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Select data courtesy of the U.S. National Library of Medicine.

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Kybernetes

Subject:
Artificial Intelligence
Publisher:
MCB UP Ltd —
Emerald Publishing
ISSN:
0368-492X
Scimago Journal Rank:
43

2023

Volume 52
Issue 13 (Feb)Issue 9 (Sep)Issue 8 (Aug)Issue 7 (Jul)Issue 6 (May)Issue 5 (May)Issue 4 (Mar)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

2022

Volume 51
Issue 13 (Dec)Issue 12 (Nov)Issue 11 (Nov)Issue 10 (Nov)Issue 9 (Sep)Issue 8 (Jul)Issue 7 (May)Issue 6 (May)Issue 5 (Mar)Issue 4 (Mar)Issue 3 (Feb)Issue 2 (Feb)Issue 1 (Jan)

2021

Volume 50
Issue 12 (Nov)Issue 11 (Nov)Issue 10 (Oct)Issue 9 (Aug)Issue 8 (Jul)Issue 7 (Jul)Issue 6 (Jul)Issue 4 (May)Issue 3 (Mar)Issue 2 (Mar)Issue 1 (Mar)

2020

Volume 50
Issue 3 (Oct)
Volume 49
Issue 12 (Nov)Issue 11 (Oct)Issue 10 (Sep)Issue 9 (Sep)Issue 8 (Aug)Issue 7 (May)Issue 6 (Jun)Issue 5 (Apr)Issue 4 (Apr)Issue 3 (Feb)Issue 2 (Jan)Issue 1 (Jan)

2019

Volume 49
Issue 10 (Nov)Issue 7 (Jul)Issue 3 (Sep)Issue 2 (Apr)Issue 1 (Oct)
Volume 48
Issue 10 (Oct)Issue 9 (Sep)Issue 8 (Sep)Issue 7 (Sep)Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Feb)Issue 2 (Feb)Issue 1 (Jan)

2018

Volume 47
Issue 10 (Oct)Issue 9 (Sep)Issue 8 (Sep)Issue 7 (Aug)Issue 6 (May)Issue 5 (May)Issue 4 (Mar)Issue 3 (Feb)Issue 2 (Feb)Issue 1 (Jan)

2017

Volume 46
Issue 10 (Nov)Issue 9 (Nov)Issue 8 (Sep)Issue 7 (Aug)Issue 06 (Jun)Issue 5 (May)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

2016

Volume 45
Issue 10 (Nov)Issue 9 (Oct)Issue 8 (Sep)Issue 7 (Aug)Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

2015

Volume 44
Issue 10 (Nov)Issue 8/9 (Sep)Issue 6/7 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

2014

Volume 43
Issue 9/10 (Nov)Issue 8 (Aug)Issue 7 (Jul)Issue 6 (Jul)Issue 5 (May)Issue 3/4 (Apr)Issue 2 (Feb)Issue 1 (Jan)

2013

Volume 42
Issue 9/10 (Oct)Issue 8 (Aug)Issue 7 (Jul)Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

2012

Volume 41
Issue 10 (Oct)Issue 9 (Oct)Issue 7/8 (Aug)Issue 5/6 (Jun)Issue 3/4 (Apr)Issue 1/2 (Mar)

2011

Volume 40
Issue 9/10 (Oct)Issue 7/8 (Aug)Issue 5/6 (Jun)Issue 3/4 (May)Issue 1/2 (Mar)

2010

Volume 39
Issue 9/10 (Oct)Issue 8 (Aug)Issue 7 (Aug)Issue 6 (Jun)Issue 5 (Jun)Issue 4 (May)Issue 3 (May)Issue 2 (Mar)Issue 1 (Mar)

2009

Volume 38
Issue 10 (Jan)Issue 9 (Oct)Issue 7/8 (Jan)Issue 6 (Jan)Issue 5 (Jan)Issue 3/4 (Jan)Issue 1/2 (Feb)

2008

Volume 37
Issue 9/10 (Oct)Issue 8 (Sep)Issue 7 (Sep)Issue 6 (Jun)Issue 5 (Jun)Issue 3/4 (Apr)Issue 2 (Feb)Issue 1 (Feb)

2007

Volume 36
Issue 9/10 (Oct)Issue 7/8 (Aug)Issue 5/6 (Jun)Issue 3/4 (Apr)Issue 2 (Feb)Issue 1 (Feb)

2006

Volume 35
Issue 10 (Dec)Issue 9 (Oct)Issue 7/8 (Aug)Issue 6 (Jul)Issue 5 (Jun)Issue 3/4 (Mar)Issue 1/2 (Jan)

2005

Volume 34
Issue 9/10 (Oct)Issue 7/8 (Aug)Issue 6 (Jul)Issue 5 (Jun)Issue 3/4 (Mar)Issue 1/2 (Jan)

2004

Volume 33
Issue 9/10 (Oct)Issue 8 (Sep)Issue 7 (Aug)Issue 5/6 (Jun)Issue 3/4 (Mar)Issue 2 (Feb)Issue 1 (Jan)

2003

Volume 32
Issue 9/10 (Dec)Issue 7/8 (Oct)Issue 5/6 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 1/2 (Feb)

2002

Volume 31
Issue 9/10 (Dec)Issue 7/8 (Oct)Issue 6 (Aug)Issue 5 (Jul)Issue 3/4 (Apr)Issue 2 (Mar)Issue 1 (Feb)

2001

Volume 30
Issue 9/10 (Dec)Issue 7/8 (Oct)Issue 5/6 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

2000

Volume 29
Issue 9/10 (Dec)Issue 7/8 (Oct)Issue 5/6 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1999

Volume 28
Issue 9 (Dec)Issue 8 (Nov)Issue 6/7 (Aug)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1998

Volume 27
Issue 9 (Dec)Issue 8 (Nov)Issue 6/7 (Aug)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1997

Volume 26
Issue 9 (Dec)Issue 8 (Nov)Issue 6/7 (Aug)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1996

Volume 25
Issue 9 (Dec)Issue 7/8 (Oct)Issue 6 (Aug)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1995

Volume 24
Issue 9 (Dec)Issue 8 (Nov)Issue 7 (Oct)Issue 6 (Aug)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1994

Volume 23
Issue 9 (Dec)Issue 8 (Nov)Issue 6/7 (Aug)Issue 5 (Jul)Issue 4 (Jun)Issue 3 (Apr)Issue 2 (Mar)Issue 1 (Feb)

1993

Volume 22
Issue 8 (Aug)Issue 7 (Jul)Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1992

Volume 21
Issue 7 (Jul)Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1991

Volume 20
Issue 7 (Jul)Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1990

Volume 19
Issue 6 (Jun)Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1989

Volume 18
Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1988

Volume 17
Issue 5 (May)Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1987

Volume 16
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1986

Volume 15
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1985

Volume 14
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1984

Volume 13
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1983

Volume 12
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1982

Volume 11
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1981

Volume 10
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1980

Volume 9
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1979

Volume 8
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1978

Volume 7
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1977

Volume 6
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1976

Volume 5
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1975

Volume 4
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1974

Volume 3
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1973

Volume 2
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)

1972

Volume 1
Issue 4 (Apr)Issue 3 (Mar)Issue 2 (Feb)Issue 1 (Jan)
journal article
LitStream Collection
Object detecting artificial retina

James G. Wilson; Richard J. Mitchell

2000 Kybernetes

doi: 10.1108/03684920010308835

This paper describes the novel use of agent and cellular neural Hopfield network techniques in the design of a self‐contained, object detecting retina. The agents, which are used to detect features within an image, are trained using the Hebbian method which has been modified for the cellular architecture. The success of each agent is communicated with adjacent agents in order to verify the detection of an object. Initial work used the method to process bipolar images. This has now been extended to handle grey scale images. Simulations have demonstrated the success of the method and further work is planned in which the device is to be implemented in hardware.
journal article
LitStream Collection
The second stir and incompleteness of quantitative analysis

Shoucheng Ou Yang; Jinghai Miao; Yong Wu; Yi Lin; Taoyong Peng; Tiangui Xiao

2000 Kybernetes

doi: 10.1108/03684920010308853

Based on the summary and analysis of the particle dynamics, developed in the past 300 years, and of fundamental properties of unevenness of natural materials, we propose the opinion of the second stir. We analyze the gains and loses of employing the non‐dimensionalization method developed in the quantitative analysis system of the first push. Combined with some theoretical models, we also consider the epistemological failures of pure quantification, linearization, and formal logic analysis.
journal article
LitStream Collection
Generation of ॅ‐dense curves and application to global optimization

A. Ziadi; Y. Cherruault

2000 Kybernetes

doi: 10.1108/03684920010308871

The reducing transformation and global optimization technique called Alienor has been developed in the 1980s by Cherruault and Guillez. These methods are based on the approximating properties of ॅ ‐dense curves. The aim of this work is to give a very large class of functions generating ॅ ‐dense curves in a hyper‐rectangle of R n .
journal article
LitStream Collection
The forecasting performance of Cartesian ARIMA search and a vector‐valued state space model

Ralf Östermark

2000 Kybernetes

doi: 10.1108/03684920010308862

The performance of Aoki’s state space algorithm and the Cartesian ARIMA search algorithm (CARlMA) of Östermark and Höglund is compared. The analysis is carried out on a set of stock prices on the Helsinki (Finland) and Stockholm (Sweden) Stock Exchanges. Demonstrates that the Finnish and Swedish stock markets differ in predictability of stock prices. With Finnish stock data, Aoki’s state space algorithm outperforms the subset of MAPE minimizing forecasts. In contrast, with Swedish stock data, ARIMA‐models of a fairly simple structure outperform Aoki’s algorithm. The stock markets are seen to differ in complexity of time series models as well as in predictability of individual asset prices.
journal article
LitStream Collection
Automation seen as delegation

Janusz Bucki; Yvon Pesqueux

2000 Kybernetes

doi: 10.1108/03684920010308880

Companies are becoming more and more dependent on data processing systems. In this context, cybernetics again finds its meaning dealing with man‐machine communication problems. The two professions (data‐processing and management) have to find an answer to the same question: how to present a model of a company as a complex system? Decision system analysis follows this trend and suggests a set of concepts and approaches that allows us to analyze and conceive complex systems, whether they be human organizations or systems of artefacts. Despite the fact that it belongs to the cybernetic trend of thinking, the analysis integrates such notions as culture, creativity, well‐being, goals, real time, suggesting a more complete vision of these aspects starting from a logical deductive model, to a renewed cybernetic vision.
journal article
LitStream Collection
Impossible measures, Contonian appearances Interpretation of the effect of high dilutions by building the Feynman measure in the real numbers of Levy and in the Solovay theory

Henri Berliocchi

2000 Kybernetes

doi: 10.1108/03684920010308899

A protocol showing the ॆ − activity of high dilutions of nitric acid is described. It is given a physical mathematical frame founded on a an approach of quantum relativistic field based on the theory of Solovay (ethers theory, remanent wave).
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