Ubiquitous Technology Research Articles

Evaluating the effectiveness and applicability of UBL (ubiquitousbased learning) in a nursing training course for dementia care

Background: The concept of Ubiquitous technologies has been introduced to medical education in several years, there has been limited publications, particularly in a nursing education. Purpose: This study assessed the effectiveness and the applicability of a UBL course in nursing training courses on dementia care. Materials and method: A controlled quasi-experimental study for 70 nursing students at Hue University of Medicine and Pharmacy were randomly selected and divided into control group with traditional teaching and research group taught by UBL. A pre-test and post-test assessed student’s knowledge (DKAT2 scale), attitude (DAS scale) and confidence (CODE scale) on dementia care were done. Results: In the DKAT2 scale and DAS scale, the intervened average score in the research group is higher control group: DKAT2: N2 = 16.86, N1 = 15.48 (p < 0.005); DAS: N2 = 102.46, N1 = 98.37 (T-test N2-N1 = 1.233, p = 0.222). In the CODE scale, the difference is non statistically significant in the two research groups and control groups (Chi- Square = 0.108, p = 0.743). Assessing the applicability of UBL in nursing training courses on dementia care, 68.6% of students rated good (Chi-Square = 4.829, p = 0.028). Conclusion: UBL contributes to improving the knowledge, perceptions, and confidence effectively of nurses students in terms of caring for patients with mental impairments. Key words: Ubiquitous-based Learning, Dementia, nursing training

LifeSnaps, a 4-month multi-modal dataset capturing unobtrusive snapshots of our lives in the wild

Ubiquitous self-tracking technologies have penetrated various aspects of our lives, from physical and mental health monitoring to fitness and entertainment. Yet, limited data exist on the association between in the wild large-scale physical activity patterns, sleep, stress, and overall health, and behavioral and psychological patterns due to challenges in collecting and releasing such datasets, including waning user engagement or privacy considerations. In this paper, we present the LifeSnaps dataset, a multi-modal, longitudinal, and geographically-distributed dataset containing a plethora of anthropological data, collected unobtrusively for the total course of more than 4 months by n = 71 participants. LifeSnaps contains more than 35 different data types from second to daily granularity, totaling more than 71 M rows of data. The participants contributed their data through validated surveys, ecological momentary assessments, and a Fitbit Sense smartwatch and consented to make these data available to empower future research. We envision that releasing this large-scale dataset of multi-modal real-world data will open novel research opportunities and potential applications in multiple disciplines.

Development of refrigeration and heat pump systems

Despite continual development over more than two centuries there is still great scope for significant development in the realms of mechanical cooling and heating. This paper reviews the nature of the historical development and identifies key motivations for technical development. It seeks to highlight where there is greatest need for future development in this ubiquitous technology. The story of the development of mechanical refrigeration is dominated by the choices made with regard to the working fluid used in the system. These choices dictate the operating parameters of temperature and pressure that the system must withstand as well as introducing constraints related to material compatibility, so the agenda for the mechanical development of systems is set by the selection of the refrigerant. All of these systems are classed as heat pumps because they extract heat from one location and deliver it to another. The commercial demand for mechanical cooling in the 19th century meant that all of these early heat pump systems were used for cooling. The concept of using the same cycle to deliver useful heat was not commercialised until the mid-twentieth century and in some ways this application of the heat pump is still in the early stages of development, particularly with regard to market penetration.

Multi-Institutional Validation of a Smartphone-Based Surface Guided Radiation Therapy (SGRT) Tracking System for Respiratory Monitoring in Radiation Therapy

