880 resultados para driving performance


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Traditional ceramic separation membranes, which are fabricated by applying colloidal suspensions of metal hydroxides to porous supports, tend to suffer from pinholes and cracks that seriously affect their quality. Other intrinsic problems for these membranes include dramatic losses of flux when the pore sizes are reduced to enhance selectivity and dead-end pores that make no contribution to filtration. In this work, we propose a new strategy for addressing these problems by constructing a hierarchically structured separation layer on a porous substrate using large titanate nanofibers and smaller boehmite nanofibers. The nanofibers are able to divide large voids into smaller ones without forming dead-end pores and with the minimum reduction of the total void volume. The separation layer of nanofibers has a porosity of over 70% of its volume, whereas the separation layer in conventional ceramic membranes has a porosity below 36% and inevitably includes dead-end pores that make no contribution to the flux. This radical change in membrane texture greatly enhances membrane performance. The resulting membranes were able to filter out 95.3% of 60-nm particles from a 0.01 wt % latex while maintaining a relatively high flux of between 800 and 1000 L/m2·h, under a low driving pressure (20 kPa). Such flow rates are orders of magnitude greater than those of conventional membranes with equal selectivity. Moreover, the flux was stable at approximately 800 L/m2·h with a selectivity of more than 95%, even after six repeated runs of filtration and calcination. Use of different supports, either porous glass or porous alumina, had no substantial effect on the performance of the membranes; thus, it is possible to construct the membranes from a variety of supports without compromising functionality. The Darcy equation satisfactorily describes the correlation between the filtration flux and the structural parameters of the new membranes. The assembly of nanofiber meshes to combine high flux with excellent selectivity is an exciting new direction in membrane fabrication.

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Using only legal sanctions to manage the speed at which people drive ignores the potential benefits of harnessing social factors such as the influence of others. Social influences on driver speeds were explored in this qualitative examination of 67 Australian drivers. Focus group interviews with 8 driver types (young, mid-age and older males and females, and self-identified Excessive and Rare speeders) were guided by Akers’ social learning theory (Akers, 1998). Findings revealed two types of influential others: people known to the driver (passengers and parents), and unknown other drivers. Passengers were generally described as having a slowing influence on drivers: responsibility for the safety of people in the car and consideration for passenger comfort were key themes. In contrast, all but the Rare speeders reported increasing their speed when driving alone. Parental role modelling was also described. In relation to other drivers, key themes included speeding to keep up with traffic flow and perceived pressure to drive faster. This ‘pressure’ from others to ‘speed up’ was expressed in all groups and reported strategies for managing this varied. Encouragingly, examples of actual or anticipated social rewards for speeding were less common than examples of social punishments. Three main themes relating to social punishments were embarrassment, breaching the trust of others, and presenting an image of a responsible driver. Impression management and self-presentation are discussed in light of these findings. Overall, our findings indicate scope to exploit the use of social sanctions for speeding and social praise for speed limit compliance to enhance speed management strategies.

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INTRODUCTION In their target article, Yuri Hanin and Muza Hanina outlined a novel multidisciplinary approach to performance optimisation for sport psychologists called the Identification-Control-Correction (ICC) programme. According to the authors, this empirically-verified, psycho-pedagogical strategy is designed to improve the quality of coaching and consistency of performance in highly skilled athletes and involves a number of steps including: (i) identifying and increasing self-awareness of ‘optimal’ and ‘non-optimal’ movement patterns for individual athletes; (ii) learning to deliberately control the process of task execution; and iii), correcting habitual and random errors and managing radical changes of movement patterns. Although no specific examples were provided, the ICC programme has apparently been successful in enhancing the performance of Olympic-level athletes. In this commentary, we address what we consider to be some important issues arising from the target article. We specifically focus attention on the contentious topic of optimization in neurobiological movement systems, the role of constraints in shaping emergent movement patterns and the functional role of movement variability in producing stable performance outcomes. In our view, the target article and, indeed, the proposed ICC programme, would benefit from a dynamical systems theoretical backdrop rather than the cognitive scientific approach that appears to be advocated. Although Hanin and Hanina made reference to, and attempted to integrate, constructs typically associated with dynamical systems theoretical accounts of motor control and learning (e.g., Bernstein’s problem, movement variability, etc.), these ideas required more detailed elaboration, which we provide in this commentary.

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Investment in residential property in Australia is not dominated by the major investment institutions in to the same degree as the commercial, industrial and retail property markets. As at December 2001, the Property Council of Australia Investment Performance Index contained residential property with a total value of $235 million, which represents only 0.3% of the total PCA Performance Index value. The majority of investment in the Australian residential property market is by small investment companies and individual investors. The limited exposure of residential property in the institutional investment portfolios has also limited the research that has been undertaken in relation to residential property performance. However the importance of individual investment in residential property is continuing to gain importance as both individuals are now taking control of their own superannuation portfolios and the various State Governments of Australia are decreasing their involvement in the construction of public housing by subsidizing low-income families into the private residential property market. This paper will: • Provide a comparison of the cost to initially purchase residential property in the various capital city residential property markets in Australia, and • Analyse the true cost and investment performance of residential property in the main residential property markets in Australia based on a standard investment portfolio in each of the State capital cities and relate these results to real estate marketing and agency practice.

