986 resultados para Giuseppe Vasi


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Recently major processor manufacturers have announced a dramatic shift in their paradigm to increase computing power over the coming years. Instead of focusing on faster clock speeds and more powerful single core CPUs, the trend clearly goes towards multi core systems. This will also result in a paradigm shift for the development of algorithms for computationally expensive tasks, such as data mining applications. Obviously, work on parallel algorithms is not new per se but concentrated efforts in the many application domains are still missing. Multi-core systems, but also clusters of workstations and even large-scale distributed computing infrastructures provide new opportunities and pose new challenges for the design of parallel and distributed algorithms. Since data mining and machine learning systems rely on high performance computing systems, research on the corresponding algorithms must be on the forefront of parallel algorithm research in order to keep pushing data mining and machine learning applications to be more powerful and, especially for the former, interactive. To bring together researchers and practitioners working in this exciting field, a workshop on parallel data mining was organized as part of PKDD/ECML 2006 (Berlin, Germany). The six contributions selected for the program describe various aspects of data mining and machine learning approaches featuring low to high degrees of parallelism: The first contribution focuses the classic problem of distributed association rule mining and focuses on communication efficiency to improve the state of the art. After this a parallelization technique for speeding up decision tree construction by means of thread-level parallelism for shared memory systems is presented. The next paper discusses the design of a parallel approach for dis- tributed memory systems of the frequent subgraphs mining problem. This approach is based on a hierarchical communication topology to solve issues related to multi-domain computational envi- ronments. The forth paper describes the combined use and the customization of software packages to facilitate a top down parallelism in the tuning of Support Vector Machines (SVM) and the next contribution presents an interesting idea concerning parallel training of Conditional Random Fields (CRFs) and motivates their use in labeling sequential data. The last contribution finally focuses on very efficient feature selection. It describes a parallel algorithm for feature selection from random subsets. Selecting the papers included in this volume would not have been possible without the help of an international Program Committee that has provided detailed reviews for each paper. We would like to also thank Matthew Otey who helped with publicity for the workshop.

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Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.

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Issues pertaining to consumer understanding of food health claims are complex and difficult to disentangle because there is a surprising lack of multidisciplinary research aimed at evaluating how consumers are influenced by factors impacting on the evaluation process. In the EU, current legislation is designed to protect consumers from misleading and false claims but there is much debate about the concept of the ‘average consumer’ referred to in the legislation. This review provides an overview of the current legislative framework, discusses the concept of the ‘average consumer’ and brings together findings on consumer understanding from an international perspective. It examines factors related to the personal characteristics of individuals such as socio-demographic status, knowledge, and attitudes, and factors pertaining to food and food supplement products such as the wording of claims and the communication of the strength and consistency of the scientific evidence. As well as providing insights for future research, the conclusions highlight the importance of enhancing the communication of scientific evidence to improve consumer understanding of food health claims.

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The K-Means algorithm for cluster analysis is one of the most influential and popular data mining methods. Its straightforward parallel formulation is well suited for distributed memory systems with reliable interconnection networks, such as massively parallel processors and clusters of workstations. However, in large-scale geographically distributed systems the straightforward parallel algorithm can be rendered useless by a single communication failure or high latency in communication paths. The lack of scalable and fault tolerant global communication and synchronisation methods in large-scale systems has hindered the adoption of the K-Means algorithm for applications in large networked systems such as wireless sensor networks, peer-to-peer systems and mobile ad hoc networks. This work proposes a fully distributed K-Means algorithm (EpidemicK-Means) which does not require global communication and is intrinsically fault tolerant. The proposed distributed K-Means algorithm provides a clustering solution which can approximate the solution of an ideal centralised algorithm over the aggregated data as closely as desired. A comparative performance analysis is carried out against the state of the art sampling methods and shows that the proposed method overcomes the limitations of the sampling-based approaches for skewed clusters distributions. The experimental analysis confirms that the proposed algorithm is very accurate and fault tolerant under unreliable network conditions (message loss and node failures) and is suitable for asynchronous networks of very large and extreme scale.

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This paper proposes and demonstrates an approach, Skilloscopy, to the assessment of decision makers. In an increasingly sophisticated, connected and information-rich world, decision making is becoming both more important and more difficult. At the same time, modelling decision-making on computers is becoming more feasible and of interest, partly because the information-input to those decisions is increasingly on record. The aims of Skilloscopy are to rate and rank decision makers in a domain relative to each other: the aims do not include an analysis of why a decision is wrong or suboptimal, nor the modelling of the underlying cognitive process of making the decisions. In the proposed method a decision-maker is characterised by a probability distribution of their competence in choosing among quantifiable alternatives. This probability distribution is derived by classic Bayesian inference from a combination of prior belief and the evidence of the decisions. Thus, decision-makers’ skills may be better compared, rated and ranked. The proposed method is applied and evaluated in the gamedomain of Chess. A large set of games by players across a broad range of the World Chess Federation (FIDE) Elo ratings has been used to infer the distribution of players’ rating directly from the moves they play rather than from game outcomes. Demonstration applications address questions frequently asked by the Chess community regarding the stability of the Elo rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The method of Skilloscopy may be applied in any decision domain where the value of the decision-options can be quantified.

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The quadridentate N-heterocyclic ligand 6-(5,5,8,8-tetramethyl-5,6,7,8-tetrahydro-1,2,4-benzotriazin- 3-yl)-2,2′ : 6′,2′′-terpyridine (CyMe4-hemi-BTBP) has been synthesized and its interactions with Am(III),U(VI), Ln(III) and some transition metal cations have been evaluated by X-ray crystallographic analysis, Am(III)/Eu(III) solvent extraction experiments, UVabsorption spectrophotometry, NMR studies and ESI-MS. Structures of 1 : 1 complexes with Eu(III), Ce(III) and the linear uranyl (UO2 2+) ion were obtained by X-ray crystallographic analysis, and they showed similar coordination behavior to related BTBP complexes. In methanol, the stability constants of the Ln(III) complexes are slightly lower than those of the analogous quadridentate bis-triazine BTBP ligands, while the stability constant for the Yb(III)complex is higher. 1H NMR titrations and ESI-MS with lanthanide nitrates showed that the ligand forms only 1 : 1 complexes with Eu(III), Ce(III) and Yb(III), while both 1 : 1 and 1 : 2 complexes were formed with La(III) and Y(III) in acetonitrile. A mixture of isomeric chiral 2 : 2 helical complexes was formed with Cu(I), with a slight preference (1.4 : 1) for a single directional isomer. In contrast, a 1 : 1 complex was observed with the larger Ag(I) ion. The ligand was unable to extract Am(III) or Eu(III) from nitric acid solutions into 1-octanol, except in the presence of a synergist at low acidity. The results show that the presence of two outer 1,2,4-triazine rings is required for the efficient extraction and separation of An(III)from Ln(III) by quadridentate N-donor ligands.

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Methods for assessing the sustainability of agricultural systems do often not fully (i) take into account the multifunctionality of agriculture, (ii) include multidimensionality, (iii) utilize and implement the assessment knowledge and (iv) identify conflicting goals and trade-offs. This chapter reviews seven recently developed multidisciplinary indicator-based assessment methods with respect to their contribution to these shortcomings. All approaches include (1) normative aspects such as goal setting, (2) systemic aspects such as a specification of scale of analysis and (3) a reproducible structure of the approach. The approaches can be categorized into three typologies: first, top-down farm assessments, which focus on field or farm assessment; second, top-down regional assessments, which assess the on-farm and the regional effects; and third, bottom-up, integrated participatory or transdisciplinary approaches, which focus on a regional scale. Our analysis shows that the bottom-up, integrated participatory or transdisciplinary approaches seem to better overcome the four shortcomings mentioned above.

