Coil enhancements for high efficiency wireless power transfer applications

Achieving high efficiency with improved power transfer range and misalignment tolerance is the major design challenge in realizing Wireless Power Transfer (WPT) systems for industrial applications. Resonant coils must be carefully designed to achieve highest possible system performance by fully utilizing the available space. High quality factor and enhanced electromagnetic coupling are key indices which determine the system performance. In this paper, design parameter extraction and quality factor optimization of multi layered helical coils are presented using finite element analysis (FEA) simulations. In addition, a novel Toroidal Shaped Spiral (TSS) coil is proposed to increase power transfer range and misalignment tolerance. The proposed shapes and recommendations can be used to design high efficiency WPT resonator in a limited space.

Efficiency of parallelisation of genetic algorithms in the data analysis context

Most real-life data analysis problems are difficult to solve using exact methods, due to the size of the datasets and the nature of the underlying mechanisms of the system under investigation. As datasets grow even larger, finding the balance between the quality of the approximation and the computing time of the heuristic becomes non-trivial. One solution is to consider parallel methods, and to use the increased computational power to perform a deeper exploration of the solution space in a similar time. It is, however, difficult to estimate a priori whether parallelisation will provide the expected improvement. In this paper we consider a well-known method, genetic algorithms, and evaluate on two distinct problem types the behaviour of the classic and parallel implementations.

Prediction of GMA welding characteristic parameter by artificial neural network system

Nowadays, demand for automated Gas metal arc welding (GMAW) is growing and consequently need for intelligent systems is increased to ensure the accuracy of the procedure. To date, welding pool geometry has been the most used factor in quality assessment of intelligent welding systems. But, it has recently been found that Mahalanobis Distance (MD) not only can be used for this purpose but also is more efficient. In the present paper, Artificial Neural Networks (ANN) has been used for prediction of MD parameter. However, advantages and disadvantages of other methods have been discussed. The Levenberg–Marquardt algorithm was found to be the most effective algorithm for GMAW process. It is known that the number of neurons plays an important role in optimal network design. In this work, using trial and error method, it has been found that 30 is the optimal number of neurons. The model has been investigated with different number of layers in Multilayer Perceptron (MLP) architecture and has been shown that for the aim of this work the optimal result is obtained when using MLP with one layer. Robustness of the system has been evaluated by adding noise into the input data and studying the effect of the noise in prediction capability of the network. The experiments for this study were conducted in an automated GMAW setup that was integrated with data acquisition system and prepared in a laboratory for welding of steel plate with 12 mm in thickness. The accuracy of the network was evaluated by Root Mean Squared (RMS) error between the measured and the estimated values. The low error value (about 0.008) reflects the good accuracy of the model. Also the comparison of the predicted results by ANN and the test data set showed very good agreement that reveals the predictive power of the model. Therefore, the ANN model offered in here for GMA welding process can be used effectively for prediction goals.

Text mining for screening efficiency? Testing within a Cochrane public health review

Background The requirement for dual screening of titles and abstracts to select papers to examine in full text can create a huge workload, not least when the topic is complex and a broad search strategy is required, resulting in a large number of results. An automated system to reduce this burden, while still assuring high accuracy, has the potential to provide huge efficiency savings within the review process. Objectives To undertake a direct comparison of manual screening with a semi‐automated process (priority screening) using a machine classifier. The research is being carried out as part of the current update of a population‐level public health review. Methods Authors have hand selected studies for the review update, in duplicate, using the standard Cochrane Handbook methodology. A retrospective analysis, simulating a quasi‐‘active learning’ process (whereby a classifier is repeatedly trained based on ‘manually’ labelled data) will be completed, using different starting parameters. Tests will be carried out to see how far different training sets, and the size of the training set, affect the classification performance; i.e. what percentage of papers would need to be manually screened to locate 100% of those papers included as a result of the traditional manual method. Results From a search retrieval set of 9555 papers, authors excluded 9494 papers at title/abstract and 52 at full text, leaving 9 papers for inclusion in the review update. The ability of the machine classifier to reduce the percentage of papers that need to be manually screened to identify all the included studies, under different training conditions, will be reported. Conclusions The findings of this study will be presented along with an estimate of any efficiency gains for the author team if the screening process can be semi‐automated using text mining methodology, along with a discussion of the implications for text mining in screening papers within complex health reviews.

