852 resultados para content-based filtering
Resumo:
Background Postnatal women (<12 months postpartum) are at increased risk of physical inactivity. Purpose To evaluate the efficacy and feasibility of a theory-based physical activity (PA) intervention delivered to postnatal women primarily via mobile telephone short message service (SMS). Methods Eighty-eight women were randomized to the intervention (n=45) or minimal contact control (n=43) condition. The 12-week intervention consisted of a face-to-face PA goal-setting consultation, a goal-setting magnet, three to five personally tailored SMS/week and a nominated support person who received two SMS per week. SMS content targeted constructs of social cognitive theory. Frequency (days/week) and duration (min/week) of PA participation and walking for exercise were assessed via self-report at baseline, 6 and 13 weeks. Results Intervention participants increased PA frequency by 1.82 days/week (SE±0.18) by 13 weeks (F(2,85)=4.46, p=0.038) and walking for exercise frequency by 1.08 days/ week (SE±0.24) by 13 weeks (F(2,85)=5.38, p=0.02). Positive trends were observed for duration (min/week) of PA and walking for exercise. Conclusions Intervention exposure resulted in increased frequency of PA and walking for exercise in postnatal women.
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Reviews into teacher education emphasise the need for preservice teachers to have more school-based experiences. In this study, a school-based experience was organised within a nine-week science curriculum university unit that allowed preservice teachers’ repeated experiences in teaching primary science. This research uses a survey, questionnaire with extended written responses, and researcher observations to investigate preservice teachers’ (n=38) learning experiences in two school settings. Survey results indicated that the majority of these preservice teachers either agreed or strongly agreed that school-based experiences developed their: personal-professional skill development (100%); system requirements (range: 81-100%); teaching practices (81-100%); student behaviour management (range: 94-100%); providing student feedback (89-94%); and reflection on practice (92-100%). Qualitative data provided insights into their development particularly for science content knowledge and receiving positive reinforcement on effective teaching behaviours. According to these preservice teachers, the school-based experiences facilitated “teachable moments – having the knowledge or skills to run with students’ questions or ideas” and allowed preservice teachers to “critically reflect between groups to make the task flow better”. Embedding school-based experiences needs to be part of each and every preservice teacher education unit so preservice teachers can develop confidence, knowledge and skills within authentic school contexts.
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Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.
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This paper presents a modified approach to evaluate access control policy similarity and dissimilarity based on the proposal by Lin et al. (2007). Lin et al.'s policy similarity approach is intended as a filter stage which identifies similar XACML policies that can be analysed further using more computationally demanding techniques based on model checking or logical reasoning. This paper improves the approach of computing similarity of Lin et al. and also proposes a mechanism to calculate a dissimilarity score by identifying related policies that are likely to produce different access decisions. Departing from the original algorithm, the modifications take into account the policy obligation, rule or policy combining algorithm and the operators between attribute name and value. The algorithms are useful in activities involving parties from multiple security domains such as secured collaboration or secured task distribution. The algorithms allow various comparison options for evaluating policies while retaining control over the restriction level via a number of thresholds and weight factors.
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Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.
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It is a big challenge to clearly identify the boundary between positive and negative streams for information filtering systems. 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 the RCV1 data collection, and substantial experiments show that the proposed approach achieves encouraging performance and the performance is also consistent for adaptive filtering as well.
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New technologies have the potential to both expose children to and protect them from television news footage likely to disturb or frighten. The advent of cheap, portable and widely available digital technology has vastly increased the possibility of violent news events being captured and potentially broadcast. This material has the potential to be particularly disturbing and harmful to young children. But on the flipside, available digital technology could be used to build in protection for young viewers especially when it comes to preserving scheduled television programming and guarding against violent content being broadcast during live crosses from known trouble spots. Based on interviews with news directors, parents and a review of published material two recommendations are put forward: 1. Digital television technology should be employed to prevent news events "overtaking" scheduled children's programming and to protect safe harbours placed in the classifications zones to protect children. 2. Broadcasters should regain control of the images that go to air during "live" feeds from obviously volatile situations by building in short delays in G classification zones.
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Hybrid system representations have been applied to many challenging modeling situations. In these hybrid system representations, a mixture of continuous and discrete states is used to capture the dominating behavioural features of a nonlinear, possible uncertain, model under approximation. Unfortunately, the problem of how to best design a suitable hybrid system model has not yet been fully addressed. This paper proposes a new joint state measurement relative entropy rate based approach for this design purpose. Design examples and simulation studies are presented which highlight the benefits of our proposed design approaches.
