The technologies, architectures, and methodologies traditionally used to develop distributed applications exhibit a variety of limitations and drawbacks when applied to large scale distributed settings (e.g., the Internet). In particular, they fail in providing the desired degree of configurability, scalability, and customizability. To address these issues, researchers are investigating a varie...

summary based on the results of the analysis of site effects, mostly those with shear wave velocity and the fundamental period chosen as the basis for classification. in revision of earthquake resistant design regulations for buildings, classification of lands should be subject to the field conditions, geological, geotechnical, geophysical, and laboratory tests.in this context, the average shea...

Change-prone classes or modules are defined as software components in the source code which are likely to change in the future. Change-proneness prediction is useful to the maintenance team as they can optimize and focus their testing resources on the modules which have a higher likelihood of change. Change-proneness prediction model can be built by using source code metrics as predictors or fe...

JEL Classification Code(s): J 31, J 71) "Perceptions of Discrimination, Effort to Obtain Psychological Balance, and Relative Wages: Can We Infer a Happiness Gradient?" There is a substantial literature that finds a linkage between happiness and relative economic well being as measured by earnings or wages. There is also a well documented racial gap in wages. One explanation for this is disparat...

This paper is concerned with automatic classification of texts in a medical domain. The process consists in classifying reports of medical discharges into classes defined by the CIE-9-MC codes. We will assign CIE-9-MC codes to reports using either a knn model or support vector machines. One of the added values of this work is the construction of the collection using the discharge reports of a m...

The task of assigning classification codes to short medical text is a hard text classification problem, especially when the set of possible codes is as big as the ICD-9-CM set. The problem, which has been only partially tamed for a subset of ICD-9-CM, becomes even harder in real world applications, where the labeled data are scarce and noisy. In this paper we first show the ineffectiveness of c...

Automatic knowledge discovery methodologies has proved to be a very strong tool which is currently widely used for the analysis of large datasets, being produced by organizations worldwide. However, this analysis is mostly done for relatively simple and structured data, such as transactional or nancial records. The real frontier for current KDD research seems to be analysis of unstructured data...

Recent research has repeatedly shown that machine learning techniques can be applied to either whole files or file fragments to classify them for analysis. We build upon these techniques to show that for samples of un-labeled compiled computer object code, one can apply the same type of analysis to classify important aspects of the code, such as its target architecture and endianess. We show th...