942 resultados para real-effort task


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We address the problem of the rangefinder-based avoidance of unforeseen static obstacles during a visual navigation task. We extend previous strategies which are efficient in most cases but remain still hampered by some drawbacks (e.g., risks of collisions or of local minima in some particular cases, etc.). The key idea is to complete the control strategy by adding a controller providing the robot some anticipative skills to guarantee non collision and by defining more general transition conditions to deal with local minima. Simulation results show the proposed strategy efficiency.

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This paper presents the development and experimental validation of a prototype system for online estimation and compensation of wind disturbances onboard small Rotorcraft unmanned aerial systems (RUAS). The proposed approach consists of integrating a small pitot-static system onboard the vehicle and using simple but effective algorithms for estimating the wind speed in real time. The baseline flight controller has been augmented with a feed-forward term to compensate for these wind disturbances, thereby improving the flight performance of small RUAS in windy conditions. The paper also investigates the use of online airspeed measurements in a closed-loop for controlling the RUAS forward motion without the aid of a global positioning system (GPS). The results of more than 80 flights with a RUAS confirm the validity of our approach.

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Changes at work are often accompanied with the threat of, or actual, resource loss. Through an experiment, we investigated the detrimental effect of the threat of resource loss on adaptive task performance. Self-regulation (i.e., task focus and emotion control) was hypothesized to buffer the negative relationship between the threat of resource loss and adaptive task performance. Adaptation was conceptualized as relearning after a change in task execution rules. Threat of resource loss was manipulated for 100 participants undertaking an air traffic control task. Using discontinuous growth curve modeling, 2 kinds of adaptation—transition adaptation and reacquisition adaptation—were differentiated. The results showed that individuals who experienced the threat of resource loss had a stronger drop in performance (less transition adaptation) and a subsequent slower recovery (less reacquisition adaptation) compared with the control group who experienced no threat. Emotion control (but not task focus) moderated the relationship between the threat of resource loss and transition adaptation. In this respect, individuals who felt threatened but regulated their emotions performed better immediately after the task change (but not later on) compared with those individuals who felt threatened and did not regulate their emotions as well. However, later on, relearning (reacquisition adaptation) under the threat of resource loss was facilitated when individuals concentrated on the task at hand.

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Educating responsive graduates. Graduate competencies include reliability, communication skills and ability to work in teams. Students using Collaborative technologies adapt to a new working environment, working in teams and using collaborative technologies for learning. Collaborative Technologies were used not simply for delivery of learning but innovatively to supplement and enrich research-based learning, providing a space for active engagement and interaction with resources and team. This promotes the development of responsive ‘intellectual producers’, able to effectively communicate, collaborate and negotiate in complex work environments. Exploiting technologies. Students use ‘new’ technologies to work collaboratively, allowing them to experience the reality of distributed workplaces incorporating both flexibility and ‘real’ time responsiveness. Students are responsible and accountable for individual and group work contributions in a highly transparent and readily accessible workspace. This experience provides a model of an effective learning tool. Navigating uncertainty and complexity. Collaborative technologies allows students to develop critical thinking and reflective skills as they develop a group product. In this forum students build resilience by taking ownership and managing group work, and navigating the uncertainties and complexities of group dynamics as they constructively and professionally engage in team dialogue and learn to focus on the goal of the team task.

