A Model of Party Discipline in a Congress

This paper studies party discipline in a congress within a political agency framework with retrospective voting. Party discipline serves as an incentive device to induce office- motivated congress members to perform in line with the party leadership's objective of controlling both the executive and the legislative branches of government. I show fi…rst that the same party is more likely to control both branches of government (i.e., uni…ed government) the stronger the party discipline in the congress is. Second, the leader of the governing party imposes more party discipline under uni…ed government than does the opposition leader under divided government. Moreover, the incumbents' aggregate performance increases with party discipline, so a representative voter becomes better off. JEL classi…cation: D72. Keywords: Party discipline; Political agency; Retrospective voting; Office-motivated politicians.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

An efficient use of virtualization in grid/cloud environments

Grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational resources. Grid enables access to the resources but it does not guarantee any quality of service. Moreover, Grid does not provide performance isolation; job of one user can influence the performance of other user’s job. The other problem with Grid is that the users of Grid belong to scientific community and the jobs require specific and customized software environment. Providing the perfect environment to the user is very difficult in Grid for its dispersed and heterogeneous nature. Though, Cloud computing provide full customization and control, but there is no simple procedure available to submit user jobs as in Grid. The Grid computing can provide customized resources and performance to the user using virtualization. A virtual machine can join the Grid as an execution node. The virtual machine can also be submitted as a job with user jobs inside. Where the first method gives quality of service and performance isolation, the second method also provides customization and administration in addition. In this thesis, a solution is proposed to enable virtual machine reuse which will provide performance isolation with customization and administration. The same virtual machine can be used for several jobs. In the proposed solution customized virtual machines join the Grid pool on user request. Proposed solution describes two scenarios to achieve this goal. In first scenario, user submits their customized virtual machine as a job. The virtual machine joins the Grid pool when it is powered on. In the second scenario, user customized virtual machines are preconfigured in the execution system. These virtual machines join the Grid pool on user request. Condor and VMware server is used to deploy and test the scenarios. Condor supports virtual machine jobs. The scenario 1 is deployed using Condor VM universe. The second scenario uses VMware-VIX API for scripting powering on and powering off of the remote virtual machines. The experimental results shows that as scenario 2 does not need to transfer the virtual machine image, the virtual machine image becomes live on pool more faster. In scenario 1, the virtual machine runs as a condor job, so it easy to administrate the virtual machine. The only pitfall in scenario 1 is the network traffic.

Regional Advisory Committee on Cancer - Second Report 2002 (PDF 132 KB)

Regional Advisory Committee on Cancer (RACC) was established in 1997 to carry forward the recommendations of the Campbell Report of 1996 and to provide advice to the Department of Health and Social Services on the future development of cancer services. The Committee meets twice a year and its membership (Appendix I) is an indication of the wide range of interests involved in Cancer Care across the community. This report records some of the key developments in cancer services over the last 3 years. åÊ Significant progress has been made toward developing a high quality and integrated cancer care network. All five Cancer Units are now operational with chemotherapy and outpatient services for the most common forms of cancer are delivered from these locations. Agreement to the start of the new Cancer Centre, at the Belfast City Hospital, currently estimated to cost å£58m, is expected shortly. As a temporary expedient two additional therapy machines will be installed in Belvoir Park Hospital to increase capacity while the building of the new Cancer Centre proceeds. åÊ To deliver high quality cancer care the workforce needs to continue to expand. This requires increasing investment in the training of professional staff in the context of an already difficult HPSS labour market. The development of the five Cancer Units has increased staff mobility in the short-term, drawing skilled staff away from the centre who have been difficult to replace. At the same time increasing numbers of patients are being offered effective therapies at both the Cancer Units and the Centre. åÊ This report contains a review of selected developments in cancer care. The first section introduces the Memorandum of Understanding and the Tripartite Agreement between the National Cancer Institute of the USA and the Health Departments both North and South. This is a unique international partnership, which promises to bring very significant advantages to both the service and research communities across the Island. åÊ åÊ åÊ

Does VAA popularity pay off ? : Smartvote users preferred candidates and their results in the 2007 Swiss federal elections

Voting is fundamental for democracy, however, this decisive democratic act requires quite an effort. Decision making at elections depends largely on the interest to gather information about candidates and parties, the effort to process the information at hand and the motivation to reach a vote choice. Especially in electoral systems with highly fragmented party systems and hundreds of candidates running for office, the process of decision making in the pre‐election sphere is highly demanding. In the age of information and communication technologies, new possibilities for gathering and processing such information are available. Voting Advice Applications (VAAs) provide guidance to voters prior to the act of voting and assist voters in choosing between different candidates and parties on the basis of issue congruence. Meanwhile widely used all over the world, scientific inquiry into the effect of such tools on electoral behavior is ongoing. This paper adds to the current debate by focusing on whether the popularity of candidates on the Swiss VAA smartvote eventually paid off at the 2007 Swiss federal elections and whether there is a direct link between the performance of a candidate on the tool and his or her electoral performance.

