Remote Platform Research Articles

Development of remote collaboration platform for manufacturing environment using mixed reality

Development of remote collaboration platform for manufacturing environment using mixed reality

Education in time of pandemic crisis – case study

Purpose: The crisis caused by the Covid-19 pandemic has seriously impacted the way we work, learn and behave in everyday life. We were forced to work from home, i.e. work remotely, and learn using methods that were rarely or even not used until the pandemic. Switching from classes at the university with direct contact with the teacher to online classes had advantages, but also some disadvantages. Some universities already had some experience in conducting online classes and knew how to use them for various types of studies. Other universities took advantage of the platforms offered by international organizations, prepared new forms of education and adapted the program to their technical capabilities. New forms of education turned out to be a big challenge for both students and professors. The aim of the study was to compare the methods of distance education used both in universities with extensive experience and in universities where distance learning, at least due to applicable legal regulations, was less popular. Design/methodology/approach: The article analyzes the distance learning methods used by universities. The results of interviews conducted with students, teachers and the authors' personal experiences are described. Findings: We have discovered that students have no problems using online education techniques and highly value the opportunity to use materials prepared by lecturers and made available on remote education platforms. Moreover, they derive satisfaction from the opportunity to learn independently and search for materials on the Internet. One of the main conclusions was that the future seems to belong to a blended learning system, combining physical and online learning. Originality/value: The value is the originality based on the interviews and post COVID point of view. Keywords: pandemic crisis, online education, case study. Category of the paper: Case study, Viewpoint.

DEVELOPMENT OF DIGITAL COMPETENCE OF CITIZENS FOR LIFELONG LEARNING

Background. The conceptual foundations of the development of digital competence for lifelong learning and the analysis of its regulatory and legal regulation have been clarified; identification of educational practices that most effectively satisfy the social and educational needs of citizens for the development of digital competence in the system of informal education. The purpose of the article is to define educational practices for the development of citizens' digital competence. It was found that the development of digital competence of citizens is based on the idea of competence; a trend towards constant updating of normative documents has been established; educational practices have been determined that will meet the needs of citizens regarding the development of digital competence in the system of non-formal education. Methods. The theoretical analysis of scientific works on the problems of developing citizens' digital competence was chosen as the research method. The search for information using scientific metric databases Google Scholar, Scopus, Web of Science, by keywords was applied; government and parliamentary information platforms and portals; theoretical analysis of scientific works on the problems of developing citizens' digital competence; content analysis of regulatory and legal documents, analytical materials, instructional and informational materials and their formalization, comparison of the capabilities of remote platforms; generalization of the received data and development of proposals. Results. Based on the results of the research, it was found that in the European educational space, the idea of competence is accepted as the conceptual basis for the development of citizens' digital competence. It has been established that today it has been developed into an innovative idea of cross-cutting key competences through a combination of formal, informal and informal education. Tendencies for constant updating of the legal regulation of the development of digital competence have been revealed. Conclusions. Educational practices aimed at the greatest satisfaction of the social and educational needs of specialists in the development of digital competence in the system of non-formal education are highlighted, which are divided into traditional and innovative forms, combining a wide range of various educational and online platforms for distance and online learning, under the guidance of a teacher or independent performance of tasks.

Development of the Readout Electronics for a MAPS-Based Beam Telescope

Along with the change of the Deutsches Elektronen-Synchrotron (DESY) II test beam facility operation mode, the existing beam telescope built with the Mimosa26 chips will be unable to meet the requirements of the much-increased beam particle rate. In this article, we present the readout electronics of a new beam telescope built with ALice PIxel Detector (ALPIDE) chips which are originally designed for the upgrade of A Large Ion Collider Experiment (ALICE). The gigabit Ethernet implemented in the high-speed transceiver of Kintex field programmable gate array (FPGA) enables individual data acquisition and control of each ALPIDE chip. The data from the multidetector plane are transmitted to the remote platform via an Ethernet switch. The global trigger is generated by an AIDA2020-trigger logic unit (TLU) by the coincidence of two pairs of plastic scintillators. The results of long-term beam tests show that the new beam telescope can achieve a lower fake hit rate and a trigger rate of 220 kHz, which increases beam utilization and reduces the difficulty of track reconstruction. The biased resolution of distribution using all six planes for tracking in a 6 GeV electron beam is measured to be about 5 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> .

