Detecting false testimonies in reputation systems using self-organizing maps

It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.

Languages for safety-certification related propertis

The Safety Certification of Software-Intensive Systems with Reusable Components project, in short SafeCer (www.safecer.eu),is targeting increased efficiency and reduced time-to-market by composable safety certification of safety- relevant embedded systems. The industrial domains targeted are within automotive and construction equipment, avionics, and rail. Some of the companies involved are: Volvo Tech- nology, Thales, TTTech, and Intecs among others. SafeCer includes more than 30 partners in six different countries and has a budget of e25.7 millions. A primary objective is to provide support for system safety arguments based on arguments and properties of system components as well as to provide support for generation of corresponding evidence in a similar compositional way. By providing support for efficient reuse of certification and stronger links between certification and development, compo- nent reuse will be facilitated, and by providing support for reuse across domains the amount of components available for reuse will increase dramatically. The resulting efficiency and reduced time to market will, together with increased quality and reduced risk, increase competitiveness and pave the way for a cross-domain market for software components qualified for certification.

Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining

La gran cantidad de datos que se registran diariamente en los sistemas de base de datos de las organizaciones ha generado la necesidad de analizarla. Sin embargo, se enfrentan a la complejidad de procesar enormes volúmenes de datos a través de métodos tradicionales de análisis. Además, dentro de un contexto globalizado y competitivo las organizaciones se mantienen en la búsqueda constante de mejorar sus procesos, para lo cual requieren herramientas que les permitan tomar mejores decisiones. Esto implica estar mejor informado y conocer su historia digital para describir sus procesos y poder anticipar (predecir) eventos no previstos. Estos nuevos requerimientos de análisis de datos ha motivado el desarrollo creciente de proyectos de minería de datos. El proceso de minería de datos busca obtener desde un conjunto masivo de datos, modelos que permitan describir los datos o predecir nuevas instancias en el conjunto. Implica etapas de: preparación de los datos, procesamiento parcial o totalmente automatizado para identificar modelos en los datos, para luego obtener como salida patrones, relaciones o reglas. Esta salida debe significar un nuevo conocimiento para la organización, útil y comprensible para los usuarios finales, y que pueda ser integrado a los procesos para apoyar la toma de decisiones. Sin embargo, la mayor dificultad es justamente lograr que el analista de datos, que interviene en todo este proceso, pueda identificar modelos lo cual es una tarea compleja y muchas veces requiere de la experiencia, no sólo del analista de datos, sino que también del experto en el dominio del problema. Una forma de apoyar el análisis de datos, modelos y patrones es a través de su representación visual, utilizando las capacidades de percepción visual del ser humano, la cual puede detectar patrones con mayor facilidad. Bajo este enfoque, la visualización ha sido utilizada en minería datos, mayormente en el análisis descriptivo de los datos (entrada) y en la presentación de los patrones (salida), dejando limitado este paradigma para el análisis de modelos. El presente documento describe el desarrollo de la Tesis Doctoral denominada “Nuevos Esquemas de Visualizaciones para Mejorar la Comprensibilidad de Modelos de Data Mining”. Esta investigación busca aportar con un enfoque de visualización para apoyar la comprensión de modelos minería de datos, para esto propone la metáfora de modelos visualmente aumentados. ABSTRACT The large amount of data to be recorded daily in the systems database of organizations has generated the need to analyze it. However, faced with the complexity of processing huge volumes of data over traditional methods of analysis. Moreover, in a globalized and competitive environment organizations are kept constantly looking to improve their processes, which require tools that allow them to make better decisions. This involves being bettered informed and knows your digital story to describe its processes and to anticipate (predict) unanticipated events. These new requirements of data analysis, has led to the increasing development of data-mining projects. The data-mining process seeks to obtain from a massive data set, models to describe the data or predict new instances in the set. It involves steps of data preparation, partially or fully automated processing to identify patterns in the data, and then get output patterns, relationships or rules. This output must mean new knowledge for the organization, useful and understandable for end users, and can be integrated into the process to support decision-making. However, the biggest challenge is just getting the data analyst involved in this process, which can identify models is complex and often requires experience not only of the data analyst, but also the expert in the problem domain. One way to support the analysis of the data, models and patterns, is through its visual representation, i.e., using the capabilities of human visual perception, which can detect patterns easily in any context. Under this approach, the visualization has been used in data mining, mostly in exploratory data analysis (input) and the presentation of the patterns (output), leaving limited this paradigm for analyzing models. This document describes the development of the doctoral thesis entitled "New Visualizations Schemes to Improve Understandability of Data-Mining Models". This research aims to provide a visualization approach to support understanding of data mining models for this proposed metaphor visually enhanced models.