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Data preprocessing is widely recognized as an important stage in anomaly detection. This paper reviews the data preprocessing techniques used by anomaly-based network intrusion detection systems (NIDS), concentrating on which aspects of the network traffic are analyzed, and what feature construction and selection methods have been used. Motivation for the paper comes from the large impact data preprocessing has on the accuracy and capability of anomaly-based NIDS. The review finds that many NIDS limit their view of network traffic to the TCP/IP packet headers. Time-based statistics can be derived from these headers to detect network scans, network worm behavior, and denial of service attacks. A number of other NIDS perform deeper inspection of request packets to detect attacks against network services and network applications. More recent approaches analyze full service responses to detect attacks targeting clients. The review covers a wide range of NIDS, highlighting which classes of attack are detectable by each of these approaches. Data preprocessing is found to predominantly rely on expert domain knowledge for identifying the most relevant parts of network traffic and for constructing the initial candidate set of traffic features. On the other hand, automated methods have been widely used for feature extraction to reduce data dimensionality, and feature selection to find the most relevant subset of features from this candidate set. The review shows a trend toward deeper packet inspection to construct more relevant features through targeted content parsing. These context sensitive features are required to detect current attacks.
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Some initial EUVL patterning results for polycarbonate based non-chemically amplified resists are presented. Without full optimization the developer a resolution of 60 nm line spaces could be obtained. With slight overexposure (1.4 × E0) 43.5 nm lines at a half pitch of 50 nm could be printed. At 2x E0 a 28.6 nm lines at a half pitch of 50 nm could be obtained with a LER that was just above expected for mask roughness. Upon being irradiated with EUV photons, these polymers undergo chain scission with the loss of carbon dioxide and carbon monoxide. The remaining photoproducts appear to be non-volatile under standard EUV irradiation conditions, but do exhibit increased solubility in developer compared to the unirradiated polymer. The sensitivity of the polymers to EUV light is related to their oxygen content and ways to increase the sensitivity of the polymers to 10 mJ cm-2 is discussed.
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Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Hence, there is an urgent need to monitor our infrastructures to prolong their life span, at the same time catering for heavier and faster moving traffics. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for structural health monitoring. The CNTs, a key material in nanotechnology has aroused great interest in the research community due to their remarkable mechanical, electrochemical, piezoresistive and other physical properties. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties when subjected to chemical solutions, to simulate a chemical reaction due to corrosion and real life corrosion experimental tests. The electrical resistance of the sensor electrode was dramatically changed due to corrosion. The novel sensor is expected to effectively detect corrosion in structures based on the measurement of electrical impedances of the CNT composite.
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In Australia, there is a crisis in science education with students becoming disengaged with canonical science in the middle years of schooling. One recent initiative that aims to improve student interest and motivation without diminishing conceptual understanding is the context-based approach. Contextual units that connect the canonical science with the students’ real world of their local community have been used in the senior years but are new in the middle years. This ethnographic study explored the learning transactions that occurred in one 9th grade science class studying an Environmental Science unit for 11 weeks. Data were derived from field notes, audio and video recorded conversations, interviews, student journals and classroom documents with a particular focus on two selected groups of students. Data were analysed qualitatively through coding for emergent themes. This paper presents an outline of the program and discussion of three assertions derived from the preliminary analysis of the data. Firstly, an integrated, coherent sequence of learning experiences that included weekly visits to a creek adjacent to the school enabled the teacher to contextualise the science in the students’ local community. Secondly, content was predominantly taught on a need-to-know basis and thirdly, the lesson sequence aligned with a model for context-based teaching. Research, teaching and policy implications of these results for promoting the context-based teaching of science in the middle years are discussed.
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This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.
