Engineering Agent-Oriented Technologies and Programming Languages for Computer Programming and Software Development

Mainstream hardware is becoming parallel, heterogeneous, and distributed on every desk, every home and in every pocket. As a consequence, in the last years software is having an epochal turn toward concurrency, distribution, interaction which is pushed by the evolution of hardware architectures and the growing of network availability. This calls for introducing further abstraction layers on top of those provided by classical mainstream programming paradigms, to tackle more effectively the new complexities that developers have to face in everyday programming. A convergence it is recognizable in the mainstream toward the adoption of the actor paradigm as a mean to unite object-oriented programming and concurrency. Nevertheless, we argue that the actor paradigm can only be considered a good starting point to provide a more comprehensive response to such a fundamental and radical change in software development. Accordingly, the main objective of this thesis is to propose Agent-Oriented Programming (AOP) as a high-level general purpose programming paradigm, natural evolution of actors and objects, introducing a further level of human-inspired concepts for programming software systems, meant to simplify the design and programming of concurrent, distributed, reactive/interactive programs. To this end, in the dissertation first we construct the required background by studying the state-of-the-art of both actor-oriented and agent-oriented programming, and then we focus on the engineering of integrated programming technologies for developing agent-based systems in their classical application domains: artificial intelligence and distributed artificial intelligence. Then, we shift the perspective moving from the development of intelligent software systems, toward general purpose software development. Using the expertise maturated during the phase of background construction, we introduce a general-purpose programming language named simpAL, which founds its roots on general principles and practices of software development, and at the same time provides an agent-oriented level of abstraction for the engineering of general purpose software systems.

Certificates for Incremental Type Checking

The central topic of this thesis is the study of algorithms for type checking, both from the programming language and from the proof-theoretic point of view. A type checking algorithm takes a program or a proof, represented as a syntactical object, and checks its validity with respect to a specification or a statement. It is a central piece of compilers and proof assistants. We postulate that since type checkers are at the interface between proof theory and program theory, their study can let these two fields mutually enrich each other. We argue by two main instances: first, starting from the problem of proof reuse, we develop an incremental type checker; secondly, starting from a type checking program, we evidence a novel correspondence between natural deduction and the sequent calculus.

Model reduction techniques in flexible multibody dynamics with application to engine cranktrain simulation

The development of a multibody model of a motorbike engine cranktrain is presented in this work, with an emphasis on flexible component model reduction. A modelling methodology based upon the adoption of non-ideal joints at interface locations, and the inclusion of component flexibility, is developed: both are necessary tasks if one wants to capture dynamic effects which arise in lightweight, high-speed applications. With regard to the first topic, both a ball bearing model and a journal bearing model are implemented, in order to properly capture the dynamic effects of the main connections in the system: angular contact ball bearings are modelled according to a five-DOF nonlinear scheme in order to grasp the crankshaft main bearings behaviour, while an impedance-based hydrodynamic bearing model is implemented providing an enhanced operation prediction at the conrod big end locations. Concerning the second matter, flexible models of the crankshaft and the connecting rod are produced. The well-established Craig-Bampton reduction technique is adopted as a general framework to obtain reduced model representations which are suitable for the subsequent multibody analyses. A particular component mode selection procedure is implemented, based on the concept of Effective Interface Mass, allowing an assessment of the accuracy of the reduced models prior to the nonlinear simulation phase. In addition, a procedure to alleviate the effects of modal truncation, based on the Modal Truncation Augmentation approach, is developed. In order to assess the performances of the proposed modal reduction schemes, numerical tests are performed onto the crankshaft and the conrod models in both frequency and modal domains. A multibody model of the cranktrain is eventually assembled and simulated using a commercial software. Numerical results are presented, demonstrating the effectiveness of the implemented flexible model reduction techniques. The advantages over the conventional frequency-based truncation approach are discussed.

A farm-level programming model to compare the atmospheric impact of conventional and organic farming

A model is developed to represent the activity of a farm using the method of linear programming. Two are the main components of the model, the balance of soil fertility and the livestock nutrition. According to the first, the farm is supposed to have a total requirement of nitrogen, which is to be accomplished either through internal sources (manure) or through external sources (fertilisers). The second component describes the animal husbandry as having a nutritional requirement which must be satisfied through the internal production of arable crops or the acquisition of feed from the market. The farmer is supposed to maximise total net income from the agricultural and the zoo-technical activities by choosing one rotation among those available for climate and acclivity. The perspective of the analysis is one of a short period: the structure of the farm is supposed to be fixed without possibility to change the allocation of permanent crops and the amount of animal husbandry. The model is integrated with an environmental module that describes the role of the farm within the carbon-nitrogen cycle. On the one hand the farm allows storing carbon through the photosynthesis of the plants and the accumulation of carbon in the soil; on the other some activities of the farm emit greenhouse gases into the atmosphere. The model is tested for some representative farms of the Emilia-Romagna region, showing to be capable to give different results for conventional and organic farming and providing first results concerning the different atmospheric impact. Relevant data about the representative farms and the feasible rotations are extracted from the FADN database, with an integration of the coefficients from the literature.

