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

Self-Evaluation: Self-Enhancement and Self-Verification03:00

Self-Evaluation: Self-Enhancement and Self-Verification

5.8K
Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...
5.8K
Heart Failure IV: Classification and Diagnostic Evaluation01:30

Heart Failure IV: Classification and Diagnostic Evaluation

368
Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
368
Optimal Foraging00:48

Optimal Foraging

13.8K
How animals obtain and eat their food is called foraging behavior. Foraging can include searching for plants and hunting for prey and depends on the species and environment.
13.8K
Classification of Titrimetric Analysis Based on Reaction Types01:01

Classification of Titrimetric Analysis Based on Reaction Types

1.7K
Titrimetric analysis in solution chemistry involves measuring the volume of solutions and is often called volumetric analysis. The standard solution of known concentration in the burette is called the titrant, whereas the solution of unknown concentration in the flask is called the analyte, or titrand. Titrimetric analyses can be classified into four types based on the reactions between the titrant and analyte.
Titrations between an acid and a base lead to neutralization reactions that form...
1.7K
Cardiovascular Drugs: Classification based on Therapeutic Indications01:18

Cardiovascular Drugs: Classification based on Therapeutic Indications

4.2K
Cardiovascular diseases, encompassing a range of conditions, can significantly affect the heart's operations and the overall circulatory system. These conditions impair the heart's ability to pump blood, leading to a deficit in oxygen supply to crucial organs. Anomalies in the heart's electrical system, known as arrhythmias, can cause heartbeats to accelerate or slow down. Usually, heart rates increase during physical activity and decrease while resting or sleeping. However,...
4.2K
Interpreting R Charts01:22

Interpreting R Charts

348
R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
348

You might also read

Related Articles

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

Sort by
Same author

A New Many-Objective Optimization Approach to Association Rule Mining: The NSGA-II/DE-ARM Algorithm.

Biomimetics (Basel, Switzerland)·2026
Same author

Chaos-Embedded Multi-Objective Intelligent Optimization-Based Explainable Classification Model for Determining Cherry Fruit Fly Infestation Levels Using Pomological Data.

Biomimetics (Basel, Switzerland)·2026
Same author

Biologically Based Intelligent Multi-Objective Optimization for Automatically Deriving Explainable Rule Set for PV Panels Under Antarctic Climate Conditions.

Biomimetics (Basel, Switzerland)·2025
Same author

Innovative multi objective optimization based automatic fake news detection.

PeerJ. Computer science·2025
Same author

A novel deep learning approach for predicting stone-free rates post-ESWL on uncontrasted CT.

PeerJ. Computer science·2025
Same author

Multi-task advanced convolutional neural network for robust lymphoblastic leukemia diagnosis, classification, and segmentation.

PeerJ. Computer science·2025
Same journal

Multiphysics Investigation on Thermal Characteristics of Internal Bio-Inspired V-Ribbed Cooling Channels for Outer Rotor PMSM.

Biomimetics (Basel, Switzerland)·2026
Same journal

Smart Logistics Model for Supply Chain Management via Brain-Inspired Geometric Deep Networks.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Systematic Taxonomy of the Sunflower Optimization Algorithm: Variants, Hybridization Strategies, Applications, and Research Directions.

Biomimetics (Basel, Switzerland)·2026
Same journal

Toward a Compositional Theory of Trust in Embodied Intelligence: A QNLP Framework for Modeling Context, Interaction, and Trustworthiness.

Biomimetics (Basel, Switzerland)·2026
Same journal

Empirical Logic for Bio-Inspired Soft Computing: Illustrative Applications in Control Engineering and Cluster Analysis.

Biomimetics (Basel, Switzerland)·2026
Same journal

A Modified Multi-Strategy Dhole Optimization Algorithm and Its Engineering Applications.

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

Related Experiment Video

Updated: Jan 28, 2026

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

11.9K

Chaos-Enhanced, Optimization-Based Interpretable Classification Model and Performance Evaluation in Food Drying.

Cagri Kaymak1, Bilal Alatas2, Suna Yildirim3

  • 1Department of Mechatronics Engineering, Faculty of Engineering, Firat University, Elazig 23119, Turkey.

Biomimetics (Basel, Switzerland)
|January 27, 2026
PubMed
Summary
This summary is machine-generated.

This study uses explainable artificial intelligence (XAI) to optimize hot-air food drying, identifying temperature and air velocity as key factors for efficient Paşa pear drying.

Keywords:
energy efficiencyexplainable artificial intelligencerule miningsmart food dryingsunflower optimization algorithm

More Related Videos

Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

1.6K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.0K

Related Experiment Videos

Last Updated: Jan 28, 2026

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification
07:47

Design and Evaluation of Smart Glasses for Food Intake and Physical Activity Classification

Published on: February 14, 2018

11.9K
Design and Optimization Strategies of a High-Performance Vented Box
14:23

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

1.6K
Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
07:35

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances

Published on: October 11, 2018

8.0K

Area of Science:

  • Agricultural Engineering
  • Food Science
  • Artificial Intelligence

Background:

  • Food drying is crucial for preservation but faces challenges in energy efficiency and quality maintenance.
  • Hot-air drying is a common method, but optimizing its parameters for regional pears like Paşa pear requires advanced analysis.

Purpose of the Study:

  • To analyze experimental data from Paşa pear hot-air drying using an explainable artificial intelligence (XAI) method.
  • To develop an intelligent drying system with autonomous control for optimizing energy efficiency and product quality.

Main Methods:

  • Utilized an intelligent drying system with a PLC-based control mechanism operating at 50°C/65°C and 0.63 m/s/1.03 m/s.
  • Applied the oscillatory chaotic sunflower optimization algorithm (OCSFO) to analyze multidimensional control and process data.
  • Developed interpretable rules without data discretization for performance classification.

Main Results:

  • Drying performance varied significantly with operating conditions, reducing product mass from 450g to 103g.
  • OCSFO achieved over 90% success in classifying drying performance into high, medium, and low classes.
  • Identified drying temperature and air velocity as dominant parameters influencing drying efficiency.

Conclusions:

  • Explainable AI, specifically OCSFO, provides a robust framework for understanding complex drying dynamics.
  • The study demonstrates that temperature and air velocity are critical for efficient pear drying, with energy consumption and cabin temperature playing supporting roles.
  • This transparent AI approach offers a valuable tool for optimizing food preservation processes.