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Many research works had the aim of creating frameworks able to model systems, of defining their requirements and properties, and of verifying their satisfiability. Many approaches involve the usage of the Model Driven Engineering throughout the whole system lifecycle in order to build systems that are correct by construction. Using models as primary artefacts helps to reduce costs and time of development. The possibility of having automatic code generation from model tools en- A ct the possibility to produce (theoretically) bug-free code starting from correct models. In this work we describe the usage of a modelling and verification tool, MetaMORP(h)OSY, for performing quality control in E-Health Domain. © 2020 CEUR-WS. All rights reserved.

This paper shows some methods of using CAD systems applied to the study of pre-design and to the analysis of the maintainability of landing gears in new planes. Particularly, according to the contemporary American rules, largely in use in aeronautics, there have been developed and applied procedures to verify the accessibility, handling, and disassembly of different landing gears developed by the Magnaghi Aerospace S.p.A. in Naples. Such controls have been carried out by integrating traditional techniques with parametric CAD systems. In particular it is showed the analysis of kinematics and of interferences during the preliminary design phase of landing gear of C27J plane and the analysis of Reliability, Availability, Maintainability and Safety (RAMS) regarding the new main landing gear of helicopter Agusta A109D/E.

La formazione di inquinanti come il particolato fine ed ultrafine è sicuramente svantaggiata in sistemi di combustione che operano in condizioni di combustione MILD perchè gli intervalli di temperatura di lavoro deprimono le cinetiche che portano alla produzione di tali sostanze. L'utilizzo di combustibili di scarso pregio, però, può determinare la necessita di prevedere sistemi di abbattimento di particolati che in questo caso possono formarsi anche in condizioni di combustione MILD. Un processo efficiente per eliminare particolati submicronici presenti nei gas esausti prevede la condensazione di vapor d'acqua sulle particelle stesse che fungono da nuclei di condensazione. Tale processo è particolarmente vantaggioso nel caso di sistemi di combustione MILD nei quali il vapor d'acqua è utilizzato come diluente. L'attività relativa a questo pacco di lavoro ha riguardato la messa a punto di un sistema sperimentale per lo studio del processo di condensazione per l'eliminazione di particolato da correnti di gas esausti. E' stata quindi realizzata una camera in flusso laminare accessibile otticamente ed i relativi sistemi di monitoraggio e controllo. E' stata, inoltre, implementata la diagnostica ottica necessaria allo studio del processo e realizzate misure sperimentali preliminari per verificare l'affidabilità dell'impianto sperimentale al variare delle condizioni di lavoro.

The reduction of particulate emission is among the most challenging problems in research field of pollutant control in combustion systems. This is due to very low efficiency of conventional separators, such as electrostatic precipitator, cyclone wet scrubber, in the collection of submicronic particles. To increase the diameter of fine and ultrafine particles by means of condensation of water vapor on the particles themselves seems to be a promising technique for industrial applications [1, 2]. Although several data are present in literature in the field of meteorology, cloud physics and aerosol science on nucleation and growth of droplets on foreign nuclei, a systematic analysis on dependence of such a process on parameters relevant from industrial point of view is not yet available. As a matter of a fact, temperature, partial pressure, properties of solid nuclei strongly affect the characteristic time and the efficiency of heterogeneous nucleation and the related dependence are needed for a proper design of a real abatement device. The aim of this work is to summarize the main physical relations governing the nucleation process and to describe the criteria followed in the design and set up of an experimental apparatus realized for the study of heterogeneous nucleation on submicronic particles in different conditions.

The prevalence of impaired glucose tolerance (IGT) and diabetes mellitus (DM) such as defined by National Diabetes Data Group criteria, and glycosylated hemoglobin levels were assessed in a series of consecutive patients who had chronic active hepatitis (CAH) or cirrhosis in the absence of any known diabetogenic risk factors and who had normal fasting glycemic levels. Based on oral glucose tolerance test, the prevalence of IGT (15%) and DM (27%) in cirrhosis was significantly higher (p less than 0.005) than that observed in CAH (0%) and controls (0%). In contrast, HbA1 levels were not statistically different in cirrhotic patients (with normal or altered glucose tolerance) as compared with CAH and control subjects.(a) HbA1 is an unsatisfactory test in the diagnosis of altered glucose tolerance in patients with cirrhosis, and (b) Cirrhosis (but not CAH) represents itself a risk factor for the development of glucose metabolism alterations. Therefore, routine oral glucose tolerance testing is warranted in these patients.

