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 & Large Hadron Collider. 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.

Structural and dynamical properties of superfluid helium: A density-functional approach

Abstract: We present a novel density functional for liquid 4 He, properly accounting for the static response function and the phonon-roton dispersion in the uniform liquid. The functional is used to study both structural and dynamical properties of superfluid helium in various geometries. The equilibrium properties of the free surface, droplets and films at zero temperature are calculated. Our predictions agree closely to the results of ab initio Monte Carlo calculations, when available. The introduction of a phenomenological velocity dependent interaction, which accounts for backflow effects, is discussed. The spectrum of the elementary excitations of the free surface and films is studied. PACS number:67.40

Reactive Local Search for the Maximum Clique Problem1

Abstract: A new Reactive Local Search (\RLS ) algorithm is proposed for the solution of the Maximum-Clique problem. \RLS is based on local search complemented by a feedback (history-sensitive) scheme to determine the amount of diversification. The reaction acts on the single parameter that decides the temporary prohibition of selected moves in the neighborhood, in a manner inspired by Tabu Search. The performance obtained in computational tests appears to be significantly better with respect to all algorithms tested at the the second DIMACS implementation challenge. The worst-case complexity per iteration of the algorithm is O(max {n,m}) where n and m are the number of nodes and edges of the graph. In practice, when a vertex is moved, the number of operations tends to be proportional to its number of missing edges and therefore the iterations are particularly fast in dense graphs.

Microstructure and mechanical properties of Ti‐6Al‐4V produced by electron beam melting of pre‐alloyed powders

Abstract: Purpose – The purpose of this paper is the microstructural and mechanical characterization of a biomedical Ti‐6Al‐4V alloy produced by electron beam melting, and the study of the stability of the as‐built microstructure upon heat treatment.Design/methodology/approach – Ti‐6Al‐4V alloy produced by electron beam melting has been mechanically characterized through tensile and fatigue testing. Its microstructure has been investigated by optical observation after etching and by X‐ray diffractometry analysis. The stability of the microstructure of the as‐built material has been deepened carrying out suitable heat treatments, after an analysis by dilatometry test.Findings – The microstructure of a Ti‐6Al‐4V alloy produced by electron beam melting has a very fine and acicular morphology, because of the intrinsically high‐solidification rate of the process. This microstructure is very stable, and the traditional thermal treatments cannot modify it; the microstructure changes significantly only when an amount of st...

Market research for requirements analysis using linguistic tools

Abstract: Numerous studies in recent months have proposed the use of linguistic instruments to support requirements analysis. There are two main reasons for this: (i) the progress made in natural language processing and (ii) the need to provide the developers of software systems with support in the early phases of requirements definition and conceptual modelling. This paper presents the results of an online market research intended (a) to assess the economic advantages of developing a CASE (computer-aided software engineering) tool that integrates linguistic analysis techniques for documents written in natural language, and (b) to verify the existence of the potential demand for such a tool. The research included a study of the language – ranging from completely natural to highly restricted – used in documents available for requirements analysis, an important factor given that on a technological level there is a trade-off between the language used and the performance of the linguistic instruments. To determine the potential demand for such tool, some of the survey questions dealt with the adoption of development methodologies and consequently with models and support tools; other questions referred to activities deemed critical by the companies involved. Through statistical correspondence analysis of the responses, we were able to outline two “profiles” of companies that correspond to two potential market niches, which are characterised by their very different approach to software development.

Reactive Search and Intelligent Optimization

Abstract: Reactive Search integrates sub-symbolic machine learning techniques into search heuristics for solving complex optimization problems. By automatically adjusting the working parameters, a reactive search self-tunes and adapts, effectively learning by doing until a solution is found. Intelligent Optimization, a superset of Reactive Search, concerns online and off-line schemes based on the use of memory, adaptation, incremental development of models, experimental algorithms applied to optimization, intelligent tuning and design of heuristics. Reactive Search and Intelligent Optimization is an excellent introduction to the main principles of reactive search, as well as an attempt to develop some fresh intuition for the approaches. The book looks at different optimization possibilities with an emphasis on opportunities for learning and self-tuning strategies. While focusing more on methods than on problems, problems are introduced wherever they help make the discussion more concrete, or when a specific problem has been widely studied by reactive search and intelligent optimization heuristics. Individual chapters cover reacting on the neighborhood; reacting on the annealing schedule; reactive prohibitions; model-based search; reacting on the objective function; relationships between reactive search and reinforcement learning; and much more. Each chapter is structured to show basic issues and algorithms; the parameters critical for the success of the different methods discussed; and opportunities and schemes for the automated tuning of these parameters. Anyone working in decision making in business, engineering, economics or science will find a wealth of information here.