Evaluating an Immersive Space-Time Cube Geovisualization for Intuitive Trajectory Data Exploration.

Eye movement recordings produce large quantities of spatiotemporal data, and are more and more frequently used as an aid to gain further insight into human thinking in usability studies in GIScience domain among others. After reviewing some common visualization methods for eye movement data, the limitations of these methods are discussed. This paper proposes an approach that enables the use of the Space-Time-Cube (STC) for representation of eye movement recordings. Via interactive functions in the STC, spatio-temporal patterns in eye movement data could be analyzed. A case study is presented according to proposed solutions for eye movement data analysis. Finally, the advantages and limitations of using the STC to visually analyze eye movement recordings are summarized and discussed.

Automated driving assistance systems (ADAS) have become increasingly prevalent in consumer vehicles, particularly at L2 level, offering various degrees of safety and comfort. However, many concerns arise regarding driver attention and engagement, as drivers may not fully understand the system limitations and their continued responsibility for vehicle control. For this reason, driver engagement is a topic of significant interest in the context of ADAS development. The European Commission is already working on future regulations regarding the integration of advanced L2 systems from a safe driving perspective, as is the NHTSA in the US. Driver engagement is included in the EuroNCAP 2030 roadmap and is also being considered as one of the criteria for the assessment of Smart Cockpit according to C-ICAP (2023). This work introduces a methodology aimed at evaluating driver engagement, which combines proving ground testing, focus groups, and dynamic driving simulator testing. Proving ground testing combines subjective metrics such as mental workload and trust, together with objective measures like Time to Collision (TTC). Results indicate differences in driver engagement between medium and advanced level 2 systems, with participants showing higher trust and lower mental workload in advanced L2 systems. Focus groups highlight generational differences in perceptions of ADAS, with younger participants demonstrating higher trust and acceptance. Also, situational awareness emerges as an important factor for a proper engagement. The upcoming driving simulator phase seeks to validate these findings in a controlled environment, integrating physiological measures and eye-tracking. Future steps include conducting cross-cultural studies to capture diverse driving habits and preferences.

Public displays that allow users to interact with them through mid-air gestures are still relatively rare, as many applications rely on touch-based interaction. This paper introduces Information Wall, a gesture-controlled public information display that provides multi-user access to contextually relevant local information using remote pointing and mid-air gestures. The application has been studied in two settings: a lab-based user study and several short-term deployments. Based on our results, we present practical guidelines for gesture-controlled public display design.

BackgroundAdolescents and young adults with spina bifida (AYA-SBs) have unique user needs, given their variable and complex symptom profile. Owing to multiple barriers to prevention and intervention treatments for secondary conditions (eg, obesity), AYA-SBs may benefit from the use of behavioral intervention technologies (BITs). However, as BITs are often designed and tested with typically developing individuals, it is unclear if existing BITs may be usable for AYA-SBs.ObjectiveThis study aimed to evaluate the usability of a high-quality, publicly available, weight management–focused mobile BIT (smartphone app) for AYA-SBs.MethodsOverall, 28 AYA-SBs attending a Young Men’s Christian Association–based summer camp completed 4 structured usability tasks using a weight management app designed for the general public called My Diet Coach (Bending Spoons). Learnability was measured by (1) time to complete task, (2) number of user errors, and (3) correct entry of data when requested by the app. Satisfaction and general usability were measured via self-reported questionnaires and qualitative feedback following interactions with the app.ResultsThe majority of the sample were able to complete the tasks, with increased completion rates and improved times on second attempts of the tasks (Ps<.05). Errors were common, and discrepancies emerged between quantitative and qualitative feedback such that self-reported measures indicated dissatisfaction but qualitative feedback was generally positive. Suggested improvements to the app included (1) tutorials, (2) simplifying the design, (3) more activity options for those who ambulate by wheelchair, and (4) notifications to prompt use.ConclusionsAYA-SBs were able to learn how to complete specific tasks independently on a weight management app, but design changes consistent with previously proposed user needs were recommended. Rather than designing entirely new BITs, it may be possible to adapt existing technologies to personalize BITs for specific populations such as AYA-SBs.