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“La questione di Trieste”, ovvero la questione del confine italo-yugoslavo all’indomani della seconda guerra mondiale costituisce da lungo tempo oggetto di attenzione e di esame da parte della storiografia italiana e straniera. Con alcune importanti eccezioni, la ricostruzione complessiva di quelle vicende ha visto il più delle volte il prevalere di un approccio storico-diplomatico che ha reso difficile comprendere con chiarezza i rapporti e le interdipendenze fra contesto locale, contesto nazionale e contesto internazionale. Attraverso la lettura incrociata dell’ampia documentazione proveniente dai fondi dei National Archives Records Administration (NARA) questo studio tenta una rilettura delle varie fasi di sviluppo della questione nel periodo compreso tra il giugno del 1945 e l’ottobre del 1954 secondo una duplice prospettiva: nella prima parte si concentra sulla politica americana a Trieste, guardando nello specifico a due aspetti interni tra loro strettamente correlati, la gestione dell’ordine pubblico e la “strategia” del consenso da realizzarsi mediante il controllo dell’informazione da un lato e la promozione di una politica culturale dall’altro. Sono aspetti entrambi riconducibili al modello del direct rule, che conferiva al governo militare alleato (GMA) piena ed esclusiva autorità di governo sulla zona A della Venezia Giulia, e che ci appaiono centrali anche per cogliere l’interazione fra istituzioni e soggetti sociali. Nella seconda parte, invece, il modificarsi della fonte d’archivio indica un cambiamento di priorità nella politica estera americana relativa a Trieste: a margine dei negoziati internazionali, i documenti del fondo Clare Boothe Luce nelle carte dell’Ambasciata mostrano soprattutto come la questione di Trieste venne proiettata verso l’esterno, verso l’Italia in particolare, e sfruttata – principalmente dall’ambasciatrice – nell’ottica bipolare della guerra fredda per rinforzare il sostegno interno alla politica atlantica. Il saggio, dunque, si sviluppa lungo due linee: dentro e fuori Trieste, dentro 1945-1952, fuori 1953-1954, perché dalle fonti consultate sono queste ad emergere come aree di priorità nei due periodi. Abstract - English The “Trieste question”, or the question regarding the Italian - Yugoslav border after the Second World War, has been the object of careful examination in both Italian and foreign historiography for a long time. With a few important exceptions, the overall reconstruction of these events has been based for the most part on historic and diplomatic approaches, which have sometimes made it rather difficult to understand clearly the relationships and interdependences at play between local, national and international contexts. Through a comparative analysis of a large body of documents from the National Archives and Records Administration (NARA), College Park MD, this essay attempts a second reading of the various phases in which the question developed between June 1945 and October 1954, following a twofold perspective: the first part focuses on American policy for Trieste, specifically looking at two internal and closely linked aspects, on the one hand, the management of ‘law and order’, as well as a ‘strategy’ of consent, to be achieved through the control of all the means of information , and, on the other, the promotion of a cultural policy. Both aspects can be traced back to the ‘direct rule’ model, which gave the Allied Military Government (AMG) full and exclusive governing authority over Venezia Giulia’s Zone A. These issues are also fundamental to a better understanding of the relationships between institutions and social subjects. In the second part of the essay , the change in archival sources clearly indicates a new set of priorities in American foreign policy regarding Trieste: outside any international negotiations for the settlement of the question, the Clare Boothe Luce papers held in the Embassy’s archives, show how the Trieste question was focused on external concerns, Italy in particular, and exploited – above all by the ambassador – within the bi-polar optic of the Cold War, in order to strengthen internal support for Atlantic policies. The essay therefore follows two main lines of inquiry: within and outside Trieste, within in 1945-1952, and outside 1953-1954, since, from the archival sources used, these emerge as priority areas in the two periods.

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The emergence and spread of infectious diseases reflects the interaction of ecological and economic factors within an adaptive complex system. We review studies that address the role of economic factors in the emergence and spread of infectious diseases and identify three broad themes. First, the process of macro-economic growth leads to environmental encroaching, which is related to the emergence of infectious diseases. Second, there are a number of mutually reinforcing processes associated with the emergence/spread of infectious diseases. For example, the emergence and spread of infectious diseases can cause significant economic damages, which in turn may create the conditions for further disease spread. Also, the existence of a mutually reinforcing relationship between global trade and macroeconomic growth amplifies the emergence/spread of infectious diseases. Third, microeconomic approaches to infectious disease point to the adaptivity of human behavior, which simultaneously shapes the course of epidemics and responds to it. Most of the applied research has been focused on the first two aspects, and to a lesser extent on the third aspect. With respect to the latter, there is a lack of empirical research aimed at characterizing the behavioral component following a disease outbreak. Future research should seek to fill this gap and develop hierarchical econometric models capable of integrating both macro and micro-economic processes into disease ecology.

