Reviewerly/exHarmony huggingface dataset:
Implementation of 34.7 fps Pose and Gaze Estimator for Real-Time Driver-Vehicle Interaction System

With the recent rapid development of autonomous driving, many researches on intelligent in-vehicle interaction technologies have been studied. Real-time driver behavior analysis is a key function for various in-vehicle interaction ap-plications. An important performance indicator here is real-time quality because it is directly related to safety. Therefore, in this paper, we design the convolutional neural network (CNN) architecture suited to in-vehicle driver behavior analysis using pose and gaze. First, we define the 11 key points for driver pose and gaze, and modeled a CNN architecture that can detect them quickly. The proposed architecture was re-generated and re-trained with layer reduction for high speed based on the residual CNN model. Furthermore, the hardware implementation result based on FPGA platform to verify the real-time performance are presented. In order to implement real-time interaction, an image processing speed of more than 30 fps and a latency time of less than 100 ms are generally required. We selected and implemented the FPGA platform to meet these requirements. The designed hardware architecture was implemented at the RTL level of the VCU118 FPGA, and simulation results show 34.7 fps and 75.3 ms latency. Finally, we implemented the driver pose and gaze estimator on the FPGA based hardware platform to experiment the driver-vehicle interaction system with the demo application. The detected pose and gaze results were transmitted to the GPU board in real time, reliably supporting 30 fps, and verified application to screen control and driver monitoring applications.
Eye Tracking Auto-Correction Using Domain Information

Webcam-based eye tracking (wcET) comes with the promise to become a pervasive platform for inexpensive, easy, and quick collection of gaze data without requiring dedicated hardware. To fulfill this promise, wcET must address issues with poor and variable spatial accuracy due to, e.g., participant movement, calibration validity, and the uncertainty of the gaze prediction method used. Eye-tracking (ET) data often suffer particularly from a considerable spatial offset that reduces data quality and heavily affects both qualitative and quantitative ET data analysis. Previous works attempted to mitigate the specific source of spatial offset, e.g., by using chin rests to limit participant movement during ET experiments, by frequent re-calibration or by incorporating head position and facial features into the gaze prediction algorithm. Yet spatial offset remains an issue for wcET, particularly in daily life settings involving children. It is currently unclear (1) if spatial offset can be automatically estimated in absence of ground truth; and (2) whether the estimated offset can be used to obtain substantially higher data quality. In response to the first research question, we propose a method to estimate the spatial offset using domain information. We estimate the spatial offset by maximizing the ET data correlation with Areas of Interests (AOIs) defined over the stimulus. To address the second research question, we developed a wcET system and ran it simultaneously with a commercial remote eye tracker, the Tobii Pro X3-120. After temporal synchronization, we calculated the average distance between the gaze points of the two systems as a measure of data quality. For all tasks investigated, we obtained an overall improvement of the raw data. Specifically, we observed an improvement of 1.35 $$^{\circ }$$ , 1.02 $$^{\circ }$$ , and 0.92 $$^{\circ }$$ in three tasks with varying characteristics of AOIs. This is an important step towards pervasive use of wcET data with a large variety of practical applications.
Exploring the Anonymity of Social Media Users Using Micro-messages

The widespread use of social media and social networking sites has transformed how people communicate. As a result, micro-messages exchanged daily by people increased drastically. The micro-messages, which limit the number of characters, are a unique way of communication. Social media users communicate publicly or privately using micro-messages. Also, social media users can use pseudo-identities to stay anonymous. The identity of the user can be revealed using author identification systems with their social media posts. The length limitation of the micro-messages introduces novel problems for author identification systems. In this work, we investigate the performance of author identification systems on micro-messages with extensive experiments. Our results demonstrate the capabilities of the author identifiers under various real-world scenarios.
Habituation to Simulator Sickness in Older Adults During a Chronic Back Pain Therapy Program with Repeated Virtual Reality Exposure

VR exergames have been tested in many cases in rehabilitation. However, VR sickness can be a major limitation in their application. Little research exists on how VR sickness changes over time in VR exergames. The purpose of the study was to determine how VR sickness develops in older adults with back pain over the course of multiple exposures to a VR exergame using a head-mounted display. The study enrolled 11 chronic back pain patients over the age of 65 years (M = 75.0, SD = 5.8) who were supervised by a physical therapist in the laboratory. Over the course of four weeks, participants completed an average of 9.18 (SD = 1.47) sessions with the VR exergame, each lasting approximately 30 min. The Simulator Sickness Questionnaire (SSQ) was used pre (after one week) and post (after four weeks) the intervention. Results showed a decrease in all three subscales of the SSQ (nausea: MD = 12.14, z = −.96, p = .34; oculomotor: MD = 8.27, z = −1.20, p = .23; disorientation: MD = 18.98, z = −1.83, p = .07) and the total score (MD = 13.94, z = −1.5, p = .12). The results indicated that a VR sickness habituation is possible during a repeated exposure in rehabilitation programs and adaptation to VR sickness should be considered when using VR in older adults.
Cybersecurity Compliance in the Public Sector: Are the Best Security Practices Properly Addressed?

