196 resultados para 180-1109
Resumo:
This chapter discusses reference modelling languages for business systems analysis and design. In particular, it reports on reference models in the context of the design-for/by-reuse paradigm, explains how traditional modelling techniques fail to provide adequate conceptual expressiveness to allow for easy model reuse by configuration or adaptation and elaborates on the need for reference modelling languages to be configurable. We discuss requirements for and the development of reference modelling languages that reflect the need for configurability. Exemplarily, we report on the development, definition and configuration of configurable event-driven process chains. We further outline how configurable reference modelling languages and the corresponding design principles can be used in future scenarios such as process mining and data modelling.
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The measurement of broadband ultrasonic attenuation (BUA) in cancellous bone at the calcaneus was first described in 1984. The assessment of osteoporosis by BUA has recently been recognized by Universities UK, within its EurekaUK book, as being one of the “100 discoveries and developments in UK Universities that have changed the world” over the past 50 years, covering the whole academic spectrum from the arts and humanities to science and technology. Indeed, BUA technique has been clinically validated and is utilized worldwide, with at least seven commercial systems providing calcaneal BUA measurement. However, a fundamental understanding of the dependence of BUA upon the material and structural properties of cancellous bone is still lacking. This review aims to provide a science- and technology-orientated perspective on the application of BUA to the medical disease of osteoporosis.
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Cooperative collision warning system for road vehicles, enabled by recent advances in positioning systems and wireless communication technologies, can potentially reduce traffic accident significantly. To improve the system, we propose a graph model to represent interactions between multiple road vehicles in a specific region and at a specific time. Given a list of vehicles in vicinity, we can generate the interaction graph using several rules that consider vehicle's properties such as position, speed, heading, etc. Safety applications can use the model to improve emergency warning accuracy and optimize wireless channel usage. The model allows us to develop some congestion control strategies for an efficient multi-hop broadcast protocol.
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Aim. This paper is a report of the effectiveness of a purpose-designed education program in improving undergraduate nursing students’ understanding and practice of infection control precautions. Background. The severe acute respiratory syndrome outbreak in 2003 highlighted that healthcare workers were under-prepared for such an epidemic. While many in-service education sessions were arranged by institutions in response to the outbreak, preservice nursing education has overlooked preparation for handling such infectious disease epidemics. Method. A quasi-experimental design was used and a 16-hour, purpose-designed infection control education programme was implemented for preservice nursing students in southern Taiwan. Self-administered questionnaires were distributed at three time points during the period September 2005 to April 2006 to examine the sustainability and effectiveness of the intervention. Results. A total of 175 preservice nursing students participated in the study. Following the education programme, students in the intervention group showed a statistically significant improvement across time in their knowledge of these precautions [F(2, 180) = 13Æ53, P < 0Æ001] and confidence in resolving infectionrelated issues [F(1Æ79, 168Æ95) = 3Æ24] when compared with those in the control group. Conclusion. To improve nursing students’ capacity in responding to infectious epidemics, an educational programme that integrates the theme of infection precautions, learning theory and teaching strategies is recommended for all nursing institutes.
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In Web service based systems, new value-added Web services can be constructed by integrating existing Web services. A Web service may have many implementations, which are functionally identical, but have different Quality of Service (QoS) attributes, such as response time, price, reputation, reliability, availability and so on. Thus, a significant research problem in Web service composition is how to select an implementation for each of the component Web services so that the overall QoS of the composite Web service is optimal. This is so called QoS-aware Web service composition problem. In some composite Web services there are some dependencies and conflicts between the Web service implementations. However, existing approaches cannot handle the constraints. This paper tackles the QoS-aware Web service composition problem with inter service dependencies and conflicts using a penalty-based genetic algorithm (GA). Experimental results demonstrate the effectiveness and the scalability of the penalty-based GA.
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With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.
