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.

The collaboration between humans and robots is one of the most disruptive and challenging research areas. Even considering advances in design and artificial intelligence, humans and robots could soon ally to perform together a number of different tasks. Robots could also became new playmates. In fact, an emerging trend is associated with the so-called phygital gaming, which builds upon the idea of merging the physical world with a virtual one in order to let physical and virtual entities, such as players, robots, animated characters and other game objects interact seamlessly as if they were all part of the same reality. This paper specifically focuses on mixed reality gaming environments that can be created by using floor projection, and tackles the issue of enabling accurate and robust tracking of off-the-shelf robots endowed with limited sensing capabilities. The proposed solution is implemented by fusing visual tracking data gathered via a fixed camera in a smart environment with odometry data obtained from robot's on-board sensors. The solution has been tested within a phygital gaming platform in a real usage scenario, by experimenting with a robotic game that exhibits many challenging situations which would be hard to manage using conventional tracking techniques.

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.

This paper presents a framework for automatically generating speech-based interfaces for controlling virtual and augmented reality (AR) applications on wearable devices. Starting from a set of natural language descriptions of application functionalities and a catalog of general-purpose icons, annotated with possible implied meanings, the framework creates both vocabulary and grammar for the speech recognizer, as well as a graphic interface for the target application, where icons are expected to be capable of evoking available commands. To minimize user's cognitive load during interaction, a semantics-based optimization mechanism was used to find the best mapping between icons and functionalities and to expand the set of valid commands. The framework was evaluated by using it with see-through glasses for AR-based maintenance and repair operations. A set of experimental tests were designed to objectively and subjectively assess first-time user experience of the automatically generated interface in relation to that of a fully personalized interface. Moreover, intuitiveness of the automatically generated interface was studied by analyzing the results obtained through trained users on the same interface. Objective measurements (in terms of false positives, false negatives, task completion rate, and average number of attempts for activating functionalities) and subjective measurements (about system response accuracy, likeability, cognitive demand, annoyance, habitability, and speed) reveal that the results obtained by the first-time users and experienced users with the proposed framework's interface are very similar, and their performances are comparable with those of both the considered references.

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

Sensors are becoming ubiquitous in all areas of science, technology, and society. In this Special Issue on \"Sensors for Entertainment\", developments in progress and the current state of application scenarios for sensors in the field of entertainment is explored

Advancements in input device and sensor technologies led to the evolution of the traditional human-machine interaction paradigm based on the mouse and keyboard. Touch-, gesture- and voice-based interfaces are integrated today in a variety of applications running on consumer devices (e.g., gaming consoles and smartphones). However, to allow existing applications running on desktop computers to utilize natural interaction, significant re-design and re-coding efforts may be required. In this paper, a framework designed to transparently add multi-modal interaction capabilities to applications to which users are accustomed is presented. Experimental observations confirmed the effectiveness of the proposed framework and led to a classification of those applications that could benefit more from the availability of natural interaction modalities

Robustly and efficiently tracking pedestrians in the infrared spectrum is a crucial requirement for a number of applications. At the same time, it is also particularly critical due to both the peculiarities of infrared images and pedestrian targets. In fact, low resolutions and high signal-to-noise ratios combined with extremely variable target signatures, chaotic trajectories, and frequent occlusions have forced researchers to develop ever more complex strategies characterized by a neat trade-off between tracking accuracy and computational complexity. Thus, most of the existing techniques might not be capable of ensuring real-time performances with a suitable degree of robustness, especially on limited-resource hardware used, e.g., in automotive or security scenarios. We present a technique that extends an extremely efficient tracking method originally tailored to targets that exhibit a clear and stable hot spot to allow it to deal with pedestrian targets by reusing its core components and integrating an occlusion detection and recovery mechanism. Experimental results obtained on public datasets confirmed that the devised method is able to obtain a robustness that is superior to that of other common approaches by maintaining the high tracking speed of the reference method

Motion capture systems provide an efficient and interactive solution for extracting information related to a human skeleton, which is often exploited to animate virtual characters. When the character cannot be assimilated to an anthropometric shape, the task to map motion capture data onto the armature to be animated could be extremely challenging. This paper presents two methodologies for the automatic mapping of a human skeleton onto virtual character armatures. Kinematics chains of the human skeleton are analyzed in order to map joints, bones and end-effectors onto an arbitrary shaped armatures. Both forward and inverse kinematics are considered. A prototype implementation has been developed by using the Microsoft Kinect as body tracking device. Results show that the proposed solution can already be used to animate truly different characters ranging from a Pixar-like lamp to different kinds of animals

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

Here we give context to the Special Issue on \"Detection and Tracking of Targets in Forward-Looking InfraRed (FLIR) Imagery\" in Sensors. We start with an introduction to the role of infrared images in today's vision-based applications, by outlining the specific challenges that characterize detection and tracking in FLIR images. We then illustrate why selected papers have been chosen to represent the domain of interest, by summarizing their main contributions to the state-of-the-art. Lastly, we sum up the main evidence found, and we underline some of the aspects that are worthy of further investigation in future research activities

Assessment is a delicate task in the overall teaching process because it may require significant time and may be prone to subjectivity. Subjectivity is especially true for disciplines in which perceptual factors play a key role in the evaluation. In previous decades, computer-based assessment techniques were developed to address the above-mentioned challenges and to automatically grade students' work in a variety of educational fields. In this paper, the application of automatic assessment strategies in the unexplored domain of computer graphics is discussed. In particular, a tool that is designed to evaluate student assignments for a 3D computer animation course taught at Politecnico di Torino University is presented. During laboratory examination sessions, students are requested to individually operate on the open-source Blender suite and to recreate a 3D animation similar to a reference one. Student's output is assessed against a set of similarity indicators, which are specifically designed to capture the technical and perceptual factors that would be blended in a traditional teacher's evaluation. A comparison of the results that are achieved by the computer-based tool with grades assigned by visual inspection confirms the effectiveness of the designed approach and displays a high-quality concurrence between automatic and manual evaluations

Augmented reality (AR) is a well-known technology that can be exploited to provide mass-market users an effective and customizable support in a large spectrum of personal applications, by overlapping computer-generated hints to the real world. Mobile devices, such as smartphones and tablets, are playing a key role in the exponential growth of this kind of solutions. Nonetheless, there exists some application domains that just started to take advantage from the AR systems. Maintenance, repair, and assembly have been considered as strategic fields for the application of the AR technology from the 1990s, but often only specialists using ad hoc hardware were involved in limited experimental tests. Nowadays, AR-based maintenance and repair procedures are available also for end-users on consumer electronics devices. This paper aims to explore new challenges and opportunities of this technology, by also presenting the software framework that is being developed in the EASE-R3 project by exploiting reconfigurable AR procedures and tele-assistance to overcome some of the limitations of current solutions

