952 resultados para User Evaluation


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The Extended Adolescent Injury Checklist (E-AIC), a self-report measure of injury based on the model of the Adolescent Injury Checklist (AIC), was developed for use in the evaluation of school-based interventions. The three stages of this development involved focus groups with adolescents and consultations with medical staff, pilot testing of the revised AIC in a high school context, and use of the finalised checklist in pre- and post-questionnaires to examine its utility. Results revealed that responses to the final version of the E-AIC were meaningful and remained consistent over time. The E-AIC appears to be a promising measure of adolescent injury that is simple, time-efficient and appropriate for use in the evaluation of school-based injury prevention programs.

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Online learning has been recognised as an effective pedagogical method and tool, and is broadly integrated into various types of teaching and learning strategies in higher education. In practice, the use of Virtual Learning Environment (VLE) in higher education has become an integral strategy for quality education. The field of design education however has not been researched extensively in regard to online learning, delivery and evaluation. This paper discusses design education from an online learning perspective. It proposes an integrated framework with three key components for online learning via VLE including an interactive delivery structure, communication channels, and learning evaluation. Additionally, the paper describes and evaluates how VLE sites for two design units were built based on an integrated framework and student learning experiences. The results indicate that online design education should be integrated with various educational values and functional features in a systematic manner, and requires designing learning evaluation protocols as part of learning activities and communicative forms within online-based learning sites.

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Proposed transmission smart grids will use a digital platform for the automation of substations operating at voltage levels of 110 kV and above. The IEC 61850 series of standards, released in parts over the last ten years, provide a specification for substation communications networks and systems. These standards, along with IEEE Std 1588-2008 Precision Time Protocol version 2 (PTPv2) for precision timing, are recommended by the both IEC Smart Grid Strategy Group and the NIST Framework and Roadmap for Smart Grid Interoperability Standards for substation automation. IEC 61850-8-1 and IEC 61850-9-2 provide an inter-operable solution to support multi-vendor digital process bus solutions, allowing for the removal of potentially lethal voltages and damaging currents from substation control rooms, a reduction in the amount of cabling required in substations, and facilitates the adoption of non-conventional instrument transformers (NCITs). IEC 61850, PTPv2 and Ethernet are three complementary protocol families that together define the future of sampled value digital process connections for smart substation automation. This paper describes a specific test and evaluation system that uses real time simulation, protection relays, PTPv2 time clocks and artificial network impairment that is being used to investigate technical impediments to the adoption of SV process bus systems by transmission utilities. Knowing the limits of a digital process bus, especially when sampled values and NCITs are included, will enable utilities to make informed decisions regarding the adoption of this technology.

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BACKGROUND: Treatment of proximal humerus fractures in elderly patients is challenging because of reduced bone quality. We determined the in vitro characteristics of a new implant developed to target the remaining bone stock, and compared it with an implant in clinical use. METHODS: Following osteotomy, left and right humeral pairs from cadavers were treated with either the Button-Fix or the Humerusblock fixation system. Implant stiffness was determined for three clinically relevant cases of load: axial compression, torsion, and varus bending. In addition, a cyclic varus-bending test was performed. RESULTS: We found higher stiffness values for the humeri treated with the ButtonFix system--with almost a doubling of the compression, torsion, and bending stiffness values. Under dynamic loading, the ButtonFix system had superior stiffness and less K-wire migration compared to the Humerusblock system. INTERPRETATION: When compared to the Humerusblock design, the ButtonFix system showed superior biomechanical properties, both static and dynamic. It offers a minimally invasive alternative for the treatment of proximal humerus fractures.

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This paper examines the issues surrounding the successful design and development of tangible technology for optimal engagement in playful activities. At present there is very little data on how, and in what contexts, tangible interactions with technology promote lasting engagement and immersion. The framework at the core of this paper has been designed to guide the effective design of tangible technology for immersive interaction. The paper investigates the relationship between tangible user interfaces (TUI) characteristics of representation and control, and immersive flow experiences produced through balancing skill and challenge in user interaction.

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Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.

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Introduction and aims: For a scaffold material to be considered effective and efficient for tissue engineering it must be biocompatible as well as bioinductive. Silk fiber is a natural biocompatible material suitable for scaffold fabrication; however, silk is tissue-conductive and lacks tissue-inductive properties. One proposed method to make the scaffold tissue-inductive is to introduce plasmids or viruses encoding a specific growth factor into the scaffold. In this study, we constructed adenoviruses encoding bone morphogenetic protein-7 (BMP-7) and incorporated these into silk scaffolds. The osteo-inductive and new bone formation properties of these constructs were assessed in vivo in a critical-sized skull defect animal model. Materials and methods: Silk fibroin scaffolds containing adenovirus particles coding BMP-7 were prepared. The release of the adenovirus particles from the scaffolds was quantified by tissue-culture infective dose (TCID50) and the bioactivity of the released viruses was evaluated on human bone marrow mesenchymal stromal cells (BMSCs). To demonstrate the in vivo bone forming ability of the virus-carrying silk fibroin scaffold, the scaffold constructs were implanted into calvarial defects in SCID mice. Results: In vitro studies demonstrated that the virus-carrying silk fibroin scaffold released virus particles over a 3 week period while preserving their bioactivity. In vivo test of the scaffold constructs in critical-sized skull defect areas revealed that silk scaffolds were capable of delivering the adenovirus encoding BMP-7, resulting significantly enhanced new bone formation. Conclusions: Silk scaffolds carrying BMP-7 encoding adenoviruses can effectively transfect cells and enhance both in vitro and in vivo osteogenesis. The findings of this study indicate silk fibroin is a promising biomaterial for gene delivery to repair critical-sized bone defects.