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3D Virtual Environments (VE) are real; they exist as digital worlds with the advantage of having none of the constraints of the real world. As such they are the perfect training ground for design students who can create, build and experiment with design solutions without the constraint of real world projects. This paper reports on an educational setting used to explore a model for using VE such as Second Life (SL) developed by Linden Labs in California, as a collaborative environment for design education. A postgraduate landscape architecture learning environment within a collaborative design unit was developed to integrate this model where the primary focus was the application of three-dimensional tools within design, not as a presentation tool, but rather as a design tool. The focus of the unit and its aims and objectives will be outlined before describing the use of SL in the unit. Attention is focused on the collaboration and learning experience before discussing the outcomes, student feedback, future projects using this model and potential for further research. The outcome of this study aims to contribute to current research on teaching and learning design in interactive VE’s. We present a case study of our first application of this model.
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The need for large scale environmental monitoring to manage environmental change is well established. Ecologists have long used acoustics as a means of monitoring the environment in their field work, and so the value of an acoustic environmental observatory is evident. However, the volume of data generated by such an observatory would quickly overwhelm even the most fervent scientist using traditional methods. In this paper we present our steps towards realising a complete acoustic environmental observatory - i.e. a cohesive set of hardware sensors, management utilities, and analytical tools required for large scale environmental monitoring. Concrete examples of these elements, which are in active use by ecological scientists, are also presented
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We propose an efficient and low-complexity scheme for estimating and compensating clipping noise in OFDMA systems. Conventional clipping noise estimation schemes, which need all demodulated data symbols, may become infeasible in OFDMA systems where a specific user may only know his own modulation scheme. The proposed scheme first uses equalized output to identify a limited number of candidate clips, and then exploits the information on known subcarriers to reconstruct clipped signal. Simulation results show that the proposed scheme can significantly improve the system performance.
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Determined the effectiveness of a psychosocial intervention, provided to expectant couples in routine antenatal classes, on the postpartum psychosocial adjustment of women and men. Preparation for Parenthood programs were randomly allocated to one of three conditions: usual service ('control'), experimental ('empathy'), or non-specific control ('baby-play'). The latter condition controlled for the non-specific effects of the intervention, these being: the provision of an extra class; asking couples to consider the early postpartum weeks; and receiving booster information after the antenatal class, and again shortly after the birth. Women and men were categorised into three levels of self-esteem, as measured antenatally: low, medium and high. 268 participants were recruited antenatally. Interview data and self-report information was collected from 202 of these women at 6 weeks postpartum, and 180 women at 6 months postpartum. The intervention consisted of a session focusing on psychosocial issues related to becoming first-time parents. Participants discussed possible postpartum concerns in separate gender groups for part of the session, and then discussed these issues with their partners
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Emissions from airport operations are of significant concern because of their potential impact on local air quality and human health. The currently limited scientific knowledge of aircraft emissions is an important issue worldwide, when considering air pollution associated with airport operation, and this is especially so for ultrafine particles. This limited knowledge is due to scientific complexities associated with measuring aircraft emissions during normal operations on the ground. In particular this type of research has required the development of novel sampling techniques which must take into account aircraft plume dispersion and dilution as well as the various particle dynamics that can affect the measurements of the aircraft engine plume from an operational aircraft. In order to address this scientific problem, a novel mobile emission measurement method called the Plume Capture and Analysis System (PCAS), was developed and tested. The PCAS permits the capture and analysis of aircraft exhaust during ground level operations including landing, taxiing, takeoff and idle. The PCAS uses a sampling bag to temporarily store a sample, providing sufficient time to utilize sensitive but slow instrumental techniques to be employed to measure gas and particle emissions simultaneously and to record detailed particle size distributions. The challenges in relation to the development of the technique include complexities associated with the assessment of the various particle loss and deposition mechanisms which are active during storage in the PCAS. Laboratory based assessment of the method showed that the bag sampling technique can be used to accurately measure particle emissions (e.g. particle number, mass and size distribution) from a moving aircraft or vehicle. Further assessment of the sensitivity of PCAS results to distance from the source and plume concentration was conducted in the airfield with taxiing aircraft. The results showed that the PCAS is a robust method capable of capturing the plume in only 10 seconds. The PCAS is able to account for aircraft plume dispersion and dilution at distances of 60 to 180 meters downwind of moving a aircraft along with particle deposition loss mechanisms during the