2,089 research outputs found
Extreme-Scale Model-Based Time Series Management with ModelarDB (Invited Talk)
No full textTo monitor critical industrial devices such as wind turbines, high quality sensors sampled at a high frequency are increasingly used. Current technology does not handle these extreme-scale time series well [Søren Kejser Jensen et al., 2017], so only simple aggregates are traditionally stored, removing outliers and fluctuations that could indicate problems. As a remedy, we present a model-based approach for managing extreme-scale time series that approximates the time series values using mathematical functions (models) and stores only model coefficients rather than data values. Compression is done both for individual time series and for correlated groups of time series. The keynote will present concepts, techniques, and algorithms from model-based time series management and our implementation of these in the open source Time Series Management System (TSMS) ModelarDB[Søren Kejser Jensen et al., 2018; Søren Kejser Jensen et al., 2019; Søren Kejser Jensen et al., 2021] . Furthermore, it will present our experimental evaluation of ModelarDB on extreme-scale real-world time series, which shows that that compared to widely used Big Data formats, ModelarDB provides up to 14× faster ingestion due to high compression, 113× better compression due to its adaptability, 573× faster aggregatation by using models, and close to linear scale-out scalability. ModelarDB is being commercialized by the spin-out company ModelarData
A foundation for spatio-textual-temporal cube analytics
No full textLarge amounts of spatial, textual, and temporal (STT) data are being produced daily. This is data containing an unstructured component (text), a spatial component (geographic position), and a time component (timestamp). Therefore, there is a need for a powerful and general way of analyzing STT data together. In this paper, we define and formalize the Spatio-Textual-Temporal Cube (STTCube) structure to enable combined effective and efficient analytical queries over STT data. Our novel data model over STT objects enables novel joint and integrated STT insights that are hard to obtain using existing methods. Moreover, we introduce the new concept of STT measures with associated novel STTOLAP operators. To allow for efficient large-scale analytics, we present a pre-aggregation framework for exact and approximate computation of STT measures. Our comprehensive experimental evaluation on a real-world Twitter dataset confirms that our proposed methods reduce query response time by 1-5 orders of magnitude compared to the No Materialization baseline and decrease storage cost between 97% and 99.9% compared to the Full Materialization baseline while adding only a negligible overhead in the STTCube construction time. Moreover, approximate computation achieves an accuracy between 90% and 100% while reducing query response time by 3-5 orders of magnitude compared to No Materialization.</p
Example-Driven Exploratory Analytics over Knowledge Graphs
No full textDue to their expressive power, Knowledge Graphs (KGs) have received increasing interest not only as means to structure and integrate heterogeneous information but also as a native storage format for large amounts of knowledge and statistical data. Therefore, analytical queries over KG data, typically stored as RDF, have become increasingly important. Yet, formulating such queries represents a difficult task for users that are not familiar with the query language (typically SPARQL) and the structure of the dataset at hand. To overcome this limitation, we propose Re2xOLAP: The first comprehensive interactive approach that allows to reverse-engineer and refine RDF exploratory OLAP queries over KGs containing statistical data. Thus, Re2xOLAP enables to perform KG exploratory analytics without requiring the user to write any query at all.We achieve this goal by first reverseengineering analytical SPARQL queries from a small set of userprovided examples and then, given the reverse-engineered query, we propose intuitive and explainable exploratory query refinements to iteratively help the user obtain the desired information. Our experiments on real-world large-scale KGs show that Re2xOLAP can efficiently reverse-engineer analytical SPARQL queries solely based on a small set of input examples. Additionally, we demonstrate the expressive power of our interactive refinement methods by showing that Re2xOLAP allows users to navigate hundreds of thousands of different exploration paths with just a few interactions.</p
J.C. Bach's London keyboard sonatas : style and context
No full textJ. C. Bach's keyboard works include several sets of accompanied sonatas, a genre that enjoyed a wide popularity during the Classical era, but never
found its way into the concert repertoire. The accompanied sonata was a genre meant for domestic performance; the solo keyboard sonata, on
the other hand, was adopted in due course by concert audiences. J. C. Bach composed works within both genres during most of his productive years, and his output constitutes a corpus of remarkable consistency. J. C. Bach's removal to London in 1762 coincided with his clear adoption of a galant style, marked by the Italianate influence, and the abandonment of most Baroque traits. The British milieu provided additional factors: the rise of the pianoforte, a thriving music-publishing market, and a great interest in domestic music making among the affluent classes. These factors marked J. C. Bach's output at various levels. Keyboard works had to conform to the proficiency of the amateur performer, a
