856 resultados para facility-based deliveries
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In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.
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This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or performing 3D map construction. For loop closure detection CAT-SLAM updates in constant time regardless of map size. We evaluate the effectiveness of CAT-SLAM on a 16km outdoor road network and determine its loop closure performance relative to FAB-MAP. CAT-SLAM recognizes 3 times the number of loop closures for the case where no false positives occur, demonstrating its potential use for robust loop closure detection in large environments.
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In this paper, we present a new algorithm for boosting visual template recall performance through a process of visual expectation. Visual expectation dynamically modifies the recognition thresholds of learnt visual templates based on recently matched templates, improving the recall of sequences of familiar places while keeping precision high, without any feedback from a mapping backend. We demonstrate the performance benefits of visual expectation using two 17 kilometer datasets gathered in an outdoor environment at two times separated by three weeks. The visual expectation algorithm provides up to a 100% improvement in recall. We also combine the visual expectation algorithm with the RatSLAM SLAM system and show how the algorithm enables successful mapping
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Teacher professional development provided by education advisors as one-off, centrally offered sessions does not always result in change in teacher knowledge, beliefs, attitudes or practice in the classroom. As the mathematics education advisor in this study, I set out to investigate a particular method of professional development so as to influence change in a practising classroom teacher’s knowledge and practices. The particular method of professional development utilised in this study was based on several principles of effective teacher professional development and saw me working regularly in a classroom with the classroom teacher as well as providing ongoing support for her for a full school year. The intention was to document the effects of this particular method of professional development in terms of the classroom teacher’s and my professional growth to provide insights for others working as education advisors. The professional development for the classroom teacher consisted of two components. The first was the co-operative development and implementation of a mental computation instructional program for the Year 3 class. The second component was the provision of ongoing support for the classroom teacher by the education advisor. The design of the professional development and the mental computation instructional program were progressively refined throughout the year. The education advisor fulfilled multiple roles in the study as teacher in the classroom, teacher educator working with the classroom teacher and researcher. Examples of the professional growth of the classroom teacher and the education advisor which occurred as sequences of changes (growth networks, Hollingsworth, 1999) in the domains of the professional world of the classroom teacher and education advisor were drawn from the large body of data collected through regular face-to-face and email communications between the classroom teacher and the education advisor as well as from transcripts of a structured interview. The Interconnected Model of Professional Growth (Clarke & Hollingsworth, 2002; Hollingsworth, 1999) was used to summarise and represent each example of the classroom teacher’s professional growth. A modified version of this model was used to summarise and represent the professional growth of the education advisor. This study confirmed that the method of professional development utilised could lead to significant teacher professional growth related directly to her work in the classroom. Using the Interconnected Model of Professional Growth to summarise and represent the classroom teacher’s professional growth and the modified version for my professional growth assisted with the recognition of examples of how we both changed. This model has potential to be used more widely by education advisors when preparing, implementing, evaluating and following-up on planned teacher professional development activities. The mental computation instructional program developed and trialled in the study was shown to be a successful way of sequencing and managing the teaching of mental computation strategies and related number sense understandings to Year 3 students. This study was conducted in one classroom, with one teacher in one school. The strength of this study was the depth of teacher support provided made possible by the particular method of the professional development, and the depth of analysis of the process. In another school, or with another teacher, this might not have been as successful. While I set out to change my practice as an education advisor I did not expect the depth of learning I experienced in terms of my knowledge, beliefs, attitudes and practices as an educator of teachers. This study has changed the way in which I plan to work as an education advisor in the future.
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This publication is the first in a series of scholarly reports on research-based practice related to the First Year Experience in Higher Education. This report synthesises evidence about practice-based initiatives and pragmatic approaches in Aotearoa (New Zealand) and Australia that aim to enhance the experience of commencing students in the higher education sector. Trends in policies, programs and practices ... examines the first year experience literature from 2000-2010. It acknowledges the uniqueness of the Australasian socio-political context and its influence on the interests and output of researchers. The review surveyed almost 400 empirical reports and conceptual discussions produced over the decade that dealt with the stakeholders, institutions and the higher education sector in Australasia. The literature is examined through two theoretical constructs or “lenses”: first, a set of first year curriculum design principles and second, the generational approach to describing the maturation of initiatives. These outcomes and suggested directions for further research provide the challenges and the opportunities for FYE adherents, both scholars and practitioners, to grapple with in the next decade.
