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

Electron Transport Chains01:28

Electron Transport Chains

112.2K
The final stage of cellular respiration is oxidative phosphorylation that consists of two steps: the electron transport chain and chemiosmosis. The electron transport chain is a set of proteins found in the inner mitochondrial membrane in eukaryotic cells. Its primary function is to establish a proton gradient that can be used during chemiosmosis to produce ATP and generate electron carriers, such as NAD+ and FAD, that are used in glycolysis and the citric acid cycle.
The ETC is comprised of...
112.2K
Machines01:19

Machines

579
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. One example of a machine is the cutting plier, which is used to cut wires by applying forces to its handles. When equal and opposite forces are exerted on the handles of the cutting plier, they cause the cutting edges to come together and apply equal and opposite reaction forces on the wire, which are greater than the applied forces.
A free-body diagram of the...
579
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

420
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
420
GIS Software, Hardware, and Sources of GIS Data01:23

GIS Software, Hardware, and Sources of GIS Data

787
A Geographic Information System (GIS) combines specialized software and hardware to effectively manage, analyze, and present spatial and related data. GIS software includes critical functionalities such as a user interface for easy navigation, database management tools for handling spatial and attribute data, and data retrieval features for efficient access. Analytical tools transform raw data into insights, while display functions produce maps and reports in various formats for effective...
787
Machines: Problem Solving II01:30

Machines: Problem Solving II

668
Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.
668
Machines: Problem Solving I01:22

Machines: Problem Solving I

714
A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...
714

You might also read

Related Articles

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

Sort by
Same author

Effect of Mo on Microstructures and Wear Properties of In Situ Synthesized Ti(C,N)/Ni-Based Composite Coatings by Laser Cladding.

Materials (Basel, Switzerland)·2017
Same author

Brain Membrane Proteome and Phosphoproteome Reveal Molecular Basis Associating with Nursing and Foraging Behaviors of Honeybee Workers.

Journal of proteome research·2017
Same author

A pairwise likelihood augmented Cox estimator for left-truncated data.

Biometrics·2017
Same author

Novel Three-Dimensional Semiconducting Materials Based on Hybrid d<sup>10</sup> Transition Metal Halogenides as Visible Light-Driven Photocatalysts.

Inorganic chemistry·2017
Same author

Association of lymphocyte-to-monocyte ratio with in-hospital and long-term major adverse cardiac and cerebrovascular events in patients with ST-elevated myocardial infarction.

Medicine·2017
Same author

Tendon injuries: Basic science and new repair proposals.

EFORT open reviews·2017
Same journal

Large-scale discovery and annotation of substructure patterns in mass spectrometry profiles.

Nature communications·2026
Same journal

Salmonella SopB suppresses post-transcriptionally regulated cytokine release to reduce early tissue inflammation and delay disease progression.

Nature communications·2026
Same journal

A human-specific microRNA controls the timing of excitatory synaptogenesis.

Nature communications·2026
Same journal

An HMA-like integrated domain in the wheat tandem kinase WTK4 recognises an RNase-like pathogen effector.

Nature communications·2026
Same journal

Learning regularities in noise engages both neural predictive activity and representational changes.

Nature communications·2026
Same journal

The H3K4 methyltransferase KMT2D is an essential cofactor for GATA1 at erythroid gene enhancers.

Nature communications·2026
See all related articles

Related Experiment Video

Updated: Feb 3, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.5K

A hardware Markov chain algorithm realized in a single device for machine learning.

He Tian1,2, Xue-Feng Wang3,4, Mohammad Ali Mohammad5

  • 1Institute of Microelectronics, Tsinghua University, Beijing, 100084, China. tianhe88@tsinghua.edu.cn.

Nature Communications
|October 19, 2018
PubMed
Summary
This summary is machine-generated.

Researchers developed a single-device Markov chain algorithm using tin selenide. This breakthrough enables machine learning hardware cores, demonstrating a random number generator with a 5% error rate.

More Related Videos

Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.1K

Related Experiment Videos

Last Updated: Feb 3, 2026

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

7.5K
Constructing and Visualizing Models using Mime-based Machine-learning Framework
06:19

Constructing and Visualizing Models using Mime-based Machine-learning Framework

Published on: July 22, 2025

2.5K
A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.1K

Area of Science:

  • Materials Science
  • Computer Engineering
  • Nanotechnology

Background:

  • Machine learning applications require significant on-chip resources like transistors and memory.
  • Implementing machine learning capabilities within a single, compact device has been a major challenge.

Purpose of the Study:

  • To develop a single-device hardware core capable of executing a Markov chain algorithm.
  • To explore the potential of two-dimensional multilayer tin selenide for novel computing applications.

Main Methods:

  • Fabrication of vertical tin oxide/tin selenide/tin oxide heterostructures.
  • Probing electrical transport properties and observing current jumps during set/reset processes.
  • Classifying observed filament states to represent Markov chain states and analyzing state transition probabilities.

Main Results:

  • Observed two sudden current jumps during electrical switching in the heterostructure device.
  • Identified and classified five distinct filament states, mapping them to three Markov chain states.
  • Demonstrated a fixed-probability random number generator with a low error rate of 5%.

Conclusions:

  • A single device based on tin selenide can successfully implement a Markov chain algorithm.
  • This approach offers a pathway towards integrated, low-resource machine learning hardware.
  • The device shows promise for applications such as random number generation.