Big data technologies and Management: What conceptual modeling can do

Storey, Veda C.; Song, Il‐Yeol

doi:10.1016/j.datak.2017.01.001

Cited by 210 publications

(121 citation statements)

References 22 publications

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“…The popularity and quality of physiological measurement devices have grown significantly in recent years [21]. These devices see increasing applicability because of fields like mobile health [14,23].…”

Section: Introductionmentioning

confidence: 99%

Recycling cardiogenic artifacts in impedance pneumography

Malik

2019

Biomedical Signal Processing and Control

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Purpose: Biomedical sensors often exhibit cardiogenic artifacts which, while distorting the signal of interest, carry useful hemodynamic information. We propose an algorithm to remove and extract hemodynamic information from these cardiogenic artifacts. Methods:We apply a nonlinear time-frequency analysis technique, the de-shape synchrosqueezing transform (dsSST), to adaptively isolate the high-and low-frequency components of a single-channel signal. We demonstrate this technique's effectiveness by removing and deriving hemodynamic information from the cardiogenic artifact in an impedance pneumography (IP). Results: The instantaneous heart rate is extracted, and the cardiac and respiratory signals are reconstructed. Conclusions: The dsSST is suitable for generating useful hemodynamic information from the cardiogenic artifact in a single-channel IP. We propose that the usefulness of the dsSST as a recycling tool extends to other biomedical sensors exhibiting cardiogenic artifacts.

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Section: Introductionmentioning

confidence: 99%

Recycling cardiogenic artifacts in impedance pneumography

Malik

2019

Biomedical Signal Processing and Control

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“…These rules rely on hidden models of data collection to be used to predict the future behavior of the organization. This prediction helps retailers in how to reveal their customers as well as learn about their common interests (Storey and Song, 2017). The purpose of the data exploration program is not to disclose what has been done previously, but to pre-screen the unusual relations between the data items and thus harness the results of such disclosure in favor of the objectives of the concerned organization Data exploration tools are used for the purpose of detecting works with their multiple capabilities through data work surveys (Abdel-Basset et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Data Exploration in the Supermarket System to Study the Behavior of the Jordanian Consumers

Aldiabat¹,

AL-Rousan²,

Alzoubi³

2019

Journal of Computer Science

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The study aimed to identify the extent of using data exploration in the supermarket system to study the behavior of the Jordanian consumers and the extent of using data exploration in commercial shops in Jordan. The study concluded that data exploration in the supermarket system is not used to study the behavior of the Jordanian consumers regarding the disclosure of products sold in the consumer basket. The results of the study showed that there is a use of data exploration in the supermarket system to study the behavior of the Jordanian consumers regarding the disclosure of bestselling products in a specified period. The study also showed that there is a use of data exploration in the super system to study the behavior of the Jordanian consumer regarding the exploration of consumer's behavior towards the product quality. The most important recommendations of the study is the need for further studies in the use of data exploration in the supermarket system to study the behavior of the consumers, especially as most shops use a system to handle sales movements, but there is not enough exploitation of the database, which can help significantly in studying the consumer's behavior.

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“…Moreover, this data model is very scalable and support clustering for spreading data over a large number of machines. It can load data at extremely high speed [5]. Some examples of column-oriented databases are Cassandra, HBase, HyperTable and so on.…”

Section: B Document-oriented Storesmentioning

confidence: 99%

Performance Evaluation of Redis and MongoDB Databases for Handling Semi-structured Data

Spal¹

2018

IJRASET

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Big data technologies and Management: What conceptual modeling can do

Cited by 210 publications

References 22 publications

Recycling cardiogenic artifacts in impedance pneumography

Recycling cardiogenic artifacts in impedance pneumography

Data Exploration in the Supermarket System to Study the Behavior of the Jordanian Consumers

Performance Evaluation of Redis and MongoDB Databases for Handling Semi-structured Data

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