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

Fineness of Cement01:15

Fineness of Cement

522
The fineness of cement directly influences the rate of hydration, as the hydration begins at the surface of the cement particles. In addition to hydration, the fineness of cement is vital for various properties of concrete including workability, gypsum requirement, and long-term behavior. The fineness of cement is represented in terms of the specific surface of cement which is typically measured in square meters per kilogram, with several methods available for this determination.
Direct...
522
Fineness Modulus01:19

Fineness Modulus

1.5K
The fineness modulus (FM) of aggregate is a numerical index that measures the coarseness or fineness of the particles. It is calculated by adding the cumulative percentages of aggregate retained on each of a specified series of sieves and dividing the sum by 100.
Consider performing sieve analysis on sand through a set of ASTM sieves. The weight of aggregate retained in each sieve and pan placed at the bottom is recorded, as given in Column B of Table 1.
To determine the fineness modulus of...
1.5K
Computed Tomography01:10

Computed Tomography

8.8K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
8.8K
Design Example: Traverse Angle Computations01:25

Design Example: Traverse Angle Computations

342
Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
342
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

647
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
647
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

389
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
389

You might also read

Related Articles

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

Sort by
Same author

Integration of multiple coinflip devices for high-quality random sampling.

Scientific reports·2025
Same author

AI-guided framework for the design of materials and devices for magnetic-tunnel-junction-based true random number generators.

Communications engineering·2025
Same author

The neurobench framework for benchmarking neuromorphic computing algorithms and systems.

Nature communications·2025
Same author

Neuromorphic computing at scale.

Nature·2025
Same author

On the path toward brain-scale simulations.

Nature computational science·2024
Same author

Role of depth in optical diffractive neural networks.

Optics express·2024

Related Experiment Video

Updated: Feb 7, 2026

Determining the Mechanical Strength of Ultra-Fine-Grained Metals
05:04

Determining the Mechanical Strength of Ultra-Fine-Grained Metals

Published on: November 22, 2021

2.6K

Computing with Spikes: The Advantage of Fine-Grained Timing.

Stephen J Verzi1, Fredrick Rothganger2, Ojas D Parekh3

  • 1Energy, Earth and Complex Systems Center, Sandia National Laboratories, NM 87185-1138, U.S.A. sjverzi@sandia.gov.

Neural Computation
|July 19, 2018
PubMed
Summary
This summary is machine-generated.

Spiking algorithms, inspired by neural networks, can enhance computational speed and reduce energy use. This study demonstrates their effectiveness in tasks like sorting and image processing, showing clear performance benefits.

More Related Videos

Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction
09:13

Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction

Published on: April 1, 2017

14.2K
Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

10.8K

Related Experiment Videos

Last Updated: Feb 7, 2026

Determining the Mechanical Strength of Ultra-Fine-Grained Metals
05:04

Determining the Mechanical Strength of Ultra-Fine-Grained Metals

Published on: November 22, 2021

2.6K
Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction
09:13

Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction

Published on: April 1, 2017

14.2K
Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

10.8K

Area of Science:

  • Neuroscience
  • Computer Science
  • Artificial Intelligence

Background:

  • Neural-inspired computing utilizes spike-based communication for potential energy and time efficiency.
  • Fundamental questions persist regarding the quantifiable advantages and optimal application scenarios for spike-based computation compared to conventional methods.
  • Directly translating existing algorithms to a spike-based medium does not inherently guarantee performance gains.

Purpose of the Study:

  • To investigate and demonstrate the performance advantages of spike-based communication and computation within algorithms.
  • To identify specific circumstances where spike-based approaches offer a comparative advantage over traditional computing methods.
  • To present novel spiking algorithms for fundamental computational tasks and an image processing application.

Main Methods:

  • Development and analysis of several spiking algorithms for core computational operations.
  • Implementation of a spiking median-filtering algorithm for image processing.
  • Comparative analysis of throughput and energy efficiency for spike-based versus conventional approaches.

Main Results:

  • Demonstrated that spike-based communication and computation can increase throughput.
  • Showcased cases where spike-based algorithms decrease energy consumption.
  • Presented successful spiking algorithms for sorting, finding extrema, and median calculations.
  • Developed a low-energy, parallel spiking median-filtering approach for image processing.

Conclusions:

  • Spiking algorithms can offer significant performance advantages in specific computational contexts.
  • Efficient computation of fundamental operations using spiking mechanisms is achievable.
  • The presented algorithms and analyses support the utility of spike-based computing for complex applications.