Monitoring di un portale web: modello e implementazione

Ogni giorno enormi quantità di dati sono prodotti come record dettagliati del comportamento di utilizzo del Web, ma l'obiettivo di trarne conoscenza rimane ancora una sfida. In questa trattazione viene descritto EOP(Eye-On-Portal), un framework di monitoring che si propone come strumento per riuscire a catturare informazioni dettagliate sulle componenti della pagina visitata dall'utente e sulle interazioni di quest'ultimo con il portale: i dati raccolti potrebbero avere utilità nell'ottimizzazione del layout e nell'usabilità del portale.

Experiences in Monitoring and Assessment of Sustainable Land Management

Although sustainable land management (SLM) is widely promoted to prevent and mitigate land degradation and desertification, its monitoring and assessment (M&A) has received much less attention. This paper compiles methodological approaches which to date have been little reported in the literature. It draws lessons from these experiences and identifies common elements and future pathways as a basis for a global approach. The paper starts with local level methods where the World Overview of Conservation Approaches and Technologies (WOCAT) framework catalogues SLM case studies. This tool has been included in the local level assessment of Land Degradation Assessment in Drylands (LADA) and in the EU-DESIRE project. Complementary site-based approaches can enhance an ecological process-based understanding of SLM variation. At national and sub-national levels, a joint WOCAT/LADA/DESIRE spatial assessment based on land use systems identifies the status and trends of degradation and SLM, including causes, drivers and impacts on ecosystem services. Expert consultation is combined with scientific evidence and enhanced where necessary with secondary data and indicator databases. At the global level, the Global Environment Facility (GEF) knowledge from the land (KM:Land) initiative uses indicators to demonstrate impacts of SLM investments. Key lessons learnt include the need for a multi-scale approach, making use of common indicators and a variety of information sources, including scientific data and local knowledge through participatory methods. Methodological consistencies allow cross-scale analyses, and findings are analysed and documented for use by decision-makers at various levels. Effective M&A of SLM [e.g. for United Nations Convention to Combat Desertification (UNCCD)] requires a comprehensive methodological framework agreed by the major players.

Deforestation and forest degradation monitoring and assessment of biomass and carbon stock of lowland rainforest in the Analanjirofo region, Madagascar

Madagascar is currently developing a policy and strategies to enhance the sustainable management of its natural resources, encouraged by United Nations Framework Convention on Climate Change (UNFCCC) and REDD. To set up a sustainable financing scheme methodologies have to be provided that estimate, prevent and mitigate leakage, develop national and regional baselines, and estimate carbon benefits. With this research study this challenge was tried to be addressed by analysing a lowland rainforest in the Analanjirofo region in the district of Soanierana Ivongo, North East of Madagascar. For two distinguished forest degradation stages: “low degraded forest” and “degraded forest” aboveground biomass and carbon stock was assessed. The corresponding rates of carbon within those two classes were calculated and linked to a multi-temporal set of SPOT satellite data acquired in 1991, 2004 and 2009. Deforestation and particularly degradation and the related carbon stock developments were analysed. With the assessed data for the 3 years 1991, 2004 and 2009 it was possible to model a baseline and to develop a forest prediction for 2020 for Analanjirofo region in the district of Soanierana Ivongo. These results, developed applying robust methods, may provide important spatial information regarding the priorities in planning and implementation of future REDD+ activities in the area.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

Monitoring Programmes, Multiple Stress Analysis and Decision Support for River Basin Management

The identification of plausible causes for water body status deterioration will be much easier if it can build on available, reliable, extensive and comprehensive biogeochemical monitoring data (preferably aggregated in a database). A plausible identification of such causes is a prerequisite for well-informed decisions on which mitigation or remediation measures to take. In this chapter, first a rationale for an extended monitoring programme is provided; it is then compared to the one required by the Water Framework Directive (WFD). This proposal includes a list of relevant parameters that are needed for an integrated, a priori status assessment. Secondly, a few sophisticated statistical tools are described that subsequently allow for the estiation of the magnitude of impairment as well as the likely relative importance of different stressors in a multiple stressed environment. The advantages and restrictions of these rather complicated analytical methods are discussed. Finally, the use of Decision Support Systems (DSS) is advocated with regard to the specific WFD implementation requirements.

Web 3.0 Monitoring im Stakeholder Management

Dieser Beitrag zeigt auf, welche Möglichkeiten der Einsatz von Web 3.0 Monitoringtechniken im Stakeholder Management bietet. Das Ziel dieses Managements ist es, unternehmerischenVorhaben zu Akzeptanz und Durchsetzungskraft zu verhelfen, indem Ansprüche an Unternehmensentscheide aktiv in den Managementprozess mit eingebunden werden.Stakeholdermaps stellen diese Ansprüche visuell dar. Sie greifen einerseits auf nicht-öffentliche Inhalte zurück und andererseits auf Inhalte, die öffentlich (zumeist im Web) verfügbar sind. Das Semantische Web bietet Möglichkeiten, diese öffentlichen Inhalte nicht nur deskriptiv (was wird argumentiert?) darzustellen, sondern auch Zusammenhänge(z.B. Netzwerke, Kontextualisierungen, Referenzierungen, Gewichtungen) aufzuzeigen. Das vorgestellte Framework kann Grundlage für die öffentlichen Inhalte von Stakeholdermaps sein.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. The author focuses on the Social Web and possibilities of its integration with the Semantic Web as resource for a semi-automated tracking of online reputations using imprecise natural language terms. The inherent structure of natural language supports humans not only in communication but also in the perception of the world. Thereby fuzziness is a promising tool for transforming those human perceptions into computer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management. For readers interested in the cross-over field of computer science, information systems, and social sciences, this book is an ideal source for becoming acquainted with the evolving field of fuzzy online reputation management in the Social Semantic Web area. ​

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

An indicator framework for assessing livelihood resilience in the context of social–ecological dynamics

Livelihood resilience draws attention to the factors and processes that keep livelihoods functioning despite change and thus enriches the livelihood approach which puts people, their differential capabilities to cope with shocks and how to reduce poverty and improve adaptive capacity at the centre of analysis. However, the few studies addressing resilience from a livelihood perspective take different approaches and focus only on some dimensions of livelihoods. This paper presents a framework that can be used for a comprehensive empirical analysis of livelihood resilience. We use a concept of resilience that considers agency as well as structure. A review of both theoretical and empirical literature related to livelihoods and resilience served as the basis to integrate the perspectives. The paper identifies the attributes and indicators of the three dimensions of resilience, namely, buffer capacity, self-organisation and capacity for learning. The framework has not yet been systematically tested; however, potentials and limitations of the components of the framework are explored and discussed by drawing on empirical examples from literature on farming systems. Besides providing a basis for applying the resilience concept in livelihood-oriented research, the framework offers a way to communicate with practitioners on identifying and improving the factors that build resilience. It can thus serve as a tool for monitoring the effectiveness of policies and practices aimed at building livelihood resilience.

Management of Joint Research Activities within ERA-ARD: Guidelines for ARD programme planning, monitoring, evaluation and impact assessment

The present document has been elaborated in the context of the ERA-ARD project “The Agricultural Research for Development (ARD) dimension of the European Research Area (ERA) “. It is based on work done within Task 3.2 to identify a set of common or compatible methodologies for ARD planning, monitoring and evaluation and impact assessment. This set should serve as a guide for the management of joint ARD activities that are presently developed within the framework of the ERA-ARD project.