Validation of Logistic Regression Models for Landslide Susceptibility Maps

A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed and documented during the field studies. The validation analysis is exploited to investigate the quality of mapping.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.

Normalisation informatique et marchés de services : le cas du XML

Extensible Markup Language (XML) is a generic computing language that provides an outstanding case study of commodification of service standards. The development of this language in the late 1990s marked a shift in computer science as its extensibility let store and share any kind of data. Many office suites software rely on it. The chapter highlights how the largest multinational firms pay special attention to gain a recognised international standard for such a major technological innovation. It argues that standardisation processes affects market structures and can lead to market capture. By examining how a strategic use of standardisation arenas can generate profits, it shows that Microsoft succeeded in making its own technical solution a recognised ISO standard in 2008, while the same arena already adopted two years earlier the open source standard set by IBM and Sun Microsystems. Yet XML standardisation also helped to establish a distinct model of information technology services at the expense of Microsoft monopoly on proprietary software

Recent advances in remote sensing image processing

Remote sensing image processing is nowadays a mature research area. The techniques developed in the field allow many real-life applications with great societal value. For instance, urban monitoring, fire detection or flood prediction can have a great impact on economical and environmental issues. To attain such objectives, the remote sensing community has turned into a multidisciplinary field of science that embraces physics, signal theory, computer science, electronics, and communications. From a machine learning and signal/image processing point of view, all the applications are tackled under specific formalisms, such as classification and clustering, regression and function approximation, image coding, restoration and enhancement, source unmixing, data fusion or feature selection and extraction. This paper serves as a survey of methods and applications, and reviews the last methodological advances in remote sensing image processing.

Quelques abus de la statistique dans la recherche médicale [Various abuses of statistics in medical research].

Statistics has become an indispensable tool in biomedical research. Thanks, in particular, to computer science, the researcher has easy access to elementary "classical" procedures. These are often of a "confirmatory" nature: their aim is to test hypotheses (for example the efficacy of a treatment) prior to experimentation. However, doctors often use them in situations more complex than foreseen, to discover interesting data structures and formulate hypotheses. This inverse process may lead to misuse which increases the number of "statistically proven" results in medical publications. The help of a professional statistician thus becomes necessary. Moreover, good, simple "exploratory" techniques are now available. In addition, medical data contain quite a high percentage of outliers (data that deviate from the majority). With classical methods it is often very difficult (even for a statistician!) to detect them and the reliability of results becomes questionable. New, reliable ("robust") procedures have been the subject of research for the past two decades. Their practical introduction is one of the activities of the Statistics and Data Processing Department of the University of Social and Preventive Medicine, Lausanne.

Social sensing for psychology: Automated interpersonal behavior assessment

In this article, we show how the use of state-of-the-art methods in computer science based on machine perception and learning allows the unobtrusive capture and automated analysis of interpersonal behavior in real time (social sensing). Given the high ecological validity of the behavioral sensing, the ease of behavioral-cue extraction for large groups over long observation periods in the field, the possibility of investigating completely new research questions, and the ability to provide people with immediate feedback on behavior, social sensing will fundamentally impact psychology.