Showing papers on "Viewpoints published in 2021"
TL;DR: This work introduces a novel pairwise loss function that enables ReID models to learn the fine-grained features by adaptively enforcing an exponential penalization on the images of small differences and a bounded penalization of large differences.
Abstract: Person Re-IDentification (ReID) aims at re-identifying persons from different viewpoints across multiple cameras. Capturing the fine-grained appearance differences is often the key to accurate person ReID, because many identities can be differentiated only when looking into these fine-grained differences. However, most state-of-the-art person ReID approaches, typically driven by a triplet loss, fail to effectively learn the fine-grained features as they are focused more on differentiating large appearance differences. To address this issue, we introduce a novel pairwise loss function that enables ReID models to learn the fine-grained features by adaptively enforcing an exponential penalization on the images of small differences and a bounded penalization on the images of large differences. The proposed loss is generic and can be used as a plugin to replace the triplet loss to significantly enhance different types of state-of-the-art approaches. Experimental results on four benchmark datasets show that the proposed loss substantially outperforms a number of popular loss functions by large margins; and it also enables significantly improved data efficiency.
116 citations
06 May 2021
TL;DR: A framework for eliciting stakeholders’ subjective fairness notions is proposed by combining a user interface that allows stakeholders to examine the data and the algorithm’s predictions with an interview protocol to probe stakeholders�’ thoughts while they are interacting with the interface.
Abstract: Recent work in fair machine learning has proposed dozens of technical definitions of algorithmic fairness and methods for enforcing these definitions. However, we still lack an understanding of how to develop machine learning systems with fairness criteria that reflect relevant stakeholders’ nuanced viewpoints in real-world contexts. To address this gap, we propose a framework for eliciting stakeholders’ subjective fairness notions. Combining a user interface that allows stakeholders to examine the data and the algorithm’s predictions with an interview protocol to probe stakeholders’ thoughts while they are interacting with the interface, we can identify stakeholders’ fairness beliefs and principles. We conduct a user study to evaluate our framework in the setting of a child maltreatment predictive system. Our evaluations show that the framework allows stakeholders to comprehensively convey their fairness viewpoints. We also discuss how our results can inform the design of predictive systems.
34 citations
01 Nov 2021
TL;DR: In this article, a survey was conducted among international mechanical engineering students specializing in manufacturing technology at the TU Dortmund University in Germany to investigate the impact of the sudden shift to online education triggered by the COVID-19 pandemic, and the results showed that both parties initially struggled with the transition, but later adapted quickly to the new style of online teaching that was inspired by the conventional flipped classroom concept.
Abstract: To investigate the impact of the sudden shift to online education triggered by the COVID-19 pandemic, a survey was conducted among international mechanical engineering students, specializing in manufacturing technology, at the TU Dortmund University. The surveyed students, were exposed to differently structured online courses from different institutes, as well as dynamic developments in each online course, over the semester and thus were able to effectively assess the pros and cons of the different teaching styles. To get the viewpoints of both the involved parties on how a successful online education course needs to be structured, a similar survey was also conducted among manufacturing engineering professors involved in Germany. The survey, a combination of Likert-scale and free-text questions, tackled the aspects of motivation to teach and learn, ensuring effective teaching and learning, and proper assessment of the learning outcomes in an online education system. The results show that both parties initially struggled with the transition, but later adapted quickly to the new style of online teaching that was inspired by the conventional flipped classroom concept. Certain structures and approaches to online teaching, such as pre-recorded lectures; interactive QA quizzes for self-assessment, are preferred by students and teachers alike. Aspects where the viewpoints differed could be explained by the difference in age and the experience in using digital equipment. A challenge specific to online engineering education is on offering laboratory experiences to students. Possible solutions such as virtual labs, remote labs and digital-live labs that aid in overcoming this challenge are presented. Finally, based on the survey results and the author experiences on digital laboratories, best practice guidelines are presented that will help the readers in the design and deployment of online engineering courses.
28 citations
TL;DR: In this article, the state-of-the-art technologies of bio-inspired smart electronic skin (E-skin) developed in a "learning-mimicking-creating" (LMC) cycle are reviewed.
27 citations
TL;DR: A novel deep architecture termed Hierarchical Mining Network (HMN), which mines as many pedestrians’ characteristics by referring to the temporal and intra-class knowledge, is presented, which is capable of evaluating each activation of features through temporal analysis.