The automatic extraction of objective features from paintings, like brushstrokes distribution, orientation and shape, could be particularly useful for different artwork analysis and management tasks. In fact, these features contribute to provide a unique signature of the artists' style and can be effectively used for artist identification and classification, artwork examination and retrieval, etc. In this paper, an automatic technique for unsupervised extraction of individual brushstrokes from digital reproductions of van Gogh's paintings is presented. Through the iterative application of segmentation, characterization and validation steps, valid brushstrokes complying with specific area and shape constraints are identified. On the extracted brushstrokes, several representative features can then be calculated, like orientation, length and width. The accuracy of the devised method is evaluated by comparing numerical results obtained on a dataset of digital reproductions of van Gogh's oil-on-canvas works with observations made by human subjects and with another recent approach for automatic brushstrokes analysis. Experimental tests showed that the devised methodology produces results that are rather close to those obtained by human subjects and, for some of the metrics considered, can provide improved performances with respect to alternative techniques

Tracking pedestrian targets in forward-looking infrared video sequences is a crucial component of a growing number of applications. At the same time, it is particularly challenging, since image resolution and signal-to-noise ratio are generally very low, while the nonrigidity of the human body produces highly variable target shapes. Moreover, motion can be quite chaotic with frequent target-to-target and target-to-scene occlusions. Hence, the trend is to design ever more sophisticated techniques, able to ensure rather accurate tracking results at the cost of a generally higher complexity. However, many of such techniques might not be suitable for real-time tracking in limited-resource environments. This work presents a technique that extends an extremely computationally efficient tracking method based on target intensity variation and template matching originally designed for targets with a marked and stable hot spot by adapting it to deal with much more complex thermal signatures and by removing the native dependency on configuration choices. Experimental tests demonstrated that, by working on multiple hot spots, the designed technique is able to achieve the robustness of other common approaches by limiting drifts and preserving the low-computational footprint of the reference method.

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

Existing tracking methods designed for interacting with projection-based displays generally require visible artifacts to be introduced in the environment in order to guarantee effective stability and accuracy. For instance, in optical-oriented approaches, either the camera sensor or the reference pattern used for tracking are often located within the user's sight (or interfere with it), thus occluding portions of the scene or altering the perception of the virtual environment. Several ways to tackle these issues have been recently explored. Proposed approaches basically aim at making the presence of tracking references in the virtual space transparent to the user. However, such solutions introduce possibly critical constraints on required hardware or environment configuration. In this work, a novel tracking approach based on imperceptible fiducial markers is proposed. The approach relies on a hiding technique that allows digital images to be embedded in (and retrieved from) a projected scene by exploiting the properties of light polarization and additive color mixing. In particular, the virtual scene is obtained by overlapping the light beams of two projectors and by dealing with markers' hiding via color compensation. A prototype setup has been deployed, where interaction with a flat surface projection environment has been evaluated in terms of tracking accuracy and artifacts avoidance performance by using a consumer camera equipped with a polarizing filter. Although the performed tests presented in this article represent only a preliminary and a partial evaluation of the proposed approach, they provided encouraging results indicating that the proposed technique could be possibly applied in more complex interaction scenarios still with limited hardware requirements

Most virtual characters' animations are based on armatures to manipulate the characters' body parts (rigging). Armatures behave as the characters' skeletons, and their segments are referred to as bones. Each bone of the skeleton is associated with a well defined set of vertices defining the character' mesh (skinning), thus allowing animators to control movements and deformations of the character itself. This paper presents a natural and intuitive interface, which uses the Microsoft Kinect, to interactively control an armature by tracking body poses. Animators can animate virtual characters in real-time by their own body poses, thus obtaining realistic and smooth animations. Moreover, the proposed interface allows animators to save time with respect to the traditional animation technique based on keyframing. Different examples are used to compare the Kinect-based interface with the keyframing approach, thus obtaining both an objective and a subjective assessment.

This paper presents a new and challenging approach to the control of mobile platforms. Natural user interfaces (NUIs) and visual computing techniques are used to control the navigation of a quadrotor in GPS-denied indoor environments. A visual odometry algorithm allows the platform to autonomously navigate the environment, whereas the user can control complex manoeuvres by gestures and body postures. This approach makes the human-computer interaction (HCI) more intuitive, usable, and receptive to the user's needs: in other words, more user-friendly and, why not, fun. The NUI presented in this paper is based on the Microsoft Kinect and users can customize the association among gestures/postures and platform commands, thus choosing the more intuitive and effective interface

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

The modular exponentiation on large numbers is computationally intensive. An effective way for performing this operation consists in using Montgomery exponentiation in the Residue Number System (RNS). This paper presents an algorithmic and architectural study of such exponentiation approach. From the algorithmic point of view, new and state-of-the-art opportunities that come from the reorganization of operations and precomputations are considered. From the architectural perspective, the design opportunities offered by well-known computer arithmetic techniques are studied, with the aim of developing an efficient arithmetic cell architecture. Furthermore, since the use of efficient RNS bases with a low Hamming weight are being considered with ever more interest, four additional cell architectures specifically tailored to these bases are developed and the tradeoff between benefits and drawbacks is carefully explored. An overall comparison among all the considered algorithmic approaches and cell architectures is presented, with the aim of providing the reader with an extensive overview of the Montgomery exponentiation opportunities in RNS.

Wireless communication advances have enabled emerging video streaming applications to mobile handheld devices. For example, it is possible to display and interact with complex 3D virtual environments on mobile devices that don't have enough computational and storage capabilities (e.g. smart phones, PDAs) through remote rendering techniques, where a server renders 3D data and streams the corresponding image flow to the client. However, due to fluctuations in bandwidth characteristics and limited mobile device CPU capabilities, it is extremely challenging to design effective systems for streaming interactive multimedia over wireless networks. This paper presents a novel approach based on a controller that can automatically adjust streaming parameters basing on feedback measures from the client device. Experimental results prove the effectiveness of the proposed solution in coping with bandwidth changes, thus providing high Quality of Service (QoS) in remote visualizations

This paper presents a system to track position and orientation of a generic mobile device equipped with a camera using a set of variable size fiducial markers. The system provides six degrees-of-freedom (6-DOF) by tracking fiducial markers through the camera and deriving the position and orientation of the device, thus making possible the implementation of innovative and affordable 3D user interfaces. The system has been integrated in a Cave Automatic Virtual Environment (CAVE) through the use of projectors and polarizers.

