A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems' Worldviews

Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot's abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi-robot system that uses the shared-world coordination paradigm autonomously schedules which robot should perform a given task, and when, using its worldview--the robot's internal representation of its belief about both its own state, and other robots' states. A key problem for operators is that robots' worldviews can fall out of sync (often due to weak communication links), leading to desynchronization of the robots' scheduling decisions and inconsistent emergent behavior (e.g., tasks not performed, or performed by multiple robots). Operators face the time-consuming and difficult task of making sense of the robots' scheduling decisions, detecting de-synchronizations, and pinpointing the cause by comparing every robot's worldview. To address these challenges, we introduce MOSAIC Viewer, a visual analytics system that helps operators (i) make sense of the robots' schedules and (ii) detect and conduct a root cause analysis of the robots' desynchronized worldviews. Over a year-long partnership with roboticists at the NASA Jet Propulsion Laboratory, we conduct a formative study to identify the necessary system design requirements and a qualitative evaluation with 12 roboticists. We find that MOSAIC Viewer is faster- and easier-to-use than the users' current approaches, and it allows them to stitch low-level details to formulate a high-level understanding of the robots' schedules and detect and pinpoint the cause of the desynchronized worldviews.Comment: To appear in IEEE Conference on Visual Analytics Science and Technology (VAST) 202

Lessons from the Development of an Anomaly Detection Interface on the Mars Perseverance Rover using the ISHMAP Framework

While anomaly detection stands among the most important and valuable problems across many scientific domains, anomaly detection research often focuses on AI methods that can lack the nuance and interpretability so critical to conducting scientific inquiry. In this application paper we present the results of utilizing an alternative approach that situates the mathematical framing of machine learning based anomaly detection within a participatory design framework. In a collaboration with NASA scientists working with the PIXL instrument studying Martian planetary geochemistry as a part of the search for extra-terrestrial life; we report on over 18 months of in-context user research and co-design to define the key problems NASA scientists face when looking to detect and interpret spectral anomalies. We address these problems and develop a novel spectral anomaly detection toolkit for PIXL scientists that is highly accurate while maintaining strong transparency to scientific interpretation. We also describe outcomes from a yearlong field deployment of the algorithm and associated interface. Finally we introduce a new design framework which we developed through the course of this collaboration for co-creating anomaly detection algorithms: Iterative Semantic Heuristic Modeling of Anomalous Phenomena (ISHMAP), which provides a process for scientists and researchers to produce natively interpretable anomaly detection models. This work showcases an example of successfully bridging methodologies from AI and HCI within a scientific domain, and provides a resource in ISHMAP which may be used by other researchers and practitioners looking to partner with other scientific teams to achieve better science through more effective and interpretable anomaly detection tools

A fieldwork of the future with user enactments

Designing radically new technology systems that people will want to use is complex. Design teams must draw on knowledge related to people’s current values and desires to envision a preferred yet plausible future. However, the introduction of new technology can shape people’s values and practices, and what-we-know-now about them does not always translate to an effective guess of what the future could, or should, be. New products and systems typically exist outside of current understandings of technology and use paradigms; they often have few interaction and social conventions to guide the design process, making efforts to pursue them complex and risky. User Enactments (UEs) have been developed as a design approach that aids design teams in more successfully investigate radical alterations to technologies ’ roles, forms, and behaviors in uncharted design spaces. In this paper, we reflect on our repeated use of UE over the past five years to unpack lessons learned and further specify how and when to use it. We conclude with a reflection on how UE can function as a boundary object and implications for future work

Deconstructing wall turbulence -visualization of resolvent modes

This article accompanies a fluid dynamics video entered into the Gallery of Fluid Motion of the 66th Annual Meeting of the APS Division of Fluid Dynamics.Comment: High and low resolution videos associated with this manuscript can be found as ancillary file

Gender, migration and the ambiguous enterprise of professionalizing domestic service: the case of vocational training for the unemployed in France

Drawing on ethnographic data concerning migrant male domestic workers, this article examines the gendered dimensions of the process of racialization in Italy and France. First, it shows that specific racialized constructions of masculinity are mobilized by the employers as well as by training and recruitment agencies. These constructions of masculinity are related to different forms of organization of the sector in each country and to different ideologies about the integration of migrants. Second, the data presented reveal the strategies used by migrant male domestic workers to reaffirm their masculinity in a traditionally feminized sector. In doing so, this article intends to explore the connections between international migration and the gendering of occupations, with regard to the construction and management of masculinities in domestic service. Finally, by examining men’s experiences, this article aims to contribute to a more complex definition of the international division of care work