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The importance of agriculture in many countries has tended to reduce as their economies move from a resource base to a manufacturing industry base. Although the level of agricultural production in first world countries has increased over the past two decades, this increase has generally been at a less significant rate compared to other sectors of the economies. Despite this increase in secondary and high technology industries, developed countries have continued to encourage and support their agricultural industries. This support has been through both tariffs and price support. Following pressure from developing economies, particularly through the World Trade Organisation (WTO), GATT Uruguay round and the Cairns Group Developed countries are now in various stages of winding back or de-coupling agricultural support within their economies. A major concern of farmers in protected agricultural markets is the impact of a free market trade in agricultural commodities on farm incomes and land values. This paper will analyse the capital and income performance of the NSW rural land market over the period 1990-1999. This analysis will be based on land use and will compare the total return from rural properties based on world agricultural commodity prices.

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Tested D. J. Kavanagh's (1983) depression model's explanation of response to cognitive-behavioral treatment among 19 20–60 yr old Ss who received treatment and 24 age-matched Ss who were assigned to a waiting list. Measures included the Beck Depression Inventory and self-efficacy (SE) and self-monitoring scales. Rises in SE and self-monitored performance of targeted skills were closely associated with the improved depression scores of treated Ss. Improvements in the depression of waiting list Ss occurred through random, uncontrolled events rather than via a systematic increase in specific skills targeted in treatment. SE regarding assertion also predicted depression scores over a 12-wk follow-up.

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Two experiments involving 87 undergraduates examined whether happiness produces increased performance on a physical task and tested whether self-efficacy mediated the results. When mood inductions covered the full range from happy to sad, mood influenced physical performance; however, evidence regarding self-efficacy was equivocal. Efficacy for the performed task was unaffected by mood, although it remained a good predictor of performance. Since mood altered efficacy for a nonperformed but more familiar task, inconsistent efficacy results could reflect task differences. Findings offer prospects for the use of mood inductions in practical sporting situations.

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PPPs are held to be a powerful way of mobilising private finance and resources to deliver public infrastructure. Theoretically, research into procurement has begun to acknowledge difficulties with the classification and assessment of different types of procurement, particularly those which do not sufficiently acknowledge variety within specific types of procurement methods. This paper advances a theoretical framework based on an evolutionary economic conceptualisation of a routine, which can accommodate the variety evident in procurement projects, in particular PPPs. The paper tests how the various elements of a PPP, as advanced in the theoretical framework, affect performance across 10 case studies. It concludes, that a limited number of elements of a PPP affect their performance, and provides strong evidence for the theoretical model advanced in this paper.

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When complex projects go wrong they can go horribly wrong with severe financial consequences. We are undertaking research to develop leading performance indicators for complex projects, metrics to provide early warning of potential difficulties. The assessment of success of complex projects can be made by a range of stakeholders over different time scales, against different levels of project results: the project’s outputs at the end of the project; the project’s outcomes in the months following project completion; and the project’s impact in the years following completion. We aim to identify leading performance indicators, which may include both success criteria and success factors, and which can be measured by the project team during project delivery to forecast success as assessed by key stakeholders in the days, months and years following the project. The hope is the leading performance indicators will act as alarm bells to show if a project is diverting from plan so early corrective action can be taken. It may be that different combinations of the leading performance indicators will be appropriate depending on the nature of project complexity. In this paper we develop a new model of project success, whereby success is assessed by different stakeholders over different time frames against different levels of project results. We then relate this to measurements that can be taken during project delivery. A methodology is described to evaluate the early parts of this model. Its implications and limitations are described. This paper describes work in progress.

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This review explores the question whether chemometrics methods enhance the performance of electroanalytical methods. Electroanalysis has long benefited from the well-established techniques such as potentiometric titrations, polarography and voltammetry, and the more novel ones such as electronic tongues and noses, which have enlarged the scope of applications. The electroanalytical methods have been improved with the application of chemometrics for simultaneous quantitative prediction of analytes or qualitative resolution of complex overlapping responses. Typical methods include partial least squares (PLS), artificial neural networks (ANNs), and multiple curve resolution methods (MCR-ALS, N-PLS and PARAFAC). This review aims to provide the practising analyst with a broad guide to electroanalytical applications supported by chemometrics. In this context, after a general consideration of the use of a number of electroanalytical techniques with the aid of chemometrics methods, several overviews follow with each one focusing on an important field of application such as food, pharmaceuticals, pesticides and the environment. The growth of chemometrics in conjunction with electronic tongue and nose sensors is highlighted, and this is followed by an overview of the use of chemometrics for the resolution of complicated profiles for qualitative identification of analytes, especially with the use of the MCR-ALS methodology. Finally, the performance of electroanalytical methods is compared with that of some spectrophotometric procedures on the basis of figures-of-merit. This showed that electroanalytical methods can perform as well as the spectrophotometric ones. PLS-1 appears to be the method of practical choice if the %relative prediction error of not, vert, similar±10% is acceptable.

