Efficient Bayesian Inference for Learning in the Ising Linear Perceptron and Signal Detection in CDMA

Efficient new Bayesian inference technique is employed for studying critical properties of the Ising linear perceptron and for signal detection in Code Division Multiple Access (CDMA). The approach is based on a recently introduced message passing technique for densely connected systems. Here we study both critical and non-critical regimes. Results obtained in the non-critical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first order transition line that ends in a continuous phase transition point. Finite size effects are also studied.Comment: 11 pages, 3 figure

ICT-based innovation and its competitive outcome: the role of information intensity

Purpose Prior research highlights the vital role of Information and Communication Technologies (ICT) for innovation in response to environmental conditions. However, there is a lack of studies that analyse the determinants of ICT investments on the innovation activities of firms in relation with their impacts on the industrial and competitive dynamics using large data sets. The paper aims to discuss these issues. Design/methodology/approach In this paper, the authors investigate the effects of ICT investments on the industrial and competitive dynamics for a large and representative panel data set. All the industries are included, and lagged effects of ICT investments are studied. The model is tested on a seven-year panel (2008–2014) of 231 Italian industries using two-stage least squares instrumental-variables estimators with industry time and fixed effects. Findings The results indicate that munificent industries and higher ICT spending are interrelated facts, showing that in sectors with more growth opportunities firms invest more in ICT and this leads to higher industry concentration, greater profit dispersion and higher competitive turbulence in the sector. Also, the paper shows that SMEs can rarely take advantage of their ICT-based innovation to start high-growth phenomena. Practical implications The results suggest that ICT-based innovation may create competitive advantages that are hard to sustain over the long-term raising important implications for managers involved in ICT-enabled innovations and policy-makers involved in building programs to foster innovation. Originality/value Against the backdrop of today’s digital transformation, the paper enriches our understanding on the disruptive effects exerted by the digitalization of the innovation process and provides a base to continue the investigation of industrial changes and competitive dynamics

The impact of IT–business strategic alignment on firm performance: The evolving role of IT in industries

This study proposes and validates a new industry taxonomy to understand the use of IT that generates superior economic returns based on the specific economic and competitive characteristics of four different industry types and the strategic role of IT in each of these industry environments. Our findings extend the well-established industry taxonomy on the strategic role of IT (Automate, Informate, Transform) by considering how IT is changing the nature of the product/service in industries where transformational logics prevail. We found that in industries where the product/service is digital in nature, the firms that achieve higher economic returns are those where IT is used to support dual strategies based on the integration of cost leadership and differentiation. Conversely, in other industries - with the exception of those producing commodities - the firms that achieve superior returns are those that use IT to support differentiation. The results of this study can help managers make intelligent decisions about competitive strategies and IT investments, depending on the business environment of the sector in which the firm operates and the generative potential of emerging technologies to do new things

Phase changes in 38 atom Lennard-Jones clusters. II: A parallel tempering study of equilibrium and dynamic properties in the molecular dynamics and microcanonical

We study the 38-atom Lennard-Jones cluster with parallel tempering Monte Carlo methods in the microcanonical and molecular dynamics ensembles. A new Monte Carlo algorithm is presented that samples rigorously the molecular dynamics ensemble for a system at constant total energy, linear and angular momenta. By combining the parallel tempering technique with molecular dynamics methods, we develop a hybrid method to overcome quasi-ergodicity and to extract both equilibrium and dynamical properties from Monte Carlo and molecular dynamics simulations. Several thermodynamic, structural and dynamical properties are investigated for LJ$_{38}$, including the caloric curve, the diffusion constant and the largest Lyapunov exponent. The importance of insuring ergodicity in molecular dynamics simulations is illustrated by comparing the results of ergodic simulations with earlier molecular dynamics simulations.Comment: Journal of Chemical Physics, accepte

Genetic algorithms for discovery of matrix multiplication methods

We present a parallel genetic algorithm for nding matrix multiplication algo-rithms. For 3 x 3 matrices our genetic algorithm successfully discovered algo-rithms requiring 23 multiplications, which are equivalent to the currently best known human-developed algorithms. We also studied the cases with less mul-tiplications and evaluated the suitability of the methods discovered. Although our evolutionary method did not reach the theoretical lower bound it led to an approximate solution for 22 multiplications