Academic literature on the topic 'Grounded'

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Journal articles on the topic "Grounded"

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Sider, Theodore. "Ground grounded." Philosophical Studies 177, no. 3 (December 14, 2018): 747–67. http://dx.doi.org/10.1007/s11098-018-1204-6.

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Litland, Jon Erling. "Could the grounds’s grounding the grounded ground the grounded?" Analysis 78, no. 1 (August 9, 2017): 56–65. http://dx.doi.org/10.1093/analys/anx116.

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Knapp, Mark L. "Grounded or Ground-Breaking?" Contemporary Psychology: A Journal of Reviews 34, no. 8 (August 1989): 797–98. http://dx.doi.org/10.1037/031034.

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Griffin, Christine. "Grounded in Grounded Theory?" Contemporary Psychology 45, no. 4 (August 2000): 380–82. http://dx.doi.org/10.1037/002239.

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Miller, Sarah. "Grounded." College English 59, no. 8 (December 1997): 936. http://dx.doi.org/10.2307/378301.

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Upson, Sandra. "Grounded." IEEE Spectrum 44, no. 1 (January 2007): 32–34. http://dx.doi.org/10.1109/mspec.2007.273039.

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BARKAWI, TARAK. "Grounded." Review of International Studies 35, no. 4 (October 2009): 860–62. http://dx.doi.org/10.1017/s0260210509990222.

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Kothari, Geeta. "Grounded." Pleiades: Literature in Context 42, no. 2-1 (September 2022): 24–28. http://dx.doi.org/10.1353/plc.2022.0086.

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Cella, Claire. "Grounded." Cream City Review 47, no. 2 (September 2023): 62. http://dx.doi.org/10.1353/ccr.2023.a915620.

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Gnad, Daniel, Álvaro Torralba, Martín Domínguez, Carlos Areces, and Facundo Bustos. "Learning How to Ground a Plan – Partial Grounding in Classical Planning." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 7602–9. http://dx.doi.org/10.1609/aaai.v33i01.33017602.

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Current classical planners are very successful in finding (nonoptimal) plans, even for large planning instances. To do so, most planners rely on a preprocessing stage that computes a grounded representation of the task. Whenever the grounded task is too big to be generated (i.e., whenever this preprocess fails) the instance cannot even be tackled by the actual planner. To address this issue, we introduce a partial grounding approach that grounds only a projection of the task, when complete grounding is not feasible. We propose a guiding mechanism that, for a given domain, identifies the parts of a task that are relevant to find a plan by using off-the-shelf machine learning methods. Our empirical evaluation attests that the approach is capable of solving planning instances that are too big to be fully grounded.
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Dissertations / Theses on the topic "Grounded"

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Jones, Kevin William. "Grounded Figure: A Winery." Thesis, Virginia Tech, 2004. http://hdl.handle.net/10919/10047.

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The nature of figure-ground relationships and their potential for use as a tool for architectural composition was investigated through the design of a winery. Included in the winery were facilities accomodating both the production and consumption of wine. These programmatic elements were used as guides for the development of multiple figure-ground relationships at a variety of scales. In addition, the dialogue between different figures as well as the careful development of the backdrop surfaces were topics of study. Several design strategies were employed to create relationships between figure elements and their backdrops, including the insertion of volumes into and through one another, the careful development of material and surface, and light. From this work, as well as previous projects, several key findings can now be articulated concerning the potential use of figure-ground relationships in the development of a work of architecture. These include the need to optimize the proportion of figure(s) relative to a given background and the key role that the disposition of figures relative to one another plays in the development of a meaningful figure-ground relationship.
Master of Architecture
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Chisnall, Anne Clare. "Grounded theory for knowledge acquisition." Thesis, De Montfort University, 1998. http://hdl.handle.net/2086/4140.

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Silberer, Carina Helga. "Learning visually grounded meaning representations." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14236.