How moderation affects remote psychophysical tasks with children.

The increasing use of remote platforms for auditory research necessitates more in-depth evaluation of assessment protocols, especially when working with children. This work investigates the influence of the presence of a moderator on remote audiovisual speech perception studies, by assessing how moderation impacts children's understanding and performance of the psychophysical tasks as well as their attention on these tasks. In sum, moderated and unmoderated methods can reliably assess audiovisual speech perception benefits. However, regardless of similar error patterns between both studies, unmoderated online studies with children are prone to more general attention lapses as suggested by higher overall error rates.

Data Acquisition and Remote Monitoring of Geological parameters for Landslide Prediction using WSN

Aiming at the problems of a large amount of redundant information, low data accuracy and difficulty in system monitoring when wireless sensor network nodes collect data. An efficient technique of data collection and remote monitoring system based on wireless sensor network is proposed. The system uses WSN nodes to real-time collection of external environment parameters. A software design for Wireless Sensor Network formation, data fusion, data transmission and transferring data to the host computer, and use of WIFI/GSM as a means of transmission to build a remote monitoring platform. The test results show that the system can realize remote real-time monitoring of the external environment, geophysical parameters and the use of data fusion algorithms increases the transmission rate and data accuracy between nodes.

Principal Labor Markets: Distance and Time Between Transferring Schools

While a growing body of literature has emphasized conditions surrounding principal turnover, less attention has been given to how within-career sorting has shaped the principal labor market. Given the recent shift towards remote and asynchronous learning platforms, this study is the first to explore how job-to-job transfer distance may shape principal sorting. Using longitudinal administrative data covering every certified principal in Texas over 20 years, we first calculate the driving distance and time for every principal transfer event in the state and determine how transfer distance and time vary by school and principal demographics. We then utilize hierarchical linear modeling to determine which school and principal characteristics are associated with increased transfer distance and driving time. We find that (1) transfer distances increased over time and did so sharply after the Great Recession, (2) White and male principals were more likely to transfer longer distances than females or principals of color, and (3) cost of living change was more associated with distance than salary change. These results add a new dimension to our understanding of the within-career transfer market of principals, pointing to potential differences in opportunity and/or preferences by principal race and sex by both labor market and locale. This study’s findings inform our understanding of the dispersion potentials of the principal labor market, offering insight into where recruitment efforts may be effectively targeted and which incentives may be attractive for hiring.

Experimental and numerical investigation of an innovative non-combustion impulse gas turbine for micro-scale electricity generation

Fulfilling electricity demand in a remote platform has been a great challenge for oil and gas industry. With only pressurized gas line available, the choice of technology that can be implemented is limited; one of it is impulse gas turbine. At the moment, no studies investigating the performance of a compact impulse gas turbine which utilizes pressurized gas line has been reported, hindering the wide adoption of this technology. This study is therefore conducted with the main objective to investigate the performance of small scale impulse gas turbine for electricity generation by using computational fluid dynamics (CFD) approach in tandem with experimental validation. Three-dimensional computational model for the turbine is developed. Concurrently, an experimental set-up, consisting of micro impulse gas turbine, electric generator, flow loop and control system, is prepared to validate the model prediction. The effect of several key parameters, such as working fluid, rotational speed, mass flow rate and input pressure are evaluated to obtain operating envelope of the turbine. Overall, good agreement is achieved between numerical model prediction and experimental measured value. On the effect of working fluid, the results indicate that the impulse gas turbine driven by natural gas at 69 bar produce maximum power output of 1743.81 W at lower speed of 4500 RPM while maximum power of 1084.04 W can be achieved when driven by compressed air at 19 bar at rotational speed of 7000 RPM. In addition, a complete operating envelope for the turbine operating with either compressed air or natural gas has been developed. Furthermore, the effect of distance between nozzle outlet and turbine blade has been evaluated for which the optimum distance within studied range is obtained: 49.62 mm for one with compressed air and 54.62 mm for one with natural gas. The result from this study is expected to serve as a guideline in designing micro impulse gas turbine for electricity generation especially for remote offshore platform.