Abstract: Video-based person re-identification (Re-ID) aims at retrieving the person through the video sequences across non-overlapping cameras. Some characteristics of pedestrians are not consecutive across frames due to the variations of viewpoints, postures, and occlusions over time. However, existing methods ignore such data peculiarity and the networks tend to only learn those salient consecutive characteristics among frames in video sequences. As a result, the learned representations fail to cover all the characteristics of pedestrians, thus lacking integrity and discrimination. To tackle this problem, we present a novel deep architecture termed Hierarchical Mining Network (HMN), which mines as many pedestrians’ characteristics by referring to the temporal and intra-class knowledge. It consists of a novel Attentive Temporal Module (ATM) and a Dynamic Supervising Branch (DSB), with a Balancing Triplet Loss (BTL) assisting the training. The proposed ATM, with pedestrian perceiving capacity, is capable of evaluating each activation of features through temporal analysis, so that the temporally scattered characteristics of pedestrians can be better aggregated and the contaminated ones can be eliminated. Then, the DSB along with the BTL further enhances the integrity of representations by multiple supervision. Specifically, the DSB perceives the diversities of intra-class samples in each mini-batch and generates targeted supervising signals for them, in which process the BTL guarantees the signals with smaller intra-class variations and larger inter-class variations. Comprehensive experiments on two video-based datasets, i.e., MARS, and DukeMTMC-VideoReID, demonstrate the contribution of each component and the superiority of the proposed HMN over the state-of-the-arts. Benchmarking our model on three popular image-based datasets, i.e., Market1501, DukeMTMC-Reid, and MSMT17 additionally verifies the promising generalizability of the proposed DSB and BTL.
25 citations
TL;DR: A review of existing 3D datasets and 3D semantic segmentation methods and efforts to solve data hungry problems are summarized for both 3D LiDAR-focused methods and general-purpose methods.
Abstract: 3D semantic segmentation is a fundamental task for robotic and autonomous driving applications. Recent works have been focused on using deep learning techniques, whereas developing fine-annotated 3D LiDAR datasets is extremely labor intensive and requires professional skills. The performance limitation caused by insufficient datasets is called data hunger problem. This research provides a comprehensive survey on the question: are we hungry for 3D LiDAR data for semantic segmentation? The studies are conducted at three levels. First, a broad review to the main 3D LiDAR datasets is conducted, followed by a statistical analysis on three representative datasets to gain an in-depth view on the datasets' size, diversity and quality, which are the critical factors in learning deep models. Second, an organized survey of 3D semantic segmentation methods is given with a focus on the mainstream of the latest research trend using deep learning techniques, followed by a systematic survey to the existing efforts to solve the data hunger problem. Finally, an insightful discussion of the remaining problems on both methodological and datasets' viewpoints, and the open questions on dataset bias, domain and semantic gap are given, leading to potential topics in future works. To the best of our knowledge, this is the first work to study the data hunger problem for 3D semantic segmentation using deep learning techniques, which are addressed in both methodological and dataset review, and we share findings and discussions through a comprehensive dataset analysis.
23 citations
TL;DR: This article examined faculty's views about the move from face-to-face (F2F) instruction to online due to the COVID-19 pandemic and found that faculty felt frustrated with their ability to best support their students within the online format.
Abstract: The purpose of this study is to examine faculty's views about the move from face-to-face (F2F) instruction to online due to the COVID-19 pandemic. The researcher used Q methodology [Q], a mixed method, to determine and describe faculty views about this situation. The participants sorted 36 statements to reveal and describe their subjective viewpoints. In Q, similar sorts are grouped together mathematically into factors, each representing a unique viewpoint. The Q-sorting process is reflective and self-referent. The operation of sorting items allows participants to provide their internal viewpoint. This is different from responding to a Likert-type survey. Additionally, the analyses allow for differentiation of views rather than an aggregate of views. Each unique viewpoint is described by a representative sort, distinguishing statements, and participants' post-sort responses. Three views emerged: Techies who like to teach (the view most positive in relation to teaching online); Overwhelmed as human beings (populated by caregivers); and It's about what cannot be done online (those who are focused on the limitations of technology and abilities for online instruction). Generally, faculty felt frustrated with their ability to best support their students within the online format. Administrators should consider the results of this study to better understand the instructional and mental-health needs of faculty especially in an emergency situation, such as COVID-19. The findings indicate that creating the best learning situations for students is not one-size-fits-all and that there are discipline and pedagogical issues to consider when moving F2F courses online that are not fixed simply with technology.