Effect of functionalized kaolinite on the curing kinetics of cycloaliphatic epoxy/anhydride system

Silane grafted kaolinite (KGS) was prepared through grinding kaolinite and then grafting with 3-aminopropyltriethoxysilane. The influence of KGS on the curing kinetics of cycloaliphatic epoxy resin was studied by non-isothermal differential scanning calorimetry at different heating rates. The reaction activation energy (Ea) was determined based on the Flynn–Wall–Ozawa method. The results of dynamic differential scanning calorimetry (DSC) kinetic analysis show that the surface hydroxyl groups of clay decreases the Ea from 70.6 kJ mol− 1 to 62.8 kJ mol− 1 and accelerates the curing reaction of the epoxy resin. The silane grafting reactions consume the surface hydroxyl groups of kaolinite and lead to a decrease in the catalytic efficiency of KGS in the curing of epoxy resin.

Proactive behavior-based safety management for construction safety improvement

Construction is one of the most hazardous industries due to its dynamic, temporary, and decentralized nature. The Hong Kong Commissioner for Labor identifies worker behavior as the root cause of construction accidents. Behavior-based safety (BBS) is one effective approach in managing employee safety issues. However, there is little research on the application of BBS in the construction industry. This research proposes an extension of the BBS approach, proactive behavior-based safety (PBBS), to improve construction safety. PBBS integrates the theory of BBS with the technology of Proactive Construction Management System (PCMS). The innovations of PBBS are: (1) automatically monitoring location-based behaviors; (2)quantitatively measuring safety performance; (3) investigating potential causes of unsafe behaviors; and (4) improving the efficiency of safety management. A pilot study of a Hong Kong construction site practicing PBBS was conducted. The experiment results showed that PBBS performed well on construction accident prevention and the Safety Index (SI) of the two project teams, with increased improvements by 36.07% and 44.70% respectively. It is concluded that PBBS is effective and adaptable to construction industry.

How does commuting behavior change due to incentives? An empirical study of the Beijing Subway System

This study examines the impact of incentives on commuters' travel behavior based upon a questionnaire survey conducted with respect to the Beijing Subway System. Overall, we find that offering incentives to commuters, particularly fast food restaurant-related services and reduced ticket fares, has a positive influence on avoiding the morning rush hour. Furthermore, by using an interaction analysis, we discover that a flexible work schedule has an impact on commuters' behavior and the efficiency of the subway system. Finally, we recommend two possible policies to maximize the utility of the subway system and to reduce congestion at the peak of morning service: (1) a set of incentives that includes free wireless internet service with a coupon for breakfast and a discount on ticket fares before the morning peak, and; (2) the introduction of a flexible work schedule.

Magnetic nanoparticles boosting the osmotic efficiency of a polymeric FO draw agent: Effect of polymer conformation

Poly sodium acrylate (PSA)-coated Magnetic Nanoparticles (PSA-MNPs) were synthesized as smart osmotic draw agent (SMDA) for water desalination by forward osmosis (FO) process. The PSA-coated MNPs demonstrated significantly higher osmotic pressure (~ 30 fold) as well as high FO water flux (~ 2–3 fold) when compared to their polymer (polyelectrolyte) counterpart, even at a very low concentration of ~ 0.13 wt.% in the draw solution. The PSA polymer chain conformation – coiled to extended – demonstrates a significant impact on the availability of the polymer hydrophilic groups in solution which is the driving force to attain higher osmotic pressure and water flux. When an optimum concentration of the polymer was anchored to a NP surface, the polymer chains assume an extended open conformation making the functional hydrophilic groups available to attract water molecules. This in turn boosts the osmotic pressure and FO water flux of the PSA-MNP draw agents. The low concentration of the PSA-MNP osmotic agent and the associated high water flux enhances the cost-effectiveness of our proposed SMDA system. In addition, easier magnetic separation and regeneration of the SMDA also improves its usability making it efficient, cost-effective and environment-friendly.

Consultation: Energy efficiency and engineering education

This report provides the Commonwealth Department of Resources, Energy and Tourism (RET) with a summary of consultation undertaken with representatives from industry and academia around Australia regarding mainstreaming energy efficiency within engineering education. Specifically, the report documents the purpose of the consultation process, key messages and emerging themes, industry-perceived gaps in energy efficiency related knowledge and skills, and academic considerations regarding graduate attributes and learning pathways to close these gaps. This information complements previous reports by presenting the current thoughts and ideas of more than 100 engineering academic and practising professionals who are actively involved in building capacity through the education system or implementing energy efficiency improvements in companies/the workplace. Furthermore, the report describes the emergence of a potential ‘community of practice’ in energy efficiency capacity building that arose during the project.

