591 resultados para collaborative assessment environments


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An often neglected but well recognised aspect of successful engineering asset management is the achievement of co-operation and collaboration between various occupational, functional and hierarchical levels present within complex technical environments. Engineering and technical contexts have been well documented for the presence of highly cohesive groups based around around functional or role orientations. However while highly cohesive groups are potentially advantageous they are also often correlated with the emergence of knowledge and information silos based around those same functional or occupational clusters. Improved collaboration and co-operation between groups has been demonstrated to result in a number of positive outcomes at an individual, group and organisational level. Example outcomes include an increased capacity for problem solving, improved responsiveness and adaptation to organisational crises, higher morale and an increased ability to leverage workforce capability. However, an essential challenge for organisations wishing to overcome informational silos is to implement mechanisms that facilitate, encourage and sustain interactions between otherwise disconnected groups. This paper reviews the ability of Web 2.0 technologies and mobile computing devices to facilitate and encourage knowledge sharing between “silo’d” groups. Commonly available tools such as Facebook, Twitter, Blogs, Wiki’s and others will be reviewed in relation to their applicability, functionality and ease-of-use by engineering and technical personnel. The paper also documents three case examples of engineering organisations that have successfully employed Web 2.0 to achieve superior knowledge management. With a number of clear recommendations the paper is an essential starting point for any organization looking at the use of new generation technologies for achieving the significant outcomes associated with knowledge transfer.

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The first use of computing technologies and the development of land use models in order to support decision-making processes in urban planning date back to as early as mid 20th century. The main thrust of computing applications in urban planning is their contribution to sound decision-making and planning practices. During the last couple of decades many new computing tools and technologies, including geospatial technologies, are designed to enhance planners' capability in dealing with complex urban environments and planning for prosperous and healthy communities. This chapter, therefore, examines the role of information technologies, particularly internet-based geographic information systems, as decision support systems to aid public participatory planning. The chapter discusses challenges and opportunities for the use of internet-based mapping application and tools in collaborative decision-making, and introduces a prototype internet-based geographic information system that is developed to integrate public-oriented interactive decision mechanisms into urban planning practice. This system, referred as the 'Community-based Internet GIS' model, incorporates advanced information technologies, distance learning, sustainable urban development principles and community involvement techniques in decision-making processes, and piloted in Shibuya, Tokyo, Japan.

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Operators of busy contemporary airports have to balance tensions between the timely flow of passengers, flight operations, the conduct of commercial business activities and the effective application of security processes. In addition to specific onsite issues airport operators liaise with a range of organisations which set and enforce aviation-related policies and regulations as well as border security agencies responsible for customs, quarantine and immigration, in addition to first response security services. The challenging demands of coordinating and planning in such complex socio-technical contexts place considerable pressure on airport management to facilitate coordination of what are often conflicting goals and expectations among groups that have standing in respect to safe and secure air travel. What are, as yet, significantly unexplored issues in large airports are options for the optimal coordination of efforts from the range of public and private sector participants active in airport security and crisis management. A further aspect of this issue is how airport management systems operate when there is a transition from business-as-usual into an emergency/crisis situation and then, on recovery, back to ‘normal’ functioning. Business Continuity Planning (BCP), incorporating sub-plans for emergency response, continuation of output and recovery of degraded operating capacity, would fit such a context. The implementation of BCP practices in such a significant high security setting offers considerable potential benefit yet entails considerable challenges. This paper presents early results of a 4 year nationally funded industry-based research project examining the merger of Business Continuity Planning and Transport Security Planning as a means of generating capability for improved security and reliability and, ultimately, enhanced resilience in major airports. The project is part of a larger research program on the Design of Secure Airports that includes most of the gazetted ‘first response’ international airports in Australia, key Aviation industry groups and all aviation-related border and security regulators as collaborative partners. The paper examines a number of initial themes in the research, including: ? Approaches to integrating Business Continuity & Aviation Security Planning within airport operations; ? Assessment of gaps in management protocols and operational capacities for identifying and responding to crises within and across critical aviation infrastructure; ? Identification of convergent and divergent approaches to crisis management used across Austral-Asia and their alignment to planned and possible infrastructure evolution.

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This paper presents Multi-Step A* (MSA*), a search algorithm based on A* for multi-objective 4D vehicle motion planning (three spatial and one time dimension). The research is principally motivated by the need for offline and online motion planning for autonomous Unmanned Aerial Vehicles (UAVs). For UAVs operating in large, dynamic and uncertain 4D environments, the motion plan consists of a sequence of connected linear tracks (or trajectory segments). The track angle and velocity are important parameters that are often restricted by assumptions and grid geometry in conventional motion planners. Many existing planners also fail to incorporate multiple decision criteria and constraints such as wind, fuel, dynamic obstacles and the rules of the air. It is shown that MSA* finds a cost optimal solution using variable length, angle and velocity trajectory segments. These segments are approximated with a grid based cell sequence that provides an inherent tolerance to uncertainty. Computational efficiency is achieved by using variable successor operators to create a multi-resolution, memory efficient lattice sampling structure. Simulation studies on the UAV flight planning problem show that MSA* meets the time constraints of online replanning and finds paths of equivalent cost but in a quarter of the time (on average) of vector neighbourhood based A*.