21 citations
06 May 2021
TL;DR: This paper presents Timelines, a design activity to assist values advocates: people who help others recognize values and ethical concerns as relevant to technical practice and reflects on how decisions on the activity’s design and facilitation enables it to assist in values advocacy practices.
Abstract: This paper presents Timelines, a design activity to assist values advocates: people who help others recognize values and ethical concerns as relevant to technical practice Rather than integrate seamlessly into existing design processes, Timelines aims to create a space for critical reflection and contestation among expert participants (such as technology researchers, practitioners, or students) and a values advocate facilitator to surface the importance and relevance of values and ethical concerns The activity’s design is motivated by theoretical perspectives from design fiction, scenario planning, and value sensitive design The activity helps participants surface discussion of broad societal-level changes related to a technology by creating stories from news headlines, and recognize a diversity of experiences situated in the everyday by creating social media posts from different viewpoints We reflect on how decisions on the activity’s design and facilitation enables it to assist in values advocacy practices
18 citations
17 citations
Posted Content•
TL;DR: GKNet outperforms reference baselines in static and dynamic grasping experiments while showing robustness to varied camera viewpoints and moderate clutter, and confirms the hypothesis that grasp keypoints are an effective output representation for deep grasp networks that provide robusts to expected nuisance factors.
Abstract: Contemporary grasp detection approaches employ deep learning to achieve robustness to sensor and object model uncertainty. The two dominant approaches design either grasp-quality scoring or anchor-based grasp recognition networks. This paper presents a different approach to grasp detection by treating it as keypoint detection. The deep network detects each grasp candidate as a pair of keypoints, convertible to the grasp representation g = {x, y, w, {\theta}}^T, rather than a triplet or quartet of corner points. Decreasing the detection difficulty by grouping keypoints into pairs boosts performance. To further promote dependencies between keypoints, the general non-local module is incorporated into the proposed learning framework. A final filtering strategy based on discrete and continuous orientation prediction removes false correspondences and further improves grasp detection performance. GKNet, the approach presented here, achieves the best balance of accuracy and speed on the Cornell and the abridged Jacquard dataset (96.9% and 98.39% at 41.67 and 23.26 fps). Follow-up experiments on a manipulator evaluate GKNet using 4 types of grasping experiments reflecting different nuisance sources: static grasping, dynamic grasping, grasping at varied camera angles, and bin picking. GKNet outperforms reference baselines in static and dynamic grasping experiments while showing robustness to varied camera viewpoints and bin picking experiments. The results confirm the hypothesis that grasp keypoints are an effective output representation for deep grasp networks that provide robustness to expected nuisance factors.
14 citations
TL;DR: In this article, the authors proposed two models based on Gated Recurrent Units (GRU) neural networks for aspect-based sentiment analysis (ABSA) and interactive attention network based on bidirectional GRU to identify sentiment polarity toward extracted aspects.
TL;DR: In this article, rational planning practices are believed to improve strategy implementation monitoring on the condition that viewpoints accrued from strategic plans and performance information are shared (i.e. strategies are shared).
Abstract: Rational planning practices are believed to improve strategy implementation monitoring on the condition that viewpoints accrued from strategic plans and performance information are shared (i.e. str...
Posted Content•
TL;DR: In this article, a normalizing flow model is used to regularize the geometry and appearance of patches rendered from unobserved viewpoints, and annealing the ray sampling space during training.
Abstract: Neural Radiance Fields (NeRF) have emerged as a powerful representation for the task of novel view synthesis due to their simplicity and state-of-the-art performance. Though NeRF can produce photorealistic renderings of unseen viewpoints when many input views are available, its performance drops significantly when this number is reduced. We observe that the majority of artifacts in sparse input scenarios are caused by errors in the estimated scene geometry, and by divergent behavior at the start of training. We address this by regularizing the geometry and appearance of patches rendered from unobserved viewpoints, and annealing the ray sampling space during training. We additionally use a normalizing flow model to regularize the color of unobserved viewpoints. Our model outperforms not only other methods that optimize over a single scene, but in many cases also conditional models that are extensively pre-trained on large multi-view datasets.
05 Oct 2021
TL;DR: The practice of eating insects, known as entomophagy, is part of a regular diet for millions of people in Asia, Latin America and Africa as discussed by the authors. But the use of insects as food is relatively new in We...
Abstract: The practice of eating insects, known as entomophagy, is part of a regular diet for millions of people in Asia, Latin America and Africa. However, the use of insects as food is relatively new in We...
