669 resultados para Measuring method


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The Child Feeding Questionnaire (CFQ) developed by Birch and colleagues (2001) is a widely used tool for measuring parental feeding beliefs, attitudes and practices. However, the appropriateness of the CFQ for use with Chinese populations is unknown. This study tested the construct validity of a novel Chinese version of the CFQ using confirmatory factor analysis (CFA). Participants included a convenience sample of 254 Chinese-Australian mothers of children aged 1-4 years. Prior to testing, the questionnaire was translated into Chinese using a translation-back-translation method, one item was re-worded to be culturally appropriate, a new item was added (monitoring), and five items that were not age-appropriate for the sample were removed. Based on previous literature, both a 7-factor and an 8-factor model were assessed via CFA. Results showed that the 8-factor model, which separated restriction and use of food rewards, improved the conceptual clarity of the constructs and provided a good fit to the data. Internal consistency of all eight factors was acceptable (Cronbach’s α: .60−.93). This modified 8-factor CFQ appears to be a linguistically and culturally appropriate instrument for assessing feeding beliefs and practices in Chinese-Australian mothers of young children.

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We identify relation completion (RC) as one recurring problem that is central to the success of novel big data applications such as Entity Reconstruction and Data Enrichment. Given a semantic relation, RC attempts at linking entity pairs between two entity lists under the relation. To accomplish the RC goals, we propose to formulate search queries for each query entity α based on some auxiliary information, so that to detect its target entity β from the set of retrieved documents. For instance, a pattern-based method (PaRE) uses extracted patterns as the auxiliary information in formulating search queries. However, high-quality patterns may decrease the probability of finding suitable target entities. As an alternative, we propose CoRE method that uses context terms learned surrounding the expression of a relation as the auxiliary information in formulating queries. The experimental results based on several real-world web data collections demonstrate that CoRE reaches a much higher accuracy than PaRE for the purpose of RC.

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We present a mini-scale method for nuclear run-on transcription assay. In our method, all the centrifuge steps can be carried out by using micro-tubes for short time (5 min each) throughout the process, including isolation of transcriptionally active nuclei and purification of labeled RNA after synthesis of RNA in isolated nuclei. The assay can be performed using a small amount of plant tissue, which enables analysis of developmental changes in transcriptional status of given genes in a single individual plant. Successful results were obtained using the tissues of flower and leaf of petunia and embryo of pea, suggesting that the method is potentially applicable to a variety of plant tissues.

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All design classes followed a systematic design approach, that, in an abstract way, can be characterized by figure 1. This approach is based on our design approach [1] that we labeled DUTCH (design for users and tasks, from concepts to handles).Consequently, each course starts with collecting, modeling, and analyzing an existing situation. The next step is the development of a vision on a future domain world where new technology and / or new representations have been implemented. This second step is the first tentative global design that will be represented in scenarios or prototypes and can be assessed. This second design model is based on both the client’s requirements and technological possibilities and challenges. In an iterative way multiple instantiations of detail design may follow, that each can be assessed and evaluated again...

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MicroRNAs (miRNAs) are a class of small non-coding RNAs with a critical role in development and environmental responses. Efficient and reliable detection of miRNAs is an essential step towards understanding their roles in specific cells and tissues. However, gel-based assays currently used to detect miRNAs are very limited in terms of throughput, sensitivity and specificity. Here we provide protocols for detection and quantification of miRNAs by RT-PCR. We describe an end-point and real-time looped RT-PCR procedure and demonstrate detection of miRNAs from as little as 20 pg of plant tissue total RNA and from total RNA isolated from as little as 0.1 l of phloem sap. In addition, we have developed an alternative real-time PCR assay that can further improve specificity when detecting low abundant miRNAs. Using this assay, we have demonstrated that miRNAs are differentially expressed in the phloem sap and the surrounding vascular tissue. This method enables fast, sensitive and specific miRNA expression profiling and is suitable for facilitation of high-throughput detection and quantification of miRNA expression.

