Ubiquitous Technology Research Articles

Why Don't We Look at Television?

The television set was for many decades a ubiquitous household technology. Though omnipresent and designed to be watched, it has faded into the background of domesticity. The era of streaming and portable viewing devices questions the continuing need for a television set-an opportune moment to reconsider the materiality of this object technology in domestic life. Taking television's entry into British homes as a case study, this essay asks what the act of looking at-rather than watching-television means. It explores the paradox in television's design and function, both to be viewed and to disappear. The essay argues that its materiality became embedded in mediated debates about design and taste, while television owners appropriated the television set according to their domestic requirements and tastes-sometimes bypassing what manufacturers and designers intended.

PACMHCI V7, MHCI, September 2023 Editorial

We have witnessed astonishing progress in mobile and ubiquitous technology in the past two decades. Our interaction-supporting devices have become increasingly capable and diverse, while the supporting infrastructure, including heterogeneous networks and cloud computing, has matured to enable our vision of a ubiquitous computing environment. As we navigate this new frontier, we find ourselves pondering the words of Bill Buxton: "Now that we can do anything, what should we do?" and, more importantly, "How should it work?" Buxton's thought-provoking statement urges us to shift our focus towards methodological considerations and, crucially, ethics. The MobileHCI community, as a whole, recognizes the importance of ethical practices in shaping our field. While our work has often touched upon privacy-maintaining interactions and service provision, it is time to delve deeper into the ethical dimensions of our research and design choices.

The ‘iron donkey’: the social lives of bicycles in northern Uganda, 1903–2015

This article investigates the history of bicycles – one of the most common technologies – in Acholiland, northern Uganda. Bicycles are among the most common means of transportation in this region, where people are recovering from a brutal armed conflict between the Ugandan government and the rebels of the Lord’s Resistance Army (1987–2006). People who own bicycles in Acholiland often speak of them as local objects. Some owners have even given their bicycles indigenous names. Others have modified their bicycles to fit their worldviews, radically changing the appearance of the bicycles. Examining the history of this ubiquitous technology in northern Uganda unlocks stories of everyday peoples previously unknown to scholars. This article recounts stories of the diffusion of technology in the region, the spread of Christianity and colonial rule, and, most importantly, the domestication of foreign technologies – making them uniquely African.

Large-Scale Indoor Localization Solution for Pervasive Smartphones Using Corrected Acoustic Signals and Data-Driven PDR

With continuous and accelerated urbanization, a large number of location-based services (LBS) have shifted from outdoor to indoor. The pervasive smartphone-based localization has been the subject of extensive work, including signals, algorithms, technologies, solutions, and applications. However, no single ubiquitous technology or solution exists for performing indoor positioning similar to the global navigation satellite system (GNSS) in the outdoor environment. The aim of this work is to develop a practical, precise, and economic smartphone-based localization solution. In order to address the challenges of utilizing the limited audible-band acoustic signal in pervasive smartphone localization, i.e., signal detection, correction, and evaluation, we present a low-cost anchor hardware, two-step signal detection method, data-driven pedestrian dead reckoning (PDR), and robust positioning algorithm. Moreover, we further propose acoustic measurement compensation approaches and measurement quality evaluation and control strategy (MQECS) to improve the performance of position estimation. Six phones, including Huawei Mate9, P9 Plus, OnePlus 6, Honor 8, Mi 10, and Google Pixel 3 are used to evaluate the localization performance in three typical wide area indoor scenarios (i.e., convention center, parking lot, and dining-hall). The total testbed area is accumulated to more than 8,800 square meters. The experimental results demonstrate that the proposed method achieves average positioning accuracies of 0.34 m (static) and 0.67 m (dynamic). In addition, the results show that the overall performance, repeatability, and stability are superior for different scenarios and devices.

