On Representing Concepts in High-dimensional Linear Spaces

Producing a mathematical model of concepts is a very important issue in artificial intelligence, because if such a model were found this, besides being a very interesting result in its own right, would also contribute to the emergence of what we could call the \u2018mathematics of thought.\u2019 One of the most interesting attempts made in this direction is P. Gardenfors\u2019 theory of conceptual spaces, a \ua8 theory which is mostly presented by its author in an informal way. The main aim of the present article is contributing to Gardenfors\u2019 theory of conceptual spaces \ua8 by discussing some of the advantages which derive from the possibility of representing concepts in high-dimensional linear spaces

A Yolo-Based Model for Breast Cancer Detection in Mammograms

This work aims to implement an automated data-driven model for breast cancer detection in mammograms to support physicians' decision process within a breast cancer screening or detection program. The public available CBIS-DDSM and the INbreast datasets were used as sources to implement the transfer learning technique on full-field digital mammography proprietary dataset. The proprietary dataset reflects a real heterogeneous case study, consisting of 190 masses, 46 asymmetries, and 71 distortions. Several Yolo architectures were compared, including YoloV3, YoloV5, and YoloV5-Transformer. In addition, Eigen-CAM was implemented for model introspection and outputs explanation by highlighting all the suspicious regions of interest within the mammogram. The small YoloV5 model resulted in the best developed solution obtaining an mAP of 0.621 on proprietary dataset. The saliency maps computed via Eigen-CAM have proven capable solution reporting all regions of interest also on incorrect prediction scenarios. In particular, Eigen-CAM produces a substantial reduction in the incidence of false negatives, although accompanied by an increase in false positives. Despite the presence of hard-to-recognize anomalies such as asymmetries and distortions on the proprietary dataset, the trained model showed encouraging detection capabilities. The combination of Yolo predictions and the generated saliency maps represent two complementary outputs for the reduction of false negatives. Nevertheless, it is imperative to regard these outputs as qualitative tools that invariably necessitate clinical radiologic evaluation. In this view, the model represents a trusted predictive system to support cognitive and decision-making, encouraging its integration into real clinical practice

A Quantum Planner for Robot Motion

The possibility of integrating quantum computation in a traditional system appears to be a viable route to drastically improve the performance of systems endowed with artificial intelligence. An example of such processing consists of implementing a teleo-reactive system employing quantum computing. In this work, we considered the navigation of a robot in an environment where its decisions are drawn from a quantum algorithm. In particular, the behavior of a robot is formalized through a production system. It is used to describe the world, the actions it can perform, and the conditions of the robot's behavior. According to the production rules, the planning of the robot activities is processed in a recognize-act cycle with a quantum rule processing algorithm. Such a system aims to achieve a significant computational speed-up

Smart assistance for students and people living in a campus

Being part of one of the fastest growing area in Artificial Intelligence (AI), virtual assistants are nowadays part of everyone's life being integrated in almost every smart device. Alexa, Siri, Google Assistant, and Cortana are just few examples of the most famous ones. Beyond these off-the-shelf solutions, different technologies which allow to create custom assistants are available. IBM Watson, for instance, is one of the most widely-adopted question-answering framework both because of its simplicity and accessibility through public APIs. In this work, we present a virtual assistant that exploits the Watson technology to support students and staff of a smart campus at the University of Palermo. Some in progress results show the effectiveness of the approach we propose

Simulation and Test of UAV Tasks with Resource-Constrained Hardware in the Loop

Simulations are indispensable to reduce costs and risks when developing and testing algorithms for unmanned aerial vehicles (UAV) especially for applications in high risk scenarios like search and rescue (SAR) operations and post-disaster damage assessment. Many UAV applications require real-time tasks for which the timeliness of computations is fundamental. However, standard simulation tools are not guaranteed to run in sync with real-time events, leading to unreliable assessments of the ability of the target hardware to perform specific tasks. In this work we present a simulation and test system able to run UAV tasks on resource-constrained target hardware possibly adopted in these applications. The system allows for hardware-in-the-loop simulations in which a virtual UAV provided with virtual sensors is controlled by the software under test (SUT) running on the target hardware, while simulated and real time are kept in sync. We provide experimental results from the execution of several increasingly difficult tasks in the system

Dietary studies in birds: testing a non-invasive method using digital photography in seabirds