Improving and strengthening cybersecurity in the public sector should represent a top priority for government agencies, including municipalities and regions. To be resilient against cyberattack surges, organizations should consider establishing a cybersecurity program based on international standards and best practices. In this paper we explore the cybersecurity compliance in the Swedish public sector in relation to the best practices and guidelines highlighted in the ISO/IEC 27001A framework. Our findings indicate that the overall security status among the municipalities and regions contained many flaws, with substantial holes and critical issues. ISO/IEC 27001A creates a standardized base, but it is somewhat theoretical and starts with a policy, not providing insights on how to govern information security. Also, most of these "ISO/IEC"-related gaps were found to have been compiled into a single "Technology" domain. Though compliance with standards, best practices, and regulatory requirements can help reduce cyber risks, it does not guarantee that an organization will have strong cybersecurity. To address this issue and assess how well organizations can protect, discern, react, and recover from cyberattacks, an effective method for measuring security performance must be developed.
Collaborative Appropriation of AI in the Context of Interacting with AI

In the context of maintaining technical equipment, AI is used to detect possible problems. Human specialists check whether a real problem is addressed, and, in this case, try to solve it. Furthermore, they go on trying to translate the problem notification into an improvement of other software components into which the AI system is embedded. Thus, every AI result is not only the cause of immediate action but is also a trigger within the process of continuous appropriation of the technical infrastructure that includes AI. The whole socio-technical system is a subject of AI-related improvement as a collaborative task that requires continuous advancement of human competences and skills. This has to be supported by a type of explainable AI by which the process of understanding the reasons driving AI output is not a task for a single end-user but rather the result of combining different specialists’ viewpoints and competences.
Prioritization Matrix to Highlight Business Opportunities

Lilia Schwarcz, relates the Covid-19 pandemic event to the end of the 20th century, as the 1st World War marked the beginning of it. The 1900s was “the century of technology, with fast-growing technology development, and the pandemic event was coming to present technology’s limitation” (Schwarcz 2020 and 2020). Countries around the world adopted different strategies to minimize the impact on their health system, population, and economy. Companies started adapting business strategies, in an attempt to keep the flow of projects and contracts. These changes affected not only management, projects, and how people work together, but also design and research methods. This paper presents the prioritization matrix method adaptation to remote research scenarios, using a real case to follow through the whole research process, mixing remote unstructured interviews, and an online working board. The adaptation has much of its structure from the adaptation of card sorting for remote scenarios, leading to meaningful insights and results for thinking. The description of the whole process presented here encompasses three phases: preceding interview, matrix workshop, and analysis. Due to non-disclosure contracts with the companies involved, this paper will focus mainly on the research structure and process, without presenting sensitive data connected to specific features.
Listening Through Technology: An Interactive Sound Walk for a Suburb in Shenzhen

“Take A Step” is a sound walk that consists of a web-based user interface that the audience opens up on their phone, and with which they control the sound design that they hear on their headphones as they walk through and around the historic “Dawan Shiju” site in the Pingshan suburb of Shenzhen. The sound walk was made by four undergraduate students from the SUSTech School of Design (Shenzhen) in close collaboration with the instructor and co-instructor and was publicly presented at the UABB Biennale in Shenzhen in 2022. With this paper, the authors, who are also the project leaders, analyze specific modalities of interaction with a socio-cultural site through the designing of a digital media experience. They describe this modality as listening through technology and show how it can raise the user’s awareness of the social, cultural, and mediatic specifics of the thematized site – not only on this given site, but in any other listening situation in the everyday as users may potentially carry the gained knowledge elsewhere. This paper puts forward the notion of technological listening as a complex modality happening in between reality and fiction, and in between the actual and the virtual. Listening to an environment through technology, the authors argue, is a method that accounts for the always multidimensional social, cultural, as well as sonic characteristics of a given site.
Misrecognized Utterance Identification in Support Systems for Daily Human-to-Human Conversations

