351 resultados para Software Tools


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This paper reports on an experiment that was conducted to determine the extent to which group dynamics impacts on the effectiveness of software development teams. The experiment was conducted on software engineering project students at the Queensland University of Technology (QUT).

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Software as a Service (SaaS) is a promising approach for Small and Medium Enterprises (SMEs) firms, in particular those that are focused on growing fast and leveraging new technology, due to the potential benefits arising from its inherent scalability, reduced total cost of ownership and the ease of access to global innovations. This paper proposes a dynamic perspective on IS capabilities to understand and explain SMEs sourcing and levering SaaS. The model is derived from combining the IS capabilities of Feeny and Willcocks (1998) and the dynamic capabilities of Teece (2007) and contextualizing it for SMEs and SaaS. We conclude that SMEs sourcing and leveraging SaaS require leadership, business systems thinking and informed buying for sensing and seizing SaaS opportunities and require leadership and vendor development for transforming in terms of aligning and realigning specific tangible and intangible assets.

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This chapter deals with technical aspects of how USDL service descriptions can be read from and written to different representations for use by humans and tools. A combination of techniques for representing and exchanging USDL have been drawn from Model-Driven Engineering and Semantic Web technologies. The USDL language's structural definition is specified as a MOF meta-model, but some modules were originally defined using the OWL language from the Semantic Web community and translated to the meta-model format. We begin with the important topic of serializing USDL descriptions into XML, so that they can be exchanged beween editors, repositories, and other tools. The following topic is how USDL can be made available through the Semantic Web as a network of linked data, connected via URIs. Finally, consideration is given to human-readable representations of USDL descriptions, and how they can be generated, in large part, from the contents of a stored USDL model.

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The study of urban morphology has become an expanding field of research within the architectural discipline, providing theories to be used as tools in the understanding and design of urban landscapes from the past, the present and into the future. Drawing upon contemporary architectural design theory, this investigation reveals what a sectional analysis of an urban landscape can add to the existing research methods within this field. This paper conducts an enquiry into the use of the section as a tool for urban morphological analysis. Following the methodology of the British school of urban morphology, sections through the urban fabric of the case study city of Brisbane are compared. The results are categorised to depict changes in scale, components and utilisation throughout various timeframes. The key findings illustrate how the section, when read in conjunction with the plan can be used to interpret changes to urban form and the relationship that this has to the quality of the urban environment in the contemporary city.

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Objective Although several validated nutritional screening tools have been developed to “triage” inpatients for malnutrition diagnosis and intervention, there continues to be debate in the literature as to which tool/tools clinicians should use in practice. This study compared the accuracy of seven validated screening tools in older medical inpatients against two validated nutritional assessment methods. Methods This was a prospective cohort study of medical inpatients at least 65 y old. Malnutrition screening was conducted using seven tools recommended in evidence-based guidelines. Nutritional status was assessed by an accredited practicing dietitian using the Subjective Global Assessment (SGA) and the Mini-Nutritional Assessment (MNA). Energy intake was observed on a single day during first week of hospitalization. Results In this sample of 134 participants (80 ± 8 y old, 50% women), there was fair agreement between the SGA and MNA (κ = 0.53), with MNA identifying more “at-risk” patients and the SGA better identifying existing malnutrition. Most tools were accurate in identifying patients with malnutrition as determined by the SGA, in particular the Malnutrition Screening Tool and the Nutritional Risk Screening 2002. The MNA Short Form was most accurate at identifying nutritional risk according to the MNA. No tool accurately predicted patients with inadequate energy intake in the hospital. Conclusion Because all tools generally performed well, clinicians should consider choosing a screening tool that best aligns with their chosen nutritional assessment and is easiest to implement in practice. This study confirmed the importance of rescreening and monitoring food intake to allow the early identification and prevention of nutritional decline in patients with a poor intake during hospitalization.

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Sustainability issues in built environment have attracted an increasingly level of attention from both the general public and the industry. As a result, a number of green building assessment tools have been developed such as the Leadership in Energy and Environmental Design (LEED) and the BRE Environmental Assessment Method (BREEAM), etc. This paper critically reviewed the assessment tools developed in Australian context, i.e. the Green Star rating tools developed by the Green Building Council of Australia. A particular focus is given to the recent developments of these assessment tools. The results showed that the office buildings take the biggest share of Green Star rated buildings. Similarly, sustainable building assessments seem to be more performance oriented which focuses on the operation stage of buildings. In addition, stakeholder engagement during the decision making process is encouraged. These findings provide useful references to the development of next generation of sustainable building assessment tools.

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The most common software analysis tools available for measuring fluorescence images are for two-dimensional (2D) data that rely on manual settings for inclusion and exclusion of data points, and computer-aided pattern recognition to support the interpretation and findings of the analysis. It has become increasingly important to be able to measure fluorescence images constructed from three-dimensional (3D) datasets in order to be able to capture the complexity of cellular dynamics and understand the basis of cellular plasticity within biological systems. Sophisticated microscopy instruments have permitted the visualization of 3D fluorescence images through the acquisition of multispectral fluorescence images and powerful analytical software that reconstructs the images from confocal stacks that then provide a 3D representation of the collected 2D images. Advanced design-based stereology methods have progressed from the approximation and assumptions of the original model-based stereology(1) even in complex tissue sections(2). Despite these scientific advances in microscopy, a need remains for an automated analytic method that fully exploits the intrinsic 3D data to allow for the analysis and quantification of the complex changes in cell morphology, protein localization and receptor trafficking. Current techniques available to quantify fluorescence images include Meta-Morph (Molecular Devices, Sunnyvale, CA) and Image J (NIH) which provide manual analysis. Imaris (Andor Technology, Belfast, Northern Ireland) software provides the feature MeasurementPro, which allows the manual creation of measurement points that can be placed in a volume image or drawn on a series of 2D slices to create a 3D object. This method is useful for single-click point measurements to measure a line distance between two objects or to create a polygon that encloses a region of interest, but it is difficult to apply to complex cellular network structures. Filament Tracer (Andor) allows automatic detection of the 3D neuronal filament-like however, this module has been developed to measure defined structures such as neurons, which are comprised of dendrites, axons and spines (tree-like structure). This module has been ingeniously utilized to make morphological measurements to non-neuronal cells(3), however, the output data provide information of an extended cellular network by using a software that depends on a defined cell shape rather than being an amorphous-shaped cellular model. To overcome the issue of analyzing amorphous-shaped cells and making the software more suitable to a biological application, Imaris developed Imaris Cell. This was a scientific project with the Eidgenössische Technische Hochschule, which has been developed to calculate the relationship between cells and organelles. While the software enables the detection of biological constraints, by forcing one nucleus per cell and using cell membranes to segment cells, it cannot be utilized to analyze fluorescence data that are not continuous because ideally it builds cell surface without void spaces. To our knowledge, at present no user-modifiable automated approach that provides morphometric information from 3D fluorescence images has been developed that achieves cellular spatial information of an undefined shape (Figure 1). We have developed an analytical platform using the Imaris core software module and Imaris XT interfaced to MATLAB (Mat Works, Inc.). These tools allow the 3D measurement of cells without a pre-defined shape and with inconsistent fluorescence network components. Furthermore, this method will allow researchers who have extended expertise in biological systems, but not familiarity to computer applications, to perform quantification of morphological changes in cell dynamics.