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Humans possess a rich semantic knowledge of words and concepts which captures the perceivable physical properties of their real-world referents and their relations. Encoding this knowledge or some of its aspects is the goal of computational models of semantic representation and has been the subject of considerable research in cognitive science, natural language processing, and related areas. Existing models have placed emphasis on different aspects of meaning, depending ultimately on the task at hand. Typically, such models have been used in tasks addressing the simulation of behavioural phenomena, e.g., lexical priming or categorisation, as well as in natural language applications, such as information retrieval, document classification, or semantic role labelling. A major strand of research popular across disciplines focuses on models which induce semantic representations from text corpora. These models are based on the hypothesis that the meaning of words is established by their distributional relation to other words (Harris, 1954). Despite their widespread use, distributional models of word meaning have been criticised as ‘disembodied’ in that they are not grounded in perception and action (Perfetti, 1998; Barsalou, 1999; Glenberg and Kaschak, 2002). This lack of grounding contrasts with many experimental studies suggesting that meaning is acquired not only from exposure to the linguistic environment but also from our interaction with the physical world (Landau et al., 1998; Bornstein et al., 2004). This criticism has led to the emergence of new models aiming at inducing perceptually grounded semantic representations. Essentially, existing approaches learn meaning representations from multiple views corresponding to different modalities, i.e. linguistic and perceptual input. To approximate the perceptual modality, previous work has relied largely on semantic attributes collected from humans (e.g., is round, is sour), or on automatically extracted image features. Semantic attributes have a long-standing tradition in cognitive science and are thought to represent salient psychological aspects of word meaning including multisensory information. However, their elicitation from human subjects limits the scope of computational models to a small number of concepts for which attributes are available. In this thesis, we present an approach which draws inspiration from the successful application of attribute classifiers in image classification, and represent images and the concepts depicted by them by automatically predicted visual attributes. To this end, we create a dataset comprising nearly 700K images and a taxonomy of 636 visual attributes and use it to train attribute classifiers. We show that their predictions can act as a substitute for human-produced attributes without any critical information loss. In line with the attribute-based approximation of the visual modality, we represent the linguistic modality by textual attributes which we obtain with an off-the-shelf distributional model. Having first established this core contribution of a novel modelling framework for grounded meaning representations based on semantic attributes, we show that these can be integrated into existing approaches to perceptually grounded representations. We then introduce a model which is formulated as a stacked autoencoder (a variant of multilayer neural networks), which learns higher-level meaning representations by mapping words and images, represented by attributes, into a common embedding space. In contrast to most previous approaches to multimodal learning using different variants of deep networks and data sources, our model is defined at a finer level of granularity—it computes representations for individual words and is unique in its use of attributes as a means of representing the textual and visual modalities. We evaluate the effectiveness of the representations learnt by our model by assessing its ability to account for human behaviour on three semantic tasks, namely word similarity, concept categorisation, and typicality of category members. With respect to the word similarity task, we focus on the model’s ability to capture similarity in both the meaning and appearance of the words’ referents. Since existing benchmark datasets on word similarity do not distinguish between these two dimensions and often contain abstract words, we create a new dataset in a large-scale experiment where participants are asked to give two ratings per word pair expressing their semantic and visual similarity, respectively. Experimental results show that our model learns meaningful representations which are more accurate than models based on individual modalities or different modality integration mechanisms. The presented model is furthermore able to predict textual attributes for new concepts given their visual attribute predictions only, which we demonstrate by comparing model output with human generated attributes. Finally, we show the model’s effectiveness in an image-based task on visual category learning, in which images are used as a stand-in for real-world objects.
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Sunde, Hans Viken. "Opplevinga av eit meiningsfullt tilvære : Ei kvalitativ intervjuundersøking." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for voksnes læring og rådgivningsvitenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-14012.