fact reflected in the accompanied output mostly. The number of movements, their length, and the inclusion of particular technical devices are readily observable differences between the two genres. The most remarkable
distinction lies perhaps in the preference for binary sonata format in the accompanied. sonatas from the mid 1760s to the 1770s, in spite of a later tendency for tripartite designs in both genres. J. C. Bach's lifelong preference for motivic phrase structure conditioned his keyboard production and partly explains the gap in quality between some of his works and sonatas composed around the same time by Haydn and Mozart, who developed more effective means to connect the melodic material
to higher structural units. J. C. Bach's influence, however, endured in Mozart's handling of melody, and his keyboard production constitutes, in spite of some flaws, a noteworthy example of elegance and craftsmanship
Towards Exploratory OLAP over Linked Open Data:a Case Study
No full textBusiness Intelligence (BI) tools provide fundamental support for analyzing large volumes of information. Data Warehouses (DW) and Online Analytical Processing (OLAP) tools are used to store and analyze data. Nowadays more and more information is available on the Web in the form of Resource Description Framework (RDF), and BI tools have a huge potential of achieving better results by integrating real-time data from web sources into the analysis process. In this paper, we describe a framework for so-called exploratory OLAP over RDF sources. We propose a system that uses a multidimensional schema of the OLAP cube expressed in RDF vocabularies. Based on this information the system is able to query data sources, extract and aggregate data, and build a cube. We also propose a computer-aided process for discovering previously unknown data sources and building a multidimensional schema of the cube. We present a use case to demonstrate the applicability of the approach.SCOPUS: cp.kinfo:eu-repo/semantics/publishe
Efficient Temporal Pattern Mining in Big Time Series Using Mutual Information
No full textVery large time series are increasingly available from an ever wider range of IoT-enabled sensors deployed in different environments. Significant insights can be gained by mining temporal patterns from these time series. Unlike traditional pattern mining, temporal pattern mining (TPM) adds event time intervals into extracted patterns, making them more expressive at the expense of increased time and space complexities. Existing TPM methods either cannot scale to large datasets, or work only on pre-processed temporal events rather than on time series. This paper presents our Frequent Temporal Pattern Mining from Time Series (FTPMfTS) approach providing: (1) The end-to-end FTPMfTS process taking time series as input and producing frequent temporal patterns as output. (2) The efficient Hierarchical Temporal Pattern Graph Mining (HTPGM) algorithm that uses efficient data structures for fast support and confidence computation, and employs effective pruning techniques for significantly faster mining. (3) An approximate version of HTPGM that uses mutual information, a measure of data correlation, to prune unpromising time series from the search space. (4) An extensive experimental evaluation showing that HTPGM outperforms the baselines in runtime and memory consumption, and can scale to big datasets. The approximate HTPGM is up to two orders of magnitude faster and less memory consuming than the baselines, while retaining high accuracy
A design space for RDF data representations
No full textRDF triplestores’ ability to store and query knowledge bases augmented with semantic annotations has attracted the attention of both research and industry. A multitude of systems offer varying data representation and indexing schemes. However, as recently shown for designing data structures, many design choices are biased by outdated considerations and may not result in the most efficient data representation for a given query workload. To overcome this limitation, we identify a novel three-dimensional design space. Within this design space, we map the trade-offs between different RDF data representations employed as part of an RDF triplestore and identify unexplored solutions. We complement the review with an empirical evaluation of ten standard SPARQL benchmarks to examine the prevalence of these access patterns in synthetic and real query workloads. We find some access patterns, to be both prevalent in the workloads and under-supported by existing triplestores. This shows the capabilities of our model to be used by RDF store designers to reason about different design choices and allow a (possibly artificially intelligent) designer to evaluate the fit between a given system design and a query workload.<br/
Duchenne muscular dystrophy: continuous noninvasive ventilatory support prolongs survival
No full textOBJECTIVE: To describe survival outcomes with noninvasive ventilation (NIV) for full ventilatory support, and a mechanically assisted cough and oximetry protocol in a series of patients with Duchenne muscular dystrophy.
