In scenographic productions, the selection of stage props is a structured process that follows a careful reading of the script and unfolds through three different phases: a visual exploration aimed at stimulating and shaping the creative vision, the selection of the props to be used on stage and their customization. While recent AI-driven approaches enable the automatic generation of 3D content, relatively few systems support sustained user involvement and iterative interpretive control throughout the authoring workflow. We present a WebXR-based Human-in-the-Loop system designed to support scenographic prop authoring by aligning AI assistance with this canonical workflow. The system provides AI-generated alternatives—images, retrieved 3D models, and textures—that users can iteratively explore, select, and refine while retaining control over creative decisions. We report an exploratory within-subject study with 20 experts in theater and cinema, comparing an AI-assisted workflow with a non-AI baseline. Results indicate that AI assistance was associated with higher perceived technology acceptance and creative support, alongside increased cognitive workload. Differences in the perceived coherence of the final props were not statistically significant, although descriptive trends suggest potential support for representing object type and symbolic meaning, indicating that AI assistance may be more effective in supporting early-stage exploration than precise semantic refinement.

Conversational Virtual Agents (CVAs) offer a promising approach for enhancing user task performance in Mixed Reality (MR) environments. This paper explores the integration of a CVA into an MR application designed to assist in solving a 2D physical puzzle, offering enhanced spatial cognitive capabilities. Using the CVA classification architecture and the MiRAS (Mixed Reality Agents) Cube Taxonomy, we developed an MR system with a state-aware assistant to guide users in a puzzle-solving task only when requested. The primary research question is whether or not the CVA needs to be embodied. We conducted a study with 34 participants to investigate the influence of Voice-only and Embodied CVAs on puzzle-solving performance, user interactions with the assistant, the assistant’s social presence, overall system cognitive workload, and users’ perceptions of future system use. Both modalities showed equivalent outcomes regarding the number of position- and orientation-related queries, perceived usability, message and affective understanding, performance, frustration, and usefulness. However, results showed that Voice-only CVA significantly enhanced task efficiency: participants completed puzzles more quickly and accurately, reporting lower effort than in the Embodied condition. These findings suggest that Voice-only CVAs may be more effective for tasks like puzzle solving, where auditory guidance alone appears sufficient to support better performance.

External Ventricular Drain (EVD) placement is a complex neurosurgical task that requires identifying a target point within the brain and accurately positioning a catheter at the appropriate angle. While Mixed Reality (MR) technologies have seen limited adoption in the operating room, they offer significant potential for developing training systems that enhance skill acquisition and retention in unaided conditions. A current gap in research concerns the effectiveness of multimodal guidance systems that incorporate both visual and audio-based MR cues. In this paper, we present an MR-based simulator for EVD placement training and evaluate the impact of three MR-guided training modalities: (1) a baseline condition using only 2D CT scans and a 2D catheter projection; (2) a visual guidance modality incorporating a 3D trajectory overlay; and (3) an embodied-audio guidance modality featuring a virtual agent delivering spoken instructions and feedback. Participants underwent a digital training phase using one of the three modalities, followed by an unaided EVD placement on a physical phantom with a real catheter to evaluate skill transfer and retention. Results indicate that both advanced MR modalities significantly improve procedural accuracy, execution speed and receive higher scores in usability and technology acceptance compared to the baseline. Notably, training with 3D visual trajectory guidance led to significantly higher unaided placement accuracy, indicating stronger skill retention. However, multimodal guidance demonstrated equivalent execution speed, while showing a trend toward lower overall cognitive load.

Educational practices are increasingly experimenting with eXtended Reality (XR) paradigms to offer novel opportunities for boundaryless learning experiences with real-time interactions in immersive environments. Digital Twins (DT) are also gaining traction in this field to facilitate personalized learning experiences. However, a still unexplored space in learning frameworks amounts to the one where XR intersects with DTs. This work wants to move a step in such a direction with the design, implementation, and test of a DT-driven XR framework to learn procedural tasks. The framework offers three distinct learning modalities where virtual and physical interactions enhance learning retention by engaging users actively in digital and real-world environments. We contextualize such a framework for procedural task learning through one of its pivotal use cases: learning Rubik’s Cube notations. To evaluate and compare the effectiveness of these modalities, we perform an experimental user campaign evaluating short-term skill retention, performance accuracy, usability, and cognitive load of each of them. We then provide an extensive statistical analysis to compare each kind of guidance while analyzing correlations between the examined variables, offering insights into optimizing instructional methodologies within XR-based educational frameworks.