Tratamiento inteligente de la información para ayuda a la toma de decisiones

Proyecto emergente centrado en el tratamiento inteligente de información procedente de diversas fuentes tales como micro-blogs, blogs, foros, portales especializados, etc. La finalidad es generar conocimiento a partir de la información semántica recuperada. Como resultado se podrán determinar las necesidades de los usuarios o mejorar la reputación de diferentes organizaciones. En este artículo se describen los problemas abordados, la hipótesis de trabajo, las tareas a realizar y los objetivos parciales alcanzados.

The design and implementation of a repository for the management of spatial data integrity constraints

This paper reviews the key features of an environment to support domain users in spatial information system (SIS) development. It presents a full design and prototype implementation of a repository system for the storage and management of metadata, focusing on a subset of spatial data integrity constraint classes. The system is designed to support spatial system development and customization by users within the domain that the system will operate.

Personalising context-aware applications

The immaturity of the field of context-aware computing means that little is known about how to incorporate appropriate personalisation mechanisms into context-aware applications. One of the main challenges is how to elicit and represent complex, context-dependent requirements, and then use the resulting representations within context-aware applications to support decision-making processes. In this paper, we characterise several approaches to personalisation of context-aware applications and introduce our research on personalisation using a novel preference model.

A roadmap for cost engineering in the automotive supplier sector

The advent of global competition has introduced the need for new competitive manufacturing strategies. The implementation of new strategies has a dramatic effect on measuring product cost compared to traditional management accounting methods. It is found that new cost management methods are required to measure success and support decision-making within the new strategies. One example is the consequences of using traditional management accounting methods for measuring the effects of lean having catastrophic results during reporting. Such results steer managers away from lean manufacture based upon a false picture of the potential benefits. This research examines cost management methods potentially applicable within the automotive supplier sector. Because of the lack of cost-related data collected within the supplier sector companies, this paper ends with a demonstration of a novel method for use in data scarce environments. Copyright © 2008 Inderscience Enterprises Ltd.

Risk based post closure care analysis for Florida landfills

Subtitle D of the Resource Conservation and Recovery Act (RCRA) requires a post closure period of 30 years for non hazardous wastes in landfills. Post closure care (PCC) activities under Subtitle D include leachate collection and treatment, groundwater monitoring, inspection and maintenance of the final cover, and monitoring to ensure that landfill gas does not migrate off site or into on site buildings. The decision to reduce PCC duration requires exploration of a performance based methodology to Florida landfills. PCC should be based on whether the landfill is a threat to human health or the environment. Historically no risk based procedure has been available to establish an early end to PCC. Landfill stability depends on a number of factors that include variables that relate to operations both before and after the closure of a landfill cell. Therefore, PCC decisions should be based on location specific factors, operational factors, design factors, post closure performance, end use, and risk analysis. The question of appropriate PCC period for Florida’s landfills requires in depth case studies focusing on the analysis of the performance data from closed landfills in Florida. Based on data availability, Davie Landfill was identified as case study site for a case by case analysis of landfill stability. The performance based PCC decision system developed by Geosyntec Consultants was used for the assessment of site conditions to project PCC needs. The available data for leachate and gas quantity and quality, ground water quality, and cap conditions were evaluated. The quality and quantity data for leachate and gas were analyzed to project the levels of pollutants in leachate and groundwater in reference to maximum contaminant level (MCL). In addition, the projected amount of gas quantity was estimated. A set of contaminants (including metals and organics) were identified as contaminants detected in groundwater for health risk assessment. These contaminants were selected based on their detection frequency and levels in leachate and ground water; and their historical and projected trends. During the evaluations a range of discrepancies and problems that related to the collection and documentation were encountered and possible solutions made. Based on the results of PCC performance integrated with risk assessment, projection of future PCC monitoring needs and sustainable waste management options were identified. According to these results, landfill gas monitoring can be terminated, leachate and groundwater monitoring for parameters above MCL and surveying of the cap integrity should be continued. The parameters which cause longer monitoring periods can be eliminated for the future sustainable landfills. As a conclusion, 30 year PCC period can be reduced for some of the landfill components based on their potential impacts to human health and environment (HH&E).

