Due to the growing adoption of Immersive Virtual Reality (IVR) in various contexts, understanding how virtual workspaces impact humans and how they should be designed is crucial. Exploring optimal design strategies that can enhance well-being within IVR environments becomes important. In real contexts, biophilic design offers a way to improve well-being by introducing natural elements. IVR can go beyond real-world constraints for integrating biophilic elements, but this aspect is scarcely addressed in literature. A valuable assistance to support the design of IVR workspaces could be offered by generative Artificial Intelligence (AI), which is becoming increasingly integrated into everyday life. The aim of this work is twofold: (i) assessing if the biophilic design of IVR workspaces can improve human well-being and (ii) investigating if AI can inspire the biophilic design properly. Thus, we conducted a user study comparing psycho-physiological and subjective metrics in three conditions. A workspace without biophilia was used as a baseline. The same was enriched with two biophilic designs: one suggested by expert designers and another inspired by AI-generated graphics, simulating a not-expert developer. The findings showed that both biophilic designs significantly improved well-being; however, AI suggestions led to a reduced sense of presence in the IVR environment.

This study aims to explore the use of Augmented Reality (AR) visual assets to convey procedural instructions, specifically for conveying information about component orientation. We focused on assembly scenarios where no affordance is provided for orientation while maintaining a consistently high affordance for how components are mounted. This information is recurrent in tasks where users are familiar with components that fit together without needing specialized tools but lack knowledge of the specific orientations required for the assembly. A typical example is placing rubber gaskets that fit smoothly into grooves but where no markings indicate the correct sealing side. We evaluated six different AR presentation modes for conveying component orientation: image, video, static side-by-side product model, animated side-by-side product model, static in-situ product model, and animated in-situ product model. The literature provides no clear agreement on which is the most effective. To fill this gap, we conducted a user study with 36 participants, measuring completion time, accuracy, and cognitive load across the six AR presentation modes. We also analyzed how users interacted with each of them and collected user subjective feedback. Our findings revealed that the animated side-by-side product model ensures better completion time, demanding less cognitive load and being favored by users.

The creation and management of content are among the main open issues for the spread of Augmented Reality. In Augmented Reality interfaces for procedural tasks, a key authoring strategy is chunking instructions and using optimized visual cues, i.e., tailored to the specific information to convey. Nevertheless, research works rarely present rationales behind their choice. This work aims to provide design guidelines for the localization of in-view and not occluded components, which is recurrent information in technical documentation. Previous studies revealed that the most suited visual cues to convey this information are auxiliary models, i.e., abstract shapes that highlight the space region where the component is located. Among them, 3D arrows are widely used, but they may produce ambiguity of information. Furthermore, from the literature, it is unclear how to design auxiliary model shapes and if they are affected by the component shapes. To fill this gap, we conducted two user studies. In the first study, we collected the preference of 45 users regarding the shape, color, and animation of auxiliary models for the localization of various component shapes. According to the results of this study, we defined guidelines for designing optimized auxiliary models based on the component shapes. In the second user study, we validated these guidelines by evaluating the performance (localization time and recognition accuracy) and user experience of 24 users. The results of this study allowed us to confirm that designing auxiliary models following our guidelines leads to a higher recognition accuracy and user experience than using 3D arrows.

Immersive Virtual Reality (IVR) training offers the capability to industrial workers to acquire skills and address complex tasks by immersing them in a safe and controlled virtual environment (VE). However, in the literature, IVR training is mainly based on principles of standardization and efficiency without considering the operators’ well-being. A novel design approach consists of the introduction in the VE of Positive Computing to improve workers’ well-being by applying the Biophilia hypothesis. In this work, we explored the possibility of introducing biophilic elements in a VE training scenario that would support psychological well-being and human potential. However, the introduction of virtual elements not related to the training task may distract operators, impairing their performance. We selected as a training scenario the assembly of a real truck engine. It is accomplished in a workstation, and operators do not interact with the surrounding VE. Therefore, we placed the training area into four different types of VEs: 3D Minimal (MIN), 3D Minimal Biophilic enriched (MIN+BIO), 3D Realistic (REAL), and 3D Realistic Biophilic enriched (REAL+BIO). We compared the MIN and REAL scenarios with the respective biophilic enriched scenarios. The performance of 40 participants was evaluated in terms of completion time, object fixation time, training task accuracy, knowledge accuracy, cognitive load, and user experience. The results revealed that introducing biophilic elements in a VR training environment attracts users’ attention in the idle phase of the training. In contrast, they keep concentrating on the task without worsening their performance during the task accomplishment.

