scholarly journals Artificial intelligence methods in diagnostics of analog systems

2014 ◽  
Vol 24 (2) ◽  
pp. 271-282 ◽  
Author(s):  
Piotr Bilski ◽  
Jacek Wojciechowski
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
The State ◽  
Future Prospects ◽  
Discussion Section ◽  
Artificial Intelligence Methods ◽  
Detection And Identification ◽  
Electronic Filter ◽  
Fault Detection And Identification ◽  
Analog Systems

Abstract The paper presents the state of the art and advancement of artificial intelligence methods in analog systems diagnostics. Firstly, the diagnostic domain is introduced and its problems explained. Then, computational intelligence approaches usable for fault detection and identification are reviewed. Particular groups of methods are presented in detail, explaining their usefulness and drawbacks. Examples, such as the induction motor or the electronic filter, are provided to show the applicability of the presented approaches for monitoring the state of analog objects from engineering domains. The discussion section reviews the presented approaches, their future prospects and problems to be solved.

scholarly journals Artificial intelligence and machine learning in design of mechanical materials

2021 ◽  
Author(s):  
Kai Guo ◽  
Zhenze Yang ◽  
Chi-Hua Yu ◽  
Markus J. Buehler
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
State Of The Art ◽  
The State

This review revisits the state of the art of research efforts on the design of mechanical materials using machine learning.

scholarly journals What you always wanted to know about the deterministic part of the International Planning Competition (IPC) 2014 (but were too afraid to ask)

2018 ◽  
Vol 33 ◽  
Author(s):  
Mauro Vallati ◽  
Lukáš Chrpa ◽  
Thomas L. Mccluskey
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
The State ◽  
Strong Impact ◽  
Significant Progress ◽  
Planning Techniques ◽  
Artificial Intelligence Planning ◽  
The Future ◽  
International Planning ◽  
Planning Approaches

AbstractThe International Planning Competition (IPC) is a prominent event of the artificial intelligence planning community that has been organized since 1998; it aims at fostering the development and comparison of planning approaches, assessing the state-of-the-art in planning and identifying new challenging benchmarks. IPC has a strong impact also outside the planning community, by providing a large number of ready-to-use planning engines and testing pioneering applications of planning techniques.This paper focusses on the deterministic part of IPC 2014, and describes format, participants, benchmarks as well as a thorough analysis of the results. Generally, results of the competition indicates some significant progress, but they also highlight issues and challenges that the planning community will have to face in the future.

scholarly journals Análisis crítico de los NeuroDerechos Humanos al libre albedrío y al acceso equitativo a tecnologías de mejora.

2020 ◽  
Vol 6 (2) ◽  
pp. 135-161
Author(s):  
Diego Alejandro Borbón Rodríguez ◽  
◽  
Luisa Fernanda Borbón Rodríguez ◽  
Jeniffer Laverde Pinzón
Keyword(s):  
Artificial Intelligence ◽  
Human Rights ◽  
Free Will ◽  
New Technologies ◽  
State Of The Art ◽  
The State ◽  
Columbia University ◽  
Equitable Access ◽  
Ethical Implications ◽  
Legal Limits

Advances in neurotechnologies and artificial intelligence have led to an innovative proposal to establish ethical and legal limits to the development of technologies: Human NeuroRights. In this sense, the article addresses, first, some advances in neurotechnologies and artificial intelligence, as well as their ethical implications. Second, the state of the art on the innovative proposal of Human NeuroRights is exposed, specifically, the proposal of the NeuroRights Initiative of Columbia University. Third, the proposal for the rights of free will and equitable access to augmentation technologies is critically analyzed to conclude that, although it is necessary to propose new regulations for neurotechnologies and artificial intelligence, the debate is still very premature as if to try to incorporate a new category of human rights that may be inconvenient or unnecessary. Finally, some considerations on how to regulate new technologies are explained and the conclusions of the work are presented.

RNA Interference Therapeutics and Human Diseases

2019 ◽  
pp. 69-83
Author(s):  
Dolly Sharma ◽  
Shailendra Singh ◽  
Trilok Chand
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Rna Interference ◽  
State Of The Art ◽  
The State ◽  
Human Diseases ◽  
Future Prospects ◽  
The Future ◽  
Rnai Therapeutics ◽  
Interference Rna

Defective protein synthesis leads to diseases. If protein synthesis can be controlled, disease causing molecules can be tailored in some way. This is the perception behind RNA interference. RNA interference (RNAi) therapeutics is branch of medicine which deals with the treatment of diseases while controlling the gene expression at RNA level. The motive of this chapter is to discover the state-of-the-art of RNAi therapeutics, to explore various techniques used by RNAi therapeutics to fight from diseases, and discuss the future prospects of it.

scholarly journals AI Feynman: A physics-inspired method for symbolic regression

2020 ◽  
Vol 6 (16) ◽  
pp. eaay2631 ◽  
Author(s):  
Silviu-Marian Udrescu ◽  
Max Tegmark
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Success Rate ◽  
Unknown Function ◽  
State Of The Art ◽  
Practical Interest ◽  
Symbolic Regression ◽  
The State ◽  
Np Hard ◽  
Test Set

A core challenge for both physics and artificial intelligence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle, functions of practical interest often exhibit symmetries, separability, compositionality, and other simplifying properties. In this spirit, we develop a recursive multidimensional symbolic regression algorithm that combines neural network fitting with a suite of physics-inspired techniques. We apply it to 100 equations from the Feynman Lectures on Physics, and it discovers all of them, while previous publicly available software cracks only 71; for a more difficult physics-based test set, we improve the state-of-the-art success rate from 15 to 90%.

Future Prospects of Superconducting RF for Accelerator Applications

2019 ◽  
Vol 10 (01) ◽  
pp. 125-156 ◽  
Author(s):  
Hasan Padamsee
Keyword(s):  
State Of The Art ◽  
The State ◽  
Future Prospects ◽  
Superconducting Rf ◽  
High Beta ◽  
Future Plans

Part I of this article provides a status update on the ongoing projects for both high-beta and low-beta applications. Some of these projects are already under production, others are perfecting prototypes and future plans. We first cover the funded projects and continue with the planned projects. The update naturally captures the state-of-the-art for superconducting RF (SRF) performance for applications in progress. Part II goes on to present a vision for future prospects for performance progress in the field, along with some advice about the likely fruitful R&D paths to follow. In general, the R&D paths chosen for discussion will benefit most SRF-based accelerators.

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