University of Trento

About: University of Trento is a education organization based out in Trento, Italy. It is known for research contribution in the topics: Population & Context (language use). The organization has 10527 authors who have published 30978 publications receiving 896614 citations. The organization is also known as: Universitá degli Studi di Trento & Universita degli Studi di Trento.

Proposed antimatter gravity measurement with an antihydrogen beam

Abstract: The principle of the equivalence of gravitational and inertial mass is one of the cornerstones of general relativity. Considerable efforts have been made and are still being made to verify its validity. A quantum-mechanical formulation of gravity allows for non-Newtonian contributions to the force which might lead to a difference in the gravitational force on matter and antimatter. While it is widely expected that the gravitational interaction of matter and of antimatter should be identical, this assertion has never been tested experimentally. With the production of large amounts of cold antihydrogen at the CERN Antiproton Decelerator, such a test with neutral antimatter atoms has now become feasible. For this purpose, we have proposed to set up the AEGIS experiment at CERN/AD, whose primary goal will be the direct measurement of the Earth's gravitational acceleration on antihydrogen with a classical Moire deflectometer.

Phase diagram and thermodynamics of the three-dimensional Bose-Hubbard model

Abstract: We report results of quantum Monte Carlo simulations of the Bose-Hubbard model in three dimensions. Critical parameters for the superfluid-to-Mott-insulator transition are determined with significantly higher accuracy than has been done in the past. In particular, the position of the critical point at filling factor $n=1$ is found to be at ${(U∕t)}_{\mathrm{c}}=29.34(2)$, and the insulating gap $\ensuremath{\Delta}$ is measured with accuracy of a few percent of the hopping amplitude $t$. We obtain the effective mass of particle and hole excitations in the insulating state---with explicit demonstration of the emerging particle-hole symmetry and relativistic dispersion law at the transition tip---along with the sound velocity in the strongly correlated superfluid phase. These parameters are the necessary ingredients to perform analytic estimates of the low temperature $(T⪡\ensuremath{\Delta})$ thermodynamics in macroscopic samples. We present accurate thermodynamic curves, including these for specific heat and entropy, for typical insulating $(U∕t=40)$ and superfluid $(t∕U=0.0385)$ phases. Our data can serve as a basis for accurate experimental thermometry, and a guide for appropriate initial conditions if one attempts to use interacting bosons in quantum information processing.

Sludge Reduction Technologies in Wastewater Treatment Plants

Abstract: Sludge Reduction Technologies in Wastewater Treatment Plants is a review of the sludge reduction techniques integrated in wastewater treatment plants with detailed chapters on the most promising and most widespread techniques. The aim of the book is to update the international community on the current status of knowledge and techniques in the field of sludge reduction. It will provide a comprehensive understanding of the following issues in sludge reduction: This book will be essential reading for managers and technical staff of wastewater treatment plants as well as graduate students and post-graduate specialists. ISBN: 9781843392781 (Print) ISBN: 9781780401706 (eBook)

Beyond Frame-level CNN: Saliency-Aware 3-D CNN With LSTM for Video Action Recognition

Abstract: Human activity recognition in videos with convolutional neural network (CNN) features has received increasing attention in multimedia understanding. Taking videos as a sequence of frames, a new record was recently set on several benchmark datasets by feeding frame-level CNN sequence features to long short-term memory (LSTM) model for video activity recognition. This recurrent model-based visual recognition pipeline is a natural choice for perceptual problems with time-varying visual input or sequential outputs. However, the above-mentioned pipeline takes frame-level CNN sequence features as input for LSTM, which may fail to capture the rich motion information from adjacent frames or maybe multiple clips. Furthermore, an activity is conducted by a subject or multiple subjects. It is important to consider attention that allows for salient features, instead of mapping an entire frame into a static representation. To tackle these issues, we propose a novel pipeline, saliency-aware three-dimensional (3-D) CNN with LSTM, for video action recognition by integrating LSTM with salient-aware deep 3-D CNN features on videos shots. Specifically, we first apply saliency-aware methods to generate saliency-aware videos. Then, we design an end-to-end pipeline by integrating 3-D CNN with LSTM, followed by a time series pooling layer and a softmax layer to predict the activities. Noticeably, we set a new record on two benchmark datasets, i.e., UCF101 with 13 320 videos and HMDB-51 with 6766 videos. Our method outperforms the state-of-the-art end-to-end methods of action recognition by 3.8% and 3.2%, respectively on above two datasets.

Clio: Schema Mapping Creation and Data Exchange

Abstract: The Clio project provides tools that vastly simplify information integration. Information integration requires data conversions to bring data in different representations into a common form. Key contributions of Clio are the definition of non-procedural schema mappings to describe the relationship between data in heterogeneous schemas, a new paradigm in which we view the mapping creation process as one of query discovery, and algorithms for automatically generating queries for data transformation from the mappings. Clio provides algorithms to address the needs of two major information integration problems, namely, data integration and data exchange . In this chapter, we present our algorithms for both schema mapping creation via query discovery, and for query generation for data exchange. These algorithms can be used in pure relational, pure XML, nested relational, or mixed relational and nested contexts.