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Gjennom intervju i fenomenologisk tradisjon har eg undersøkt tre unge menn si oppleving av meining i deira eigne liv. Forskingsdeltakarane vurderar sjølv kva hendingar som er relevante. På bakgrunn av intervjua har eg prøvd å finne ein essens i opplevingane. Inspirert av kodingsprosessane i Grounded Theory har eg komme fram til fem kategoriar som representerar ulike måtar forskingsdeltakarane opplever meining på. Eg prøvar vidare å seie noko om kva samanheng det ser ut til å vere mellom kategoriane. Resultata frå analysen munnar ut i ein kontekstuelt forankra lokal teori. Den lokale teorien blir i drøfta i lys av generelle teoriar og tidligare empirisk forsking. I drøftinga ser eg at forskjellige teoretiske utgangspunkt bidreg til ei rik forståing av meining som omgrep. Til slutt ser eg på kva mine funn og drøftingar betyr for forsking og praksis innanfor rådgivingspedagogikk. Eg konkluderar med at meining som omgrep er relevant for menneske generelt og rådgivarar spesielt.
In this research paper I will present the results of analysis based on the interviews of three young men and their experiences with meaning in their own lives. The interviews are placed within a phenomenological tradition, and the participants themselves decide what experiences are deemed relevant. Inspired by the coding processes of Grounded Theory I have searched for an essence of the experiences the participants share. Through categorical analysis I have reached five categories, which intend to describe the different ways in which the participants experience meaning. By looking at the interaction between the categories I reach a contextual local theory. This local theory is discussed in light of general theory and previous empiric research. In the discussion I will point out how the different theoretical views contribute to a rich understanding of meaning as a concept. Based on my general discussion I look at what impact my findings may have on future counselling research and practice. I will conclude that the concept of meaning should be relevant to human beings in general and counsellors in particular.
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Ross, Candace Cheronda. "Grounded semantic parsing using captioned videos." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/118036.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 45-47).
We develop a semantic parser which is trained in a grounded setting using pairs of videos captioned with sentences. This setting is both data-efficient requiring little annotation and far more similar to the experience of children where they observe their environment and listen to speakers. The semantic parser recovers the meaning of English sentences despite not having access to any annotated sentences and despite the ambiguity inherent in vision where a sentence may refer to any combination of objects, object properties, relations or actions taken by any agent in a video. We introduce a new corpus for grounded language acquisition. Learning to understand language, turn sentences into logical forms, by using captioned video will significantly expand the range of data that parsers can be trained on, lower the effort of training a semantic parser, and ultimately lead to a better understanding of child language acquisition.
by Candace Cheronda Ross.
S.M.
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Wiese, Eliane. "Toward Sense Making with Grounded Feedback." Research Showcase @ CMU, 2015. http://repository.cmu.edu/dissertations/628.

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In STEM domains, robust learning includes not only fluency with procedures, but also recognition and application of the conceptual principles that underlie them. Grounded feedback is one instructional approach proposed to help students integrate conceptual knowledge into their learning of procedures. Grounded feedback functions primarily by having students take an action in the target domain (often symbolic) and receiving feedback in a representation that is easier to reason with. This thesis defines grounded feedback and evaluates its effectiveness. I define grounded feedback with four characteristics: (1) The feedback reflects students’ inputs according to rules that are inherent to the topic of study. For example, an inputted equation with two variables may be shown as a graph. (2) The feedback facilitates selfevaluation - by examining the feedback, students can evaluate for themselves if their answers are correct or not. (3) Students do not directly manipulate the feedback representation. Instead, the inputs are in a format that matches the domain learning goals. (4) The feedback conveys information about the nature of errors, not just that a particular action was incorrect. For example, the feedback may indicate the direction or magnitude of the error. Some prior experiments on systems with the four characteristics of grounded feedback found greater learning of target procedures (Nathan 1998) and greater transfer (Mathan & Koedinger 20015), relative to robust controls. Over four studies with 4th and 5th graders, this thesis explores three tutor designs for fraction addition that incorporate visualizations of magnitude, including grounded feedback. Two studies of grounded feedback show effects of robust learning relative to correctness feedback, including greater future learning (in study 2) and transfer (in study 3). Another study found little difference between grounded feedback with and without correctness. In the last study, relative to correctness feedback, two implementations of dynamically linked concrete representations (variations on grounded feedback) showed greater robust learning (pre-test to delayed test). The correctness feedback tutor, used in three of these studies, is a high-bar control, including immediate step-level correctness feedback and adaptive on-demand hints. Indications of more robust learning with the grounded feedback tutor are promising, though not conclusive. Grounded feedback is intended to leverage concrete representations to elicit students’ prior knowledge of relevant concepts. Over two Difficulty Factor Assessments, 5th graders demonstrated difficulty incorporating magnitude information when evaluating fraction addition equations. In particular, students could generally evaluate an equation correctly when it was represented with fraction bars. However, including symbols with the bars interfered with students’ evaluations by triggering incorrect transfer from whole-number addition. Students also did not fully grasp that when two positive fractions are added, the resulting sum is bigger than each addend alone. These findings may help explain why the benefits of grounded feedback are not as strong as proponents of concrete representations might hope. Namely, the target population may not be able to take full advantage of the magnitude visualization because they lack pre-requisite knowledge of how fraction addition involves magnitude.
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Coleman, Donnie Steve. "Technological Immersion Learning: A Grounded Theory." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/75155.