To support smooth conversation between people, we are developing a support system that provides appropriate conversation topics when the speaker cannot immediately think of a topic. The problem with this system is that speech recognition errors occur frequently. The system may not be able to provide appropriate conversation topics due to speech recognition errors. Various methods have been proposed to prevent speech recognition errors, but these methods are still insufficient for domain free daily conversation. Vocalizations become ambiguous across multiple words in human-to-human daily conversation. We believe that it is necessary to understand how acoustic features change due to ambiguous vocalizations, and how changes in acoustic features affect speech recognition results, and to develop countermeasures based on these findings. This paper discusses the speech utterances characteristics that are prone to speech recognition errors to identify speech recognition errors caused by ambiguity in daily speech. In particular, we focus on F0 and mora, and analyze how these factors differ between correctly and incorrectly recognized speech. We confirmed that the F0 extraction rate tends to be lower for misrecognized speech parts than for correctly recognized speech, and we confirmed that the mora length tends to be shorter for misrecognized speech parts. Regarding the mora, there were a small number of misrecognized utterances in which the mora was extremely long, and the standard deviation of the mor of the misrecognized utterances tended to be larger than that of the misrecognized utterances. By comparing the transcribed sentences with the recognition result sentences, we analyzed the factors contributing to the above tendency, and found that the phenomenon of vowel voicelessness was promoted in daily conversation, with the absence or shortening of vocalized segments including not only vowels but also consonant parts before and after them, and the phenomenon of voiceless nasal sounds at the end of utterances. When the above voicelessness occurred at word-word boundaries, it was found that the words before and after the boundary could be combined and misrecognized as completely different words. In the future, we would like to quantify these features and propose a misrecognized utterances identification method.
Ethical Considerations of High Performance Computing Access for Pervasive Computing

High performance computing makes many contemporary pervasive computing interactions possible such as increasingly accurate weather forecasts, market-scale financial services on demand, and big data analysis for highly personalized services. However, access to high performance computing resources is not necessarily equitable. Not everyone is uplifted by this computational power. Rather, high performance computing access can be seen as another aspect of the digital divide. We acknowledge the ways in which equitable access to high performance computing resources has improved over time while also identifying potential threats to access of these resources. We provide considerations from the perspective of two popular ethical theories (contractarianism and utilitarianism) for reasoning about how these threats may be overcome or prevented from coming to pass. These perspectives can be extended to inform policy created by high performance computing providers.
Using Machine Learning to Model Potential Users with Health Risk Concerns Regarding Microchip Implants

Understanding traits that are associated with users who are willing to accept microchip implants can help drive future microchip designs, but little is known in this space. We applied three Machine Learning classifiers, that are Decision Trees, Random Forest and XGBoost on demographic information (user characteristics) of 255 survey respondents. The aim was to recognize dominant features and characteristics that lead participants to be categorized as having “Health risk” concern regarding micro-chipping. Comparison of the classifiers in the prediction tasks demonstrated that XGBoost provides the best performance in term of accuracy, precision and recall. XGBoost also showed that “Migration status”, “Race”, “Age” and “Degree” are the most important and “Medical Condition” is the next important characteristic of potential users with “Health risk” concerns about micro-chipping. Further research is needed to classify other concerns and expectations of the survey respondents and to create a fuller understanding of the users willing to accept microchip implants.
IPlay: Towards Social Media for Community-Design Design

Online social networks are now common place in day-to-day lives. They are also increasingly used to drive social action initiatives, either led by government or communities themselves. However, such initiatives are mainly used for crowd sourcing community views or coordinating activities. In this paper we present the iPlay platform that combines social media with toy sharing concepts to empower communities to discuss and realize community resource sharing. We designed the systems to assist people in communities to share locally relevant information. It mainly includes idle toys, public facilities, public spaces, children's activities, etc. It involves mobile app, to record, store and share media, and users can transfer media by their cell-phones. This system talks about the positive significance of social media in community design. By community design and information sharing widen information access, the approach drives a shift towards large-scale engagement of community stakeholders for community Involvement.
Research About Influence of Information Presentation in UI on Scanability