Background: Schwannomas, also called neurinomas, are rare benign tumors of the neural cells that can develop from the sheaths of nervous structures of several districts, although the most frequent sites are the cranial nerves (25%–45%). Rarely, cases show neck schwannomas in the thyroid parenchyma, while the cases of thyroid-bed schwannomas mimicking a thyroid-gland lesions are anecdotal. Methods: We report the case of a 70-year-old man with a preoperative-imaging diagnosis of a thyroid neoplasm, confirmed as Thyr 4 by fine-needle cytology. Results: During surgery, an extra-thyroidal lesion was discovered, determined to be a neck schwannoma through definitive pathology. A literature review of cases of thyroid-bed-lesion schwannomas misinterpreted as thyroid neoplasms was carried out. Conclusions: In the case of suspicious extra-thyroidal lesions, we advocate for a close routine cooperation between the cytologist, the radiologist, and the surgeon in the attempt to reach an accurate preoperative diagnosis.

Opposed to whole wheat (WWP), traditional pizza (TP) is loved by patients with type 1 diabetes mellitus (T1DM) despite causing hyperglycemia. 50 well-trained T1DM patients had higher glucose levels after TP than after WWP or mixed flour pizza, which however was tasty, digestible and metabolically appropriate to break diet monotony.

The increasing adoption of digital technologies to manage and process information used in everyday life, results in an increase in the demand for digital data analysis for investigative purposes. In fact, the reconstruction of computer and telematic crimes, or, in general, of crimes committed with computer systems, require the adoption of Computer Forensics best practices in order to extract relevant evidences from electronic devices, guaranteeing the integrity of data and their admissibility during a trial. The process of extraction, conservation, analysis and documentation of a forensic investigation can be enhanced by a framework that support investigators during their work, correlating evidences collected by different forensic tools. So, in this work we propose a semantic methodology and a system architecture for evidences correlation aiming to provide enhanced retrieval and reasoning capabilities.

The use of pervasive IoT devices in Smart Cities, have increased the Volume of data produced in many and many field. Interesting and very useful applications grow up in number in E-health domain, where smart devices are used in order to manage huge amount of data, in highly distributed environments, in order to provide smart services able to collect data to fill medical records of patients. The problem here is to gather data, to produce records and to analyze medical records depending on their contents. Since data gathering involve very different devices (not only wearable medical sensors, but also environmental smart devices, like weather, pollution and other sensors) it is very difficult to classify data depending their contents, in order to enable better management of patients. Data from smart devices couple with medical records written in natural language: we describe here an architecture that is able to determine best features for classification, depending on existent medical records. The architecture is based on pre-filtering phase based on Natural Language Processing, that is able to enhance Machine learning classification based on Random Forests. We carried on experiments on about 5000 medical records from real (anonymized) case studies from various health-care organizations in Italy. We show accuracy of the presented approach in terms of Accuracy-Rejection curves.

A lot of research has been done during the first months of 2020 regarding the Covid-19. Researchers of different fields worked and cooperated to understand the virus better, in order to manage the pandemic and to model its spread. A series of tools have been developed in this sense, but there is a lack of work with regards to what has been developed from the scientific community. We would like to, at least partially, summarise the results obtained so far by analysing some of the published papers on the matter. To achieve such a result, we are going to use different python libraries that allow analysing texts. The entire work has been done with python on the Google Colaboratory platform.

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works The interest of Industry 4.0 in smart contracts and blockchain technologies is growing up day by day. Smart contracts have enabled new kinds of interactions whereby contractors can even fully automate processes they agree on. This technology is really appealing in Internet of Things (IoT) domain because smart devices generate events for software agents involved in a smart contract execution, making full automation possible. However, smart contracts have to comply with national and international laws and accountability of participant's actions. Soundness of a smart contract has to be verified in terms of law compliance. Here, we propose a model for verification and validation of law compliance of smart contracts in IoT environments. The main goal of this article is to propose a formal model (based on multiagent logic and ontological description of contracts) for validating law compliance of smart contracts and to determine potential responsibilities of failures

Viral Marketing can be considered as the modern version of the ancient "word-of-mouth" advertising, in which companies choose a restricted number of persons, considered "influential", recommending them products or services that will be thus iteratively suggested. In this paper, we propose cognitive models and algorithms for marketing applications through Online Social Networks, considered as a graph database, and define the concept of influence graph leveraging particular user behavioral patterns, by querying the initial heterogeneous graph network. We also model the diffusion across the network, without any preliminary information, as a Combinatorial Multi-Armed Bandit problem, for the selection of most influential users. We have used the YELP social network as case study for our approach, showing how it is possible to generate an influence graph considering several kinds of relevant paths (mainly considering reviews to the same firms) by which a user can influence other ones. Several experiments have been carried out and discussed, putting into evidence the effectiveness and efficacy of the proposed methods for influence maximization with respect to other approaches of state of the art.

e-Health applications enable one to acquire, process, and share patient medical data to improve diagnosis, treatment, and patient monitoring. Despite the undeniable benefits brought by the digitization of health systems, the transmission of and access to medical information raises critical issues, mainly related to security and privacy. While several security mechanisms exist that can be applied in an e-Health system, they may not be adequate due to the complexity of involved workflows, and to the possible inherent correlation among health-related concepts that may be exploited by unauthorized subjects. In this article, we propose a novel methodology for the validation of security and privacy policies in a complex e-Health system, that leverages a formal description of clinical workflows and a semantically enriched definition of the data model used by the workflows, in order to build a comprehensive model of the system that can be analyzed with automated model checking and ontology-based reasoning techniques. To validate the proposed methodology, we applied it to two case studies, subjected to the directives of the EU GDPR regulation for the protection of health data, and demonstrated its ability to correctly verify the fulfillment of desired policies in different scenarios.

