary operating cellular communications networks. Measurements data of speech and video telephony have been collected using modern experimental equipment. More specifically, key performance indicators of radio, speech and video quality are evoked. The objective of our study is to critically investigate the performance of speech and video telephony at live cellular networks correlating significant QoS parameters from radio and the service side. Simple non-linear regression models are also proposed for speech and video quality prediction. Finally, the paper represents the splendid positive influences of the continuous performance evaluation for the optimization of the mobile networks. There are also briefly given guidelines for mobile networks benchmarking.     

Assessment of energy dissipation mechanisms for AT-cut QCM sensors with high frequency impedance analysis and optimization heuristics

In the present contribution, five unloaded AT-cut quartz crystal microbalance (QCM) sensors with nominal resonant frequencies equal to 5, 5.2 and 10 MHz, bearing silver (5.2 MHz) and gold electrodes (5 and 10 MHz) on their main surfaces, were bonded on a high pressure cell and studied with respect to their electrical and frequency response in the temperature range from 20 °C to 150 °C at a nitrogen atmosphere (P?=?1 atm). The goal was the qualitative and the quantitative identification of energy dissipation mechanisms of quartz resonators, based on their electrical response and effective properties (quartz viscosity and oscillation area). Electrical response measurements took place with high frequency impedance analysis (HF-IA), while admittance data were processed with the use of equivalent circuit theory and the Differential Evolution heuristic for nonlinear optimization, equipped with an error analysis module. Apart from the inherent energy dissipation due to sensor mounting and electrode related mass and stress effect, dissipation was also induced due to the manifestation of thermally active point defects at temperatures between 65 °C and 145 °C. These point defects are attributed to the movement of interstitial sodium ions within the crystal lattice. Energy dissipation was also observed due to temperature dependent (70–90 °C) creep deformation of the 60Sn-40Pb solder joints which bonded the mounted sensors to the experimental setup. A critical discussion on the magnitude of all observed dissipation mechanisms is presented.     

A Massively Parallel Time-Dependent Least-Time-Path Algorithm for Intelligent Transportation Systems Applications

This article is concerned with the problem of computing in parallel time-dependent least-time paths that can be used in real-time intelligent transportation systems applications. A message-passing scheme is presented, and its correctness is proved. The algorithm's computational complexity is shown to be O (| T |²| V |²), an improvement by | V | over the best-known sequential algorithm. The algorithm is implemented, coded, and computationally tested on actual and random networks with promising results. The algorithm is implemented on a CRAY-T3D supercomputer using a Parallel Virtual Machine environment that allows portability to lower-end multiprocessor machines.     

Influence of ozone on traffic-related particulate matter on the generation of hydroxyl radicals through a heterogeneous synergistic effect

Epidemiologic studies suggest that ozone (O(3)) and airborne particulate matter (PM) can interact causing acute respiratory inflammation and other respiratory diseases. Recent studies investigated the hypothesis that the effects of air pollution caused by O(3) and PM are larger than the effect of these two pollutants individually. We investigated the hypothesis that ozone and traffic-related PM (PM(10) and PM(2.5), diesel and gasoline exhaust particles) interact synergistically to produce increasing amounts of highly reactive hydroxyl radicals (HO) in a heterogeneous aqueous mixture at physiological pH. Electron paramagnetic resonance (EPR) and spin trapping were used for the measurements. Results showed that HO radicals are generated by the catalytic action of PM surface area with ozone and that EPR peak intensities are two to three times higher compared to PM samples without ozone. Incubation of the nucleoside 2'-deoxyguanosine (dG) in aqueous mixtures of ozone and PM at pH 7.4 resulted in the hydroxylation at C(8) position of dG. The formation of 8-hydroxy-2'-deoxyguanosine (8-OHdG) showed a 2-2.5-fold increase over control (PM without O(3)). These results suggest that PM and O(3) act synergistically generating a sustained production of reactive HO radicals. Partitioning of O(3) into the particle phase depends on the concentration, hygroscopicity and particle size.     

Mobile social networking: reconnect virtual community with physical space

Online social networks (OSNs) such as Facebook and MySpace, etc., greatly improve our social connectivity and collaboration. However, those applications lead to a shift from physical communities to virtual communities. The recent availability of mobile broadband connections and location technologies, their increasing affordability, and the usability of new mobile devices (e.g. smartphones) have led to the emergence of mobile social networks (MSNs), which re-connect the virtual community to the physical region, and move users between them in a way that enhances both. Currently, MSN applications are mushrooming and racing to replicate the success of social computing in the mobile domain. We argue that the potential success of MSNs lies in active collaboration among users, which naturally arises many interdisciplinary challenges. However, there exists no systematical survey about MSNs. This paper thoroughly characterizes the basic design principles, research architecture, typical techniques, and fundamental issues in MSNs from cross-discipline and application viewpoints. Our contributions lie in the following aspects: First, we summarized the basic design principles and fundamental issues that run through MSN researches and applications; then, from multidisciplinary viewpoint, the research architecture is divided into multi-dimensional structural characteristics and evolution of users’ rational behaviors. Finally, from application perspective, MSNs are categorized into two areas: Socially inspired mobile networking technologies, and enhanced real social life with mobile computing (people-centric tasks and place centric tasks). Briefly, this paper organizes the isolated topics and systems in existing work into meaningful categories, and structures the design space for identifying social-technical challenges, inspiring potentially interesting social networking applications, and suggesting important research opportunities.     

High resolution melting analysis for quantitative detection of bovine milk in pure water buffalo mozzarella and other buffalo dairy products

Identification of buffalo dairy products has become an important issue to ascertain product quality, consumer rights and absence of food-borne allergic reactions. A polymerase chain reaction (PCR) followed by a high resolution melting (HRM) analysis was developed and applied for species specific detection of bovine milk in nine different commercial buffalo dairy products. A specific buffalo 12S rRNA and a bovine d-loop primer pair, targeting the mitochondrial genome, were employed in a duplex PCR assay. The analysis developed was found capable of identifying the presence of bovine milk down to 1% in commercial buffalo milk products and also of quantifying the ratio of bovine into buffalo milk. HRM was proven to be a fast and accurate technique for a routine authentication testing of mozzarella and other buffalo milk products.     

Kefir Immobilized on Corn Grains as Biocatalyst for Lactic Acid Fermentation and Sourdough Bread Making

Abstract: The natural mixed culture kefir was immobilized on boiled corn grains to produce an efficient biocatalyst for lactic acid fermentation with direct applications in food production, such as sourdough bread making. The immobilized biocatalyst was initially evaluated for its efficiency for lactic acid production by fermentation of cheese whey at various temperatures. The immobilized cells increased the fermentation rate and enhanced lactic acid production compared to free kefir cells. Maximum lactic acid yield (68.8 g/100 g) and lactic acid productivity (12.6 g/L per day) were obtained during fermentation by immobilized cells at 37 °C. The immobilized biocatalyst was then assessed as culture for sourdough bread making. The produced sourdough breads had satisfactory specific loaf volumes and good sensory characteristics. Specifically, bread made by addition of 60% w/w sourdough containing kefir immobilized on corn was more resistant regarding mould spoilage (appearance during the 11^th day), probably due to higher lactic acid produced (2.86 g/Kg of bread) compared to the control samples. The sourdough breads made with the immobilized biocatalyst had aroma profiles similar to that of the control samples as shown by headspace SPME GC‐MS analysis.     

Barcode High Resolution Melting (Bar-HRM) analysis for detection and quantification of PDO “Fava Santorinis” (Lathyrus clymenum) adulterants

Legumes considered as one of the most important crops worldwide. Due to high price as a PDO product, commercial products of “Fava Santorinis” are often subjected to adulterations from other legume products coming from other Lathyrus or Vicia and Pisum species. Using plant DNA barcoding regions (trnL and rpoC) coupled with High Resolution Melting (Bar-HRM) we have developed a method allowing us to detect and authenticate PDO “Fava Santorinis”. Bar-HRM proved to be a very sensitive tool able to genotype Lathyrus and its closed relative species and to detect admixtures, being sensitive enough to as low as 1:100 of non-“Fava Santorinis” in “Fava Santorinis” commercial products. In conclusion, Bar-HRM analysis can be a faster, with higher resolution and cost effectiveness alternative method to authenticate PDO “Fava Santorinis” and to quantitatively detect adulterations in “Fava Santorinis” with other relative commercial “Fava” food products.