User:Cristinac/Day1: Difference between revisions
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Gold 1000 dictionaries | Gold 1000 dictionaries | ||
:The neural processes of language | '':The neural processes of language | ||
:Or: why we have a free mind. | :Or: why we have a free mind. | ||
:Kim Wende | :Kim Wende'' | ||
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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 50: | Line 51: | ||
:(Des)Anonymisation Technique | '':(Des)Anonymisation Technique | ||
:Hans Lammerant | :Hans Lammerant'' | ||
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 18:15, 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