Predictive Analysis on Future Impact of Ubiquitous Education Technology in Higher Education and Research

Purpose: Ubiquitous education technology refers to the group of technologies used for the integration of various aspects of higher education and research aiming to create an environment that supports seamless learning, collaboration, and innovation. This approach uses a range of digital tools, platforms, and resources, to enhance teaching and learning, and facilitate research activities to empower students and researchers. Ubiquitous education technology makes online education superior in terms of accessibility, collaboration and communication, personalization and adaptability, and effective research support through providing digital libraries, online databases, and research management tools to enable efficient literature reviews, data analysis, collaboration among researchers, and dissemination of research findings. The benefits of ubiquitous education technology include Enhanced Learning Outcomes, Flexibility and Convenience, Global Collaboration and Networking, and improved Research Efficiency and Innovation. Various challenges like the digital divide, Technical Support and Training, and Data Security and Privacy issues are yet to be addressed. Methodology: The paper uses the exploratory research method in which the relevant information are collected from various sources are analysed, compared, evaluated, and interpreted for the creation of new knowledge. Predictive analysis framework is used for studying the future impact of various education technologies on ubiquitous higher education and Research guiding. Results: In this paper, the various possibilities of the transformation of higher education and research into ubiquitous by embracing digital tools and resources are discussed. It also includes how institutions can create dynamic learning environments that facilitate research collaborations and prepare students for the demands of the digital age. Originality/Value: Based on evaluating the abilities & features of emerging ubiquitous educational technologies, the transformation of the future higher education industry is predicted and forecasted. Type of Paper: Exploratory Research Paper.

A study on the knowledge-based information system for evacuation situation awareness in the case of fire

This study is on designing a knowledge-based information system for evacuation situation awareness in case of fire. First, in the design of this system, various progress of urban fires was stored and learned in the database so that multiple fire situations could be recognized. In addition, it is to be actively applied to fire disaster prevention through the knowledge-based Fire Dynamics Simulator information system so that it can be actively used for situational information of evacuees and property protection. Moreover, this system is designed to reduce damage to human life and property in the event of a fire in a building, etc. For this purpose, fire extinguishment can be predicted based on building information such as structure and building materials. Natural disasters leading to significant fires can be prevented by predicting fire evolution between buildings. Damage to human life and property due to fire can be contained. This system is a knowledge-based information system that optimizes ubiquitous technologies. It can respond to minimize damage by periodically recognizing the situation of evacuees in case of fire and notifying the central control center of the problem.

Using a Smartwatch App to Understand Young Adult Substance Use: Mixed Methods Feasibility Study.

Young adults in the United States exhibit some of the highest rates of substance use compared to other age groups. Heavy and frequent substance use can be associated with a host of acute and chronic health and mental health concerns. Recent advances in ubiquitous technologies have prompted interest and innovation in using technology-based data collection instruments to understand substance use and associated harms. Existing methods for collecting granular, real-world data primarily rely on the use of smartphones to study and understand substance use in young adults. Wearable devices, such as smartwatches, show significant potential as platforms for data collection in this domain but remain underused. This study aims to describe the design and user evaluation of a smartwatch-based data collection app, which uses ecological momentary assessments to examine young adult substance use in daily life. This study used a 2-phase iterative design and acceptability evaluation process with young adults (aged 18-25 y) reporting recent alcohol or cannabis use. In phase 1, participants (8/15, 53%) used the data collection app for 14 days on their Apple Watches to report their substance use patterns, social contexts of substance use, and psychosocial risk factors (eg, affect). After this 14-day deployment, the participants completed a user experience survey and a semistructured interview to record their perspectives and experiences of using the app. Formative feedback from this phase informed feature modification and refinement of the app. In phase 2, an additional cohort (7/15, 47%) used the modified app for 14 days and provided feedback through surveys and interviews conducted after the app use period. Analyses of overall app use patterns indicated high, consistent use of the app, with participants using the app for an average of 11.73 (SD 2.60) days out of 14 days of data collection. Participants reported 67 instances of substance use throughout the study, and our analysis indicates that participants were able to respond to ecological momentary assessment prompts in diverse temporal and situational contexts. Our findings from the user experience survey indicate that participants found the app usable and functional. Comparisons of app use metrics and user evaluation scores indicate that the iterative app design had a measurable and positive impact on users' experience. Qualitative data from the participant interviews highlighted the value of recording substance use patterns, low disruption to daily life, minimal overall burden, preference of platforms (smartphones vs smartwatches), and perspectives relating to privacy and app use in social contexts. This study demonstrated the acceptability of using a smartwatch-based app to collect intensive, longitudinal substance use data among young adults. The findings document the utility of smartwatches as a novel platform to understand sensitive and often-stigmatized behaviors such as substance use with minimal burden.

