Acoustic emission activity from the two main types of small multi-cylinder diesel engine fuel injection systems

Effective fuel injector operation and efficient combustion are two of the most critical aspects when Diesel engine performance, efficiency and reliability are considered. Indeed, it is widely acknowledged that fuel injection equipment faults lead to increased fuel consumption, reduced power, greater levels of exhaust emissions and even unexpected engine failure. Previous investigations have identified fuel injector related acoustic emission activity as being caused by mechanisms such as fuel line pressure build-up; fuel flow through injector nozzles, injector needle opening and closing impacts and premixed combustion related pulses. Few of these investigations however, have attempted to categorise the close association and interrelation that exists between fuel injection equipment function and the acoustic emission generating mechanisms. Consequently, a significant amount of ambiguity remains in the interpretation and categorisation of injector related AE activity with respect to the functional characteristics of specific fuel injection equipment. The investigation presented addresses this ambiguity by detailing a study in which AE signals were recorded and analysed from two different Diesel engines employing the two commonly encountered yet fundamentally different types of fuel injection equipment. Results from tests in which faults were induced into fuel injector nozzles from both indirect-injection and direct-injection engines show that functional differences between the main types of fuel injection equipment results in acoustic emission activity which can be specifically related to the type of fuel injection equipment used.

Technoeconomic analysis of an integrated microalgae photobioreactor, biodiesel and biogas production facility

As fossil fuel prices increase and environmental concerns gain prominence, the development of alternative fuels from biomass has become more important. Biodiesel produced from microalgae is becoming an attractive alternative to share the role of petroleum. Currently it appears that the production of microalgal biodiesel is not economically viable in current environment because it costs more than conventional fuels. Therefore, a new concept is introduced in this article as an option to reduce the total production cost of microalgal biodiesel. The integration of biodiesel production system with methane production via anaerobic digestion is proved in improving the economics and sustainability of overall biodiesel stages. Anaerobic digestion of microalgae produces methane and further be converted to generate electricity. The generated electricity can surrogate the consumption of energy that require in microalgal cultivation, dewatering, extraction and transesterification process. From theoretical calculations, the electricity generated from methane is able to power all of the biodiesel production stages and will substantially reduce the cost of biodiesel production (33% reduction). The carbon emissions of biodiesel production systems are also reduced by approximately 75% when utilizing biogas electricity compared to when the electricity is otherwise purchased from the Victorian grid. The overall findings from this study indicate that the approach of digesting microalgal waste to produce biogas will make the production of biodiesel from algae more viable by reducing the overall cost of production per unit of biodiesel and hence enable biodiesel to be more competitive with existing fuels.

Developing people capabilities for the promotion of sustainability in facility management practices

This thesis investigates the potential people capability factors that can influence the implementation of sustainability agenda in facility management practices. Twenty three critical factors were identified and separated into four categories of strategic, anticipatory, interpersonal and system thinking capabilities. An Interpretive structural model was then developed to explore the interrelationship and priority of each critical factor. A set of guidelines for action and potential effects of each people capability factor were presented for the industry to promote sustainability endeavour in facility management practices.

Combustion enhancement in a scramjet engine using oxygen enrichment and porous fuel injection

This paper reports on the experimental testing of oxygen-enriched porous fuel injection in a scramjet engine. Fuel was injected via inlet mounted, oxide-based ceramic matrix composite (CMC) injectors on both flow path surfaces that covered a total of 9.2 % of the intake surface area. All experiments were performed at an enthalpy of 3.93−4.25±3.2% MJ kg−1, flight Mach number 9.2–9.6 and an equivalence ratio of 0.493±3%. At this condition, the engine was shown to be on the verge of achieving appreciable combustion. Oxygen was then added to the fuel prior to injection such that two distinct enrichment levels were achieved. Combustion was found to increase, by as much as 40 % in terms of combustion-induced pressure rise, over the fuel-only case with increasing oxygen enrichment. Further, the onset of combustion was found to move upstream with increasing levels of oxygen enrichment. Thrust, both uninstalled and specific, and specific impulse were found to be improved with oxygen enrichment. Enhanced fuel–air mixing due to the pre-mixing of oxygen with the fuel together with the porous fuel injection are believed to be the main contributors to the observed enhanced performance of the tested engine.

