Immersive Learning Research Network

Computer games have now been around for over three decades and the term serious games has been attributed to the use of computer games that are thought to have educational value. Game-based learning (GBL) has been applied in a number of different fields such as medicine, languages and software engineering. Furthermore, serious games can be a very effective as an instructional tool and can assist learning by providing an alternative way of presenting instructions and content on a supplementary level, and can promote student motivation and interest in subject matter resulting in enhanced learning effectiveness. REVLAW (Real and Virtual Reality Law) is a research project that the departments of Law and Computer Science of Westminster University have proposed as a new framework in which law students can explore a real case scenario using Virtual Reality (VR) technology to discover important pieces of evidence from a real-given scenario and make up their mind over the crime case if this is a murder or not. REVLAW integrates the immersion into VR as the perception of being physically present in a non-physical world. The paper presents the prototype framework and the mechanics used to make students focus on the crime case and make the best use of this immersive learning approach.

Distributed parallelization of greedy Mobile Network Optimization algorithms

The Mobile Network Optimization (MNO) technologies have advanced at a tremendous pace in recent years. And the Dynamic Network Optimization (DNO) concept emerged years ago, aimed to continuously optimize the network in response to variations in network traffic and conditions. Yet, DNO development is still at its infancy, mainly hindered by a significant bottleneck of the lengthy optimization runtime. This paper identifies parallelism in greedy MNO algorithms and presents an advanced distributed parallel solution. The solution is designed, implemented and applied to real-life projects whose results yield a significant, highly scalable and nearly linear speedup up to 6.9 and 14.5 on distributed 8-core and 16-core systems respectively. Meanwhile, optimization outputs exhibit self-consistency and high precision compared to their sequential counterpart. This is a milestone in realizing the DNO. Further, the techniques may be applied to similar greedy optimization algorithm based applications.

La ética hacker frente al capitalismo netárquíco: software libre y peer production en las iniciativas de Economía Colaborativa en Andalucía

En los últimos años el término Economía Colaborativa se ha popularizado sin que, hasta el momento, haya sido definido de manera inequívoca. Bajo esta denominación se engloban experiencias tan diversas como bancos de tiempo, huertos urbanos, startups o grandes plataformas digitales. La proliferación de este tipo de iniciativas puede relacionarse con una multiplicidad de factores tales como el desarrollo tecnológico, la recesión económica y otras crisis superpuestas (medioambiental, de cuidados, de valores, de lo político) y un cierto cambio en los valores sociales. Entre 2014-2015 se han realizado dos investigaciones en Andalucía de manera casi paralela y con una metodología similar. La primera de ellas pretendía identificar prácticas de Economía Colaborativa en el entorno universitario. La segunda investigación identificaba experiencias de emprendimiento a nivel autonómico. A luz de los resultados obtenidos se plantea la siguiente cuestión sobre la naturaleza misma de la Economía Colaborativa: ¿nos encontramos ante prácticas postcapitalistas que abren el camino a una sociedad más justa e igualitaria o, más bien, estamos ante una respuesta del capital para, una vez más, seguir extrayendo de manera privada el valor que se genera socialmente? Este artículo, partiendo del análisis del conjunto de iniciativas detentadas en Andalucía, se centra en aquellas basadas en el software libre y la producción digital concluyendo cómo, gracias a la incorporación de ciertos aspectos de la ética hacker y las lógicas del conocimiento abierto, éstas pueden situarse dentro de un escenario de fomento de los comunes globales frente a las lógicas imperantes del capitalismo netárquico. 

D6.1 – Ecosystem Software Platform with Underlying Software Repository, Digital Library and Media Archive

The objective of D6.1 is to make the Ecosystem software platform with underlying Software Repository, Digital Library and Media Archive available to the degree, that the RAGE project can start collecting content in the form of software assets, and documents of various media types. This paper describes the current state of the Ecosystem as of month 12 of the project, and documents the structure of the Ecosystem, individual components, integration strategies, and overall approach. The deliverable itself is the deployment of the described components, which is now available to collect and curate content. Whilst this version is not yet feature complete, full realization is expected within the next few months. Following this development, WP6 will continue to add features driven by the business models to be defined by WP7 later on in the project.

