3,293 research outputs found
Sharing Human-Generated Observations by Integrating HMI and the Semantic Sensor Web
No full textCurrent “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is soun
TIRADS, SRE and SWE in INDETERMINATE thyroid nodule characterization: which has better diagnostic performance?
No full textPurpose: To assess Strain Ratio (SRE) and Shear Wave Elastography (SWE) accuracy alone and with TIRADS classification, for the risk stratification of indeterminate thyroid nodules.
Materials and methods: 128 Patients with 128 indeterminate nodules candidates for thyroidectomy underwent preoperative staging neck ultrasound and were classified according to K-TIRADS score. After TIRADS evaluation, semi-quantitative (SRE) and quantitative (SWE expressed in kPa) elastosonography were performed and relative diagnostic performances, alone and in combination, were compared through ROC curves analysis. In order to maximize the SRE and SWE sensitivity and specificity, their cut-off values were calculated using the Liu test. Bonferroni test was used to evaluate statistically significant differences with a p value < 0.05.
Results: Sensitivity, specificity, PPV and NPV were, respectively, 71.4%, 82.4%, 62.5%, 87.5% for K-TIRADS baseline US, 85.7%, 94.1%, 85.7%, 94.1% for SRE and 57.1%, 79.4%, 53.3%, 81.8% for SWE (kPa expressed). SRE evaluation showed the best diagnostic accuracy compared to the SWE (kPa expressed) (p < 0.05) and to the K-TIRADS (p > 0.05). The association of SRE with conventional ultrasound with K-TIRADS score increased sensitivity (92.9% vs 71.4%) but decreased the specificity than conventional US alone (76.5% vs 82.4%).
Conclusion: Strain Elastosonography can be associated with K-TIRADS US examination in the thyroid nodule characterization with indeterminate cytology; in fact, adding the SRE to K-TIRADS assessment significantly increases its sensitivity and negative predictive value. However, further multicenter studies on larger population are warranted
Updated monthly and new daily bias correction for assimilation-based passive microwave SWE retrieval
No full textSnow water equivalent (SWE) is a valuable characteristic of global snowpack, and it can be estimated using passive spaceborne radiometer measurements. The radiometer-based GlobSnow SWE retrieval methodology, which assimilates weather station snow depth observations with passive microwave brightness temperatures, has improved the reliability and accuracy of SWE retrieval when compared to stand-alone radiometer passive microwave (PMW) methods. However, even this assimilation-based method fails to estimate large (> 150 mm) SWE values as snow changes from a scatterer to an emitter. Correcting for these systematic biases can improve PMW-based SWE estimates, especially for high SWE magnitudes. Previously, a monthly bias correction using snow course observations was applied to the GlobSnow v3 product for February–May. This method reduced the spread in March SWE estimated from four gridded products. In this research, we use newly available snow course data to update this bias correction and expand it to cover the months of December through May; we also extend the monthly bias correction to a daily bias correction. The new monthly and daily bias corrections are applied to an updated version of the GlobSnow product - Snow CCI v3.1 product. The Northern Hemisphere climatological snow mass from the Snow CCI v3.1 bias corrected products (daily and monthly) is consistent with that from a suite of reanalysis products. This represents a significant improvement for the months of April and May compared to the original GlobSnow v3.0 bias corrected product, as is the provision of daily bias corrected SWE estimates.</p
Knowledge, attitudes and practices with regard to malaria control in an endemic rural area of Myanmar.