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Early Childhood Education (ECE) has a long history of building foundations for children to achieve their full potential, enabling parents to participate in the economy while children are cared for, addressing poverty and disadvantage, and building individual, community and societal resources. In so doing, ECE has developed a set of cultural practices and ways of knowing that shape the field and the people who work within it. ECE, consequently, is frequently described as unique and special (Moss, 2006; Penn, 2011). This works to define and distinguish the field while, simultaneously, insulating it from other contexts, professions, and ideas. Recognising this dualism illuminates some of the risks and challenges of operating in an insular and isolated fashion. In the 21st century, there are new challenges for children, families and societies to which ECE must respond if it is to continue to be relevant. One major issue is how ECE contributes to transition towards more sustainable ways of living. Addressing this contemporary social problem is one from which Early Childhood teacher education has been largely absent (Davis & Elliott, 2014), despite the well recognised but often ignored role of education in contributing to sustainability. Because of its complexity, sustainability is sometimes referred to as a ‘wicked problem’ (Rittel & Webber, 1973; Australian Public Service Commission, 2007) requiring alternatives to ‘business as usual’ problem solving approaches. In this chapter, we propose that addressing such problems alongside disciplines other than Education enables the Early Childhood profession to have its eyes opened to new ways of thinking about our work, potentially liberating us from the limitations of our “unique” and idiosyncratic professional cultures. In our chapter, we focus on understandings of culture and diversity, looking to broaden these by exploring the different ‘cultures’ of the specialist fields of ECE and Design (in this project, we worked with students studying Architecture, Industrial Design, Landscape Architecture and Interior Design). We define culture not as it is typically represented, i.e. in relation to ideas and customs of particular ethnic and language groups, but to the ideas and practices of people working in different disciplines and professions. We assert that different specialisms have their own ‘cultural’ practices. Further, we propose that this kind of theoretical work helps us to reconsider ways in which ECE might be reframed and broadened to meet new challenges such as sustainability and as yet unknown future challenges and possibilities. We explore these matters by turning to preservice Early Childhood teacher education (in Australia) as a context in which traditional views of culture and diversity might be reconstructed. We are looking to push our specialist knowledge boundaries and to extend both preservice teachers and academics beyond their comfort zones by engaging in innovative interdisciplinary learning and teaching. We describe a case study of preservice Early Childhood teachers and designers working in collaborative teams, intersecting with a ‘real-world’ business partner. The joint learning task was the design of an early learning centre based on sustainable design principles and in which early Education for Sustainability (EfS) would be embedded Data were collected via focus group and individual interviews with students in ECE and Design. Our findings suggest that interdisciplinary teaching and learning holds considerable potential in dismantling taken-for-granted cultural practices, such that professional roles and identities might be reimagined and reconfigured. We conclude the chapter with provocations challenging the ways in which culture and diversity in the field of ECE might be reconsidered within teacher education.

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This thesis has investigated how to cluster a large number of faces within a multi-media corpus in the presence of large session variation. Quality metrics are used to select the best faces to represent a sequence of faces; and session variation modelling improves clustering performance in the presence of wide variations across videos. Findings from this thesis contribute to improving the performance of both face verification systems and the fully automated clustering of faces from a large video corpus.

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Recently, efficient scheduling algorithms based on Lagrangian relaxation have been proposed for scheduling parallel machine systems and job shops. In this article, we develop real-world extensions to these scheduling methods. In the first part of the paper, we consider the problem of scheduling single operation jobs on parallel identical machines and extend the methodology to handle multiple classes of jobs, taking into account setup times and setup costs, The proposed methodology uses Lagrangian relaxation and simulated annealing in a hybrid framework, In the second part of the paper, we consider a Lagrangian relaxation based method for scheduling job shops and extend it to obtain a scheduling methodology for a real-world flexible manufacturing system with centralized material handling.

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The new furnace at the Materials Characterization by X-ray Diffraction beamline at Elettra has been designed for powder diffraction measurements at high temperature (up to 1373 K at the present state). Around the measurement region the geometry of the radiative heating element assures a negligible temperature gradient along the capillary and can accommodate either powder samples in capillary or small flat samples. A double capillary holder allows flow-through of gas in the inner sample capillary while the outer one serves as the reaction chamber. The furnace is coupled to a translating curved imaging-plate detector, allowing the collection of diffraction patterns up to 2[theta] [asymptotically equal to] 130°.

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Consumer electronics increasingly find their way into cars and are often portrayed as unwanted distractions. As part of our endeavour to capitalise on these technologies as safety tools rather than safety threats, we suggest to use smartphones, head-up displays, vehicle interfaces, and other digital gadgets: a) as readily available and lightweight sensing devices, and b) as platforms for engaging interventions that provide safe stimuli in real- time while driving. In our effort to make safe driving behaviours more fun, we explore ways to apply gamification to driving. In this paper, we illustrate the need for a careful balance between fun and safety and reveal ethical issues that arise when introducing new technology interventions into this complex and safety- critical design space.

