Implementation of mobile satellite services in developing countries: The Mexican experience

An analysis of the differences between Developing Countries (DCs) and Industrialized Countries (ICs), in the context of Mobile Satellite Services (MSSs) providers and regulators, is presented. Additionally, a series of recommendations that may improve the odds for a successful implementation of MSSs in DCs are provided

Youth unemployment in Belgium: diagnosis and key remedies

In Belgium youth unemployment is structurally higher than the European (EU27) average, in particular for the low educated. In this study we set a diagnosis of the main structural factors and advance key remedies. We analyze the system of employment protection, education and passive and active labor market policies. A high minimum wage, a strict separation between school and work, and a vertically segmented schooling system with high retention rates and too early tracking are identified as main causal factors. Strict employment protection legislation is only concern for high-skilled youth. Reducing labor costs at low wages and a fundamental schooling reform that aims at dismantling the strict barrier between school and work are proposed as key remedies. In addition, youth should be entitled as of the start of unemployment to a low benefit based on the principle of “mutual obligation”. Very intensive and durable guidance is to be targeted to the low educated

Towards a constructional approach to discourse-level phenomena : the case of the Spanish interpersonal epistemic stance construction

This study contributes to a better understanding of how constructional models can be applied to discourse-level phenomena, and constitute a valuable complementation to previous grammaticalization accounts of pragmatic markers. The case study that is presented concerns the recent development of the interpersonal epistemic stance construction in Spanish. The central argument is that the expanding use of sabes as a pragmatic marker can best be fully understood by taking into account the composite network of related expressions which Spanish speakers have at their disposal when performing a particular speech act. The diachronic analysis is documented with spoken corpus examples collected in recent decades, and is mainly informed by frequency data measuring the productivity, as well as formal properties of the construction and its instances

Redefining Stewardship: Public Lands and Rural Communities in the Pacific Northwest

pdf contains 24 page

Software cost estimation

The paper gives an overview of the state of the art of software cost estimation (SCE). The main questions to be answered in the paper are: (1) What are the reasons for overruns of budgets and planned durations? (2) What are the prerequisites for estimating? (3) How can software development effort be estimated? (4) What can software project management expect from SCE models, how accurate are estimations which are made using these kind of models, and what are the pros and cons of cost estimation models

An ontology enhanced parallel SVM for scalable spam filter training

This is the post-print version of the final paper published in Neurocomputing. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Spam, under a variety of shapes and forms, continues to inflict increased damage. Varying approaches including Support Vector Machine (SVM) techniques have been proposed for spam filter training and classification. However, SVM training is a computationally intensive process. This paper presents a MapReduce based parallel SVM algorithm for scalable spam filter training. By distributing, processing and optimizing the subsets of the training data across multiple participating computer nodes, the parallel SVM reduces the training time significantly. Ontology semantics are employed to minimize the impact of accuracy degradation when distributing the training data among a number of SVM classifiers. Experimental results show that ontology based augmentation improves the accuracy level of the parallel SVM beyond the original sequential counterpart