<h3>Purpose/Objective(s)</h3> Surface guidance radiation therapy (SGRT) systems are becoming standard-of-care for patient setup and motion monitoring. However, commercial systems remain inaccessible to resource-limited clinics around the world. The iOS Surface Audiovisual Biofeedback (iSAVB) system implements ubiquitous mobile technology as a versatile tool for surface imaging in resource-strapped clinics. The purpose of this study is to establish a robust validation platform, commission iSAVB at multiple participating institutions, and validate iSAVB using phantom motion and against commercial systems during patient treatments. <h3>Materials/Methods</h3> Three participating institutions are implementing, validating, and comparing the iSAVB system against current clinical SGRT systems. The iSAVB system consists of depth camera enabled iOS device, to acquire real-time point-cloud data for surface rendering, a 3D printed stand capable of mounting and indexing on a treatment couch, and aa tablet (or external workstation) for audio-visual feedback and signal processing. Validation of the iSAVB system was performed against commercial optical systems at each center using a respiratory motion phantom. Motion traces were analyzed using linear regressions and Bland-Altman analysis. <h3>Results</h3> The iSAVB system was successfully installed at an initial institution and tested on phantoms and healthy volunteers. For free-breathing traces, iSAVB was significantly correlated to phantom input motion (r=0.99, p<0.0001; bias=0.00±0.05cm, 95%CI=−0.1cm,0.1cm) and commercial system motion (r=0.99, p<0.0001; bias=0.00±0.07cm, 95%CI=−0.14cm,0.14cm). Systems are currently being installed at the two additional institutions that will perform similar commissioning and validation. <h3>Conclusion</h3> A multi-center validation shows the iSAVB system can be used for surface motion monitoring and provides SGRT capabilities similar to current high-end clinical systems. The iSAVB system can be used for 3D/IMRT/VMAT treatments, although future validation is required for SBRT treatments. Future work includes establishing reliable commissioning protocols that follow TG-302 guidelines for resource-strapped departments to benefit from affordable and accurate surface imaging guidance. Reference:

Exploring children’s exposure to voice assistants and their ontological conceptualizations of life and technology

Digital Voice Assistants (DVAs) have become a ubiquitous technology in today’s home and childhood environments. Inspired by (Bernstein and Crowley, J Learn Sci 17:225–247, 2008) original study (n = 60, age 4–7 years) on how children’s ontological conceptualizations of life and technology were systematically associated with their real-world exposure to robotic entities, the current study explored this association for children in their middle childhood (n = 143, age 7–11 years) and with different levels of DVA-exposure. We analyzed correlational survey data from 143 parent–child dyads who were recruited on ‘Amazon Mechanical Turk’ (MTurk). Children’s ontological conceptualization patterns of life and technology were measured by asking them to conceptualize nine prototypical organically living and technological entities (e.g., humans, cats, smartphones, DVAs) with respect to their biology, intelligence, and psychology. Their ontological conceptualization patterns were then associated with their DVA-exposure and additional control variables (e.g., children’s technological affinity, demographic/individual characteristics). Compared to biology and psychology, intelligence was a less differentiating factor for children to differentiate between organically living and technological entities. This differentiation pattern became more pronounced with technological affinity. There was some evidence that children with higher DVA-exposure differentiated more rigorously between organically living and technological entities on the basis of psychology. To the best of our knowledge, this is the first study exploring children’s real-world exposure to DVAs and how it is associated with their conceptual understandings of life and technology. Findings suggest although psychological conceptualizations of technology may become more pronounced with DVA-exposure, it is far from clear such tendencies blur ontological boundaries between life and technology from children’s perspective.

Designing in Pandemic Context: Scientific Collaboration through the OpenDesign Platform

Abstract The Coronavirus pandemic and the consequent situation of social isolation have affected research design, especially in fields working directly with people. While online tools enable communication and collaboration, some specific domains involving contemporary technology-based systems, such as socioenactive systems, demand a deeper understanding of human-embodied action in real-world scenarios with ubiquitous technology. This work addresses this issue by presenting a study in which a research team used the OpenDesign Platform (ODP) to conduct a process of ideation and consolidation of a socioenactive-based system solution during pandemics and physical presence limitations. The contributions are twofold: addressing the demands of the research team working remotely and envisaging an interaction scenario for people in a socioenactive system, even without their copresence in the same physical space. Results have shown the strengths and weaknesses of the ODP and lessons learned towards supporting systems for teamwork in such systems’ ideation context.

The Development of Intelligent Education and Teachers' Professional Informatization Led by an Intelligent Ubiquitous Network.

This study applies intelligent ubiquitous network technology to the field of education and leads to the benign development of intelligent education and teachers' professional informatization. This study proposes the concepts of eco-classroom, smart education, and flipped classroom and conducts practical research on the teaching effectiveness of the three elements of eco-classroom: teachers, students, and environment. Because of the problems of inaccurate positioning of data fusion, single application function, and difficulty of automatic correlation of data stored in multiple networks in the intelligent ubiquitous sensing environment, the method and path of multidimensional data fusion governance are proposed and put into practice to achieve good results in practice. Based on the characteristics of ubiquitous learning in time, space, and dimensional changes between reality and time, combined with the law of knotted learning and Bloom's mastery learning theory, the five components of the teaching model and their correlations are sorted out, and the teaching model of higher education under the vision of ubiquitous learning is constructed to achieve the goal of students' mastering knowledge and skills and promote the innovation of the education and teaching model. The model interaction site is created, a ranking system is developed, and professional standards for the new era are developed to help educators reconstruct their professional competencies. The concept and characteristics of knowledge sharing in the ubiquitous network environment are analyzed, the knowledge sharing model in the ubiquitous network learning environment is constructed, the status of knowledge sharing practice in the ubiquitous network environment is studied, and suggestions for improvement are put forward to optimize knowledge sharing in the ubiquitous network learning environment.

