Contributions to the Construction of Extensible Semantic Editors

This dissertation addresses the need for easier construction and extension of language tools. Specifically, the construction and extension of so-called semantic editors is considered, that is, editors providing semantic services for code comprehension and manipulation. Editors like these are typically found in state-of-the-art development environments, where they have been developed by hand. The list of programming languages available today is extensive and, with the lively creation of new programming languages and the evolution of old languages, it keeps growing. Many of these languages would benefit from proper tool support. Unfortunately, the development of a semantic editor can be a time-consuming and error-prone endeavor, and too large an effort for most language communities. Given the complex nature of programming, and the huge benefits of good tool support, this lack of tools is problematic. In this dissertation, an attempt is made at narrowing the gap between generative solutions and how state-of-the-art editors are constructed today. A generative alternative for construction of textual semantic editors is explored with focus on how to specify extensible semantic editor services. Specifically, this dissertation shows how semantic services can be specified using a semantic formalism called refer- ence attribute grammars (RAGs), and how these services can be made responsive enough for editing, and be provided also when the text in an editor is erroneous. Results presented in this dissertation have been found useful, both in industry and in academia, suggesting that the explored approach may help to reduce the effort of editor construction

On the role of Computational Logic in Data Science: representing, learning, reasoning, and explaining knowledge

In this thesis we discuss in what ways computational logic (CL) and data science (DS) can jointly contribute to the management of knowledge within the scope of modern and future artificial intelligence (AI), and how technically-sound software technologies can be realised along the path. An agent-oriented mindset permeates the whole discussion, by stressing pivotal role of autonomous agents in exploiting both means to reach higher degrees of intelligence. Accordingly, the goals of this thesis are manifold. First, we elicit the analogies and differences among CL and DS, hence looking for possible synergies and complementarities along 4 major knowledge-related dimensions, namely representation, acquisition (a.k.a. learning), inference (a.k.a. reasoning), and explanation. In this regard, we propose a conceptual framework through which bridges these disciplines can be described and designed. We then survey the current state of the art of AI technologies, w.r.t. their capability to support bridging CL and DS in practice. After detecting lacks and opportunities, we propose the notion of logic ecosystem as the new conceptual, architectural, and technological solution supporting the incremental integration of symbolic and sub-symbolic AI. Finally, we discuss how our notion of logic ecosys- tem can be reified into actual software technology and extended towards many DS-related directions

On the dynamic allocation of assets subject to failure and replenishment

Problems of the dynamic allocation of assets subject to both failure and replenishment are common. We consider a problem inspired by naval search, where unmanned aerial vehicles are required to search an area of ocean for targets. The vehicles will require refuelling or rearming; this is represented by the aspects of failure and replenishment. Similar models can arise from considering problems of search and rescue, environmental monitoring, or project management. We formulate several versions of the problem, initially using the framework of a Markov decision process, bearing in mind trade-offs between real-world fidelity and mathematical tractability. We first consider models where rewards are gained independently from different tasks, before moving on to consider a specific kind of dependence in the rewards. We use a variety of mathematical techniques, including restless bandits, to formulate near-optimal policies for a slew of models. We consider and investigate the various policies through comprehensive computational modelling. For the independent case, we find that a Whittle index policy is extremely close to optimal while being computationally efficient. For the dependent formulation, we create a class of policies guaranteed to contain the optimal, parameterise the space, then choose the best from a limited set of parameters, augmenting with a single step of policy improvement. We close with some thoughts about what we have learned, considerations about applying the results presented in this thesis, and a discussion of intensifications and extensions we did not have time to consider

Chaotification as a Means of Broadband Vibration Energy Harvesting with Piezoelectric Materials

Computing advances and component miniaturization in circuits coupled with stagnating battery technology have fueled growth in the development of high efficiency energy harvesters. Vibration-to-electricity energy harvesting techniques have been investigated extensively for use in sensors embedded in structures or in hard-to-reach locations like turbomachinery, surgical implants, and GPS animal trackers. Piezoelectric materials are commonly used in harvesters as they possess the ability to convert strain energy directly into electrical energy and can work concurrently as actuators for damping applications. The prototypical harvesting system places two piezoelectric patches on both sides of the location of maximum strain on a cantilever beam. While efficient around resonance, performance drops dramatically should the driving frequency drift away from the beam\u27s fundamental frequency. To date, researchers have worked to improve harvesting capability by modifying material properties, using alternative geometries, creating more efficient harvesting circuits, and inducing nonlinearities. These techniques have partially mitigated the resonance excitation dependence for vibration-based harvesting, but much work remains. In this dissertation, an induced nonlinearity destabilizes a central equilibrium point, resulting in a bistable potential function governing the cantilever beam system. Depending on the environment, multiple stable solutions are possible and can coexist. Typically, researchers neglect chaos and assume that with enough energy in the ambient environment, large displacement trajectories can exist uniquely. When subjected to disturbances a system can fall to coexistent lower energy solutions including aperiodic, chaotic oscillations. Treating chaotic motion as a desirable behavior of the system allows frequency content away from resonance to produce motion about a theoretically infinite number of unstable periodic orbits that can be stabilized through control. The extreme sensitivity to initial conditions exhibited by chaotic systems paired with a pole placement control strategy pioneered by Ott, Grebogi, and Yorke permits small perturbations to an accessible system parameter to alter the system response dramatically. Periodic perturbation of the system trajectories in the vicinity of isolated unstable orbit points can therefore stabilize low-energy chaotic oscillations onto larger trajectory orbits more suitable for energy harvesting. The periodic perturbation-based control method rids the need of a system model. It only requires discrete displacement, velocity, or voltage time series data of the chaotic system driven by harmonic excitation. While the analysis techniques are not fundamentally limited to harmonic excitation, this condition permits the use of standard discrete mapping techniques to isolate periodic orbits of interest. Local linear model fits characterize the orbit and admit the necessary control perturbation calculations from the time series data. This work discusses the feasibility of such a method for vibration energy harvesting, displays stable solutions under various control algorithms, and implements a hybrid bench-top experiment using MATLAB and LabVIEW FPGA. In conclusion, this work discusses the limitations for wide-scale use and addresses areas of further work; both with respect to chaotic energy harvesting and parallel advances required within the field as a whole

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen