Microwave curing of epoxy polymers reinforced with carbon nanotubes

The driver for this study is the observation that heating of carbon nanotubes (CNTs) with electromagnetic field can offer a more efficient and cost‐effective alternative in heat transfer for the production of composites. The idea of this study is twofold; CNT can work as microwave (MW) radiation susceptors and they can act as nanoreinforcements in the final system. To test these assumptions, a household oven was modified to control the curing schedule. Polymers with different CNT concentrations were prepared (0.5 and 1.0 wt %). The dispersion of the CNTs in the epoxy was achieved using shear‐mixing dissolver technique. MW and conventionally cured specimens were also produced in a convection oven for reference. Thermal and mechanical tests were used as control point. A curing schedule investigation was further performed to quantify the energy and time‐saving capabilities using CNT and MWs. The presence of CNTs into epoxy matrix has been proven beneficial for the shortening of the curing time. MW‐cured composites showed the same degree of polymerization with the conventionally cured composites in a shorter time period and this time was reduced as the CNT concentration was increased. A good distribution of the CNT is required to avoid hot spot effects and local degradation. Mechanical performance was, in some cases, favored by the use of CNT. The benefit from the use of MWs and CNT could reach at least 40% in terms of energy needed and time without sacrificing mechanical performance. © 2013 Wiley Periodicals, Inc. J. Appl. Polym. Sci., 2013     

Evaluation of channel dependent bandwidth allocation in wireless access networks: centralized and distributed approach

The problem of bandwidth allocation in wireless access networks is studied in this paper, investigating the performance of two approaches. Firstly, we use centralized algorithms, such as bankruptcy division rules and Nash bargaining. Secondly, a distributed algorithm is proposed in order to find the optimal solution of the bandwidth allocation problem. In both approaches, the allocation rules are properly modified to incorporate the influence of the channel state resulting in a more efficient and fair bandwidth allocation. The channel dependent centralized and distributed schemes are compared in terms of efficiency and fairness with a view to highlighting the advantages and disadvantages of every approach.     

Predicting returns on Canadian exchange rates with artificial neural networks and EGARCH-M models

This paper investigates the problem of predicting daily returns based on five Canadian exchange rates using artificial neural networks and EGARCH-M models. First, the statistical properties of five daily exchange rate series (US Dollar, German Mark, French Franc, Japanese Yen and British Pound) are analysed. EGARCH-M models on the Generalised Error Distribution (GED) are fitted to the return series, and serve as comparison standards, along with random walk models. Second, backpropagation networks (BPN) using lagged returns as inputs are trained and tested. Estimated volatilities from the EGARCH-M models are used also as inputs to see if performance is affected. The question of spillovers in interrelated markets is investigated with networks of multiple inputs and outputs. In addition, Elman-type recurrent networks are also trained and tested. Comparison of the various methods suggests that, despite their simplicity, neural networks are similar to the EGARCH-M class of nonlinear models, but superior to random walk models, in terms of insample fit and out-of-sample prediction performance.     

Wall factor for acceleration and terminal velocity of falling spheres at high reynolds numbers

The wall factor for spheres in the acceleration and terminal velocity ranges was determined experimentally for very high Reynolds numbers (13 500 < Re < 70 000). Experiments were performed with 12, 15, 18, 21, 25 and 31.75 mm spheres, falling in water inside cylinders 3.4, 4.9, 7, 10, 14 and 19 cm in diameter. A published empirical equation was found to yield good results for the terminal velocity wall factor in the range of studied Reynolds numbers.     

Interactive theatre via mixed reality and Ambient Intelligence

Our system of Mixed Reality and 3D Live with Ambient Intelligence (AmI) is indented to bring performance art to the people while offering to the performance artists a creative tool to extend the grammar of the traditional theatre. Actors and dancers at different places are captured by multiple cameras and their images are rendered in 3D form in such a way that they can play and dance together on the same place in real-time. Our Quanticum Man is an allegory of the time of the General Relativity and the matter of the Quantum Mechanics. The new type of interactive theatre enables social networking by supporting simultaneous participants in human-to-human social manner.     