How to Create Business Value Through Technological Innovations Using ICCT Underlying Technologies

Purpose: Organizations are struggling to sustain and grow in the 21st century due to many challenges and uncertainties while doing their business. Long-term sustaining in the business needs retaining the existing customers and attracting new customers through various strategies for satisfying, delighting, and enlightening existing customers, and creating overwhelming demand through business value creation for attracting new customers. It is a challenge for all the decision-makers to find out how to create business value to retain existing customers and attract new customers. Here, a conceptual and exploratory analysis is made of how the innovations using technology create business value for organizations in general. Methodology: This conceptual analysis uses an exploratory research method. The information is collected using Google, Google Scholar, and Artificial Intelligence GPT search engines using appropriate keywords and prompt engineering respectively and the collected, analysed, compared, evaluated, and interpreted towards creating business value using technology with special emphasis on the use of ICCT underlying technologies. The advantages, benefits, constraints, and disadvantages of business value creation using ICCT underlying technologies for business value creation are listed from stakeholders’ points of view. Outcome: The role of twelve ICCT Underlying Technologies including AI, Blockchain, Business intelligence, Cloud computing, Cyber security, 3D printing, IoT, Quantum computing, Mobile marketing, Information storage technology, Ubiquitous education technology, and VR & AR for Business Value Creation like Innovation and Differentiation, Customer focus, Operational efficiency, Strategic Partnerships and Alliances, Talent Management, Effective Marketing and Branding, Financial Performance and Growth, Sustainability and Corporate Social Responsibility, and Adaptability and Agility. Originality/Value: New knowledge and interpretation are presented on how to create business value for long time sustainability by organizations in every industry. Type o Paper: Exploratory Research Analysis

Over-the-Air Max-Consensus in Clustered Networks Adopting Half-Duplex Communication Technology

This work considers a network of autonomous agents that exploit the superposition property of the wireless channel for achieving max-consensus under communication constraints. In technical applications, superposition (or interference) is traditionally avoided by physically separating transmissions from different agents, e.g., by employing TDMA (Time Division Multiple Access) or FDMA (Frequency Division Multiple Access) protocols. In contrast, Over-the-Air Computation relies on simultaneous transmissions of signals in the same frequency band to boost performance. This paper extends the results presented in Molinari et al. [14] in a significant way: rather than requiring a new and hardly accessible technology that allows simultaneous receiving and transmission of signals (Full-Duplex), we present a solution based on cheap and ubiquitous Half-Duplex technology. However, Half-Duplex technology only allows agents to either receive or transmit at a given time, hence, requiring agents to be grouped into clusters. The proposed method, first, enables each cluster to achieve max-consensus within itself. Then, agents belonging to more than one cluster spread the information across different clusters that are, in general, not synchronized. The proposed max-consensus protocol can deal with asynchronism, and allows the network to achieve max-consensus within a finite number of steps. Simulations confirm our theoretical results.