BackgroundElectrocardiogram (ECG) monitoring in daily life is essential for effective management of cardiovascular disease, a leading cause of death. Wearable ECG measurement systems in the form of clothing have been proposed to replace Holter monitors used for clinical ECG monitoring; however, they have limitations in daily use because they compress the upper body and, in doing so, cause discomfort during wear.ObjectiveThe purpose of this study was to develop a wireless wearable ECG monitoring system that includes a textile ECG electrode that can be applied to the lining of pants and can be used in the same way that existing lower clothing is worn, without compression to the upper body.MethodsA textile electrode with stretchable characteristics was fabricated by knitting a conductive yarn together with polyester-polyurethane fiber, which was then coated with silver compound; an ECG electrode was developed by placing it on an elastic band in a modified limb lead configuration. In addition, a system with analog-to-digital conversion, wireless communication, and a smartphone app was developed, allowing users to be able to check and store their own ECGs in real time. A signal processing algorithm was also developed to remove noise from the obtained signal and to calculate the heart rate. To evaluate the ECG and heart rate measurement performance of the developed module, a comparative evaluation with a commercial device was performed. ECGs were measured for 5 minutes each in standing, sitting, and lying positions; the mean absolute percentage errors of heart rates measured with both systems were then compared.ResultsThe system was developed in the form of a belt buckle with a size of 53 × 45 × 12 mm (width × height × depth) and a weight of 23 g. In a qualitative evaluation, it was confirmed that the P-QRS-T waveform was clearly observed in ECGs obtained with the wearable system. From the results of the heart rate estimation, the developed system could track changes in heart rate as calculated by a commercial ECG measuring device; in addition, the mean absolute percentage errors of heart rates were 1.80%, 2.84%, and 2.48% in the standing, sitting, and lying positions, respectively.ConclusionsThe developed system was able to effectively measure ECG and calculate heart rate simply through being worn as existing clothing without upper body pressure. It is anticipated that general usability can be secured through further evaluation under more diverse conditions.

With the introduction of Extended Validation SSL certificates in Internet Explorer 7.0, web browsers are introducing new indicators to convey status information about different types of certificates. We carried out a user study which compared a proposed new interface in the Mozilla Firefox browser with an alternative interface of our own design to investigate how users react to these new indicators. Our study included eye tracking data which provided empirical evidence with respect to which parts of the browser interface users tended to look at during the study and which areas went unnoticed. Our results show that, while the new interface features in the unmodified Firefox browser went unnoticed by all users in our study, the modified design was noticed by over half of the participants, and most users show a willingness to adopt these features once made aware of their functionality.

Usability problems in the interaction between patients and telemedicine platforms has been recognized as a deterrent in the public's acceptance and use of this alternative healthcare delivery method. Therefore, evaluating the usability of telemedicine provider websites, with a focus on potential patients' first interaction with telemedicine, is a critical research inquiry. To this end, a novel survey was developed to conduct an unmoderated remote usability test (URUT) of the Teladoc website. Teladoc is one of the largest providers of Direct-to-Consumer (DTC) telemedicine. The Teladoc Website Usability Survey (TWUS) instrument collected both objective task completion success metrics and subjective user feedback. A codebook was developed to categorize design features and user interface aspects that affected usability. The TWUS and codebook demonstrated value in identifying usability problems with the Teladoc interface and can be applied in other telemedicine or Health Information Technology (HIT) usability studies. Identifying and addressing usability issues is an important approach to increase the widespread acceptance and adoption of these healthcare delivery technologies.

Multifaceted Longitudinal Study of Surgical Resident Education, Quality of Life, and Patient Care Before and After July 2011