Effect of nitrification inhibitors (DMPP and 3MP+ TZ) on soil nitrous oxide emissions from a sub-tropical vegetable production system in Queensland, Australia

The use of nitrification inhibitors, in combination with ammonium based fertilisers, has been promoted recently as an effective method to reduce nitrous oxide (N2O) emissions from fertilised agricultural fields, whilst increasing yield and nitrogen use efficiency. Vegetable cropping systems are often characterised by high inputs of nitrogen fertiliser and consequently elevated emissions of nitrous oxide (N2O) can be expected. However, to date only limited data is available on the use of nitrification inhibitors in sub-tropical vegetable systems. A field experiment investigated the effect of the nitrification inhibitors (DMPP & 3MP+TZ) on N2O emissions and yield from a typical vegetable production system in sub-tropical Australia. Soil N2O fluxes were monitored continuously over an entire year with a fully automated system. Measurements were taken from three subplots for each treatment within a randomized complete blocks design. There was a significant inhibition effect of DMPP and 3MP+TZ on N2O emissions and soil mineral N content directly following the application of the fertiliser over the vegetable cropping phase. However this mitigation was offset by elevated N2O emissions from the inhibitor treatments over the post-harvest fallow period. Cumulative annual N2O emissions amounted to 1.22 kg-N/ha, 1.16 kg-N/ha, 1.50 kg-N/ha and 0.86 kg-N/ha in the conventional fertiliser (CONV), the DMPP treatment, the 3MP+TZ treatment and the zero fertiliser (0N) respectively. Corresponding fertiliser induced emission factors (EFs) were low with only 0.09 - 0.20% of the total applied fertiliser lost as N2O. There was no significant effect of the nitrification inhibitors on yield compared to the CONV treatment for the three vegetable crops (green beans, broccoli, lettuce) grown over the experimental period. This study highlights that N2O emissions from such vegetable cropping system are primarily controlled by post-harvest emissions following the incorporation of vegetable crop residues into the soil. It also shows that the use of nitrification inhibitors can lead to elevated N2O emissions by storing N in the soil profile that is available to soil microbes during the decomposition of the vegetable residues over the post-harvest phase. Hence the use of nitrification inhibitors in vegetable systems has to be treated carefully and fertiliser rates need to be adjusted to avoid excess soil nitrogen during the postharvest phase.

Reviewing in-vehicle systems to improve fuel efficiency and road safety

Road transport plays a significant role in various industries and mobility services around the globe and has a vital impact on our daily lives. However it also has serious impacts on both public health and the environment. In-vehicle feedback systems are a relatively new approach to encouraging driver behavior change for improving fuel efficiency and safety in automotive environments. While many studies claim that the adoption of eco-driving practices, such as eco-driving training programs and in-vehicle feedback to drivers, has the potential to improve fuel efficiency, limited research has integrated safety and eco-driving. Therefore, it is crucial to understand the human factors related theories and practices which will inform the design of an in-vehicle Human Machine Interface (HMI) that could provide real-time driver feedback and consequently improve both fuel efficiency and safety. This paper provides a comprehensive review of the current state of published literature on in-vehicle systems to identify and evaluate the impact of eco-driving and safety feedback systems. This paper also discusses how these factors may conflict with one another and have a negative effect on road safety, while also exploring possible eco-driving practices that could encourage more sustainable, environmentally-conscious and safe driving behavior. The review revealed a lack of comprehensive theoretical research integrating eco-driving and safe driving, and no current available HMI covering both aspects simultaneously. Furthermore, the review identified that some eco-driving in-vehicle systems may enhance fuel efficiency without compromising safety. The review has identified a range of concepts which can be developed to influence driver acceptance of safety and eco-driving systems within the area of HMI. This can promote new research aimed at enhancing our understanding of the relationship between eco-driving and safety from the human factors viewpoint. This provides a foundation for developing innovative, persuasive and acceptable in-vehicle HMI systems to improve fuel efficiency and road safety.