Immersive and Collaborative Data Visualization Using Virtual Reality Platforms

Effective data visualization is a key part of the discovery process in the era of big data. It is the bridge between the quantitative content of the data and human intuition, and thus an essential component of the scientific path from data into knowledge and understanding. Visualization is also essential in the data mining process, directing the choice of the applicable algorithms, and in helping to identify and remove bad data from the analysis. However, a high complexity or a high dimensionality of modern data sets represents a critical obstacle. How do we visualize interesting structures and patterns that may exist in hyper-dimensional data spaces? A better understanding of how we can perceive and interact with multi dimensional information poses some deep questions in the field of cognition technology and human computer interaction. To this effect, we are exploring the use of immersive virtual reality platforms for scientific data visualization, both as software and inexpensive commodity hardware. These potentially powerful and innovative tools for multi dimensional data visualization can also provide an easy and natural path to a collaborative data visualization and exploration, where scientists can interact with their data and their colleagues in the same visual space. Immersion provides benefits beyond the traditional desktop visualization tools: it leads to a demonstrably better perception of a datascape geometry, more intuitive data understanding, and a better retention of the perceived relationships in the data.Comment: 6 pages, refereed proceedings of 2014 IEEE International Conference on Big Data, page 609, ISBN 978-1-4799-5665-

Multioccupant Activity Recognition in Pervasive Smart Home Environments

been the center of lot of research for many years now. The aim is to recognize the sequence of actions by a specific person using sensor readings. Most of the research has been devoted to activity recognition of single occupants in the environment. However, living environments are usually inhabited by more than one person and possibly with pets. Hence, human activity recognition in the context of multi-occupancy is more general, but also more challenging. The difficulty comes from mainly two aspects: resident identification, known as data association, and diversity of human activities. The present survey paper provides an overview of existing approaches and current practices for activity recognition in multi-occupant smart homes. It presents the latest developments and highlights the open issues in this field

'If You Desire to Enjoy Life, Avoid Unpunctual People': Women, Timetabling and Domestic Advice, 1850–1910

In the second half of the nineteenth century domestic advice manuals applied the language of modern, public time management to the private sphere. This article uses domestic advice and cookery books, including Isabella Beeton's Book of Household Management, to argue that women in the home operated within multiple, overlapping temporalities that incorporated daily, annual, linear and cyclical scales. I examine how seasonal and annual timescales coexisted with the ticking clock of daily time as a framework within which women were instructed to organize their lives in order to conclude that the increasing concern of advice writers with matters of timekeeping and punctuality towards the end of the nineteenth century indicates not the triumph of 'clock time' but rather its failure to overturn other ways of thinking about and using time

Metabolic alterations underlying Bevacizumab therapy in glioblastoma cells

Anti-VEGF therapy with Bevacizumab is approved for glioblastoma treatment, however, it is known that tumors acquired resistance and eventually became even more aggressive and infiltrative after treatment. In the present study we aimed to unravel the potential cellular mechanisms of resistance to Bevacizumab in glioblastoma in vitro models. Using a panel of glioblastoma cell lines we found that Bevacizumab is able to block the secreted VEGF by the tumor cells and be internalized to the cytoplasm, inducing cytotoxicity in vitro. We further found that Bevacizumab increases the expression of hypoxic (HIF-1α and CAIX) and glycolytic markers (GLUT1 and MCT1), leading to higher glucose uptake and lactate production. Furthermore, we showed that part of the consumed glucose by the tumor cells can be stored as glycogen, hampering cell dead following Bevacizumab treatment. Importantly, we found that this change on the glycolytic metabolism occurs independently of hypoxia and before mitochondrial impairment or autophagy induction. Finally, the combination of Bevacizumab with glucose uptake inhibitors decreased in vivo tumor growth and angiogenesis and shift the expression of glycolytic proteins. In conclusion, we reported that Bevacizumab is able to increase the glucose metabolism on cancer cells by abrogating autocrine VEGF in vitro. Define the effects of anti-angiogenic drugs at the cellular level can allow us to discover ways to revert acquired resistance to this therapeutic approaches in the futureThis study was partially developed under the scope of the project NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER), and through the Competitiveness Factors Operational Programme (COMPETE), by Portuguese funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038, and by Brazilian MCTI/CNPq No 73/2013. VMG was recipient from a PhD fellowship (SFRH/BD/51997/2012) from Fundação para a Ciência e Tecnologia (FCT), Portugal. FC was recipient of a master FAPESP fellowship (n° 2014/03684-0) and “BEPE - Bolsa Estágio de Pesquisa no Exterior” (n° 2015/02691-6). OM is recipient of a post-doc fellowship (SFRH/BPD/108351/2015) from FCT, Portugalinfo:eu-repo/semantics/publishedVersio

Understanding a language of ‘aristocracy’, 1700-1850

This article engages with current debates about linguistic usage but in a new way. It examines linguistic change, the shifts in frequency of usage of ‘aristocracy,’ both qualitatively and quantitatively, at specific moments and over time, in print of the period 1700 to 1850. Digital resources are utilized to provide broad quantitative evidence not previously available to historians. The potential use and value of digitized sources is also explored in calculating the volume and frequency of keyword appearance within a broad set of genres. This article also examines qualitatively usage of ‘aristocracy’ by contemporaries and historians and concludes that historians have often used the term anachronistically. It reveals that for much of the eighteenth century ‘aristocracy’ was entirely a political term confined primarily to the educated elite but that by 1850 it had become a common social descriptor of an elite class. It also compares the trajectory of usage of ‘aristocracy’ with that of ‘democracy’ and accounts for the divergence in such usage. It is argued here that analyzing the prevalence and usage of ‘aristocracy’ in contemporary contexts reveals an important narrative of linguistic changes that parallel shifts in political and social culture