Polytechnic University of Milan

About: Polytechnic University of Milan is a education organization based out in Milan, Italy. It is known for research contribution in the topics: Computer science & Finite element method. The organization has 18231 authors who have published 58416 publications receiving 1229711 citations. The organization is also known as: PoliMi & L-NESS.

Conceptual modeling of data-intensive Web applications

Abstract: Many of the Web applications around us are data-intensive; their main purpose is to present a large amount of data to their users Most online trading and e-commerce sites fall into this category, as do digital libraries and institutional sites describing private and public organizations Several commercial Web development systems aid rapid creation of data-intensive applications by supporting semiautomatic data resource publishing Automatic publishing is typically subject to the constraints of database schemas, which limit an application designer's choices Thus, Web application development often requires adaptation through programming, and programs end up intricately mixing data, navigation, and presentation semantics Presentation is often a facade for elements of structure, composition, and navigation Despite this frequently unstructured development process, data-intensive applications, based on large data sets organized within a repository or database, generally follow some typical patterns and rules We describe these patterns and rules using WebML as a conceptual tool to make such notions explicit WebML is a conceptual Web modeling language that uses the entity-relationship (ER) model for describing data structures and an original, high-level notation for representing Web content composition and navigation in hypertext form

Neuromorphic Learning and Recognition With One-Transistor-One-Resistor Synapses and Bistable Metal Oxide RRAM

Abstract: Resistive switching memory (RRAM) has been proposed as an artificial synapse in neuromorphic circuits due to its tunable resistance, low power operation, and scalability. For the development of high-density neuromorphic circuits, it is essential to validate the state-of-the-art bistable RRAM and to introduce small-area building blocks serving as artificial synapses. This paper introduces a new synaptic circuit consisting of a one-transistor/one-resistor structure, where the resistive element is a HfO2 RRAM with bipolar switching. The spike-timing-dependent plasticity is demonstrated in both the deterministic and stochastic regimes of the RRAM. Finally, a fully connected neuromorphic network is simulated showing online unsupervised pattern learning and recognition for various voltages of the POST spike. The results support bistable RRAM for high-performance artificial synapses in neuromorphic circuits.