678 resultados para fsae formula student unibo motorsport ecu single board rio controller lambda labview


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PURPOSE: This pilot project’s aim was to trial a tool and process for developing students’ ability to engage in self-assessment using reflection on their clinical experiences, including feedback from workplace learning, in order to aid them in linking theory to practice and develop strategies to improve performance. BACKGROUND: In nursing education, students can experience a mismatch in performance compared to theoretical learning, this is referred to as the ‘theory practice gap’ (Scully 2011, Chan Chan & Liu 2011). One specific contributing factor seems to be students’ inability to engage in meaningful reflection and self-correcting behaviours. A self-assessment strategy was implemented within a third year clinical unit to ameliorate this mismatch with encouraging results, as students developed self-direction in addressing learning needs. In this pilot project the above strategy was adapted for implementation between different clinical units, to create a whole of course approach to integrating workplace learning. METHOD: The methodology underpinning this project is a scaffolded, supported reflective practice process. Improved self-assessment skills is achieved by students reflecting on and engaging with feedback, then mapping this to learning outcomes to identify where performance can be improved. Evaluation of this project includes: collation of student feedback identifying successful strategies along with barriers encountered in implementation; feedback from students and teachers via above processes and tools; and comparison of the number of learning contracts issued in clinical nursing units with similar cohorts. RESULTS: Results will be complete by May 2012 and include analysis of the data collected via the above evaluation methods. Other outcomes will include the refined process and tool, plus resources that should improve cost effectiveness without reducing student support. CONCLUSION: Implementing these tools and processes over the entire student’s learning package, will assist them to demonstrate progressive development through the course. Students will have learnt to understand feedback and integrate these skills for life-long learning.

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Background: The 30-item USDI is a self-report measure that assesses depressive symptoms among university students. It consists of three correlated three factors: Lethargy, Cognitive-Emotional and Academic motivation. The current research used confirmatory factor analysis to asses construct validity and determine whether the original factor structure would be replicated in a different sample. Psychometric properties were also examined. Method: Participants were 1148 students (mean age 22.84 years, SD = 6.85) across all faculties from a large Australian metropolitan university. Students completed a questionnaire comprising of the USDI, the Depression Anxiety Stress Scale (DASS) and Life Satisfaction Scale (LSS). Results: The three correlated factor model was shown to be an acceptable fit to the data, indicating sound construct validity. Internal consistency of the scale was also demonstrated to be sound, with high Cronbach Alpha values. Temporal stability of the scale was also shown to be strong through test-retest analysis. Finally, concurrent and discriminant validity was examined with correlations between the USDI and DASS subscales as well as the LSS, with sound results contributing to further support the construct validity of the scale. Cut-off points were also developed to aid total score interpretation. Limitations: Response rates are unclear. In addition, the representativeness of the sample could be improved potentially through targeted recruitment (i.e. reviewing the online sample statistics during data collection, examining the representativeness trends and addressing particular faculties within the university that were underrepresented). Conclusions: The USDI provides a valid and reliable method of assessing depressive symptoms found among university students.

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In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.

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Multilevel converters, because of the benefits they attract in generating high quality output voltage, are used in several applications. Various modulation and control techniques are introduced by several researchers to control the output voltage of the multilevel converters like space vector modulation and harmonic elimination (HE) methods. Multilevel converters may have a DC link with equal or unequal DC voltages. In this study a new HE technique based on the HE method is proposed for multilevel converters with unequal DC link voltage. The DC link voltage levels are considered as additional variables for the HE method and the voltage levels are defined based on the HE results. Increasing the number of voltage levels can reduce lower order harmonic content because of the fact that more variables are created. In comparison to previous methods, this new technique has a positive effect on the output voltage quality by reducing its total harmonic distortion, which must take into consideration for some applications such as uninterruptable power supply, motor drive systems and piezoelectric transducer excitation. In order to verify the proposed modulation technique, MATLAB simulations and experimental tests are carried out for a single-phase four-level diode-clamped converter.

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This paper proposes a framework to analyse performance on multiple choice questions with the focus on linguistic factors. Item Response Theory (IRT) is deployed to estimate ability and question difficulty levels. A logistic regression model is used to detect Differential Item Functioning questions. Probit models testify relationships between performance and linguistic factors controlling the effects of question construction and students’ background. Empirical results have important implications. The lexical density of stems affects performance. The use of non-Economics specialised vocabulary has differing impacts on the performance of students with different language backgrounds. The IRT-based ability and difficulty help explain performance variations.

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The actin microfilament plays a critical role in many cellular processes including embryonic development, wound healing, immune response, and tissue development. It is commonly organized in the form of networks whose mechanical properties change with changes in their architecture due to cell evolution processes. This paper presents a new nonlinear continuum mechanics model of single filamentous actin (F-actin) that is based on nanoscale molecular simulations. Following this continuum model of the single F-actin, mechanical properties of differently architected lamellipodia are studied. The results provide insight that can contribute to the understanding of the cell edge motions of living cells.