Understanding and engineering spontaneous orientation polarization in organic light-emitting devices

Organic light-emitting devices (OLEDs) are a ubiquitous technology for displays with growing application in a variety of other spaces. The future success of this technology depends on further improvements in device efficiency and stability. One pathway for improvement relies on engineering molecular orientation in the organic thin films comprising an OLED. This review is focused on the subsequent spontaneous alignment of molecular electric dipole moments, known as spontaneous orientation polarization (SOP), a phenomenon observed for many common OLED materials. The magnitude of polarization fields associated with SOP rival what is experienced in an OLED under high injection and can significantly impact electronic and excitonic behavior. Here, we first review current work describing the mechanism for the formation of SOP, reflecting an interplay between several factors, such as molecular shape, intermolecular interactions, and processing conditions. We also consider several strategies to tune the polarization sign and magnitude, with emphasis on connecting observations to quantitative models of SOP formation. Building on this discussion of SOP in organic thin films, we review how polarization in OLED active layers impacts key aspects of device performance, including charge injection, luminescence efficiency, and stability. Finally, this review concludes with an outlook on areas of future development needed to realize broad control over SOP for a variety of applications, highlighting gaps in our current understanding of this phenomenon.

Toward Tailoring Just-in-Time Adaptive Intervention Systems for Workplace Stress Reduction: Exploratory Analysis of Intervention Implementation.

Integrating stress-reduction interventions into the workplace may improve the health and well-being of employees, and there is an opportunity to leverage ubiquitous everyday work technologies to understand dynamic work contexts and facilitate stress reduction wherever work happens. Sensing-powered just-in-time adaptive intervention (JITAI) systems have the potential to adapt and deliver tailored interventions, but such adaptation requires a comprehensive analysis of contextual and individual-level variables that may influence intervention outcomes and be leveraged to drive the system's decision-making. This study aims to identify key tailoring variables that influence momentary engagement in digital stress reduction microinterventions to inform the design of similar JITAI systems. To inform the design of such dynamic adaptation, we analyzed data from the implementation and deployment of a system that incorporates passively sensed data across everyday work devices to send just-in-time stress reduction microinterventions in the workplace to 43 participants during a 4-week deployment. We evaluated 27 trait-based factors (ie, individual characteristics), state-based factors (ie, workplace contextual and behavioral signals and momentary stress), and intervention-related factors (ie, location and function) across 1585 system-initiated interventions. We built logistical regression models to identify the factors contributing to momentary engagement, the choice of interventions, the engagement given an intervention choice, the user rating of interventions engaged, and the stress reduction from the engagement. We found that women (odds ratio [OR] 0.41, 95% CI 0.21-0.77; P=.03), those with higher neuroticism (OR 0.57, 95% CI 0.39-0.81; P=.01), those with higher cognitive reappraisal skills (OR 0.69, 95% CI 0.52-0.91; P=.04), and those that chose calm interventions (OR 0.43, 95% CI 0.23-0.78; P=.03) were significantly less likely to experience stress reduction, while those with higher agreeableness (OR 1.73, 95% CI 1.10-2.76; P=.06) and those that chose prompt-based (OR 6.65, 95% CI 1.53-36.45; P=.06) or video-based (OR 5.62, 95% CI 1.12-34.10; P=.12) interventions were substantially more likely to experience stress reduction. We also found that work-related contextual signals such as higher meeting counts (OR 0.62, 95% CI 0.49-0.78; P<.001) and higher engagement skewness (OR 0.64, 95% CI 0.51-0.79; P<.001) were associated with a lower likelihood of engagement, indicating that state-based contextual factors such as being in a meeting or the time of the day may matter more for engagement than efficacy. In addition, a just-in-time intervention that was explicitly rescheduled to a later time was more likely to be engaged with (OR 1.77, 95% CI 1.32-2.38; P<.001). JITAI systems have the potential to integrate timely support into the workplace. On the basis of our findings, we recommend that individual, contextual, and content-based factors be incorporated into the system for tailoring as well as for monitoring ineffective engagements across subgroups and contexts.

