A Perforating Tool Kit as a Computational Paradigm

2016 ◽  
Author(s):  
Jim Wight ◽  
G. G. Craddock ◽  
Dennis Haggerty ◽  
Fabian Rojas ◽  
Jonathan Montiverdi ◽  
...  
Keyword(s):  
Computational Paradigm

scholarly journals New Technologies of Motor Control and Rehabilitation

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Albertas Skurvydas
Keyword(s):  
Motor Control ◽  
New Technologies ◽  
Modern Science ◽  
Computational Approach ◽  
Neural Cells ◽  
Motor Rehabilitation ◽  
Principal Mechanism ◽  
Brain Stroke ◽  
Computational Paradigm ◽  
The Brain

Modern paradigms of motor control and rehabilitation are analyzed in the paper. Two main paradigms, i. e. computational approach and dynamical system approach are engaged in rivalry in motor control and learning research at present. From the standpoint of computational paradigm the principal mechanism of motor control and learning consists in the ability of the brain “to calculate” (acting as some kind of biological computer). According to the paradigm of dynamical systems the mechanism of motor control is time dependent. In other words, it can be different each time. The main principles of motor control and properties of movements are given considerable attention in the paper. Besides, modern methods of motor rehabilitation after stroke are emphasized in the paper. Fitting of neuroprosthesis and restoration of damaged neural cells are significant maiden steps in modern science. The scientists are engaged in search for: a) constraining such mechanism prosthesis that would submit to the efforts of human will and b) restoring neural cells damaged because of the brain stroke suffered.Keywords: motor control, rehabilitation, stroke.

Intermezzo

2014 ◽  
Author(s):  
Subrata Dasgupta
Keyword(s):  
High School ◽  
World War Ii ◽  
A Priori ◽  
World War ◽  
Structure Of Scientific Revolutions ◽  
Scientific Context ◽  
Computational Paradigm ◽  
Doctoral Work ◽  
Mature Science ◽  
Dominant Paradigm

By the end of World War II, independent of one another (and sometimes in mutual ignorance), a small assortment of highly creative minds—mathematicians, engineers, physicists, astronomers, and even an actuary, some working in solitary mode, some in twos or threes, others in small teams, some backed by corporations, others by governments, many driven by the imperative of war—had developed a shadowy shape of what the elusive Holy Grail of automatic computing might look like. They may not have been able to define a priori the nature of this entity, but they were beginning to grasp how they might recognize it when they saw it. Which brings us to the nature of a computational paradigm. Ever since the historian and philosopher of science Thomas Kuhn (1922–1996) published The Structure of Scientific Revolutions (1962), we have all become ultraconscious of the concept and significance of the paradigm, not just in the scientific context (with which Kuhn was concerned), but in all intellectual and cultural discourse. A paradigm is a complex network of theories, models, procedures and practices, exemplars, and philosophical assumptions and values that establishes a framework within which scientists in a given field identify and solve problems. A paradigm, in effect, defines a community of scientists; it determines their shared working culture as scientists in a branch of science and a shared mentality. A hallmark of a mature science, according to Kuhn, is the emergence of a dominant paradigm to which a majority of scientists in that field of science adhere and broadly, although not necessarily in detail, agree on. In particular, they agree on the fundamental philosophical assumptions and values that oversee the science in question; its methods of experimental and analytical inquiry; and its major theories, laws, and principles. A scientist “grows up” inside a paradigm, beginning from his earliest formal training in a science in high school, through undergraduate and graduate schools, through doctoral work into postdoctoral days. Scientists nurtured within and by a paradigm more or less speak the same language, understand the same terms, and read the same texts (which codify the paradigm).

scholarly journals A computational paradigm for real-time MEG neurofeedback for dynamic allocation of spatial attention

2020 ◽  
Vol 19 (1) ◽  
Author(s):  
Kunjan D. Rana ◽  
Sheraz Khan ◽  
Matti S. Hämäläinen ◽  
Lucia M. Vaina
Keyword(s):  
Real Time ◽  
Spatial Attention ◽  
Dynamic Allocation ◽  
Computational Paradigm

scholarly journals Brain-inspired computational paradigm dedicated to fault diagnosis of PEM fuel cell stack

2017 ◽  
Vol 42 (8) ◽  
pp. 5410-5425 ◽  
Author(s):  
Zhixue Zheng ◽  
Simon Morando ◽  
Marie-Cécile Pera ◽  
Daniel Hissel ◽  
Laurent Larger ◽  
...  
Keyword(s):  
Fuel Cell ◽  
Fault Diagnosis ◽  
Pem Fuel Cell ◽  
Fuel Cell Stack ◽  
Computational Paradigm

A computational paradigm for multiresolution topology optimization (MTOP)

2009 ◽  
Vol 41 (4) ◽  
pp. 525-539 ◽  
Author(s):  
Tam H. Nguyen ◽  
Glaucio H. Paulino ◽  
Junho Song ◽  
Chau H. Le
Keyword(s):  
Topology Optimization ◽  
Computational Paradigm ◽  
Multiresolution Topology Optimization

INTERACTION-ORIENTED SOFTWARE DEVELOPMENT

2001 ◽  
Vol 11 (03) ◽  
pp. 259-279 ◽  
Author(s):  
MICHAEL N. HUHNS
Keyword(s):  
Software Engineering ◽  
Software Development ◽  
Software Components ◽  
New Approach ◽  
Reusable Software ◽  
Current State ◽  
Computational Paradigm ◽  
And Behavior

This paper describes a new approach to the production of robust software. We first motivate the approach by explaining why the two major goals of software engineering — correct software and reusable software — are not being addressed by the current state of software practice. We then describe a methodology based on active, cooperative, and persistent software components, i.e., agents, and show how the methodology produces robust and reusable software. We derive requirements for the structure and behavior of the agents, and report on preliminary experiments on applications based on the methodology. We conclude with a roadmap for development of the methodology and ruminations about uses for the new computational paradigm.

Sign in / Sign up

Export Citation Format

Share Document