Abstract To study the evolution of specific cultures and times different kinds of pictures could be adopted. Family album photos may reveal socio-historical insights regarding those specific cultures and times. Along this path, this work addresses the problem of automatically dating an image by resorting to the analysis of an analog family album photo dataset. In particular, the IMAGO collection, which contains Italian photos shot in the 20th century, was considered. Thanks to the IMAGO dataset, it was possible to apply different deep learning-based architectures to date images belonging to photo albums without needing any other sources of information. In addition, we carried out cross-dataset experiments, which also involved models trained on American datasets, observing temporal shifts which may be due to known intercultural influences. We further explore such a possibility by qualitatively analyzing the cross-dataset interpretation of the trained deep-learning models with the Uniform Manifold Approximation and Projection (UMAP) algorithm. In conclusion, deep learning models revealed their potential in terms of possible applications to intercultural research, from different points of view.

Abstract An invisible layer of knowledge is progressively growing with the emergence of situated visualizations and reality-based information retrieval systems. In essence, digital content will overlap with real-world entities, eventually providing insights into the surrounding environment and useful information for the user. The implementation of such a vision may appear close, but many subtle details separate us from its fulfillment. This kind of implementation, as the overlap between rendered virtual annotations and the camera’s real-world view, requires different computer vision paradigms for object recognition and tracking which often require high computing power and large-scale datasets of images. Nevertheless, these resources are not always available, and in some specific domains, the lack of an appropriate reference dataset could be disruptive for a considered task. In this particular scenario, we here consider the problem of wine recognition to support an augmented reading of their labels. In fact, images of wine bottle labels may not be available as wineries periodically change their designs, product information regulations may vary, and specific bottles may be rare, making the label recognition process hard or even impossible. In this work, we present augmented wine recognition, an augmented reality system that exploits optical character recognition paradigms to interpret and exploit the text within a wine label, without requiring any reference image. Our experiments show that such a framework can overcome the limitations posed by image retrieval-based systems while exhibiting a comparable performance.

Although one of the most popular practices in photography since the end of the 19th century, an increase in scholarly interest in family photo albums dates back to the early 1980s. Such collections of photos may reveal sociological and historical insights regarding specific cultures and times. They are, however, in most cases scattered among private homes and only available on paper or photographic film, thus making their collection and analysis by historians, socio-cultural anthropologists, and cultural theorists very cumbersome. Computer-based methodologies could aid such a process in various ways, speeding up the cataloging step, for example, with the use of modern computer vision techniques. We here investigate such an approach, introducing the design and development of a multimedia application that may automatically catalog vernacular pictures drawn from family photo albums. To this aim, we introduce the IMAGO dataset, which is composed of photos belonging to family albums assembled at the University of Bologna’s Rimini campus since 2004. Exploiting the proposed application, IMAGO has offered the opportunity of experimenting with photos taken between the years 1845 and 2009. In particular, it has been possible to estimate their socio-historical content, i.e., the dates and contexts of the images, without resorting to any other sources of information. Exceeding our initial expectations, such an approach has revealed its merit not only in terms of performance but also in terms of the foreseeable implications for the benefit of socio-historical research. To the best of our knowledge, this contribution is among the few that move along this path at the intersection of socio-historical studies, multimedia computing, and artificial intelligence.

Several new models and formats for the digital transformation of the manufacturing industry appear because of the rapid integration of information technology and the real economy, as well as the increasingly obvious evolution trend of industrial digitalization, networking, and intelligence.Among them, digital twins have increasingly become a research hotspot in all sectors of the industry and have broad prospects.It maps physical objects in virtual space in a digital way and simulates their behavioral characteristics in real environments.It makes the gap between virtuality and reality disappear based on their closed-loop interaction.Digital twins are undoubtedly an important and strategic technology in response to familiar products, production, and services.It can also speculate some indicators that cannot be directly measured by machine learning through collecting the direct data of limited physical sensor indicators.This can realize an assessment of the current state, a diagnosis of past problems, and a prediction of future trends, and simulate possibilities to provide more comprehensive decision support.Driven by "Industry 4.0/5.0", the concept of "Digital Twins" is setting off a new wave of industrial simulation boom.Entity industrial objects or systems are fully digitized, and models including virtual objects, virtual processes, and virtual plant areas are established.These digital twins can be placed in virtual environments to analyze, simulate, verify, test, and adjust various situations such as product or process optimization, optimizing the operation of real objects or systems, and increasing their added value.Also, the expression of "virtual reality" for scene visualization and the new scene interaction mode will be more conducive to better visual effects and interactive operations in the digital world.The combination of digital twins and virtual reality is currently widely used as guidance instructions for operation and maintenance, early warning of error prevention, and information tips to improve the efficiency and accuracy of operators.Virtual reality brings users better vision and senses through smart hardware like glasses and helmets.However, there is still room for improvement in the technical level of smart hardware.And rational hardware configuration and cost-reduction can be realized gradually with the improvement of R & D. Now the focus in this field should be how to enhance user experience and enrich products.In "Integrating digital twins and deep learning for medical image analysis in the era of COVID-19", the authors introduce a digital-twin-based smart healthcare system integrated with medical devices to collect information regarding the current health condition, configuration, and maintenance history of the device/ machine/system.Furthermore, medical images, that is, X-rays, are analyzed by using a deep-learning model to detect the infection of COVID-19.The designed system is based on the cascade recurrent convolution neural network (RCNN) architecture.In this architecture, the detector stages are deeper and more sequentially selective against small and close false positives.This architecture is a multi-stage extension of the RCNN model and sequentially trained using the output of one stage for training the other.At each stage, the bounding