The Changing Role of Higher Education in the Era of AI-based GPTs

Purpose: Technology has become an increasingly important tool in solving social and economic problems. Advents in technology are changed many aspects in the education sector. Ubiquitous education technology offered an alternative way of providing education anytime, anywhere, and any amount of time thereby reducing both the cost and time spent on higher education. It also increases the quality of education and made it affordable to everyone. Currently, the use of AI-based GPYs changed the game further, and by providing ubiquitous global information, GPTs can change the higher education model further. In this paper, we have made an exploratory analysis on how AI-based GPTs are affecting the conventional model of education both offline &amp; online. Findings: There is a paradigm shift in the focus of the objective of higher education. Earlier the focus was on learning skills by information identification, information collection, understanding, and applying to solve problems. Now after the availability of AI-based GPTs, the focus is shifted to the use of research skills like Information analysis, comparison, evaluation, interpretation, and creation /generation to identify new problems along with their optimum solution. Originality/Value: The paper compares the changing role of higher education from learning skill focus to research skill focus due to the advent and free availability of AI-based GPTs to HE stakeholders. Type of Paper: Exploratory study.

Small farmers, big tech: agrarian commerce and knowledge on Myanmar Facebook.

Despite increasing attention to the sensors, drones, robots, and apps permeating agri-food systems, little attention has been paid to social media, perhaps the most ubiquitous digital technology in rural areas globally. This article draws on analysis of farming groups on Myanmar Facebook to posit social media as appropriated agritech: a generic technology incorporated into existing circuits of economic and social exchange that becomes a site of agrarian innovation. Through analysis of an original archive of popular posts collected from Myanmar-language Facebook pages and groups related to agriculture, I explore the ways that farmers, traders, agronomists and agricultural companies use social media to further agrarian commerce and knowledge. These activities evidence that farmers use Facebook not only to exchange market or planting information, but also to interact in ways structured by existing social, political and economic relations. More broadly, my analysis builds on insights from STS and postcolonial computing to disrupt assumptions about the totalizing power of digital technologies and affirm the relevance of social media to agriculture, while inviting new research into the surprising, ambiguous relationships between small farmers and big tech.

Benefits of RFID Technology in the Provision of Medical Services at Mass Gathering Events

Introduction:Radiofrequency Identification (RFID) is becoming a ubiquitous technology that provides methods of tracking and organizing complex processes, and has had previously described benefits when used in medical and clinical situations such as disaster and mass casualty incidents. However, the potential benefits of this technology have not yet been examined or applied to mass gathering events such as music festivals using the medical lens.Method:RFID at music festivals was observed and characterized at a Canadian multi-day festival through a combination of (1) observation of real world application of the use of RFID-enabled attendee wristbands and (2) the development of a proposed implementation framework using expert input in event medical care, public health, festival safety and event organization. Potential roles for RFID technology in enhancing attendee safety, facilitating event medical care and collaborating with other on-site services, and promoting research agendas for these unique events were explored.Results:Observed and theoretical roles for RFID fell into four main domains: (1) the presence of important encoded personal health data and contacts specific to individuals that would be accessible in case of an emergency, (2) the unique, anonymous identification of attendees who access (and re-access) medical as well as other services, including during handovers between these services, (3) support for any larger public health research projects aimed at understanding the behaviors and flow of attendees, including recreational substance use and related harm reduction efforts, and (4) the storage of festival-tailored data throughout the event on RFID-enabled wristbands (eg previous medical visit details, self-entered substance use history, etc).Conclusion:The use of RFID at music festivals has clear benefits. It allows for the dynamic access and retrieval of important data that can aid safety and support the provision of timely and tailored medical care. Security and privacy issues need consideration where attendee data is concerned.