Development of Manipulator Digital Twin Experimental Platform Based on RCP

From the perspective of teaching and researching, we developed a manipulator digital twin experiment platform (named the remote experience platform, REP) based on a rapid control prototype (RCP). The platform consisted of a controlled target, a real-time controller, rapid prototype configuration software, and supervisory control software. The controlled target was a 6-DOF manipulator, divided into a physical entity and its digital twin. The 3D model and mathematical model of the manipulator were constructed as an experimental entity in a digital space. The whole system provided flexible and intuitive experimental scenes without the restraints of time and place. Based on RCP technology, students can design various complex control strategies using simulation tools such as Matlab/Simulink, then convert the graphical model into executable code to be performed in target hardware. The framework and development methods of the proposed system are elaborated in this paper. An example is demonstrated, including invocation of algorithms, one-click code generation and compilation, real-time verification and online parameter adjustment, and more. The feasibility and practicability of the system are verified through the PID control experiment of the manipulator.

2202. Influenza Surveillance of Families in an Observational Household Study 2019-2021

Abstract Background Families with children may be at higher risk for influenza infection. Community transmission can suffer from underreporting as testing is often not performed. We studied the epidemiology of influenza in households with school-aged children using home-based sample collection. Methods We conducted a remote household study surveilling respiratory viruses from November 2019-June 2021, in King County, Washington (WA), USA. Households with school-aged children were enrolled, mailed home specimen collection kits, and asked to self-assess for weekly acute respiratory illness (ARI) using remote survey platforms. Participants with ARI symptoms were prompted to complete serial illness surveys and self-collect/parent collect mid-turbinate nasal swabs. Samples were sent to a University of Washington study laboratory for RT-PCR influenza testing. Influenza rates were compared to WA Department of Health (DOH) reporting. Results A total of 1861 ARI events were reported among 992 adults and 869 children in 470 households; 75 influenza cases were detected (36 influenza A and 39 influenza B). The study participant median age was 32 years (0-84), 10 years (1-49) for influenza A, and 11 years (3-49) for influenza B cases. Overall 13% of households had an influenza case, of which 13 (22%) reported &amp;gt;1 case. A total of 81% of participants reported receipt of one dose of the 2019-2020 influenza vaccine, including 91% of influenza A and 90% of influenza B cases, and 84% received the 2020-2021 influenza vaccine. Like WA DOH, we observed a wave of influenza B cases followed by influenza A in 2019-2020. During influenza season 2020-2021, WA DOH reported 9 positive influenza tests and none observed in our study. Commonly, influenza case-patients reported were fever, cough, rhinorrhea, and fatigue. GI symptoms were more common in children than adults. Of the cases, 92% of influenza A and 78% of influenza B occurred in children. Figure 1.Influenza A and B cases from 2019-2021Figure 2A.Reported Symptoms of Influenza A D0-Day of reported onset, D7-7 days after reported illness onset. No participants &amp;gt;49 years were positive for influenza. D0: 30 participants responded and of respondents, 13% &amp;lt;5 years, 47% 5-12 years, 3% 13-17 years, and 37% 18-49 years. D7: 31 participants responded and of respondents 13% &amp;lt;5 years, 48% 5-11 years, 3% 12-17 years, and 36% 18-49 years. Figure 2B.Reported Symptoms of Influenza B D0-Day of reported onset, D7-7 days after reported illness onset. No participants &amp;gt;49 years were positive for influenza. D0: 28 participants responded and of respondents, 4% &amp;lt;5 years, 57% 5-12 years, 14% 13-17 years, and 25% 18-49 years. D7: 28 participants responded and of respondents, 4% &amp;lt;5 years, 57% 5-11 years, 18% 12-17 years, and 21% 18-49 years. Conclusion Influenza illness in 2019-2020 was initially influenza B, and subsequently replaced by influenza A. Most cases were in children and adolescents, despite at least one dose of influenza vaccine. Symptoms were widely distributed and similar between influenza A and B. Influenza incidence in our cohort declined to zero with the rise of SARS-CoV-2 cases and widespread mitigation efforts. Disclosures Janet A. Englund, MD, AstraZeneca: Advisor/Consultant|AstraZeneca: Grant/Research Support|GlaxoSmithKline: Grant/Research Support|Meissa Vaccines: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Grant/Research Support|Sanofi Pasteur: Advisor/Consultant Helen Y. Chu, MD, MPH, Cepheid: Reagents|Ellume: Advisor/Consultant|Gates Ventures: Grant/Research Support|Merck: Advisor/Consultant|Pfizer: Advisor/Consultant.