A secure authentication and key management scheme for Wireless Sensors Network

In recent years, the adaptation of Wireless Sensor Networks (WSNs) to application areas requiring mobility increased the security threats against confidentiality, integrity and privacy of the information as well as against their connectivity. Since, key management plays an important role in securing both information and connectivity, a proper authentication and key management scheme is required in mobility enabled applications where the authentication of a node with the network is a critical issue. In this paper, we present an authentication and key management scheme supporting node mobility in a heterogeneous WSN that consists of several low capabilities sensor nodes and few high capabilities sensor nodes. We analyze our proposed solution by using MATLAB (analytically) and by simulation (OMNET++ simulator) to show that it has less memory requirement and has good network connectivity and resilience against attacks compared to some existing schemes. We also propose two levels of secure authentication methods for the mobile sensor nodes for secure authentication and key establishment.

Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Model-driven development of sensor network applications with optimization of non-functional constraints

Wireless sensor networks (WSNs) differ from conventional distributed systems in many aspects. The resource limitation of sensor nodes, the ad-hoc communication and topology of the network, coupled with an unpredictable deployment environment are difficult non-functional constraints that must be carefully taken into account when developing software systems for a WSN. Thus, more research needs to be done on designing, implementing and maintaining software for WSNs. This thesis aims to contribute to research being done in this area by presenting an approach to WSN application development that will improve the reusability, flexibility, and maintainability of the software. Firstly, we present a programming model and software architecture aimed at describing WSN applications, independently of the underlying operating system and hardware. The proposed architecture is described and realized using the Model-Driven Architecture (MDA) standard in order to achieve satisfactory levels of encapsulation and abstraction when programming sensor nodes. Besides, we study different non-functional constrains of WSN application and propose two approaches to optimize the application to satisfy these constrains. A real prototype framework was built to demonstrate the developed solutions in the thesis. The framework implemented the programming model and the multi-layered software architecture as components. A graphical interface, code generation components and supporting tools were also included to help developers design, implement, optimize, and test the WSN software. Finally, we evaluate and critically assess the proposed concepts. Two case studies are provided to support the evaluation. The first case study, a framework evaluation, is designed to assess the ease at which novice and intermediate users can develop correct and power efficient WSN applications, the portability level achieved by developing applications at a high-level of abstraction, and the estimated overhead due to usage of the framework in terms of the footprint and executable code size of the application. In the second case study, we discuss the design, implementation and optimization of a real-world application named TempSense, where a sensor network is used to monitor the temperature within an area.

Letting the managers manage: analyzing capacity to conserve biodiversity in a cross-border protected area network

Biodiversity loss is one of the most significant drivers of ecosystem change and is projected to continue at a rapid rate. While protected areas, such as national parks, are seen as important refuges for biodiversity, their effectiveness in stemming biodiversity decline has been questioned. Public agencies have a critical role in the governance of many such areas, but there are tensions between the need for these agencies to be more “adaptive” and their current operating environment. Our aim is to analyze how institutions enable or constrain capacity to conserve biodiversity in a globally significant cross-border network of protected areas, the Australian Alps. Using a novel conceptual framework for diagnosing biodiversity institutions, our research examined institutional adaptive capacity and more general capacity for conserving biodiversity. Several intertwined issues limit public agencies’ capacity to fulfill their conservation responsibilities. Narrowly defined accountability measures constrain adaptive capacity and divert attention away from addressing key biodiversity outcomes. Implications for learning were also evident, with protected area agencies demonstrating successful learning for on-ground issues but less success in applying this learning to deeper policy change. Poor capacity to buffer political and community influences in managing significant cross-border drivers of biodiversity decline signals poor fit with the institutional context and has implications for functional fit. While cooperative federalism provides potential benefits for buffering through diversity, it also means protected area agencies have restricted authority to address cross-border threats. Restrictions on staff authority and discretion, as public servants, have further implications for deploying capacity. This analysis, particularly the possibility of fostering “ambidexterity”—creatively responding to political pressures in a way that also achieves a desirable outcome for biodiversity conservation—is one promising way of building capacity to buffer both political influences and ecological pressures. The findings and the supporting analysis provide insight into how institutional capacity to conserve biodiversity can be enhanced in protected areas in Australia and elsewhere, especially those governed by public agencies and/or multiple organizations and across jurisdictions.

