885 resultados para Knowledge-based information gathering, ontology, world knowledge base, user background knowledge, local instance repository, user information needs


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In this paper the author reports on the introduction of the flipped classroom integrating located, online and virtual world learning environments to support the collaborative lived experiences of a group of students and the educator participating in a higher education undergraduate art unit, Navigating the Visual World. A qualitative narrative methodology, A/r/tography, incorporating both image making and textual recording is used to explore and identify interwoven aspects of the artist/ researcher/ educator relationship in the creative artistic process of exploring concepts of identity within inquiry based art practice. Selected student examples, including a collaborative group assessment project demonstrate effective student engagement with experiential blended learning within the flipped classroom.

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Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

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The Gascoyne-Murchison region of Western Australia experiences an arid to semi-arid climate with a highly variable temporal and spatial rainfall distribution. The region has around 39.2 million hectares available for pastoral lease and supports predominantly catle and sheep grazing leases. In recent years a number of climate forecasting systems have been available offering rainfall probabilities with different lead times and a forecast period; however, the extent to which these systems are capable of fulfilling the requirements of the local pastoralists is still ambiguous. Issues can range from ensuring forecasts are issued with sufficient lead time to enable key planning or decisions to be revoked or altered, to ensuring forecast language is simple and clear, to negate possible misunderstandings in interpretation. A climate research project sought to provide an objective method to determine which available forecasting systems had the greatest forecasting skill at times of the year relevant to local property management. To aid this climate research project, the study reported here was undertaken with an overall objective of exploring local pastoralists' climate information needs. We also explored how well they understand common climate forecast terms such as 'mean', median' and 'probability', and how they interpret and apply forecast information to decisions. A stratified, proportional random sampling was used for the purpose of deriving the representative sample based on rainfall-enterprise combinations. In order to provide more time for decision-making than existing operational forecasts that are issued with zero lead time, pastoralists requested that forecasts be issued for May-July and January-March with lead times counting down from 4 to 0 months. We found forecasts of between 20 and 50 mm break-of-season or follow-up rainfall were likely to influence decisions. Eighty percent of pastoralists demonstrated in a test question that they had a poor technical understanding of how to interpret the standard wording of a probabilistic median rainfall forecast. this is worthy of further research to investigate whether inappropriate management decisions are being made because the forecasts are being misunderstood. We found more than half the respondents regularly access and use weather and climate forecasts or outlook information from a range of sources and almost three-quarters considered climate information or tools useful, with preferred methods for accessing this information by email, faxback service, internet and the Department of Agriculture Western Australia's Pastoral Memo. Despite differences in enterprise types and rainfall seasonality across the region we found seasonal climate forecasting needs were relatively consistent. It became clear that providing basic training and working with pastoralists to help them understand regional climatic drivers, climate terminology and jargon, and the best ways to apply the forecasts to enhance decision-making are important to improve their use of information. Consideration could also be given to engaging a range of producers to write the climate forecasts themselves in the language they use and understand, in consultation with the scientists who prepare the forecasts.

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In Australia, plantation forests have increased in area by around 50% in the last 10 years. While this expansion has seen a modest 8% increase for softwoods, hardwood plantations have dramatically increased by over 150%. Hardwood plantations grown for high quality sawn timber are slow to mature, with a crop rotation time potentially reaching 35 years. With this long lead-time, each year the risk from fire, pests and adverse weather events dramatically increases, while not translating into substantially higher financial returns to the grower. To justify continued expansion of Australia's current hardwood plantation estate, it is becoming necessary to develop higher value end-uses for both pulpwood and smaller 'sawlog' resources. The use of the low commercial value stems currently culled during thinning appears to be a necessary option to improve the industry profitability and win new markets. This paper provides background information on Australian forests and plantations and gives an overview of potential uses of Australian hardwood plantation thinning logs, as their mechanical properties. More specifically, this paper reports on the development of structural Veneer Based Composite (VBC) products from hardwood plantation thinning logs, taking advantage of a recent technology developed to optimise the processing of this resource. The process used to manufacture a range of hollow-form veneer laminated structural products is presented and the mechanical characteristics of these products are investigated in the companion paper. The market applications and future opportunities for the proposed products are also discussed, as potential benefits to the timber industry. © RILEM 2014.