01 Aug 2021
TL;DR: This paper explores the subject of social engineering from an interdisciplinary perspective and proposes a proposed framework that provides researchers with a flexible model to use in their studies with an emphasis on a philosophical or practical ethics perspective.
Abstract: Social engineering is the act of using manipulation and deception to obtain access to confidential information. It is considered one of the leading threats to information security today. The topic is complex and increasing in prevalence among individuals and businesses. This paper explores the subject of social engineering from an interdisciplinary perspective. A literature review from the information technology, psychology, and business disciplines explains the interconnected nature of the topic as well as the necessity to comprehend it from multiple viewpoints. An ethical perspective follows the literature review and analyzes social engineering research from a philosophical and professional viewpoint. A proposed framework provides researchers with a flexible model to use in their studies with an emphasis on a philosophical or practical ethics perspective.
Posted Content•
TL;DR: This article proposed a cross-lingual stance detection model based on pattern-exploiting training with a novel label encoder to simplify the verbalization procedure and further proposed sentiment-based generation of stance data for pre-training.
Abstract: The goal of stance detection is to determine the viewpoint expressed in a piece of text towards a target. These viewpoints or contexts are often expressed in many different languages depending on the user and the platform, which can be a local news outlet, a social media platform, a news forum, etc. Most research in stance detection, however, has been limited to working with a single language and on a few limited targets, with little work on cross-lingual stance detection. Moreover, non-English sources of labelled data are often scarce and present additional challenges. Recently, large multilingual language models have substantially improved the performance on many non-English tasks, especially such with limited numbers of examples. This highlights the importance of model pre-training and its ability to learn from few examples. In this paper, we present the most comprehensive study of cross-lingual stance detection to date: we experiment with 15 diverse datasets in 12 languages from 6 language families, and with 6 low-resource evaluation settings each. For our experiments, we build on pattern-exploiting training, proposing the addition of a novel label encoder to simplify the verbalisation procedure. We further propose sentiment-based generation of stance data for pre-training, which shows sizeable improvement of more than 6% F1 absolute in low-shot settings compared to several strong baselines.
TL;DR: It is shown that multi-view modeling outperforms diagram-oriented modeling by means of usability and efficiency of modeling, and quality of models, and the developed modeling tool is openly available, allowing its adoption and use in R-BPM practice.
Abstract: Risk-aware Business Process Management (R-BPM) has been addressed in research since more than a decade. However, the integration of the two independent research streams is still ongoing with a lack of research focusing on the conceptual modeling perspective. Such an integration results in an increased meta-model complexity and a higher entry barrier for modelers in creating conceptual models and for addressees of the models in comprehending them. Multi-view modeling can reduce this complexity by providing multiple interdependent viewpoints that, all together, represent a complex system. Each viewpoint only covers those concepts that are necessary to separate the different concerns of stakeholders. However, adopting multi-view modeling discloses a number of challenges particularly related to managing consistency which is threatened by semantic and syntactic overlaps between the viewpoints. Moreover, usability and efficiency of multi-view modeling have never been systematically evaluated. This paper reports on the conceptualization, implementation, and empirical evaluation of e-BPRIM, a multi-view modeling extension of the Business Process-Risk Management-Integrated Method (BPRIM). The findings of our research contribute to theory by showing, that multi-view modeling outperforms diagram-oriented modeling by means of usability and efficiency of modeling, and quality of models. Moreover, the developed modeling tool is openly available, allowing its adoption and use in R-BPM practice. Eventually, the detailed presentation of the conceptualization serves as a blueprint for other researchers aiming to harness multi-view modeling.
TL;DR: In this article, the authors proposed an innovative, pragmatic approach to CCC training through tailored subspecialty training in advanced heart failure and transplant cardiology (AHFTC), using elective time to enrich AHFTC training with skills and experiences necessary to become a highly skilled critical care cardiologist.
Posted Content•
TL;DR: Wang et al. as discussed by the authors reported a study of the critical challenges and benefits of incorporating accessibility into software development and design, and established a set of guidelines to help practitioners be aware of accessibility challenges and benefit factors.