Cinéma, machine à mondes : essai sur les films à univers multiples

Dans cet ouvrage, l'auteur propose une conceptualisation théorique de la coprésence en un même film de mondes multiples en abordant différents paramètres (hétérogénéité de la facture de l'image, pratiques du montage alterné, typologie des enchâssements, expansion sérielle, etc.) sur la base d'un corpus de films de fiction récents qui appartiennent pour la plupart au genre de la science-fiction (Matrix, Dark City, Avalon, Resident Evil, Avatar,...). Issue de la filmologie, la notion de « diégèse » y est développée à la fois dans le potentiel d'autonomisation dont témoigne la conception mondaine qui semble dominer aujourd'hui à l'ère des jeux vidéo, dans ses liens avec le récit et dans une perspective intermédiale. Les films discutés ont la particularité de mettre en scène des machines permettant aux personnages de passer d'un monde à l'autre : les modes de figuration de ces technologies sont investigués en lien avec les imaginaires du dispositif cinématographique et les potentialité du montage. La comparaison entre les films (Tron et son récent sequel, Totall Recall et son remake) et entre des oeuvres filmiques et littéraires (en particulier les nouvelles de Philip K. Dick et Simlacron 3 de Galouye) constitue un outil d'analyse permettant de saisir la contemporanéité de cette problématique, envisagée sur le plan esthétique dans le contexte de l'imagerie numérique.

Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling

An active learning method is proposed for the semi-automatic selection of training sets in remote sensing image classification. The method adds iteratively to the current training set the unlabeled pixels for which the prediction of an ensemble of classifiers based on bagged training sets show maximum entropy. This way, the algorithm selects the pixels that are the most uncertain and that will improve the model if added in the training set. The user is asked to label such pixels at each iteration. Experiments using support vector machines (SVM) on an 8 classes QuickBird image show the excellent performances of the methods, that equals accuracies of both a model trained with ten times more pixels and a model whose training set has been built using a state-of-the-art SVM specific active learning method

Ultrasound monitoring of structural urinary tract disease in Schistosoma haematobium infection

A major advance in our understanding of the natural history of Schistosoma haematobium-related morbidity has come through the introduction of the portable ultrasound machines for non-invasive examination of the kidneys and bladder. With the use of generators or battery packs to supply power in non-clinical field settings, and with the use of instant photography or miniaturized thermal printers to record permanent images, it is possible to examine scores of individuals in endemic communities every day. Broad-based ultrasound screening has allowed better definition of age-specific disease risks in urinary schistosomiasis. Results indicate that urinary tract abnormalities are common (18% overall prevalence) in S. haematobium transmission areas, with a 2-4% risk of either severe bladder abnormality or advanced ureteral obstruction. In longitudinal surveys, ultrasound studies have shown that praziquantel and metrifonate therapy are rapidly effective in reversing urinary tract abnormalities among children. The benefits of treating adults are less well known, but research in progress should help to define this issue. Similarly, the prognosis of specific ultrasound findings needs to be clarified, and the ease of sonographic examination will make such long-term follow-up studies feasible. In summary, the painless, quick, and reproducible ultrasound examination has become an essential tool in the study of urinary schistosomiasis.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

The Strength of Promissory Representation : What Makes MPs Change their Positions ?

The paper analyses the positional congruence between pre-election statements in the Swiss voting assistance application "smartvote" and post-election behaviour in the Swiss lower house between 2003 and 2009. For this purpose, we selected 34 smartvote questions which subsequently came up in parliament. Unlike previous studies which assessed the program-to-policy linkage of governments or party groups the paper examines the question at the level of individual MPs which seems appropriate for political systems which follow the idea of power dispersion. While the average rate of political congruence is at some 85 percent, a multivariate analysis detects the underlying factors which push or curb a candidate's propensity to change his or her mind once elections are over. The results show that positional changes are more likely if (1) MPs are freshmen, (2) individual voting behaviour is invisible to the public, (3) the vote is not about a party's core issue, (4) the MP belongs to a party which is located in the political centre, and (5) if the pre-election statement is in disagreement with the majority position of the legislative party group. The last-mentioned factor is paramount: the farer away a candidate's pre-election profile from his or her party is located, the weaker turns out to be the electoral link of promissory representation.

Disseny i implementació de la base de dades : Sistema de votació ciutadana a nivell Europeu a través d'Internet

La Comunitat Europea ha encarregat el disseny i implementació d'una base de dades per a un futur sistema de votacions ciutadanes per Internet. Aquest projecte realitza una proposta del disseny de la base de dades segons els requeriments especificats, i la seva implementació en un sistema de gestió de bases de dades, que en aquest cas és l'ORACLE.

Disseny i implementació de la base de dades d'un sistema de votació ciutadà a nivell Europeu a través d'Internet

La Comunitat Europea desitja implementar una aplicació per a gestionar les votacions ciutadanes a través d'Internet. Aquesta, dins de la partida pressupostària destinada a fomentar la participació ciutadana dins de l'àmbit polític Europeu, ha decidit obrir un concurs públic per rebre propostes sobre el disseny d'una base de dades (BD) que els hi serveixi de magatzem d'informació per a la futura aplicació.

Disseny i implementació de la base de dades d'un sistema de votació ciutadana a nivell europeu a través d'Internet

Disseny d'una base de dades (BD), que els hi serveixi de magatzem d'informació per a la futura aplicació de votacions ciutadanes a través d'Internet, que volen implementar.