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We develop an optimal, distributed, and low feedback timer-based selection scheme to enable next generation rate-adaptive wireless systems to exploit multi-user diversity. In our scheme, each user sets a timer depending on its signal to noise ratio (SNR) and transmits a small packet to identify itself when its timer expires. When the SNR-to-timer mapping is monotone non-decreasing, timers of users with better SNRs expire earlier. Thus, the base station (BS) simply selects the first user whose timer expiry it can detect, and transmits data to it at as high a rate as reliably possible. However, timers that expire too close to one another cannot be detected by the BS due to collisions. We characterize in detail the structure of the SNR-to-timer mapping that optimally handles these collisions to maximize the average data rate. We prove that the optimal timer values take only a discrete set of values, and that the rate adaptation policy strongly influences the optimal scheme's structure. The optimal average rate is very close to that of ideal selection in which the BS always selects highest rate user, and is much higher than that of the popular, but ad hoc, timer schemes considered in the literature.

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As alternate care levels are transferred from hospital to community settings, health care workers in long term care are caring for individuals where conditions are more medically complex. In response to this situation decision makers in long term care are pursuing the goal of practice based on the best evidence. Identifying the information needs of health care workers in this environment represents the first step towards cultivating a best practice culture in long term care. The purpose of this study was to identify what information resources staff need to improve clinical and managerial decision making. The perceptions of health care workers at two long term care organizations were investigated through quantitative and qualitative methods, using a questionnaire and focus groups. In each of the settings there were gaps in the availability of resources and perceived needs for education. The findings from both settings revealed the need for more information resources to assist staff to improve individual care of residents and develop better approaches to health problems.

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A new two-level real-time vehicle detection method is proposed in order to meet the robustness and efficiency requirements of real world applications. At the high level, pixels of the background image are classified into three categories according to the characteristics of Red, Green, Blue (RGB) curves. The robustness of the classification is further enhanced by using
line detection and pattern connectivity. At the lower level, an exponential forgetting algorithm with adaptive parameters for different categories is utilised to calculate the background and reduce the distortion by the small motion of video cameras. Scene tests show that the proposed method is more robust and faster than previous methods, which is very suitable for real-time vehicle detection in outdoor environments, especially concerning locations where the level of illumination changes frequently and speed detection is important.

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Whereas user participation has been embraced worldwide as a means to provide better patient outcomes, the implementation of formative, action research approaches in online health information has remained under-explored. The purpose of this study is to present an action research-based methodology that allows the scoping of health information and design needs in complex, multi-user online environments. The project's four main stages were informed by an iterative, formative approach involving continuous expert and user evaluation. The study suggests that an action research-inspired formative approach can be successfully employed to generate user-participation. Moreover, sustained user-participation effectively addresses most quality issues regarding content, language, and accessibility raised in the recent literature. The paper concludes that an action research approach geared to develop online health resources deserves more attention.

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This study unites the concepts of self-directed learning and information literacy in the external higher education environment. It asserts that many attempts by librarians at building better working relationships with distance educators have failed because the approaches of distance educators to the information needs of students are not adequately addressed. This exploratory and qualitatively based study examines the approaches of ten distance educators at Southern Cross University (SCU) to the information needs of their external students. It then makes recommendations based on these interviews which aim to improve relationships and co-operation between libraries and distance educators and to promote self-directed learning approaches by external students.

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Even though the importance of the local monotonicity property for function approximation problems is well established, there are relative few investigations addressing issues related to the fulfillment of the local monotonicity property in Fuzzy Inference System (FIS) modeling. We have previously conducted a preliminary study on the local monotonicity property of FIS models, with the assumption that the extrema point(s) (i.e., the maximum and/or minimum point(s)) is either known precisely or totally unknown. However, in some practical situations, the extrema point(s) can be known imprecisely (as an interval or a fuzzy set). In this paper, the imprecise information is exploited to construct an FIS model that fulfills the local monotonicity property. A procedure to estimate the extrema point(s) of a function is devised. Applicability of the findings to a datadriven modeling problem is further demonstrated.