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The paper provides an assessment of the performance of commercial Real Time Kinematic (RTK) systems over longer than recommended inter-station distances. The experiments were set up to test and analyse solutions from the i-MAX, MAX and VRS systems being operated with three triangle shaped network cells, each having an average inter-station distance of 69km, 118km and 166km. The performance characteristics appraised included initialization success rate, initialization time, RTK position accuracy and availability, ambiguity resolution risk and RTK integrity risk in order to provide a wider perspective of the performance of the testing systems. ----- ----- The results showed that the performances of all network RTK solutions assessed were affected by the increase in the inter-station distances to similar degrees. The MAX solution achieved the highest initialization success rate of 96.6% on average, albeit with a longer initialisation time. Two VRS approaches achieved lower initialization success rate of 80% over the large triangle. In terms of RTK positioning accuracy after successful initialisation, the results indicated a good agreement between the actual error growth in both horizontal and vertical components and the accuracy specified in the RMS and part per million (ppm) values by the manufacturers. ----- ----- Additionally, the VRS approaches performed better than the MAX and i-MAX when being tested under the standard triangle network with a mean inter-station distance of 69km. However as the inter-station distance increases, the network RTK software may fail to generate VRS correction and then may turn to operate in the nearest single-base RTK (or RAW) mode. The position uncertainty reached beyond 2 meters occasionally, showing that the RTK rover software was using an incorrect ambiguity fixed solution to estimate the rover position rather than automatically dropping back to using an ambiguity float solution. Results identified that the risk of incorrectly resolving ambiguities reached 18%, 20%, 13% and 25% for i-MAX, MAX, Leica VRS and Trimble VRS respectively when operating over the large triangle network. Additionally, the Coordinate Quality indicator values given by the Leica GX1230 GG rover receiver tended to be over-optimistic and not functioning well with the identification of incorrectly fixed integer ambiguity solutions. In summary, this independent assessment has identified some problems and failures that can occur in all of the systems tested, especially when being pushed beyond the recommended limits. While such failures are expected, they can offer useful insights into where users should be wary and how manufacturers might improve their products. The results also demonstrate that integrity monitoring of RTK solutions is indeed necessary for precision applications, thus deserving serious attention from researchers and system providers.

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Large mysticete whales represent a unique challenge for chemical risk assessment. Few epidemiological investigations are possible due to the low incidence of adult stranding events. Similarly their often extreme life-history adaptations of prolonged migration and fasting challenge exposure assumptions. Molecular biomarkers offer the potential to complement information yielded through tissue chemical analysis, as well as providing evidence of a molecular response to chemical exposure. In this study we confirm the presence of cytochrome P450 reductase (CPR) and cytochrome P450 isoenzyme 1A1 (CYP1A1) in epidermal tissue of southern hemisphere humpback whales (Megaptera novaeangliae). The detection of CYP1A1 in the integument of the humpback whale affords the opportunity for further quantitative non-destructive investigations of enzyme activity as a function of chemical stress.

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Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

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The impact of digital technology within the creative industries has brought with it a range of new opportunities for collaborative, cross-disciplinary and multi-disciplinary practice. Along with these opportunities has come the need to re-evaluate how we as educators approach teaching within this new digital culture. Within the field of animation, there has been a radical shift in the expectations of students, industry and educators as animation has become central to a range of new moving image practices. This paper interrogates the effectiveness of adopting a studio-based collaborative production project as a method for educating students within this new moving-image culture. The project was undertaken, as part of the Creative Industries Transitions to New Professional Environments program at Queensland University of Technology (QUT) in Brisbane Australia. A number of students studying across the Creative Industries Faculty and the Faculty of Science and Technology were invited to participate in the development of a 3D animated short film. The project offered students the opportunity to become actively involved in all stages of the creative process, allowing them to experience informal learning through collaborative professional practice. It is proposed that theoretical principles often associated with andragogy and constructivism can be used to design and deliver programs that address the emerging issues surrounding the teaching of this new moving image culture.

