Good practices in logistics for SMEs: a strategy for the global marketplace

Thanks to globalization, the environment in which companies operate today has changed. Whereas a few decades ago, the same government generated protectionist policies, today with the opening of markets, competition is not only national but also international, so companies, regardless of their size, must make changes in their business model, aiming at the internationalization of markets both for the acquisition of materials and goods and for the marketing of their products, being more agile in responding to their customers in terms of product quality, expected delivery time and cost. It is in this scenario where logistics plays a fundamental role as a tool for competitiveness and, therefore, the following work aims to highlight the impact of logistics on SMEs and the need to aim for continuous improvement of their logistics processes. By means of a qualitative/descriptive methodology, relevant aspects are reviewed, finding as a final result essential components that SMEs must incorporate to attend a world-class market

Prediction rules in e-learning systems using genetic programming

This paper describes the use of Data Mining Techniques to improve teaching–learning processes in the linear programming course offered at the Engineering Faculty at Mumbai University, India. The proposed approach seeks to model the student’s interaction with the study material using prediction rules whose interpretation will allow to detect the weaknesses of the educational process and evaluate the quality of the study material. The proposed rule discovery method is the Evolutionary Algorithms and particularly the Grammar-Based Genetic Programming (GB-GP), which is compared to association rules and decision tree construction for discovering prediction rules

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements