Blockchain technology is receiving an ever-increasing attention. In this work, we present pros and cons of this technology, by taking the point of view of (IT) professionals evaluating whether to embrace this technology or not for their business. Use cases selected from a particular domain represented by the insurance sector are analyzed, and several application guidelines that can be generalized and applied to other sectors are identified

The last couple of years witnessed the explosion of two major technological revolutions, with vehicles, that started to be regarded as the next frontier for artificial intelligence and blockchain, which began to be considered by the wider public for the great changes it could bring in a number of heterogeneous domains. In order to take part in these revolutions, in this paper we show how blockchain and sensors installed on a vehicle could be combined to (semi-)automatically activate/deactivate car insurance covers in an envisaged on-demand insurance scenario. We present a prototype, which includes a mobile app and a portable electronic device to be installed onboard. The mobile app lets the driver dynamically change the status of specific insurance covers (in some cases, after pictures of the vehicle have been taken to attest its conditions). Each modification (and picture hash) is saved on the blockchain within a smart contract, in order to certify changes made (and vehicle's status). Sensors embedded in the electronic device are used to collect passengers' and vehicle's data. Data are then used to automatically modify insurance covers based on car/environment conditions and preferences set. The proposed solution could help lowering policy modification costs and limiting insurance frauds.

Software for computer animation is generally characterized by a steep learning curve, due to the entanglement of both sophisticated techniques and interaction methods required to control 3D geometries. This paper proposes a tool designed to support computer animation production processes by leveraging the affordances offered by articulated tangible user interfaces and motion capture retargeting solutions. To this aim, orientations of an instrumented prop are recorded together with animator's motion in the 3D space and used to quickly pose characters in the virtual environment. High-level functionalities of the animation software are made accessible via a speech interface, thus letting the user control the animation pipeline via voice commands while focusing on his or her hands and body motion. The proposed solution exploits both off-the-shelf hardware components (like the Lego Mindstorms EV3 bricks and the Microsoft Kinect, used for building the tangible device and tracking animator's skeleton) and free open-source software (like the Blender animation tool), thus representing an interesting solution also for beginners approaching the world of digital animation for the first time. Experimental results in different usage scenarios show the benefits offered by the designed interaction strategy with respect to a mouse \& keyboard-based interface both for expert and non-expert users.

Computer-supported assessment tools can bring significant benefits to both students and teachers. When integrated in traditional education workflows, they may help to reduce the time required to perform the evaluation and consolidate the perception of fairness of the overall process. When integrated within on-line intelligent tutoring systems, they could provide students with a timely feedback and support self-assessment activities. The current work presents an alternative approach (and not just a \"yet-another-implementation\") to the problem of automatically evaluating technical skills needed to create 3D computer animations. Although some solutions have been reported already in the literature, their applicability is partially constrained, as they require the teaching staff to define evaluation criteria that are strictly linked to the particular animation technique being assessed. Students are forced to operate in environments where they can only perform a part of the required animation steps, by using a pre-defined set of techniques and tools. To address such limitations, the proposed system exploits shape- and time-based features extracted from the 3D point clouds (i.e., the set of data points) describing animated geometries, which are independent of the particular animation techniques used. Experimental observations collected in the evaluation of course assignments in which students were asked to recreate 3D animations of deformable meshes prepared by the teaching staff showed a good correlation between automatic and manual evaluations. Obtained results confirmed the ability of the proposed approach to cope with heterogeneous evaluation tasks in which the relevant learning outcomes can be properly considered.

The players of the digital industry look at network Big Data as an incredible source of revenues, which can allow them to design products, services and market strategies ever more tailored to users' interests and needs. This is the case of data collected by Web analytics tools, which describe the way users interact with Web contents and where their attention focuses onto during navigation. Given the complexity of information to analyze, existing tools often make use of visualization strategies to represent data aggregated throughout separate sessions and multiple users. In particular, heat maps are often adopted to study the distribution of mouse activity and identify page regions that are more frequently reached during interaction. Unfortunately, since Web contents are accessed via ever more heterogeneous devices, region-based heat maps cannot be exploited anymore to aggregate data concerning user's attention, since the same Web content may move to another page location or exhibit a different aspect depending on the access device used or the user agent setup. This paper presents the design of a visual analytics framework capable to deal with the above limitation by adopting a data collection approach that combines information about regions displayed with information about page structure. This way, the well-known heat map-based visualization can be produced, where interactions can be aggregated on a per-element basis independently of the specific access configuration. Experimental results showed that the framework succeeds in accurately quantifying user's attention and replicating results obtained by manual processing.

A recent trend in human-computer interaction is to ease the creation of content such as apps and games via intelligent systems, allowing nonskilled users to define a given system's behavior through visual programming or simplified metalanguages. However, when the number of elements to be controlled increases, the complexity could become comparable to that of traditional coding strategies. This article addresses this issue by proposing a framework for automatically configuring a system's behavior based on user input and context information. Framework effectiveness has been tested in a game-creation scenario and used for automatically mapping user commands on virtual character actions based on a natural language description of the game scene. The use of semantics-based mapping reduces the effort and complexity linked with the configuration of the interaction logic, thus decreasing the number of commands needed for controlling the characters. The Web extra includes the questionnaire and full catalogue of descriptions collected

The ever more complex labor world and the current economic crisis ask learners and workers to continuously update their qualification level to stay relevant on the market. Hence, education and training providers need to adjust their offer in order to cope with such evolving requirements. However, because of the huge number of variables to consider, finding the right learning content able to let an individual fill his/her competency gap may be a task hard to accomplish. In this paper we propose a semantic-based recommender system that is designed to cross heterogeneous information about learners' and workers' background as well as advertised job positions with a catalogue of online courses in order to identify the most appropriate learning resources. Experimental observations showed a good agreement between human and automatic recommendations, confirming the applicability of the emerging semantic technology to the generation of user-centered services capable to adapt to individual's learning needs

This survey of current job search and recruitment tools focuses on applying a computer-based approach to job matchmaking. The authors present a semantic-based software platform, LO-MATCH - developed in the framework of a European project on lifelong learning - that highlights future research directions. There are three related Web extras that provide supplemental material

In the recent years, new business models of provision of services are grown for different kind of software thanks to the development of cloud environments. A large number of companies use 3D software tools and can be interested in adopting 3D visualization as a functionality of the cloud infrastructure rather than the single employee's workstation, saving hardware resources and licenses costs. Remote visualization solutions allows to decouple computing resources on one side and visualization resources on the other side; rendering servers are in charge to compute and stream to the user's device the output graphics of the intended software as a sequence of individual frames. However, the provision of highly graphics-oriented software within a cloud can be particularly challenging due to a number of technological limitations from bandwidth requirements to latency-related issues. In this scenario, the calculation of the differences between successive frames (Diff-Map) is of paramount importance to reduce the bandwidth usage and computational complexity. Diff-Map calculation is time and resource consuming, therefore a method for the calculation of an approximated Diff-Map is proposed. This paper, after analyzing the main recent technological trends followed in the research domain for the development of effective remote visualization solutions, addresses the analysis of network bandwidth usage and computational speed by adopting approximated Diff-Map methods for encoding and transmitting only relevant data pertaining to changed areas of the frame buffer. A set of experimental tests demonstrates the savings in bandwidth consumption and performance speed up going towards a quality tradeoff, alleviating the burden of transmitting excessive useless data to remote client viewers.

When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental tests

In recent years, mobility of students and workers started to be considered as a way for answering skill shortages in the European labor world. However, in order to implement effective mobility practices, suitable instruments supporting transparency and readability of the outcomes of learning processes as well as of the needs of companies and employers in general have to be developed. In fact, though some instruments have been introduced (like, for instance, the European Qualification Framework, EQF, the European Credit system for Vocational Education and Training, ECVET, etc.), they are often seen as theoretical tools rather than a practical help for involved stakeholders. In this work, the results of the TIPTOE project, a transnational initiative funded by the European Commission under the Lifelong Learning Programme are illustrated. In particular, the semantic-based methodology for the construction of a European-wide profile mixing education and labor worlds perspectives in the trade sector is discussed. Furthermore, a number of tools allowing end-users to compare owned qualifications to the reference one and supporting stakeholders in the reading of national educational and occupational profiles in the EQF dimension are presented

Learning semantics, which is intended as a way to provide digital learning resources with a meaning and make them processable by machines by mimicking human reasoning, is changing the way teaching and learning processes are being carried out. Through semantic processing, a machine could act as a personal assistant at the service of learners, trainers and other actors involved in the education context, and could help them to address knowledge-intensive problems, encompassing the creation, management and personalization of learning paths, the identification of suitable learning resources, the automatic grading of assignments and exams, etc. This paper aims to draft an overall picture of learning semantics, by illustrating enabling technologies, providing hints on how a semantic system for learning could be realized, presenting relevant application scenarios, showing expected benefits, discussing challenges and threats and outlining possible solutions.

The technological development that has taken place over recent years has affected the way that the Web is exploited by users. In fact, a user is no longer seen as a mere observer; instead, he or she actively takes part in the production of new knowledge, which is then made available to other users. In this scenario, which is characterized by ever-growing information, new approaches (e.g., based on semantic technologies) for processing large amounts of content must be developed. Other sectors, including education and learning, as well as job seeking and hiring activities, could benefit from the exploitation of tools that can be developed within the Semantic Web initiative. As a consequence of the use of semantic technologies, learners could find more efficient training paths that provide them with their missing areas of competence and training institutes could analyze and modify existing qualifications according to a market's requirements, while companies could effectively identify the best candidates for a given job, not only within national boundaries but also worldwide. This study aims to present an overview of recent research in the field of semantic technologies applied to education and job-seeking contexts. Issues that are related to students' and workers' mobility, job seeking and hiring and the improvement of qualification offers will be analyzed and compared, by distinguishing three fields of research: knowledge base creation, the development of strategies for the integration of heterogeneous systems and the definition of inference rules, and the identification of methodologies for the visualization of qualification outcomes and curricula

The increasing popularity of robotics and related applications in modern society makes interacting and communicating with robots of crucial importance. In service robotics, where robots operate to assist human beings in their daily life, natural interaction paradigms capable to foster an ever more intuitive and effective collaboration between involved actors are needed. The aim of this paper is to discuss activities that have been carried out to create a 3D immersive simulation environment able to ease the design and evaluation of natural human-robot interfaces in generic usage contexts. The proposed framework has been exploited to tackle a specific use case represented by a robotics-enabled office scenario and to develop two user interfaces based on augmented reality, speech recognition as well as gaze and body tracking technologies. Then, a user study has been performed to study user experience in the execution of semi-autonomous tasks in the considered scenario though both objective and subjective observations. Besides confirming the validity of the devised approach, the study provided precious indications regarding possible evolutions of both the simulation environment and the service robotic scenario considered.

The ability to plan a training path fulfilling working needs plays a key role, when it comes to finding the desired job. Nonetheless, in a dynamic scenario characterized by frequent technological innovations and economic changes, as the present one, getting a clear picture of the requirements of the world of work could become difficult, as it would imply performing a deep periodic evaluation of available job offers, and matching them with own previous experience. Intelligent systems able to automatically match résumés with job offers already exist, but they are mostly targeted to recruiters, instead of learners. This work aims at filling this gap, by presenting a system for comparing learners' acquirements - expressed in terms of learning outcomes - with companies requirements. The proposed system relies on semantics for processing natural language texts and exploits bar charts to visualize learning outcomes and their levels in order to quickly depict similarities and differences between résumés and job offers. An evaluation, conducted on 50 volunteers, underlined the added value of the system.

The fast pace of change in high technology product development requires high flexibility and adaptation in product design and technology management. Within this context, appropriate learning environments are planned to shape future Information and Communication Technology staff in such a way they could get able to keep up with new trends and innovations. A constructivist educational model based on Active Learning represents a step towards this vision for staff training. This paper deals with a new organization of a 13 weeks course based on the inverted class model, where students are introduced to the problem-posing domain by a direct involvement of enterprises, which participate specifically to the problem definition and assessment phases. In the case study shown, students simulate a production business unit in all the phases that characterize the product/service development life cycle. A mixed traditional and company-based organization of the course is supposed to improve students competences by proposing solutions leveraging on appropriate tools taken from traditional experiences and also gaining benefits from a learning-by-doing approach that encourages the use of state-of-the-art solutions. A preliminary study is performed to see how expected professional competences are met during the course, with the additional goal of collecting indications that could help to improve the learning framework for future editions of the course

Drone-based delivery of goods could become a reality in the near future, as witnessed by the increasing successful experiences in both research and commercial fields. In this paper, a prototype system exploiting a do it yourself quad copter drone for delivering products is proposed. On the one hand, the hardware choices made in order to limit risks arising from autonomous delivery are presented. On the other hand, a framework for orders placement and shipment is shown. The advantages of a system like the one described in this paper are mainly related to an increased delivery speed, especially in urban contexts with traffic, to the possibility to make deliveries in areas usually difficult to be reached, and to the drone's ability to autonomously carry out consignments. A practical use case, in which the proposed system is used for delivering drugs (an application in which the need to quickly receive the good might be particularly important) is shown. Nevertheless, the proposed prototype could be employed in other contexts, such as take-away deliveries, product shipments, registered mail consignments, etc

The availability of annotated multimedia contents is a crucial requirement for a number of applications. In the context of education it could support the automatic summarization of recorded lessons or the retrieval of learning material. In the field of entertainment, it could serve to recommend audio and video resources based on user's attitudes. In this work, a framework supporting video viewing experience augmentation on mobile devices by means of image- and text-based annotations extracted on-demand from Wikipedia is presented. Speech recognition is exploited to periodically get text snaps from the audio track of the video currently displayed on the mobile device, while query-by-images is used to generate a text summary of extracted video frames. Keywords obtained are treated by semantic techniques to find named entities associated with the multimedia contents, which are then superimposed to the video and displayed to the user in a synchronized way. Promising results obtained with a prototype implementation showed the feasibility of the proposed solution, which could be possibly combined with other systems, e.g., providing information about user's location, preferences, etc. to build up more sophisticated context-aware applications

Students and learners mobility is more and more becoming a praxis. Nonetheless, despite the legislative efforts carried out by the European Commission, devoted to the definition of standards for describing qualifications, the comparison of qualifications contents, for instance in the phases of identification of more suitable training to attend abroad, or during the recognition of prior learning, still requires a considerable amount of efforts and time. This difficulty could be mainly attributed to the fact that qualification contents are usually expressed heterogeneously. In this work, a way to tackle this heterogeneity, by relying on a semantic thesaurus for graphically displaying main similarities and dissimilarities among qualifications is presented. By means of such representation, users could quickly become aware of the main characteristics of a training course, with respect to the others, without having to read all the textual information related to them

Citizens' mobility and employability are receiving ever more attention by the European legislation. Various instruments have been defined to overcome lexical and semantic differences in the descriptions of qualifications, résumés and job profiles. However, the above differences still represent a significant constraint when abilities of non-European people have to be validated either for education and training or occupation purposes. In this work, a web platform that exploits semantic technologies to address such heterogeneity issues is presented. The platform allows migrants to annotate their knowledge, skills and competences in a shared format based on the European tools. The resulting knowledge base is then used to enable the automatic matchmaking of job seekers' abilities with companies' needs. The platform can additionally be used to support students and workers in the identification of their competence gap with respect to a given education or occupation opportunity, so that to personalize their further training

La mobilità di lavoratori e studenti rappresenta oggi un obiettivo di primaria importanza, in particolare nel contesto della istruzione e formazione professionale. Ciononostante, sebbene a livello Europeo siano stati sviluppati alcuni importanti strumenti a supporto della mobilità, esistono tuttora significative barriere che ostacolano la realizzazione di una concreto spazio comune del lavoro e dell'educazione. Una possibilità per superare le suddette limitazioni consiste nella creazione di profili professionali con validità trans-nazionale o trans-settoriale, che possano essere utilizzati dagli organismi di formazione e dagli attori di riferimento dei diversi settori economici per il raccordo tra qualifiche nazionali, regionali o settoriali. In questo lavoro viene illustrata una metodologia che sfrutta un approccio derivato da web semantico basato su ontologie e tassonomie per identificare un profilo comune Europeo nel settore del commercio e per raccordare singoli profili e qualifiche al Quadro Europeo delle Qualifiche a supporto della crescita di un mondo della formazione efficacemente connesso a quello del lavoro in una reale dimensione Europea

The labor market is today characterized by a marked competitiveness. The ability to accurately choose the right education and training paths leading to the acquisition of the right competences required for a given job position, as well as the capability to properly select human resources based on precise job requirements are becoming more and more key factors to success. Nevertheless, the comparison of education opportunities generally requires a manual analysis of huge qualification descriptions and course syllabi, whereas staff selection (or job seeking activities) often relies on non-automated processes mainly based on an extensive check of applicants' curriculum vitae (or of possible job offers). The above tasks are extremely time consuming and, given the large amount of information to be considered, they also risk to provide unsatisfactory results. In this paper, the above issues are addressed in the perspective of semantic technologies. In particular, a webbased application is presented, which exploits ontological descriptions and tag cloud-based visualization strategies to generate a direct representation of the overlap between learners' needs and existing education and training paths, as well as between job seekers' profiles and company requirements. This way, potential users are provided with an effective support for matching job and study offers with corresponding demands

Students and workers mobility in the European scenario represents today a big challenge. During the last years, several initiatives have been carried out to deal with the above picture, being the European Qualication Framework (EQF), a common architecture for describing qualications, one of the most signicant. In parallel, several research activities were established with the aim of exploiting semantic technologies for qualication comparison in the context of human resources acquisition. In this paper, the EQF specications are applied in a practical scenario to develop a ranking algorithm allowing for qualication comparison on the basis of knowledge, skill and competence concepts, potentially aimed at supporting European employers during the recruitment phases

Students' mobility is a relevant topic but, while in Higher Education transfers between Universities are a praxis, in Vocational Educational and Training are still a declaration of intent. The main obstacles are basically related to the heterogeneity of national qualification systems, and to the lack for definitive transparency measures. Although several European instruments are being introduced in this perspective (like the European Qualification Framework), the internationalization process is still in a preliminary phase. In this paper, a methodology exploiting formal descriptions for supporting the creation of mutual understanding and for defining transnational referencing rules is defined. Rules, developed by actors involved in VET provision, are then applied to a knowledge base hosting annotated national qualifications to experiment qualification comparison and to measure competence gap