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The Technological Immersion Learning Theory (TILT) was developed through a classic grounded theory study in the seminal tradition of Glaser and Strauss (1967) and Glaser (1978, 1992, 1998, 2001, 2007). The purpose of the study was to investigate an exemplary case of self-determined technology enthusiasts in the hopes of generating a substantive grounded theory that conceptualizes their experiences and concerns. Twelve unstructured interviews of amateur radio enthusiasts from the eastern United States provided the initial / primary data for this study. Experimenting and self-teaching in technological activities was highlighted as the main concern of the participants. The basic social process (BSP) of technological immersion learning (TIL) emerged as a theoretical construct and core variable that illuminates the experiences of individuals immersed in a community of practice, where hands-on engagement with technology is a primary activity. Adventuring, Affirmation, Doing Technology, Experimenting, Overcoming Challenge, Self-teaching, and Social Networking were properties of technological immersion learning that interact dialectically in an amplifying causal loop, with Problem solving and Designing as active sub processes in response to unmet challenges. TIL occurs cyclically in three stages, beginning with Induction, a credentialing stage wherein the neophyte is prepared with the necessary knowledge and skill to become a novice participant in an activity. The transition from Induction into the Immersion phase is a status passage whereby the novice is absorbed into the technical culture of the group and commences autonomous active participation in hands-on experimenting. Hands-on experiences with experimenting, problem solving and social interactions provide diverse learning and affirmation for the doer and multiple sources of feedback that promote sustained engagement. The transition into the Maturation phase proceeds gradually over time, with prolonged engagement and cumulative gains in knowledge, skill, and experience. Maturation is a quasi-stable state that remains responsive to new contexts as a random-walk process, wherein trigger events can initiate new cycles of technological immersion learning in a perpetually evolving process of personal development. Engagement, Empowerment, and Self-Actualization are underlying dimensions of the TIL basic social process that provide the impetus for continued persistence and personal development.
Ph. D.
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Smart, Susanna Jennifer. "Grounded Theory of Rosen Method Bodywork." Kent State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=kent1524757138389208.

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Aalders, Cynthia Yvonne. "Catharine Parr Traill a grounded spirituality /." Online full text .pdf document, available to Fuller patrons only, 2001. http://www.tren.com.

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Naqvi, Syed Asad Ali. "The grounded incident fault theories (GIFTs) method." Thesis, Lancaster University, 2014. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.719799.

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Accidents, and incidents of faults and failures are an unavoidable reality for even moderately complex systems. Accidents, though unfortunate events, also provide an opportunity to uncover vulnerabilities and latent errors in systems. In this vein accident and incident analysis plays an important role in improving system dependability and robustness. Incidents when analysed individually often seem to be caused due to isolated reasons. However, when incidents are analysed in the context of other incidents in the broader domain then patterns begin to emerge between them. These patterns may indicate basic and underlying reasons for incidents, known as root causes. The practice of analysing a number of incidents together is called Multi-incident analysis. The state of the art of multi-incident analysis is dominated by quantitative methods that mostly use statistical analysis to find correlations between concepts. These methods are limited in their ability to identify systemic reasons for accidents, faults, and failures. To overcome this shortcoming, qualitative methods are sometimes used in incident analysis; in an effort to acquire a better understanding of the incident space. However, these methods do not provide any methodological support to guide the qualitative analysis towards the discovery of root causes. This thesis presents the Grounded Incident Fault Theories (GIFTs) method for multi-incident analysis. GIFTs is a qualitative multi-incident analysis method that provides methodological support to identify root causes and mitigation strategies by analysing past incident in a particular domain. GIFTs is a synthesis of two methods: The Incident Fault Tree (IFT), which is a method for incident analysis and documentation; and The Grounded Theory Method (GTM), which is a qualitative analysis method for building theories and discovering insights about phenomenon through the aggregation of data. GIFTs merges these two methods in a way that the whole is greater than the sum of its parts. In GIFTs the Incident Fault Tree guides the Grounded Theory process to efficiently identify the most important concepts with respect to understanding and mitigating faults and failures.
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Books on the topic "Grounded"

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Grounded. London: Titan Bks., 1993.