Abstract: Being able to access software in daily life is vital for everyone, and thus accessibility is a fundamental challenge for software development. However, given the number of accessibility issues reported by many users, e.g., in app reviews, it is not clear if accessibility is widely integrated into current software projects and how software projects address accessibility issues. In this paper, we report a study of the critical challenges and benefits of incorporating accessibility into software development and design. We applied a mixed qualitative and quantitative approach for gathering data from 15 interviews and 365 survey respondents from 26 countries across five continents to understand how practitioners perceive accessibility development and design in practice. We got 44 statements grouped into eight topics on accessibility from practitioners' viewpoints and different software development stages. Our statistical analysis reveals substantial gaps between groups, e.g., practitioners have Direct v.s. Indirect accessibility relevant work experience when they reviewed the summarized statements. These gaps might hinder the quality of accessibility development and design, and we use our findings to establish a set of guidelines to help practitioners be aware of accessibility challenges and benefit factors. We also propose some remedies to resolve the gaps and to highlight key future research directions.
TL;DR: In this article, the authors argue that intersectional theories of risk with poststructuralist theories of emotion can be used to argue for city safety and fear by combining insights from intersectional theory of risk and emotion.
Abstract: The aim of this article is to engage theoretically with city safety and fear by combining insights from intersectional theories of risk with poststructuralist theories of emotion. We argue that the...
TL;DR: In this article, a democratic perspective, a diversity of opinions and viewpoints on the media facilitates the public sphere, playing a key role as a social institution dedicated to informed citizenship, from a democratic point of view.
Abstract: Journalism facilitates the public sphere, playing a key role as a social institution dedicated to informed citizenship. From a democratic perspective, a diversity of opinions and viewpoints on the ...
TL;DR: By understanding facets of professional identity, the development of future educational interventions and departmental initiatives, which might support key components of professional identities, can be explored and an enhanced understanding of speciality work culture is gained.
Abstract: Professional identities research in medical education has made significant contributions to the field. However, what comprises professional identities is rarely interrogated. This research tackles this relatively understudied component of professional identities research by understanding emergency medicine physicians’ perspectives on the important elements that comprise their professional identities. Q-methodology was used to identify different clusters of viewpoints on professional identities; by extension, the core components that comprise emergency medicine physicians’ professional identities are disclosed. Thirty-three emergency medicine physicians were recruited, through purposive sampling, from five hospitals across Taiwan. R software was used to analyse the Q-sorts, determine loadings on each viewpoint and formulate the viewpoint array. Analysis of interview data enhanced our understanding of these viewpoints. In total, twenty-five emergency medicine physicians loaded onto four distinct viewpoints, reflecting dominant perspectives of emergency medicine physicians’ understanding of their professional identities. These distinct viewpoints demonstrated what emergency medicine physicians deemed significant in how they understood themselves. The viewpoints comprised: skills acquisition, capabilities and practical wisdom; coping ability and resilience; professional recognition and self-esteem; and wellbeing and quality of life. All viewpoints stressed the importance of trust between colleagues. These findings demonstrate the multitude of ways in which seemingly unified professional identities diverge across groups of individuals. An enhanced understanding of speciality work culture is gained. By understanding facets of professional identities, the development of future educational interventions and departmental initiatives, which might support key components of professional identities, can be explored.
TL;DR: In this article, the authors elaborate multiple dimensions of ethical perception in professionalism and introduce novel didactic viewpoints on educational routes through which professionals learn and develop ethical perceptions in a professional setting.
Abstract: This article aims to elaborate multiple dimensions of ethical perception in professionalism and introduces novel didactic viewpoints on educational routes through which professionals learn and deve...
TL;DR: An impression of the breadth of the IBD-research landscape in the UK is presented, in light of the top 10 research priorities published in 2016, where optimal treatment strategy has been the most studied research priority by academic and industry-sponsored trials.
Abstract: Background Since publication of the top 10 research priorities in inflammatory bowel disease (IBD) based on the James Lind Alliance Priority Setting Partnership, the question remains whether this has influenced the IBD-research landscape. This study aimed to create an overview of the current distribution of research interests of trials in the UK. Methods The ClinicalTrials.gov database and European Union Clinical Trials Register were screened for clinical trials set up from 9 August 2016 to 16 November 2019 in the UK involving adult patients with IBD. Results Of 20 non-industry-sponsored studies, a quarter investigated treatment strategies considering efficacy, safety and cost-effectiveness (priority 1). Four evaluated the role of diet (priorities 3 and 7). Development/assessment of biomarkers for patient stratification (priority 2) and fatigue (priority 8) were subject of three studies. IBD-related pain and control of diarrhoea/incontinence were each subject of 2 studies (priorities 4 and 6). The effect of gut microbiota (priority 10) and optimal strategy for perianal Crohn’s disease (priority 5) was the focus of 2 studies each. One study evaluated surgery for terminal ileal Crohn’s disease (priority 9). Of 63 industry-sponsored studies, 59 focused on priority 1. Conclusions This study presents an impression of the breadth of the IBD-research landscape in the UK, in light of the top 10 research priorities published in 2016. Optimal treatment strategy has been the most studied research priority by academic and industry-sponsored trials. Fewer studies focused on patient-reported outcomes. It remains debatable to what extent the current research landscape adequately represents all stakeholders’ viewpoints on needs for expanded knowledge in IBD, particularly the patients’ perspective.