Automatic target tracking in forward-looking infrared (FLIR) imagery is a challenging research area in computer vision. This task could be even more critical when real-time requirements have to be taken into account. In this context, techniques exploiting the target intensity profile generated by an intensity variation function (IVF) proved to be capable of providing significant results. However, one of their main limitations is represented by the associated computational cost. In this paper, an alternative approach based on genetic algorithms (GAs) is proposed. GAs are search methods based on evolutionary computations, which exploit operators inspired by genetic variation and natural selection rules. They have been proven to be theoretically and empirically robust in complex space searches by their founder, J. H. Holland. Contrary to most optimization techniques, whose goal is to improve performances toward the optimum, GAs aim at finding near-optimal solutions by performing parallel searches in the solution space. In this paper, an optimized target search strategy relying on GAs and exploiting an evolutionary approach for the computation of the IVF is presented. The proposed methodology was validated on several data sets, and it was compared against the original IVF implementation by Bal and Alam. Experimental results showed that the proposed approach is capable of significantly improving performances by dramatically reducing algorithm processing time

Tracking targets in forward-looking infrared (FLIR) video sequences taken from airborne platforms is a challenging task. Several tracking failure modes can occur; in particular, discontinuities due to platform's motion can produce the so called ego-motion failure leading to unrecoverable errors in tracking the target. A novel ego-motion compensation technique for UAVs (unmanned aerial vehicles) is proposed. Data received from the autopilot can be used to predict the motion of the platform, thus allowing to identify a smaller region of the image (subframe) where the candidate target has to be searched for in the next frame of the sequence. The presented methodology is compared with a recently robust algorithm for automatic target tracking; experimental results show that the proposed motion estimation approach helps to improve performance both in terms of frames processed per second (targets are searched in smaller regions) and in terms of robustness (targets are correctly tracked for all the sequence's frames)

With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general-purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. The next-generation Web architecture, represented by the Semantic Web, provides the layered architecture possibly allowing overcoming this limitation. Several search engines have been proposed, which allow increasing information retrieval accuracy by exploiting a key content of Semantic Web resources, that is, relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper, we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information that could be extracted from user queries and on annotated resources. Relevance is measured as the probability that a retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition

This framework lets users easily and effectively use desktop applications on mobile devices without any redesign. An automatically generated description of the original interface lets the original application be recreated and migrated to nomadic scenarios. Users can also customize interfaces to suit their needs and match a device's capabilities

A radix-2 digit-recurrence algorithm and architecture for the computation of the cube root are presented in this paper. The original recurrence based on the concept of completing the cube is modified to allow an efficient implementation of the algorithm and the cycle time and area cost of the resulting architecture are estimated as 7.5 times the delay of a full adder and around 9,000 nandl cells, respectively, for double-precision computations

Mobile devices such as Personal Digital Assistants, Tablet PCs, and cellular phones have greatly enhanced user capability to connect to remote resources. Although a large set of applications are now available bridging the gap between desktop and mobile devices, visualization of complex 3D models is still a task hard to accomplish without specialized hardware. This paper proposes a system where a cluster of PCs, equipped with accelerated graphics cards managed by the Chromium software, is able to handle remote visualization sessions based on MPEG video streaming involving complex 3D models. The proposed framework allows mobile devices such as smart phones, Personal Digital Assistants (PDAs), and Tablet PCs to visualize objects consisting of millions of textured polygons and voxels at a frame rate of 30 fps or more depending on hardware resources at the server side and on multimedia capabilities at the client side. The server is able to concurrently manage multiple clients computing a video stream for each one; resolution and quality of each stream is tailored according to screen resolution and bandwidth of the client. The paper investigates in depth issues related to latency time, bit rate and quality of the generated stream, screen resolutions, as well as frames per second displayed

Global and local histogram equalization (HE) proved to be effective techniques for contrast enhancement. Local HE allows to achieve high contrast enhancement rates but its high computational complexity limits its applicability in many resource constrained scenarios. On the contrary, global HE complexity is relatively low but enhancement rate is often unsatisfactory. Recently, an algorithm exploiting a low-pass filter (LPF) mask to obtain a partially overlapped sub-block HE effect (POSHE) has been presented. POSHE allows to produce the high local HE contrast with the simplicity of global HE. In this paper a generalization of POSHE approach exploiting cascaded multistep binomial filtering HE (CMBFHE) in order to get the same LPF mask is proposed. By relying on the same filter mask, contrast enhancement capability of CMBFHE is exactly the same of POSHE. Additionally, results show that a significant speedup with respect to the previous fastest method is achieved because of the efficient implementation of the filtering approach; moreover hardware implementations can be effectively designed. This makes CMBFHE a suitable solution in all those consumer electronics related environments including camcorders, digital cameras and video surveillance where on-the-fly local-like contrast enhancement is required

In recent years many experimental investigations have been carried out on vasculogenesis and angiogenesis, the mechanisms of blood vessels formation. Neovascularization is a hallmark of embryogenesis and many other physiological processes, such as wound healing or endometrium vascularization during the mestrual cycle. Angiogenesis also plays a key role in tumor growth, tumor metastasis and other pathological processes including many inflammatory diseases. Understanding biological phenomena regulating angiogenesis is therefore essential for clinical treatment of cancer and other angiogenesis-dependent diseases. This paper describes the development of a fully-automated computerized angiogenesis analysis system, which enables angiogenesis parameters to be quantified in an in-vitro model. The proposed methodology works on phase contrast microscopy snap photographs of cultured endothelial cell plates, and extracts a detailed graph-based representation of the blood vessels network thus supporting accurate angiogenesis parameters measurement

The spread of robotics in many sectors of human life is driving researchers to focus more and more on human-robot interaction (HRI). This multidisciplinary field addresses all of the issues related to the interaction between robots and people. HRI incorporates contributions from artificial intelligence, cognitive science, human factors, psychology and social science, among others. This paper provides a summary of the main themes of HRI from the point of view of both technology and the user experience.

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.