The advancements of Artificial Intelligence, Big Data Analytics, and the Internet of Things paved the path to the emergence and use of Digital Twins (DTs) as technologies to “twin” the life of a physical entity in different fields, ranging from industry to healthcare. At the same time, the advent of eXtended Reality (XR) in industrial and consumer electronics has provided novel paradigms that may be put to good use to visualize and interact with DTs. XR technologies can support human-to-human interactions for training and remote assistance and could transform DTs into collaborative intelligence tools. We here present the Human Collaborative Intelligence empowered Digital Twin framework (HCLINT-DT) integrating human annotations (e.g., textual and vocal) to allow the creation of an all-in-one-place resource to preserve such knowledge. This framework could be adopted in many fields, supporting users to learn how to carry out an unknown process or explore others’ past experiences. The assessment of such a framework has involved implementing a DT supporting human annotations, reflected in both the physical world (Augmented Reality) and the virtual one (Virtual Reality). The outcomes of the interface design assessment confirm the interest in developing HCLINT-DT-based applications. Finally, we evaluated how the proposed framework could be translated into a manufacturing context.

Since the beginning of the 2010 decade, many improvements have been made in terms of Virtual Reality (VR) hardware technologies and software platforms. Such trend is expected to continue, pushing the penetration rate of VR headsets. In the meantime, two research questions emerge: (a) how 3D-based immersive environments may get to be used, and with which benefits, in place of 2D ones, and, (b) how to support such integration. We focus on the latter, taking as a case study SUMO, a well-known PC-based vehicular traffic simulation tool. To this aim, we adopt an approach based on the OpenGL intercept technique, with the implementation of the OGL2VR middleware, which has been extended to remove graphical artifacts and to include the on/off toggling of dynamic elements in a 3D scene. We here describe the solutions that have been embraced, as well as the challenges that still remain along this path, to render dynamic traffic animations in an immersive setting to support the use of a blended 2D/3D environment.

Virtual reality is slowly transitioning from a specialized laboratory-only technology, to a consumer electronics appliance. In this transition, two interesting research questions amount to how 2D-based content and applications may benefit (or be hurt) by the adoption of 3D-based immersive environments and to how to proficiently support such integration. Acknowledging the relevance of the former, we here consider the latter question, focusing our attention on the diversified family of PC-based simulation tools and platforms. VR-based visualization is, in fact, widely understood and appreciated in the simulation arena, but mainly confined to high performance computing laboratories. Our contribution here aims at characterizing the simulation tools which could benefit from immersive interfaces, along with a general framework and a preliminary implementation which may be put to good use to support their transition from uniquely 2D to blended 2D/3D environments.

In this paper we propose a theoretical model, which may be put to good use to analyze the energy consumption of a smartphone where a random number of different applications are assumed to run, for random intervals of time, consuming the available energy resources. The problem is formulated in terms of the following mobile application(s) parameters, namely: (i) the maximum possible running time, (ii) the average amount of energy consumed per time unit while running, (iii) the average number of apps that are employed during a given smartphone's usage. The model is solved in terms of the probability distribution function of the energy consumed on a given smartphone. The proposed model is then validated by simulation means, in order to prove its applicability in quantifying the amount of energy consumed.

We here propose to collect and analyze large amounts of multimedia data from different public and private sources, in the form of text, image, video, to predict relevant information about specific quantities related to fashion brands, such as their sales volumes and/or trends. To this aim, we deem deep learning techniques as the suitable instrument capable of managing extremely large amounts of multimedia data. While a few works exist in literature on learning applications in the fashion area, where text is used to perform sentiment analysis operations, limited research has also considered images and videos in this context. In this paper, starting with an overview of the state of the art of the applications of artificial intelligence for fashion, we set the stage for a holistic approach for the deep learning based analysis of multimedia data related to fashion.