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Nontechnical skills relating to team functioning are vital to the effective delivery of patient care and safety. In this study, we develop a reliable behavioral marker tool for assessing nontechnical skills that are critical to the success of ward-based multidisciplinary healthcare teams. The Team Functioning Assessment Tool (TFAT) was developed and refined using a literature review, focus groups, card-sorting exercise, field observations, and final questionnaire evaluation and refinement process. Results demonstrated that Clinical Planning, Executive Tasks, and Team Relations are important facets of effective multidisciplinary healthcare team functioning. The TFAT was also shown to yield acceptable inter-rater agreement.

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With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

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Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

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Background Rapid developments in technology have encouraged the use of smartphones in physical activity research, although little is known regarding their effectiveness as measurement and intervention tools. Objective This study systematically reviewed evidence on smartphones and their viability for measuring and influencing physical activity. Data Sources Research articles were identified in September 2013 by literature searches in Web of Knowledge, PubMed, PsycINFO, EBSCO, and ScienceDirect. Study Selection The search was restricted using the terms (physical activity OR exercise OR fitness) AND (smartphone* OR mobile phone* OR cell phone*) AND (measurement OR intervention). Reviewed articles were required to be published in international academic peer-reviewed journals, or in full text from international scientific conferences, and focused on measuring physical activity through smartphone processing data and influencing people to be more active through smartphone applications. Study Appraisal and Synthesis Methods Two reviewers independently performed the selection of articles and examined titles and abstracts to exclude those out of scope. Data on study characteristics, technologies used to objectively measure physical activity, strategies applied to influence activity; and the main study findings were extracted and reported. Results A total of 26 articles (with the first published in 2007) met inclusion criteria. All studies were conducted in highly economically advantaged countries; 12 articles focused on special populations (e.g. obese patients). Studies measured physical activity using native mobile features, and/or an external device linked to an application. Measurement accuracy ranged from 52 to 100 % (n = 10 studies). A total of 17 articles implemented and evaluated an intervention. Smartphone strategies to influence physical activity tended to be ad hoc, rather than theory-based approaches; physical activity profiles, goal setting, real-time feedback, social support networking, and online expert consultation were identified as the most useful strategies to encourage physical activity change. Only five studies assessed physical activity intervention effects; all used step counts as the outcome measure. Four studies (three pre–post and one comparative) reported physical activity increases (12–42 participants, 800–1,104 steps/day, 2 weeks–6 months), and one case-control study reported physical activity maintenance (n = 200 participants; >10,000 steps/day) over 3 months. Limitations Smartphone use is a relatively new field of study in physical activity research, and consequently the evidence base is emerging. Conclusions Few studies identified in this review considered the validity of phone-based assessment of physical activity. Those that did report on measurement properties found average-to-excellent levels of accuracy for different behaviors. The range of novel and engaging intervention strategies used by smartphones, and user perceptions on their usefulness and viability, highlights the potential such technology has for physical activity promotion. However, intervention effects reported in the extant literature are modest at best, and future studies need to utilize randomized controlled trial research designs, larger sample sizes, and longer study periods to better explore the physical activity measurement and intervention capabilities of smartphones.

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The team functioning assessment tool (TFAT) has been shown to be a reliable behavioral marker tool for assessing nontechnical skills that are critical to the success of ward-based healthcare teams. This paper aims to refine and shorten the length of the TFAT to improve usability, and establish its reliability and construct validity. Psychometric testing based on 110 multidisciplinary healthcare teams demonstrated that the TFAT is a reliable and valid tool for measuring team members’ nontechnical skills in regards to Clinical Planning, Executive Tasks, and Team Functioning. Providing support for concurrent validity, high TFAT ratings were predicted by low levels of organizational constraints and high levels of group potency. There was also partial support for the negative relationships between time pressure, leadership ambiguity, and TFAT ratings. The paper provides a discussion on the applicability of the tool for assessing multidisciplinary healthcare team functioning in the context of improving team effectiveness and patient safety for ward-based hospital teams.