890 ARTIFICIAL INTELLIGENCE EMPOWERS REMOTE MONITORING OF IMPLANTABLE LOOP RECORDERS

Abstract Background The implantable loop recorder (ILR) is a subcutaneous device used to diagnose heart rhythm disorders, allowing the detection of any arrhythmic episodes which are related to the onset of patient-reported symptoms. Although the importance of implantable cardiac monitors has been widely recognized, it is also true that due to their subcutaneous nature, they are inclined to detect false-positive episodes which generate several warnings requiring additional checks from the health care personnel. For this reason implanted cardiac devices monitoring has been recently implemented by the use of artificial intelligence (AI), which applies deep learning algorithms for speeding up the telemetry follow-up checks without affecting the accuracy. Considering the increased need of remote monitoring during pandemics, such achievement should reduce the overwork superimposed on healthcare providers, but to date it is not known to what extent this technology confers a quantitative gain. Our main purpose is to demonstrate how AI can enhance remote monitoring of patients with implantable cardiac monitors, reducing false positives and improving the accuracy of information received by cardiologist. Methods we included twenty-six patients who undergoing ILR implantation between May 2019 and April 2022. Mean age was 58 ± 28 years and there was a higher prevalence of male subjects (n = 20; 76,9%). Fifteen patients received ILR implemented by the use of AI, eleven patients received ILR with standard remote monitoring system. We did follow up from April 2022 to September 2022 with dedicated remote monitoring platforms. The main events detected by ILR were atrial fibrillation (AF), pauses &amp;gt; 3 sec, supraventricular and ventricular arrhythmias, patient's symptom. Results among AI-ILR a total of 25 events were recorded and 92% (n= 23) of these were correctly identified, meanwhile 4% (n= 1) event was considered as false positive. AI implementation showed a sensitivity of 93% (95% CI 0,7018 to 0,9966) and specificity of 90% (95% CI 0,5958 to 0,9949) Among the ILR not supported by AI a total of 26 events were registered, in 76,9% (n=20) of these there was a true correspondence between the event reported and the real event, while in 19,1% (n=5) there wasn't correspondence with a sensitivity of 91% (95% CI 0,6461 to 0,9957) and specificity of 64% (95% CI 0,3876 to 0,8366). Based on these data, AI improves the accuracy of diagnosis, reducing the incidence of false positives with an important saving time for health care providers. Conclusions with our analysis we support the hypothesis that AI algorithms can augment diagnostic capabilities and provides an important contribute to clinical decision-making. The implementation of ILR monitoring with AI is still at the beginning, but continuously further investigations will determine the real added value of these algorithm. The wider adoption of AI technology in cardiovascular medicine seems eventually inevitable in the digital world of 21st century healthcare.

Telecommuting and Remote Work Revolution: Are Workers More Effective and Productive Working from Home? (A Multi-Perspective Analysis)

Working from Home (WFH) has become a profound workplace culture in developed and developing countries with a concern whether it should be continued or discontinued. Therefore, the purpose of this paper was to examine the subject of telecommuting and remote work revolution against whether workers are more effective and productive working from home? To accomplish this, a descriptive research design that is multi-perspective in nature and utilizes the content analysis approach was adopted. The paper presented a brief history of teleworking, different remote working platforms, performance of teleworkers, factors affecting performance of remote workers and concluding remarks which embodies recommendations.

Identifying Core Competencies for Remote Delivery of Psychological Interventions: A Rapid Review.

