Diogene-CT: tools and methodologies for teaching and learning coding

Computational thinking is the capacity of undertaking a problem-solving process in various disciplines (including STEM, i.e. science, technology, engineering and mathematics) using distinctive techniques that are typical of computer science. It is nowadays considered a fundamental skill for students and citizens, that has the potential to affect future generations. At the roots of computational-thinking abilities stands the knowledge of computer programming, i.e. coding. With the goal of fostering computational thinking in young students, we address the challenging and open problem of using methods, tools and techniques to support teaching and learning of computer-programming skills in school curricula of the secondary grade and university courses. This problem is made complex by several factors. In fact, coding requires abstraction capabilities and complex cognitive skills such as procedural and conditional reasoning, planning, and analogical reasoning. In this paper, we introduce a new paradigm called ACME (“Code Animation by Evolved Metaphors”) that stands at the foundation of the Diogene-CT code visualization environment and methodology. We develop consistent visual metaphors for both procedural and object-oriented programming. Based on the metaphors, we introduce a playground architecture to support teaching and learning of the principles of coding. To the best of our knowledge, this is the first scalable code visualization tool using consistent metaphors in the field of the Computing Education Research (CER). It might be considered as a new kind of tools named as code visualization environments

Spice-up your coding lessons with the ACME approach

It is nowadays considered a fundamental skill for students and citizens the capacity of undertaking a problem-solving process in various disciplines (including STEM, i.e. science, technology, engineering and mathematics) using distinctive techniques that are typical of computer science. These abilities are usually called Computational Thinking and at the roots of them stands the knowledge of coding. With the goal of encouraging Computational Thinking in young students, we discuss tools and techniques to support the teaching and the learning of coding in school curricula. It is well known that this problem is complex due to the fact that it requires abstraction capabilities and complex cognitive skills such as procedural and conditional reasoning, planning, and analogical reasoning. In this paper, we present ACME (“Code Animation by Evolved Metaphors”) that stands at the foundation of the Diogene-CT code visualization environment and methodology. We discuss visual metaphors for both procedural and object-oriented programming. Based on them, we introduce a playground architecture to support teaching and learning of the principles of coding. To the best of our knowledge, this is the first scalable code visualization tool using consistent metaphors in the field of Computing Education Research (CER)

Cleaning data with Llunatic

Data cleaning (or data repairing) is considered a crucial problem in many database-related tasks. It consists in making a database consistent with respect to a given set of constraints. In recent years, repairing methods have been proposed for several classes of constraints. These methods, however, tend to hard-code the strategy to repair conflicting values and are specialized toward specific classes of constraints. In this paper, we develop a general chase-based repairing framework, referred to as Llunatic, in which repairs can be obtained for a large class of constraints and by using different strategies to select preferred values. The framework is based on an elegant formalization in terms of labeled instances and partially ordered preference labels. In this context, we revisit concepts such as upgrades, repairs and the chase. In Llunatic, various repairing strategies can be slotted in, without the need for changing the underlying implementation. Furthermore, Llunatic is the first data repairing system which is DBMS-based. We report experimental results that confirm its good scalability and show that various instantiations of the framework result in repairs of good quality

Collecting built environment information using UAVs: Time and applicability in building inspection activities

The Italian way of thinking about maintenance is too often one-sided. Indeed, it is considered not so much as a useful practice to prevent the occurrence of a fault (ex ante), but as an intervention to solve it (ex post). Analyzing the legislation relating to the construction sector, it can be seen that it does not clearly define the responsibilities, timescales and methods in which maintenance interventions must be planned and carried out. For this reason, this practice is still very weak compared, for example, to the industrial sector, where it is an established practice. Currently, the complexity of reading the maintenance plans drawn up by designers and the considerable costs associated with maintenance operations discourage owners and managers from even carrying out preliminary inspection operations. This research aims to stimulate these stakeholders to carry out inspection operations regularly, highlighting their costs and benefits. In particular, working on a case study in Piedmont, the costs of visual inspections carried out in the traditional way are compared with those that would be incurred if unmanned aerial vehicles (UAVs) were used. Finally, the collateral benefits of inspections carried out with UAVs are highlighted

The effect of ceramic YSZ powder morphology on coating performance for industrial TBCs

