Autor: Georgiou, M. - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Legal implications of critical infrastructure protection; the experience of the Cyprus Cybercrime Center
Autorzy:: Tsadiras, A.
Bachtsetzis, Ch. S.
Georgiou, M.
Boustras, G.
Mylona, V.
Powiązania:: https://bibliotekanauki.pl/articles/2069222.pdf
Data publikacji:: 2016
Wydawca:: Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:: cybercrime law
legal framework
Cyprus cybercrime
legal implications
cyber security
cyber sexual abuse
Opis:: Cyber related crime is an important aspect of Critical Infrastructure. The recent accession of Cyprus to the EU, its small size and its remoteness are important factors that have influenced its ability to characterize its CI’s as well as create (rather harmonize) its legal background. The paper discusses Directive 2011/-93/EU on combating the sexual abuse and sexual exploitation of children and child pornography and its transposition into the Cyprus legal order. The Directive was incorporated in the Cypriot law with the Prevention and Combating of Sexual Abuse, Sexual Exploitation of Children and Child Pornography Law 91(I)/2014, as amended by Law 105(I)/2014 on Legal Aid, aiming at preventing, suppressing and combating crimes of sexual abuse and sexual exploitation of children, child pornography and solicitation of children for sexual purposes.
Źródło:: Journal of Polish Safety and Reliability Association; 2016, 7, 1; 217--224
2084-5316
Pojawia się w:: Journal of Polish Safety and Reliability Association
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Learning style recognition based on an adjustable three-layer fuzzy cognitive map
Autorzy:: Georgiou, D. A.
Botsios, S.
Mitropoulou, V.
Papaioannou, M.
Schizas, C.
Tsoulouhas, G.
Powiązania:: https://bibliotekanauki.pl/articles/91896.pdf
Data publikacji:: 2011
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: learning style
adaptive educational hypermedia systems
Kolb’s learning cycle
Fuzzy Cognitive Map
FCM
Learning Ability Factors
Bayesian networks
cognitive map
three-layer fuzzy
Opis:: Identification of learning styles supports Adaptive Educational Hypermedia Systems compiling and presenting tutorials custom in cognitive characteristics of each individual learner. This work addresses the issue: identifying the learning style of students, following the Kolb’s learning cycle. To this purpose, we propose a three-layers Fuzzy Cognitive Map (FCM) in conjunction with a dynamic Hebbian rule for learning styles recognition. The form of FCMs is designed by humans who determine its weighted interconnections among concepts. But the human factor may not be as reliable as it should be. Thus, a FCM model of the system allowing the adjustment of its weights using additional learners’ characteristics such as the Learning Ability Factors. In this article, two consecutively interconnected FCM (in the form of a three layer FCM) are presented. The schema’s efficiency has been tested and compared to known results after a fine-tuning of the weights of the causal interconnections among concepts. The simulations results of training the process system verify the effectiveness, validity and advantageous characteristics of those learning techniques for FCMs. The online recognition of learning styles by using threelayer Fuzzy Cognitive Map improves the accuracy of recognition obtained using Bayesian Networks that uses quantitative measurements of learning style taken from statistical samples. This improvement is due to the fuzzy nature of qualitative characterizations (such as learning styles), and the presence of intermediate level nodes representing Learning Ability Factors. Such factors are easily recognizable characteristics of a learner to improve adjustment of weights in edges with one end in the middle-level nodes. This leads to the establishment of a more reliable model, as shown by the results given by the application to a test group of students.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 4; 333-347
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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