Automatic speech recognition for unmanned aerial vehicles

Unmanned aerial vehicles (UAVs), also known as unmanned aerial systems (UASs), are quickly becoming a ubiquitous technology, poised to enter some key large-scale markets in the very near future. Fleets of such vehicles will be required in these large-scale deployments for commercial, industrial, and emergency response, along with the ability to efficiently control these fleets. Voice control and communication between human operators and these fleets will become imperative. This paper explores the framework for building an automatic speech recognition (ASR) use to the control of unmanned aerial vehicles (UAVs). The ARS system will be used by Aeronyde Corporation to fully-autonomous fleets with minimal human intervention. Aeronyde Corporation is working to shift and advance the current industry thinking of unmanned platforms from Remotely Piloted Aircraft (RPA) to fully-autonomous fleets with minimal human intervention. The Aeronyde Avionics package enables a single operator to control and monitor missions of many drones in real time anywhere in the world. The “1 Pilot – Many Drones” approach to aerial data collection is revolutionary for Big Data aggregation and analytics of the 4th Industrial Revolution. Multi-UAV autonomous aerial systems will transform data acquisition for many commercial applications, including: agriculture and forestry, railroad inspections, pipeline inspections, powerline inspections, windmill inspections, terrain mapping, search and rescue, firefighting and police work, and border patrol.

The kind of problem a smart city is

Digital technologies not only alter the material fabric of cities, but condition and constrain the complex networks of trust that emerge among neighbours and strangers as they engage one another in shared civic spaces. In this sense, a media ecology of the city would borrow from studies of urban sociology, political economy and cybernetics to reconsider what ethical implications smart technologies would have when sown into the fabric of an urban environment. This article introduces Jane Jacobs’s urban theory as a complexity approach to media ecology that provides insight into how urban environments, as media of communication and commerce, cultivate the ethical character of social relations among neighbours and strangers. It is argued that Jacobs’s urban theory provides sufficient ground for figuring the ethical implications of highly integrated and ubiquitous digital technologies within the organized complexity of urban environments and offers an alternative way of cultivating urban ecologies of communication.

Competency Experience-Based Training (CEBT) Model with Ubiquitous Community of Practice (U-CoP) to Enhance Transformation Digital Supervisor

Research subject Competency Experience-Based Training (CEBT) Model with Ubiquitous Community of Practice (U-CoP) to Enhance Transformation Digital Supervisor. This research aims to evaluate the digital supervisor competency trained with the Competency Experience-Based Training (CEBT) Model with Ubiquitous Community of Practice (U-CoP). The researcher has divided the research process into 3 steps as follows: Step 1: To develop the Competency Experience-Based Training (CEBT) Model with Ubiquitous Community of Practice (U-CoP) to enhance transformation digital supervisor. Step 2: To develop the Competency Experience-Based Training course with Ubiquitous Community of Practice (U-CoP) to enhance transformation digital supervisor. Step 3: Evaluate the digital supervisor competency trained with the Competency Experience-Based Training (CEBT) Model with Ubiquitous Community of Practice (U-CoP). The results of the research were as follows: 1) the Competency Experience-Based Training course with Ubiquitous Community of Practice (U-CoP) to enhance transformation digital supervisor, it consists of 3 main processes and 10 sub-steps. Ubiquitous community of practice consists of 2 parts. 1) Community of practice, and Ubiquitous technology 2) Competency Experience-Based Training course with Ubiquitous Community of Practice (U-CoP) to enhance transformation digital supervisor consisting of 6 components. The results of the evaluation of digital supervisor competency in training participants with a model developed using pre-training and post-training surveys showed that trainees scored higher than their pre-training digital supervisor competency at a statistically significant .01 level.