Microblogging services, such as Twitter, are gaining interests as a means of sharing information in social networks. Numerous works have shown the potential of using Twitter posts (or tweets) in order to infer the existence and magnitude of real-world events. In the medical domain, there has been a surge in detecting public health related tweets for early warning so that a rapid response from health authorities can take place. In this paper, we present a temporal analytics tool for supporting a comparative, temporal analysis of disease outbreaks between Twitter and official sources, such as, World Health Organization (WHO) and ProMED-mail. We automatically extract and aggregate outbreak events from official outbreak reports, producing time series data. Our tool can support a correlation analysis and an understanding of the temporal developments of outbreak mentions in Twitter, based on comparisons with official sources.

Nowadays a large number of companies world-wide has moved their applications in the cloud, exploiting a lot of types of functions, such as customer relationship management, human resources, accounting and document sharing. In this work we propose "'CloSe"', a cloud system for document composition, which offers editing/composing aiding services by exploiting semantic based technology. Close is the evolution, in cloud technology, of a monolithic system architecture for document processing, based on semantic methodologies, that we have developed in the past years. We intend to migrate our system procedures to the Internet Cloud technology that guarantees several advantages in terms of usability, scalability and fault tolerance. The proposed system will help the users in the process of writing documents, exploiting information and data contained in apposite document bases, collected from heterogeneous sources, in order to suggest proper fragments to be inserted into the document. We have produced a system prototype that realizes semantic retrieval functionalities, in order to assist the specialist and generic user in the document composition aiding activities. Moreover we have reported some experimental results that we have carried out for evaluating the impact of the system on enhancing user effort in composing documents by suggesting appropriate document segments, which encouraged us to extend the system in the cloud.

The coexistence of different formats and physical supports to store data is one of the main open issues in document management systems, in particular, the presence of unstructured data represents a huge limitation for the elaboration and analysis of many documents and processes. At this aim we are exploiting the adoption of different techniques to analyze texts and automatically extract relevant information, concepts or complex relations, in this paper we proposed a general framework for data transformation and implemented such model trough an architecture based on semantic analysis. The analysis that can be performed on data has many different applications, in this paper we illustrate an interesting perspective related on how to enforce a fine grained access control on sensitive data that are in capsulated in unstructured, monolithic files. We also presented a case study for the formalization and protection of e-health medical records.

The exchange of information between heterogeneous and distributed health information systems preserving the semantics is an important open issue for the health care sector. In this paper, we propose an approach that, exploiting the Semantic Web technologies, has the objective of allowing semantic interoperability among software agents for e-Health applications that preserves, not only the semantic of transmitted messages, but also the subjectivity of agent's world vision in the communication The proposed approach exploits the Semantic Triangle Model to differentiate the roles of referents (real world objects) and concepts (mental image or impression about a real object) in the communication process and ensures an effective semantic interoperability without the need of a unique shared conceptualization.

The e-Health is going to change the way how patients and healthcare providers interact. The exchange of confidential and integer information is one of the major open issues for the health care sector. While it is quite easy to enforce fine grain access control policies to new well structured medical records managed by newly designed information systems, many eHealth systems are based on “document management systems”. In the practice the system provides a digital version of the whole medical record and it is impossible to enforce fine grain access rules. In this paper we propose the adoption of a semantic based methodology that is able to automatically retrieve the security level associated to a portion of a medical record and use this information to classify resources and locate the proper security rules to apply.

In this work we present SpLaSH (Spoken Language Search Hawk), a toolkit used to perform complex queries on spoken language corpora. In SpLaSH, tools for the integration of time aligned annotations (TMA), by means of annotation graphs, with text aligned ones (TXA), by means of generic XML files, are provided. SpLaSH imposes a very limited number of constraints to the data model design, allowing the integration of annotations developed separately within the same dataset and without any relative dependency. It also provides a GUI allowing three types of queries: simple query on TXA or TMA structures, sequence query on TMA structure and cross query on both TXA and TMA integrated structures. Index Terms: search tools, speech corpora, time-aligned annotations, text-aligned annotations.