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Dietary studies give vital insights into foraging behaviour, with implications for understanding changing environmental conditions and the anthropogenic impacts on natural resources. Traditional diet sampling methods may be invasive or subject to biases, so developing non-invasive and unbiased methods applicable to a diversity of species is essential. We used digital photography to investigate the diet fed to chicks of a prey-carrying seabird and compared our approach (photo-sampling) to a traditional method (regurgitations) for the greater crested tern Thalasseus bergii. Over three breeding seasons, we identified >24 000 prey items of at least 48 different species, more than doubling the known diversity of prey taken by this population of terns. We present a method to estimate the length of the main prey species (anchovy Engraulis encrasicolus) from photographs, with an accuracy <1 mm and precision ~ 0·5 mm. Compared to regurgitations at two colonies, photo-sampling produced similar estimates of prey composition and size, at a faster species accumulation rate. The prey compositions collected by two researchers photo-sampling concurrently were also similar. Photo-sampling offers a non-invasive tool to accurately and efficiently investigate the diet composition and prey size of prey-carrying birds. It reduces biases associated with observer-based studies and is simple to use. This methodology provides a novel tool to aid conservation and management decision-making in the light of the growing need to assess environmental and anthropogenic change in natural ecosystems.Department of Science and Technology, South Afric

Yeasts and moulds contaminants of food ice cubes and their survival in different drinks

Aims: To evaluate the levels of unicellular and filamentous fungi in ice cubes produced at different levels and to determine their survival in alcoholic beverages and soft drinks. Methods and Results: Sixty samples of ice cubes collected from home level (HL) productions, bars and pubs (BP) and industrial manufacturing plants (MP) were investigated for the presence and cell density of yeasts and moulds. Moulds were detected in almost all samples, while yeasts developed from the majority of HL and MP samples. Representative colonies of microfungi were subjected to phenotypic and genotypic characterization. The identification was carried out by restriction fragment length polymorphism (RFLP) analysis of the region spanning the internal transcribed spacers (ITS1 and ITS2) and the 5·8S rRNA gene. The process of yeast identification was concluded by sequencing the D1/D2 region of the 26S rRNA gene. The fungal biodiversity associated with food ice was represented by nine yeast and nine mould species. Strains belonging to Candida parapsilosis and Cryptococcus curvatus, both opportunistic human pathogens, and Penicillium glabrum, an ubiquitous mould in the ice samples analysed, were selected to evaluate the effectiveness of the ice cubes to transfer pathogenic microfungi to consumers, after addition to alcoholic beverages and soft drinks. All strains retained their viability. Conclusions: The survival test indicated that the most common mode of consumption of ice cubes, through its direct addition to drinks and beverages, did not reduce the viability of microfungi. Significance and Impact of the Study: This study evidenced the presence of microfungi in food ice and ascertained their survival in soft drinks and alcoholic beverages

Selected lactic acid bacteria as a hurdle to the microbial spoilage of cheese: application on a traditional raw ewes’ milk cheese.

To evaluate the efficacy of lactic acid bacteria (LAB) to improve the hygienic safety of a traditional raw milk cheese, the raw ewes’ milk protected denomination of origin (PDO) Pecorino Siciliano cheese was used as a model system. Different Pecorino Siciliano curds and cheeses were used as sources of autochthonous LAB subsequently used as starter and non-starter LAB. These were screened for their acidification capacity and autolysis. Starter LAB showing the best performance were genotypically differentiated and identified: two strains of Lactococcus lactis subsp. lactis were selected. From the nonstarter LAB, Enterococcus faecalis, Lactococcus garvieae and Streptococcus macedonicus strains were selected. The five cultures were used in individual or dual inocula to produce experimental cheeses in a dairy factory for which production was characterised by high numbers of undesirable bacteria. At 5- month of ripening, the experimental cheeses produced with LAB were characterised by undetectable levels of enterobacteria and pseudomonads and the typical sensory attributes

Application of hydrogen peroxide to improve the microbiological stability of food ice produced in industrial facilities

This work was aimed to produce an “active” food ice to preserve its microbiological safety over time. With this in mind, ice cubes were processed with the addition of H2O2 to water before freezing. Four food ice productions were performed at the industrial level: one control trial without the addition of H2O2 (0OX) and three experimental trials obtained by adding 4, 8, and 12 mg/L of H2 O2 (4OX, 8OX, and 12OX), respectively. After production, all food ice trials were artificially contaminated with 102 CFU/100 mL of water-borne pathogenic bacteria (Escherichia coli ATCC 25922, Enteroccus faecalis ATCC 29212, and Pseudomonas aeruginosa ATCC 27853) inoculated individually. Thawed ice samples were then subjected to microbiological analyses performed by the membrane filtration method and the results indicated that only trial 12OX was able to inactivate all bacteria strains. In conclusion, the addition of 12 mg/L H2O2 represents an optimal cost-effective strategy to preserve the microbiological stability of food ice even when it is improperly handled after production