Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Distributed Loads: Problem Solving

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

Quantifying Work

Quantifying Work

As a system undergoes a change, its internal energy can change, and energy can be transferred from the system to the surroundings, or from the surroundings to the system.

Distributed Loads

Distributed Loads

Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...

Principle of Virtual Work: Problem Solving

Principle of Virtual Work: Problem Solving

The principle of virtual work is an essential concept in the field of mechanics and engineering. This is used to solve problems related to the equilibrium of a structure or system. It is based on the assumption that if a system is in equilibrium, the work done by all the forces during a virtual displacement is zero. This principle is applied by considering virtual displacements of the system and the corresponding work done by internal and external forces.
To apply the principle of virtual work,...

Work Done During Volume Change

Work Done During Volume Change

In mechanics, work is done on an object when the force acting on it displaces the object. In thermodynamics, work done on a system can be estimated when the system's volume changes during any thermodynamic process.
Consider a gas confined to a cylinder fitted with a movable piston at one end. If the gas expands from volume V1 to volume V2, it exerts a force on the piston, such that the piston moves by a distance dr.
The work done by the gas on the piston can be expressed as

You might also read

Related Articles

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

Sort by

Same author

Association of Porcine Swine Leukocyte Antigen (SLA) Haplotypes with B- and T-Cell Immune Response to Foot-and-Mouth Disease Virus (FMDV) Peptides.

Vaccines·2020

Same author

Data-Driven Interaction Review of an Ed-Tech Application.

Sensors (Basel, Switzerland)·2019

Same author

A Comparison of Machine Learning and Deep Learning Techniques for Activity Recognition using Mobile Devices.

Sensors (Basel, Switzerland)·2019

Same author

Evolutionary Design of Convolutional Neural Networks for Human Activity Recognition in Sensor-Rich Environments.

Sensors (Basel, Switzerland)·2018

Search research articles

Related Experiment Videos

Coin.AI: A Proof-of-Useful-Work Scheme for Blockchain-Based Distributed Deep Learning.

Alejandro Baldominos¹, Yago Saez¹

¹Computer Science Department, Universidad Carlos III of Madrid, Leganés, 28911 Madrid, Spain.

Entropy (Basel, Switzerland)

|December 3, 2020

Summary

This paper proposes Coin.AI, a novel cryptocurrency using proof-of-useful-work by training deep learning models for mining. This approach aims to reduce energy consumption and democratize AI access.

Keywords:

blockchain cryptocurrency deep learning neural networks proof-of-work

Related Experiment Videos

Area of Science:

Computer Science
Artificial Intelligence
Blockchain Technology

Background:

Cryptocurrencies like Bitcoin utilize proof-of-work (PoW) for block generation, often involving energy-intensive cryptographic problem-solving.
The primary drawback of traditional PoW is its substantial energy consumption with no tangible real-world utility beyond network security.

Purpose of the Study:

To introduce a theoretical proof-of-useful-work (PoUW) scheme for a cryptocurrency named Coin.AI.
To propose an alternative to energy-intensive PoW by integrating deep learning model training into the mining process.

Main Methods:

The Coin.AI system mandates miners to train deep learning models; block generation is contingent upon achieving a performance threshold.
A distributed verification mechanism allows nodes to efficiently validate trained models, triggering block creation.
A proof-of-storage scheme is introduced to incentivize users for hosting deep learning models.

Main Results:

The proposed PoUW system offers a theoretical framework for energy-efficient cryptocurrency mining.
The system enables efficient model verification by network nodes.
It establishes a mechanism for rewarding storage providers within the network.

Conclusions:

Coin.AI presents a viable alternative to traditional PoW, aligning cryptocurrency mining with productive computational tasks.
The proposed system has the potential to democratize access to artificial intelligence by leveraging distributed computing resources.