Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Survival Tree01:19

Survival Tree

105
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a...
105
Classification of Systems-II01:31

Classification of Systems-II

171
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
171
Classification of Systems-I01:26

Classification of Systems-I

211
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
211
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

127
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
127
Per-Unit Sequence Models01:26

Per-Unit Sequence Models

93
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
93
Aggregates Classification01:29

Aggregates Classification

344
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
344

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Phenotypic, genomic, and functional characterization of Corynebacterium sp. nov. isolated by droplet-based cultivation from vaginal swabs of a preeclampsia patient.

BMC microbiology·2026
Same author

Distinct vaginal microbial signatures in pregnancies complicated by antiphospholipid syndrome: depletion of <i>Lactobacillus johnsonii</i> and enrichment of <i>Bifidobacterium dentium</i>.

Microbiology spectrum·2026
Same author

A microbiota-host axis mediates prostaglandin sensitivity: Lactobacillus crispatus as a biomarker and regulator of human labor induction.

NPJ biofilms and microbiomes·2026
Same author

Photoinduced intramolecular S-α-C(sp<sup>3</sup>)-H functionalization enabled by an electron donor-acceptor complex-Mediated radical relay.

Chemical science·2026
Same author

Prognostic value of micro-RNA in ovarian cancer: a systematic review and meta-analysis.

Frontiers in oncology·2026
Same author

Targeted delivery to joints of the rheumatoid arthritis drug betulin using folic acid-coated nanoparticles based on human serum albumin.

International journal of biological macromolecules·2026
Same journal

RETRACTED: Zhang et al. A Novel Framework for Reconstruction and Imaging of Target Scattering Centers via Wide-Angle Incidence in Radar Networks. <i>Sensors</i> 2025, <i>25</i>, 6802.

Sensors (Basel, Switzerland)·2026
Same journal

Enhancing Unsupervised Multi-Source Domain Adaptation for Person Re-Identification via Mixture of Experts and Graph-Based Relation.

Sensors (Basel, Switzerland)·2026
Same journal

Development of an Instrumented Glove for Palmar Pressure Assessment in Kayakers.

Sensors (Basel, Switzerland)·2026
Same journal

Development and Experimental Validation of an Autonomous IoT-Based Monitoring System for Real-Time Water Quality Assessment in the Amazon River.

Sensors (Basel, Switzerland)·2026
Same journal

Semi-Supervised Adversarial Learning Framework for Controller Area Network Bus Intrusion Detection.

Sensors (Basel, Switzerland)·2026
Same journal

Smart Optimization Method for Safety Signs in Innovative Manufacturing Environments Integrating Industrial Field IoT Sensors and Knowledge Graphs.

Sensors (Basel, Switzerland)·2026
See all related articles

Related Experiment Video

Updated: Jul 16, 2025

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.1K

A Cardinality Estimator in Complex Database Systems Based on TreeLSTM.

Kaiyang Qi1, Jiong Yu1,2, Zhenzhen He2

  • 1School of Software, Xinjiang University, Urumqi 830091, China.

Sensors (Basel, Switzerland)
|September 9, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a novel TreeLSTM neural network for more accurate database query cardinality estimation. The new model improves query optimization by better handling complex queries and multiple table correlations.

Keywords:
cardinality estimationdeep learningquery optimizationtree long short-term memory

More Related Videos

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

9.4K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

Related Experiment Videos

Last Updated: Jul 16, 2025

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis
06:56

Author Spotlight: Advancements in X-ray CT Tool Chain for Tree Core Analysis

Published on: September 22, 2023

1.1K
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

9.4K
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

Area of Science:

  • Database Management Systems
  • Artificial Intelligence
  • Machine Learning

Background:

  • Accurate cardinality estimation is crucial for database query optimization.
  • Traditional methods struggle with multi-table correlations and complex queries.
  • Existing learning-based methods show promise but still have limitations.

Purpose of the Study:

  • To develop an advanced cardinality estimation model for complex SQL queries.
  • To improve the accuracy of query optimization in database systems.
  • To address the limitations of current learning-based cardinality estimation techniques.

Main Methods:

  • Proposed a sampling-based Tree Long Short-Term Memory (TreeLSTM) neural network.
  • Modeled SQL queries as trees, considering predicate relationships and join correlations.
  • Introduced a novel loss function to improve estimation accuracy across different cardinality scales.

Main Results:

  • The TreeLSTM model demonstrated superior performance in cardinality estimation.
  • Outperformed traditional methods and other deep learning approaches on real-world datasets.
  • Achieved significant improvements in Q-error, Mean Absolute Error (MAE), and Symmetric Mean Absolute Percentage Error (SMAPE).

Conclusions:

  • The proposed TreeLSTM model effectively captures complex query structures and multi-table join relationships.
  • This approach significantly enhances the accuracy and quality of cardinality estimation.
  • The method offers a promising solution for optimizing complex database queries.