Brain injury can cause a variety of physical effects and cognitive deficits. Although it has not yet been systematically adopted in clinical settings, virtual reality promises to be an excellent therapeutic tool for regaining both locomotor and neurological capacities. This work presents the design and implementation of VR2 (Virtual Reality Rehabilitation), a customizable rehabilitation framework intended to enable the creation of motivating rehabilitation scenarios based on an ecologically valid semi-immersive system. Following the implementation phase, a study to test the acceptability of VR2 in a group of subjects with cerebral lesions was conducted to investigate the usability of the framework. The group consisted of 11 people from 22 to 70 years of age, who were divided into two groups depending on the chronicity of disorder. The adequacy of the interface between patient and system was verified through questionnaires containing subjective questions, which revealed good overall acceptance and enjoyment of the tool. Moreover, to obtain early results useful for tuning the overall system in preparation for rigorous clinical trials, a set of preliminary cognitive tests concerning the rehabilitation protocol was conducted within the same group. Although the preliminary findings are promising and reveal a positive trend in neurocognitive investigations, the system should undergo clinical trials before being used in real clinical settings.

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

In recent years, unmanned aerial vehicles have received a significant attention in the research community, due to their adaptability in different applications, such as surveillance, disaster response, traffic monitoring, transportation of goods, first aid, etc. Nowadays, even though UAVs can be equipped with some autonomous capabilities, they often operate in high uncertainty environments in which supervisory systems including human in the control loop are still required. Systems envisaging decision-making capabilities and equipped with flexible levels of autonomy are needed to support UAVs controllers in monitoring operations. The aim of this paper is to build an adjustable autonomy system able to assist UAVs controllers by predicting mental workload changes when the number of UAVs to be monitored highly increases. The proposed system adjusts its level of autonomy by discriminating situations in which operators' abilities are sufficient to perform UAV supervision tasks from situations in which system suggestions or interventions may be required. Then, a user study was performed to create a mental-workload prediction model based on operators' cognitive demand in drone monitoring operations. The model is exploited to train the system developed to infer the appropriate level of autonomy accordingly. The study provided precious indications to be possibly exploited for guiding next developments of the adjustable autonomy system proposed.

The goal of desktop-class graphics hardware is generally to provide the maximum performances possible to end users. This goal is shared also by mobile hardware designers, although, due the use of a battery as power source, a greater attention needs to be devoted to energy saving. In the last years, a number of approaches to hardware design have been experimented aimed to trade-off the quality of the visual experience with the usage of computational resources, that is to say, with energy consumption. The objective of this work is to tackle energy issues at the software, i.e., at the application level, by introducing a high-level library based on OpenGL ES (often abbreviated GLES) that can be exploited by developers to create energy-aware graphics applications letting end users chose the maximum amount of energy to consume.

Commercial off-the-shelf (COTS) robots are becoming ever more ubiquitous. Among the most common applications there are toy robots. In order to keep their cost down, these robots are usually equipped with the minimum set of sensors necessary for their basic functioning. Specifically, to add entertainment value, they often feature a video camera and, in most of the games developed so far, players are basically tele-operating them through a smartphone app. The present paper aims to show how to provide existing consumer-grade robots with new capabilities to transform them in more appealing gaming companions. In particular, by considering as a test bench a wheeled, non-holonomic COTS robot whose only accessible sensor is a low-resolution camera, previously unavailable localization and autonomous navigation capabilities are developed for it by exploiting dead reckoning and artificial landmark detection algorithms. These capabilities could then be exploited to create new types of games, which can be played in free-scale unknown environments and feature new forms of interaction. Implementation details of a sorting game in which the robot acts as a referee are reported.

The increasing popularity of unmanned aerial vehicles (UAVs) in critical applications makes supervisory systems based on the presence of human in the control loop of crucial importance. In UAV-traffic monitoring scenarios, where human operators are responsible for managing drones, systems flexibly supporting different levels of autonomy are needed to assist them when critical conditions occur. The assessment of UAV controllers' performances thus their mental workload may be used to discriminate the level and type of automation required. The aim of this paper is to build a mental-workload prediction model based on UAV operators' cognitive demand to support the design of an adjustable autonomy supervisory system. A classification and validation procedure was performed to both categorize the cognitive workload measured by ElectroEncephaloGram signals and evaluate the obtained patterns from the point of view of accuracy. Then, a user study was carried out to identify critical workload conditions by evaluating operators' performances in accomplishing the assigned tasks. Results obtained in this study provided precious indications for guiding next developments in the field.

Continuous advancements in the field of robotics and its increasing spread across heterogeneous application scenarios make the development of ever more effective user interfaces for human-robot interaction (HRI) an extremely relevant research topic. In particular, Natural User Interfaces, e.g., based on hand and body gestures, proved to be an interesting technology to be exploited for designing intuitive interaction paradigms in the field of HRI. However, the more sophisticated the HRI interfaces become, the more important is to provide users with an accurate feedback about the state of the robot as well as of the interface itself. In this work, an Augmented Reality (AR)-based interface is deployed on a head-mounted display to enable tele-operation of a remote robot team using hand movements and gestures. A user study is performed to assess the advantages of wearable AR compared to desktop-based AR in the execution of specific tasks.

The use of virtual reality (VR) is widespread in a growing number of application domains. Continuous technological advancements in the field of computer graphics made VR an interesting tool for learning purposes, especially in sport. Examples can be found in different sports such as rugby, baseball, soccer, golf, etc. This paper presents a VR-based training system that can be used as a self-learning tool to improve the execution of a given technical gesture. In particular, the basketball free throw gesture is considered. To assess the usefulness of the proposed system, experimental tests were carried out in a small-scale setup by involving 18 non-skilled volunteers. Results demonstrated that the designed system can improve the execution of the considered gesture in terms of both timing and spatial positioning compared to an alternative technique based on video projection.

Providing an effective cognitive aid to both lay people and healthcare providers in Basic Life Support and Defibrillation (BLSD) procedures is a relevant educational goal in resuscitation. A self-instruction learning simulation program was developed to maximize learning results, helping to enhance motor skills and the retention of cognitive knowledge, reduce instructor intervention and cost. Microsoft HoloLens technology was used, enabling users to interact with high definition holograms. Holo-BLSD was developed as a mixed reality (MR) self-instruction training environment allowing also assessment, using a standard low-cost CPR manikin to deliver tactile information. The manikin was \"augmented\" by an interactive virtual environment reproducing realistic scenarios. Learners used natural gestures, body movements and spoken commands to perform their tasks, with virtual 3D objects anchored to the manikin and to the environment. We believe such a project is the first in the domain of BLSD.

