@conference {liciotti2015human,
	title = {Human activity analysis for in-home fall risk assessment},
	booktitle = {Communication Workshop (ICCW), 2015 IEEE International Conference on},
	year = {2015},
	pages = {284{\textendash}289},
	publisher = {IEEE},
	organization = {IEEE},
	author = {Daniele Liciotti and Gionata Massi and Emanuele Frontoni and Adriano Mancini and Primo Zingaretti}
}
@conference {Massi2014,
	title = {A real-time reliability and durability testing framework},
	booktitle = {MESA 2014 - 10th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications, Conference Proceedings},
	year = {2014},
	note = {cited By 0},
	abstract = {This paper presents a methodological framework for designing testing and measurement systems fully integrated with the enterprise information system. In comparison with the most common solutions for designing embedded testing platforms the proposed framework sets itself at a higher level of abstraction. The proposed framework allows getting different, programmable test benches that can run in parallel, and it does not restrict the choice of hardware, sensors and actuators, as it happens with commercial development systems for the same kind of machines. The framework is conceived to be used on embedded boards equipped with the GNU/Linux operating system and with at least one network interface. By using open data formats, the framework provides an easy way to exchange data with enterprise information systems, thus assuring interoperability with different IT solutions. The paper includes the description of a cooker hood testing system designed and implemented with this framework, and which highlights the advantages of the proposed development method.},
	doi = {10.1109/MESA.2014.6935592},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84911979615\&partnerID=40\&md5=9e44e4e4151cf14b313983a811b7c3f1},
	author = {Gionata Massi and Morganti, G. and Claudi, A. and Primo Zingaretti}
}
@article {De Giovanni2013682,
	title = {An adaptive genetic algorithm for large-size open stack problems},
	journal = {International Journal of Production Research},
	volume = {51},
	number = {3},
	year = {2013},
	note = {cited By 4},
	pages = {682-697},
	abstract = {The problem of minimising the maximum number of open stacks arises in many contexts (production planning, cutting environments, very-large-scale- integration circuit design, etc.) and consists of finding a sequence of tasks (products, cutting patterns, circuit gates, etc.) that determines an efficient utilisation of resources (stacks). We propose a genetic approach that combines classical genetic operators (selection, order crossover and pairwise interchange mutation) with an adaptive search strategy, where intensification and diversification phases are obtained by neighbourhood search and by a composite and dynamic fitness function that suitably modifies the search landscape. Computational tests on random and real-world benchmarks show that the proposed approach is competitive with the state of the art for large-size problems, providing better results for some classes of instances. {\textcopyright} 2013 Taylor \& Francis Group, LLC.},
	doi = {10.1080/00207543.2012.657256},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84871203028\&partnerID=40\&md5=348f92aa3ac3bf64ecb1f5b6d04a2ae1},
	author = {De Giovanni, L. and Gionata Massi and F. Pezzella}
}
@article {De Giovanni2013627,
	title = {A heuristic and an exact method for the gate matrix connection cost minimization problem},
	journal = {International Transactions in Operational Research},
	volume = {20},
	number = {5},
	year = {2013},
	note = {cited By 1},
	pages = {627-643},
	abstract = {In many applications, a sequencing of patterns (electronic circuit nodes, cutting patterns, product orders, etc.) has to be found in order to optimize some given objective function, giving rise to the so-called open stack problems. We focus on a problem related to the optimization of gate matrix layouts: electronic circuits are obtained by connecting gates and one seeks a gate layout permutation that minimizes connection costs under restrictions on the circuit area. In the literature, the connection costs and circuit area are also known as time of open stacks and maximum number of open stacks, respectively. We propose a genetic algorithm providing heuristic solutions and a branch-and-cut algorithm based on a new linear integer programming formulation that represents, to the best of our knowledge, the first exact method proposed in the literature. The algorithms have been tested on real instances and on data sets from the literature. The computational results give evidence that the proposed methods provide solutions that improve the ones found by the approaches presented in the literature. {\textcopyright} 2013 International Federation of Operational Research Societies.},
	doi = {10.1111/itor.12025},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84881022755\&partnerID=40\&md5=243ec854395721c11c14eec4036e7a7b},
	author = {De Giovanni, L. and Gionata Massi and F. Pezzella and Pfetsch, M.E. and Rinaldi, G. and Ventura, P.d}
}