Although self-ordering is convenient, people tend to feel uneasy when using it. For example, they cite issues such as “I am not sure if I can operate the system well” and “I feel rushed because there are people waiting in line behind me.” Therefore, it is necessary to alleviate this psychological burden. This study aims to address this problem with scanability (quick and easy to understand) and clarifies the high scanability of UI. In this study, we first identified the issues of self-order UI by observing users. Next, we surveyed the existing self-orders and summarized their UI elements. Finally, we created a UI sample and examined the impact of the UI design on scanability. Furthermore, we determined the scanability of the product photo size, text size, text color, and margins by measuring the selection time and number of errors. Additionally, while scanability was less likely to affect the perceived time, it was more likely to affect the perception quality.
Research on the Strategy of Digital Services in the Adoption Scene of Pet Shelters

Shelters are mainly established out of love in the name of individuals or a few people. Due to the limited time, energy, and money of the managers themselves, they cannot effectively maintain the status quo for a long time. In terms of supplies, pets, adoption, etc. The information management experience is not good; on the other hand, most adopters still hold a negative attitude towards the adoption method for reasons such as private security, channel credibility, and pet health. The intervention of digital services can effectively solve their problems in information management, resource allocation, trust building, etc., and improve pet adoption's success rate, indirectly alleviating stray pets' social problems. Therefore, based on the current development dilemma of shelters and the social background of pet adoption, this paper adopts a mixed quantitative and qualitative research method and summarizes the core pain points of pet adoption in the shelter scene at the current stage through relevant tools of service design, and puts forward a discussion on digitalization. The design strategy and principles of the service in the shelter scenario are of great significance to the digital transformation of the shelter.
Analysis on the Language Use of L2 Japanese Speakers Regarding to Their Proficiency in Group Discussion Conversations

This paper presents the analysis on the language use of non-native (L2) Japanese speakers with focus on their proficiency in group discussion conversations. Due to the demographic development the necessity to close the resulting gap with foreign employees/workers and thus, non-native speakers is increasing. This work is based on a corpus collected in an experiment which acquired multimodal sensory data in collaborative tasks with unbalanced mixed setup, composed of one none-native speaker and three native (L1) speakers. Each group was given the task to discuss two topics and find a joint decision. This work aims to find the insights how the proficiency of the speakers and the difference in being a native or non-native speakers changes the used vocabulary and decision-making process, which will later be a major issue to ensure an efficient work of such mixed groups. The analysis is based on findings of a total number of seven groups and thus seven L2 speakers. The analysis is on the activeness of the participants during the discussion, the variety of their vocabularies, and language familiarity on using modifier and oral-only expressions based on the results of POS (part of speech) analysis. The results show the characteristics which can be used in automatic assessment on proficiency level.
The Comparison of Slider and Somatosensory Interfaces in Parametric Modeling for Chair Shape Manipulation

This research parametric design programs to create a simple and effective way for products to interact with users, and through the interactions and models generated compared to traditional parametric models, documents and summarizes the models and processes, and then makes recommendations for future interactive customization systems. In experiment phase, chairs were classified into block, column and surface shapes, and based on these three categories, the Swan Chair, The Red and Blue Chair and the Panton Chair were used as reference models. Six participants (two experienced and four novice designers) were invited to modify three chairs and create a shape of their choice for each of the two models, comparing the user experience of body-controlled modelling with that of the traditional parametric programmed, and collecting suggestions and feedback through semi-structured retrospective interview after the experiments. According to the analysis of the results, the novice designers consider the somatosensory system to be new, fast and easy to use, more intuitive and easier to understand than the traditional interface, and through the somatosensory system they could quickly see if the shape was reasonable and comfortable. However, novices also felt that somatosensory was limited by the body’s inability to make too many gestures and that the accuracy of the capture could be improved. Experienced designer felt that the somatosensory system possesses the intuitive nature of body sensing and shape decision can be done quickly, but that it is inconvenient and uncontrollable when it comes to accurately controlling the arbitrary parameters of the model, and that the development of the model is limited by the limitations of the body.
The Tribrid-Meeting-Setup – Improving Hybrid Meetings Using a Telepresence Robot

Hybrid meetings are the standard solution to balance remote and on-site work. They are built around on-site participants, and online and on-demand (offline) participants are at risk of being ignored. This paper set out to determine how hybrid meetings could be more engaging and interactive. As a solution, the Tribrid-Meeting-Setup (TMS) is presented. The TMS allows online participants to have an active role during the meeting by using a Telepresence-Robot (TPR) and give an interactive perspective of the meeting to the on-demand (offline) participants by recording the meeting in a 360° video format. An iterative prototype development approach was implemented for designing the TMS. This article summarizes how to build a TMS, the results of the first test using the TMS, and further recommendations for the TMS.