No full textMalaria is a global health problem, in particular, a major health problem within Southeast Asia. This study aimed to investigate malaria control within a rural area of Myanmar, where traditionally non-western medicine is the preferred treatment. Whilst malaria was perceived by the local people to be a major health problem, knowledge about the mode of transmission and correct treatment for malaria was relatively low. Consequently, the practices of the local people to control malaria were often ill-informed or based on cultural and traditional beliefs.Kyawt-Kyawt-Swe , Pearson A.http://www.ncbi.nlm.nih.gov/sites/entrez/1527274
Improving SWE Estimation by Fusion of Snow Models with Topographic and Remotely Sensed Data
No full textThis paper presents a new concept to derive the snow water equivalent (SWE) based on the joint use of snow model (AMUNDSEN) simulation, ground data, and auxiliary products derived from remote sensing. The main objective is to characterize the spatial-temporal distribution of the model-derived SWE deviation with respect to the real SWE values derived from ground measurements. This deviation is due to the intrinsic uncertainty of any theoretical model, related to the approximations in the analytical formulation. The method, based on the k-NN algorithm, computes the deviation for some labeled samples, i.e., samples for which ground measurements are available, in order to characterize and model the deviations associated to unlabeled samples (no ground measurements available), by assuming that the deviations of samples vary depending on the location within the feature space. Obtained results indicate an improved performance with respect to AMUNDSEN model, by decreasing the RMSE and the MAE with ground data, on average, from 154 to 75 mm and from 99 to 45 mm, respectively. Furthermore, the slope of regression line between estimated SWE and ground reference samples reaches 0.9 from 0.6 of AMUNDSEN simulations, by reducing the data spread and the number of outliers
Swe-Clarin: Language Resources and Technology for Digital Humanities
No full textCLARIN AND SWE-CLARIN
CLARIN (Common Language Resources and Technology Infrastructure) is a European Research Infrastructure Consortium (ERIC), an ESFRI (European Strategy Forum on Research Infrastructures) initiative which aims at (a) making extensive language-based materials available as primary research data to the Humanities and Social Sciences (HSS) research communities; and (b) offering state-of-the-art language technology (LT) as an e- research tool for this purpose, positioning CLARIN centrally in what is often referred to as the digital humanities (DH).
Swe-Clarin as the Swedish CLARIN node was established in 2015 with funding from the Swedish Research Council by a consortium consisting of 9 members – so-called Swe-Clarin centers – representing the Swedish academic community as well as public memory institutions. The academic members are well balanced over the LT field, covering existing and possible research areas and user groups, and the memory institutions provide access to many of the language-based materials of interest to the users. Swe-Clarin is coordinated by Språkbanken, University of Gothenburg.
From the start, Swe-Clarin has aimed to establish good relations to the HSS fields and open the door for all researchers who wish to work with DH research using text and speech as primary research data. To avoid being a project by language technologists for linguists, we strive to include the HSS researchers in the process as early as possible. Our preferred way of doing this has been to establish small pilot projects with at least one member from the HSS field and at least one Swe-Clarin consortium member, together formulating a research question the addressing of which requires working with large language-based materials. Ideally, the collaboration should additionally always include a data owner, a person or persons representing the institution where the text or speech data is kept – typically a memory institution.
The pilot projects aim to spread the word of Swe-Clarin, show the potential of using language technology in DH research, create a user base for the tools and resources developed and maintained by Swe-Clarin, and last but not least, having this development being informed by input from users in the earliest possible stages of the project. Some pilot projects are already underway (see below).
In addition to the pilot projects, we have arranged workshops and user days and published newsletters and a blog. The workshops held so far have been on topics such as: general introduction to Swe-Clarin, our tools and resources; historical resources and tools; making cultural heritage text data available for research; and HSS research on digitized speech data, such as those of the Swedish Media Archive. We have started a series of workshops called Swe-Clarin on tour where Språkbanken’s widely used Korp corpus infrastructure (Borin et al. 2012) is used to explore previously unexplored materials in a hands-on manner, giving researchers of LT and HSS the opportunity to meet and discuss research questions and the potentials of using LT for DH. The experience from working with HSS researchers will help reveal the limitations of existing tools and hopefully also engender general methodological discussion, thus setting the stage for future development of tools more appropriate for DH research. The first such workshop was held at Stockholm University in the spring of 2016. It featured the ethnographic questionnaires collected by the Nordic Museum since the late 1920s and now digitized by them, and it was attended mainly by ethnologists. The next workshop in the series will be held in Umeå in conjunction with the Swedish Language Technology Conference in November 2016. There the material in focus will be the Swedish Government Official Reports (Statens offentliga utredningar, SOU), in the version digitized by the National Library of Sweden, comprising more than 400 million words covering the years 1922–1998.