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Klise, Kate. Grounded. New York: Feiwel and Friends, 2010.

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Grounded. Dublin, Ireland: Little Island, 2012.

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Grounded. Waterville, Maine: Thorndike Press, A part of Gale, Cengage Learning, 2013.

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Oktay, Julianne S. Grounded theory. New York, NY: Oxford University Press, 2012.

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Akmakjian, Alan P. Grounded angels. Conover, NC: Third Lung Press, 1993.

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Strübing, Jörg. Grounded Theory. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-24425-5.

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Strübing, Jörg. Grounded Theory. Wiesbaden: VS Verlag für Sozialwissenschaften, 2004. http://dx.doi.org/10.1007/978-3-322-95015-4.

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Strübing, Jörg. Grounded Theory. Wiesbaden: VS Verlag für Sozialwissenschaften, 2014. http://dx.doi.org/10.1007/978-3-531-19897-2.

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Strübing, Jörg. Grounded Theory. Wiesbaden: VS Verlag für Sozialwissenschaften, 2008. http://dx.doi.org/10.1007/978-3-531-91968-3.

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Book chapters on the topic "Grounded"

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Elton, David J. "Exploding Soils (Extreme Slaking)." In Grounded!, 1–6. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch01.

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Elton, David J. "Rice Is Nice (an Exercise in Pile Capacity)." In Grounded!, 7–11. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch02.

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Elton, David J. "Break that Block (the Power of Bentonite)." In Grounded!, 12–16. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch03.

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Elton, David J. "A Retaining Wall Made of Paper." In Grounded!, 17–24. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch04.

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Elton, David J. "Slip Slidin’ away with Effective Stress." In Grounded!, 25–30. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch05.

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Elton, David J. "Magic Beaker (Sand Defies Gravity)." In Grounded!, 31–34. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch06.

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Elton, David J. "Effective Potato Chips." In Grounded!, 35–40. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch07.

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Elton, David J. "Foam Balls in a Pipe (Soil Arching)." In Grounded!, 41–45. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch08.

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Elton, David J. "Geotechnical Rorschach Test (Water Flows around a Drain, instead of into the Drain)." In Grounded!, 46–50. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch09.

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Elton, David J. "Hairy Soil." In Grounded!, 51–54. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784413920.ch10.

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Conference papers on the topic "Grounded"

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Liu, Vicki, Carmen Banea, and Rada Mihalcea. "Grounded emotions." In 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII). IEEE, 2017. http://dx.doi.org/10.1109/acii.2017.8273642.

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Westerlaken, Michelle, and Stefano Gualeni. "Grounded Zoomorphism." In the 2014 Workshops. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2693787.2693796.

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Wu, Chen Henry, Yinhe Zheng, Xiaoxi Mao, and Minlie Huang. "Transferable Persona-Grounded Dialogues via Grounded Minimal Edits." In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-main.183.

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Hong, Young Ki, and Rashaunda M. Henderson. "Spiral defected ground structures in grounded coplanar waveguide." In 2011 IEEE Radio and Wireless Symposium (RWS). IEEE, 2011. http://dx.doi.org/10.1109/rws.2011.5725499.

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Ort, Teddy, Igor Gilitschenski, and Daniela Rus. "GROUNDED: The Localizing Ground Penetrating Radar Evaluation Dataset." In Robotics: Science and Systems 2021. Robotics: Science and Systems Foundation, 2021. http://dx.doi.org/10.15607/rss.2021.xvii.080.