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Adults diagnosed with primary brain tumours often experience physical, cognitive and neuropsychiatric impairments and decline in quality of life. Although disease and treatment-related information is commonly provided to cancer patients and carers, newly diagnosed brain tumour patients and their carers report unmet information needs. Few interventions have been designed or proven to address these information needs. Accordingly, a three-study research program, that incorporated both qualitative and quantitative research methods, was designed to: 1) identify and select an intervention to improve the provision of information, and meet the needs of patients with a brain tumour; 2) use an evidence-based approach to establish the content, language and format for the intervention; and 3) assess the acceptability of the intervention, and the feasibility of evaluation, with newly diagnosed brain tumour patients. Study 1: Structured concept mapping techniques were undertaken with 30 health professionals, who identified strategies or items for improving care, and rated each of 42 items for importance, feasibility, and the extent to which such care was provided. Participants also provided data to interpret the relationship between items, which were translated into ‘maps’ of relationships between information and other aspects of health care using multidimensional scaling and hierarchical cluster analysis. Results were discussed by participants in small groups and individual interviews to understand the ratings, and facilitators and barriers to implementation. A care coordinator was rated as the most important strategy by health professionals. Two items directly related to information provision were also seen as highly important: "information to enable the patient or carer to ask questions" and "for doctors to encourage patients to ask questions". Qualitative analyses revealed that information provision was individualised, depending on patients’ information needs and preferences, demographic variables and distress, the characteristics of health professionals who provide information, the relationship between the individual patient and health professional, and influenced by the fragmented nature of the health care system. Based on quantitative and qualitative findings, a brain tumour specific question prompt list (QPL) was chosen for development and feasibility testing. A QPL consists of a list of questions that patients and carers may want to ask their doctors. It is designed to encourage the asking of questions in the medical consultation, allowing patients to control the content, and amount of information provided by health professionals. Study 2: The initial structure and content of the brain tumour specific QPL developed was based upon thematic analyses of 1) patient materials for brain tumour patients, 2) QPLs designed for other patient populations, and 3) clinical practice guidelines for the psychosocial care of glioma patients. An iterative process of review and refinement of content was undertaken via telephone interviews with a convenience sample of 18 patients and/or carers. Successive drafts of QPLs were sent to patients and carers and changes made until no new topics or suggestions arose in four successive interviews (saturation). Once QPL content was established, readability analyses and redrafting were conducted to achieve a sixth-grade reading level. The draft QPL was also reviewed by eight health professionals, and shortened and modified based on their feedback. Professional design of the QPL was conducted and sent to patients and carers for further review. The final QPL contained questions in seven colour-coded sections: 1) diagnosis; 2) prognosis; 3) symptoms and problems; 4) treatment; 5) support; 6) after treatment finishes; and 7) the health professional team. Study 3: A feasibility study was conducted to determine the acceptability of the QPL and the appropriateness of methods, to inform a potential future randomised trial to evaluate its effectiveness. A pre-test post-test design was used with a nonrandomised control group. The control group was provided with ‘standard information’, the intervention group with ‘standard information’ plus the QPL. The primary outcome measure was acceptability of the QPL to participants. Twenty patients from four hospitals were recruited a median of 1 month (range 0-46 months) after diagnosis, and 17 completed baseline and follow-up interviews. Six participants would have preferred to receive the information booklet (standard information or QPL) at a different time, most commonly at diagnosis. Seven participants reported on the acceptability of the QPL: all said that the QPL was helpful, and that it contained questions that were useful to them; six said it made it easier to ask questions. Compared with control group participants’ ratings of ‘standard information’, QPL group participants’ views of the QPL were more positive; the QPL had been read more times, was less likely to be reported as ‘overwhelming’ to read, and was more likely to prompt participants to ask questions of their health professionals. The results from the three studies of this research program add to the body of literature on information provision for brain tumour patients. Together, these studies suggest that a QPL may be appropriate for the neuro-oncology setting and acceptable to patients. The QPL aims to assist patients to express their information needs, enabling health professionals to better provide the type and amount of information that patients need to prepare for treatment and the future. This may help health professionals meet the challenge of giving patients sufficient information, without providing ‘too much’ or ‘unnecessary’ information, or taking away hope. Future studies with rigorous designs are now needed to determine the effectiveness of the QPL.
Resumo:
Mobile phones are now powerful and pervasive making them ideal information browsers. The Internet has revolutionized our lives and is a major knowledge sharing media. However, many mobile phone users cannot access the Internet (for financial or technical reasons) and so the mobile Internet has not been fully realized. We propose a novel content delivery network based on both a factual and speculative analysis of today’s technology and analyze its feasibility. If adopted people living in remote regions without Internet will be able to access essential (static) information with periodic updates.