An empirical examination of the determinants of honey consumption in Romania

While not much attention has been paid in the international literature to the consumption of premium food products with enhanced quality properties in Central‐Eastern European Countries (CEECs), the present survey aims to investigate consumer behaviour in Romania as regards ‘honey’ as an example of such a product. The research concludes that, despite the changes in eating habits induced by changes in the retail environment, honey remains a popular product, the purchase of which in bulk from producers and in open markets is still the dominant trend. The survey further identifies four main dimensions of honey‐purchasing motivation: medical benefits of its consumption, dietary quality, ethical character of honey and suitability with food consumption lifestyle. Using these dimensions validated by factor analysis, three clusters of honey consumers in Romania emerged through cluster analysis: the common consumers, the younger consumers indifferent towards honey and the enthusiastic consumers, who are also more willing to pay premium prices for the organic type of honey. If the first segment may be the keenest on competitive prices, quality differentiation strategies can target the enthusiastic honey consumers. The distinctive features of Romanian consumers also include a low attention paid to labels, related in a low awareness of the energy content of honey. Quality cues are defined by search attributes of the bulk product (colour, taste, aroma, thickness), rather than credence attributes (warranties, brand name, country‐of‐origin). Marketers targeting this market should be aware of this scepticism towards label information, which necessitates more communication effort to built consumer trust.     

A generic framework for energy evaluation on wireless sensor networks

Due to reliance on batteries, energy consumption has always been of significant concern for sensor node networks. This work presents the design and implementation of a house-build experimental platform, named Energy Management System for Wireless Sensor Networks (EMrise) for the energy management and exploration on wireless sensor networks. Consisting of three parts, the SystemC-based simulation environment of EMrise enables the HW/SW co-simulation for energy evaluation on heterogeneous sensor networks. The hardware platform of EMrise is further designed to facilitate the realistic energy consumption measurement and calibration as well as accurate energy exploration. In the meantime, a generic genetic algorithm based optimization framework of EMrise is also implemented to automatically, quickly and intelligently fine tune hundreds of possible solutions for the given task to find the best suitable energy-aware tradeoffs.     

A top-down event-driven approach for concurrent activity recognition

In this paper a framework for automatic online workflow recognition in industrial environments where the issue of concurrent activities rises, is presented. The framework consists of three main parts: The first part is devoted to detecting activity in specific Regions of Interest (ROIs) of the video sequence. This is effected by separating each frame into ROIs and representing the resulting subimages through feature vectors. By observing these vectors we can determine when there is action in a particular ROI. The second part of the framework lies in examining whether the detected activity corresponds to a workflow related event. This is accomplished by HMM modeling. Finally, the third part employs a string matching based technique to confirm the validity of the observed sequence of events or correct any detection or classification errors. This last step also addresses a top down approach by informing lower system levels (such as image representation or object tracking) about the errors committed. The performance of the proposed approach is thoroughly evaluated under real-life complex visual workflow understanding scenarios, in an industrial plant. The obtained results are compared and discussed.     

Development of damage probability matrices based on Greek earthquake damage data

A comprehensive study is presented for empirical seismic vulnerability assessment of typical structural types,representative of the building stock of Southern Europe, based on a large set of damage statistics. The observational database was obtained from post-earthquake surveys carried out in the area struck by the September 7, 1999 Athens earthquake. After analysis of the collected observational data, a unified damage database has been created which comprises 180,945 damaged buildings from/after the near-field area of the earthquake. The damaged buildings are classified in specific structural types,according to the materials, seismic codes and construction techniques in Southern Europe. The seismic demand is described in terms of both the regional macroseismic intensity and the ratio ag/ao, where ag is the maximum peak ground acceleration (PGA) of the earthquake event and ao is the unique value PGA that characterizes each municipality shown on the Greek hazard map. The relative and cumulative frequencies of the different damage states for each structural type and each intensity level are computed in terms of damage ratio. Damage probability matrices (DPMs) and vulnerability curves are obtained for specific structural types. A comparison analysis is fulfilled between the produced and the existing vulnerability models.