Deep Learning and Artificial Intelligence are slowly revolutionizing many fields of applications, having the potential to replace humans in a variety of tasks and jobs. Nevertheless, creativity has always been considered something inherently human: recent research shows that, however, this may not always be the case. From this standpoint, this paper focuses on music and on the recent advancements in deep learning applied to the generation of musical content. We argue that, while those models are able to produce results that could actually be considered music, the role of the human musician still remains preponderant in the production of a musical piece. We here reflect on such limitations, directing our efforts to imagining new tools and instruments that may allow to experience new forms of interaction while supporting novel processes of creativity and music production.

The relationships between fashion and technology are, year by year, increasing in number and depth. Information and communication technologies (ICT) do not have an influence, in fact, only on the manufacturing processes behind the production of clothes and accessories, but nowadays have implications on the end products as well as on their advertisement. This is witnessed by the plethora of designers that are today considering the use of consumer electronics in their creations and by the number of fashion brands that are exploring non conventional communication strategies including the use of ICT platforms. On the other hand, also consumers have changed their habits and ways of approaching products: consider, as a relevant example, the large share of users that today buy fashion online rather than in a brick and mortar shop. Now, what is by many considered the fourth wave of consumer electronics, i.e., the advent of Virtual and Augmented Reality, may have important implications on such relationships, setting new paths for product discovery and brand communication. In this scenario, we here experiment with gamification and Virtual Reality, showing the result of presenting a fashion game to an audience of fashion experts. Our results confirm the promising opportunities that the use of such technologies may provide to such creative and commercial domain.

In this paper we propose event goodput, i.e., the fraction of events which may be successfully managed by a system, as a relevant metric to describe the performance of battery powered real-time sensor networks. Unlike other performance metrics as response, completion, maximum lateness times, all representing fundamental, but different, figures of merit for the description of the behavior of real-time systems, event goodput provides an immediate and a direct relation with the events which may be satisfactorily managed (or not) by a real-time application. We will show such metric well serves the purpose of describing the performance of battery powered, random event-driven networks, such as sensor networks deployed for surveillance and intrusion detection applications, operating in time critical scenarios. In essence, such real-time systems may be assessed in terms of the fraction of events which they successfully/unsuccessfully detect and report within a time interval of interest. The importance of such metric is here demonstrated providing a simulation model and results where the use of the event goodput metric is discussed in conjunction with those metrics which are traditionally utilized for the assessment of a real-time sensor networks.

This paper completes an analysis started with two previous contributions, which have first identified Facebook as the most interesting social media for Crohn's disease patients and then Infliximab as the most discussed, both positively and negatively, treatment. In particular, in our second contribution, we concentrated on the satisfaction that emerged from online posts regarding Infliximab and compared it to the body of pertaining medical literature. We here finish off such work, comparing the satisfaction recorded by automatic means through the use of sentiment analysis techniques to the satisfaction recorded by expert physicians. In brief, two results appear to be of particular interest for the Crohn's disease community of patients: (a) physicians tend to classify as neutral many posts that were previously classified as negative, and, (b) posts of patients that have been treated with Infliximab for a long time are never classified as negative by medical examiners. In addition, this short paper sets forth, with strength, a problem of methodological nature: is it possible to effectively analyze the big data of patient online posts without a stronger cooperation between data analysts and medical experts?

Anonymity, speed and big data are all ingredients at the basis of an intense online medical information prosumerism supported by search-engines, websites, forums and social networks. Fostering reliable medical ecosystems requires an exploitation of such data, controlling quality and delineating user behaviors. This strongly emerges with chronic patients: they are expected to devote a long use of the Internet on the same health topics; nonetheless a limited amount of research has investigated their online resources and behavior. We uncover the role of online social networks for a growing community of chronic patients: Crohn's disease patients. Our contribution is twofold: (a) we characterize the data exchanged by Crohn's patients, (b) while analyzing how they deal with given topics of medical interest. In particular, of great medical relevance is the result that Infliximab is the treatment that mostly influences the Crohn's patient community sentiments. We are confident our analysis of the health heritage exchanged online can help improve Crohn's patients' experience, exceeding the traditional practices that typically concentrate on individuals rather than on communities.

Mobile communication devices are expected to overtake traditional desktop PCs and become the dominant point of entry to the Internet. This technology shift has boosted user demand for multimedia applications and services which are now typically accessed through the wireless interface. Users expect to be always connected and able to run a variety of applications which sometimes impose contrasting requirements. Of particular research interest in this scenario is the coexistence between two popular categories of traffic: elastic and real-time, both of them covering a wide range of user applications. In this paper, we investigate the above issue in the scenario where service connectivity is provided through a multihop wireless network. To this end, we study two representative applications, one for each of the above categories, which are content download and interactive game play. We show by means of extensive simulations, how both the content download's goodput and the online game's per-packet delivery delay can be improved through an appropriate solution implemented on the wireless Internet Gateway.

