Collaborative Development and Evaluation of Text-processing Workflows in a UIMA-supported Web-based Workbench

Challenges in creating comprehensive text-processing worklows include a lack of the interoperability of individual components coming from different providers and/or a requirement imposed on the end users to know programming techniques to compose such workflows. In this paper we demonstrate Argo, a web-based system that addresses these issues in several ways. It supports the widely adopted Unstructured Information Management Architecture (UIMA), which handles the problem of interoperability; it provides a web browser-based interface for developing workflows by drawing diagrams composed of a selection of available processing components; and it provides novel user-interactive analytics such as the annotation editor which constitutes a bridge between automatic processing and manual correction. These features extend the target audience of Argo to users with a limited or no technical background. Here, we focus specifically on the construction of advanced workflows, involving multiple branching and merging points, to facilitate various comparative evalutions. Together with the use of user-collaboration capabilities supported in Argo, we demonstrate several use cases including visual inspections, comparisions of multiple processing segments or complete solutions against a reference standard, inter-annotator agreement, and shared task mass evaluations. Ultimetely, Argo emerges as a one-stop workbench for defining, processing, editing and evaluating text processing tasks

Building trainable taggers in a web-based, UIMA-supported NLP workbench

Argo is a web-based NLP and text mining workbench with a convenient graphical user interface for designing and executing processing workflows of various complexity. The workbench is intended for specialists and nontechnical audiences alike, and provides the ever expanding library of analytics compliant with the Unstructured Information Management Architecture, a widely adopted interoperability framework. We explore the flexibility of this framework by demonstrating workflows involving three processing components capable of performing self-contained machine learning-based tagging. The three components are responsible for the three distinct tasks of 1) generating observations or features, 2) training a statistical model based on the generated features, and 3) tagging unlabelled data with the model. The learning and tagging components are based on an implementation of conditional random fields (CRF); whereas the feature generation component is an analytic capable of extending basic token information to a comprehensive set of features. Users define the features of their choice directly from Argo’s graphical interface, without resorting to programming (a commonly used approach to feature engineering). The experimental results performed on two tagging tasks, chunking and named entity recognition, showed that a tagger with a generic set of features built in Argo is capable of competing with taskspecific solutions.

Internet of Healthcare: Opportunities and Legal Challenges in Internet of Things-Enabled Telehealth Ecosystems

The COVID-19 public health crisis has accelerated the transformation of health systems to become more closely tied to citizens/patients and increasingly dependent on the provision and use of telehealth services. Internet of Things (IoT)-enabled telehealth systems (deployed in conjunction with AI systems) could facilitate the smart transformation of healthcare from a merely reactive system to a data-driven and person-centred system that provides remote health diagnosis, monitoring and treatment services, integrated real-time response solutions, as well as prospective insights. However, the realisation of these health-related benefits requires the processing of vast amounts of data concerning health. These operations and the use of new enabling technologies raises significant legal concerns and questions the applicability of existing/proposed legal concepts. For this reason, the research analyses the adequateness of EU privacy, data protection, data governance, AI governance and other regulatory rules in IoT-enabled (and AI-augmented) telehealth systems. In addition, the research aims to identify technical and organisational measures (best practices), which could facilitate the implementation of normative principles in these information systems in an effective manner

Different fractal properties of positive and negative returns

We perform an analysis of fractal properties of the positive and the negative changes of the German DAX30 index separately using Multifractal Detrended Fluctuation Analysis (MFDFA). By calculating the singularity spectra $f(\alpha)$ we show that returns of both signs reveal multiscaling. Curiously, these spectra display a significant difference in the scaling properties of returns with opposite sign. The negative price changes are ruled by stronger temporal correlations than the positive ones, what is manifested by larger values of the corresponding H\"{o}lder exponents. As regards the properties of dominant trends, a bear market is more persistent than the bull market irrespective of the sign of fluctuations.Comment: presented at FENS2007 conference, 8 pages, 4 Fig

Stock market return distributions: from past to present

We show that recent stock market fluctuations are characterized by the cumulative distributions whose tails on short, minute time scales exhibit power scaling with the scaling index alpha > 3 and this index tends to increase quickly with decreasing sampling frequency. Our study is based on high-frequency recordings of the S&P500, DAX and WIG20 indices over the interval May 2004 - May 2006. Our findings suggest that dynamics of the contemporary market may differ from the one observed in the past. This effect indicates a constantly increasing efficiency of world markets.Comment: to appear in Physica

Jet Correlations of Identified Particles in PHENIX

Azimuthal two particle correlations at intermediate $p_{T}$ with one of the particles identified have been measured at PHENIX. Trigger ($2.5 < p_{T} < 4.0 GeV/c$) baryons and mesons show little significant difference in the number of associated particles ($1.7 < p_{T} < 2.5 GeV/c$) independent of centrality. For inclusive hadron triggers with $2.5 < p_{T} < 4.0 GeV/c$, associated fragmentation particles with $1.0 < p_{T} < 2.5 GeV/c$ show a higher baryon to meson ratio on the away side.Comment: talk given at Quark Matter 2004, 4 pages 4 figur

Dihadron Correlation in Jets Produced in Heavy-Ion Collisions

The difference between the structures of jets produced in heavy-ion and hadronic collisions can best be exhibited in the correlations between particles within those jets. We study the dihadron correlations in jets in the framework of parton recombination. Two types of triggers, $\pi^+$ and proton, are considered. It is shown that the recombination of thermal and shower partons makes the most important contribution to the spectra of the associated particles at intermediate $p_T$. In $pp$ collisions the only significant contribution arises from shower-shower recombination, which is negligible in heavy-ion collisions. Moments of the associated-particle distributions are calculated to provide simple summary of the jet structures for easy comparison with experiments.Comment: 24 pages in Latex + 5 figure

Cross-correlations in Warsaw Stock Exchange

We study the inter-stock correlations for the largest companies listed on Warsaw Stock Exchange and included in the WIG20 index. Our results from the correlation matrix analysis indicate that the Polish stock market can be well described by a one factor model. We also show that the stock-stock correlations tend to increase with the time scale of returns and they approach a saturation level for the time scales of at least 200 min, i.e. an order of magnitude longer than in the case of some developed markets. We also show that the strength of correlations among the stocks crucially depends on their capitalization. These results combined with our earlier findings together suggest that now the Polish stock market situates itself somewhere between an emerging market phase and a mature market phase.Comment: presented by R.Rak at FENS2007 conference, 9 pages, 4 Fig