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Global communicationrequirements andloadimbalanceof someparalleldataminingalgorithms arethe major obstacles to exploitthe computational power of large-scale systems. This work investigates how non-uniform data distributions can be exploited to remove the global communication requirement and to reduce the communication costin parallel data mining algorithms and, in particular, in the k-means algorithm for cluster analysis. In the straightforward parallel formulation of the k-means algorithm, data and computation loads are uniformly distributed over the processing nodes. This approach has excellent load balancing characteristics that may suggest it could scale up to large and extreme-scale parallel computing systems. However, at each iteration step the algorithm requires a global reduction operationwhichhinders thescalabilityoftheapproach.Thisworkstudiesadifferentparallelformulation of the algorithm where the requirement of global communication is removed, while maintaining the same deterministic nature ofthe centralised algorithm. The proposed approach exploits a non-uniform data distribution which can be either found in real-world distributed applications or can be induced by means ofmulti-dimensional binary searchtrees. The approachcanalso be extended to accommodate an approximation error which allows a further reduction ofthe communication costs. The effectiveness of the exact and approximate methods has been tested in a parallel computing system with 64 processors and in simulations with 1024 processing element

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The third chapter, data mining in education, examines potentials and constraints in the use of data mining in education, summarizing the potential they have to offer meaningful support to: students, teachers, tutors, authors, developers, researchers, and the education and training institutions in which they work and study.

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Climate change is putting Colombian agriculture under significant stress and, if no adaptation is made, the latter will be severely impacted during the next decades. Ramirez-Villegas et al. (2012) set out a government-led, top-down, techno-scientific proposal for a way forward by which Colombian agriculture could adapt to climate change. However, this proposal largely overlooks the root causes of vulnerability of Colombian agriculture, and of smallholders in particular. I discuss some of the hidden assumptions underpinning this proposal and of the arguments employed by Ramirez-Villegas et al., based on existing literature on Colombian agriculture and the wider scientific debate on adaptation to climate change. While technical measures may play an important role in the adaptation of Colombian agriculture to climate change, I question whether the actions listed in the proposal alone and specifically for smallholders, truly represent priority issues. I suggest that by i) looking at vulnerability before adaptation, ii) contextualising climate change as one of multiple exposures, and iii) truly putting smallholders at the centre of adaptation, i.e. to learn about and with them, different and perhaps more urgent priorities for action can be identified. Ultimately, I argue that what is at stake is not only a list of adaptation measures but, more importantly, the scientific approach from which priorities for action are identified. In this respect, I propose that transformative rather than technical fix adaptation represents a better approach for Colombian agriculture and smallholders in particular, in the face of climate change.

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Projected changes in the extra-tropical wintertime storm tracks are investigated using the multi-model ensembles from both the third and fifth phases of the World Climate Research Programme's Coupled Model Intercomparison Project (CMIP3 and CMIP5). The aim is to characterize the magnitude of the storm track responses relative to their present-day year-to-year variability. For the experiments considered, the ‘middle-of-the-road’ scenarios in each CMIP, there are regions of the Northern Hemisphere where the responses of up to 40% of the models exceed half of the inter-annual variability, and for the Southern Hemisphere there are regions where up to 60% of the model responses exceed half of the inter-annual variability.

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Pesticide use among smallholder coffee producers in Jamaica has been associated with significant occupational health effects. Research on pesticide handling practices, however, has been scarce, especially in eastern Jamaica. This explorative study aims at filling this gap and provides a first basis to develop effective interventions to promote a safer pesticide use. A random sample of 81 coffee farmers was surveyed. The majority of farmers reported to suffer from at least one health symptom associated with pesticide handling, but safety practices were scarcely adopted. There was also the risk that other household members and the wider local community are exposed to pesticides. The lack of training on pesticide management, the role of health services and the cost for protective equipment seemed to be the most significant factors that influence current pesticide handling practices in eastern Jamaica. Further research is recommended to develop a systemic understanding of farmer’s behaviour to provide a more solid basis for the development of future intervention programmes.