The preparation of a set for a television production is a complex work; usually, several objects have to be manually placed in the environment and the configuration might be changed many times before finding the final set up. This configuration phase can be expensive and time consuming when large and heavy objects have to be moved. In order to tackle this issue, virtual sets allow the director of production to create virtual scenes before placing real objects. This paper proposes an alternative approach based on augmented reality technologies: objects of the scene are computer generated assets, which can be placed and manipulated in a real environment. With respect virtual sets, the proposed solution allows the director to move in a real scene enriched by computer-generated objects to be placed in the environment. The user wears an AR headset and manipulates objects by a tablet. The proposed system was evaluated by a group of 9 testers, which had to create an augmented TV set. Subjective and objective parameters have been used to assess the system usability.

In the last years, robotic telepresence solutions have received a significant attention from both the commercial and academic worlds, due to their ability to allow people to feel physically present at a remote place and move in it. Operating a mobile robot with some autonomous capabilities from distance can enable a wide range of mass-market applications, encompassing teleconferencing, virtual tourism, etc. In these scenarios, the possibility to interact with the robot in a natural way becomes of crucial importance. The aim of this paper is to investigate, through a comparative analysis, the usability of two major approaches used today for controlling telepresence robots, i.e., keyboard and point-and-click video navigation. A control system featuring the above interfaces plus a combination of the two has been developed, and applied to the operation of a prototype telepresence robot in an office scenario. The system additionally includes functionalities found in many research and industry solutions, like map-based localization and \"augmented\" navigation. Then, a user study has been performed to assess the usability of the various control modalities for the execution of some navigation tasks in the considered context. The study provided precious indications to be possibly exploited for guiding next developments in the field.

Using digital instruments to support artistic expression and creativity is a hot topic. In this work, we focused on the design of a suitable interface for Augmented Reality-based constructive art on handheld devices. Issues to be faced encompassed how to give artists sense of spatial dimensions, how to provide them with different tools for realizing artworks, and how much moving away from ``the real'' and going towards ``the virtual''. Through a touch-capable device, such as a smartphone or a tablet, we offer artists a clean workspace, where they can decide when to introduce artworks and tools. In fact, besides exploiting the multi-touch functionality and the gyroscopes/accelerometers to manipulate artworks in six degrees of freedom (6DOF), the proposed solution exploits a set of printed markers that can be brought into the camera's field of view to make specific virtual tools appear in the augmented scene. With such tools, artists can decide to control, e.g., manipulation speed, scale factor, scene parameters, etc., thus complementing functionalities that can be accessed via the device's screen.

The continuous progress in the field of robotics and the diffusion of its related application scenarios in today's modern world makes human interaction and communication with robots an aspect of fundamental importance. The development of interfaces based on natural interaction paradigms is getting an increasingly captivating topic in Human-Robot Interaction (HRI), due to their intrinsic capabilities in providing ever more intuitive and effective control modalities. Teleoperation systems require to handle a non-negligible amount of information coming from on-board sensors as well as input devices, thus increasing the workload of remote users. This paper presents the design of a 3D User Interface (3DUI) for the control of teleoperated robotic platforms aimed at increasing the interaction efficiency. A hand gesture driven controller is used as input modality to naturally map the position and gestures of the user's hand to suitable commands for controlling the platform components. The designed interface leverages on mixed reality to provide a visual feedback to the control commands issued by the user. The visualization of the 3DUI is superimposed to the video stream provided by an on-board camera. A user study confirmed that the proposed solution is able to improve the interaction efficiency by significantly reducing the completion time for tasks assigned in a remote reach-and-pick scenario.

Augmented Reality (AR) is expected to change the way we play, by transforming the world around us in an incredibly rich gaming environment. In this work, connected robots and natural interaction means are combined with projected AR to create a gaming experience more physical and engaging.

A 3D User Interface for manipulating virtual objects in Augmented Reality scenarios on handheld devices is presented. The proposed solution takes advantage of two interaction techniques. The former (named ``cursor mode'') exploits a cursor, which position and movement are bound to the view of the device; the cursor allows the user to select objects and to perform coarse-grain manipulations by moving the device. The latter (referred to as ``tuning mode'') uses the physical affordances of a tangible interface to provide the user with the possibility to refine objects in all their aspects (position, rotation, scale, color, and so forth) with a fine-grained control

Interacting with 3D contents is a challenging task and the implementation of natural and effective interfaces is usually demanded to computer programmers. On the other hand, exhibit designers would greatly take advantage of graphic tools able to completely hide technical details and code programming. This paper presents a graphic editor where interface designers can intuitively link objects, gestures and actions together, without needing computer science skills. Tests show the advantages of the proposed solution both for experts and beginners; moreover, a real example concerning the exhibit of the digital Nefertiti's bust within a holographic case controlled by hand gestures has been implemented.

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.

Several virtual and augmented reality tasks involve users in hands-free interactions; in this case, speech-based systems are often preferred for their intuitiveness and naturalness. On the other hand, the robustness of this kind of interfaces can be an issue, thus affecting both the usability and the user experience, when they are used in noisy environments. This paper proposes a one switch interface triggered by vocal commands: three different scanning algorithms are tested. With this kind of interface users can sequentially select the desired command, thus improving the robustness of traditional speech recognition-based interfaces. Latency time is an issue for one switch interfaces, but it is shown how a bidirectional scanning algorithm based on a non binary switch can strongly mitigate this problem. Vocal one switch (VOS) interfaces are compared with a traditional multi-word speech interface both objectively (in terms of robustness and efficiency) and subjectively (user feedback).

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

This paper studies the opportunities coming from the use of consumer devices like smartphones and tablets to perform maintenance and assembly procedures with Augmented Reality (AR). Pros and cons are evaluated by comparing completion times and errors made while executing a maintenance procedure with an AR-based tool and paper-based instructions

Knowing how users interact with Web contents is essential in order to design more effective Web pages and sites. A way to get the data needed for studying Web activity is via analytics tools that, given the amount of information to be processed, generally support the interpretation of results via graphics representations of either raw or aggregated data. With aggregated data, it is quite common to use heat maps, i.e., visual diagrams where colors can depict, among others, the amount of clicks/taps on a given region of the Web page or the areas that are reached more frequently when the page is scrolled. However, existing viewport-based solutions are not designed to aggregate data about the areas that received users' attention when page visualization may change from one device to another. In this paper, a framework capable to support a better understanding of a Web page as a unique information container by collecting information about mobile users' activity on multiple devices and visualizing it in an aggregated map on a per-element rather than a per-region basis is reported.