Risk Based Post Closure Care Analysis for Florida Landfills

Subtitle D of the Resource Conservation and Recovery Act (RCRA) requires a post closure period of 30 years for non hazardous wastes in landfills. Post closure care (PCC) activities under Subtitle D include leachate collection and treatment, groundwater monitoring, inspection and maintenance of the final cover, and monitoring to ensure that landfill gas does not migrate off site or into on site buildings. The decision to reduce PCC duration requires exploration of a performance based methodology to Florida landfills. PCC should be based on whether the landfill is a threat to human health or the environment. Historically no risk based procedure has been available to establish an early end to PCC. Landfill stability depends on a number of factors that include variables that relate to operations both before and after the closure of a landfill cell. Therefore, PCC decisions should be based on location specific factors, operational factors, design factors, post closure performance, end use, and risk analysis. The question of appropriate PCC period for Florida’s landfills requires in depth case studies focusing on the analysis of the performance data from closed landfills in Florida. Based on data availability, Davie Landfill was identified as case study site for a case by case analysis of landfill stability. The performance based PCC decision system developed by Geosyntec Consultants was used for the assessment of site conditions to project PCC needs. The available data for leachate and gas quantity and quality, ground water quality, and cap conditions were evaluated. The quality and quantity data for leachate and gas were analyzed to project the levels of pollutants in leachate and groundwater in reference to maximum contaminant level (MCL). In addition, the projected amount of gas quantity was estimated. A set of contaminants (including metals and organics) were identified as contaminants detected in groundwater for health risk assessment. These contaminants were selected based on their detection frequency and levels in leachate and ground water; and their historical and projected trends. During the evaluations a range of discrepancies and problems that related to the collection and documentation were encountered and possible solutions made. Based on the results of PCC performance integrated with risk assessment, projection of future PCC monitoring needs and sustainable waste management options were identified. According to these results, landfill gas monitoring can be terminated, leachate and groundwater monitoring for parameters above MCL and surveying of the cap integrity should be continued. The parameters which cause longer monitoring periods can be eliminated for the future sustainable landfills. As a conclusion, 30 year PCC period can be reduced for some of the landfill components based on their potential impacts to human health and environment (HH&E).

Transição demográfica e a questão educacional: uma abordagem para o ensino médio do Rio Grande do Norte

Due to demographic transition process, the educational public sector politics formers encounter a highly specific demographic situation because, nowadays, despite the demographic transition, population is still growing because of the demographic inertia; however, due to steady decline in fertility, young population tends to decrease in next years. In this way, aiming to make high school widely accessible in the country, the issue of education quality is highlighted as well the importance of the physical structure of schools and their teaching equipments to confirm a favorable or not environment for developing educational processes. In this way, this work aims to relate the enrollment of students as school types with the demand of young people who will be able to attend high school on the Rio Grande do Norte state by the year of 2020, emphasizing teaching unities structural aspects, from a school profiling to the design of three prospective alternatives. So, from INEP's Scholar Census data and IBGE population's projections, this work is composed by four stages: i) literature review about research related subjects; ii) database design and build; iii) school profiling; and, iv) prospective alternatives creation. As results, three alternatives relate potential demand and enrollment using the built profiles and they are: i) “Alternative A” attends PEE's requirements related to demands but do not provide improvements in the school structural aspects; ii) “Alternative B” points into an increase of enrollment offering to the detriment of school's structural conditions which are offered to these students; iii) “Alternative C” propitiates a quantitative enrollment increasing combined with improvements on school's physical structure. These alternatives help to support decision making related to goals and realization of universal access with physical conditions which are necessary to a favorable environment to educational activity development.