The purpose of this work is to create an interactive chatbot that can help specialists to get information about food and health-related questions. This project uses main techniques of information processing as grammar tagging. The program gets information from a digital encyclopedia, named medlineplus.gov. This is one of the most complete encyclopedias on the web. Firstly we had to import necessary libraries as nltk and numpy that are useful for information processing, re to use regular expression, string for string type, bs4 to parse html lines and want to know the right extension and urllib.request to use websites and get information from these ones. We also have imported pos_tag from nltk to do grammar parsing and stop-words from nltk.corpus to find meaningless words. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Researchers and companies are making great efforts to create new ways of interaction with a increasing number and types of electronic devices, with particular attention to the conversational interface, whether spoken or written. The cultural heritage domain can bring many benefits from the great effort in this field, as a smart conversational system can provide both room/hotel/apartment information and information related to the area, natural or cultural points of interest, tourist routes, social events, history etc. The paper’s main goal is to present a quick and effective service to the tourists visiting a city for the first time. Learning the cultural preferences of the users can enhance customer satisfaction, since a smart system can propose them customised tours in order to reach point of interests according to the expressed preferences. The interaction with the user is simplified by a conversational interface (chatbot). © Springer Nature Switzerland AG 2021.

Artificial Intelligence application are becoming increasingly complex and sophisticated in order to shorten the gap between the users and digital systems. Nowadays, researchers and companies are making a big effort to develop new forms of interactions with a growing number and kinds of electronic devices, with a particular attention on the conversational interface, spoken or written. A chatbot is software that simulates and processes human conversations, allowing users to interact with digital devices as if they were communicating with a real person. In this paper we introduce a Chatbot for the cultural heritage domain [1], able to respond to a simple single-line query or to suggest users, as a digital assistants, by providing increasing levels of customisation through the collection and the processing of users’ conversations. © 2020, Springer Nature Switzerland AG.

In this work we propose a tool able to monitor aeroplanes crashes, providing reports and views to managers, in order to improve services for the safety of passengers on board. We exploited Business Intelligence data visualisation tools functionalities to design specific data processing phases, from the pre-processing to the cleaning and filtering and finally visualisation of the reports. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Conversational systems are growing their success among users thanks to their ability to collect and rank users’ preferences and provide them relevant information in a simple way. In this paper we present C’Meal, a chatbot-based conversational framework which, given some ingredients and other requests entered by the user as input, researches the most appropriate recipe. Two categories of people are addressed in the program: those who want to discover new recipes, and those who want to create a recipe with the few ingredients left in the fridge to reduce food waste. The user must formulate his request in both cases by inserting the desired ingredients and other specific requests as a meal type or method of cooking. © Springer Nature Switzerland AG 2021.

The application of artificial intelligence is becoming increasingly complex and sophisticated to shorten the gap between users and digital systems. IA techniques can bring a lot of advantage in facing the issue of allergic reaction related to food allergies. Recognising and avoiding the foods on which it is based is an effective way to avoid an allergic reaction. To identify possible allergens, it is important to read the food labels carefully or to know what are the ingredients from which it is made. In this paper we present a system that exploits the techniques and tools of Artificial Intelligence to extract and analyse the ingredients of a recipe, and alert the user to the presence of possible allergens. The performed experimentation shows that the system can alert the user of allergens in Wikipedia Cookbok dataset recipes. © Springer Nature Switzerland AG 2021.

With the terms “Cloud Computing” we mean a model in which computation, software and storage resources do not require knowledge of the physical location and configuration of the system that provides the service in question by the end user. Thanks to the widespread use of the Internet, applications can now be used as services on the network. Many interesting areas of application are enjoying of these benefits, such as legal domain: The use of systems for conflict resolution can help lawyers, mediators and judges with the objective to reach an agreement between the parties. In this paper we introduce the architecture of a cloud-oriented web application, developed within the European project CREA (Conflict Resolution with Equitative Algorithms, Figure). Its objective is the application of algorithms to solve civil matters, into the allocation of goods, leading the parties to a friendly solution before or during the trial comparison. © Springer Nature Switzerland AG 2020.