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Related Concept Videos

Range00:59

Range

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The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
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A state function is a thermodynamic property that depends solely on the current state of a system, irrespective of its history or how it arrived at that state. These functions are represented by capital letters, such as U, H, and S, which stand for internal energy, enthalpy, and entropy, respectively.For instance, the value of internal energy depends on the system's state variables and remains unaffected by the process path. This means that whether the system underwent a linear process or a...
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A somewhat easy to compute quantitative estimate of a data set’s central tendency is its midrange, which is defined as the mean of the minimum and maximum values of an ordered data set.
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Unusual results are those that have a very low chance of occurring. Unusual results can be identified using probabilities and the range rule of thumb. In problems involving probability, unusual results can be observed in 2 instances – an unusually high number of successes or an unusually low number of successes.
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In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
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Related Experiment Video

Updated: Apr 21, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

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On Optimal Differentially Private Mechanisms for Count-Range Queries.

Chen Zeng1, Jin-Yi Cai2, Pinyan Lu3

  • 1University of Wisconsin-Madison, zeng@cs.wisc.edu.

Database Theory-- ICDT : International Conference ... Proceedings. International Conference on Database Theory
|November 4, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces differentially private mechanisms for count-range queries, proving an optimal solution for single users. Surprisingly, a multi-user mechanism exists for threshold queries, offering a two-approximation for general count-range queries.

Related Experiment Videos

Last Updated: Apr 21, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

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Area of Science:

  • Computer Science
  • Data Privacy
  • Database Systems

Background:

  • Differentially private mechanisms are crucial for protecting sensitive data during query answering.
  • Count-range queries, a natural class of queries, have not been previously studied in the context of differential privacy.
  • Existing mechanisms for count queries do not extend to count-range queries for multiple consumers.

Purpose of the Study:

  • To develop a provably optimal differentially private mechanism for count-range queries for a single consumer.
  • To investigate the existence of a multi-consumer differentially private mechanism for count-range queries.
  • To explore mechanisms for threshold queries and their approximation capabilities for general count-range queries.

Main Methods:

  • Developed a novel differentially private mechanism for count-range queries.
  • Proved the optimality of the single-consumer mechanism.
  • Demonstrated the non-existence of a multi-consumer mechanism for general count-range queries.
  • Developed and analyzed a mechanism for threshold queries.

Main Results:

  • An optimal differentially private mechanism for single-consumer count-range queries was developed.
  • It was proven that no multi-consumer differentially private mechanism exists for general count-range queries.
  • A differentially private mechanism for threshold queries was shown to exist and provides a two-approximation for general count-range queries.

Conclusions:

  • The study provides foundational differentially private mechanisms for count-range and threshold queries.
  • Highlights the limitations of multi-consumer privacy mechanisms for certain query types.
  • The threshold query mechanism offers a practical approach for approximating count-range queries under differential privacy.