Remote Experiments Research Articles

Ubiq-exp: A toolkit to build and run remote and distributed mixed reality experiments

Developing mixed-reality (MR) experiments is a challenge as there is a wide variety of functionality to support. This challenge is exacerbated if the MR experiment is multi-user or if the experiment needs to be run out of the lab. We present Ubiq-Exp - a set of tools that provide a variety of functionality to facilitate distributed and remote MR experiments. We motivate our design and tools from recent practice in the field and a desire to build experiments that are easier to reproduce. Key features are the ability to support supervised and unsupervised experiments, and a variety of tools for the experimenter to facilitate operation and documentation of the experimental sessions. We illustrate the potential of the tools through three small-scale pilot experiments. Our tools and pilot experiments are released under a permissive open-source license to enable developers to appropriate and develop them further for their own needs.

Online data collection to address language sampling bias: lessons from the COVID-19 pandemic

Abstract The COVID-19 pandemic has massively limited how linguists can collect data, and out of necessity, researchers across several disciplines have moved data collection online. Here we argue that the rising popularity of remote web-based experiments also provides an opportunity for widening the context of linguistic research by facilitating data collection from understudied populations. We discuss collecting production data from adult native speakers of Tagalog using an unsupervised web-based experiment. Compared to equivalent lab experiments, data collection went quicker, and the sample was more diverse, without compromising data quality. However, there were also technical and human issues that come with this method. We discuss these challenges and provide suggestions on how to overcome them.

Switching to online: Testing the validity of supervised remote testing for online reinforcement learning experiments.

Online experiments are an alternative for researchers interested in conducting behavioral research outside the laboratory. However, an online assessment might become a challenge when long and complex experiments need to be conducted in a specific order or with supervision from a researcher. The aim of this study was to test the computational validity and the feasibility of a remote and synchronous reinforcement learning (RL) experiment conducted during the social-distancing measures imposed by the pandemic. An additional feature of this study was to describe how a behavioral experiment originally created to be conducted in-person was transformed into an online supervised remote experiment. Open-source software was used to collect data, conduct statistical analysis, and do computational modeling. Python codes were created to replicate computational models that simulate the effect of working memory (WM) load over RL performance. Our behavioral results indicated that we were able to replicate remotely and with a modified behavioral task the effects of working memory (WM) load over RL performance observed in previous studies with in-person assessments. Our computational analyses using Python code also captured the effects of WM load over RL as expected, which suggests that the algorithms and optimization methods were reliable in their ability to reproduce behavior. The behavioral and computational validation shown in this study and the detailed description of the supervised remote testing may be useful for researchers interested in conducting long and complex experiments online.Supplementary InformationThe online version contains supplementary material available at 10.3758/s13428-022-01982-6.

Mitigation strategies for participant non-attendance in VR remote collaborative experiments

COVID-19 led to the temporary closure of many HCI research facilities disrupting many ongoing user studies. While some studies could easily move online, this has proven problematic for virtual reality (VR) studies. The main challenge of remote VR study is the recruitment of participants who have access to specialized hardware such as head-mounted displays. This challenge is exacerbated in collaborative VR studies, where multiple participants need to be available and remotely connect to the study simultaneously. We identify the latter as the worst-case scenario regarding resource wastage and frustration. Across two collaborative user studies, we identified the personal connection between the experimenter and the participant as a critical factor in reducing non-attendance. We compare three recruitment strategies that we have iteratively developed based on our recent experiences. We introduce a metric to quantify the cost for each recruitment strategy, and we show that our final strategy achieves the best metric score. Our work is valuable for HCI researchers recruiting participants for collaborative VR remote studies, but it can be easily extended to every remote experiment scenario.

Mechatronic acoustic research system for generating real large-scale dynamic datasets

To support spatial audio research, we aim to take recordings from complex acoustic environments with moving sources and microphones, however we observe a lack of research tools that can accomplish this. Past approaches recorded people engaging in various tasks, which produces rich data that unfortunately lacks repeatability. We propose using robots to recreate dynamic scenes without the inherent variability of human motion. To be useful, this Mechatronic Acoustic Research System must be remotely accessible, offer concise representations of dynamic scenes, support a variety of robot and audio devices, and synchronize robot motion. In this talk, we show how we solved these challenges. Remote experimentation is facilitated by our virtual interface, which uses a simple GUI to describe robot motion and audio playback/recording. A digital twin physical simulation is used for visualization and validation of motion paths. We propose using the Robot Operating System for multi-robot coordination so that networked robots can be incorporated with little overhead. We use MARS to run experiments where a cable-driven parallel robot moves a loudspeaker along a 3D path while being recorded from distributed Matrix Voice microphone arrays. We evaluate the measured audio to show repeatability of the system, justifying its use in research.