Mental states monitoring through passive Brain-Computer Interface systems

The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

Portfolio Approaches in Constraint Programming

Recent research has shown that the performance of a single, arbitrarily efficient algorithm can be significantly outperformed by using a portfolio of —possibly on-average slower— algorithms. Within the Constraint Programming (CP) context, a portfolio solver can be seen as a particular constraint solver that exploits the synergy between the constituent solvers of its portfolio for predicting which is (or which are) the best solver(s) to run for solving a new, unseen instance. In this thesis we examine the benefits of portfolio solvers in CP. Despite portfolio approaches have been extensively studied for Boolean Satisfiability (SAT) problems, in the more general CP field these techniques have been only marginally studied and used. We conducted this work through the investigation, the analysis and the construction of several portfolio approaches for solving both satisfaction and optimization problems. We focused in particular on sequential approaches, i.e., single-threaded portfolio solvers always running on the same core. We started from a first empirical evaluation on portfolio approaches for solving Constraint Satisfaction Problems (CSPs), and then we improved on it by introducing new data, solvers, features, algorithms, and tools. Afterwards, we addressed the more general Constraint Optimization Problems (COPs) by implementing and testing a number of models for dealing with COP portfolio solvers. Finally, we have come full circle by developing sunny-cp: a sequential CP portfolio solver that turned out to be competitive also in the MiniZinc Challenge, the reference competition for CP solvers.

Bone-implant interface. Evaluation of osteoblastic cells behavior on nanopatterned titanium surfaces: an in vitro analysis

Protein-adsorption occurs immediately following implantation of biomaterials. It is unknown at which extent protein-adsorption impacts the cellular events at bone-implant interface. To investigate this question, we compared the in-vitro outcome of osteoblastic cells grown onto titanium substrates and glass as control, by modulating the exposure to serum-derived proteins. Substrates consisted of 1) polished titanium disks; 2) polished disks nanotextured with H2SO4/H2O2; 3) glass. In the pre-adsorption phase, substrates were treated for 1h with αMEM alone (M-noFBS) or supplemented with 10%-foetal-bovine-serum (M-FBS). MC3T3-osteoblastic-cells were cultured on the pre-treated substrates for 3h and 24h, in M-noFBS and M-FBS. Subsequently, the culture medium was replaced with M-FBS and cultures maintained for 3 and 7days. Cell-number was evaluated by: Alamar-Blue and MTT assay. Mitotic- and osteogenic-activities were evaluated through fluorescence-optical-microscope by immunolabeling for Ki-67 nuclear-protein and Osteopontin. Cellular morphology was evaluated by SEM-imaging. Data were statistically analyzed using ANOVA-test, (p<0.05). At day3 and day7, the presence or absence of serum-derived proteins during the pre-adsorption phase had not significant effect on cell-number. Only the absence of FBS during 24h of culture significantly affected cell-number (p<0.0001). Titanium surfaces performed better than glass, (p<0.01). The growth rate of cells between day3 and 7 was not affected by the initial absence of FBS. Immunolabeling for Ki-67 and Osteopontin showed that the mitotic- and osteogenic- activity were ongoing at 72h. SEM-analysis revealed that the absence of FBS had no major influence on cell-shape. • Physico-chemical interactions without mediation by proteins are sufficient to sustain the initial phase of culture and guide osteogenic-cells toward differentiation. • The challenge is avoiding adsorption of ‘undesirables’ molecules that negatively impact on the cueing cells receive from surface. This may not be a problem in healthy patients, but may have an important role in medically-compromised-individuals in whom the composition of tissue-fluids is altered.