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Physical inactivity is a serious concern both nationally and internationally. Despite the numerous benefits of performing regular physical activity, many individuals lead sedentary lifestyles. Of concern, though, is research showing that some population sub-groups are less likely to be active, such as parents of young children. Although there is a vast amount of research dedicated to understanding people.s physical activity-related behaviours, there is a paucity of research examining those factors that influence parental physical activity. More importantly, research applying theoretical models to understand physical activity decision-making among this at-risk population is limited. Given the current obesity epidemic, the decline in physical activity with parenthood, and the many social and health benefits associated with regular physical activity, it is important that adults with young children are sufficiently active. In light of the dearth of research examining parental physical activity and the scant research applying a theory-based approach to gain this understanding, the overarching aim of the current program of research was to adopt a mixed methods approach as well as use sound theoretical frameworks to understand the regular physical activity behaviour of mothers and fathers with young children. This program of research comprised of three distinct stages: a qualitative stage exploring individual, social, and psychological factors that influence parental regular physical activity (Stage 1); a quantitative stage identifying the important predictors of parental regular physical activity intentions and behaviour using sound theoretical frameworks and testing a single-item measure for assessing parental physical activity behaviour (Stage 2); and a qualitative stage exploring strategies for an intervention program aimed at increasing parental regular physical activity (Stage 3). As a thesis by publication, eight papers report the findings of this program of research; these papers are presented according to the distinct stages of investigation that guided this program of research. Stage One of the research program comprised a qualitative investigation using a focus group/interview methodology with parents of children younger than 5 years of age (N = 40; n = 21 mothers, n = 19 fathers) (Papers 1, 2, and 3). Drawing broadly on a social constructionist approach (Paper 1), thematic analytic methods revealed parents. understandings of physical activity (e.g., requires effort), patterns of physical activity-related behaviours (e.g., grab it when you can, declining physical activity habits), and how constructions of social role expectations might influence parents. physical activity decision making (e.g., creating an active family culture, guilt and selfishness). Drawing on the belief-based framework of the TPB (Paper 2), thematic content analytic methods revealed parents. commonly held beliefs about the advantages (e.g., improves parenting practices), disadvantages (e.g., interferes with commitments), barriers (e.g., time), and facilitators (e.g., social support) to performing regular physical activity. Parents. normative beliefs about social approval from important others or groups (e.g., spouse/partner) were also identified. Guided by theories of social support, Paper Three identified parents. perceptions about the specific social support dimensions that influence their physical activity decision making. Thematic content analysis identified instrumental (e.g., providing childcare, taking over chores), emotional (e.g., encouragement, companionship), and informational support (e.g., ideas and advice) as being important to the decision-making of parents in relation to their regular physical activity behaviour. The results revealed also that having support for being active is not straightforward (e.g., guilt-related issues inhibited the facilitative nature of social support for physical activity). Stage Two of the research program comprised a quantitative examination of parents. physical activity intentions and behaviour (Papers 4, 5, 6, and 7). Parents completed an extended TPB questionnaire at Time 1 (N = 580; n = 288 mothers, n = 292 fathers) and self-reported their physical activity at Time 2, 1 week later (N = 458; n = 252 mothers, n = 206 fathers). Paper Four revealed key behavioural (e.g., improving parenting practices), normative (e.g., people I exercise with), and control (e.g., lack of time) beliefs as significant independent predictors of parental physical activity. A test of the TPB augmented to include the constructs of self-determined motivation and planning was assessed in Paper Five. The findings revealed that the effect of self-determined motivation on intention was fully mediated by the TPB variables and the impact of intention on behaviour was partially mediated by the planning variables. Slight differences in the model.s motivational sequence between the sexes were also noted. Paper Six investigated, within a TPB framework, a range of social influences on parents. intentions to be active. For both sexes, attitude, perceived behavioural control, group norms, friend general support, and an active parent identity predicted intentions, with subjective norms and family support further predicting mothers. intentions and descriptive norms further predicting fathers. intentions. Finally, the measurement of parental physical activity was investigated in Paper Seven of Stage Two. The results showed that parents are at risk of low levels of physical activity, with the findings also revealing validation support for a brief single-item physical activity measure. Stage Three of the research program comprised a qualitative examination of parents. (N = 12; n = 6 mothers, n = 6 fathers) ideas for strategies that may be useful for developing and delivering an intervention program aimed at increasing parental physical activity (Paper 8). Parents revealed a