CCi-CLOUD: A framework for community based remote cochlear implant user experiments based on the CCi-MOBILE research platform

The speech processing field has recently developed a critical need for conducting listener experiments remotely versus traditional in-person methods due to social distancing measures enforced by COVID-19 pandemic. CCi-MOBILE is our current hardware research platform created to support the Cochlear Implant research community, facilitating the development of new strategies & algorithms for improving sound quality and scientific investigation for CI users/systems. In this study, CCi-CLOUD, a virtual platform, is proposed and developed to expand the functionality of CCi-MOBILE to allow for both subject testing and scientific studies to be performed remotely. CCi-CLOUD portal is established with three support categories: (i) Remote Desktop: with direct connect support for CI user remote experimentation; (ii) Cloud Data Storage: for data sharing among researchers & subjects; (iii) Online Web App: serves as a portal which connects CI subjects with the CI research community. Three multimodal sound experiments are considered in this study as a virtual experimental framework including speech recognition, speaker identification, and sound type classification for both CI and normal hearing (NH) users. Experimental evaluation is performed for both In-Lab and Remote/Online scenarios to benchmark experimental protocols and infrastructure validity for CI/NH subjects. Results on consistency between the two modalities are also discussed.

Introducing the Fear Learning and Anxiety Response (FLARe) app and web portal for the remote delivery of fear conditioning experiments

Experimental paradigms measuring key psychological constructs can enhance our understanding of mechanisms underlying human psychological well-being and mental health. Delivering such paradigms remotely affords opportunities to reach larger, more representative samples than is typically possible with in-person research. The efficiency gained from remote delivery makes it easier to test replication of previously established effects in well-powered samples. There are several challenges to the successful development and delivery of remote experimental paradigms, including use of an appropriate delivery platform, identifying feasible outcome measures, and metrics of participant compliance. In this paper, we present FLARe (Fear Learning and Anxiety Response), open-source software in the form of a smartphone app and web portal for the creation and delivery of remote fear conditioning experiments. We describe the benefits and challenges associated with the creation of a remote delivery platform for fear conditioning, before presenting in detail the resultant software suite, and one instance of deploying this using the FLARe Research infrastructure. We provide examples of the application of FLARe to several research questions which illustrate the benefits of the remote approach to experiment delivery. The FLARe smartphone app and web portal are available for use by other researchers and have been designed to be user-friendly and intuitive. We hope that FLARe will be a useful tool for those interested in conducting well-powered fear conditioning studies to inform our understanding of the development and treatment of anxiety disorders.

Driving Course Engagement Through Multimodal Strategic Technologies

This paper describes the development of a new second-year level undergraduate Physics course at the University of Newcastle, comprising three four-week modules (encompassing Special Relativity, Nuclear and Particle Physics) for a combined roster of both Newcastle and James Cook students. A series of multimodal digital learning technology platforms were employed to see if they could maximise student engagement. Specifically, a flipped classroom system was trialled whereby students were tasked with creating their own lecture notes from online videos (created using Lightboard and PowerPoint). This approach resulted in 90% of the class actively engaging with the lecture content. Weekly online tutorial workshops consistently achieved an attendance rate of approximately 85% and included an online quiz based on embedded questions within the lecture videos. In addition, innovative STEM laboratory workshops exploited active engagement strategies including purely online worksheets to blended and remote experiments. The inclusion of a Slack-based project management hub enabled students to work seamlessly under constantly changing COVID-19 restrictions while exposing them to planning, management and Python control coding, under the visage of “embracing technology and best practice to deliver the greatest possible student experience”. A review of students’ view of the Lightboard and PowerPoint lecture content was conducted with Lightboard being the student’s outright preference.

Ideal gas law and fluid dynamics simulation: characterizing an air bubble rising from the bottom of a lake

The use of animations, simulations, and remote lab experiments has taken a new turn during the pandemic. When teaching introductory-level physics courses, the simulations and animations play an important role. Carefully designed simulations assist students visualize real-life situations and help understand complex physics concepts behind them. Some of these simulations guide students to understand the problem itself and encourage them to adjust variables and observe the changes. Not to mention, both students and instructors can benefit from these simulations in any environment, remote, or in-person. We designed a simulation to demonstrate the rise of an air bubble from a certain depth of a lake. Assuming the gas trapped inside the air bubble to be ideal, using Ideal Gas Law, we designed the simulation to show how the volume of the bubble expands as it ascends. To solve for volume as it reaches the surface, we employed knowledge from fluid dynamics. We incorporated equations to account for the pressure variations with the depth. Unlike in other simulations, here we share a link with the user, permitting them to alter the program. This gives users an opportunity to understand the coding of the simulation, if they are interested in creating similar animations in the future.

