Self organizing maps as a novel tool for data analysis in education

Young people currently live and are connected to the virtual world in a natural and simple way. Nevertheless, in spite of the great advantages of the use of Information and Communication Technology, and particularly social networks, there are several drawbacks, principally security and privacy of net users. However, human behaviour is strongly non-linear, so usual statistical analysis does not yield accurate results. Now, machine learning algorithms are very common in solving real life non-linear problems, such as economics, medicine and engineering. So it would be worthy to apply this methodology on education data sets. In this work, a non-linear, visual algorithm named Self Organizing Map (SOM) has been applied in order to extract some conclusions about related aspects mainly, to security and privacy perception of teenagers when using Virtual Social Networks. SOMs are a particular tool based on Artificial Neural Networks, and provide both a non linear approach and a visualization tool of data. The present work proposes a study to determine and analyze the different aspects. A methodology based on a survey consisting of 27 questions has been carried out on a 170 teenagers, aged between 12 and 16 years. SOMs have been applied on variables related to Facebook privacy and security issues. Data on every variable have been mapped into a 7x12 neurons network. The results have revealed a lack of knowledge of privacy, protection mechanisms and even their own image, that Virtual Social Network implements. A lack of awareness and sensibility about the problems that a thoughtless use of these social networks can cause has been detected. In other way, this work also has proved that SOM is a valuable, interesting tool to infer knowledge from non-linear data and a different proposal from the classical linear statistical methods

Application of Market Models to Network Equilibrium Problems

We present a general two-side market model with divisible commodities and price functions of participants. A general existence result on unbounded sets is obtained from its variational inequality re-formulation. We describe an extension of the network flow equilibrium problem with elastic demands and a new equilibrium type model for resource allocation problems in wireless communication networks, which appear to be particular cases of the general market model. This enables us to obtain new existence results for these models as some adjustments of that for the market model. Under certain additional conditions the general market model can be reduced to a decomposable optimization problem where the goal function is the sum of two functions and one of them is convex separable, whereas the feasible set is the corresponding Cartesian product. We discuss some versions of the partial linearization method, which can be applied to these network equilibrium problems.Comment: 18 pages, 3 table

Unreduced Dynamic Complexity: Towards the Unified Science of Intelligent Communication Networks and Software

Operation of autonomic communication networks with complicated user-oriented functions should be described as unreduced many-body interaction process. The latter gives rise to complex-dynamic behaviour including fractally structured hierarchy of chaotically changing realisations. We recall the main results of the universal science of complexity (http://cogprints.org/4471/) based on the unreduced interaction problem solution and its application to various real systems, from nanobiosystems (http://cogprints.org/4527/) and quantum devices to intelligent networks (http://cogprints.org/4114/) and emerging consciousness (http://cogprints.org/3857/). We concentrate then on applications to autonomic communication leading to fundamentally substantiated, exact science of intelligent communication and software. It aims at unification of the whole diversity of complex information system behaviour, similar to the conventional, "Newtonian" science order for sequential, regular models of system dynamics. Basic principles and first applications of the unified science of complex-dynamic communication networks and software are outlined to demonstrate its advantages and emerging practical perspectives

Polynomial Bell inequalities

It is a recent realization that many of the concepts and tools of causal discovery in machine learning are highly relevant to problems in quantum information, in particular quantum nonlocality. The crucial ingredient in the connection between both fields is the tool of Bayesian networks, a graphical model used to reason about probabilistic causation. Indeed, Bell's theorem concerns a particular kind of a Bayesian network and Bell inequalities are a special case of linear constraints following from such models. It is thus natural to look for generalized Bell scenarios involving more complex Bayesian networks. The problem, however, relies on the fact that such generalized scenarios are characterized by polynomial Bell inequalities and no current method is available to derive them beyond very simple cases. In this work, we make a significant step in that direction, providing a general and practical method for the derivation of polynomial Bell inequalities in a wide class of scenarios, applying it to a few cases of interest. We also show how our construction naturally gives rise to a notion of non-signalling in generalized networks.Comment: 9 pages (including appendix

Adaptive Importance Sampling for Performance Evaluation and Parameter Optimization of Communication Systems

We present new adaptive importance sampling techniques based on stochastic Newton recursions. Their applicability to the performance evaluation of communication systems is studied. Besides bit-error rate (BER) estimation, the techniques are used for system parameter optimization. Two system models that are analytically tractable are employed to demonstrate the validity of the techniques. As an application to situations that are analytically intractable and numerically intensive, the influence of crosstalk in a wavelength-division multiplexing (WDM) crossconnect is assessed. In order to consider a realistic system model, optimal setting of thresholds in the detector is carried out while estimating error rate performances. Resulting BER estimates indicate that the tolerable crosstalk levels are significantly higher than predicted in the literature. This finding has a strong impact on the design of WDM networks. Power penalties induced by the addition of channels can also be accurately predicted in short run-time

Considering Pigeons for Carrying Delay Tolerant Networking based Internet traffic in Developing Countries

There are many regions in the developing world that suffer from poor infrastructure and lack of connection to the Internet and Public Switched Telephone Networks (PSTN). Delay Tolerant Networking (DTN) is a technology that has been advocated for providing store-and-forward network connectivity in these regions over the past few years. DTN often relies on human mobility in one form or another to support transportation of DTN data. This presents a socio-technical problem related to organizing how the data should be transported. In some situations the demand for DTN traffic can exceed that which is possible to support with human mobility, so alternative mechanisms are needed. In this paper we propose using live carrier pigeons (columba livia) to transport DTN data. Carrier pigeons have been used for transporting packets of information for a long time, but have not yet been seriously considered for transporting DTN traffic. We provide arguements that this mode of DTN data transport provides promise, and should receive attention from research and development projects. We provide an overview of pigeon characteristics to analyze the feasibility of using them for data transport, and present simulations of a DTN network that utilizes pigeon transport in order to provide an initial investigation into expected performance characteristics