scholarly journals Web Augmentation as a Technique to Diminish User Interactions in Repetitive Tasks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Inigo Aldalur ◽  
Alain Perez ◽  
Felix Larrinaga.
2011 ◽  
Author(s):  
Seokchan Yun ◽  
Heungseok Do ◽  
Jinuk Jung ◽  
Song Mina ◽  
Namgoong Hyun ◽  
...  

2018 ◽  
Vol 27 (1) ◽  
pp. 5-21
Author(s):  
Amanda Dennis

Lying in ditches, tromping through mud, wedged in urns, trash bins, buried in earth, bodies in Beckett appear anything but capable of acting meaningfully on their environments. Bodies in Beckett seem, rather, synonymous with abjection, brokenness, and passivity—as if the human were overcome by its materiality: odours, pain, foot sores, decreased mobility. To the extent that Beckett's personae act, they act vaguely (wandering) or engage in quasi-obsessive, repetitive tasks: maniacal rocking, rotating sucking stones and biscuits, uttering words evacuated of sense, ceaseless pacing. Perhaps the most vivid dramatization of bodies compelled to meaningless, repetitive movement is Quad (1981), Beckett's ‘ballet’ for television, in which four bodies in hooded robes repeat their series ad infinitum. By 1981, has all possibility for intentional action in Beckett been foreclosed? Are we doomed, as Hamm puts it, to an eternal repetition of the same? (‘Moments for nothing, now as always, time was never and time is over, reckoning closed and story ended.’)This article proposes an alternative reading of bodily abjection, passivity and compulsivity in Beckett, a reading that implies a version of agency more capacious than voluntarism. Focusing on Quad as an illustrative case, I show how, if we shift our focus from the body's diminished possibilities for movement to the imbrication of Beckett's personae in environments (a mound of earth), things, and objects, a different story emerges: rather than dramatizing the impossibility of action, Beckett's work may sketch plans for a more ecological, post-human version of agency, a more collaborative mode of ‘acting’ that eases the divide between the human, the world of inanimate objects, and the earth.Movements such as new materialism and object-oriented ontology challenge hierarchies among subjects, objects and environments, questioning the rigid distinction between animate and inanimate, and the notion of the Anthropocene emphasizes the influence of human activity on social and geological space. A major theoretical challenge that arises from such discourses (including 20th-century challenges to the idea of an autonomous, willing, subject) is to arrive at an account of agency robust enough to survive if not the ‘death of the subject’ then its imbrication in the material and social environment it acts upon. Beckett's treatment of the human body suggests a version of agency that draws strength from a body's interaction with its environment, such that meaning is formed in the nexus between body and world. Using the example of Quad, I show how representations of the body in Beckett disturb the opposition between compulsivity (when a body is driven to move or speak in the absence of intention) and creative invention. In Quad, serial repetition works to create an interface between body and world that is receptive to meanings outside the control of a human will. Paradoxically, compulsive repetition in Beckett, despite its uncomfortable closeness to addiction, harnesses a loss of individual control that proposes a more versatile and ecologically mindful understanding of human action.


Author(s):  
Mahesh K. Joshi ◽  
J.R. Klein

New technologies like artificial intelligence, robotics, machine intelligence, and the Internet of Things are seeing repetitive tasks move away from humans to machines. Humans cannot become machines, but machines can become more human-like. The traditional model of educating workers for the workforce is fast becoming irrelevant. There is a massive need for the retooling of human workers. Humans need to be trained to remain focused in a society which is constantly getting bombarded with information. The two basic elements of physical and mental capacity are slowly being taken over by machines and artificial intelligence. This changes the fundamental role of the global workforce.