The increasing turbine inlet temperatures in modern gas turbines have raised concerns about the corrosion of ceramic thermal barrier coatings (TBCs) caused by molten silicate deposits, commonly referred to as “CMAS” due to their main constituents (CaO-MgO-Al2O3-SiO2). The objective of this study was to investigate the combined influence of powder morphology and chemical composition on the CMAS resistance and thermal cycling resistance of ceramic monolayer and bi-layer coatings created through Atmospheric Plasma Spraying (APS). Three powder morphologies were examined: porous Agglomerated and Sintered (A&S) granules, Hollow Spherical (HOSP) powders, and dense, irregular Fused and Crushed (F&C) particles. Monolayer 7-8YSZ coatings with both porous and dense vertically cracked (DVC) microstructures, and bi-layer coatings consisting of a bottom layer of porous standard 7-8YSZ and a top layer composed of a porous high‑yttrium ZrO2–55 wt% Y2O3 were obtained using all three powder types (A&S, HOSP, or F&C). Furthermore, the bi-layer systems were deposited with different ratios between the individual layer thicknesses and/or different total thickness. FEG-SEM, EDX, and micro-Raman analyses, were conducted to assess the coatings' performance. Nanoindentation high-speed mapping and pillar splitting test were performed to evaluate the mechanical behaviour. The study on 8YSZ monolayers shows that coatings from a F&C feedstock exhibit higher density, reducing the CMAS penetration. However, these coatings demonstrate poorer thermal cycling performance due to increased stiffness and thermal stresses. Coatings from HOSP and A&S powders allow CMAS penetration but offer stress relief pathways, enhancing the coating's ability to withstand thermal stresses. Bi-layer coatings with a 55YSZ top coat show superior CMAS resistance compared to 7-8YSZ monolayer coatings, with limited penetration causing top coat peeling. The thickness ratio between the layers also affects thermal cycling resistance, where a thinner 55YSZ layer extends the TBC lifetime

A Novel Transformer-Based IMU Self-Calibration Approach through On-Board RGB Camera for UAV Flight Stabilization

During flight, unmanned aerial vehicles (UAVs) need several sensors to follow a predefined path and reach a specific destination. To this aim, they generally exploit an inertial measurement unit (IMU) for pose estimation. Usually, in the UAV context, an IMU entails a three-axis accelerometer and a three-axis gyroscope. However, as happens for many physical devices, they can present some misalignment between the real value and the registered one. These systematic or occasional errors can derive from different sources and could be related to the sensor itself or to external noise due to the place where it is located. Hardware calibration requires special equipment, which is not always available. In any case, even if possible, it can be used to solve the physical problem and sometimes requires removing the sensor from its location, which is not always feasible. At the same time, solving the problem of external noise usually requires software procedures. Moreover, as reported in the literature, even two IMUs from the same brand and the same production chain could produce different measurements under identical conditions. This paper proposes a soft calibration procedure to reduce the misalignment created by systematic errors and noise based on the grayscale or RGB camera built-in on the drone. Based on the transformer neural network architecture trained in a supervised learning fashion on pairs of short videos shot by the UAV’s camera and the correspondent UAV measurements, the strategy does not require any special equipment. It is easily reproducible and could be used to increase the trajectory accuracy of the UAV during the flight

An Automated Algorithm for Extracting Website Skeleton

The huge amount of information available on the Web has attracted many research e#orts into developing wrappers that extract data from webpages. However, as most of the systems for generating wrappers focus on extracting data at page-level, data extraction at site-level remains a manual or semi-automatic process. In this paper, we study the problem of extracting website skeleton, i.e. extracting the underlying hyperlink structure that is used to organize the content pages in a given website. We propose an automated algorithm, called the Sew algorithm, to discover the skeleton of a website. Given a page, the algorithm examines hyperlinks in groups and identifies the navigation links that point to pages in the next level in the website structure. The entire skeleton is then constructed by recursively fetching pages pointed by the discovered links and analyzing these pages using the same process. Our experiments on real life websites show that the algorithm achieves a high recall with moderate precision

On the well-posedness of uncalibrated photometric stereo under general lighting

Uncalibrated photometric stereo aims at estimating the 3D-shape of a surface, given a set of images captured from the same viewing angle, but under unknown, varying illumination. While the theoretical foundations of this inverse problem under directional lighting are well-established, there is a lack of mathematical evidence for the uniqueness of a solution under general lighting. On the other hand, stable and accurate heuristical solutions of uncalibrated photometric stereo under such general lighting have recently been proposed. The quality of the results demonstrated therein tends to indicate that the problem may actually be well-posed, but this still has to be established. The present paper addresses this theoretical issue, considering first-order spherical harmonics approximation of general lighting. Two important theoretical results are established. First, the orthographic integrability constraint ensures uniqueness of a solution up to a global concave-convex ambiguity , which had already been conjectured, yet not proven. Second, the perspective integrability constraint makes the problem well-posed, which generalizes a previous result limited to directional lighting. Eventually, a closed-form expression for the unique least-squares solution of the problem under perspective projection is provided , allowing numerical simulations on synthetic data to empirically validate our findings