The COVID-19 pandemic led to a rapid shift toward remote delivery of psychological interventions and transition to voice-only and video communication platforms. However, agreement is lacking on key competencies that are aligned with equitable approaches for standardized training and supervision of remote psychological intervention delivery. A rapid review was conducted to identify and describe competencies that could inform best practices of remote services delivery during and after the COVID-19 pandemic. Scopus, MEDLINE, and PsycINFO were searched for literature published in English (2015-2021) on competencies for synchronous, remote psychological interventions that can be measured through observation. Of 135 articles identified, 12 met inclusion criteria. Studies targeted populations in high-income countries (11 in the United States and Canada, one in Saudi Arabia) and focused on specialist practitioners, professionals, or trainees in professional or prelicensure programs working with adult populations. Ten skill categories were identified: emergency and safety protocols for remote services, facilitating communication over remote platforms, remote consent procedures, technological literacy, practitioner-client identification for remote services, confidentiality during remote services, communication skills during remote services, engagement and interpersonal skills for remote services, establishing professional boundaries during remote services, and encouraging continuity of care during remote services. These 10 skills domains can offer a foundation for refinement of discrete, individual-level competencies that can be aligned with global initiatives promoting use of observational competency assessment during training and supervision programs for psychological interventions. More research is needed on identification of and agreement on remote competencies and on their evaluation.

Deploying Digital Health Technologies for Remote Physical Activity Monitoring of Rural Populations With Chronic Neurologic Disease

ObjectiveThe objective of this pilot study was to examine the feasibility of a remote physical activity monitoring program, quantify baseline activity levels, and examine predictors of activity among rurally residing adults with Parkinson disease (PD) or stroke. DesignThirty-day observational study. Participants completed standardized assessments, connected a wearable device, and synced daily step counts via a remote monitoring platform. SettingCommunity-based remote monitoring. ParticipantsRurally residing adults with PD or stroke enrolled in the Veterans Health Administration. InterventionN/A. Main Outcome MeasuresFeasibility was evaluated using recruitment data (response rates), study completion (completed assessments and connected the wearable device), and device adherence (days recording ≥100 steps). Daily step counts were examined descriptively. Predictors of daily steps were explored across the full sample, then by diagnosis, using linear mixed-effects regression analyses. ResultsForty participants (n=20 PD; n=20 stroke) were included in the analysis with a mean (SD) age of 72.9 (7.6) years. Participants resided 252.6 (105.6) miles from the coordinating site. Recruitment response rates were 11% (PD) and 6% (stroke). Study completion rates were 71% (PD) and 80% (stroke). Device adherence rates were 97.0% (PD) and 95.2% (stroke). Participants with PD achieved a median [interquartile range] of 2618 [3896] steps per day and participants with stroke achieved 4832 [7383] steps. Age was the only significant predictor of daily steps for the full sample (-265 steps, 95% confidence interval [-407, -123]) and by diagnosis (PD, -175 steps, [-335, -15]; stroke, -357 steps [-603, -112]). ConclusionsA remote physical activity monitoring program for rurally residing individuals with PD or stroke was feasible. This study establishes a model for a scalable physical activity program for rural, older populations with neurologic conditions from a central coordinating site.

An examination of the usability of the Mayo Test Drive remote cognitive testing platform in older adults with and without cognitive impairment

AbstractBackgroundMayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web‐based platform for self‐administered assessment for novel (Stricker Learning Span) and open access (Symbols Test) cognitive measures with previously demonstrated validity and reliability. Our study aim was to examine the usability of MTD, defined as the extent to which MTD was used to achieve the desired study goal of completing a testing session among participants willing to engage in an all‐remote study.Methods248 Mayo Clinic Study of Aging and Mayo Alzheimer’s Disease Research Center participants were invited to participate in this ancillary, uncompensated remote pilot study via email. To examine 1) willingness to participate in a remote cognitive assessment study and 2) usability of MTD, the initiation and completion rates of MTD were examined by cognitively unimpaired (CU; n = 142) and cognitively impaired (CI; n = 106) groups (see Figure 1). These rates and other factors associated with MTD feasibility were further explored across age in CU (i.e., 50–69, 70–79, and 80+ years) and specific diagnostic groups in CI (i.e., individuals with dementia, mild cognitive impairment (MCI), and possible MCI).ResultsSession completion rate (usability) was 98% across all participants who chose to participate, and, surprisingly, completion rates did not vary by age or diagnostic groups (p = .69; see Table 1). As expected, more individuals chose to participate in the CU (77%) versus CI (52%) group (p &lt; .001). In terms of feasibility, individuals over 80 and with CI were more likely to have some contact with the study coordinator. Use of smartphones decreased with age, with most CU individuals over 70 using a personal computer (69‐73%; Table 2).ConclusionsThough the CI group was less likely to choose to participate than the CU group, out of those that did choose to participate the rate of completion was 98%. This demonstrates high usability of MTD. Study coordinator support and a flexible testing platform is critical for facilitating participation in remote testing across the aging population, and more supports and incentives may be needed for individuals with cognitive impairment to improve participation rates.

