Boundary layer control for airships

An investigation is summarized of the aerodynamic principle of boundary layer control for nonrigid LTA craft. The project included a wind tunnel test on a BLC body of revolution at zero angle of attack. Theoretical analysis is shown to be in excellent agreement with the test data. Methods are evolved for predicting the boundary layer development on a body of revolution and the suction pumping and propulsive power requirements. These methods are used to predict the performance characteristics of a full-scale airship. The analysis indicates that propulsive power reductions of 15 to 25 percent and endurance improvements of 20 to 40 percent may be realized in employing boundary-layer control to nonrigid airships

INTEGRATING ONTOLOGY AND COGNITIVE LINGUISTICS FOR NATURAL LANGUAGE PRODUCTION AND UNDERSTANDING

Ontologies have been designed to capture the semantic knowledge of a domain in a machine understandable form. Current standards for managing ontologies like OWL are lacking in linguistic grounding, and are not able to achieve a clear link with natural language. Bridging this gap, unskilled users could be able to infer the information described in the ontology and it would be possible either producing or parsing utterances about the represented domain automatically. Moreover, as in the case of enterprises, it could be very useful to extract information from external documental corpora that are related to the same domain. Many attempts have been made with the aim to create a natural language interface to ontology but very few of them use grammars during interaction; such interfaces are focused only on verbalizing information contained in the ontology, while it is often necessary to give exhaustive answers to the users\u2019s queries by retrieving data outside of the knowledge base. The work presented in this thesis has been inspired by theories in the field of Cognitive Linguistics, and in particular by the Construction Grammar, to create a grammar-based tool for ontology verbalization that combines OWL ontologies with Fluid Construction Grammar (FCG). Currently, FCG is the only computational implementation of Construction Grammar that performs both production, and parsing using the same set of constructions. The main idea is to compute both lexical and grammatical constructions (the meaning-form couples) in the FCG from the ontology. To achieve this goal, a suitable set of rules based on linguistic typology have been defined to infer semantics and syntax from the RDF triples inside the OWL structure, while combining them as the poles of constructions in the FCG. To allow verbalization from external documents related to the ontology, synonymous constructions have been defined, which are matched to free text. Computing all possible syntactic forms for the same meaning was achieved using linguistic rules. The information retrieval procedure outlined above allows semantic annotation of the text as a side effect. A system for automatic generation of contents for Semantic MediaWiki from standard Wikipedia pages has been implemented in this respect. The combination of OWL with FCG and the integration of external documents in the ontology are the core of the system whose theoretical background, modeling, design, and evaluation with respect to other contributes in this research field form the main subjects of this thesis

A cognitive architecture for inner speech

A cognitive architecture for inner speech is presented. It is based on the Standard Model of Mind, integrated with modules for self- talking. Briefly, the working memory of the proposed architecture includes the phonological loop as a component which manages the exchanging information between the phonological store and the articulatory control system. The inner dialogue is modeled as a loop where the phonological store hears the inner voice produced by the hidden articulator process. A central executive module drives the whole system, and contributes to the generation of conscious thoughts by retrieving information from long-term memory. The surface form of thoughts thus emerges by the phonological loop. Once a conscious thought is elicited by inner speech, the perception of new context takes place and then repeating the cognitive loop. A preliminary formalization of some of the described processes by event cal- culus, and early results of their implementation on the humanoid robot Pepper by SoftBank Robotics are discussed

A calculus for robot inner speech and self-awareness

The inner speech is the common mental experience the humans have when they dialogue with themselves. It is widely acknowledged that inner speech is related to awareness and self-awareness. The inner speech reproduces and expands in the mind social and physical sources of awareness. In this preliminary work, a calculus based on a first-order modal logic to automate inner speech is presented. It attempts to make the existing inner speech theories suitable for robot. By making robot able to talk to itself, it is possible to analyze the role of inner speech in robot awareness and self-awareness, opening new interesting research scenarios not yet investigated

Developing Self-Awareness in Robots via Inner Speech

The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is outlined in a simplified setup

Robots as intelligent assistants to face COVID-19 pandemic

Motivation: The epidemic at the beginning of this year, due to a new virus in the coronavirus family, is causing many deaths and is bringing the world economy to its knees. Moreover, situations of this kind are historically cyclical. The symptoms and treatment of infected patients are, for better or worse even for new viruses, always the same: More or less severe flu symptoms, isolation and full hygiene. By now man has learned how to manage epidemic situations, but deaths and negative effects continue to occur. What about technology? What effect has the actual technological progress we have achieved? In this review, we wonder about the role of robotics in the fight against COVID. It presents the analysis of scientific articles, industrial initiatives and project calls for applications from March to now highlighting how much robotics was ready to face this situation, what is expected from robots and what remains to do. Results: The analysis was made by focusing on what research groups offer as a means of support for therapies and prevention actions. We then reported some remarks on what we think is the state of maturity of robotics in dealing with situations like COVID-19