We present a REST approach to build Health services on the Web. Our proposal originates by the necessity of evolving the current regional health service to accommodate emerging needs that are too complex to accomplish with the current system. The original system extends on the regional scale of Emilia-Romagna, and it is one of the most advanced in Italy. Our architecture inherits some of the basic Web methodologies and techniques to implement an highly scalable and flexible system that is capable to satisfy the current needs and their planned evolutions. Moreover, our approach should allow for an effortlessly addressing of future requirements not foreseen at the moment. Without revolutionizing the current IT infrastructure, our approach introduces a new paradigm that could be implemented by a sophisticated interface to access data and resources.

ABSTRACT The increase of wasted time and pollution due to vehicular traffic has paved the way to many different countermeasures, ranging from the enforcement of congestion tolls to the commercialization of vehicles powered by low‐emission hybrid engines. Advanced traveler information systems (ATISs), which are capable of supplying updated traffic information to all those citizens that are driving through city roads, represent a prominent approach to combat vehicular congestion. In brief, ATISs are concerned with collecting, processing, and disseminating traffic information, providing data that can be profitably exploited by an on‐board navigation system to compute the most convenient route to a given destination. Indeed, their role becomes progressively more relevant as their accuracy and reliability increases, thus encouraging more and more people to utilize them while driving. With this in mind, we devised a new congestion detection model that accurately estimates and forecasts the short‐term congestion state of a road without requiring any prior knowledge regarding any of its parameters. Such model can be easily integrated within an ATIS and usefully applied to any given road. The efficacy of our model is here proved through the results of several experiments, which witness the validity of our approach. Copyright © 2012 John Wiley & Sons, Ltd.

The ever-increasing processing power that can today support large scale and detailed simulations increased the depth of the research carried out on protocols and apps developed for single hop and multi-hop Vehicular Ad Hoc Network (VANET) environments. It is now possible, for example, to verify the effectiveness of peer-to-peer one-hop file exchange protocols between vehicles, while taking into account the effects that buildings have on point-to-point transmissions at street intersections, or also verify how a high density of vehicles can impact the transfer of multimedia information through multiple hops between passengers involved into an online game. However, what has not been possible so far, for the obvious reason that no highly dense VANETs in reality exists, is to effectively test any type of application or communication protocol in a real setting, especially for the scenarios concerned with multi-hop communications. But this may change, with the introduction of a creative approach to VANET research: we will here describe how it is possible to experiment with applications and protocols in scenarios that are close to reality, by simply using a few real vehicle resources. As an example of how this can be done, we will provide preliminary results from a set of experiments on a vehicular highway accident warning system, results that would have not been observable in reality without the adoption of our creative methodology.

This paper investigates a given branch of the music information retrieval field, specifically that of audio thumbnail, through which a piece of music can be automatically summarized. We first provide a survey on the different techniques available today for the generation of music summaries, and then we propose a practical method that, based on best practices, is able to summarize songs with a great efficacy.

Thanks to an ever increasing processing power that can today support advanced graphical capabilities within high bandwidth mobile devices, augmented reality technologies are now ubiquitous, finding profitable uses in a wide variety of scenarios. Augmented reality principles, in fact, can be beneficially put to good use within many types of mobile applications: for example, augmented city guides can properly display additional virtual objects that show how a monument was at the time of its construction (e.g., the Colosseum with the inclusion of its missing parts), or augmented games can add fictitious characters and objects to real world settings in proper places (e.g., Lara Croft in search of Bartoli in Venice). Nonetheless, the totality of such augmented mobile applications, to the best of our knowledge, limit the interactions that may occur to those that can happen between a single mobile user and the objects that are displayed on his/her mobile platform screen. In this work, we show that it is possible to devise a new interaction paradigm, augmenting augmented reality apps with the interactions that may occur between multiple users via the virtual objects displayed on multiple mobile platforms. In particular, we applied such ideas to the devise of a shooting game set in the 17thcentury to celebrate the 300thanniversary since the foundation of the Academy of Science of Bologna by Count Luigi Ferdinando Marsili. The paper describes and discusses the design choices and the technical issues at the basis of our system.