Supervised latent dirichlet allocation models for efficient activity representation

Local spatio-temporal features with a Bag-of-visual words model is a popular approach used in human action recognition. Bag-of-features methods suffer from several challenges such as extracting appropriate appearance and motion features from videos, converting extracted features appropriate for classification and designing a suitable classification framework. In this paper we address the problem of efficiently representing the extracted features for classification to improve the overall performance. We introduce two generative supervised topic models, maximum entropy discrimination LDA (MedLDA) and class- specific simplex LDA (css-LDA), to encode the raw features suitable for discriminative SVM based classification. Unsupervised LDA models disconnect topic discovery from the classification task, hence yield poor results compared to the baseline Bag-of-words framework. On the other hand supervised LDA techniques learn the topic structure by considering the class labels and improve the recognition accuracy significantly. MedLDA maximizes likelihood and within class margins using max-margin techniques and yields a sparse highly discriminative topic structure; while in css-LDA separate class specific topics are learned instead of common set of topics across the entire dataset. In our representation first topics are learned and then each video is represented as a topic proportion vector, i.e. it can be comparable to a histogram of topics. Finally SVM classification is done on the learned topic proportion vector. We demonstrate the efficiency of the above two representation techniques through the experiments carried out in two popular datasets. Experimental results demonstrate significantly improved performance compared to the baseline Bag-of-features framework which uses kmeans to construct histogram of words from the feature vectors.

Mental health facility design: The case for person-centred care

There is a schism between a growing chorus for person-centred models of care and the prevalent paradigms for the design of mental health facilities. This argument proposes that architectural solutions have traditionally been geared around staff-centred concerns like ease of patient management. It suggests that the demands for person-centred models of care are important because evidence suggests that the physical environment is a causal factor in mental illness, and that even minor concessions towards person-centred models of care consistently exert a disproportionate and sustained positive influence on the behaviour of mental health patients. While the traditional mental health unit layout is unsatisfactory for person-centred care and effective recovery, other approaches that have been well tested and found to be effective is described along with a statement about subtle details that will improve facilities for all users.

"It broke our hearts": Understanding parents' lived experiences of their child's admission to an acute mental health care facility

This article reports the evaluative findings of an Early Psychosis Education Program (EPEP) designed to support parents caring for their child who was recently admitted to the psychiatric intensive care unit of an inpatient mental health care facility in Australia. The EPEP offered education on mental illness, treatment options, and medication, as well as information on the recovery model of care. The EPEP was facilitated by two RNs and was evaluated for educational effectiveness using a simple pre- and postevaluation questionnaire. The evaluation revealed two themes expressed by parents: "We didn't see it coming," and "Hopelessness and helplessness." The themes highlighted the parents' lack of mental health care knowledge prior to the EPEP, which had a significant impact on the parents' experiences and well-being. The evaluative findings highlighted a need for a nurse-led EPEP within the community. A community EPEP has the potential to strengthen the partnership between parents, families, and mental health service providers and to help with the provision of a recovery framework of care.

Challenges and opportunities in using wastewater analysis to measure drug use in a small prison facility

Introduction and Aims Wastewater analysis (WWA) is intended to be a direct and objective method of measuring substance use in large urban populations. It has also been used to measure prison substance use in two previous studies. The application of WWA in this context has raised questions as to how best it might be used to measure illicit drug use in prisons, and whether it can also be used to measure prescription misuse. We applied WWA to a small regional prison to measure the use of 12 licit and illicit substances. We attempted to measure the non-medical use of methadone and buprenorphine and to compare our findings with the results of the prison's mandatory drug testing (MDT). Design and Methods Representative daily composite samples were collected for two periods of 12 consecutive days in May to July 2013 and analysed for 18 drug metabolites. Prescription data and MDT results were obtained from the prison and compared with the substance use estimates calculated from WWA data. Results Daily use of methamphetamine, methadone, buprenorphine and codeine was detected, while sporadic detection of ketamine and methylone was also observed. Overall buprenorphine misuse appeared to be greater than methadone misuse. Discussion and Conclusions Compared with MDT, WWA provides a more comprehensive picture of prison substance use. WWA also has the potential to measure the misuse of medically prescribed substances. However, a great deal of care must be exercised in quantifying the usage of any substance in small populations, such as in prisons.