An examination of the usability of the Mayo Test Drive remote cognitive testing platform in older adults with and without cognitive impairment.

Mayo Test Drive (MTD): Test Development through Rapid Iteration, Validation and Expansion, is a web-based platform for self-administered assessment for novel (Stricker Learning Span) and open access (Symbols Test) cognitive measures with previously demonstrated validity and reliability. Our study aim was to examine the usability of MTD, defined as the extent to which MTD was used to achieve the desired study goal of completing a testing session among participants willing to engage in an all-remote study. 248 Mayo Clinic Study of Aging and Mayo Alzheimer's Disease Research Center participants were invited to participate in this ancillary, uncompensated remote pilot study via email. To examine 1) willingness to participate in a remote cognitive assessment study and 2) usability of MTD, the initiation and completion rates of MTD were examined by cognitively unimpaired (CU; n = 142) and cognitively impaired (CI; n = 106) groups (see Figure 1). These rates and other factors associated with MTD feasibility were further explored across age in CU (i.e., 50-69, 70-79, and 80+ years) and specific diagnostic groups in CI (i.e., individuals with dementia, mild cognitive impairment (MCI), and possible MCI). Session completion rate (usability) was 98% across all participants who chose to participate, and, surprisingly, completion rates did not vary by age or diagnostic groups (p =.69; see Table 1). As expected, more individuals chose to participate in the CU (77%) versus CI (52%) group (p < .001). In terms of feasibility, individuals over 80 and with CI were more likely to have some contact with the study coordinator. Use of smartphones decreased with age, with most CU individuals over 70 using a personal computer (69-73%; Table 2). Though the CI group was less likely to choose to participate than the CU group, out of those that did choose to participate the rate of completion was 98%. This demonstrates high usability of MTD. Study coordinator support and a flexible testing platform is critical for facilitating participation in remote testing across the aging population, and more supports and incentives may be needed for individuals with cognitive impairment to improve participation rates.

An efficient producer mobility management technique for real-time communication in NDN-based Remote Health Monitoring systems

The remote Health Monitoring (RHM) system is a remote healthcare platform that provides real-time monitoring services and brings convenience and safety for doctors as well as patients. Named Data Network (NDN) is a future network architecture, which is a kind of Information-Centric Network. NDN’s advantages in data security and performance can make the health system more reliable and efficient. However, in the existing NDN network architecture, there exist some producer mobility issues that can impede the proceeding towards real-time and seamless communication. To solve the problem, a Neighborhood Registration Scheme (NRS) is proposed here. When the mobile producer moves from one AP to another, it has not registered into the new AP and thus cannot receive the Interest Packet (IntP) from the consumer in time, which can cause data losses. Meanwhile, the updating process in the NDN map also takes a considerable time, which can also cause delay, referred to as updating delay. This is due to some consumers having got the new location of the mobile producer while others have not. The scheme proposes in this paper is to register the mobile producer not only into the nearest Access Point (AP) but also multiple neighbor APs. In this way, the delay caused by AP switching and package loss rate can be effectively reduced, which allows mobile producers to move across the cells with low latency and Packet Loss (PL) rate. NRS is a comprehensive routing algorithm that designs the modified packet transmission strategy. Compare to the Anchor-less strategy, the proposed NRS decreases about 80% PL rate and saves 16% delay time, whereas, NRS reduces more than 90% PL rate and saves 40% delay time than Hop-count strategy in high-speed producer mobility scenarios. These improvements are necessary for RHM because low delay and PL are the most important requirements of the RHM that can strengthen the real-time monitoring for patients, information interaction between doctors and patients, and safety assurance. By setting the proper parameters, NRS can promise to have no PL and acceptable network cost.