Adapting prospective structural analysis to strengthen sustainable management and capacity building in community-based natural resource management contexts

Local communities collectively managing common pool resources can play an important role in sustainable management, but they often lack the skills and context-specific tools required for such management. The complex dynamics of social-ecological systems (SES), the need for management capacities, and communities’ limited empowerment and participation skills present challenges for community-based natural resource management (CBNRM) strategies. We analyzed the applicability of prospective structural analysis (PSA), a strategic foresight tool, to support decision making and to foster sustainable management and capacity building in CBNRM contexts and the modifications necessary to use the tool in such contexts. By testing PSA in three SES in Colombia, Mexico, and Argentina, we gathered information regarding the potential of this tool and its adaptation requirements. The results suggest that the tool can be adapted to these contexts and contribute to fostering sustainable management and capacity building. It helped identify the systems’ dynamics, thus increasing the communities’ knowledge about their SES and informing the decision-making process. Additionally, it drove a learning process that both fostered empowerment and built participation skills. The process demanded both time and effort, and required external monitoring and facilitation, but community members could be trained to master it. Thus, we suggest that the PSA technique has the potential to strengthen CBNRM and that other initiatives could use it, but they must be aware of these requirements.

Indicadores energéticos: instrumentos de apoio ao desenvolvimento sustentável

Energy indicators are tools to support decision-making on energy. The growing debate on sustainable development, contributed to the energy indicators began to incorporate, besides the traditional economic, social and environmental information. Therefore, taking sustainable development into account, it is important to know contributions and limitations of these tools. The overall goal of this study is to analyze the contributions and limitations of the energy indicators as assets to support sustainable development.This study can be classified as descriptive because it relies on bibliographical and documental material. As a result of documental analysis, 55 energy indicators for sustainable development (EISD) were selected. The selection took place by identification of those indicators through the institutions International Atomic Energy Agency (IAEA), Helio International and World Energy Council (WEC), among 19 institutions involved in research on energy identified in the survey. The study stresses that most of the selected indicators focuses on the economic dimension, 19 EISDs (34.54%), followed by 10 EISDs (18.18%) focused on the environmental dimension, 9 EISDs (16.36%) focused on the social issues, 7 EISDs (12.45%) are classified as resilience, 4 EISDs (7.27%) is about governance, 3 EISDs (5.45%) focused on vulnerability and 3 EISDs (5.45%) is about policy. Despite the inclusion of indicators associated with other dimensions than economy, information provided by those indicators emerges as their own limitation. Because, recently, indicators’ information were used to promote sustainable development as well as the opposite. Additionally, the study identified EISDs whose components were not specified. They may enable generation of information far from the real scenario, if components dissociated EISD would be taking into consideration or even the non-consideration of relevant components. Despite limitations, EISDs assisting decision-makers contributes to the pursuit of sustainable development. But they may be improved through information about environmental issues, such as emission of atmospheric pollutants, soil and water, resulting from energy sources, helps identifying which sources are more or less harmful for sustainable development. However, difficulty in collecting data, identifying the components for calculation of each indicator and even interpretation of this, as analyzed, may not only fail to contribute to sustainable development, as can delay taking corrective or preventive decisions.

Os hábitos de leitura dos estudantes do ensino básico da Região Autónoma dos Açores

Tese de Doutoramento, Educação (Metodologia do Ensino da Língua Portuguesa), 15 de Julho 2013, Universidade dos Açores.

Desenvolvimento de sistema automatizado para o monitoramento da degradação de resíduos de brometo de etídio

Tese (doutorado)—Universidade de Brasília, Instituto de Química, Programa de Pós-Graduação em Química, 2015.

Kwantyfikacja wybranych świadczeń ekosystemów na poziomie lokalnym. Przykład gminy Krajenka

Wydział Nauk Geograficznych i Geologicznych