Using the CALANDA time series management system

Dreyer, Werner; Dittrich, Angelika Kotz; Schmidt, Duri

doi:10.1145/568271.223902

Cited by 2 publications

(3 citation statements)

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“…It is mentioned in [30] that a lot of real data such as stock movements and exchange rates can be modelled by brown noise 4 which has a skewed energy spectrum in the frequency domain. This class of noise has a property that after the sequences are transformed by discrete Fourier transform, the first few coefficients will contain most of the energy.…”

Section: Noise Classmentioning

confidence: 99%

“…A query language [2] and a query processing scheme [3] for sequence queries have been proposed to facilitate the retrieval of sequence data. New computer systems [4,5] have also emerged recently to meet the new requirements of sequence data management.…”

Section: Introductionmentioning

confidence: 99%

“…Consider the query sequence Q (5,10,6,12,4) and the two data sequences A (6,5,7,10,11), B (15,20,16,22,14) in Figure 1 and assume that the error bound is set to 15. Note that B is produced by shifting Q upward for 10 units.…”

Section: Introductionmentioning

confidence: 99%

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An Efficient Hash-Based Algorithm for Sequence Data Searching

Chu¹

1998

The Computer Journal

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In real life, data collected day by day often appear in sequences and this type of data is called sequence data. The technique of searching for similar patterns among sequence data is very important in many applications. We first point out that there are some deficiencies in the existing definitions of sequence similarity. We then introduce a definition of sequence similarity based on the shape of sequences. The definition is also extended to handle sequence matching with linear scaling in both amplitude and time dimensions. A fast sequence searching algorithm based on extendable hashing is also proposed. The algorithm can match linearly scaled sequences and guarantee that no qualified data subsequence is falsely rejected. Several experiments are performed on real data (stock price movement) and synthetic data to measure the performance of the algorithm in different aspects.

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Section: Noise Classmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Efficient Hash-Based Algorithm for Sequence Data Searching

Chu¹

1998

The Computer Journal

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The impact of EMTALA on medical malpractice framework models: a review

Shenoy

2022

Patient Saf Surg

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The Emergency Medical Treatment & Active Labor Act (EMTALA) is a healthcare law specific to screening, stabilizing, and transferring (or accepting) patients with emergency medical conditions and active labor. This law, contextual to Medicare-participating hospitals, ensures public access to emergency medical services, regardless of the individual’s ability to pay. The Defensive Medicine (DM) model and Physician Responsiveness to Standard-of-care Reforms (PRSRs) model are two medical malpractice frameworks leveraged in this paper. The nodes of these frameworks comprise of the treatment-versus-no-treatment dynamics and cutoff thresholds. Cutoff thresholds are specific to health risks and treatment price rates. Health risks stem from those with treating or not treating a patient as well as those inherent from the patient’s ailment. Treatment price rates are subcategorized into customary and efficient price rates. Given the above nodes of these frameworks, this paper examines how the above medical malpractice models synchronize and sequentially align with the legal obligations of this law. This paper, furthermore, contemplatively describes how the incentivize/penalize dynamics interrelate to the push/pull dynamics of the PRSRs malpractice model. Thereafter, this paper applies the above push/pull dynamics contextual to the three specific obligations of this law, essentially, screening, stabilizing, and transferring (or accepting) emergency care patients. Conclusively, this paper illustrates the above network in a cascading algorithm that ligates the nodes of these frameworks to EMTALA's obligations.

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Using the CALANDA time series management system

Cited by 2 publications

References 1 publication

An Efficient Hash-Based Algorithm for Sequence Data Searching

An Efficient Hash-Based Algorithm for Sequence Data Searching

The impact of EMTALA on medical malpractice framework models: a review

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