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Smart matrices are required in bone tissueengineered grafts that provide an optimal environment for cells and retain osteo-inductive factors for sustained biological activity. We hypothesized that a slow-degrading heparin-incorporated hyaluronan (HA) hydrogel can preserve BMP-2; while an arterio–venous (A–V) loop can support axial vascularization to provide nutrition for a bioartificial bone graft. HA was evaluated for osteoblast growth and BMP-2 release. Porous PLDLLA–TCP–PCL scaffolds were produced by rapid prototyping technology and applied in vivo along with HA-hydrogel, loaded with either primary osteoblasts or BMP-2. A microsurgically created A–V loop was placed around the scaffold, encased in an isolation chamber in Lewis rats. HA-hydrogel supported growth of osteoblasts over 8 weeks and allowed sustained release of BMP-2 over 35 days. The A–V loop provided an angiogenic stimulus with the formation of vascularized tissue in the scaffolds. Bone-specific genes were detected by real time RT-PCR after 8 weeks. However, no significant amount of bone was observed histologically. The heterotopic isolation chamber in combination with absent biomechanical stimulation might explain the insufficient bone formation despite adequate expression of bone-related genes. Optimization of the interplay of osteogenic cells and osteo-inductive factors might eventually generate sufficient amounts of axially vascularized bone grafts for reconstructive surgery.

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This research report documents work conducted by the Center for Transportation (CTR) at The University of Texas at Austin in analyzing the Joint Analysis using the Combined Knowledge (J.A.C.K.) program. This program was developed by the Texas Department of Transportation (TxDOT) to make projections of revenues and expenditures. This research effort was to span from September 2008 to August 2009, but the bulk of the work was completed and presented by December 2008. J.A.C.K. was subsequently renamed TRENDS, but for consistency with the scope of work, the original name is used throughout this report.

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This report provides an evaluation of the Capalaba Youth Space.The evaluation included elements of process and impact evaluation and used a participatory action research approach informed by engagement processes, focus groups, a community survey, interviews and secondary analysis of existing data.

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[Selection of papers from the Older Road User Safety Symposium, 26 November 2000, Brisbane, Australia.]----- This publication is a selection of papers on older road user safety which were presented at the Older Road User Safety Symposium on Sunday 26 November 2000 at the Sheraton Brisbane Hotel, Queensland, Australia. The Symposium was held on the day before Australia’s annual Road Safety Research, Policing and Education Conference, which provided an opportunity to garner both presenters and participants from the wider road safety community in Australia. Road safety is a large and diverse area of scholarship and practice, and many disciplines are drawn on in the processes of understanding and addressing road safety problems. The safety of older road users is no different. As this selection shows, work on older road user safety can be informed by demography, research on the mental and physical effects of ageing, social research on older people as road users, evaluation of educational and behavioural interventions, road crash analysis, engineering research and practice, and reviews of policy approaches within Australia and elsewhere. It is possible to summarise these into four constellations, which are reflected in the papers selected for this publication: social impacts and responses; physical and cognitive capability; specific road use performance; and environment/ecology. Though three years have passed since the Symposium, the issues raised in these papers remain current.

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The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

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Suburbanisation has been internationally a major phenomenon in the last decades. Suburb-to-suburb routes are nowadays the most widespread road journeys; and this resulted in an increment of distances travelled, particularly on faster suburban highways. The design of highways tends to over-simplify the driving task and this can result in decreased alertness. Driving behaviour is consequently impaired and drivers are then more likely to be involved in road crashes. This is particularly dangerous on highways where the speed limit is high. While effective countermeasures to this decrement in alertness do not currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behaviour in real-time. The aim of this study is to evaluate in real-time the level of alertness of the driver through surrogate measures that can be collected from in-vehicle sensors. Slow EEG activity is used as a reference to evaluate driver's alertness. Data are collected in a driving simulator instrumented with an eye tracking system, a heart rate monitor and an electrodermal activity device (N=25 participants). Four different types of highways (driving scenario of 40 minutes each) are implemented through the variation of the road design (amount of curves and hills) and the roadside environment (amount of buildings and traffic). We show with Neural Networks that reduced alertness can be detected in real-time with an accuracy of 92% using lane positioning, steering wheel movement, head rotation, blink frequency, heart rate variability and skin conductance level. Such results show that it is possible to assess driver's alertness with surrogate measures. Such methodology could be used to warn drivers of their alertness level through the development of an in-vehicle device monitoring in real-time drivers' behaviour on highways, and therefore it could result in improved road safety.

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Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.

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Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.