Reworking the Web, Reworking the World: How Web 2.0 is Changing our Society

Web 2.0 refers to a suite of technologies that have dramatically lowered the interaction costs of two-way communication over the World Wide Web, which has democratized the production of information and applications across the internet. To sum up the Web 2.0 phenomena in a sentence: lower communication costs have led to opportunities for more inclusive, collaborative, democratic online participation. As the costs of communicating online decreased, more people, in terms of million, decided that it was worth their while to participate in these communication networks. These people did not just communicate more, they started communicating in qualitatively different ways than before. As these millions found new media for expression and collaboration, they opened possibilities for a more inclusive, open, democratic society, possibilities which may or may not be realized.There is no doubt that this democratization, these contributions from many millions of web participants, has produced a series of profound social, political and economic changes that this paper will seek to document. The changes inspired by the democratization of the web, however, will not of necessity lead to a more equitable distribution of power and resources in our society. The future of the web will depend upon the degree to which this blossoming of online participation will allow ordinary citizens and consumers to have greater voice and influence in shaping society and the degree to which powerful political and commercial interests can co-opt and constrain the surge of online enthusiasm in the support of the established hierarchy.

Gravity Models in R

Gravity models are used to explain bilateral flows related to the sizes of bilateral partners, a measure of distance between them and other influences on interaction costs. The underlying idea is rather simple. The greater the masses of two bodies and the smaller the distance between them, the stronger they attract each other. This concept is applied to several research topics such as trade, migration or foreign direct investment. Even though the basic idea of gravity models is rather simple, they can become very complex when it comes to the choice of models or estimation methods. The package \textbf{gravity} targets to provide \proglang{R} users with the functions necessary to execute the most common estimation methods for gravity models, especially for cross-sectional data. Gravitätsmodelle werden verwendet, um bilaterale Ströme zu erklären. Dabei werden sowohl die Größen und die Distanz der jeweiligen Partner als auch weitere Einflussfaktoren zur Erklärung herangezogen. Die zugrundeliegende Idee dieser Modelle beruht auf dem Gravitätsprinzip. Je schwerer zwei Körper und je kleiner deren Distanz zueinander, desto stärker ist ihre gegenseitige Anziehungskraft. Dieses Konzept wird auf verschiedene Forschungsreiche angewendet, so zum Beispiel Handel, Migration und ausländische Direktinvestitionen. Auch wenn die zugrundeliegende Idee von Gravitätsmodellen eher einfach ist, so kann deren Schätzung je nach Wahl des zugrundegelegten ökonomischen Zusammenhangs komplex werden. Das Paket \textbf{gravity} ermöglicht es \proglang{R}-Nutzern die gängigsten Verfahren für Gravitätsmodelle in der Querschnittsanalyse zu verwenden.

Interactive Segmentation of Pancreases in Abdominal Computed Tomography Images and Its Evaluation Based on Segmentation Accuracy and Interaction Costs

The present paper proposed an interactive segmentation method of pancreases in abdominal computed tomography (CT) images based on the anatomical knowledge of medical doctors and the statistical information of pancreas shapes. This segmentation method consisted of two phases: training and testing. In the training phase, pancreas regions were manually extracted from sample CT images for training, and then a probabilistic atlas (PA) was constructed from the extracted regions. In the testing phase, a medical doctor selected seed voxels for a pancreas and background in a CT image for testing by use of our graphical user interface system. The homography transformation was used to fit the PA to the seeds. The graph cut technique whose data term was weighted by the transformed PA was applied to the test image. The seed selection, the atlas transformation, and the graph cut were executed iteratively. This doctor-in-the-loop segmentation method was applied to actual abdominal CT images of fifteen cases. The experimental results demonstrated that the proposed method was more accurate and effective than the conventional graph cut.