Proceedings Scholar Metrics: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2011-2015)

The objective of this report is to present a list of proceedings (conferences, workshops, symposia, meetings) in the areas of Computer Science, Electrical & Electronic Engineering, and Communications covered by Google Scholar Metrics and ranked according to their h-index. Google Scholar Metrics only displays publications that have published at least 100 papers and have received at least one citation in the last five years (2010-2014). The searches were conducted between the 7th and 12th of December, 2016. A total of 1634 proceedings have been identified.Martín-Martín, A.; Ayllón, JM.; Orduña Malea, E.; Delgado López-Cózar, E. (2016). Proceedings Scholar Metrics: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2011-2015). http://hdl.handle.net/10251/11237

Proceedings Scholar Metrics 2017: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2012-2016)

EC3 Reports;22The objective of this report is to present a list of proceedings (conferences, workshops, symposia, meetings) in the areas of Computer Science, Electrical & Electronic Engineering, and Communications covered by Google Scholar Metrics and ranked according to their h-index. Google Scholar Metrics only displays publications that have published at least 100 papers and have received at least one citation in the last five years (2012-2016). The currently were conducted between the 18th and 22th of December, 2017. A total of 1,918 queries proceedings have been identified.Delgado López-Cózar, E.; Orduña Malea, E. (2017). Proceedings Scholar Metrics 2017: H Index of proceedings on Computer Science, Electrical & Electronic Engineering, and Communications according to Google Scholar Metrics (2012-2016). http://hdl.handle.net/10251/11237

The DKAP Project The Country Report of Vietnam

Viet Nam is at the beginning of the Fourth Industrial Revolution. In order to grasp the opportunities that the revolution has brought about, and to successfully build the society of digital citizens, there must be the demand of enhancing the capacity and capability for students to meet international standards in terms of Information and Communications Technology (ICT) skills. Viet Nam was selected as one of the four countries (Viet Nam, Bangladesh, Fiji, and the Republic of Korea) to join UNESCO Bangkok’s “Digital Kids Asia Pacific (DKAP)” project, a comparative cross-national study with the aim to seek the understanding and address children’s ICT practices, attitudes, behaviors, and competency levels within an educational context. Thanks to the project, the Vietnamese research team completely conducted the survey in twenty (20) schools from five (5) provinces in Viet Nam. With the data on the digital citizenship competency levels of 1,061 10th grade students, the research team discovered the valuable findings to draw an initial big picture for Vietnamese policy makers, educators, and teachers about digital citizenship competencies of 15-year-old Vietnamese students

A discourse in conflict : resolving the definitional uncertainty of cyber war : a thesis presented in partial fulfilment for the requirements for the degree of Master of Arts in Defence and Security Studies at Massey University, Albany, New Zealand

Since emerging in academic literature in the 1990s, definitions of ‘cyber war’ and cyber warfare’ have been notably inconsistent. There has been no research that examines these inconsistencies and whether they can be resolved. Using the methodology of discourse analysis, this thesis addresses this research need. Analysis has identified that the study of cyber war and cyber warfare is inherently inter-disciplinary. The most prominent academic disciplines contributing definitions are Strategic Studies, Security Studies, Information and Communications Technology, Law, and Military Studies. Despite the apparent definitional uncertainty, most researchers do not offer formal definitions of cyber war or cyber warfare. Moreover, there is little evidentiary basis in literature to distinguish between cyber war and cyber warfare. Proximate analysis of definitions of cyber war and cyber warfare suggests a high level of inconsistency between dozens of definitions. However, through deeper analysis of both the relationships between definitions and their underlying structure, this thesis demonstrates that (a) the relationships between definitions can be represented hierarchically, through a discourse hierarchy of definitions; and (b) all definitions share a common underlying structure, accessible through the application of a structural definition model. Crucially, analysis of definitions via these constructs allows a foundational definition of cyber war and cyber warfare to be identified. Concomitantly, use of the model identifies the areas of greatest inter-definitional inconsistency and the implications thereof and contributes to the construction of a taxonomy of definitions of cyber war and cyber warfare. Considered holistically, these research outputs allow for significant resolution of the inconsistency between definitions. Moreover, these outputs provide a basis for the emergence of dominant functional definitions that may aid in the development of policy, strategy, and doctrine

An agent-driven semantical identifier using radial basis neural networks and reinforcement learning

Due to the huge availability of documents in digital form, and the deception possibility raise bound to the essence of digital documents and the way they are spread, the authorship attribution problem has constantly increased its relevance. Nowadays, authorship attribution,for both information retrieval and analysis, has gained great importance in the context of security, trust and copyright preservation. This work proposes an innovative multi-agent driven machine learning technique that has been developed for authorship attribution. By means of a preprocessing for word-grouping and time-period related analysis of the common lexicon, we determine a bias reference level for the recurrence frequency of the words within analysed texts, and then train a Radial Basis Neural Networks (RBPNN)-based classifier to identify the correct author. The main advantage of the proposed approach lies in the generality of the semantic analysis, which can be applied to different contexts and lexical domains, without requiring any modification. Moreover, the proposed system is able to incorporate an external input, meant to tune the classifier, and then self-adjust by means of continuous learning reinforcement.Comment: Published on: Proceedings of the XV Workshop "Dagli Oggetti agli Agenti" (WOA 2014), Catania, Italy, Sepember. 25-26, 201