range of strategies for what to include in a physical activity intervention designed for parents of young children. For example, parents identified persuasion and information type messages, problem-solving strategies that engage parents in generating a priority list of their lifestyle commitments, and behavioural modification techniques such as goal setting and incentives. Social intervention strategies (e.g., social comparison, counselling) and environmental approaches (e.g., community-based integrative parent/child programs) were also identified as was a skill-based strategy in helping parents generate a flexible life/family plan. Additionally, a range of strategies for how to best deliver a parental physical activity intervention was discussed. Taken as a whole, Paper Eight found that adopting a multifaceted approach in both the design and implementation of a resultant physical activity intervention may be useful in helping to increase parental physical activity. Overall, this program of research found support for parents as a unique group who hold both similar and distinctive perceptions about regular physical activity to the general adult population. Thus, these findings highlight the importance of targeting intervention strategies for parents of young children. Additionally, the findings suggest that it might also be useful to tailor some messages specifically to each sex. Effective promotion of physical activity in parents of young children is essential given the low rate of activity in this population. Results from this program of research highlight parents as an at-risk group for inactivity and provide an important first step in identifying the factors that influence both mothers. and fathers. physical activity decision making. These findings, in turn, provide a foundation on which to build effective intervention programs aimed at increasing parents. regular physical activity which is essential for ensuring the health and well-being of parents with young children.
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Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.
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Overcoming many of the constraints to early stage investment in biofuels production from sugarcane bagasse in Australia requires an understanding of the complex technical, economic and systemic challenges associated with the transition of established sugar industry structures from single product agri-businesses to new diversified multi-product biorefineries. While positive investment decisions in new infrastructure requires technically feasible solutions and the attainment of project economic investment thresholds, many other systemic factors will influence the investment decision. These factors include the interrelationships between feedstock availability and energy use, competing product alternatives, technology acceptance and perceptions of project uncertainty and risk. This thesis explores the feasibility of a new cellulosic ethanol industry in Australia based on the large sugarcane fibre (bagasse) resource available. The research explores industry feasibility from multiple angles including the challenges of integrating ethanol production into an established sugarcane processing system, scoping the economic drivers and key variables relating to bioethanol projects and considering the impact of emerging technologies in improving industry feasibility. The opportunities available from pilot scale technology demonstration are also addressed. Systems analysis techniques are used to explore the interrelationships between the existing sugarcane industry and the developing cellulosic biofuels industry. This analysis has resulted in the development of a conceptual framework for a bagassebased cellulosic ethanol industry in Australia and uses this framework to assess the uncertainty in key project factors and investment risk. The analysis showed that the fundamental issue affecting investment in a cellulosic ethanol industry from sugarcane in Australia is the uncertainty in the future price of ethanol and government support that reduces the risks associated with early stage investment is likely to be necessary to promote commercialisation of this novel technology. Comprehensive techno-economic models have been developed and used to assess the potential quantum of ethanol production from sugarcane in Australia, to assess the feasibility of a soda-based biorefinery at the Racecourse Sugar Mill in Mackay, Queensland and to assess the feasibility of reducing the cost of production of fermentable sugars from the in-planta expression of cellulases in sugarcane in Australia. These assessments show that ethanol from sugarcane in Australia has the potential to make a significant contribution to reducing Australia’s transportation fuel requirements from fossil fuels and that economically viable projects exist depending upon assumptions relating to product price, ethanol taxation arrangements and greenhouse gas emission reduction incentives. The conceptual design and development of a novel pilot scale cellulosic ethanol research and development facility is also reported in this thesis. The establishment of this facility enables the technical and economic feasibility of new technologies to be assessed in a multi-partner, collaborative environment. As a key outcome of this work, this study has delivered a facility that will enable novel cellulosic ethanol technologies to be assessed in a low investment risk environment, reducing the potential risks associated with early stage investment in commercial projects and hence promoting more rapid technology uptake. While the study has focussed on an exploration of the feasibility of a commercial cellulosic ethanol industry from sugarcane in Australia, many of the same key issues will be of relevance to other sugarcane industries throughout the world seeking diversification of revenue through the implementation of novel cellulosic ethanol technologies.
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There is significant interest in Human-computer interaction methods that assist in the design of applications for use by children. Many of these approaches draw upon standard HCI methods,such as personas, scenarios, and probes. However, often these techniques require communication and kinds of thinking skills that are designer centred,which prevents children with Autism Spectrum Disorders or other learning and communication disabilities from being able to participate. This study investigates methods that might be used with children with ASD or other learning and communication disabilities to inspire the design of technology based intervention approaches to support their speech and language development. Similar to Iversen and Brodersen, we argue that children with ASD should not be treated as being in some way “cognitively incomplete”. Rather they are experts in their everyday lives and we cannot design future IT without involving them. However, how do we involve them Instead of beginning with HCI methods, we draw upon easy to use technologies and methods used in the therapy professions for child engagement, particularly utilizing the approaches of Hanen (2011) and Greenspan (1998). These approaches emphasize following the child’s lead and ensuring that the child always has a legitimate turn at a detailed level of interaction. In a pilot project, we have studied a child’s interactions with their parents about activities over which they have control – photos that they have taken at school on an iPad. The iPad was simple enough for this child with ASD to use and they enjoyed taking and reviewing photos. We use this small case study as an example of a child-led approach for a child with ASD. We examine interactions from this study in order to assess the possibilities and limitations of the child-led approach for supporting the design of technology based interventions to support speech and language development.
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Autonomous guidance of agricultural vehiclesis vital as mechanized farming production becomes more prevalent. It is crucial that tractor-trailers are guided with accuracy in both lateral and longitudinal directions, whilst being affected by large disturbance forces, or slips, owing to uncertain and undulating terrain. Successful research has been concentrated on trajectory control which can provide longitudinal and lateral accuracy if the vehicle moves without sliding, and the trailer is passive. In this paper, the problem of robust trajectory tracking along straight and circular paths of a tractor-steerable trailer is addressed. By utilizing a robust combination of backstepping and nonlinear PI control, a robust, nonlinear controller is proposed. For vehicles subjected to sliding, the proposed controller makes the lateral deviations and the orientation errors of the tractor and trailer converge to a neighborhood near the origin. Simulation results are presented to illustrate that the suggested controller ensures precise trajectory tracking in the presence of slip.
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Materials with one-dimensional (1D) nanostructure are important for catalysis. They are the preferred building blocks for catalytic nanoarchitecture, and can be used to fabricate designer catalysts. In this thesis, one such material, alumina nanofibre, was used as a precursor to prepare a range of nanocomposite catalysts. Utilising the specific properties of alumina nanofibres, a novel approach was developed to prepare macro-mesoporous nanocomposites, which consist of a stacked, fibrous nanocomposite with a core-shell structure. Two kinds of fibrous ZrO2/Al2O3 and TiO2/Al2O3 nanocomposites were successfully synthesised using boehmite nanofibers as a hard temperate and followed by a simple calcination. The alumina nanofibres provide the resultant nanocomposites with good thermal stability and mechanical stability. A series of one-dimensional (1D) zirconia/alumina nanocomposites were prepared by the deposition of zirconium species onto the 3D framework of boehmite nanofibres formed by dispersing boehmite nanofibres into a butanol solution, followed by calcination at 773 K. The materials were characterised by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), and Fourier Transform Infrared spectroscopy (FT-IR). The results demonstrated that when the molar percentage, X, X=100*Zr/(Al+Zr), was > 30%, extremely long ZrO2/Al2O3 composite nanorods with evenly distributed ZrO2 nanocrystals formed on their surface. The stacking of such nanorods gave rise to a new kind of macroporous material without the use of any organic space filler\template or other specific drying techniques. The mechanism for the formation of these long ZrO2/Al2O3 composite nanorods is proposed in this work. A series of solid-superacid catalysts were synthesised from fibrous ZrO2/Al2O3 core and shell nanocomposites. In this series, the zirconium molar percentage was varied from 2 % to 50 %. The ZrO2/Al2O3 nanocomposites and their solid superacid counterparts were characterised by a variety of techniques including 27Al MAS-NMR, SEM, TEM, XPS, Nitrogen adsorption and Infrared Emission Spectroscopy. NMR results show that the interaction between zirconia species and alumina strongly correlates with pentacoordinated aluminium sites. This can also be detected by the change in binding energy of