SOME SWE-CLARIN PILOT PROJECTS
Attitudes Toward Rhetoric Over TimeIn this pilot project, a historian of rhetoric at Uppsala University together with the Swe-Clarin center Språkbanken explored how Språkbanken’s Korp infrastructure could be applied to the research question of how the attitudes to rhetoric expressed in Swedish public discourse have changed over the last 200 years. The focus in the pilot project was on a large (almost 1 billion words) digitized historical newspaper material provided by the National Library, but some preliminary studies of modern social media were also included for comparison. (Viklund and Borin 2016)
A Text Analysis Toolbox for Learner LanguageThe Swe-Clarin center at Uppsala University has developed SWEGRAM, a web service that provides automatic linguistic annotation at word and sentence level, which can subsequently be used to derive statistics on different linguistic characteristics of the texts, for example, the number of words and sentences in a text, the average length of a word, the distribution of word classes or different measures of readability. In a collaboration with researchers at the Department of Scandinavian Languages at Uppsala University, SWEGRAM has been made the basis for a web-based tool for annotation and quantitative analysis of student essays for the national exam in Swedish and Swedish as a second language for different grades (3rd, 6th, 9th grade). (Megyesi et al. 2016)
The Annotated Strindberg CorpusThe Swe-Clarin center at Stockholm University in collaboration with the Swedish Literature Bank (Litteraturbanken) and the editorial team of the National Edition of August Strindberg’s Collected Works aim to construct a linguistically annotated corpus of Strindberg’s collected works. The National Edition consists of 72 volumes with about 6 million words published between 1981 and 2012. The annotated version of the corpus will enable new kinds of research to be conducted on this material, as well as pave the way for even deeper annotation in the future. (Nilsson Björkenstam et al. 2014)
LAST BUT NOT LEAST
We strongly encourage you to contact us if you are interested in any of our resources, in conducting a pilot study with us or if you have any ideas or questions regarding digital humanities research with respect to language technology and resources: <[email protected]>. See also <https://sweclarin.se>.
REFERENCES
Borin, L., Forsberg, M., & Roxendal, J. (2012). Korp – the corpus infrastructure of Språkbanken. In Proceedings of LREC 2012 (pp. 474–478). Istanbul: ELRA.
Megyesi, B., Näsman, J., & Palmér, A. (2016). The uppsala corpus of student writings: Corpus creation, annotation, and analysis. In Proceedings of LREC 2016 (pp. 3192–3199). Portorož: ELRA.
Nilsson Björkenstam, K., Gustafson Capková, S., & Wirén, M. (2014). The Stockholm University Strindberg Corpus: Content and possibilities. In R. Lysell (Ed.), Strindberg on international stages/Strindberg in translation. Cambridge: Cambridge Scholars Publishing.