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After the primary researches on constructability issue which were implemented in United States, United Kingdom and Australia, more explorations were applied on that in order to assess this unique scientific fact in East Asian country of Malaysia. Based on the latest researches done on constructability concept in Malaysia, the most Critical Constructability Activities (CCAs) are defined according to amount of contractors’ participation in each activity and amount of gap between actual and potential effects of each of them on achieving the overall objectives of the construction projects with more cost and time savings and better quality which is the whole aim of a beneficial constructability activity. The present research aims to assess the current findings on CCAs in order to identify the types of contractors and projects which these CCAs are getting performed in and also the types of contracts is used in these CCAs. Finally it was found that there are some significant differences in amount of contractors’ involvement in CCAs among various considered independent variables. This study uses the former researches to help Malaysian construction stakeholders to find out the barriers of constructability implementation in building projects via giving more details on application of CCAs among different IVs.

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Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

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Scalable high-resolution tiled display walls are becoming increasingly important to decision makers and researchers because high pixel counts in combination with large screen areas facilitate content rich, simultaneous display of computer-generated visualization information and high-definition video data from multiple sources. This tutorial is designed to cater for new users as well as researchers who are currently operating tiled display walls or 'OptiPortals'. We will discuss the current and future applications of display wall technology and explore opportunities for participants to collaborate and contribute in a growing community. Multiple tutorial streams will cover both hands-on practical development, as well as policy and method design for embedding these technologies into the research process. Attendees will be able to gain an understanding of how to get started with developing similar systems themselves, in addition to becoming familiar with typical applications and large-scale visualisation techniques. Presentations in this tutorial will describe current implementations of tiled display walls that highlight the effective usage of screen real-estate with various visualization datasets, including collaborative applications such as visualcasting, classroom learning and video conferencing. A feature presentation for this tutorial will be given by Jurgen Schulze from Calit2 at the University of California, San Diego. Jurgen is an expert in scientific visualization in virtual environments, human-computer interaction, real-time volume rendering, and graphics algorithms on programmable graphics hardware.

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This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

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A country’s prosperity relies on the creative potential of its people. Educating gifted students must be a priority for educators and education systems if society is to capitalise on their potential to contribute to an economical and sustainable future. Given the importance of teachers in supporting academic achievement, educating preservice teachers on how to cater for gifted students commences the process as they can foster the implementation of current teaching practices that draw on substantial research into the education of gifted children. This study investigated preservice teachers’ perceptions for teaching gifted students after participating in a school-based intervention with gifted students. The teachers implemented differentiated curriculum activities that catered for the diverse needs of learners. Participants (n=22) were surveyed at the end of the program on their perceptions of how to differentiate the curriculum for meeting the needs of the student. Analysis of the survey indicated these preservice teachers agreed or strongly agreed they had developed skills in curriculum planning (91%) with well-designed activities (96%), and lesson preparation skills (96%). They also claimed they were enthusiastic for teaching (91%) and had understanding of school practices and policies (96%). However, only 46% agreed they had knowledge of syllabus documents with 50% claiming an ability to provide written feedback on the student’s learning. Furthermore, only 64% suggested they had educational language from the syllabus and effective student management strategies. Preservice teachers require direction on how to cater for diversity by building knowledge from direct gifted education experiences. The survey may be used as a diagnostic tool to determine areas for developing education experiences related to the education of the gifted for preservice teachers.

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Project alliancing is a new alternative to traditional project delivery systems, especially in the commercial building sector. The Collaborative Process is a theoretical model of people and systems characteristics that are required to reduce the adversarial nature of most construction projects. Although developed separately, both are responses to the same pressures. Project alliancing was just used successfully to complete the National Museum of Australia. This project was analyzed as a case study to determine the extent to which it could be classified as a “collaborative project”. Five key elements of The Collaborative Process were reviewed and numerous examples from the management of this project were cited that support the theoretical recommendations of this model. In the case of this project, significant added value was delivered to the client and many innovations resulted from the collective work of the parties to the contract. It was concluded that project alliances for commercial buildings offer many advantages over traditional project delivery systems, which are related to increasing the levels of collaboration among a project management team.

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Developments in school education in Australia over the past decade have witnessed the rise of national efforts to reform curriculum, assessment and reporting. Constitutionally the power to decide on curriculum matters still resides with the States. Higher stakes in assessment, brought about by national testing and international comparative analyses of student achievement data, have challenged State efforts to maintain the emphasis on assessment to promote learning while fulfilling accountability demands. In this article lessons from the Queensland experience indicate that it is important to build teachers' assessment capacity and their assessment literacy for the promotion of student learning. It is argued that teacher assessment can be a source of dependable results through moderation practice. The Queensland Studies Authority has recognised and supported the development of teacher assessment and moderation practice in the context of standards-driven, national reform. Recent research findings explain how the focus on learning can be maintained by avoiding an over-interpretation of test results in terms of innate ability and limitations and by encouraging teachers to adopt more tailored diagnosis of assessment data to address equity through focus on achievement for all. Such efforts are challenged as political pressures related to the Australian government’s implementation of national testing and national partnership funding arrangements tied to the performance of students at or below minimum standards become increasingly apparent.