Educational Technology and Related Education Conferences for June to December 2015

The 33rd edition of the conference list covers selected events that primarily focus on the use of technology in educational settings and on teaching, learning, and educational administration. Only listings until December 2015 are complete as dates, locations, or Internet addresses (URLs) were not available for a number of events held from January 2016 onward. In order to protect the privacy of individuals, only URLs are used in the listing as this enables readers of the list to obtain event information without submitting their e-mail addresses to anyone. A significant challenge during the assembly of this list is incomplete or conflicting information on websites and the lack of a link between conference websites from one year to the next

DAG-Based Attack and Defense Modeling: Don't Miss the Forest for the Attack Trees

This paper presents the current state of the art on attack and defense modeling approaches that are based on directed acyclic graphs (DAGs). DAGs allow for a hierarchical decomposition of complex scenarios into simple, easily understandable and quantifiable actions. Methods based on threat trees and Bayesian networks are two well-known approaches to security modeling. However there exist more than 30 DAG-based methodologies, each having different features and goals. The objective of this survey is to present a complete overview of graphical attack and defense modeling techniques based on DAGs. This consists of summarizing the existing methodologies, comparing their features and proposing a taxonomy of the described formalisms. This article also supports the selection of an adequate modeling technique depending on user requirements

Reducing complexity in developing wireless sensor network systems using model-driven development

Wireless Sensor Network (WSN) is a collection of small and low-powered gadgets called sensor nodes (motes), which are capable of sensing the environment, collecting and processing the sensed data, and communicating with each other to accomplish a specific task. Moreover, all sensed and processed data are finally handed over to a central gathering point called a base station (sink), where all collected data are stored and can be reviewed by the user. Most of the current methods concerning WSN development are application or platform-dependent; hence it is not a trivial task to reuse developed applications in another environment. Therefore, WSN application development is a challenging and complex task because of the low-level technical details and programming complexity. Furthermore, most WSN development projects are managed by software engineers, not application field experts or WSN end users. Consequently, WSN solutions are considered expensive, due to the amount of effort that has to be put into these projects. This research project aims to reduce the complexity in developing WSN applications, by abstracting the low-level technical and programming details for average developers and domain experts. In this research, we argue that reducing complexity can be achieved by defining a new Domain-Specific Language (DSL) as a new application development and programming abstraction, which supports multi-levels modelling (i.e. network, group, and node-level). The outcome of this work is the definition of a new language called SenNet, which is an open source DSL programming abstraction that enables application developers to concentrate on the high-level application logic rather than the low-level complex details. SenNet was developed using the principles of Model-Driven Development (MDD) and macro-programming. Developers can use SenNet as a high-level programming abstraction to auto-generate a ready-to-deploy single node nesC code for all sensor nodes that comprise the SenNet application. SenNet gives developers the flexibility they need by offering them a broad range of predefined monitoring tasks and activities, enabling developers to develop different application types such as Sense-Forward (SF), and Event-Triggered (ET); besides providing a set of node-level and in-network data processing tasks. The current SenNet version is configured to generate nesC code, yet SenNet can be set up to produce and generate any programming language such as Java, or C++, by reconfiguring the code generator to produce the new language format, without changing the language design and produced semantics. Various tests and user study have been used to evaluate SenNet’s usability and functional suitability. Evaluation results found that SenNet could save 88.45% of the LOC required to be programmed by a developer, and 87.14% of the required vocabularies. Furthermore, results showed that SenNet could save 92.86% and 96.47% of the program length and volume respectively. Most of the user study participants (96%) found SenNet to be usable and helps to achieve the required WSN application with reduced development effort. Moreover, 82% of the participants believe that SenNet is functionally suitable for WSN application development. Two real-world business case studies developed were used to assess SenNet’s appropriateness to develop WSN real applications, and how it can be used to develop applications related to data processing tasks. Based on the final evaluation results, it can be concluded that our research has been successful in introducing SenNet as a new abstraction to reduce complexity in the WSN application development process

Advances and Applications of Dezert-Smarandache Theory (DSmT) for Information Fusion (Collected Works), Vol. 4

The fourth volume on Advances and Applications of Dezert-Smarandache Theory (DSmT) for information fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics. The contributions (see List of Articles published in this book, at the end of the volume) have been published or presented after disseminating the third volume (2009, http://fs.unm.edu/DSmT-book3.pdf) in international conferences, seminars, workshops and journals. First Part of this book presents the theoretical advancement of DSmT, dealing with Belief functions, conditioning and deconditioning, Analytic Hierarchy Process, Decision Making, Multi-Criteria, evidence theory, combination rule, evidence distance, conflicting belief, sources of evidences with different importance and reliabilities, importance of sources, pignistic probability transformation, Qualitative reasoning under uncertainty, Imprecise belief structures, 2-Tuple linguistic label, Electre Tri Method, hierarchical proportional redistribution, basic belief assignment, subjective probability measure, Smarandache codification, neutrosophic logic, Evidence theory, outranking methods, Dempster-Shafer Theory, Bayes fusion rule, frequentist probability, mean square error, controlling factor, optimal assignment solution, data association, Transferable Belief Model, and others. More applications of DSmT have emerged in the past years since the apparition of the third book of DSmT 2009. Subsequently, the second part of this volume is about applications of DSmT in correlation with Electronic Support Measures, belief function, sensor networks, Ground Moving Target and Multiple target tracking, Vehicle-Born Improvised Explosive Device, Belief Interacting Multiple Model filter, seismic and acoustic sensor, Support Vector Machines, Alarm classification, ability of human visual system, Uncertainty Representation and Reasoning Evaluation Framework, Threat Assessment, Handwritten Signature Verification, Automatic Aircraft Recognition, Dynamic Data-Driven Application System, adjustment of secure communication trust analysis, and so on. Finally, the third part presents a List of References related with DSmT published or presented along the years since its inception in 2004, chronologically ordered