Viklund, J., & Borin, L. (2016). How can big data help us study rhetorical history? In Selected Papers from the CLARIN Annual Conference 2015 (pp. 79–93). Linköping: LiU EP
Verfahrensdokumentation für SWE: Skala zur Allgemeinen Selbstwirksamkeitserwartung
No full textMit den Skalen lassen sich Überzeugungen subjektiver Kontrollierbarkeit bzw. Kompetenzerwartungen in verschiedenen Anforderungssituationen erfassen, nämlich für die Schule, das Studium und das allgemeine Leben. Die Konzeption der Skalen erfolgte in Anlehnung an die sozial-kognitive Lerntheorie von Bandura (1977) und dem darin enthaltenen Konzept positiver Situations-Handlungs-Erwartungen. Das Verfahren liegt in drei bereichsspezifischen Versionen vor: (1) Schulspezifische Selbstwirksamkeit (WIRKSCHUL; k = 13); (2) Allgemeine Selbstwirksamkeit (WIRKALL; k = 20); von dieser Skala liegt eine Kurzform mit 10 Items vor (WIRKALL-K; modifizierte Nachfolgeversion: Skala zur Allgemeinen Selbstwirksamkeitserwartung SWE); (3) Studiumsspezifische Selbstwirksamkeit (WIRKSTUD; k = 7). Reliabilität: Zum Nachweis der Zuverlässigkeit wurde für verschiedene Stichproben die Retestreliabilität (rtt) bzw. Cronbachs Alpha ermittelt (.71 bis .89). Von 264 Auszubildenden liegen Retestwerte nach einem Jahr für die Skalen WIRKALL (rtt = .57) und WIRKALL-K (rtt = .54) vor. Validität: Das Verfahren besitzt inhaltlich-logische Gültigkeit. Zur internen Validierung wurden Korrelationen zu einer Reihe von anderen Eigenschaftskonstrukten berechnet. Aus den Zusammenhängen lässt sich eine Reihe von Validitätshinweisen gewinnen.The scales can be used to record convictions of subjective controllability or expectations of competence in various requirement situations, namely for school, study and general life. The scales were designed in accordance with the social-cognitive learning theory of Bandura (1977) and the concept of positive situation-action expectations contained therein. The method is available in three area-specific versions: (1) School-specific self-efficacy (WIRKSCHUL; k = 13); (2) General self-efficacy (WIRKALL; k = 20); a short form of this scale with 10 items is available (WIRKALL-K; modified follow-up version: scale for general self-efficacy expectation SWE); (3) Study-specific self-efficacy (WIRKSTUD; k = 7) Reliability: To provide evidence of reliability, the retestreliability (rtt) or Cronbach's alpha was determined for various samples (.71 to .89). Retest values after one year are available for the REAL (rtt = .57) and REAL-K (rtt = .54) scales from 264 trainees. Validity: The procedure is valid in terms of content and logic. For internal validation, correlations to a number of other property constructs were calculated. From these correlations a number of validity clues can be obtained.reviewedpublishedVersio
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Effect of ENSO phase on large-scale snow water equivalent distribution in a GCM
No full textUnderstanding links between the El Nino-Southern Oscillation (ENSO) and snow would be useful for seasonal forecasting, but also for understanding natural variability and interpreting climate change predictions. Here, a 545-year run of the general circulation model HadCM3, with prescribed external forcings and fixed greenhouse gas concentrations, is used to explore the impact of ENSO on snow water equivalent (SWE) anomalies. In North America, positive ENSO events reduce the mean SWE and skew the distribution towards lower values, and vice versa during negative ENSO events. This is associated with a dipole SWE anomaly structure, with anomalies of opposite sign centered in western Canada and the central United States. In Eurasia, warm episodes lead to a more positively skewed distribution and the mean SWE is raised. Again, the opposite effect is seen during cold episodes. In Eurasia the largest anomalies are concentrated in the Himalayas. These correlations with February SWE distribution are seen to exist from the previous June-July-August (JJA) ENSO index onwards, and are weakly detected in 50-year subsections of the control run, but only a shifted North American response can be detected in the anaylsis of 40 years of ERA40 reanalysis data. The ENSO signal in SWE from the long run could still contribute to regional predictions although it would be a weak indicator onl
Correlation Coefficient-based K-means Clustering for K-NN
No full textK-nearest neighbor algorithm is one of themost popular classifications in machine learningzone. However, as k-nearest neighbor is a lazylearning method, when a system bases on hugeamount of history data, it faces processingperformance degradation. Many researchersusually care about only classification accuracy,but the speed of estimation also play an essentialrole in real time prediction systems. For this issue,this research proposes correlation coefficientbasedk-mean clustering for k-nearest neighboraiming at upgrading the performance of k-nearestneighbor classification by improving processingtime performance. For the experiments, we usedthe real data sets, Breast Cancer, Breast Tissueand Iris, from UCI machine learning repository.Moreover, the real traffic data collected fromOjana junction, Route 58, Okinawa, Japan, wasalso utilized to show the efficiency of this method.By using these datasets, we prove the betterprocessing performance and prediction accuracyof the new approach by comparing the classicalk-nearest neighbor with the new k-nearestneighbor
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