FERN: Fair Team Formation for Mutually Beneficial Collaborative Learning

Automated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">team formation</i> is becoming increasingly important for a plethora of applications in open-source community projects, remote working platforms, as well as online educational systems. The latter case, in particular, poses significant challenges that are specific to the educational domain. Indeed, teaming students aims to accomplish far more than the successful completion of a specific task. It needs to ensure that all the members in the team benefit from the collaborative work, while also ensuring that the participants are not discriminated against with respect to their protected attributes, such as race and gender. Toward achieving these goals, this article introduces <monospace xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FERN</monospace> , a fair team formation approach that promotes mutually beneficial peer learning, dictated by protected group fairness as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">equality of opportunity</i> in collaborative learning. We formulate the problem as a multi-objective discrete optimization problem. We show this problem to be NP-hard and propose a heuristic hill-climbing algorithm. Extensive experiments on both the synthetic and real-world datasets against well-known team formation techniques show the effectiveness of the proposed method.

Remotely administered computerized cognitive test battery with older adults

AbstractBackgroundComputerized cognitive assessments are an efficient and sensitive method of identifying cognitive impairments in aging and cognitively impaired populations. The current study examines the feasibility and reliability of remote, home testing with a new tool, the California Cognitive Assessment Battery (CCAB).MethodThe CCAB runs on a remote tablet platform (Figure 1) and includes telemedical interaction with an examiner via video chat (Figure 2). Examiners administer a comprehensive set of cognitive tests, including verbal, visual, memory, and processing speed tasks, as well as psychological questionnaires (Figure 3). The tasks are scored automatically, including consensus automated speech recognition (CASR) for the transcription of responses on verbal tasks (e.g., list‐learning memory tasks, picture description, verbal fluency). For the current study, the CCAB was administered remotely to 185 healthy older military veterans (aged 60–89; 18% women) in their homes, with testing sessions under video and audio supervision and assistance. The battery was administered three times within one week to assess test‐retest reliability.ResultReaction times, word onset latency, response accuracy, error types, and speech samples were collected and analyzed. Participant experience was generally favorable: 98% of participants completed all three testing sessions, with 99% of all tests in those sessions completed successfully. Additionally, after a mid‐year software and examiner procedure reformulation of a small subset of CCAB tests, there was a 42% decrease in test failures and a 6% decrease in repeated tests. Individual test times were overall highly uniform across participants (Figure 4), with an entire CCAB battery having low daily test time variability. Also, compared to home noise levels, recorded speech levels were sufficient to support CASR transcript generation for scoring verbal tasks (Figure 5). Finally, in a subset of 50 participants, similar test battery characteristics were found when a CCAB session was repeated later under laboratory conditions.ConclusionThe CCAB shows promise as an objective, reliable automated digital assessment tool to evaluate cognitive functioning in adults both at home and in the laboratory or clinic.

Enrollment and Completion Characteristics for Novel Remote Delivery Modes of the Self-management Programs During the COVID-19 Pandemic: Exploratory Analysis.

In-person, evidence-based, peer-facilitated chronic disease self-management programs have been shown to be effective for individuals from a variety of backgrounds, including rural and minority populations and those with lower socioeconomic status. Based in social learning theory, these programs use group processes to help participants better manage their chronic disease symptoms and improve their quality of life. During the pandemic, these in-person programs were forced to rapidly transition to remote delivery platforms, and it was unclear whether doing so increased disparities within our rural population. The objectives of this analysis were to ascertain self-management program enrollment and completion characteristics between 2 remote delivery platforms, as well as determine the individual level characteristics that drove enrollment and completion across delivery modes. We analyzed enrollment and completion characteristics of 183 individuals who either enrolled in a self-management workshop delivered through a web-based videoconference (VC) system or through a traditional, audio-only conference call (CC) offered by our health care network between April and December 2020. Chi-square tests of association were used to describe the characteristics of and differences between groups. Logistic regression analysis was used to determine significant predictors of enrollment and completion. Those who enrolled in the VC platform were significantly likelier to be younger and college educated than those who enrolled in the CC platform. Those who completed a program, regardless of delivery mode, were likelier to be older and college educated than those who did not complete a program. Multivariate analyses indicated that of those enrolled in the CC platform, completers were likelier to not be enrolled in Medicaid. Among those enrolled in the VC platform, completers were older, college graduates, female, and likelier to have reported poorer health than those who did not complete the program. The transition of self-management programs to remote delivery modes, particularly to those that rely on VC platforms, revealed that certain demographic groups may no longer be able or willing to access the service. Efforts need to be made to increase engagement in remote self-management workshops. In addition, equivalent quality services that do not rely on a digital platform must continue to be offered in order to promote health equity.