Collective land system in China: Congenital flaw or acquired irrational weakness?

With the level of urbanization in China now exceeding 50%, its collective rural land system is under increasing pressure, creating conditions in which there is increasing conflict between the efficient use of land for agricultural purposes and its retention as security for the rural population. This paper first examines the fundamental nature of China's collective land system by analyzing the collectivization history of China, then provides a comprehensive appraisal of the strengths and weaknesses of the collective land system's role in history and the challenges it faces in modern times. The main changes needed for the current collective system are identified as (1) the establishment of a new transfer mechanism for potential collective construction land, (2) the completion of land rights verification and consolidation work, and (3) the endowment of villagers with more rights to enjoy the distribution of land incremental value. The paper's main contribution is to question the relevance of collective rural land system in contemporary China, where a shift is now taking place from one of pure economic development to one involving more social concerns, and propose potential viable amendments to integrate the need for both perspectives.

How does complex adaptive system theory inform innovation in complex project based organisations?

Innovation enables organisations to endure by responding to emergence and to improve efficiency. Innovation in a complex organisation can be difficult due to complexities contributing to slow decision-making. Complex projects fail due to an inability to respond to emergence which consumes finances and impacts on resources and organisational success. Therefore, for complex organisations to improve on performance and resilience, it would be advantageous to understand how to improve the management of innovation and thus, the ability to respond to emergence. The benefits to managers are an increase in the number of successful projects and improved productivity. This study will explore innovation management in a complex project based organisation. The contribution to the academic literature will be an in-depth, qualitative exploration of innovation in a complex project based organisation using a comparative case study approach.

Integration and optimization of pressure retarded osmosis with reverse osmosis for power generation and high efficiency desalination

Salinity gradient power is proposed as a source of renewable energy when two solutions of different salinity are mixed. In particular, Pressure Retarded Osmosis (PRO) coupled with a Reverse Osmosis process (RO) has been previously suggested for power generation, using RO brine as the draw solution. However, integration of PRO with RO may have further value for increasing the extent of water recovery in a desalination process. Consequently, this study was designed to model the impact of various system parameters to better understand how to design and operate practical PRO-RO units. The impact of feed salinity and recovery rate for the RO process on the concentration of draw solution, feed pressure, and membrane area of the PRO process was evaluated. The PRO system was designed to operate at maximum power density of . Model results showed that the PRO power density generated intensified with increasing seawater salinity and RO recovery rate. For an RO process operating at 52% recovery rate and 35 g/L feed salinity, a maximum power density of 24 W/m2 was achieved using 4.5 M NaCl draw solution. When seawater salinity increased to 45 g/L and the RO recovery rate was 46%, the PRO power density increased to 28 W/m2 using 5 M NaCl draw solution. The PRO system was able to increase the recovery rate of the RO by up to 18% depending on seawater salinity and RO recovery rate. This result suggested a potential advantage of coupling PRO process with RO system to increase the recovery rate of the desalination process and reduce brine discharge.

Evaluation of polymeric nanomedicines targeted to PSMA: Effect of ligand on targeting efficiency

Targeted nanomedicines offer a strategy for greatly enhancing accumulation of a therapeutic within a specific tissue in animals. In this study, we report on the comparative targeting efficiency toward prostate-specific membrane antigen (PSMA) of a number of different ligands that are covalently attached by the same chemistry to a polymeric nanocarrier. The targeting ligands included a small molecule (glutamate urea), a peptide ligand, and a monoclonal antibody (J591). A hyperbranched polymer (HBP) was utilized as the nanocarrier and contained a fluorophore for tracking/analysis, whereas the pendant functional chain-ends provided a handle for ligand conjugation. Targeting efficiency of each ligand was assessed in vitro using flow cytometry and confocal microscopy to compare degree of binding and internalization of the HBPs by human prostate cancer (PCa) cell lines with different PSMA expression status (PC3-PIP (PSMA+) and PC3-FLU (PSMA−). The peptide ligand was further investigated in vivo, in which BALB/c nude mice bearing subcutaneous PC3-PIP and PC3-FLU PCa tumors were injected intravenously with the HBP-peptide conjugate and assessed by fluorescence imaging. Enhanced accumulation in the tumor tissue of PC3-PIP compared to PC3-FLU highlighted the applicability of this system as a future imaging and therapeutic delivery vehicle.