measurements. Characterization of the plume in terms of particle number, mass (PM2.5), gaseous emissions and particle size distribution takes only 5 minutes allowing large numbers of tests to be completed in a short time. The results were broadly consistent and compared well with the available data. Comprehensive measurements and analyses of the aircraft plumes during various modes of the landing and takeoff (LTO) cycle (e.g. idle, taxi, landing and takeoff) were conducted at Brisbane Airport (BNE). Gaseous (NOx, CO2) emission factors, particle number and mass (PM2.5) emission factors and size distributions were determined for a range of Boeing and Airbus aircraft, as a function of aircraft type and engine thrust level. The scientific complexities including the analysis of the often multimodal particle size distributions to describe the contributions of different particle source processes during the various stages of aircraft operation were addressed through comprehensive data analysis and interpretation. The measurement results were used to develop an inventory of aircraft emissions at BNE, including all modes of the aircraft LTO cycle and ground running procedures (GRP). Measurements of the actual duration of aircraft activity in each mode of operation (time-in-mode) and compiling a comprehensive matrix of gas and particle emission rates as a function of aircraft type and engine thrust level for real world situations was crucial for developing the inventory. The significance of the resulting matrix of emission rates in this study lies in the estimate it provides of the annual particle emissions due to aircraft operations, especially in terms of particle number. In summary, this PhD thesis presents for the first time a comprehensive study of the particle and NOx emission factors and rates along with the particle size distributions from aircraft operations and provides a basis for estimating such emissions at other airports. This is a significant addition to the scientific knowledge in terms of particle emissions from aircraft operations, since the standard particle number emissions rates are not currently available for aircraft activities.
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It is a big challenge to clearly identify the boundary between positive and negative streams. Several attempts have used negative feedback to solve this challenge; however, there are two issues for using negative relevance feedback to improve the effectiveness of information filtering. The first one is how to select constructive negative samples in order to reduce the space of negative documents. The second issue is how to decide noisy extracted features that should be updated based on the selected negative samples. This paper proposes a pattern mining based approach to select some offenders from the negative documents, where an offender can be used to reduce the side effects of noisy features. It also classifies extracted features (i.e., terms) into three categories: positive specific terms, general terms, and negative specific terms. In this way, multiple revising strategies can be used to update extracted features. An iterative learning algorithm is also proposed to implement this approach on RCV1, and substantial experiments show that the proposed approach achieves encouraging performance.
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Furniture and appliance related injuries in children under 5 years of age accounts for an estimated 180 emergency presentations annually in Queensland. Injuries occur when children push or pull items over, climb and fall off furniture, or climb and tip the item over. Children under 2 years of age tend to injure themselves by pulling items over onto themselves Children over 2 years of age are more likely to be injured after climbing the item and either falling off or tipping the item over onto themselves. Tip over injuries (where the item falls over and injures the child) in children under 5 years of age account for an estimated 115 emergency presentations annually in Queensland. The item most commonly associated with a tip over injury is a television (with or without the cabinet) Prevention requires better design and selection of furniture with inherent stability coupled with mechanisms to install or fix less stable items
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This article explores two matrix methods to induce the ``shades of meaning" (SoM) of a word. A matrix representation of a word is computed from a corpus of traces based on the given word. Non-negative Matrix Factorisation (NMF) and Singular Value Decomposition (SVD) compute a set of vectors corresponding to a potential shade of meaning. The two methods were evaluated based on loss of conditional entropy with respect to two sets of manually tagged data. One set reflects concepts generally appearing in text, and the second set comprises words used for investigations into word sense disambiguation. Results show that for NMF consistently outperforms SVD for inducing both SoM of general concepts as well as word senses. The problem of inducing the shades of meaning of a word is more subtle than that of word sense induction and hence relevant to thematic analysis of opinion where nuances of opinion can arise.
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We argue that web service discovery technology should help the user navigate a complex problem space by providing suggestions for services which they may not be able to formulate themselves as (s)he lacks the epistemic resources to do so. Free text documents in service environments provide an untapped source of information for augmenting the epistemic state of the user and hence their ability to search effectively for services. A quantitative approach to semantic knowledge representation is adopted in the form of semantic space models computed from these free text documents. Knowledge of the user’s agenda is promoted by associational inferences computed from the semantic space. The inferences are suggestive and aim to promote human abductive reasoning to guide the user from fuzzy search goals into a better understanding of the problem space surrounding the given agenda. Experimental results are discussed based on a complex and realistic planning activity.