554 resultados para modified local ternary pattern
Resumo:
AIMS: To test a model that delineates advanced practice nursing from the practice profile of other nursing roles and titles. BACKGROUND: There is extensive literature on advanced practice reporting the importance of this level of nursing to contemporary health service and patient outcomes. Literature also reports confusion and ambiguity associated with advanced practice nursing. Several countries have regulation and delineation for the nurse practitioner, but there is less clarity in definition and service focus of other advanced practice nursing roles. DESIGN: A statewide survey. METHODS: Using the modified Strong Model of Advanced Practice Role Delineation tool, a survey was conducted in 2009 with a random sample of registered nurses/midwives from government facilities in Queensland, Australia. Analysis of variance compared total and subscale scores across groups according to grade. Linear, stepwise multiple regression analysis examined factors influencing advanced practice nursing activities across all domains. RESULTS: There were important differences according to grade in mean scores for total activities in all domains of advanced practice nursing. Nurses working in advanced practice roles (excluding nurse practitioners) performed more activities across most advanced practice domains. Regression analysis indicated that working in clinical advanced practice nursing roles with higher levels of education were strong predictors of advanced practice activities overall. CONCLUSION: Essential and appropriate use of advanced practice nurses requires clarity in defining roles and practice levels. This research delineated nursing work according to grade and level of practice, further validating the tool for the Queensland context and providing operational information for assigning innovative nursing service.
Resumo:
Here mixed convection boundary layer flow of a viscous fluid along a heated vertical semi-infinite plate is investigated in a non-absorbing medium. The relationship between convection and thermal radiation is established via boundary condition of second kind on the thermally radiating vertical surface. The governing boundary layer equations are transformed into dimensionless parabolic partial differential equations with the help of appropriate transformations and the resultant system is solved numerically by applying straightforward finite difference method along with Gaussian elimination technique. It is worthy to note that Prandlt number, Pr, is taken to be small (<< 1) which is appropriate for liquid metals. Moreover, the numerical results are demonstrated graphically by showing the effects of important physical parameters, namely, the modified Richardson number (or mixed convection parameter), Ri*, and surface radiation parameter, R, in terms of local skin friction and local Nusselt number coefficients.
Resumo:
Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.
Resumo:
Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.
Resumo:
Transformation toughening ceramics (TTCs) are engineering materials which combine ceramic properties such as hardness, corrosion resistance and low thermal conductivity with good toughness and mechanical strength. At elevated temperatures their use is limited due to destabilisation of the transformation toughening microstructure (partially stabilised zirconia or PSZ) or creep and hydrothermal degradation (tetragonal zirconia polycrystals or TZPs). Despite these limitations, the use of TTCs, particularly zirconia based, has become widespread. To date, most commercial TTCs are based on combinations of zirconia and one stabilising oxide. This work investigates a zirconia ceramic containing two stabilisers, namely yttria and titania in roughly equal proportions.
Resumo:
A new control method for battery storage to maintain acceptable voltage profile in autonomous microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.
Resumo:
Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).
Resumo:
Chemical treatments of kaolins to produce nanocrystalline or "X-ray amorphous", stable aluminosilicates with variable - but reproducible - types of micro- and meso-porosity have been developed. These materials show cation exchange capacities and surface area values significantly higher (ranging from 10x to 100x) than kaolin and show good acid resistance to pH~3.0. The combination of these properties offers strong potential for many new applications of kaolin-derived materials in large worldwide markets such as environmental remediation and catalysis. Kaolin amorphous derivative (KAD) is well-suited to removal of many toxic metals down to ppb range from acid mine drainage. Engineering development trials of the KAD manufacturing process and the utilisation of KAD in polluted waters such as acid mine drainage indicates that scale-up from bench-scale is not a barrier to market entry.
Resumo:
In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.
Resumo:
The 2011 floods illustrated once again Queensland’s vulnerability to flooding and similar disasters. Climate change will increase the frequency and magnitude of such events and will have a variety of other impacts. To deal with these impacts governments at all levels need to be prepared and work together. Like the rest of the nation most of the population of the state is located in the coastal areas and these areas are more vulnerable to the impacts of climate change. This paper examines climate change adaptation efforts in coastal Queensland. The aim is increasing local disaster resilience of people and property through fostering coordination between local and state government planning activities in coastal high hazard areas. By increasing the ability of local governments and state agencies to coordinate planning activities, we can help adapt to impacts of climate change. Towards that end, we will look at the ways that these groups currently interact, especially with regard to issues involving uncertainty related to climate change impacts. Through an examination of climate change related activities by Queensland’s coastal local governments and state level planning agencies and how they coordinate their planning activities at different levels we aim to identify the weaknesses of the current planning system in responding to the challenges of climate change adaptation and opportunities for improving the ways we plan and coordinate planning, and make recommendations to improve resilience in advance of disasters so as to help speed up recovery when they occur.
