A comparative analysis of methods for pruning decision trees

In this paper, we address the problem of retrospectively pruning decision trees induced from data, according to a top-down approach. This problem has received considerable attention in the areas of pattern recognition and machine learning, and many distinct methods have been proposed in literature. We make a comparative study of six well-known pruning methods with the aim of understanding their theoretical foundations, their computational complexity, and the strengths and weaknesses of their formulation. Comments on the characteristics of each method are empirically supported. In particular, a wide experimentation performed on several data sets leads us to opposite conclusions on the predictive accuracy of simplified trees from some drawn in the literature. We attribute this divergence to differences in experimental designs. Finally, we prove and make use of a property of the reduced error pruning method to obtain an objective evaluation of the tendency to overprune/underprune observed in each method     

Digital watermarking robust to geometric distortions.

In this paper, we present two watermarking approaches that are robust to geometric distortions. The first approach is based on image normalization, in which both watermark embedding and extraction are carried out with respect to an image normalized to meet a set of predefined moment criteria. We propose a new normalization procedure, which is invariant to affine transform attacks. The resulting watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. The second approach is based on a watermark resynchronization scheme aimed to alleviate the effects of random bending attacks. In this scheme, a deformable mesh is used to correct the distortion caused by the attack. The watermark is then extracted from the corrected image. In contrast to the first scheme, the latter is suitable for private watermarking applications, where the original image is necessary for watermark detection. In both schemes, we employ a direct-sequence code division multiple access approach to embed a multibit watermark in the discrete cosine transform domain of the image. Numerical experiments demonstrate that the proposed watermarking schemes are robust to a wide range of geometric attacks.     

Localized dissection of the abdominal aorta. Diagnosis and surgical treatment

Abdominal aortic dissection is a rare pathology. As far as we are concerned, only 59 cases have been reported in the English literature. In the last two years, two cases were treated at our Institution. Both were males, over 70 years of age. They were evaluated with ultrasonography, angiography (1 case) and Magnetic Resonance Imaging which showed localised dissection of the abdominal aorta with aneurysmal dilatation. They underwent surgical treatment with good results. At 1 and 2 years from operation both patients are alive and well. A postoperative ultrasonography didn't show any residual dissection.     

Resonant Quantum Phenomena for an rf-SQUID: Moderate Underdamped and Extreme Underdamped Limit

We study the resonant quantum behaviour of a macroscopic superconducting system interacting with an external field. First we consider the resonant tunneling assisted by microwave frequency in the moderate underdamped quantum regime. Then we consider the resonant process in the extreme underdamped limit. In both regimes we have investigated a small frequency range, where resonant phenomena take place. The transition probability W from the left to the right potential well has been numerically calculated for an rf-SQUID as function of the external flux φ _x for both regimes. Results indicate that, in a proper frequency and φ _x range, the transition probability W can present two or three resonant peaks, depending on the damping regime.