Autonomous Version of Collatz Conjecture: Freedom of Choice Makes Unsolved Problem Solvable

2021 ◽  
Author(s):  
Yurii Sheliazhenko
Keyword(s):  
Unsolved Problem ◽  
Freedom Of Choice ◽  
Collatz Conjecture ◽  
Autonomous Version

Freedom of choice for poor families.

1999 ◽  
Vol 54 (2) ◽  
pp. 144-145 ◽  
Author(s):  
Sandra Scarr
Keyword(s):  
Freedom Of Choice ◽  
Poor Families

Freedom of choice, ease of use, and the formation of consumer preferences

2011 ◽  
Author(s):  
Kyle Murray ◽  
Gerald Haubl
Keyword(s):  
Consumer Preferences ◽  
Ease Of Use ◽  
Freedom Of Choice

Hussein: US Lacks Freedom of Choice

1982 ◽  
Vol 11 (2) ◽  
pp. 164-167
Author(s):  
King Hussein ◽  
Hani Khayr ◽  
Shakri Nasrallah
Keyword(s):  
Freedom Of Choice

Consumers' Freedom of Choice: Lessons from the Cellular Market

2009 ◽  
Author(s):  
Adi Ayal
Keyword(s):  
Freedom Of Choice

Impact of Investor Autonomy and Freedom of Choice on International Stock Market Liquidity Commonality

2017 ◽  
Author(s):  
Pawan Jain ◽  
Mohamed A. Mekhaimer ◽  
Ronald W. Spahr ◽  
Mark Allen Sunderman
Keyword(s):  
Stock Market ◽  
Market Liquidity ◽  
Freedom Of Choice ◽  
Stock Market Liquidity

On the Fundamentals of Collatz Conjecture

2018 ◽  
Author(s):  
Joseph Olloh
Keyword(s):  
Collatz Conjecture

Remote Sensing as a Tool for Archaeological Exploration and Mapping of Archaeological Sites (on the Example of Altai Model Sites)

2019 ◽  
Vol 951 (9) ◽  
pp. 40-54
Author(s):  
E.P. Krupochkin ◽  
S.I. Sukhanov ◽  
D.A. Vorobiev
Keyword(s):  
Remote Sensing ◽  
Computer Vision ◽  
Interdisciplinary Research ◽  
Software Package ◽  
Morphological Analysis ◽  
Remote Sensing Data ◽  
Archaeological Sites ◽  
Freedom Of Choice ◽  
Setting Parameters ◽  
Aerospace Images

The article is devoted to the problem of using remote sensing data for studying and mapping archaeological sites in interdisciplinary research. The purpose of the experiments is to develop a methodology for searching and mapping archeological monuments based on the interpretation of aerospace images. The problem to be solved is formalized search and the procedure of selecting objects. The complex of tasks for ridentifying objects from images cannot be realated only to the field of decryption, it also deals with the field of information processing signals (computer vision), and this is where the great potential for continuing experiments is seen. In the process of implementing the tasks, the Detection Artefacts software package was developed, which is based on noise reduction, filtering, morphological analysis, binarization, etc. Its notable feature is the freedom of choice settings, the ability of setting parameters

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