Understanding Coping Intentions of Fitness Tracker Users: An Empirical Investigation Using Fear Appeals

A rapid increase in violations of health information privacy in the context of ubiquitous technology has prompted the paramount importance of academic attention to users’ behavior post data breaches. This research explores the impact of privacy concerns and perceived threats to privacy violations on fitness tracker users’ coping behaviors. A model was synthesized by combining the core dimensions of the Extended Parallel Process Model, Internet Users’ Information Privacy Concern, and Coping Theory. A survey was conducted among 260 fitness tracker users. The Structural Equation Modeling results indicate privacy concern strongly influences an individual’s perceived threat, affecting one’s choice of post-privacy violation coping behavior. Further, results confirm the fear of losing one’s data privacy, resulting in a shift in the attitude towards the technology itself. Manufacturers and policymakers need to re-examine privacy policies and post data breach protocols keeping in mind consumer coping behaviors.

Multiclass Classification of Grape Diseases Using Deep Artificial Intelligence

Protecting agricultural crops is essential for preserving food sources. The health of plants plays a major role in impacting the yield of agricultural output, and their bad health could result in significant economic loss.This is especially important in small-scale and hobby-farming products such as fruits. Grapes are an important and widely cultivated plant, especially in the Mediterranean region, with an over USD 189 billion global market value. They are consumed as fruits and in other manufactured forms (e.g., drinks and sweet food products). However, much like other plants, grapes are prone to a wide range of diseases that require the application of immediate remedies. Misidentifying these diseases can result in poor disease control and great losses (i.e., 5–80% crop loss). Existing computer-based solutions may suffer from low accuracy, may require high overhead, and be poorly deployable and prone to changes in image quality. The work in this paper aims at utilizing a ubiquitous technology to help farmers in combatting plant diseases. Particularly, deep-learning artificial-intelligence image-based applications were used to classify three common grape diseases: black measles, black rot, and isariopsis leaf spot. In addition, a fourth healthy class was included. A dataset of 3639 grape leaf images (1383 black measles, 1180 black rot, 1076 isariopsis leaf spot, and 423 healthy) was used. These images were used to customize and retrain 11 convolutional network models to classify the four classes. Thorough performance evaluation revealed that it is possible to design pilot and commercial applications with accuracy that satisfies field requirements. The models achieved consistently high performance values (&gt;99.1%).

Sensor Technology and Intelligent Systems in Anorexia Nervosa: Providing Smarter Healthcare Delivery Systems.

Ubiquitous technology, big data, more efficient electronic health records, and predictive analytics are now at the core of smart healthcare systems supported by artificial intelligence. In the present narrative review, we focus on sensing technologies for the healthcare of Anorexia Nervosa (AN). We employed a framework inspired by the Interpersonal Neurobiology Theory (IPNB), which posits that human experience is characterized by a flow of energy and information both within us (within our whole body), and between us (in the connections we have with others and with nature). In line with this framework, we focused on sensors designed to evaluate bodily processes (body sensors such as implantable sensors, epidermal sensors, and wearable and portable sensors), human social interaction (sociometric sensors), and the physical environment (indoor and outdoor ambient sensors). There is a myriad of man-made sensors as well as nature-based sensors such as plants that can be used to design and deploy intelligent systems for human monitoring and healthcare. In conclusion, sensing technologies and intelligent systems can be employed for smarter healthcare of AN and help to relieve the burden of health professionals. However, there are technical, ethical, and environmental sustainability issues that must be considered prior to implementing these systems. A joint collaboration of professionals and other members of the society involved in the healthcare of individuals with AN can help in the development of these systems. The evolution of cyberphysical systems should also be considered in these collaborations.

Mobile-assisted language learning (MALL) research trends and patterns through bibliometric analysis: Empowering language learners through ubiquitous educational technologies

Mobile devices and technologies have proliferated extensively and become an integral part of life and learning. Mobile-assisted language learning (MALL) has progressed as an emerging area of research corresponding to recent advances in mobile technologies and the proliferation of smartphones and tablet computers. Accordingly, this study examined MALL research between 2008 and 2020 through a bibliometric analysis using social network analysis (SNA) and text mining techniques. The SNA and text mining analysis suggest five broad research themes: (1) self-regulated language learning by defining one's own learning objectives, (2) providing learner agency and motivation by empowering autonomy, (3) personalizing learning through artificial intelligence (AI)-supported mobile learning (m-learning), (4) MALL for learning in the wild, and (5) MALL to support higher education. The findings show that while MALL research has been considerably operationalized around linguistic factors, nonlinguistic factors relating to learners' interactions with mobile devices or applications have been largely overlooked. It was found that MALL scholarship has recently tended to incorporate the use of mobile devices in informal learning contexts and outside the classroom due to the flexibility and anytime anywhere functionality of m-learning. The study concludes with several suggestions and highlights the areas that need more attention in MALL research.