Robot’s Inner Speech Effects on Human Trust and Anthropomorphism

Inner Speech is an essential but also elusive human psychological process that refers to an everyday covert internal conversation with oneself. We argued that programming a robot with an overt self-talk system that simulates human inner speech could enhance both human trust and users’ perception of robot’s anthropomorphism, animacy, likeability, intelligence and safety. For this reason, we planned a pre-test/post-test control group design. Participants were divided in two different groups, one experimental group and one control group. Participants in the experimental group interacted with the robot Pepper equipped with an over inner speech system whereas participants in the control group interacted with the robot that produces only outer speech. Before and after the interaction, both groups of participants were requested to complete some questionnaires about inner speech and trust. Results showed differences between participants’ pretest and post-test assessment responses, suggesting that the robot’s inner speech influences in participants of experimental group the perceptions of animacy and intelligence in robot. Implications for these results are discussed

Hybrid Propulsion Efficiency Increment through Exhaust Energy Recovery—Part 1: Radial Turbine Modelling and Design

The efficiency of Hybrid Electric Vehicles (HEVs) may be substantially increased if the energy of the exhaust gases, which do not complete the expansion inside the cylinder of the internal combustion engine, is efficiently recovered by means of a properly designed turbogenerator and employed for vehicle propulsion; previous studies, carried out by the same authors of this work, showed a potential hybrid vehicle fuel efficiency increment up to 15% by employing a 20 kW turbine on a 100 HP rated power thermal unit. The innovative thermal unit here proposed is composed of a supercharged engine endowed with a properly designed turbogenerator, which comprises two fundamental elements: an exhaust gas turbine expressly designed and optimized for the application, and a suitable electric generator necessary to convert the recovered energy into electric energy, which can be stored in the on-board energy storage system of the vehicle. In these two parts, the realistic efficiency of the innovative thermal unit for hybrid vehicle is evaluated and compared to a traditional turbocharged engine. In Part 1, the authors present a model for the prediction of the efficiency of a dedicated radial turbine, based on a simple but effective mean-line approach; the same paper also reports a design algorithm, which, owing to some assumptions and approximations, allows a fast determination of the proper turbine geometry for a given design operating condition. It is worth pointing out that, being optimized for quasi-steady power production, the exhaust gas turbine considered is quite different from the ones commonly employed for turbocharging application; for this reason, and in consideration of the required power size, such a turbine is not available on the market, nor has its development been previously carried out in the scientific literature. In the Part 2 paper, a radial turbine geometry is defined for the thermal unit previously calculated, employing the design algorithm described in Part 1; the realistic energetic advantage that could be achieved by the implementation of the turbogenerator on a hybrid propulsion system is evaluated through the performance prediction model under the different operating conditions of the thermal unit. As an overall result, it was estimated that, compared to a reference traditional turbocharged engine, the turbocompound system could gain vehicle efficiency improvement between 3.1% and 17.9%, depending on the output power level, while an average efficiency increment of 10.9% was determined for the whole operating range

Hybrid Propulsion Efficiency Increment through Exhaust Energy Recovery—Part 2: Numerical Simulation Results

The efficiency of hybrid electric vehicles may be substantially increased if the energy of exhaust gases, which do not complete the expansion inside the cylinder of the internal combustion engine, is efficiently recovered using a properly designed turbo-generator and employed for vehicle propulsion. Previous studies, carried out by the same authors of this work, showed a potential hybrid vehicle fuel efficiency increment up to 15% employing a 20 kW turbine on a 100 HP-rated power thermal unit. The innovative thermal unit proposed here is composed of a supercharged engine endowed with a properly designed turbo-generator, which comprises two fundamental elements: an exhaust gas turbine expressly designed and optimized for the application, and a suitable electric generator necessary to convert the recovered energy into electric energy, which can be stored in the on-board energy storage system of the vehicle. In this two-part work, the realistic efficiency of the innovative thermal unit for hybrid vehicles is evaluated and compared to a traditional turbocharged engine. In Part 1, the authors presented a model for the prediction of the efficiency of a dedicated radial turbine, based on a simple but effective mean-line approach; the same paper also reports a design algorithm, which, thanks to some assumptions and approximations, allows fast determination of the right turbine geometry for a given design operating condition. It is worth pointing out that, being optimized for quasi-steady power production, the exhaust gas turbine here considered is quite different from the ones commonly employed for turbocharging applications; for this reason, and in consideration of the required power size, such a turbine is not available on the market, nor has its development been previously carried out in the scientific literature. In this paper, Part 2, a radial turbine geometry is defined for the thermal unit previously calculated, employing the design algorithm described in Part 1; the realistic energetic advantages that could be achieved by the implementation of the turbo-generator on a hybrid propulsion system are evaluated through the performance prediction model under different operating conditions of the thermal unit. As an overall result, it was estimated that, compared to a reference traditional turbocharged engine, the turbo-compound system could gain vehicle efficiency improvement between 3.1% and 17.9%, according to the output power delivered, with an average efficiency increment of 10.9% evaluated on the whole operating range

A Review of Selected Applications of GNSS CORS and Related Experiences at the University of Palermo (Italy)

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years