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

Augmented Reality (AR) has been proved to be an effective tool to improve and enhance the learning experience of students. On the other hand, issues regarding the inflexibility of AR contents can strongly limit the usability of AR applications in education. This paper presents results obtained by using the AR framework designed and developed for the EASE-R3 European project and focused on the generation of maintenance procedures for machine tools. The high system flexibility allows instructors to easily make maintenance procedures suitable for the skill level of technicians to be trained. A case study is presented and results gathered so far analyzed and assessed

This paper presents a new architecture supporting the development of enhanced reading applications. It exploits the thin-client paradigm to let the authors produce interactive components to be embedded in today e-books, thus enriching text contents with focused and customized graphics widgets generated from the interface of existing programs running in remote

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

The widespread adoption of mobile devices is giving everyone access to augmented reality systems, possibly involving a huge number of people in AR-based apps, with a pervasive social impact that cannot be neglected. AR systems are becoming affordable to everyone and especially useful in the maintenance field. This report aims to describe in a clear and accessible way the workflow to design and develop an augmented reality (AR) application for supporting maintenance procedures. The main focus of this paper is the evaluation of markerless tracking systems, as they could provide environment-independent solutions. The tests performed on a real use case outline the robustness of 3D CAD tracking with respect to other solutions

Motion capture systems provide an efficient and interactive solution for extracting information related to a human skeleton, which is often exploited to animate virtual characters. When the character can- not be assimilated to an anthropometric shape, the task to map mo- tion capture data onto the armature to be animated could be extremely challenging. This paper presents a novel methodology for the automatic mapping of a human skeleton onto virtual character armatures. By ex- tending the concept of graph similarity, joints and bones of the tracked human skeleton are mapped onto an arbitrary shaped armature. A pro- totype implementation has been developed by using the Microsoft Kinect as body tracking device. Preliminary results show that the proposed so- lution can already be used to animate truly different characters such as a Pixar-like lamp, a fish or a dog.

This work describes the \"CSCT Living Lab\", where a new approach to learning, based on computational thinking and inquiry-based science, is practiced and shaped. Ten high schools, together with seven technical institutions and other three, chosen among vocational ones, have been involved. All these members, represented by teachers interested in joining the process, gave life to the lab, where enhanced scenarios for learning are planned, implemented and traced. An abstraction model is also proposed, to promote a collaborative learning context for teachers and students, derived from effective experiences carried out at University and Politecnico di Torino. A specific example, coming from process control domain, is described to show part of the scenario adopted to make inter-disciplinary learning a sustainable and effective experience

In this paper, a framework allowing to extend the applicability of natural user interaction techniques to existing programs is presented. Body gestures captured by a depth camera are mapped to application commands, and a wide set of common desktop applications can be controlled without any code rewriting

In this work, the energy cost for 3D graphics processing on consumer devices is analyzed, and a framework mixing local and remote visualization techniques to trade off between rendering performances and power saving is proposed

The evolution of input device technologies led to identification of the natural user interface (NUI) as the clear evolution of the human-machine interaction, following the shift from command-line interfaces (CLI) to graphical user interfaces (GUI). The design of user interfaces requires a careful mapping of complex user \"actions\" in order to make the human-computer interaction (HCI) more intuitive, usable, and receptive to the user's needs: in other words, more user-friendly and, why not, fun. NUIs constitute a direct expression of mental concepts and the naturalness and variety of gestures, compared with traditional interaction paradigms, can offer unique opportunities also for new and attracting forms of human-machine interaction. In this paper, a kinect-based NUI is presented; in particular, the proposed NUI is used to control the Ar.Drone quadrotor

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

In recent years there has been an increasing effort in investigating integrated solutions to reduce energy consumption levels in different domains. In this perspective, tools thought as a support for the simulation and experimentation of energy saving strategies could constitute a valid help both in the design and validation phases. Within the above scenario, this paper presents a framework for monitoring, simulating and controlling energy-aware street lighting systems capable of optimizing their energy consumption levels based on environmental conditions and established lighting policies. The devised system allows operators to visually inspect (and control) the power saving impact of specific dimming rules in both monitored and simulated environments through the use of advanced 3D vision and interaction capabilities. In fact, a virtual interface is able to recreate the lighting effect within digital city environments, which can be explored by using immersive stereoscopic techniques. Moreover, natural user interfaces based on the recognition of user gestures and poses and voice commands are exploited to improve virtual navigation of the lighting infrastructures. By addressing all the presented aspects, the proposed system aims at constituting an effective tool to develop and analyze energy saving solutions in the domain of (but not necessarily limited to) future public street lighting.

This paper presents a framework for controlling remote applications by means of personalized multi-touch interfaces. The designed framework allows end-users to fully personalize the mapping between gestures and input commands. A two-tier architecture has been developed. A formal description of the original interface is automatically generated at the server side to identify a set of available actions for controlling existing applications. The client is in charge of loading the description of the target application, allowing the user to shape the preferred mapping between gestures and actions. Finally, the server converts the identified actions into one or more commands understandable by the original computer interface. The implementation of the system for this work specifically relies on handheld multi-touch devices. Test results are encouraging, both from an objective and a subjective point of view; indeed, the designed framework resulted to outperform a traditional GUI both in terms of number of actions to perform a task and average completion time

Cloud computing is regarded to as an impressive technology, as software and hardware resources become invisible to the users (they \"fade\" in the cloud), and they replaced by services. In this sense, cloud computing can be considered as an evolution of former virtualization approaches, with service providers delivering on-demand access to various back-end frameworks and front-end applications. This approach requires to strongly trust these providers, as users are forced to give up control on programs and data that were previously hosted on their machines. A possible way to alleviate this drawback could be to enable users \"participate\" to the cloud with their own applications, thus creating \"personal\" clouds, which could be even shared with other users. In this paper, we present a prototype implementation of the above idea, which consists of a framework that allows today's applications to be put into the cloud by exploiting user interface automation and accessibility information embedded in modern window-based graphics toolkits

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

This paper presents a framework enabling 6-DOF interaction with generic visualization environments through mobile devices. Features computed on image frames captured by on-board camera are used to develop an affordable and effective 3D user interface