Obtaining realistic three-dimensional (3D) representations of objects is one of the key research topics in Computer Vision. The applications of such researches, in fact, are multifaceted and range from serious scenarios, such as medical imaging systems, to leisure ones, including entertainment systems which support filmmaking (e.g., 3D movies such as Avatar), gaming (e.g., Microsoft Kinect) and music (e.g., House of Cards video by Radiohead), citing here only a few. Several techniques have been employed in the past three decades to acquire 3D information from generic objects: photogrammetry, stereovision, holography, time-of-flight cameras, interferometry and structured light, among others. Many of such techniques are capable of providing 3D information with high fidelity, and are also apt to track any surface movements with great precision and great performances, but often require the use of specialized and proprietary hardware and software. We here present a system that prevents from falling into such a nuisance, as it is based on existing 3D information extraction algorithms and solely requires off-the-shelf devices: a projector, a webcam and a notebook. In addition, the proposed system avoids the fall of any complexity on users' shoulders, as all settings and tuning procedures are implemented in software.

The advances made in both Human Computer Interfaces (HCIs) and in Mixed Reality (MR) systems during the past decade have opened the gates to countless new applications in fields ranging from applied science to fine arts. In fact, computers have evolved from boxes with which it was possible to interact solely using mice, keyboards and monitors, to become devices that permeate and intersect with the space where human beings live and move, being now capable of interpreting their gestures as long as mixing with and contain the objects that surround them. Such richness has been widely employed within new and engaging computer games, where it is now possible to play while moving and connecting to the virtual characters that compose mixed worlds, directly from home. However, such potential is far from being fully exploited everywhere. In public spaces such as museums and exhibitions, for example, new means of interaction and mixed worlds could contemporarily reach two goals: (a) augment the user experience, and, (b) increase visitors' accessibility to all artifacts. In this work we show how both goals have been achieved with the devise and implementation of Mercator Atlas Robot, an application that supports the exploration of Mercator's World Atlas, the book that first has wholly described the world through a collection of maps. In particular, we here describe how the combination of a gestural interface and mixed reality paradigms has let visitors travel through Mercator's volume in a simple and intuitive way. All this has been possible with only low cost, off-the-shelf, hardware, where all the intelligence is entirely based on software components.

Hands-free gaming systems are likely to gain, in the near future, the total share of the electronic gaming market. Such process has been anticipated by the introduction of the Nintendo Wii that, within a few months from its launch, stably reached the top ranking of sales among gaming systems. We can expect something similar will occur once the for-long expected Microsoft Kinect system will be available on the shelves of computer gaming stores. In general, it is clear from this sequence of events, that the opportunity of playing a game naturally, performing the same movements that would be made in a real setting, has a magnetic effect on customers. What, instead, is less evident is the great wealth of research that has been performed in the recent years to reach such result. In fact, behind the development of such gaming platforms strenuous research efforts have been made in a number of areas, which include and are not limited to hand following techniques and gesture recognition algorithms. As a beneficial side effect, the development of these areas can also play an important role in a number of other applications, including technical and artistic interactive exhibitions. In this paper we will describe the process that led us to devise a novel hand following and an innovative gesture recognition technique that both can easily be applied to exhibition scenarios (e.g., museums, fairs, etc.) and in general all those performing events where a pre-defined set of gestures are needed to enjoy a cultural experience, as they can be easily jointly put to good use to recognize a predefined set of movements. Our algorithms are robust and easy to implement, for this reason they are particularly suited for exhibition scenarios where stands can often change or adapted to new requirements.

The specific features of inter-vehicular communications are allowing the deployment of a broad gamut of possible applications including traffic control, road safety and in-car entertainment. At the basis of all this lies the improvement of VANET-based transmission techniques that are becoming technologically mature. Within this context, in this paper we provide an experimental comparison between two of the most effectual algorithms whose aim is that of quickly broadcasting messages throughout a given platoon of vehicles. The most prominent characteristic of both the algorithms under investigation is that they were designed for wireless vehicle-to-vehicle (V2V) communications, with in mind only realistic transmission conditions (that is, asymmetric and variable vehicles' transmission ranges). Even if both algorithms were conceived based on the idea to span application messages as far as possible, while minimizing the number of relaying vehicles, our extensive analysis demonstrates that one of the two outperforms the other.

We present an overview or the video games available at the Film Library of Bologna. This institution, in collaboration with the University of Bologna, has a whole collateral branch dedicated to the video games, as they can be considered a recreational activity somehow related to movies. This collection of video games conceptually starts from the ones that are strictly connected to movies, and then expands to a wider class of video games. A video game could be related with a movie either as its direct inspiration, its prequel or collateral plot, or also be created as a direct consequence of that movie. The expansion of the collection available in the Library includes a historical set of video games. In this paper we discuss the historical perspective of the relationship between technology and video games, providing a complete historical view of the video games by means of the titles and the consoles available in the Library. Several dedicated consoles are still in working conditions and could be used by the visitors of the Library.