Human Activity Recognition from Wi-Fi CSI data using Principal Component-based Wavelet CNN

Human Activity Recognition (HAR) is an emerging technology with applications in the surveillance, security, and healthcare sectors. Noninvasive HAR systems based on Wi-Fi Channel State Information (CSI) signals can be developed leveraging the rapid growth of ubiquitous Wi-Fi technologies and the correlation between CSI dynamics and body motions. In this paper, we propose Principal Component-based Wavelet Convolutional Neural Network (or PCWCNN) – a novel approach for HAR that offers robustness and efficiency for practical real-time applications. Our proposed method incorporates two efficient preprocessing algorithms – the Principal Component Analysis (PCA) and the Discrete Wavelet Transform (DWT). We employ an adaptive activity segmentation algorithm that is accurate and computationally light. Additionally, we used Wavelet CNN – a deep convolutional network analogous to the well-studied ResNet and DenseNet networks, for activity classification. We evaluate the performance of our proposed PCWCNN algorithm on both line-of-sight data and non-line-of-sight data. We empirically show that our proposed PCWCNN algorithm performs very well on these real datasets, outperforming relevant state-of-the-art approaches.

P155 Function is impaired during patient-reported idiopathic inflammatory myopathy flares - results from a longitudinal smartphone-based study

Abstract Background/Aims Idiopathic inflammatory myopathy (IIM) is a chronic autoimmune inflammatory disease characterised by myositis, thus impacting function and activities of daily living. Patients frequently refer to an exacerbation of IIM symptoms as a “flare”, however IIM flares have not been defined. High-frequency data collected via ubiquitous digital technologies, such as daily patient-reported outcome measurements, provide the opportunity to identify novel findings. This study aims to investigate associations between patient-reported IIM flares and function, thus characterising a priority area for patients. Methods The Myositis Physical Activity Device Study recruited a UK-based adult IIM cohort who completed weekly function and flare questions (i.e. every 7 days) via a specially designed smartphone-based app throughout a 13 week period in 2019/20. Weekly function questions, selected as priorities by a patient focus group from the Health Assessment Questionnaire, addressed carrying, exercise, socialising, reaching, and bending (4-point ordinal answers). A weekly flare question (binary “yes”/“no”) was also asked. The distribution of answers for function questions in participant-reported flare and non-flare weeks was calculated. Fisher’s exact test was used to determine whether there is a statistically significant difference between ‘flare’ and ‘non-flare’ weeks within each domain. Results Data on 21 participants (65% female) were collected across thirteen study weeks. In total, 1330 function questions and 266 flare questions were answered. 83 flare weeks and 183 non-flare weeks were reported. A lower proportion of answers across each function domain were answered as “without any difficulty” in flare weeks, compared to non-flare weeks (Table 1); the proportional difference was greatest for carrying and exercising. A higher proportion of answers across each function domain were answered as “with some difficulty” or “with much difficulty” in flare weeks, compared to non-flare weeks; the proportional difference was greatest for reaching and bending. Statistically significant difference (p-value &amp;lt;0.05, calculated via Fisher’s exact test) of all domains was observed between flare and non-flare weeks. Conclusion Functional impairment is associated with patient-reported IIM flare. The impact of flares upon activities of daily living highlights the need for further characterisation of IIM flares and the potential of patient-reported flares as a “digital biomarker” via smartphone-based app reporting. Disclosure G. Howard: None. N.S. Krogh: None. W. Dixon: None. H. Chinoy: None. A. Oldroyd: None.

The Development of a Research Framework for Inventory Performance Improvement of the Automotive Manufacturing Industry: Review of Literature from 2011 - 2020

The main purpose of this study is to examine existing literature on how inventory performance in the automotive manufacturing supply chain can be improved. Articles reviewed are from the last ten years that is related to automotive manufacturing industry and targeted to inventory performance. Transformational changes are happening in the automotive manufacturing supply chains with ubiquitous technology leading the transformation. Inherently, due to its outsourced manufacturing in dispersed locations globally, communication and coordination would be affected in some form. This results in companies in the automotive manufacturing supply chain resorting to holdmore inventory to mitigate the uncertainty. Therefore, to address this issue, this study conceptualises a theoretical framework that is adapted from Galbraith’s (1974) Organisational Information Processing Theory. The recommended framework may provide a guide to practitioners on understanding the intricacies of supply chain integration and how technology tools may help in mitigating risks and improve inventory performance.