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Driven by the rapid development of ubiquitous and pervasive computing, personalized services and applications are deployed to support our lives. Accordingly, the number of interfaces and devices (smartphone, tablet computer, etc.) provided to access and consume these services is growing continuously. To simplify the complexity of managing many accounts with different credentials, Single Sign-On (SSO) solutions have been introduced. However, a single password for many accounts represents a single-point-of-failure. Furthermore, once initiated SSO session is a high potential risk when the working station is left unlocked and unattended. In this paper, we present a conception of a Persistent Single Sign-On (PSSO) for ubiquitous home environments by involving the capabilities of Behavioral Biometrics to check the identity of the user continuously in an unobtrusive manner.

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Because professions seek graduates who can 'collaborate, share skills and knowledge, and communicate' (Kruck and Reif, 2001, p 37), it is important that university graduates are not equipped solely with the content knowledge of their discipline, but also with prospective employment skills. Furthermore, when students 'interact more in positive ways with their teachers and peers, they gain more in terms of essential skills and competencies, such as critical thinking, problem~solving [and] effective communication' (NSSE, 2000, p 2)./n this way, peer assisted fellowing has the potential to enhance students' professional development, and provide the social inclusion and engagement necessary for effective learning. This session describes two peer assisted learning models embedded within first year QUT Faculty of Law units. Through a partnership between teaching staff, student mentors and mentees, the models aim to facilitate student socialisation whilst supplementing understanding of substantive law with the development of academic and work·related skills. Mentor and mentee perceptions, and program implications, are considered.

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The disparity that exists between the highest and lowest achievers together with deficit approaches to teaching, learning and assessment raise serious equity issues related to fairness, validity, culture and access, which were analysed in a recent Australian Research Council funded project. This chapter explores the potential that exists for teachers to work with Indigenous Teacher Assistants (ITAs) to secure cultural connectedness in teaching, learning and assessment of Indigenous students. The study was a design experiment, which was conducted in seven Catholic and Independent primary schools in northern Queensland and involved semi-structured focus group interviews with Year 4 and 6 Indigenous students, principals, teachers and Indigenous Teacher Assistants. Classroom observations and document analyses were also conducted. This corpus of data was analysed using a sociocultural theoretical lens. The use of a sociocultural analysis helped to identify cultural influences, Indigenous students’ funds of knowledge and values. The information from this analysis was made explicit to teachers to demonstrate how they could enhance their pedagogic and assessment practices by embracing and extending the cultural spaces for learning and teaching of Indigenous students. The way in which teachers construct their interactions for greater cultural connectedness and enhanced learning would appear to rely on relationship building with Indigenous staff, Indigenous students’ cultural knowledge, and improved understanding of assessment and related equity issues.

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ICT integration has been advocated to provide opportunities to improve students’ achievement and engagement through transforming the educational setting. A valuable tool that contributes in enhancing and developing students’ cognitive skills for lifelong learning, ICT integration has introduced a new educational philosophy, shifting the role of students into a more central position in the pedagogical processes. Kuwait, as with many other countries, has recently planned ICT integration to develop its citizen’s capacities. This study sought to capture the principals’, teachers’, and students’ perceptions of ICT integration in pedagogical activities, as well as how ICT is being used for learning and teaching activities in three ICT leading Kuwaiti secondary schools. Interviews with principals, teachers, and students were conducted, along with an open-ended questionnaire for the teachers, researcher observations, and document analysis. The findings revealed that ICT integration in Kuwait needed to be reinforced to accomplish the ICT integration objectives. A call for further support for teachers, and a reconsideration of the ICT integration strategies were also recommended.

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We demonstrated for the first time by ab initio density functional calculation and molecular dynamics simulation that C0.5(BN)0.5 armchair single-walled nanotubes (NT) are gapless semiconductors and can be spontaneously formed via the hybrid connection of graphene/BN Nanoribbons (GNR/BNNR) at room temperature. The direct synthesis of armchair C0.5(BN)0.5 via the hybrid connection of GNR/BNNR is predicted to be both thermodynamically and dynamically stable. Such novel armchair C0.5(BN)0.5 NTs possess enhanced conductance as that observed in GNRs. Additionally, the zigzag C0.5(BN)0.5 SWNTs are narrow band gap semiconductors, which may have potential application for light emission. In light of recent experimental progress and the enhanced degree of control in the synthesis of GNRs and BNNR, our results highlight an interesting avenue for synthesizing a novel specific type of C0.5(BN)0.5 nanotube (gapless or narrow direct gap semiconductor), with potentially important applications in BNC-based nanodevices.

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The interaction of bare graphene nanoribbons (GNRs) was investigated by ab initio density functional theory calculations with both the local density approximation (LDA) and the generalized gradient approximation (GGA). Remarkably, two bare 8-GNRs with zigzag-shaped edges are predicted to form an (8, 8) armchair single-wall carbon nanotube (SWCNT) without any obvious activation barrier. The formation of a (10, 0) zigzag SWCNT from two bare 10-GNRs with armchair-shaped edges has activation barriers of 0.23 and 0.61 eV for using the LDA and the revised PBE exchange correlation functional, respectively, Our results suggest a possible route to control the growth of specific types SWCNT via the interaction of GNRs.

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The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

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The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.