Constraint Programming-based Job Dispatching for Modern HPC Applications

A High-Performance Computing job dispatcher is a critical software that assigns the finite computing resources to submitted jobs. This resource assignment over time is known as the on-line job dispatching problem in HPC systems. The fact the problem is on-line means that solutions must be computed in real-time, and their required time cannot exceed some threshold to do not affect the normal system functioning. In addition, a job dispatcher must deal with a lot of uncertainty: submission times, the number of requested resources, and duration of jobs. Heuristic-based techniques have been broadly used in HPC systems, at the cost of achieving (sub-)optimal solutions in a short time. However, the scheduling and resource allocation components are separated, thus generates a decoupled decision that may cause a performance loss. Optimization-based techniques are less used for this problem, although they can significantly improve the performance of HPC systems at the expense of higher computation time. Nowadays, HPC systems are being used for modern applications, such as big data analytics and predictive model building, that employ, in general, many short jobs. However, this information is unknown at dispatching time, and job dispatchers need to process large numbers of them quickly while ensuring high Quality-of-Service (QoS) levels. Constraint Programming (CP) has been shown to be an effective approach to tackle job dispatching problems. However, state-of-the-art CP-based job dispatchers are unable to satisfy the challenges of on-line dispatching, such as generate dispatching decisions in a brief period and integrate current and past information of the housing system. Given the previous reasons, we propose CP-based dispatchers that are more suitable for HPC systems running modern applications, generating on-line dispatching decisions in a proper time and are able to make effective use of job duration predictions to improve QoS levels, especially for workloads dominated by short jobs.

Design, development, and analysis of hybrid metal-composite tube for industrial application

In the aerospace, automotive, printing, and sports industries, the development of hybrid Carbon Fiber Reinforced Polymer (CFRP)-metal components is becoming increasingly important. The coupling of metal with CFRP in axial symmetric components results in reduced production costs and increased mechanical properties such as bending, torsional stiffness, mass reduction, damping, and critical speed compared to the single material-built ones. In this thesis, thanks to a novel methodology involving a rubbery/viscoelastic interface layer, several hybrid aluminum-CFRP prototype tubes were produced. Besides, an innovative system for the cure of the CFRP part has been studied, analyzed, tested, and developed in the company that financed these research activities (Reglass SRL, Minerbio BO, Italy). The residual thermal stresses and strains have been investigated with numerical models based on the Finite Element Method (FEM) and compared with experimental tests. Thanks to numerical models, it was also possible to reduce residual thermal stresses by optimizing the lamination sequence of CFRP and determining the influence of the system parameters. A novel software and methodology for evaluating mechanical and damping properties of specimens and tubes made in CFRP were also developed. Moreover, to increase the component's damping properties, rubber nanofibers have been produced and interposed throughout the lamination of specimens. The promising results indicated that the nanofibrous mat could improve the material damping factor over 77% and be adopted in CFRP components with a negligible increment of weight or losing mechanical properties.

Fabrication and characterization of hybrid ferromagnetic-organic heterostructures for spintronics application

Recent research in the field of organic spintronics highlighted the peculiar spin-dependent properties of the interface formed by an organic semiconductor (OSC) chemisorbed over a 3d ferromagnetic metal, also known as spinterface. The hybridization between the molecular and metallic orbitals, typically π orbitals of the molecule and the d orbitals of the ferromagnet, give rise to spin dependent properties that were not expected by considering the single components of interfaces, as for example the appearance of a magnetic moment on non-magnetic molecules or changes in the magnetic behavior of the ferromagnet. From a technological viewpoint these aspects provide novel engineering schemes for spin memory and for spintronics devices, featuring unexpected interfacial magnetoresistance, spin-filtering effects and even modulated magnetic anisotropy. Applications of these concepts to devices require nevertheless to transfer the spinterface effects from an ideal interface to room temperature operating thin films. In this view, my work presents for the first time how spinterface effects can be obtained even at room temperature on polycrystalline ferromagnetic Co thin films interfaced with organic molecules. The considered molecules were commercial and widely used in the field of organic electronics: Fullerene (C60), Gallium Quinoline (Gaq3) and Sexithiophene (T6). An increase of coercivity, up to 100% at room temperature, has been obtained on the Co ultra-thin films by the deposition of an organic molecule. This effect is accompanied by a change of in-plane anisotropy that is molecule-dependent. Moreover the Spinterface effect is not limited to the interfacial layer, but it extends throughout the whole thickness of the ferromagnetic layer, posing new questions on the nature of the 3d metal-molecule interaction.

