User:Cristinac/Day1: Difference between revisions

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hyper association
hyper association
metacognition: when we reflect we can access concepts, flex them and reassociate them
metacognition: when we reflect we can access concepts, flex them and reassociate them
we should look for free will in neuroscience
we should look for free will in neuroscience
Line 55: Line 56:


denial of service
denial of service
data protection: when is data personal or not? Libre text: any information related to an identified or identifiable person
data protection: when is data personal or not? Libre text: any information related to an identified or identifiable person
technical means which can be reasonably used to changing non personal data to personal data
technical means which can be reasonably used to changing non personal data to personal data
combining several data sets: can become a problem
combining several data sets: can become a problem
not an easy thing to analyze, to make sure it isn’t personal data in legal terms
not an easy thing to analyze, to make sure it isn’t personal data in legal terms
research claiming to be able to identify people based on age gender and  
 
research claiming to be able to identify people based on age gender and location
 
based on that research: how to anonymise, are you able to infer data about a person?
based on that research: how to anonymise, are you able to infer data about a person?
not all personal data has to be by definition private
not all personal data has to be by definition private
add noise to be able to maintain anonymity and disguise
add noise to be able to maintain anonymity and disguise
randomization techniques, adding mistakes
randomization techniques, adding mistakes
group people by generalizations: a minimum number prevents people from being identified
group people by generalizations: a minimum number prevents people from being identified
data mining and copyright: search engine on local news articles. 11 words minimum to copyright a title
http://ec.europa.eu/justice/data-protection/index_en.htm
https://en.wikipedia.org/wiki/Homomorphic_encryption
http://dataprotection.ky/index.php/resources/eu-framework
http://www.opendatacenteralliance.org/docs/Data_Security_Framework_Rev1.0.pdf
Group brainstorming
http://10.1.10.1:9001/p/table4b

Latest revision as of 17:15, 19 January 2015

The Nearest Neighbours inherit from their Gold1000 Parent

10.1.10.1 cqrrelations

Gold 1000 dictionaries


:The neural processes of language

Or: why we have a free mind.
Kim Wende


causality-freewill.net

meaningful semantic information in the brain. causality=cement of the universe Axiom: the force is everywhere heteromodal association cortex

Why language/ why the semantic network? free thought ability to create new and meaningful abstract information ex 1: talking in sleep; ex 2: schizophrenia

while we are saying something at the same time we are generating the reason to do so putting energy into word production

language makes us subjective individuals lateralisation cerebellar hemispheric dominance varies between individuals what is semantic memory? continuous “reason production” = verbal fluency the task: 3 conditions: on screen one single word (cue word) then 3 different fluency tasks, semantic associations

what is verbal/conceptual memory? active when you hear language too words that have a meaning=semantic retrieval,

hyper association

metacognition: when we reflect we can access concepts, flex them and reassociate them we should look for free will in neuroscience when we generate explicitly meaning association we put more effort in image retrieving retrieving meaning about relations=causality concept of causality in semantic theory=relatedness, meaningful relations

the germans have 2 words for it: reflection and elaboration (nachdenken)



:(Des)Anonymisation Technique

Hans Lammerant


denial of service

data protection: when is data personal or not? Libre text: any information related to an identified or identifiable person

technical means which can be reasonably used to changing non personal data to personal data

combining several data sets: can become a problem

not an easy thing to analyze, to make sure it isn’t personal data in legal terms

research claiming to be able to identify people based on age gender and location

based on that research: how to anonymise, are you able to infer data about a person?

not all personal data has to be by definition private

add noise to be able to maintain anonymity and disguise

randomization techniques, adding mistakes

group people by generalizations: a minimum number prevents people from being identified

data mining and copyright: search engine on local news articles. 11 words minimum to copyright a title

http://ec.europa.eu/justice/data-protection/index_en.htm

https://en.wikipedia.org/wiki/Homomorphic_encryption

http://dataprotection.ky/index.php/resources/eu-framework

http://www.opendatacenteralliance.org/docs/Data_Security_Framework_Rev1.0.pdf


Group brainstorming

http://10.1.10.1:9001/p/table4b