Scalable Solid-Template Reduction for Designed Reduced Graphene Oxide Architectures

Herein, we report a solid-state reduction process (in contrast to solution-based approach) by using an environmentally friendly reductant, such as vitamin C (denoted VC), to be directly employed to solid-state graphene oxide (GO) templates to give the highly active rGO architecture with a sheet resistance of as low as 10 Ω sq–1. In addition, predesigned rGO patterns/tracks with tunable resistivity can be directly “written” on a preprepared solid GO film via the inkjet-printing technique using VC/H2O as the printing-ink. This advanced reduction process allows foreign active materials to be preincorporated into the GO matrix to form quality active composite architectures.

Using data mining for digital ink recognition: dividing text and shapes in sketched diagrams

The low accuracy rates of textshape dividers for digital ink diagrams are hindering their use in real world applications. While recognition of handwriting is well advanced and there have been many recognition approaches proposed for hand drawn sketches, there has been less attention on the division of text and drawing ink. Feature based recognition is a common approach for textshape division. However, the choice of features and algorithms are critical to the success of the recognition. We propose the use of data mining techniques to build more accurate textshape dividers. A comparative study is used to systematically identify the algorithms best suited for the specific problem. We have generated dividers using data mining with diagrams from three domains and a comprehensive ink feature library. The extensive evaluation on diagrams from six different domains has shown that our resulting dividers, using LADTree and LogitBoost, are significantly more accurate than three existing dividers.

The impact of occupant behaviour on residential greenhouse gas emissions reduction

In 2011-12, greenhouse gas emissions from the Australian residential sector were 101.6 Mt and are expected to grow by 38% by 2050. In order to reduce these emissions, much emphasis has been placed on increasing the energy efficiency of buildings and appliances. Occupant behaviour, however, is probably the single most significant factor which determines energy use and emissions. This paper describes research undertaken to rank the most common occupant behaviours, based upon their impact on greenhouse gas emissions associated with residential energy use, in an architect-designed house in Australia. The occupant behaviours investigated were changing: the heating and cooling temperature set points, window openings, external blind use and lighting use. Simulations were carried out using Primero and EnergyPlus software. Based on the simulation results of greenhouse gas emissions, the following ranking of overall influence (from most influential to the least) has been determined: external blind use was one of the most effective measures to reduce emissions. Cooling set point temperature was similarly important with the magnitude of impact depending on the set point e.g. a 2°C increase had an impact comparable to the use of external blinds. The impact of the heating set point temperature was also dependent on the set point and overall slightly lower compared to the cooling set point temperature. Lighting use was the least influential parameter in the context of this study.

Cooperative data scheduling in hybrid vehicular ad hoc networks: VANET as a software defined network

This paper presents the first study on scheduling for cooperative data dissemination in a hybrid infrastructure-to-vehicle (I2V) and vehicle-to-vehicle (V2V) communication environment. We formulate the novel problem of cooperative data scheduling (CDS). Each vehicle informs the road-side unit (RSU) the list of its current neighboring vehicles and the identifiers of the retrieved and newly requested data. The RSU then selects sender and receiver vehicles and corresponding data for V2V communication, while it simultaneously broadcasts a data item to vehicles that are instructed to tune into the I2V channel. The goal is to maximize the number of vehicles that retrieve their requested data. We prove that CDS is NP-hard by constructing a polynomial-time reduction from the Maximum Weighted Independent Set (MWIS) problem. Scheduling decisions are made by transforming CDS to MWIS and using a greedy method to approximately solve MWIS. We build a simulation model based on realistic traffic and communication characteristics and demonstrate the superiority and scalability of the proposed solution. The proposed model and solution, which are based on the centralized scheduler at the RSU, represent the first known vehicular ad hoc network (VANET) implementation of software defined network (SDN) concept.