METHODS: We monitored end-tidal carbon dioxide (PETCO2), SpO2, vital capacity, maximum insufflation capacity, and cough peak flow. Nocturnal NIV was initiated for symptomatic hypoventilation. An oximeter and mechanically assisted cough device were prescribed when the pa- tient’s maximum assisted cough peak flow fell below 300 L/min. Patients used up to continuous NIV and mechanically assisted cough to return SpO2 to > 95% during intercurrent respiratory infections or as otherwise needed. We recorded respiratory and cardiac hospitalizations and mortality, and quantified survival by duration of continuous NIV dependence (ie, unable to maintain oxygenation without the ventilator).
RESULTS: With advancing Duchenne muscular dystrophy, 101 nocturnal-only NIV users extended their NIV use throughout the daytime hours and required it continuously for 7.4 +- 6.1 years to 30.1 +- 6.1 years of age, with 56 patients still alive. Twenty-six of the 101 became continuously dependent without requiring hospitalization. Eight tracheostomized users were decannulated to NIV. Thirty-one consecutive unweanable intubated patients were extubated to NIV plus mechanically assisted cough. Of the 67 deaths (including 8 patients who died from heart failure before requiring ventilator use), 34 (52%) were probably cardiac, 14 (21%) were probably respiratory, and 19 (27%) were of unknown or other etiology.
CONCLUSIONS: Continuous NIV along with mechanically assisted cough and oximetry as needed can prolong life and obviate tracheotomy in patients with Duchenne muscular dystrophy. Unweanable patients can be decannulated and extubated to NIV plus mechanically assisted cough.Peer reviewe
Paul Bach-y-Rita, neuroscience's forgotten genius
No full textThesis: S.M. in Science Writing, Massachusetts Institute of Technology, Department of Humanities, Graduate Program in Science Writing, 2013.Cataloged from PDF version of thesis. Vita.Includes bibliographical references (pages 24-29).Dr. Paul Bach-y-Rita was a visionary neuroscientist and an early pioneer of the theory of neuroplasticity. He is the father of sensory substitution, a field which explores how one sensory modality can be transferred to another. This work culminated in the invention of the Brainport, a device that transmits information through electrodes on the tongue. Bach-y- Rita's company, Wicab, developed two versions of the Brainport. One uses visual information to reveal the sighted world to the blind; another uses body alignment information to help "wobblers" (individuals with vestibular conditions) navigate. The author received exclusive access to Bach-y-Rita's unpublished memoirs. These papers-supplemented by visits to Bach-y-Rita's home in Wisconsin and personal interviews with his family and colleagues-help tell the story of a revolutionary technology that failed to reach the public who needed it.by Aviva Hope Rutkin.S.M. in Science Writin
Respiratory muscle aids to avert respiratory failure and tracheostomy: a new patient management paradigm
No full textAn April 2010 consensus of clinicians from 22 centers in 18 countries reported 1,623 spinal muscular atrophy type 1, Duchenne muscular dystrophy, and amyotrophic lateral sclerosis noninvasive intermittent positive pressure ventilatory support users, of whom 760 developed continuous dependence that prolonged their survival by more than 3,000 patient-years without tracheostomies. Four of the centers routinely extubated unweanable patients with Duchenne muscular dystrophy, so that none of their more than 250 such patients has undergone tracheotomy. This article describes the manner in which this is accomplished; that is, the use of noninvasive inspiratory and expiratory muscle aids to prevent ventilatory failure and to permit the extubation and tracheostomy tube decannulation of patients with no autonomous ability to breathe (ie, who are “unweanable” from ventilator support). Noninvasive airway pressure aids can provide up to continuous ventilatory support for patients with little or no vital capacity and can provide for effective cough flows for patients with severely dysfunctional expiratory muscles.Peer reviewe
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