Frame-driven Extraction of Linked Data and Ontologies from Text

Ontology design and population -core aspects of semantic technologies- re- cently have become fields of great interest due to the increasing need of domain-specific knowledge bases that can boost the use of Semantic Web. For building such knowledge resources, the state of the art tools for ontology design require a lot of human work. Producing meaningful schemas and populating them with domain-specific data is in fact a very difficult and time-consuming task. Even more if the task consists in modelling knowledge at a web scale. The primary aim of this work is to investigate a novel and flexible method- ology for automatically learning ontology from textual data, lightening the human workload required for conceptualizing domain-specific knowledge and populating an extracted schema with real data, speeding up the whole ontology production process. Here computational linguistics plays a fundamental role, from automati- cally identifying facts from natural language and extracting frame of relations among recognized entities, to producing linked data with which extending existing knowledge bases or creating new ones. In the state of the art, automatic ontology learning systems are mainly based on plain-pipelined linguistics classifiers performing tasks such as Named Entity recognition, Entity resolution, Taxonomy and Relation extraction [11]. These approaches present some weaknesses, specially in capturing struc- tures through which the meaning of complex concepts is expressed [24]. Humans, in fact, tend to organize knowledge in well-defined patterns, which include participant entities and meaningful relations linking entities with each other. In literature, these structures have been called Semantic Frames by Fill- 6 Introduction more [20], or more recently as Knowledge Patterns [23]. Some NLP studies has recently shown the possibility of performing more accurate deep parsing with the ability of logically understanding the structure of discourse [7]. In this work, some of these technologies have been investigated and em- ployed to produce accurate ontology schemas. The long-term goal is to collect large amounts of semantically structured information from the web of crowds, through an automated process, in order to identify and investigate the cognitive patterns used by human to organize their knowledge.

Structural verification of the ESEO spacecraft: from launch loads analysis to composite panels verification

The present thesis work was performed in the frame of ESEO (European Student Earth Orbiter) project. The activities that are described in this document were carried out in the Microsatellites and Space Micro systems Lab led by Professor Paolo Tortora and in ALMASpace company facilities. The thesis deals with ESEO structural analysis, at system and unit level, and verification: after determining the design limit loads to be applied to the spacecraft as an envelope of different launchers load profiles, a finite element structural analysis was performed on the model of the satellite in order to ensure the capability to withstand the loads encountered during the launch; all the analyses were performed according to ESA standards and using the software MSC NASTRAN SIMXPERT. Amplification factors were derived and used to determine loads to be considered at unit level. In particular structural analyses were carried out on the GPS unit, the payload developed for ESEO by students of University of Bologna and results were used in the preparation of GPS payload design definition file. As for the verification phase a study on the panels and inserts to be used in the spacecraft was performed: different designs were created exploiting methods to optimize weight and mechanical behavior. The configurations have been analyzed and results compared to select the final design.

Structural failures due to lack of bracing

The goal of the research is to provide an overview of those factors that play a major role in structural failures and also to focus on the importance that bracing has in construction accidents. A temporary bracing system is important to construction safety, yet it is often neglected. Structural collapses often occur due to the insufficient support of loads that are applied at the time of failure. The structural load is usually analyzed by conceiving the whole structure as a completed entity, and there is frequently a lack of design or proper implementation of systems that can provide stability during construction. Often, the specific provisions and requirements of temporary bracing systems are left to the workers on the job site that may not have the qualifications or expertise for proper execution. To effectively see if bracing design should get more attention in codes and standards, failures which could have been avoided with the presence and/or the correct design of a bracing system were searched and selected among a variety of cases existing in the engineering literature. Eleven major cases were found, which span in a time frame of almost 70 years, clearly showing that the topic should get more attention. The case studies are presented in chronological order and in a systematic way. The failed structure is described in its design components and the sequence of failure is reconstructed. Then, the causes and failure mechanism are presented. Advice on how to avoid similar failures from happening again and hypothetic solutions which could have prevented the collapses are identified. The findings shows that insufficient or nonexistent bracing mainly results from human negligence or miscalculation of the load analysis and show that time has come to fully acknowledge that temporary structures should be more accounted for in design and not left to contractors' means and methods of construction.