Ricerc@Sapienza

We prove that for k ≪4n regular resolution requires length nΩ(k) to establish that an Erdős–Rényi graph with appropriately chosen edge density does not contain a k-clique. This lower bound is optimal up to the multiplicative constant in the exponent, and also implies unconditional nΩ(k) lower bounds on running time for several state-of-the-art algorithms for finding maximum cliques in graphs.

In official statistics, interest for data integration has been increasingly growing, due to the need of extracting information from different sources. However, the effects of these procedures on the validity of the resulting statistical analyses has been disregarded for a long time. In recent years, it has been largely recognized that linkage is not an error-free procedure and linkage errors, as false links and/or missed links, can invalidate the reliability of estimates in standard statistical models.

Data-driven approaches to problem solving and data analysis are becoming more and more important problems to consider and on which apply research ideas. In this respect, the capability to explore data, understands how algorithmic approaches work and steer them toward the desired goals make Visualization and Visual Analytics strong research fields in which to invest efforts. While this importance has been understood by several countries (e.g., USA, Germany, France) in Italy the research efforts in these fields are still disjointed. With the first edition of the ITA.WA.

Due to the advent of novel technologies and digital opportunities allowing to simplify user lives, healthcare is increasingly evolving towards digitalization. This represent a great opportunity on one side but it also exposes healthcare organizations to multiple threats (both digital and not) that may lead an attacker to compromise the security of medial processes and potentially patients' safety. Today technical cybersecurity countermeasures are used to protect the confidentiality, integrity and availability of data and information systems - especially in the healthcare domain.

Fuzz testing techniques are becoming pervasive for their ever-improving ability to generate crashing trial cases for programs. Memory safety violations however can lead to silent corruptions and errors, and a fuzzer may recognize them only in the presence of sanitization machinery. For closed-source software combining sanitization with fuzzing incurs practical obstacles that we try to tackle with an architecture-independent proposal called QASan for detecting heap memory violations.

Purpose: The purpose of this paper is to investigate additive manufacturing (AM) phenomenon extending previous research results by studying in-depth the economic sustainability of AM technology and bringing out the contextual factors that drive its superior performances in comparison with conventional manufacturing, and justify its adoption in rapid prototyping (RP) from an economic point of view. Design/methodology/approach: Data have been collected through a worldwide survey. Respondents were from 105 companies adopting the technology from 23 countries worldwide.

Mobile Cloud Computing (MCC) helps increasing performance of intensive mobile applications by offloading heavy tasks to cloud computing infrastructures. The first step in this procedure is partitioning the application into small tasks and identifying those that are better suited for offloading. The method call partitioning strategy splits the code into a set of method calls that are offloaded to remote servers. Quite often, many applications need to make use of multiple servers for parallel processing of intensive computational operations.

In 1999, the International Federation of Clinical Neurophysiology (IFCN) published “IFCN Guidelines for topographic and frequency analysis of EEGs and EPs” (Nuwer et al., 1999).

This special issue of the International Journal of Approximate Reasoning (IJAR) focuses on recent advances in soft methods in probability and statistics.The special issue is a follow-up of the 8th International Conference on Soft Methods in Probability and Statistics (SMPS2016),which took place in Rome (Italy) in September 2016 (http://www.sbai.uniroma1.it/smps2016/index.php).