Power Efficient Video Multipath Transmission over Wireless Multimedia Sensor Networks

This paper proposes a power efficient multipath video packet scheduling scheme for minimum video distortion transmission (optimised Video QoS) over wireless multimedia sensor networks. The transmission of video packets over multiple paths in a wireless sensor network improves the aggregate data rate of the network and minimizes the traffic load handled by each node. However, due to the lossy behavior of the wireless channel the aggregate transmission rate cannot always support the requested video source data rate. In such cases a packet scheduling algorithm is applied that can selectively drop combinations of video packets prior to transmission to adapt the source requirements to the channel capacity. The scheduling algorithm selects the less important video packets to drop using a recursive distortion prediction model. This model predicts accurately the resulting video distortion in case of isolated errors, burst of errors and errors separated by a lag. Two scheduling algorithms are proposed in this paper. The Baseline scheme is a simplified scheduler that can only decide upon which packet can be dropped prior to transmission based on the packet’s impact on the video distortion. This algorithm is compared against the Power aware packet scheduling that is an extension of the Baseline capable of estimating the power that will be consumed by each node in every available path depending on its traffic load, during the transmission. The proposed Power aware packet scheduling is able to identify the available paths connecting the video source to the receiver and schedule the packet transmission among the selected paths according to the perceived video QoS (Peak Signal to Noise Ratio—PSNR) and the energy efficiency of the participating wireless video sensor nodes, by dropping packets if necessary based on the distortion prediction model. The simulation results indicate that the proposed Power aware video packet scheduling can achieve energy efficiency in the wireless multimedia sensor network by minimizing the power dissipation across all nodes, while the perceived video quality is kept to very high levels even at extreme network conditions (many sensor nodes dropped due to power consumption and high background noise in the channel).     

Model analysis of sorption isotherms

The equation developed by Blahovec and Yanniotis, which is based on surface adsorption and solution water, was applied for fitting experimental sorption data for starchy and high protein foods, fruits and vegetables, nuts, legumes, and seeds. Analysis of sorption isotherms shows that surface adsorption is more important than solution water in the isotherms for cereals, potatoes, legumes and seeds, while in vegetables, fruits, meat, milk products and some nuts solution water is more important. The ratio of solution water to surface adsorption increases as water activity increases, it is higher for the adsorption isotherm than the desorption isotherm at any water activity value and decreases as temperature increases.     

Volatile fraction of commercial thyme honeys produced in Mediterranean regions and key volatile compounds for geographical discrimination: A chemometric approach

The aim of the present study was to investigate the volatile fraction and discriminate 34 commercial thyme honeys from Morocco, Egypt, Spain, and Greece according to geographical origin, using key volatile compounds in combination with chemometrics. Sixty-two volatile compounds belonging to different classes were identified and semi-quantified using headspace solid phase micro-extraction coupled to gas chromatography/mass spectrometry (HS-SPME-GC/MS). Applying chemometric analyses to 17 volatiles (p < 0.05), honeys were successfully discriminated according to geographical origin. Correct classification rate was 88.2% using the cross-validation method. Volatile compounds proved to be a powerful tool for discriminating commercial thyme honeys from different countries.     

Relations between environmental black carbon sorption and geochemical sorbent characteristics

Pyrogenic carbon particles in sediments (soot and charcoal, collectively termed "black carbon" or BC) appear to be efficient sorbents of many hydrophobic organic compounds, so they may play an important role in the fate and toxicity of these substances. To properly model toxicant sorption behavior, it is important to (i) quantify the magnitude of the role of BC in sorption and (ii) elucidate which geochemical BC characteristics determine the strength of environmental BC sorption. Sorption isotherms of d10-phenanthrene (d10-PHE) were determined over a wide concentration range (0.0003-20 microg/L), for five sediments with widely varying characteristics. From the sorption isotherms, we determined Freundlich coefficients of environmental BC sorption, K(F,BCenv. These varied from 10(4.7) to 10(5.5). From the data, it could be deduced that BC was responsible for 49-85% of the total d10-PHE sorption at a concentration of 1 ng/L. At higher concentrations, the importance of BC for the sorption process diminished to <20% at 1 microg/L and 0-1% at 1 mg/L. There were no significant relationships between BC sorption strength and the tested geochemical BC characteristics [the fraction of small (<38 microm) BC particles, the BC resistance to high-temperature oxidation, the fraction of biomass-derived BC, the native polycyclic aromatic hydrocarbon and total organic carbon contents]. Because of the limited variation in BC sorption strength with widely varying BC characteristics, the presented BC sorption coefficients may putatively be used as generic starting points for environmental modeling purposes.     

Microbiological and physicochemical characterisation of green table olives of Halkidiki and Conservolea varieties processed by the Spanish method on industrial scale

The microbiological and physicochemical changes of industrially fermented Halkidiki and Conservolea green table olives were determined. Samples were analysed to monitor the population of lactic acid bacteria (LAB), yeasts and Enterobacteriaceae, together with changes in pH, acidity, salinity, colour, lactic acid, acetic acid and ethanol. LAB and yeast species diversity was evaluated at the beginning (1 day), middle (75 days) and final (135 days) stages of fermentation by RAPD-PCR genomic fingerprinting. Results revealed vigorous lactic acid processes as indicated by the dominance of LAB over yeasts. No Enterobacteriaceae could be detected after 30 days. Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) dominated in the beginning of fermentation in both varieties. In the end, Lactiplantibacillus pentosus (formerly Lactobacillus pentosus) and Pediococcus ethanolidurans prevailed in Halkidiki and Conservolea varieties, respectively. As for yeasts, Kluyveromyces lactis/marxianus and Pichia manshurica prevailed at the onset of fermentation in Halkidiki and Conservolea varieties, whereas in the end Pichia membranifaciens dominated in both varieties.     

Electric vehicle charging in stochastic smart microgrid operation with fuel cell and RES units

Plug-in electric vehicles increasingly augment their share in the global market as they appear to be an economic and emission-free alternative to modern means of transportation. As their presence strengthens, ways that will ensure economic charge along with uninterrupted grid operation are necessary to be found. This paper aims to approach the economic optimization problem that includes several Electric Vehicles (EVs) within a Low Voltage (LV) network comprising various Distributed Energy Resources (DER) as fuel cell, Renewable Energy Sources (RES), (photovoltaics, wind turbine) etc. via a scenario based simulation. The purpose is to investigate the main variables of the grid, such as its operating cost, charging patterns, power injection from the upstream network, resulting from the coordinated control of DER in Smart Microgrid operation in conjunction to the flexible load the controlled EV charging introduces. The base case study is that of absence of EVs, and therefore the demand is met only by the upstream network and the DER units. Subsequently, EVs are introduced as controllable loads and finally as dispatchable storage units incorporating a Vehicle to Grid (V2G) capability to the Smart Microgrid. Furthermore, the problem is not tackled deterministically and although forecasts for all network parameters are assumed to be known, forecasting errors and stochastic driver patterns cannot be ignored. Thus, for each imposed policy, a scenario based approach is implemented to determine operating cost in various cases along to DER utilization and the effect EVs bear on these results.     

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.     

A framework for designing cloud forensic-enabled services (CFeS)

Requirements Engineering - Cloud computing is used by consumers to access cloud services. Malicious actors exploit vulnerabilities of cloud services to attack consumers. The link between these two...