La realizzazione di reti per illuminazione stradale basate su tecnologie innovative e su soluzioni di monitoraggio e controllo intelligenti può indubbiamente contribuire ad una gestione più razionale ed efficiente delle risorse energetiche. In questo lavoro viene presentata una piattaforma software basata su soluzioni web e su tecniche di computer grafica e realtà virtuale progettata per la simulazione e la supervisione remota di infrastrutture pubbliche di illuminazione basate su punti luce a LED intelligenti in uno scenario di città digitale

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

The application of computer graphics techniques to the creation of digital city environments is receiving increasing attention in the last years. This is in part due to the fact that, by mixing heterogeneous components like geographic information systems, virtual model repositories and smart sensor networks, digital cities are expected to be able to allow the various stakeholders involved in urban planning and management to effectively design, monitor and operate present as well as future city infrastructures. In this work, a software framework exploiting web and virtual reality technologies to remotely manage a network of LED-based smart luminaries is presented. The integration of public lighting systems into the digital city picture is considered of particular interest, since through these novel solutions, forthcoming intelligent lighting networks could be supervised in an integrated way, and specific safety, security and energy saving policies could be easily implemented

This paper describes a novel method to detect false alarms in target tracking applications based on image-based feature descriptors. The number of matches between the local feature descriptors in the reference target and in the candidate target is used to assess the reliability of the tracking algorithm used and, in case, to activate a suitable recovery mechanism. The proposed approach has been evaluated on a series of Forward Looking Infrared (FLIR) sequences provided by the U.S. Army Aviation and Missile Command (AMCOM)

A wide variety of remotely controlled mobile robots have been developed in the past. Despite the evolution in robotics functionalities, not much effort has been made to customize control interfaces to meet user preferences and needs. General users can find difficulties in controlling mobile robots by standard interfaces. On the other hand, recent advances in multi-touch devices now allow researchers to design and implement intuitive and user friendly interfaces. This paper presents recent efforts to control mobile platforms by using customizable multi-touch gestures drawn on a commonly available hand-held device. In particular, a live stream video coming from an on board camera allows both to automatically and manually control the platform to accomplish target tracking and following tasks

This paper presents a solution to control mobile robots by using customizable haptic and multi-touch gesture interfaces on handheld devices. Images coming from a camera allows both to automatically and manually control the robot

Wireless communication advances enable emerging video streaming applications to mobile handheld devices. For example, it is possible to show and interact with a complex 3D virtual environment on a \"thin\" mobile device through remote rendering techniques, where a rendering server is in charge to render 3D data and stream the corresponding image flow to the demanding client. However, due to bandwidth fluctuating characteristics and limited mobile device CPU capabilities, it is extremely challenging to design effective systems for interactive streaming multimedia over wireless networks. This paper presents a novel approach based on a controller able to automatically adjust streaming parameters basing on feedback measures coming back from the client device. Experimental results prove the effectiveness of the proposed solution to cope with bandwidth changes, thus providing a high Quality of Service (QoS) in remote visualizations.

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

This work presents the methodology used to leverage ontologies for the vocational education & training (VET) domain under an European context.The ontology use provides a means to tackle the problem of information integration of the qualification systems on each country, allowing a common data access. The project involved qualification systems at post-secondary non-academic level of diverse EU countries, formalizing their profiles, activities, competences, learning outcomes, etc. In particular, the Dutch system is used as study case

The present work describes the work carried out in the EU LdV HELeN Projec regarding the use of web ontologies as a way to tackle the qualification systems? integration for enabling transparency and mobility of students at European level. Qualification systems at post-secondary non-academic level of nine EU countries have been formalized in terms of profile, activities, competences, learning outcomes, etc. first using UML for a human-readable model and then using OWL for a machine-processable one. In addition, concrete qualification profiles have been used as study case to validate the ontology correctness

This work presents the use of ontologies as a way to tackle the problem of integration of qualification systems in order to enable the transparency and mobility of students at European level. For this, qualification systems at post-secondary non-academic levels of nine EU countries have been formalized in terms of profile, activities, competences, learning outcomes, etc., first using UML for a human-readable model and then using OWL for a machine-processable one. In addition, concrete qualification profiles have been used as a case study to check the models' correctness

This paper investigates the problem of tracking individual circular cell nuclei of endothelial cells during their migration. The purpose is to extract statistical information to support research activities devoted to reaching a better understanding of the underlying biological phenomena. This goal is achieved by exploiting a general tracking framework based on a multiframe point correspondence approach and capable of translating the matching problem into a maximum path cover problem over a graph based representation of moving objects. The application to phase contrast microscopy images containing hundreds of cells aggregating to form capillary tubes required to design an ad-hoc weight function capable of properly handling cells occlusion and aggregation.

Vascularization is defined as the sprouting of new blood vessels by expansion of the endothelium by proliferation, migration and remodeling. Vascularization is fundamental to healing, reproduction as well as embryonic development. It also plays a key role in tumor growth, tumor metastasis and other pathological processes. Understanding biological phenomena driving the creation of vascular structures is therefore essential for clinical treatment of cancer and other vascularization-related diseases. Recently, an analytical model capable of mimicking the process of in-vitro vascular network creation from randomly seeded endothelial cells has also been proposed. This paper presents the development of a novel neural network based segmentation technique working on phase contrast microscopy snap photographs of cultured endothelial cells which allows for cell structures geometry quantitative analysis thus constituting a key instrument in the development of computerized tools for vascularization parameters measurement as well as supporting also analytical model deployment and validation.

This paper presents a comprehensive framework for quantitative analysis of vascular processes from in-vitro videomicroscopy data. By following an active contours based approach, we designed a quasi-automatic technique enabling highly interacting motile endothelial cells (ECs) tracking in large field of view phase contrast microscopy video sequences. Our work was motivated by the necessity of validating through statistical analysis an analytical model mimicking ECs behavior. However, the proposed framework could also constitute an invaluable tool supporting general experimental studies on vascularization. Our tracking technique has been extensively validated on realistic data-sets by comparison with a manually defined ground-truth.

Vasculogenesis is defined as the sprouting of new blood vessels by expansion of the endothelium by proliferation, migration and remodeling. Vasculogenesis is fundamental to wound healing, reproduction as well as embryonic development. Moreover, it is involved in tumor growth, tumor metastasis and other pathological processes. The availability of dedicated image-based analysis systems would constitute an invaluable support in understanding biological phenomena regulating vasculogenesis processes. In this paper we present an unsupervised segmentation technique which allows for accurate classification of blood vessel networks in in-vitro microscopy images. Results achieved through the proposed technique are validated and compared with experimental observations.