The Management of IoT-Based Organizational and Industrial Digitalization Using Machine Learning Methods

Recently, the widespread adoption of the Internet of Things (IoT) model has led to the development of intelligent and sustainable industries that support the economic security of modern societies. These industries can offer their participants a higher standard of living and working services via digitalization. The IoT also includes ubiquitous technology for extracting context information to deliver valuable services to customers. With the growth of connected things, the related designs often suffer from high latency and network overheads, resulting in unresponsiveness. The continuous transmission of enormous amounts of sensor data from IoT nodes is problematic because IoT-based sensor nodes are highly energy-constrained. Recently, the research community in the field of IoT and digitalization has labored to build efficient platforms using machine learning (ML) algorithms. ML models that run directly on edge devices are intensely interesting in the context of IoT applications. The use of intelligence ML algorithms in the IoT can automate training, learning, and problem-solving while enabling decision-making based on past data. Therefore, the primary aim of this research is to provide a systematic procedure to review the state-of-the-art on this scope and offer a roadmap for future studies; thus, a structure is introduced for industry sustainability, based on ML methods. The publications were reviewed using a systematic approach that divided the papers into four categories: reinforcement learning, semi-supervised learning, unsupervised learning, and supervised learning. The results showed that ML models could manage IoT-enabled industries efficiently and provide better results compared to other models, with significant differences in learning time and performance. The study findings are considered from a variety of angles concerning the industrial sector’s capacity management of the new elements of Industry 4.0 by combining the industry IoT and ML. Additionally, unique and relevant instructions are provided for the designers of expert intelligent production systems in industrial domains.

Socioenactive Interaction: Addressing Intersubjectivity in Ubiquitous Design Scenarios

People’s interaction with computers has been explained through several theories and methods throughout the history of computers and their uses; more complex scenarios of ubiquitous and pervasive computing experimented nowadays invite other ways of considering human-technology interaction. The enactive approach to cognition, centered in human experience in the environment, has shown itself as a possibility to understand interaction in these new scenarios. In this paper we present a view of interaction, named socioenactive, to explain our relation with contemporary computational technologies in scenarios of ubiquitous and pervasive systems, understood from the enactivist perspective. After presenting core concepts related to intersubjectivity that helped to build up what we mean by socioenactive interaction, we illustrate it with some scenarios of ubiquitous and pervasive technology (situated in a school, a museum and a hospital), designed for the study of the phenomena of interaction. Graspable aspects of intersubjectivity are raised in the considered scenarios and affordances for the socioenactive interaction are illustrated. Implications of the study are discussed leading to aspects to consider in a research agenda in the field.

Single-Shot Reconfigurable Femtosecond Imaging of Ultrafast Optical Dynamics.

Understanding ultrafast dynamics in the femtosecond timescale plays a pivotal role in fundamental research and technology innovation. Spatiotemporal observation of those events in real-time requires imaging speeds greater than 1012 frames per second (fps), far beyond the fundamental speed limits of the ubiquitous semiconductor sensor technologies. In addition, a majority of femtosecond events are non-repeatable or difficult-to-repeat since they either work in a highly unstable nonlinear regime or require extreme or rare conditions to initiate. Therefore, the traditional pump-probe imaging approach fails since it heavily depends on precise event repetition. Single-shot ultrafast imaging emerges as the only solution; however, existing techniques cannot reach more than 15×1012 fps, and they only record an insufficient number of frames. Compressed ultrafast spectral photography (CUSP) is proposed to overcome these limitations. Here, CUSP's full design space is explored by manipulating the ultrashort optical pulse in the active illumination. Via parameter optimization, an extraordinarily fast frame rate of 219×1012 fps is achieved. This implementation of CUSP is also highly flexible, allowing various combinations of imaging speeds and numbers of frames (several hundred up to 1000) to be readily deployed in diverse scientific studies, such as laser-induced transient birefringence, self-focusing, and filaments in dielectric media.