Relationship marketing in Latin American context: Implications for small Finnish software companies in Latin American B2B partnerships

After a productivity decrease of established national export industries in Finland such as mobile and paper industries, innovative, smaller companies with the intentions to internationalize right from the start have been proliferating. For software companies early internationalization is an especially good opportunity, as Internet usage becomes increasingly homogeneous across borders and software products often do not need a physical distribution channel. Globalization also makes Finnish companies turn to unfamiliar export markets like Latin America, a very untraditional market for Finns. Relationships consisting of Finnish and Latin American business partners have therefore not been widely studied, especially from a new-age software company’s perspective. To study these partnerships, relationship marketing theory was taken into the core of the study, as its practice focuses mainly on establishing and maintaining relationships with stakeholders at a profit, so that the objectives of all parties are met, which is done by a mutual exchange and fulfillment of promises. The most important dimensions of relationship marketing were identified as trust, commitment and attraction, which were then focused on, as the study aims to understand the implications Latin American business culture has for the understanding, and hence, effective application of relationship marketing in the Latin American market. The question to be answered consecutively was how should the dimensions of trust, commitment and attraction be understood in business relationships in Latin America? The study was conducted by first joining insights given by Latin American business culture literature with overall theories on the three dimensions. Through pattern matching, these insights were compared to empirical evidence collected from business professionals of the Latin American market and from the experiences of Finnish software businesses that had recently expanded into the market. What was found was that previous literature on Latin American business culture had already named many implications for the relationship marketing dimensions that were relevant also for small Finnish software firms on the market. However, key findings also presented important new drivers for the three constructs. Local presence in the area where the Latin American partner is located was found to drive or enhance trust, commitment and attraction. High-frequency follow up procedures were in turn found to drive commitment and attraction. Both local presence and follow up were defined according to the respective evidence in the study. Also, in the context of Finnish software firms in relationships with Latin American partners, the national origins or the foreignness of the Finnish party was seen to enhance trust and attraction in the relationship

Requirement Risk Level Forecast Using Bayesian Networks Classifiers

Requirement engineering is a key issue in the development of a software project. Like any other development activity it is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.

Evaluating conservation and fisheries management strategies by linking spatial prioritization software and ecosystem and fisheries modelling tools

Well-designed marine protected area (MPA) networks can deliver a range of ecological, economic and social benefits, and so a great deal of research has focused on developing spatial conservation prioritization tools to help identify important areas. However, whilst these software tools are designed to identify MPA networks that both represent biodiversity and minimize impacts on stakeholders, they do not consider complex ecological processes. Thus, it is difficult to determine the impacts that proposed MPAs could have on marine ecosystem health, fisheries and fisheries sustainability. Using the eastern English Channel as a case study, this paper explores an approach to address these issues by identifying a series of MPA networks using the Marxan and Marxan with Zones conservation planning software and linking them with a spatially explicit ecosystem model developed in Ecopath with Ecosim. We then use these to investigate potential trade-offs associated with adopting different MPA management strategies. Limited-take MPAs, which restrict the use of some fishing gears, could have positive benefits for conservation and fisheries in the eastern English Channel, even though they generally receive far less attention in research on MPA network design. Our findings, however, also clearly indicate that no-take MPAs should form an integral component of proposed MPA networks in the eastern English Channel, as they not only result in substantial increases in ecosystem biomass, fisheries catches and the biomass of commercially valuable target species, but are fundamental to maintaining the sustainability of the fisheries. Synthesis and applications. Using the existing software tools Marxan with Zones and Ecopath with Ecosim in combination provides a powerful policy-screening approach. This could help inform marine spatial planning by identifying potential conflicts and by designing new regulations that better balance conservation objectives and stakeholder interests. In addition, it highlights that appropriate combinations of no-take and limited-take marine protected areas might be the most effective when making trade-offs between long-term ecological benefits and short-term political acceptability.

