University of Patras

About: University of Patras is a education organization based out in Pátrai, Greece. It is known for research contribution in the topics: Population & Catalysis. The organization has 13372 authors who have published 31263 publications receiving 677159 citations. The organization is also known as: Panepistímio Patrón.

Primitive Path Identification and Entanglement Statistics in Polymer Melts: Results from Direct Topological Analysis on Atomistic Polyethylene Models

Abstract: A large number of well-equilibrated atomistic configurations of linear, strictly monodisperse polyethylene (PE) melts of molecular length ranging from C24 up to C1000, obtained through extensive Monte Carlo simulations based on chain connectivity altering algorithms, have been subjected to a detailed topological analysis. Primitive paths are geometrically constructed connecting the two ends of a polymer chain (which in all cases are considered as fixed in space) under the constraint of no chain crossability, such that the multiple disconnected (coarse-grained) path has minimum contour length. When applied to a given, dense polymer configuration in 3-D space, the algorithm returns the primitive path (PP) and the related number and positions of entanglements (kinks) for all chains in the simulation box, thus providing extremely useful information for the topological structure (the primitive path network) hidden in bulk PE. In particular, our analysis demonstrates that once a characteristic chain length valu...

Ozonolysis of α-pinene: parameterization of secondary organic aerosol mass fraction

Abstract: . Existing parameterizations tend to underpredict the α-pinene aerosol mass fraction (AMF) or yield by a factor of 2–5 at low organic aerosol concentrations (

Hidden messages in heavy-tails: DCT-domain watermark detection using alpha-stable models

Abstract: This paper addresses issues that arise in copyright protection systems of digital images, which employ blind watermark verification structures in the discrete cosine transform (DCT) domain. First, we observe that statistical distributions with heavy algebraic tails, such as the alpha-stable family, are in many cases more accurate modeling tools for the DCT coefficients of JPEG-analyzed images than families with exponential tails such as the generalized Gaussian. Motivated by our modeling results, we then design a new processor for blind watermark detection using the Cauchy member of the alpha-stable family. The Cauchy distribution is chosen because it is the only non-Gaussian symmetric alpha-stable distribution that exists in closed form and also because it leads to the design of a nearly optimum detector with robust detection performance. We analyze the performance of the new detector in terms of the associated probabilities of detection and false alarm and we compare it to the performance of the generalized Gaussian detector by performing experiments with various test images.