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Young members of the MY-X team co-operate successfully with PhD-Students in frame of the conference of Szarvas!

The MY-X team (incl. joung members) participated on the conference 'In memoriam Enyedi György'

Bárdy-Péter-Prize for a member of the MY-X team concerning his innovation potential!

Gábor-Dénes-Prize (special prize for mathematics) for a member of the MY-X team!

Special Prize in Minsk in frame of an essay-competition for a member of the MY-X team concerning a study about reform approches in education!

III. Prize in the Hlavay competition for a member of the MY-X team!

NTP-NFTÖ financial support for a member of the MY-X team!

Successful presentation in TUDOK-competition in Nyíregyháza and later in Székesfehérvár by a member of the MY-X team!

Last modified: 2015.VII.19.14:08 - MIAÚ-RSS
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Robot for attitude-risk exploration

Leading article: 2018. December (MIAU No. 244.)
(Previous article: MIAU No. 243.)

Keywords: similarity analysis, 2DM-frame

The objective of the study is to show the steps leading to a context-free attitude-risk-evaluation robot which is demonstrated through an example coming from the field of the IT-security – especially it handles with biometrical techniques like fingerprint, face, palm, iris, retina, signature, writing speed, voice, DNA. The attitude-risk will be estimated in case of questionnaires about employee’s attitudes concerning the acceptance of biometrical techniques. Risk should be derived in an automated and consistence-oriented way. Risks can be interpreted both in form of unconscious misunderstanding of questions/answer-options and in form of conscious hidden preferences of the employees. Risk detection can be defined on contextual levels and/or based on context-free logs. The contextual way for risk detection leads to suspected answer-options, questions, persons – based on the estimated answers deriving from each person-question-answer-unit where the number of persons and/or questions should be maximized. The risk can be defined per answer-option as difference between the factual and the estimated answers. The elementary risk components can also be aggregated in case of persons and/or questions. The context-free logs describe the process of the answering based on timestamps and events like dragging/dropping option-cards as mouse movements where specific attributes can be derived from the raw log-data: e.g. duration of answering in general and per question/position, number of corrections, etc. In ideal case, the contextual and log-based suspects will be run parallel, it means, they will give a consistent picture through independent interpretation of contextual and behaviour patterns (which will lead to the same suspicions). Although the demonstration here and now uses phenomena of the IT-security but the entire system can be involved into arbitrary risk detection processes like harmony-defections of sport/work teams. More (DOC) *** More (PDF)

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