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With the introduction of the PCEHR (Personally Controlled Electronic Health Record), the Australian public is being asked to accept greater responsibility for the management of their health information. However, the implementation of the PCEHR has occasioned poor adoption rates underscored by criticism from stakeholders with concerns about transparency, accountability, privacy, confidentiality, governance, and limited capabilities. This study adopts an ethnographic lens to observe how information is created and used during the patient journey and the social factors impacting on the adoption of the PCEHR at the micro-level in order to develop a conceptual model that will encourage the sharing of patient information within the cycle of care. Objective: This study aims to firstly, establish a basic understanding of healthcare professional attitudes toward a national platform for sharing patient summary information in the form of a PCEHR. Secondly, the studies aims to map the flow of patient related information as it traverses a patient’s personal cycle of care. Thus, an ethnographic approach was used to bring a “real world” lens to information flow in a series of case studies in the Australian healthcare system to discover themes and issues that are important from the patient’s perspective. Design: Qualitative study utilising ethnographic case studies. Setting: Case studies were conducted at primary and allied healthcare professionals located in Brisbane Queensland between October 2013 and July 2014. Results: In the first dimension, it was identified that healthcare professionals’ concerns about trust and medico-legal issues related to patient control and information quality, and the lack of clinical value available with the PCEHR emerged as significant barriers to use. The second dimension of the study which attempted to map patient information flow identified information quality issues, clinical workflow inefficiencies and interoperability misconceptions resulting in duplication of effort, unnecessary manual processes, data quality and integrity issues and an over reliance on the understanding and communication skills of the patient. Conclusion: Opportunities for process efficiencies, improved data quality and increased patient safety emerge with the adoption of an appropriate information sharing platform. More importantly, large scale eHealth initiatives must be aligned with the value proposition of individual stakeholders in order to achieve widespread adoption. Leveraging an Australian national eHealth infrastructure and the PCEHR we offer a practical example of a service driven digital ecosystem suitable for co-creating value in healthcare.

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The Rapid Visual Information Processing (RVIP) task, a serial discrimination task where task performance believed to reflect sustained attention capabilities, is widely used in behavioural research and increasingly in neuroimaging studies. To date, functional neuroimaging research into the RVIP has been undertaken using block analyses, reflecting the sustained processing involved in the task, but not necessarily the transient processes associated with individual trial performance. Furthermore, this research has been limited to young cohorts. This study assessed the behavioural and functional magnetic resonance imaging (fMRI) outcomes of the RVIP task using both block and event-related analyses in a healthy middle aged cohort (mean age = 53.56 years, n = 16). The results show that the version of the RVIP used here is sensitive to changes in attentional demand processes with participants achieving a 43% accuracy hit rate in the experimental task compared with 96% accuracy in the control task. As shown by previous research, the block analysis revealed an increase in activation in a network of frontal, parietal, occipital and cerebellar regions. The event related analysis showed a similar network of activation, seemingly omitting regions involved in the processing of the task (as shown in the block analysis), such as occipital areas and the thalamus, providing an indication of a network of regions involved in correct trial performance. Frontal (superior and inferior frontal gryi), parietal (precuenus, inferior parietal lobe) and cerebellar regions were shown to be active in both the block and event-related analyses, suggesting their importance in sustained attention/vigilance. These networks and the differences between them are discussed in detail, as well as implications for future research in middle aged cohorts.

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Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

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This paper presents real-time simulation models of electrical machines on FPGA platform. Implementation of the real-time numerical integration methods with digital logic elements is discussed. Several numerical integrations are presented. A real-time simulation of DC machine is carried out on this FPGA platform and important transient results are presented. These results are compared to simulation results obtained through a commercial off-line simulation software.

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The inhibitory effect of FeSO4-dependent cytosolic protein on microsomal HMGCoA reductase is on the enzyme activity and not an artifact of loss of the product, mevalonate, through phosphorylation, unlike that of ATP.Mg effect.

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The fault-tolerant multiprocessor (ftmp) is a bus-based multiprocessor architecture with real-time and fault- tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (spn) and developspn-based performance models forftmp. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times.