The presence of different kinds of artifacts has long been a problem in the analysis and interpretation of electroencephalographic recordings. Recently blind source separation by Independent Component Analysis (ICA) has been successfully employed for the detection and removal of artifactual components and new methods for the automatic identification of the artifactual components are being proposed. In this paper we focus on the automatic removal of eyeblink components from EEG data. First a model of the topographic maps associated to the ICA eyeblink component and a distance quantifying the resemblance to the model are defined. To further improve the reliability of the system, an eyeblink detector was designed which locates the individual eyeblinks within the component, thus confirming the nature of the activation.

In this paper the design and development of a low-cost homecare architecture for remote patient telemetry built upon a Java-based embedded computer is presented. The proposed architecture has been validated by experiencing real-time ECG monitoring by means of desktop PCs equipped with Web browsers, Personal Digital Assistants and WAP-enabled GSM/GPRS mobile phones. The modular approach followed in the development of the home station allows additional medical devices to be easily integrated to fulfil the requirements of heterogeneous homecare scenarios. We expect that the availability of such a low-cost telemedicine device will contribute to further extend healthcare reach to the homecare environment.

This paper presents the preliminary results in the development of a framework for ubiquitous monitoring in a Intensive Care Unit environment, which aims at enabling mobile access to real-time bedside monitoring data and to a comprehensive electronic patient's clinical record at any moment in time and from any location, by means of a PDA device capable of secure wireless communications. The main goal of the proposed architecture is to optimise the employment of human resources involved in monitoring activities, while at the same time enhancing the quality of delivered services and improving the level of attention to patients.

A new category of devices, known as Personal Digital Assistant (PDA), has become increasingly widespread since the end of the nineties. A large number of software applications have been developed for PDAs, but high-quality 3D graphics still remain beyond the computational capability of these devices.This paper tackles this issue by proposing a generic solution for hardware-accelerated remote rendering on cluster. The rendering task is submitted to a PC/workstation cluster (each cluster machine is equipped by a graphics accelerator) by means of the Chromium architecture. Each machine renders a part of the image that is then reassembled and sent to the PDA via a software bridge. On the PDA side, the user can explore the scene using an ad-hoc navigation interface.The proposed solution allows to display extremely realistic and complex models in an interactive way. Moreover, our architecture does not depend on commercial solutions/products and can be easily modified in order to better fulfill requirements of specific applications

Computationally intensive applications often require the employment of parallel/distributed solutions in order to strongly reduce execution times. Workstations and PCs connected by a fast local network provide effective, low-cost, and general purpose solutions that are quickly replacing special purpose proprietary architectures for a wide spectrum of disciplines. The issue to monitor the performance (fundamental to check the efficiency of a distributed application) of cluster architectures is addressed in this work. This paper presents a multi-channel architecture for remote monitoring-management tailored to display information on PDA devices. Users can remotely monitor the system critical activities and cluster resources utilization; moreover, we provide the possibility to perform some management tasks (for instance, shutdown and reboot) useful for maintaining the integrity of the system and to harness the full cluster potential.

A novel neural network-based technique for segmentation of single-channel magnetic resonance images is presented. The segmentation of single-channel magnetic resonance images is a daunting task due to the relatively little information available at each pixel site. The proposed algorithm is based on unsupervised clustering by means of a Kohonen Self-Organizing Map: unsupervised segmentation algorithms are highly desirable in order to eliminate intra- and interobserver variability. Particular attention has been devoted to the choice of suitable features, in order to ensure an accurate and reliable segmentation: in particular, a feature set extracted from the neighborhood of each pixel has been evaluated. The proposed technique has been tested on simulated magnetic resonance images to assess its stability against the presence of noise and intensity inhomogeneities. Moreover, it has been tested on real magnetic resonance images of both volunteers and brain tumor patients. The preliminary results presented make the proposed technique a promising alternative for the segmentation of single-channel magnetic resonance images and encourage further investigation.

Standardization is a key issue in the field of biosignals acquisition and storage. By easing the interoperability between medical devices and telemedical information systems, it facilitates telemedicine system design and health care center collaboration, thus enhancing the quality of delivered sanitary assistance. While in the field of medical imaging the DICOM standard has gained widespread acceptance, in the field of biomedical signals acquisition and storage many alternatives still exist. In this paper, we investigate the feasibility and validity of the implementation of an integrated, patient-based clinical database compliant with the CEN/TC251 Vital Sign Information Representation (VITAL) ENV standard. Both the conceptual model and the implementation of the clinical database are presented. To validate the applicability and the performance of the proposed solution, the designed database has been tested into an advanced telemedicine platform addressing crucial healthcare scenarios

This paper presents an advanced telemedicine architecture enabling mobile teleconsulting and telediagnosis applications in the medical imaging domain. The feasibility of a portable teleradiology unit based on a Personal Digital Assistant (PDA) and providing medical experts with wireless connectivity over the General Packet Radio Service (GPRS) of the GSM telecommunication network has been experienced by extending to mobile users the interactive services currently provided by an existing regional network for radiological teleconsulting devoted to mild head injury case management. Moreover, the effectiveness of synchronous cooperative work applications including voice conferencing and medical data sharing in a mobile environment has been evaluated. By ensuring skilled medical staff availability wherever and wherever needed still providing the same capabilities of traditional telemedicine systems over broadband networks, the proposed architecture will contribute to increase the quality of remote health care delivery

In this paper, a mobile teleconsultation system based on the use of a PDA is presented. The proposed architecture has been evaluated both over a low bandwidth GPRS public network well-suited for remote emergency diagnosis and in a broad-band WLAN IEEE 802.11 environment suitable for in-hospital care management. The simulation studies with radiological images and ECG signals shows the effectiveness of such a solution in both an interactive and an off-line scenario

In this paper a PVM-based distributed platform of the well known REYES rendering architecture developed byPix ar is presented. This work effectivelyt ackles issues related to load balancing and memory allocation by a master-slave paradigm. In particular, the rendering is distributed performing both an image and an object space subdivision; in this way, low memory resources are necessary to the slave side. Examples show the effectiveness of the proposed work.

In this paper, a mobile teleconsultation system based on the use of a PDA is presented. The proposed architecture has been evaluated both over a low bandwidth GPRS public network well-suited for remote emergency diagnosis and in a broad-band WLAN IEEE 802.11 environment suitable for in-hospital care management. The simulation studies with radiological images and ECG signals shows the effectiveness of such a solution in both an interactive and an off-line scenario.