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The molecular and metal profile fingerprints were obtained from a complex substance, Atractylis chinensis DC—a traditional Chinese medicine (TCM), with the use of the high performance liquid chromatography (HPLC) and inductively coupled plasma atomic emission spectroscopy (ICP-AES) techniques. This substance was used in this work as an example of a complex biological material, which has found application as a TCM. Such TCM samples are traditionally processed by the Bran, Cut, Fried and Swill methods, and were collected from five provinces in China. The data matrices obtained from the two types of analysis produced two principal component biplots, which showed that the HPLC fingerprint data were discriminated on the basis of the methods for processing the raw TCM, while the metal analysis grouped according to the geographical origin. When the two data matrices were combined into a one two-way matrix, the resulting biplot showed a clear separation on the basis of the HPLC fingerprints. Importantly, within each different grouping the objects separated according to their geographical origin, and they ranked approximately in the same order in each group. This result suggested that by using such an approach, it is possible to derive improved characterisation of the complex TCM materials on the basis of the two kinds of analytical data. In addition, two supervised pattern recognition methods, K-nearest neighbors (KNNs) method, and linear discriminant analysis (LDA), were successfully applied to the individual data matrices—thus, supporting the PCA approach.

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In December 2007, random roadside drug testing commenced in Queensland, Australia. Subsequently, the aim of this study was to explore the preliminary impact of Queensland’s drug driving legislation and enforcement techniques by applying Stafford and Warr’s [Stafford, M. C., & Warr, M. (1993). A reconceptualization of general and specific deterrence. Journal of Research in Crime and Delinquency, 30, 123-135] reconceptualization of deterrence theory. Completing a comprehensive drug driving questionnaire were 899 members of the public, university students, and individuals referred to a drug diversion program. Of note was that approximately a fifth of participants reported drug driving in the past six months. Additionally, the analysis indicated that punishment avoidance and vicarious punishment avoidance were predictors of the propensity to drug drive in the future. In contrast, there were indications that knowing of others apprehended for drug driving was not a sufficient deterrent. Sustained testing and publicity of the legislation and countermeasure appears needed to increase the deterrent impact for drug driving.

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The driving task requires sustained attention during prolonged periods, and can be performed in highly predictable or repetitive environments. Such conditions could create drowsiness or hypovigilance and impair the ability to react to critical events. Identifying vigilance decrement in monotonous conditions has been a major subject of research, but no research to date has attempted to predict this vigilance decrement. This pilot study aims to show that vigilance decrements due to monotonous tasks can be predicted through mathematical modelling. A short vigilance task sensitive to short periods of lapses of vigilance called Sustained Attention to Response Task is used to assess participants’ performance. This task models the driver’s ability to cope with unpredicted events by performing the expected action. A Hidden Markov Model (HMM) is proposed to predict participants’ hypovigilance. Driver’s vigilance evolution is modelled as a hidden state and is correlated to an observable variable: the participant’s reactions time. This experiment shows that the monotony of the task can lead to an important vigilance decline in less than five minutes. This impairment can be predicted four minutes in advance with an 86% accuracy using HMMs. This experiment showed that mathematical models such as HMM can efficiently predict hypovigilance through surrogate measures. The presented model could result in the development of an in-vehicle device that detects driver hypovigilance in advance and warn the driver accordingly, thus offering the potential to enhance road safety and prevent road crashes.

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This study explores whether the relation between internal audit quality and firm performance is associated with firm characteristics of information asymmetry and uncertainty (growth opportunities) and certain governance controls (audit committee effectiveness). The results from this preliminary study of 60 Malaysian companies show that the association between internal audit quality and firm performance is stronger for firms with high growth opportunities and that this positive association is weakened by increasing audit committee independence. These findings demonstrate the internal auditors conflicting roles and question the governance recommendations that require all members of the audit committee to be non-executive directors.

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Purpose – The purpose of this paper is to examine the use of bid information, including both price and non-price factors in predicting the bidder’s performance. Design/methodology/approach – The practice of the industry was first reviewed. Data on bid evaluation and performance records of the successful bids were then obtained from the Hong Kong Housing Department, the largest housing provider in Hong Kong. This was followed by the development of a radial basis function (RBF) neural network based performance prediction model. Findings – It is found that public clients are more conscientious and include non-price factors in their bid evaluation equations. With the input variables used the information is available at the time of the bid and the output variable is the project performance score recorded during work in progress achieved by the successful bidder. It was found that past project performance score is the most sensitive input variable in predicting future performance. Research limitations/implications – The paper shows the inadequacy of using price alone for bid award criterion. The need for a systemic performance evaluation is also highlighted, as this information is highly instrumental for subsequent bid evaluations. The caveat for this study is that the prediction model was developed based on data obtained from one single source. Originality/value – The value of the paper is in the use of an RBF neural network as the prediction tool because it can model non-linear function. This capability avoids tedious ‘‘trial and error’’ in deciding the number of hidden layers to be used in the network model. Keywords Hong Kong, Construction industry, Neural nets, Modelling, Bid offer spreads Paper type Research paper