Abstract. Four simulations with the ECHAM/MESSy Atmospheric Chemistry (EMAC) model have been evaluated with the Earth System Model Validation Tool (ESMValTool) to identify differences in simulated ozone and selected climate parameters that resulted from (i) different setups of the EMAC model (nudged vs. free-running) and (ii) different boundary conditions (emissions, sea surface temperatures (SSTs) and sea ice concentrations (SICs)). To assess the relative performance of the simulations, quantitative performance metrics are calculated consistently for the climate parameters and ozone. This is important for the interpretation of the evaluation results since biases in climate can impact on biases in chemistry and vice versa. The observational data sets used for the evaluation include ozonesonde and aircraft data, meteorological reanalyses and satellite measurements. The results from a previous EMAC evaluation of a model simulation with nudging towards realistic meteorology in the troposphere have been compared to new simulations with different model setups and updated emission data sets in free-running time slice and nudged quasi chemistry-transport model (QCTM) mode. The latter two configurations are particularly important for chemistry-climate projections and for the quantification of individual sources (e.g., the transport sector) that lead to small chemical perturbations of the climate system, respectively. With the exception of some specific features which are detailed in this study, no large differences that could be related to the different setups (nudged vs. free-running) of the EMAC simulations were found, which offers the possibility to evaluate and improve the overall model with the help of shorter nudged simulations. The main differences between the two setups is a better representation of the tropospheric and stratospheric temperature in the nudged simulations, which also better reproduce stratospheric water vapor concentrations, due to the improved simulation of the temperature in the tropical tropopause layer. Ozone and ozone precursor concentrations, on the other hand, are very similar in the different model setups, if similar boundary conditions are used. Different boundary conditions however lead to relevant differences in the four simulations. Biases which are common to all simulations are the underestimation of the ozone hole and the overestimation of tropospheric column ozone, the latter being significantly reduced when lower lightning emissions of nitrogen oxides are used. To further investigate possible other reasons for such bias, two sensitivity simulations with an updated scavenging routine and the addition of a newly proposed HNO3-forming channel of the HO2+NO reaction were performed. The update in the scavenging routine resulted in a slightly better representation of ozone compared to the reference simulation. The introduction of the new HNO3-forming channel significantly reduces the overestimation of tropospheric ozone. Therefore, including the new reaction rate could potentially be important for a realistic simulation of tropospheric ozone, although laboratory experiments and other model studies need to confirm this hypothesis and some modifications to the rate, which has a strong dependence on water vapor, might also still be needed.

In order to quickly navigate with the known rough azimuth and location information by three FOVs positioning and orientation device,a fast recognition method for local star pattern is proposed. First,we analyse the reasons of the low efficiency when performing the stars identification using global recognition database.Next,we note that it is a preferred method to perform star identification in one FOV firstly and identify the remaining stars between different FVOs,and give the angular distance error threshold. Then,we propose a method to generate the local recognition database,which can reduce the redundancy of identification information and improve recognition efficiency. The simulaion and field experiment results show that the correct iden-tification rate using this recognition method is improved up to 99. 19%,and rocognition time is about 24. 3ms,which can satisfy the system requirements for fast and efficient navigation. It also proves the correctness of the preferred recognition order.

In this paper, we propose a hand gesture-based interface for navigating 3D virtual space using Leap Motion and machine learning. Using the interface, the user can control an avatar in a first-person perspective by making it move in 4 directions, rotate its viewpoint, grasp/release an object, and adjust moving/rotating speed. After defining 9 types of hand gesture, we used the leap motion device to capture 150 hand skeletal datasets for each type, and converted them into feature datasets, with which we developed a heuristic algorithm and a machine learning (multilayer perceptron) model for hand gesture recognition. Experimental results showed that the machine learning model was much more accurate than the heuristic algorithm. We also implemented 3 methods for 3D virtual space navigation: the use of keyboard and mouse (KB) and the use of the leap motion device with the heuristic algorithm (HA) and the machine learning model (ML). After conducting a user study in which each of 15 subjects was guided to find a target object and move it to a start position with the methods, we found from the user study that the method ML outperformed the others in task time and in most of qualitative aspects.