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The ability to identify and assess user engagement with transmedia productions is vital to the success of individual projects and the sustainability of this mode of media production as a whole. It is essential that industry players have access to tools and methodologies that offer the most complete and accurate picture of how audiences/users engage with their productions and which assets generate the most valuable returns of investment. Drawing upon research conducted with Hoodlum Entertainment, a Brisbane-based transmedia producer, this chapter outlines an initial assessment of the way engagement tends to be understood, why standard web analytics tools are ill-suited to measuring it, how a customised tool could offer solutions, and why this question of measuring engagement is so vital to the future of transmedia as a sustainable industry.

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Background There are few theoretically derived questionnaires of physical activity determinants among youth, and the existing questionnaires have not been subjected to tests of factorial validity and invariance, The present study employed confirmatory factor analysis (CFA) to test the factorial validity and invariance of questionnaires designed to be unidimensional measures of attitudes, subjective norms, perceived behavioral control, and self-efficacy about physical activity. Methods Adolescent girls in eighth grade from two cohorts (N = 955 and 1,797) completed the questionnaires at baseline; participants from cohort 1 (N = 845) also completed the questionnaires in ninth grade (i.e., 1-year follow-up). Factorial validity and invariance were tested using CFA with full-information maximum likelihood estimation in AMOS 4.0, Initially, baseline data from cohort 1 were employed to test the fit and, when necessary, to modify the unidimensional models. The models were cross-validated using a multigroup analysis of factorial invariance on baseline data from cohorts 1 and 2, The models then were subjected to a longitudinal analysis of factorial invariance using baseline and follow-up data from cohort i, Results The CFAs supported the fit of unidimensional models to the four questionnaires, and the models were cross-validated, as indicated by evidence of multigroup factorial invariance, The models also possessed evidence of longitudinal factorial invariance. Conclusions Evidence was provided for the factorial validity and the invariance of the questionnaires designed to be unidimensional measures of attitudes, subjective norms, perceived behavioral control, and self-efficacy about physical activity among adolescent girls, (C) 2000 American Health Foundation and academic Press.

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In this paper, the inherent mechanism of social benefits associated with smart grid development is examined based on the pressure state response (PSR) model from resource economics. The emerging types of technology brought up by smart grid development are regarded as pressures. The improvements of the performance and efficiency of power system operation, such as the enhanced capability of accommodating renewable energy generation, are regarded as states. The effects of smart grid development on society are regarded as responses. Then, a novel method for evaluating social benefits from smart grid development is presented. Finally, the social benefits from smart grid development in a province in northwest China are carried out by using the developed evaluation system, and reasonable evaluation results are attained.

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Interior permanent-magnet synchronous motors (IPMSMs) become attractive candidates in modern hybrid electric vehicles and industrial applications. Usually, to obtain good control performance, the electric drives of this kind of motor require one position, one dc link, and at least two current sensors. Failure of any of these sensors might lead to degraded system performance or even instability. As such, sensor fault resilient control becomes a very important issue in modern drive systems. This paper proposes a novel sensor fault detection and isolation algorithm based on an extended Kalman filter. It is robust to system random noise and efficient in real-time implementation. Moreover, the proposed algorithm is compact and can detect and isolate all the sensor faults for IPMSM drives. Thorough theoretical analysis is provided, and the effectiveness of the proposed approach is proven by extensive experimental results.

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Semantic Space models, which provide a numerical representation of words’ meaning extracted from corpus of documents, have been formalized in terms of Hermitian operators over real valued Hilbert spaces by Bruza et al. [1]. The collapse of a word into a particular meaning has been investigated applying the notion of quantum collapse of superpositional states [2]. While the semantic association between words in a Semantic Space can be computed by means of the Minkowski distance [3] or the cosine of the angle between the vector representation of each pair of words, a new procedure is needed in order to establish relations between two or more Semantic Spaces. We address the question: how can the distance between different Semantic Spaces be computed? By representing each Semantic Space as a subspace of a more general Hilbert space, the relationship between Semantic Spaces can be computed by means of the subspace distance. Such distance needs to take into account the difference in the dimensions between subspaces. The availability of a distance for comparing different Semantic Subspaces would enable to achieve a deeper understanding about the geometry of Semantic Spaces which would possibly translate into better effectiveness in Information Retrieval tasks.