the 3d electrons of the zirconium. The acidity of the obtained superacids was tested by using them as catalysts for the benzolyation of toluene. It was found that a sample with a 50 % zirconium molar percentage possessed the highest surface acidity equalling that of pristine sulfated zirconia despite the reduced mass of zirconia. Preparation of hierarchically macro-mesoporous catalyst by loading nanocrystallites on the framework of alumina bundles can provide an alternative system to design advanced nanocomposite catalyst with enhanced performance. A series of macro-mesoporous TiO2/Al2O3 nanocomposites with different morphologies were synthesised. The materials were calcined at 723 K and were characterised by X-ray diffraction (XRD), Scanning electron microscopy (SEM), Transmission electron microscope (TEM), N2 adsorption/desorption, Infrared Emission Spectroscopy (IES), and UV-visible spectroscopy (UV-visible). A modified approach was proposed for the synthesis of 1D (fibrous) nanocomposite with higher Ti/Al molar ratio (2:1) at lower temperature (<100oC), which makes it possible to synthesize such materials on industrial scale. The performances of a series of resultant TiO2/Al2O3 nanocomposites with different morphologies were evaluated as a photocatalyst for the phenol degradation under UV irradiation. The photocatalyst (Ti/Al =2) with fibrous morphology exhibits higher activity than that of the photocatalyst with microspherical morphology which indeed has the highest Ti to Al molar ratio (Ti/Al =3) in the series of as-synthesised hierarchical TiO2/Al2O3 nanocomposites. Furthermore, the photocatalytic performances, for the fibrous nanocomposites with Ti/Al=2, were optimized by calcination at elevated temperatures. The nanocomposite prepared by calcination at 750oC exhibits the highest catalytic activity, and its performance per TiO2 unit is very close to that of the gold standard, Degussa P 25. This work also emphasizes two advantages of the nanocomposites with fibrous morphology: (1) the resistance to sintering, and (2) good catalyst recovery.
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This article introduces a model for group facilitation in the humanities based on Carl Rogers’s model for group psychotherapy. Certain aspects of Rogers’s reflective learning strategies are re-appraised and principles, specific only to psychotherapy, are introduced. Five of Rogers’s axioms are applied to the tutorial discussion model: a non-directive approach, climate-setting, facilitation, reflective listening and positive regard. The model, which has been trialed in tutorials at The University of Queensland, encourages self-direction, active learning and critical thinking.
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The existing Collaborative Filtering (CF) technique that has been widely applied by e-commerce sites requires a large amount of ratings data to make meaningful recommendations. It is not directly applicable for recommending products that are not frequently purchased by users, such as cars and houses, as it is difficult to collect rating data for such products from the users. Many of the e-commerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user's query are retrieved and recommended to the user. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their online navigation behaviour. This paper proposes to integrate collaborative filtering and search-based techniques to provide personalized recommendations for infrequently purchased products. Two different techniques are proposed, namely CFRRobin and CFAg Query. Instead of using the target user's query to search for products as normal search based systems do, the CFRRobin technique uses the products in which the target user's neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAg Query technique uses the products that the user's neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAg Query perform better than the standard Collaborative Filtering (CF) and the Basic Search (BS) approaches, which are widely applied by the current e-commerce applications. The CFRRobin and CFAg Query approaches also outperform the e- isting query expansion (QE) technique that was proposed for recommending infrequently purchased products.
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For more than a decade research in the field of context aware computing has aimed to find ways to exploit situational information that can be detected by mobile computing and sensor technologies. The goal is to provide people with new and improved applications, enhanced functionality and better use experience (Dey, 2001). Early applications focused on representing or computing on physical parameters, such as showing your location and the location of people or things around you. Such applications might show where the next bus is, which of your friends is in the vicinity and so on. With the advent of social networking software and microblogging sites such as Facebook and Twitter, recommender systems and so on context-aware computing is moving towards mining the social web in order to provide better representations and understanding of context, including social context. In this paper we begin by recapping different theoretical framings of context. We then discuss the problem of context- aware computing from a design perspective.
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A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.