TL;DR: In the realm of local government, private sector practices that once seemed taboo such as branding are increasingly employed within public administration as mentioned in this paper, where surveys and interviews were used to evaluate the effectiveness of these practices.
Abstract: In the realm of local government, private sector practices that once seemed taboo such as branding are increasingly employed within public administration. This study utilizes surveys and interviews...
29 Mar 2021
TL;DR: Four unique viewpoints emerged such that one represents cybersecurity best practices and the remaining three viewpoints represent poor cybersecurity behaviors that indicate a need for educational interventions within both the public and private sectors.
Abstract: The purpose of this paper is to reveal and describe the divergent viewpoints about cybersecurity within a purposefully selected group of people with a range of expertise in relation to computer security.,Q methodology [Q] uses empirical evidence to differentiate subjective views and, therefore, behaviors in relation to any topic. Q uses the strengths of qualitative and quantitative research methods to reveal and describe the multiple, divergent viewpoints that exist within a group where individuals sort statements into a grid to represent their views. Analyses group similar views (sorts). In this study, participants were selected from a range of types related to cybersecurity (experts, authorities and uninformed).,Four unique viewpoints emerged such that one represents cybersecurity best practices and the remaining three viewpoints represent poor cybersecurity behaviors (Naive Cybersecurity Practitioners, Worried but not Vigilant and How is Cybersecurity a Big Problem) that indicate a need for educational interventions within both the public and private sectors.,Understanding the divergent views about cybersecurity is important within smaller groups including classrooms, technology-based college majors, a company, a set of IT professionals or other targeted groups where understanding cybersecurity viewpoints can reveal the need for training, changes in behavior and/or the potential for security breaches which reflect the human factors of cybersecurity.,A review of the literature revealed that only large, nation-wide surveys have been used to investigate views of cybersecurity. Yet, surveys are not useful in small groups, whereas Q is designed to investigate behavior through revealing subjectivity within smaller groups.
TL;DR: This paper explored women's viewpoints on egg freezing in Austria, a country where egg freezing for social reasons is currently not allowed, and found that three distinct viewpoints were identified: (1) women should decide for themselves, (2) we should accept nature but change policy, and (3) we need an informed societal debate.
Abstract: Egg freezing has emerged as a technology of assisted reproductive medicine that allows women to plan for the anticipated loss of fertility and hence to preserve the option to conceive with their own eggs. The technology is surrounded by value-conflicts and is subject to ongoing discussions. This study aims at contributing to the empirical-ethical debate by exploring women’s viewpoints on egg freezing in Austria,
where egg freezing for social reasons is currently not allowed. Q-methodology was used to identify prevailing viewpoints on egg freezing. 46 female participants ranked a set of 40 statements onto a 9-column forced choice ranking grid according to the level of agreement. Participants were asked to explain their ranking in a follow-up survey. By-person factor analysis was used to identify distinct viewpoints which were interpreted using both the quantitative and the qualitative data. Three distinct viewpoints were identified: (1) “women should decide for themselves”, (2) “we should accept nature but change policy”, and (3) “we need an informed societal debate”. These viewpoints provide insights into how biomedical innovations such as egg freezing are perceived by women in Austria and illustrate the normative tensions regarding such innovations. Acknowledging the different prioritizations of values regarding assisted reproductive technologies is important to better understand the underlying normative tensions in a country where egg freezing for social reasons is currently not allowed. The study adds new empirical insights to the ongoing debate by outlining and discussing viewpoints of those directly affected: women. Following up on the lay persons perspective is particularly important in the context of future biomedical innovations that may challenge established norms and create new tensions. It therefore also adds to the societal debate and supports evidence-informed policy making in that regard.
TL;DR: An experiment was conducted to test selected open data standards' performance on a variety of fronts, including augmented reality, virtual reality, and e-commerce.
Abstract: Industry desires a digital thread of information that aligns as-designed, as-planned, as-executed, and as-inspected viewpoints. An experiment was conducted to test selected open data standards' abi...