2021 ◽  
Vol 39 (2) ◽  
pp. 1-29
Author(s):  
Qingyao Ai ◽  
Tao Yang ◽  
Huazheng Wang ◽  
Jiaxin Mao

How to obtain an unbiased ranking model by learning to rank with biased user feedback is an important research question for IR. Existing work on unbiased learning to rank (ULTR) can be broadly categorized into two groups—the studies on unbiased learning algorithms with logged data, namely, the offline unbiased learning, and the studies on unbiased parameters estimation with real-time user interactions, namely, the online learning to rank. While their definitions of unbiasness are different, these two types of ULTR algorithms share the same goal—to find the best models that rank documents based on their intrinsic relevance or utility. However, most studies on offline and online unbiased learning to rank are carried in parallel without detailed comparisons on their background theories and empirical performance. In this article, we formalize the task of unbiased learning to rank and show that existing algorithms for offline unbiased learning and online learning to rank are just the two sides of the same coin. We evaluate eight state-of-the-art ULTR algorithms and find that many of them can be used in both offline settings and online environments with or without minor modifications. Further, we analyze how different offline and online learning paradigms would affect the theoretical foundation and empirical effectiveness of each algorithm on both synthetic and real search data. Our findings provide important insights and guidelines for choosing and deploying ULTR algorithms in practice.


Author(s):  
Alexander Bigazzi ◽  
Gurdiljot Gill ◽  
Meghan Winters

Assessments of interactions between road users are crucial to understanding comfort and safety. However, observers may vary in their perceptions and ratings of road user interactions. The objective of this paper is to examine how perceptions of yielding, comfort, and safety for pedestrian interactions vary among observers, ranging from members of the public to road safety experts. Video clips of pedestrian interactions with motor vehicles and bicycles were collected from 11 crosswalks and shown to three groups of participants (traffic safety experts, an engaged citizen advisory group, and members of the general public) along with questions about yielding, comfort, and risk of injury. Experts had similar views of yielding and comfort to the other two groups, but a consistently lower assessment of injury risk for pedestrians in the study. Respondent socio-demographics did not relate to perceptions of yielding, comfort, or risk, but self-reported travel habits did. Respondents who reported walking more frequently rated pedestrian comfort as lower, and respondents who reported cycling more frequently rated risk as lower for pedestrian interactions with both motor vehicles and bicycles. Findings suggest small groups of engaged citizens can provide useful information about public perspectives on safety that likely diverge from expert assessments of risk, and that sample representation should be assessed in relation to travel habits rather than socio-demographics.


2021 ◽  
Vol 9 (6) ◽  
pp. 572
Author(s):  
Luca Di Di Angelo ◽  
Francesco Duronio ◽  
Angelo De De Vita ◽  
Andrea Di Di Mascio

In this paper, an efficient and robust Cartesian Mesh Generation with Local Refinement for an Immersed Boundary Approach is proposed, whose key feature is the capability of high Reynolds number simulations by the use of wall function models, bypassing the need for accurate boundary layer discretization. Starting from the discrete manifold model of the object to be analyzed, the proposed model generates Cartesian adaptive grids for a CFD simulation, with minimal user interactions; the most innovative aspect of this approach is that the automatic generation is based on the segmentation of the surfaces enveloping the object to be analyzed. The aim of this paper is to show that this automatic workflow is robust and enables to get quantitative results on geometrically complex configurations such as marine vehicles. To this purpose, the proposed methodology has been applied to the simulation of the flow past a BB2 submarine, discretized by non-uniform grid density. The obtained results are comparable with those obtained by classical body-fitted approaches but with a significant reduction of the time required for the mesh generation.


Robotics ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 3
Author(s):  
Tudor B. Ionescu

A novel approach to generic (or generalized) robot programming and a novel simplified, block-based programming environment, called “Assembly”, are introduced. The approach leverages the newest graphical user interface automation tools and techniques to generate programs in various proprietary robot programming environments by emulating user interactions in those environments. The “Assembly” tool is used to generate robot-independent intermediary program models, which are translated into robot-specific programs using a graphical user interface automation toolchain. The generalizability of the approach to list, tree, and block-based programming is assessed using three different robot programming environments, two of which are proprietary. The results of this evaluation suggest that the proposed approach is feasible for an entire range of programming models and thus enables the generation of programs in various proprietary robot programming environments. In educational settings, the automated generation of programs fosters learning different robot programming models by example. For experts, the proposed approach provides a means for generating program (or task) templates, which can be adjusted to the needs of the application at hand on the shop floor.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.


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