Functional engineering of hybrid heterostructures for application in electronic, optical and optoelectronic nanostructured devices

Interfacing materials with different intrinsic chemical-physical characteristics allows for the generation of a new system with multifunctional features. Here, this original concept is implemented for tailoring the functional properties of bi-dimensional black phosphorus (2D bP or phosphorene) and organic light-emitting transistors (OLETs). Phosphorene is highly reactive under atmospheric conditions and its small-area/lab-scale deposition techniques have hampered the introduction of this material in real-world applications so far. The protection of 2D bP against the oxygen by means of functionalization with alkane molecules and pyrene derivatives, showed long-term stability with respect to the bare 2D bP by avoiding remarkable oxidation up to 6 months, paving the way towards ultra-sensitive oxygen chemo-sensors. A new approach of deposition-precipitation heterogeneous reaction was developed to decorate 2D bP with Au nanoparticles (NP)s, obtaining a “stabilizer-free” that may broaden the possible applications of the 2D bP/Au NPs interface in catalysis and biodiagnostics. Finally, 2D bP was deposited by electrospray technique, obtaining oxidized-phosphorous flakes as wide as hundreds of µm2 and providing for the first time a phosphorous-based bidimensional system responsive to electromechanical stimuli. The second part of the thesis focuses on the study of organic heterostructures in ambipolar OLET devices, intriguing optoelectronic devices that couple the micro-scaled light-emission with electrical switching. Initially, an ambipolar single-layer OLET based on a multifunctional organic semiconductor, is presented. The bias-depending light-emission shifted within the transistor channel, as expected in well-balanced ambipolar OLETs. However, the emitted optical power of the single layer-based device was unsatisfactory. To improve optoelectronic performance of the device, a multilayer organic architecture based on hole-transporting semiconductor, emissive donor-acceptor blend and electron-transporting semiconductor was optimized. We showed that the introduction of a suitable electron-injecting layer at the interface between the electron-transporting and light-emission layers may enable a ≈ 2× improvement of efficiency at reduced applied bias.

Application of augmented reality in craniofacial surgery: a feasibility study

Augmented Reality (AR) is a novel promising technology, which is gaining success in the medical field. A number of applications in surgery have been described, but few studies have been focusing on pediatric craniofacial surgery. In this research project, the Authors have been implementing a system for intraoperative surgical navigation by means of HoloLens 2 by Microsoft, applied to pediatric craniofacial surgery. The Authors tested the device in a preclinical setting first, and then moved to patients. The Authors assessed the accuracy of the HoloLens 2 by performing 36 procedures in vitro on a printed 3D model of a patient. In clinical setting, 10 patients were prospectively enrolled in the study. The virtual surgical planning was designed for each patient and uploaded onto the software which allows for the AR interface and the standard neurosurgical navigator. For each patient, the surgeon has been drawing osteotomy lines both under the guidance of HoloLens2 and of the neurosurgical navigator. The Author then checked the accuracy with calibrated CAD CAM cutting guides with different grooves, in order to assess the accuracy of the osteotomies performed. We tested levels of accuracy of ±1.5 mm and ±1mm . In the preclinical setting, the HoloLens 2 performed with levels of accuracy of 1.5 mm, whereas in the real setting, surgeons were able to trace the osteotomy lines under the AR guidance for an amount of 45% (0.4 SD) of the entire line, with an accuracy level of ±1.5 mm. This percentage lowers to 34% (0.4 SD) when assessing accuracy level of ±1 mm. The results of the same tasks for the standard navigator are 36% and 16%, for ±1.5 mm and ± 1 mm accuracy level, respectively. The Authors reported encouraging results both in the preclinical and the clinical setting.

Addressing challenges in heterogeneous embedded systems programming: security and performance

Embedded systems are increasingly integral to daily life, improving and facilitating the efficiency of modern Cyber-Physical Systems which provide access to sensor data, and actuators. As modern architectures become increasingly complex and heterogeneous, their optimization becomes a challenging task. Additionally, ensuring platform security is important to avoid harm to individuals and assets. This study primarily addresses challenges in contemporary Embedded Systems, focusing on platform optimization and security enforcement. The initial section of this study delves into the application of machine learning methods to efficiently determine the optimal number of cores for a parallel RISC-V cluster to minimize energy consumption using static source code analysis. Results demonstrate that automated platform configuration is not only viable but also that there is a moderate performance trade-off when relying solely on static features. The second part focuses on addressing the problem of heterogeneous device mapping, which involves assigning tasks to the most suitable computational device in a heterogeneous platform for optimal runtime. The contribution of this section lies in the introduction of novel pre-processing techniques, along with a training framework called Siamese Networks, that enhances the classification performance of DeepLLVM, an advanced approach for task mapping. Importantly, these proposed approaches are independent from the specific deep-learning model used. Finally, this research work focuses on addressing issues concerning the binary exploitation of software running in modern Embedded Systems. It proposes an architecture to implement Control-Flow Integrity in embedded platforms with a Root-of-Trust, aiming to enhance security guarantees with limited hardware modifications. The approach involves enhancing the architecture of a modern RISC-V platform for autonomous vehicles by implementing a side-channel communication mechanism that relays control-flow changes executed by the process running on the host core to the Root-of-Trust. This approach has limited impact on performance and it is effective in enhancing the security of embedded platforms.