Resumo:
Cyclone Yasi struck the Cassowary Coast of Queensland in the early hours of Feb 3, 2011, destroying many homes sand property, including the destruction of the Cardwell and district historical society’s premises. With their own homes flattened, many were forced to live in mobile accommodation, with extended family, or leave altogether. The historical society members however were more devastated by their flattened foreshore museum and loss of their collection material. A call for assistance was made through the OHAA Qld branch, who along with QUT sponsored a trip to somehow plan how they could start to pick up the pieces to start again. This presentation highlights the need for communities to gather, preserve and present their own stories, in a way that is sustainable and meaningful to them, but that good advice and support along the way is important. Two 2 day workshops were held in March and then September, augmented by plenty of email correspondence and phone calls in between. Participants learnt that if they could conduct quality oral history interviews, they could later use these in many exhibitable ways including: documentary pieces; digital stories; photographic collections; creative short stories; audio segments –while also drawing closely together a suffering community. This story is not only about the people who were interviewed about the night Yasi struck, but the amazing women (all over 50) of the historical society who were willing to try and leap the digital divide that faces older Australians, especially those in rural Australia, so that their older local stories would not be lost and so that new stories could also be remembered.
Resumo:
Purpose – Recent knowledge management (KM) literature suggests that KM activities are not independent of each other, rather they interact with each other to form a process which receives input from both external and internal business environments, and then produces new knowledge for future utilisation. The purpose of this paper is to empirically investigate the relationships between KM activities within the construction business context in order to identify and map the pattern of their interactions. Design/methodology/approach – A questionnaire survey was administered to a sample of contracting organisations operating in Hong Kong to elicit opinions of construction professionals on the intensity of KM activities currently being executed by their organisations in order to facilitate knowledge capture, sharing and utilisation. More than 150 respondents from 99 organisations responded to the survey. Additionally, a total of 15 semi-structured interviews were undertaken to provide a unique perspective on many of the challenges facing local construction organisations when dealing with KM activities. Findings – Knowledge acquisition and utilisation play paramount roles in the development of the organisational knowledge asset. The higher the intensity of these two activities, the larger the organisational knowledge pool which, in turn, demands greater knowledge dissemination capacity. This dissemination capacity enables more active and intense responses to market changes and clients' needs, thus facilitating and stimulating acquisition and utilisation of new tacit knowledge, thus improving organisational business performance. Originality/value – Interactions between KM activities were empirically investigated, from a strategic perspective, in the construction business context.
Resumo:
A process for the preparation of a modified kaolin from a kaolin group mineral which includes expansion and contraction of layers of the kaolin group mineral. The layers comprising one Si-tetrahedral sheet and one Al-octahedral sheet. The expansion and contraction may be initiated by initial intercalation of a reagent which can penetrate kaolin layers to reach an interlayer region there between to form an intercalate. Subsequently, the intercalation may be followed by de-intercalation which involves the removal of the reagent. By the above process, there is provided crystalline modified kaolins having the following properties: (i) an increased interlayer space compared to corresponding kaolin group minerals; (ii) an increased susceptibility to intercalation by cations, anions or salts compared to corresponding kaolin group minerals; and (iii) an increased exfoliated morphology compared to corresponding kaolin group minerals.
Resumo:
In order to comprehend user information needs by concepts, this paper introduces a novel method to match relevance features with ontological concepts. The method first discovers relevance features from user local instances. Then, a concept matching approach is developed for matching these features to accurate concepts in a global knowledge base. This approach is significant for the transition of informative descriptor and conceptional descriptor. The proposed method is elaborately evaluated by comparing against three information gathering baseline models. The experimental results shows the matching approach is successful and achieves a series of remarkable improvements on search effectiveness.
Resumo:
Aim his study reports the use of exploratory factor analysis to determine construct validity of a modified advanced practice role delineation tool. Background Little research exists on specific activities and domains of practice within advanced practice nursing roles, making it difficult to define service parameters of this level of nursing practice. A valid and reliable tool would assist those responsible for employing or deploying advanced practice nurses by identifying and defining their service profile. This is the third paper from a multi-phase Australian study aimed at assigning advanced practice roles. Methods A postal survey was conducted of a random sample of state government employed Registered nurses and midwives, across various levels and grades of practice in the state of Queensland, Australia, using the modified Advanced Practice Role Delineation tool. Exploratory factor analysis, using principal axis factoring was undertaken to examine factors in the modified tool. Cronbach’s alpha coefficient determined reliability of the overall scale and identified factors. Results There were 658 responses (42% response rate). The five factors found with loadings of ≥.400 for 40 of the 41 APN activities were similar to the five domains in the Strong model. Cronbach’s alpha coefficient was .94 overall and for the factors ranged from 0.83 to 0.95. Conclusion Exploratory factor analysis of the modified tool supports validity of the five domains of the original tool. Further investigation will identify use of the tool in a broader healthcare environment.