Protocol to design techniques for implementing software development best practices

Software engineering best practices allow significantly improving the software development. However, the implementation of best practices requires skilled professionals, financial investment and technical support to facilitate implementation and achieve the respective improvement. In this paper we proposes a protocol to design techniques to implement best practices of software engineering. The protocol includes the identification and selection of process to improve, the study of standards and models, identification of best practices associated with the process and the possible implementation techniques. In addition, technical design activities are defined in order to create or adapt the techniques of implementing best practices for software development.

Sistema de conmutación y control de llamadas basado en OpenBTS y Asterisk

El presente trabajo empleó herramientas de hardware y software de licencia libre para el establecimiento de una estación base celular (BTS) de bajo costo y fácil implementación. Partiendo de conceptos técnicos que facilitan la instalación del sistema OpenBTS y empleando el hardware USRP N210 (Universal Software Radio Peripheral) permitieron desplegar una red análoga al estándar de telefonía móvil (GSM). Usando los teléfonos móviles como extensiones SIP (Session Initiation Protocol) desde Asterisk, logrando ejecutar llamadas entre los terminales, mensajes de texto (SMS), llamadas desde un terminal OpenBTS hacia otra operadora móvil, entre otros servicios.

Base de Datos “I&D” Primera Experiencia con el Software Microisis, Versión 3.0 Multiusuario -Versión de Prueba-

La normalización facilita la comunicación y permite el intercambio de información con cualquier institución nacional o internacional. Este objetivo es posible a través de los formatos de comunicación para intercambio de información automatizada como CEPAL, MARC., FCC.La Escuela de Bibliotecología, Documentación e Información de la Universidad Nacional utiliza el software MICROISIS en red para la enseñanza. Las bases de datos que se diseñan utilizan el formato MARC y para la descripción bibliográfica las RCAA2.Se presenta la experiencia con la base de datos “I&D” sobre desarrollo rural, presentando la Tabla de Definición de Campos, la hoja de trabajo, el formato de despliegue y Tabla de selección de Campos.

Determination of thresholds in marine molluscs as an alternative to the Environmental Quality Standards in marine water defined in the Water Framework Directive

The Water Framework Directive (WFD) establishes Environmental Quality Standards (EQS) in marine water for 34 priority substances. Among these substances, 25 are hydrophobic and bioaccumulable (2 metals and 23 organic compounds). For these 25 substances, monitoring in water matrix is not appropriate and an alternative matrix should be developed. Bivalve mollusks, particularly mussels (Mytilus edulis, Mytilus galloprovincialis), are used by Ifremer as a quantitative biological indicator since 1979 in France, to assess the marine water quality. This study has been carried out in order to determine thresholds in mussels at least as protective as EQS in marine water laid down by the WFD. Three steps are defined: - Provide an overview of knowledges about the relations between the concentrations of contaminants in the marine water and mussels through bioaccumulation factor (BAF) and bioconcentration factor (BCF). This allows to examine how a BCF or a BAF can be determined: BCF can be determined experimentally (according to US EPA or ASTM standards), or by Quantitative Activity-Structure Relationship models (QSAR): four equations can be used for mussels. BAF can be determined by field experiment; but none standards exists. It could be determined by using QSAR but this method is considered as invalid for mussels, or by using existing model: Dynamic Budget Model, but this is complex to use. - Collect concentrations data in marine water (Cwater) in bibliography for those 25 substances; and compare them with concentration in mussels (Cmussels) obtained through French monitoring network of chemicals contaminants (ROCCH) and biological integrator network RINBIO. According to available data, this leads to determine the BAF or the BCF (Cmussels /Cwater) with field data. - Compare BAF and BCF values (when available) obtained with various methods for these substances: BCF (stemming from the bibliography, using experimental process), BCF calculated by QSAR and BAF determined using field data. This study points out that experimental BCF data are available for 3 substances (Chlorpyrifos, HCH, Pentachlorobenzene). BCF by QSAR can be calculated for 20 substances. The use of field data allows to evaluate 4 BAF for organic compounds and 2 BAF for metals. Using these BAF or BCF value, thresholds in shellfish can be determined as an alternative to EQS in marine water.