Borrowing from the geeks: What can healthcare facility design learn from IT?

People get into healthcare because they want to help society. And when a new hospital is briefed, everyone tries to do their best, but the process is mired by the impossibility of the task. Stakeholders rarely understand the architectural process, nobody can predict the future, and the only thing for certain is that everything will change as the project unfolds, revealing errors in initial assumptions and calculations, shifts in needs, new technologies etc. Yet there’s always pressure to keep to the programme and to press on regardless. This chaos leads eventually to suboptimal results: hospitals the world over are riddled with inefficiencies, idiosyncrasies, incredible wastage and features that lead to poor clinical outcomes. This talk will sketch out the basics of Scrum, the most popular open-source Lean/Agile methodology. It will discuss what healthcare designers can learn from the geeks in Silicon Valley reduce risk, meet deadlines and deliver the highest possible value for the budget despite the uncertainty.

Semi-supervised document clustering via loci

Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

Detecting rare events using Kullback-Leibler divergence: A weakly supervised approach

Video surveillance infrastructure has been widely installed in public places for security purposes. However, live video feeds are typically monitored by human staff, making the detection of important events as they occur difficult. As such, an expert system that can automatically detect events of interest in surveillance footage is highly desirable. Although a number of approaches have been proposed, they have significant limitations: supervised approaches, which can detect a specific event, ideally require a large number of samples with the event spatially and temporally localised; while unsupervised approaches, which do not require this demanding annotation, can only detect whether an event is abnormal and not specific event types. To overcome these problems, we formulate a weakly-supervised approach using Kullback-Leibler (KL) divergence to detect rare events. The proposed approach leverages the sparse nature of the target events to its advantage, and we show that this data imbalance guarantees the existence of a decision boundary to separate samples that contain the target event from those that do not. This trait, combined with the coarse annotation used by weakly supervised learning (that only indicates approximately when an event occurs), greatly reduces the annotation burden while retaining the ability to detect specific events. Furthermore, the proposed classifier requires only a decision threshold, simplifying its use compared to other weakly supervised approaches. We show that the proposed approach outperforms state-of-the-art methods on a popular real-world traffic surveillance dataset, while preserving real time performance.

Flow field and traverse times for fan forced injection of fumigant via circular or annular inlet into stored grain

Fan forced injection of phosphine gas fumigant into stored grain is a common method to treat infestation by insects. For low injection velocities the transport of fumigant can be modelled as Darcy flow in a porous medium where the gas pressure satisfies Laplace's equation. Using this approach, a closed form series solution is derived for the pressure, velocity and streamlines in a cylindrically stored grain bed with either a circular or annular inlet, from which traverse times are numerically computed. A leading order closed form expression for the traverse time is also obtained and found to be reasonable for inlet configurations close to the central axis of the grain storage. Results are interpreted for the case of a representative 6m high farm wheat store, where the time to advect the phosphine to almost the entire grain bed is found to be approximately one hour.

12-weeks supervised exercise training is a feasible and efficacious treatment for reducing depression in youth with major depressive disorder

Introduction: Major Depressive Disorder (MDD) has high prevalence among adolescents and young adults. Evidence of any effective treatments is limited. Exercise as an effective treatment for adults has some support but studies in younger populations are lacking. Therefore the aim of this study was to investigate the feasibility and preliminary efficacy of brief motivational interviewing (MI) plus 12-weeks exercise training as a treatment for MDD in youth...