When IT Creates Legal Vulnerability: Not Just Overutilization but Underprovisioning of Health Care Could be a Consequence

We study the potential impact of the legal vulnerability created by ubiquitous information technology (IT) and provide insights into its unintended consequences in a typical healthcare screening context. Screening policies determine the level of care provision (i.e., whether to conduct a test) based on patient risk information. If IT shares risk information with physicians in the testing stage, follow-up decisions may be more accurate. Yet, physicians may also face heightened legal risk from increased information visibility. In this context, we examine the socially optimal screening (based on risk information) and follow-up policies (based on risk and test information). Litigation is generally associated with the overutilization of health care because of physicians’ defensive medicine practices. In contrast, we find that the strategic underprovisioning of health care through screening policies could be a consequence of information sharing in the presence of litigation concerns. The underprovisioning of health care is aggravated if the precision of risk information relative to that of the medical test increases or the physician becomes more self-interested and less patient oriented. However, limits on malpractice damages can alleviate the underprovisioning of health care.

Machine learning model for snow depth estimation using a multisensory ubiquitous platform

Snow depth estimation is an important parameter that guides several hydrological applications and climate change prediction. Despite advances in remote sensing technology and enhanced satellite observations, the estimation of snow depth at local scale still requires improved accuracy and flexibility. The advances in ubiquitous and wearable technology promote new prospects in tackling this challenge. In this paper, a wearable IoT platform that exploits pressure and acoustic sensor readings to estimate and classify snow depth classes using some machine-learning models have been put forward. Significantly, the results of Random Forest classifier showed an accuracy of 94%, indicating a promising alternative in snow depth measurement compared to in situ, LiDAR, or expensive large-scale wireless sensor network, which may foster the development of further affordable ecological monitoring systems based on cheap ubiquitous sensors.

Ni máquina, ni humano ni disponible: Do College Admissions Offices Use Chatbots and Can They Speak Spanish?

Colleges continue to use technology to connect students to information, but a research gap exists regarding how colleges use a ubiquitous technology in the business world: chatbots. Moreover, no work has addressed whether chatbots address Spanish-speaking students seeking higher education in the form of automated (AI) chatbot responses in Spanish or Spanish-programmed chatbots. This study randomly sampled 331 United States institutions of higher education to learn if these institutions embed chatbots on their undergraduate admissions websites and if these chatbots have been programmed to speak Spanish. Results suggest 21% of institutions (n=71) embed chatbots into their admissions websites and only 28% of those chatbots (n= 20) were programmed to provide Spanish-language admissions information. Implications for college access and equity for English learners and L1 Spanish speakers are addressed.

We just ‘SHAREit’: Smartphones, data and music sharing in urban Papua New Guinea

AbstractThis article examines how the use of mobile phones and associated software creates and sustains regionally diverse urban communities. There is an interdependent connection between music that is highly participatory and locally relevant, and processes involved in sustaining key social relationships across a variety of groupings. Increasingly ubiquitous technologies such as mobile phones are used for musical purposes in ways that specifically put certain processes to work to sustain these social phenomena. This connects people with transnational software‐based commerce through social media, local telecommunications companies and phone manufacturers. That results in the navigation of ecologies and economies of data, hardware and software that work in local urban circumstances. In the case of data, we demonstrate how modes of exchange and reciprocity tied to social relationships exhibit similarities with informal economies of tobacco and betelnut. With social groups, the church‐based community perspective provides urban examples of communities that cross regions, and extended family networks. This ethnographic perspective shows how increasingly global technologies are used in urbanite Melanesia in ways that sustain longstanding values and practices, while also incorporating identities and associations around changing urban, national and international circumstances.

Prompto

Micro-learning [1], cognitive training, and even memory training [2] are a few examples of applications that have been made easier-to-use and more available with mobile, wearable, and ubiquitous technologies. Many of them are also presented through conversational interfaces. Current systems for learning and training focus on providing prompts via notifications to start the training sessions at times when we are available. They use timebased or activity-based reminders to prompt us to engage in the notified tasks, be it learning a new word or playing a cognition-enhancing game. A key challenge is that a well-timed prompt may not be effective if the user is not cognitively available to engage in the intervention [3]. Prompto [4] is a mobile system that opportunistically provides prompts when users are cognitively available: during moments of lowered cognitive load and emotional arousal; these are likely during calm and idle moments. At these moments, we are possibly more receptive to learning and remembering.

Assessing the impact of Visible Light Communication on our daily life usage of Ubiquitous Computing Technology

Assessing the impact of Visible Light Communication on our daily life usage of Ubiquitous Computing Technology