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In 2012 the existing eight disciplines of Creative Industries Faculty, QUT combined with the School of Design (formerly a component of the Faculty of Built Environment and Engineering) to create a super faculty that includes the following disciplines: Architecture, Creative Writing & Literary Studies, Dance, Drama, Fashion, Film & Television, Industrial Design, Interior Design, Journalism, Media & Communication, Landscape Architecture, Music & Sound and Urban Design. The university’s research training unit AIRS (Advanced Information Retrieval Skills) is a systematic introduction to research level information literacies. It is currently being redesigned to reflect today’s new data intensive research environment and facilitate the capacity for life-long learning. Upon completion participants are expected to be able to: 1. Demonstrate an understanding of the theory of advanced search and evaluative strategies to efficiently yield appropriate resources to create original research. 2. Apply appropriate data management strategies to organise and utilize your information proficiently, ethically and legally. 3. Identify strategies to ensure best practice in the use of information sources, information technologies, information access tools and investigative methods. All Creative Industries Faculty research students must complete this unit into which CI Librarians teach discipline specific material. The library employs a team of research specific experts as well as Liaison Librarians for each faculty. Together they develop and deliver a generic research training program that provides researcher training in the following areas: Managing Research Data, QUT ePrints: New features for tracking your research impact, Tracking Research Impact, Research Students and the Library: Overview of Library Research Support Services, Technologies for Research Collaboration, Open Access Publishing, Greater Impact via Creative Commons Licence, CAMBIA - Navigating the patent literature, Uploading Publications to QUT ePrints Workshop, AIRS for supervisors, Finding Existing Research Data, Keeping up to date:Discovering and managing current awareness information and Getting Published. In 2011 Creative Industries initiated a new faculty specific research training program to promote capacity building for research within their Faculty, with workshops designed and developed with Faculty Research Leaders, The Office of Research and Liaison Librarians. “Show me the money” which assists staff to pursue alternative funding sources was one such session that was well attended and generated much discussion and interest. Drop in support sessions for ePrints, EndNote referencing software and Tracking Research Impact for the Creative Industries were also popular options on the menu. Liaison Librarians continue to provide one-on-one consultations with individual researchers as requested. This service assists Librarians greatly with getting to know and monitoring their researchers’ changing needs. The CI Faculty has enlisted two Research Leaders, one for each of the two Schools (Design and Media, Entertainment & Creative Arts) whose role it is to mentor newer research staff. Similarly within the CI library liaison team one librarian is assigned the role of Research Coordinator, whose responsibility it is to be the primary liaison with the Assistant Dean, Research and other key Faculty research managers and is the one most likely to attend Faculty committees and meetings relating to research support.

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During an intensive design-led workshop multidisciplinary design teams examined options for a sustainable multi-residential tower on an inner urban site in Brisbane (Australia). The main aim was to demonstrate the key principles of daylight to every habitable room and cross-ventilation to every apartment in the subtropical climate while responding to acceptable yield and price points. The four conceptual design proposals demonstrated a wide range of outcomes, with buildings ranging from 15 to 30 storeys. Daylight Factor (DF), view to the outside, and the avoidance of direct sunlight were the only quantitative and qualitative performance metrics used to implement daylighting to the proposed buildings during the charrette. This paper further assesses the daylighting performance of the four conceptual designs by utilizing Climate-based daylight modeling (CBDM), specifically Daylight Autonomy (DA) and Useful Daylight Illuminance (UDI). Results show that UDI 100-2000lux calculations provide more useful information on the daylighting design than DF. The percentage of the space with a UDI <100-2000lux larger than 50% ranged from 77% to 86% of the time for active occupant behaviour (occupancy from 6am to 6pm). The paper also highlights the architectural features that mostly affect daylighting design in subtropical climates.

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This paper discusses first year students’ responses and outcomes to the integration of digital technologies in their second semester foundational visualisation class; ‘Visualisation II’. As the second class in the Visualisation series, previous analogue knowledge taught in ‘Visualisation I’ is compounded with new digital technologies establishing the introduction to a myriad of hybrid visualisation tools and techniques for design exploration and design artefact. This research examines the differentiation between analogue and digital design, common precedents of the two, and reflects upon the environment and class structure with the learning experiences and confidence of surveyed participants.

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Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

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In recent years there has been a large emphasis placed on the need to use Learning Management Systems (LMS) in the field of higher education, with many universities mandating their use. An important aspect of these systems is their ability to offer collaboration tools to build a community of learners. This paper reports on a study of the effectiveness of an LMS (Blackboard©) in a higher education setting and whether both lecturers and students voluntarily use collaborative tools for teaching and learning. Interviews were conducted with participants (N=67) from the faculties of Science and Technology, Business, Health and Law. Results from this study indicated that participants often use Blackboard© as an online repository of learning materials and that the collaboration tools of Blackboard© are often not utilised. The study also found that several factors have inhibited the use and uptake of the collaboration tools within Blackboard©. These have included structure and user experience, pedagogical practice, response time and a preference for other tools.