Università degli Studi eCampus

About: Università degli Studi eCampus is a education organization based out in Novedrate, Italy. It is known for research contribution in the topics: Anxiety & Planck. The organization has 124 authors who have published 538 publications receiving 21483 citations. The organization is also known as: Universita degli Studi eCampus.

Overview on the application of ISO/TS 16949:2009, in a worldwide leader company in the production of stainless steel tubes for automotive exhaust systems

Abstract: This paper presents an overview on the quality approach of a company that is at the leading edge in the sector of stainless steel-based products and represents an example of best practice in pursuing a continual improvement and the customer satisfaction. In this study, the attention has been focused on the application of the technical specification ISO 16949:2009 in accordance with the ISO 9000:2008, for the quality control of stainless steel tubes produced for automotive applications in one of the company plant devoted to the realisation of welded tubes for mufflers and exhaust pipes. The case study examined demonstrates how the effective adoption of the standards can help in reaching the highest level of performances in the production process, giving high-quality products and consolidating the company position on the market.

MQTT-Auth: a Token-based Solution to Endow MQTT with Authentication and Authorization Capabilities

Abstract: Security in the Internet of Things is a current hot topic and it may comprise different aspects such as confidentiality and integrity of personal data, as well as the authentication and the authorization to access smart objects that are spreading more and more in our every-day lives. In this work we focus on MQTT (Message Queue Telemetry Transport), a message-based communication protocol explicitly designed for low-power machine-to-machine communications and based on the publish-subscribe paradigm. First of all, we provide an accurate analysis of some of the most recent security solutions and improvements of MQTT found in the literature. Secondly, we describe in detail a novel secure solution, called MQTT-Auth, to protect specific topics in MQTT. This solution is based on the AugPAKE security algorithm for guaranteeing confidentiality, and onto two tokens which permit to authenticate the usage of a topic and to guarantee authorization in accessing a topic respectively. MQTT-Auth can also be easily extended to a hierarchical structure of topics and entities. Finally, we compare MQTT-Auth with some solutions for securing MQTT being present in the relevant literature, and we provide some details on how MQTT-Auth has been implemented and successfully tested.

A MapReduce-based fuzzy associative classifier for big data

Abstract: In this paper, we propose an efficient distributed fuzzy associative classification model based on the MapReduce paradigm. The learning algorithm first mines a set of fuzzy association classification rules by employing a distributed version of a fuzzy extension of the well-known FP-Growth algorithm. Then, it prunes this set by using three purposely adapted types of pruning. We implemented the distributed fuzzy associative classifier using the Hadoop framework. We show the scalability of our approach by carrying out a number of experiments on a real-world big dataset. In particular, we evaluate the achievable speedup on a small computer cluster, highlighting that the proposed approach allows handling big datasets even with modest hardware support.

Acquisition, Processing and Evaluation of Down Hole Data for Monitoring Efficiency of Drilling Processes

Abstract: This paper presents a study carried out in collaboration with a company leader in the production of drilling tools and sensors. Data were gathered during a period of four months in two horizontal well of an oil field with the aim of assessing the relationship between Mechanical Specific Energy (MSE) and drilling efficiency trough the analysis of the most significant drilling parameters. There are several models and measurement systems available for measuring such parameters, however in many practical cases the possible maximum performances are not achieved and this suggests the idea that there is still room, from a research point of view, to increase acquisition accuracy and their correct evaluation. In this study, down hole data were acquired to calculate significant parameters for assessing drilling performances which can contribute to the avoidance of errors in torque calculation due to the effect of drill string friction and the consequent distortion of MSE curve. Moreover, the same data implemented in a model for Rate of Penetration (ROP) calculation and a map correlating RPM and Weight on Bit (WOB) values with Rate of Penetration was drawn.