In 1980 we published a report in Science which showed that differential course-taking does account for the large sex differences in mathematical reasoning ability found among intellectually talented seventh graders. Pallas and Alexander (1983) have recently claimed that our original paper did make clear our intention to focus on mathematical reasoning ability rather than other features of quantitative ability. We wish to point out that the abstract (A substantial difference in mathematical reasoning ability ... in favor of boys was found), the first paragraph (three times), the methods section (the mathematical section [of the SAT-M] is particularly designed to measure mathematical reasoning ability), the main conclusion (Moreover, the greatest disparity between the boys and girls is in the upper ranges of mathematical reasoning ability), the lead paragraph of the discussion (It is notable that we observed sizable sex differences in mathematical reasoning ability in seventh grade students), and numerous places elsewhere throughout the paper explicitly employ the phrase mathematical reasoning ability. It is, therefore, understandable that we are puzzled by how our use of the term mathematical reasoning ability 13 times in prominent places in a 2,000 word article does make clear our intention to focus specifically on mathematical reasoning ability. Pallas and Alexander (1983) have also suggested that our work was only an indirect test of the differential coursework hypothesis. They state that [t]he finding that other, unspecified factors also contribute to the sex difference in quantitative performance hardly compels one to the conclusion that specialized coursework does not (p. 4). We did draw that conclusion. Our sole conclusion was that differential course-taking does account for the sex differences we observed. It could account for the differences because we showed that the boys and girls in our study had had the same amount of formal training. That is as direct as one can get.

The use of virtual reality technology has become popular in modern theme parks across the world. Attractions using virtual reality technologies offer highly immersive experiences as if people are really staying in fictional worlds that the theme parks like to create. Haptic feedback is an important piece in virtual reality, where it can increase the immersion and enjoyment, but most virtual reality attractions in theme parks do not offer enough haptic feedback. In this paper, we present HapticDaijya, which is a waist-worn robot capable of giving various haptic and tactile feedback on the torso, neck, face, arms and hands. We present the design and implementation of HapticDaijya. Then, we show a user study and analyze the results for investigating its feasibility. Also, we present preliminary evaluation results that gauged the user’s accuracy in distinguishing the locations of taps applied on the chest, as well as general usability and user acceptance.

SoundSignature is a music application that integrates a custom OpenAI Assistant to analyze users' favorite songs. The system incorporates state-of-the-art Music Information Retrieval (MIR) Python packages to combine extracted acoustic/musical features with the assistant's extensive knowledge of the artists and bands. Capitalizing on this combined knowledge, SoundSignature leverages semantic audio and principles from the emerging Internet of Sounds (IoS) ecosystem, integrating MIR with AI to provide users with personalized insights into the acoustic properties of their music, akin to a musical preference personality report. Users can then interact with the chatbot to explore deeper inquiries about the acoustic analyses performed and how they relate to their musical taste. This interactivity transforms the application, acting not only as an informative resource about familiar and/or favorite songs, but also as an educational platform that enables users to deepen their understanding of musical features, music theory, acoustic properties commonly used in signal processing, and the artists behind the music. Beyond general usability, the application also incorporates several well-established open-source musician-specific tools, such as a chord recognition algorithm (CREMA), a source separation algorithm (DEMUCS), and an audio-to-MIDI converter (basic-pitch). These features allow users without coding skills to access advanced, open-source music processing algorithms simply by interacting with the chatbot (e.g., can you give me the stems of this song?). In this paper, we highlight the application's innovative features and educational potential, and present findings from a pilot user study that evaluates its efficacy and usability.

The rise of social media has transformed consumer experience in service innovation, particularly in video-based influencer marketing. This study investigates the unintended consequences of chapter progress bars—a widely used interface feature intended to facilitate video navigation—on consumer engagement. Although designed to enhance user experience, progress bars may inadvertently heighten consumer impatience and, in turn, reduce purchase intention. Across five studies, including large-scale behavioral analysis of more than 181,500 real-time user comments and a series of controlled experiments, results show that chapter progress bars increase consumer impatience and lower purchase intention. Furthermore, impatience mediates this relationship, and the effect is moderated by efficiency goals; consumers with stronger efficiency orientations are more sensitive to segmentation cues and exhibit greater impatience and lower engagement, whereas those with lower efficiency orientations are largely unaffected. This research extends the literatures on influencer marketing, consumer impatience, and digital service design by demonstrating how interface features shape consumer psychology and purchase intention. The findings offer practical insights for creators and platform designers, emphasizing the need to balance navigation efficiency with sustained consumer purchase intention in digital content strategies. Funding: Z. Zhang was supported by the National Natural Science Foundation of China [Grant 71972043]. X. Fan was supported by the National Natural Science Foundation of China [Grant 72572040]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2024.0172 .