Using a smartphone camera to explore ray optics beyond the thin lens equation

Ray optics is a staple of introductory physics classes, but many students do not have the opportunity to explore optics beyond the thin lens equation. In this paper, we expand upon a successful remote experiment using a smartphone camera to explore both the successes and limitations of the thin lens equation. Application of the thin lens equation reveals a linear relationship between the object distance and the inverse image height in pixels. Using the open-source image analysis tool ImageJ to measure the image height, we can find the effective focal length of the smartphone camera lens. Our measured focal lengths agree well with the stated manufacturer values for the effective focal lengths. Further application of the thin lens equation is not successful, but a modification of the analysis leads to an explanation and experimental determination of the location of the principal planes in the smartphone camera systems. This experiment can work well at the introductory level, either in person or remote, and can be used as an introduction or motivation to explore more advanced topics in ray optics.

Feasibility of Tablet-Based Remote Data Collection Method for Measuring Hearing Aid Preference.

The purpose of this study was to determine the feasibility of a tablet-based remote data collection method for measuring preference for hearing aid signal processing features. Participants were nine individuals with bilateral mild to moderately severe sensorineural hearing loss. Stimuli were spatialized low-context sentences mixed with six-talker babble at two realistic signal-to-noise ratios (3 and 8 dB) and processed through a hearing aid simulator. Preference for full factorial combinations of three common hearing aid processing features (two levels each) was elicited using a paired-comparison task. Participants completed two versions of the experiment: The lab version was completed in a sound-treated booth using a custom MATLAB application on a desktop computer; the remote version was completed in a quiet room in the participant's home, using a custom MATLAB executable application on a tablet. Both versions used the same calibrated headphones. Strict infection control protocols were followed. McNemar's test showed no association between preference and data collection method for the majority of the conditions. Percentage agreement and kappa scores were moderate/fair across most conditions. The results indicated that the remote versus lab versions did not have a systematic effect on preference. However, the relatively low agreement and kappa scores suggested within-subject variability in the outcome (preference). The tablet-based version of remote experimentation was comparable to the lab-based version for eliciting preference for hearing aid signal processing features.

Remote experiments and automation for biological SAXS at SSRL BL4-2

Remote experiments and automation for biological SAXS at SSRL BL4-2

Remote experiments at SRS beamlines at Advanced Photon Source

Remote experiments at SRS beamlines at Advanced Photon Source

Fractional Differential Equations in the Standard Construction Model of the Educational Application of the Internet of Things

Abstract This article proposes a software fusion processing method for multi-sensor monitoring the Internet of Things based on the fractional differential filtering algorithm. The purpose is to solve the difference between the detection data caused by the difference in each production information sampling node’s equipment performance and working environment. The article applies the above algorithm to the remote detection data fusion processing experiment of the discrete manufacturing system of the Internet of Things. The research found that the algorithm realizes the remote high-precision measurement of the Internet of Things sensor information. The fractional integral operator has high fusion accuracy in remote detection data fusion processing.

Distance learning: an interdisciplinary experiment on Rayleigh scattering

Abstract As a result of social distancing measures in response to the Covid-Sars 2 pandemic, our school sent chemistry kits to the students’ homes for remote experimentation. This allowed the performance of ∼25 experiments per person in each of the Fall 2020 and Spring 2021 semesters in an elective chemistry course. Students were requested to design some experiments of their own and then have the entire group reproduce them. One such experiment consisted of the anodic indirect electrogeneration of colloidal sulfur by solution acidification to produce thiosulfate disproportionation. This was evidenced by the well-known Rayleigh scattering phenomenon. Here, the trajectory and polarization state of light are modified by its interaction with a medium containing particles of smaller diameter than the wavelengths of incident light. If white light interacts with this medium, the smaller wavelengths (e.g., blue, violet) are radially scattered while the longer wavelengths (e.g., orange, red) pass through the suspension. Such scattering is responsible for beautiful sunsets and blue skies and is produced here by an indirect electrochemical process that generates colloidal sulfur. Students evidence the scattering of light shone from simple cell phone flashlights. The entire procedure is performed in a 2-h class session. Key student outcomes are presented.

Driven by notifications - exploring the effects of badge notifications on user experience.

Notification badges are an unexplored category of visual feedback to which we are continuously exposed. This study aims to deepen knowledge on the topic by measuring the behavioral effects of notification badges on a large sample of smartphone users. More precisely, the goal of the study is to observe if the presence of notification badges increases the frequency of clicks on apps. More than 1000 participants were involved in a remote between-subjects experiment, allocated into fifteen equinumerous groups of comparison. Each participant was presented with a smartphone screen displaying fifteen app icons and just one badge notification. Participants were asked to perform a remote user test called First Impression Click Test: a methodology that indicates where they would click first to accomplish a given task (i.e., Where would you click first on this screen?). Our results show a large increase in the number of clicks on apps with notification badges compared to those without notification badges and suggest the important ability of these small affordances to attract attention and stimulate action. Based on the evidence provided, our findings have practical implications for user experience design.

Remote iVR for Nutrition Education: From Design to Evaluation

While different crowdsourcing platforms promote remote data collection, experiments in the immersive Virtual Reality (iVR) research community are predominantly performed in person. The COVID-19 pandemic, however, has forced researchers in different disciplines, including iVR, to seriously consider remote studies. In this paper, we present a remote study using the Immersive Virtual Alimentation and Nutrition (IVAN) application, designed to educate users about food-energy density and portion size control. We report on the results of a remote experiment with 45 users using the IVAN app. In IVAN, users actively construct knowledge about energy density by manipulating virtual food items, and explore the concept of portion size control through hypothesis testing and assembling virtual meals in iVR. To explore the feasibility of conducting remote iVR studies using an interactive health-related application for nutrition education, two conditions were devised (interactive vs. passive). The results demonstrate the feasibility of conducting remote iVR studies using health-related applications. Furthermore, the results also indicate that regardless of level of interactivity learners significantly improved their knowledge about portion size control after using the IVAN (p < 0.0001). Adding interactivity, however, suggests that the perceived learning experience of users could be partially affected. Learners reported significantly higher scores for immediacy of control in the interactive condition compared to those in the passive condition (p < 0.05). This study demonstrates the feasibility of conducting an unsupervised remote iVR experiment using a complex and interactive health-related iVR app.

Effects of Meal Similarity on Interpersonal Synchronization in Three-Party Remote Dining

In recent years, online commensality, such as remote dining, has become a way to connect people in different places. In remote dining, people have drinks, snacks, or meals while chatting with each other via video calls and seek connectedness and belonging. However, many people feel that there is a gap between real-life and digital co-eating and that interaction in current remote dining fails to satisfy the need for companionship. Unlike real-life co-eating, in remote dining, one's meal may not be similar to that of a partner's because people usually prepare their own food separately. In this study, we focused on the effects of meal similarity on interpersonal synchronization and subjective feelings. We conducted a laboratory-based remote dining experiment and video analysis to investigate whether eating similar meals in remote conditions has any effect on eating behavior and to explore the relationship between meal similarity, interpersonal synchronization, and subjective feelings. The results showed that participants ate at a faster pace and conducted eating actions more frequently. They were more synchronized with their partners, and the feeling of togetherness was stronger. Thus, we suggest that preparing similar meals or ordering the same dishes can enhance the remote dining experience.

Summary of the 13th IAEA technical meeting on plasma control systems, data management and remote experiments in fusion research

This report summarizes the contributions presented at the IAEA technical meeting on 13th IAEA technical meeting on plasma control systems, data management and remote experiments in fusion research, hosted by UKAEA and held virtually, on 5–8 July 2021. The meeting brought together 90 experts from nuclear fusion research sites worldwide. The main topics of the meeting were plasma control; machine control, monitoring, safety and remote manipulation; data acquisition and signal processing; database techniques for information storage and retrieval; advanced computing and massive data analysis; remote participation and virtual laboratory; and fast network technology and its application.

Course Teaching Design and Practice Analysis by Intelligent Electronic Technology under Big Data

The exploration expects to improve the teaching quality of the electronic technology distance course. The teaching management system of the electronic technology network course is constructed based on a flipped classroom. Firstly, the idea of the flipped classroom is analyzed, and the electronic technology course is designed. Secondly, the teaching management system of the electronic technology network course is established, and the remote experiment module is discussed. Finally, the questionnaire survey is made to investigate the use effect of the system. The results show that about 79% of the students are satisfied with the system. About 80% think it allows them to focus on the teaching process. Only 1.3% think that this system does not work for their learning. This shows that the system can help students improve their learning efficiency. However, the main defect is the lack of a real-time feedback module for users on the application effect of the system. In a word, the exploration provides a reference for developing and designing the follow-up network course teaching system.