Energy efficient and perceived QoS aware video routing over Wireless Multimedia Sensor Networks

Wireless Sensor Networks (WSNs) have an ever increasing variety of multimedia based applications. Ιn these types of applications, network nodes should ideally maximize QoS and minimize energy expenditures in video communication. This article presents PEMuR, a novel dual scheme for efficient video communication, which aims at both energy saving and high QoS attainment. To achieve its objectives, PEMuR proposes the combined use of an energy aware hierarchical routing protocol with an intelligent video packet scheduling algorithm. The adopted routing protocol enables the selection of the most energy efficient routing paths, manages the network load according to the energy residues of the nodes and prevents useless data transmissions through the proposed use of an energy threshold. In this way, an outstanding level of energy efficiency is achieved. Additionally, the proposed packet scheduling algorithm enables the reduction of the video transmission rate with the minimum possible increase of distortion. In order to do so, it makes use of an analytical distortion prediction model that can accurately predict the resulted video distortion due to any error pattern. Thus, the algorithm may cope with limited available channel bandwidth by selectively dropping less significant packets prior to their transmission. Simulation results demonstrate the effectiveness of the proposed scheme.     

Achieving downscaling of Meteosat thermal infrared imagery using artificial neural networks

This study presents the successful application of artificial neural networks (ANNs) for downscaling Meteosat Second Generation thermal infrared satellite imagery. The scope is to examine, propose, and develop an integrated methodology to improve the spatial resolution of Meteosat satellite images. The proposed approach may contribute to the development of a general methodology for monitoring and downscaling Earth’s surface characteristics and cloud systems, where there is a clear need for contiguous, accurate, and high-spatial resolution data sets (e.g. improvement of climate model input data sets, early warning systems about extreme weather phenomena, monitoring of parameters such as solar radiation fluxes, land-surface temperature, etc.). Moderate Resolution Imaging Spectroradiometer (MODIS) images are used to validate the downscaled Meteosat images. In terms of the ANNs, a multilayer perceptron (MLP) is used and the results are shown to compare favourably against a linear regression approach.     

Enrichment of table olives with polyphenols extracted from olive leaves

The possibility to increase the nutritional value of table olives using polyphenols extracted from olive leaves was studied. Leaves were subjected to extraction using water with proportions of 1%, 5% and 10% of leaves and various temperatures and times (room temperature/24 h, 40 °C/10 min and 70 °C/5 min). The antioxidant activity of extracts was determined using the Rancimat method and their content in oleuropein and hydroxytyrosol was determined by HPLC. The extract with the highest antioxidant activity and polyphenol content (10% ratio of olive leaves extracted at room temperature for 24 h) was used for the treatment of debittered table olives. The treated and untreated olives were subjected to determination of their α-tocopherol, oleuropein and hydroxytyrosol content. A 457% increase was observed for oleuropein and 109% for hydroxytyrosol content after treatment. Sensory evaluation of treated table olives showed an increase in bitterness. However, treated and untreated table olives showed equal overall acceptability and overall preference.     

A Counter Propagating Lens‐Mirror System for Ultrahigh Throughput Single Droplet Detection

Fluorescence‐based detection schemes provide for multiparameter analysis in a broad range of applications in the chemical and biological sciences. Toward the realization of fully portable analysis systems, microfluidic devices integrating diverse functional components have been implemented in a range of out‐of‐lab environments. That said, there still exits an unmet and recognized need for miniaturized, low‐cost, and sensitive optical detection systems, which provide not only for efficient molecular excitation, but also enhanced photon collection capabilities. To this end, an optofluidic platform that is adept at enhancing fluorescence light collection from microfluidic channels is presented. The central component of the detection module is a monolithic parabolic mirror located directly above the microfluidic channel, which acts to enhance the number of emitted photons reflected toward the detector. In addition, two‐photon polymerization is used to print a microscale‐lens below the microfluidic flow channel and directly opposite the mirror, to enhance the delivery of excitation radiation into the channel. Using such an approach, it is demonstrated that fluorescence signals can be enhanced by over two orders of magnitude, with component parallelization enabling the detection of pL‐volume droplets at rates up to 40 000 droplets per second.     

Demonstrating multi-objective screening of chemical batch process alternatives during early design phases

One of the key challenges for the design of sustainable chemical processes is to incorporate such concepts in the early phases of process design. In recent years, a few frameworks have been published to this direction, focusing mainly on continuous processes. However, the wide use of batch processes for the production of “low volume high value” chemicals makes the extension of such frameworks to this production environment indispensable. In the present study a recently presented multi-stage framework for multi-objective continuous process assessment is modified to incorporate batch process design aspects (e.g., cycle times, equipment utilization) in the form of early design phase indicators. Accordingly, a Productivity Loss Index (PLI) is defined for estimating periodic costs and environmental impacts, economic and environmental indicators are adjusted and a procedure to generate a base case separation process flowsheet is implemented. The modified framework is demonstrated on the design of a production process for 4-(2-methoxyethyl)-phenol considering seven potential synthesis routes.     

Removal of ammonium,iron and manganese from potable water in biofiltration units: a review

Ammonium, and trace metals such as iron and manganese are common inorganic pollutants present in waters. Several surface and groundwaters contain natural or increased concentrations of these pollutants that are observed either isolated or in pairs, or all three together. Although several processes have been established for the biological removal of one of the above‐mentioned pollutants, only recently have important studies been performed on the efficient and cost‐effective simultaneous biological removal of two or more substances. This paper reviews the variety of full‐ and pilot‐scale biological filters that have been used for combined or simultaneous biological removal, as well as factors and conditions that were found to affect the process. The main results regarding research progress on combined or simultaneous biological removal are evaluated. Finally, the kinetic models and simulation approaches used are discussed. © 2013 Society of Chemical Industry