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A more natural, intuitive, user-friendly, and less intrusive Human–Computer interface for controlling an application by executing hand gestures is presented. For this purpose, a robust vision-based hand-gesture recognition system has been developed, and a new database has been created to test it. The system is divided into three stages: detection, tracking, and recognition. The detection stage searches in every frame of a video sequence potential hand poses using a binary Support Vector Machine classifier and Local Binary Patterns as feature vectors. These detections are employed as input of a tracker to generate a spatio-temporal trajectory of hand poses. Finally, the recognition stage segments a spatio-temporal volume of data using the obtained trajectories, and compute a video descriptor called Volumetric Spatiograms of Local Binary Patterns (VS-LBP), which is delivered to a bank of SVM classifiers to perform the gesture recognition. The VS-LBP is a novel video descriptor that constitutes one of the most important contributions of the paper, which is able to provide much richer spatio-temporal information than other existing approaches in the state of the art with a manageable computational cost. Excellent results have been obtained outperforming other approaches of the state of the art.

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As a rural state, Ohio has a vital interest in addressing rural health and information needs. NetWellness is a Web-based consumer health information service that focuses on the needs of the residents of Ohio. Health sciences faculty from the state's three Carnegie Research I universities—University of Cincinnati, Case Western Reserve University, and The Ohio State University—create and evaluate content and provide Ask an Expert service to all visitors. Through partnerships at the state and local levels, involving public, private, commercial, and noncommercial organizations, NetWellness has grown from a regional demonstration project in 1995 to a key statewide service. Collaboration with public libraries, complemented by alliances with kindergarten through twelfth grade agencies, makes NetWellness Ohio's essential health information resource.

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This study aimed to identify: i) the prevalence of malnutrition according to the scored Patient Generated-Subjective Global Assessment (PG-SGA); ii) utilization of available nutrition resources; iii) patient nutrition information needs; and iv) external sources of nutrition information. An observational, cross-sectional study was undertaken at an Australian public hospital on 191 patients receiving oncology services. According to PG-SGA, 49% of patients were malnourished and 46% required improved symptom management and/or nutrition intervention. Commonly reported nutrition-impact symptoms included: peculiar tastes (31%), no appetite (24%) and nausea (24%). External sources of nutrition information were accessed by 37%, with popular choices being media/internet (n=19) and family/friends (n=13). In a sub-sample (n=65), 32 patients were aware of the available nutrition resources, 23 thought the information sufficient and 19 patients had actually read them. Additional information on supplements and modifying side effects was requested by 26 patients. Malnutrition is common in oncology patients receiving treatment at an Australian public hospital and almost half require improved symptom management and/or nutrition intervention. Patients who read the available nutrition information found it useful, however awareness of these nutrition resources and the provision of information on supplementation and managing symptoms requires attention.

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Searching for health advice on the web is becoming increasingly common. Because of the great importance of this activity for patients and clinicians and the effect that incorrect information may have on health outcomes, it is critical to present relevant and valuable information to a searcher. Previous evaluation campaigns on health information retrieval (IR) have provided benchmarks that have been widely used to improve health IR and record these improvements. However, in general these benchmarks have targeted the specialised information needs of physicians and other healthcare workers. In this paper, we describe the development of a new collection for evaluation of effectiveness in IR seeking to satisfy the health information needs of patients. Our methodology features a novel way to create statements of patients’ information needs using realistic short queries associated with patient discharge summaries, which provide details of patient disorders. We adopt a scenario where the patient then creates a query to seek information relating to these disorders. Thus, discharge summaries provide us with a means to create contextually driven search statements, since they may include details on the stage of the disease, family history etc. The collection will be used for the first time as part of the ShARe/-CLEF 2013 eHealth Evaluation Lab, which focuses on natural language processing and IR for clinical care.