Infrastructure networks like Internet have some coverage gaps (e.g. rural areas) where no service connectivity is provided. Cellular networks could be used in alternative but they usually associate their services with a usage cost. Nowadays, the growing number of mobile devices equipped with a wireless interface and the end-user trend to shift toward wireless technology has opened new possibilities for networking. Opportunistic networking seems a feasible solution in filling in these coverage gaps by providing service connectivity where it is not sustained by an infrastructure. In this context we provide a delay tolerant platform that ensures service connectivity where it is absent. Our approach follows the Delay/Disruption Tolerant Networking (DTN) paradigm by implementing a store-and-forward communication model between mobile users and carrier entities (e.g. buses), where a user delegates the carrier a task (bundle), the carrier stores it locally and whenever service connectivity is available (e.g. wi-fi at the bus station) tries to accomplish it, successively notifying the user of the task output next time they encounter again.

Abstract An inelastic flow is a flow with an inelastic rate, i.e., the rate is fixed, and it cannot be dynamically adjusted to traffic and load condition as in elastic flows like TCP. Real time, interactive sessions, and video/audio streaming are typical examples of inelastic flows. Reliable support of inelastic flows in wirelessad hocnetworks is extremely challenging because flows and routes dynamically change and flows compete for the shared wireless channel. Bandwidth must be reserved for inelastic flows at session set up time. To avoid repeated attempts to set up reservations in a ‘volatile’ network and prevent serious network capacity degradation due to call set up overhead, a Call Admission Control strategy robust to mobility must be developed. In this paper we propose ProbeCast, a probe based call admission control scheme with QoS guarantees for inelastic flows. ProbCast was designed for multicast streams but can also work, by default, for unicast. In ProbeCast, a path (or a tree) is probed for capacity availability. If an intermediate link along the probed path fails to meet the QoS requirement, the flow is ‘pushed back’ via backpressure upstream to an intermediate branch or possibly to the source. The backpressure principle is simple; however, its implementation requires some care to avoid unfairness and eventual capture by one of the flows sharing a congested bottleneck. We show that proportional fairness among inelastic contenders will prevent capture. To achieve this, we have developed the Neighborhood Proportional Drop (N‐PROD) scheme. N‐PROD guarantees fair rejection of unfeasible flows and maintains the same proportional drop rate among surviving flows in the same contention domain. We demonstrate the efficacy and robustness of ProbeCast for unicast as well as multicast scenarios using the Qualnet simulation platform. Copyright © 2010 John Wiley & Sons, Ltd.

Social system networks with high data rates and limited storage will discard data if the system cannot connect and upload the data to a central server. We address the challenge of limited storage capacity in mobile health systems during network partitions with a heuristic that achieves efficiency in storage capacity by modifying the granularity of the medical data during long intercontact periods. Patterns in the connectivity, reception rate, distance, and location are extracted from the social system network and leveraged in the global algorithm and online heuristic. In the global algorithm, the stochastic nature of the data is modeled with maximum likelihood estimation based on the distribution of the reception rates. In the online heuristic, the correlation between system position and the reception rate is combined with patterns in human mobility to estimate the intracontact and intercontact time. The online heuristic performs well with a low data loss of 2.1%-6.1%.

Road congestion results in a huge waste of time and productivity for millions of people. A possible way to deal with this problem is to have transportation authorities distribute traffic information to drivers, which, in turn, can decide (or be aided by a navigator) to route around congested areas. Such traffic information can be gathered by relying on static sensors placed at specific road locations (e.g., induction loops and video cameras) or by having single vehicles report their location, speed, and travel time. While the former approach has been widely exploited, the latter has come about only more recently; consequently, its potential is less understood. For this reason, in this paper, we study a realistic test case that allows the evaluation of the effectiveness of such a solution. As part of this process, (a) we designed a system that allows vehicles to crowd-source traffic information in an ad hoc manner, allowing them to dynamically reroute based on individually collected traffic information; (b) we implemented a realistic network-mobility simulator that allowed us to evaluate such a model; and (c) we performed a case study that evaluates whether such a decentralized system can help drivers to minimize trip times, which is the main focus of this paper. This study is based on traffic survey data from Portland, OR, and our results indicate that such navigation systems can indeed greatly improve traffic flow. Finally, to test the feasibility of our approach, we implemented our system and ran some real experiments at UCLA's C-Vet test bed.

The main idea behind this paper is to take advantage of game design and implementation to learn several principles of distributed systems. This approach represents the other end of the spectrum with respect to the usual meaning of edutainment. The educational part is the building of a game, instead of playing that game. This paper shows how several of the main principles of distributed systems have a “natural” mapping in distributed games, thus inducing their deep comprehension in the developers of the game. We discuss an experimentation that lasted several years, involving students of computer science, at the forth year of their curricula in our University. The course in distributed systems requires the design and implementation of a distributed game, and the students are requested to perform that task in small groups. The students are requested to design and implement a Web based game between peers, avoiding any form of centralization during the game playing. Moreover, the game has to be tolerant to some kind of faults, keeping coherent behavior for the correct players.