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Zhou, Luowei, Yannis Kalantidis, Xinlei Chen, Jason J. Corso, and Marcus Rohrbach. "Grounded Video Description." In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2019. http://dx.doi.org/10.1109/cvpr.2019.00674.

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Roy, Deb. "Grounded speech communication." In 6th International Conference on Spoken Language Processing (ICSLP 2000). ISCA: ISCA, 2000. http://dx.doi.org/10.21437/icslp.2000-753.

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Kartci, Aslihan, Norbert Herencsar, Kamil Vrba, and Shahram Minaei. "Novel grounded capacitor-based resistorless tunable floating/grounded inductance simulator." In 2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2016. http://dx.doi.org/10.1109/mwscas.2016.7870125.

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Le, Hung, Nancy Chen, and Steven Hoi. "VGNMN: Video-grounded Neural Module Networks for Video-Grounded Dialogue Systems." In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.naacl-main.247.

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Gidey, Habtom Kahsay, Diego Marmsoler, and Jonas Eckhardt. "Grounded Architectures: Using Grounded Theory for the Design of Software Architectures." In 2017 IEEE International Conference on Software Architecture Workshops (ICSAW). IEEE, 2017. http://dx.doi.org/10.1109/icsaw.2017.41.

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Reports on the topic "Grounded"

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Balzer, Robert. Semantically Grounded Briefings. Fort Belvoir, VA: Defense Technical Information Center, December 2005. http://dx.doi.org/10.21236/ada443554.

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Hwang, Tim. Deepfakes: A Grounded Threat Assessment. Center for Security and Emerging Technology, July 2020. http://dx.doi.org/10.51593/20190030.

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The rise of deepfakes could enhance the effectiveness of disinformation efforts by states, political parties and adversarial actors. How rapidly is this technology advancing, and who in reality might adopt it for malicious ends? This report offers a comprehensive deepfake threat assessment grounded in the latest machine learning research on generative models.
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Mullen, G. M. Choppers Grounded: The Supply-Demand Problem. Fort Belvoir, VA: Defense Technical Information Center, January 1988. http://dx.doi.org/10.21236/ada264258.

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Zettlemoyer, Luke, and Dieter Fox. Integrated Intelligence: Robot Instruction via Interactive Grounded Learning. Fort Belvoir, VA: Defense Technical Information Center, January 2016. http://dx.doi.org/10.21236/ad1008203.

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Zhou, Q., K. H. Lee, N. E. Goldstein, H. F. Morrison, and A. Becker. Fracture detection using a grounded subsurface vertical electric dipole. Office of Scientific and Technical Information (OSTI), August 1986. http://dx.doi.org/10.2172/6607811.

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Kucheryavyy, Konstantin, Gary Lyn, and Andrés Rodríguez-Clare. Grounded by Gravity: A Well-Behaved Trade Model with Industry-Level Economies of Scale. Cambridge, MA: National Bureau of Economic Research, August 2016. http://dx.doi.org/10.3386/w22484.

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Gopalakrishnan, Sivasankari, Delisia R. Matthews, and Marguerite Moore. A Grounded Analysis of Collaborative Consumption among Apparel Consumers: Identification of Motivations for Engagement. Ames: Iowa State University, Digital Repository, November 2016. http://dx.doi.org/10.31274/itaa_proceedings-180814-1501.

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Gauz, Maurice. 'This Would Be Much Funner in Person': A Qualitative Grounded Theory Analysis of Cybergrooming. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1802.

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Bright, Nicola, Keita Durie, Renee Tuifagalele, and Taniora Robinson. Ngā whai painga o Te Ao Haka | The positive impacts of Te Ao Haka for ākonga, whānau, and kaiako. NZCER, February 2023. http://dx.doi.org/10.18296/rep.0027.

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Abstract:
This report It sets out out to understand what benefits and changes can occur for ākonga Māori, whānau, and kaiako when a subject such as Te Ao Haka—that is grounded in te Ao Māori and centres Māori culture, language and identity, knowledge systems, and iwi traditions—has mana ōrite or equal status within NCEA and The New Zealand Curriculum.
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Rothrock, Elaine. The behavior of coalitions as interorganizational structures: an exploratory study using a grounded theory approach. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.1615.

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