Wireless home entertainment is strongly emerging in the consumer market. This is happening thanks to various number of home appliances that can connect wireless to the Internet, as witnessed by the recent launch of Sony Bravia. For this reason there is an interest, in the research community, to design and develop the protocol architecture of Home Entertainment Centers (HECs). HECs are entertainment hubs capable to handle heterogeneous media, thus behaving as gateways, and to support the main multimedia services (e.g., TVs, game consoles, etc.) at home. As the interactivity of these services is crucial to guarantee a satisfactory quality of service to the end user, it is important to understand which protocols HECs have to use to exchange data and how these perform on a home wireless link. Following recent findings that confirm that TCP still occupies the lion share of Internet residential traffic, the scope of this paper is to show that among the most used and popular candidates, TCP Westwood is capable to best adapt to a home scenario that entails an increase of the bandwidth requirements and a widespread use of wireless connections.

With the development of vehicular networks, it is possible to implement accident warning systems that directly (i.e., without any external supporting infrastructure) alert approaching vehicles. In this scenario, each vehicle is provided with a sensor that, under abnormal conditions, triggers an alarm message. A vehicle that receives this information: (a) warns the driver; and (b) relays such information to following vehicles for safety purposes. We here present an optimal algorithm for one dimensional (1D), multi-lane, strip-shaped portions of roads. It guarantees alarm messages are received along the minimum hop path, even when communications are asymmetric and transmission ranges vary from vehicle to vehicle. To the best of our knowledge, this is the first algorithm capable of reaching such performance under realistic wireless propagation assumptions.

Depression is one of the leading causes of disability. Methods are needed to quantitatively classify emotions in order to better understand and treat mood disorders. This research proposes techniques to improve communication in body sensor network (BSN) that gathers data on the affective states of the patient. These BSNs can continuously monitor, discretely quantify, and classify a patient's depressive states. In addition, data on the patient's lifestyle can be correlated with his/her physiological conditions to identify how various stimuli trigger symptoms. This continuous stream of data is an improvement over a snapshot of localized symptoms that a doctor often collects during a medical examination. Our research first quantifies how the body interferes with communication in a BSN and detects a pattern between the line of sight of an embedded device and its reception rate. Then, a mathematical model of the data using linear programming techniques determines the optimal placement and number of sensors in a BSN to improve communication. Experimental results show that the optimal placement of embedded devices can reduce power cost up to 27% and reduce hardware costs up to 47%. This research brings researchers a step closer to continuous, real-time systemic monitoring that will allow one to analyze the dynamic human physiology and understand, diagnosis, and treat mood disorders.

Recent years have seen an exponential increase of DVD equipped and navigation assisted cars. Nowadays a car trip can be both entertaining for passengers and computer assisted for drivers. In a further integration of automotive and information technologies, cars will be able to communicate to each other and to the Internet supporting safety, infotainment and pollution prevention applications. The research area which investigates topics, Vehicular Ad hoc NETworks (VANETs), is being widely investigated by both industry and academia. Position information plays a central role in many communication routing schemes designed for VANETs. This trend is justified by the feasibility of algorithms that route packets based on geographical proximity to the destination and by the widespread availability of navigation systems in cars. Geographical information is usually assumed accurate and precise. None of the algorithms available in literature, to the best of our knowledge, take into account possible position estimation errors. This paper is a first step in assessing the precision of a commercial GPS receiver for the support of vehicular communications. As we shall see, the performance of the receiver under investigation heavily depends on the type of urban area within this is employed. We believe that a strong understanding of the accuracy of such estimates is important to improve the performance and reliability of a vehicular network infrastructure.

Multicast streaming is gaining increasing importance in wireless ad hoc networks, in part because ad hoc scenarios often include team activities and the requirement for distribution of audio, video and situation awareness to the members. At the network level, techniques for routing the multimedia streams are quite mature. Much more challenging is the allocation of resources, the fair sharing among streams and the control of congestion.

Fast-FMS is a new network protocol designed to support fast and effective multimedia delivery in 3G networks. In particular, Fast-FMS provides a reliable session between two mobile customers that want to transmit multimedia and data while on a voice conversation. The protocol leverages the multi-RAB feature of 2.5+ cellular networks to provide a new almost-real-time class of services that fill the gap between the costly circuit-switched video-call service and the basic services based on MMS. © 2005 IEEE.