Relevant bibliographies by topics / A-priori spatial knowledge

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  2. Books
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  4. Conference papers

Academic literature on the topic 'A-priori spatial knowledge'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "A-priori spatial knowledge"

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Zheng, Yi, and Cheng Yi Wang. "A Priori-Knowledge Method of Bridge Outline Extraction Based on Airborne LiDAR Data." Advanced Materials Research 718-720 (July 2013): 2438–42. http://dx.doi.org/10.4028/www.scientific.net/amr.718-720.2438.

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Bridge information is the most basic spatial data to build 3D digital city and virtual earth, and it plays an important role as clues and reference during extraction of other surface targets. The crucial problem is the extraction of the boundary line of the bridge. It is the research focus of many experts and scholars. This paper presented a method of bridge extraction using airborne LiDAR data. The biggest advantage of the method is based on priori-knowledge and by analyzing the spatial structural characteristics and geometric characteristics of the bridge. Experiments show that this method has a good accuracy compared with the result of expert interpretation.
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Luo, Li, and Giorgos Mountrakis. "Converting local spectral and spatial information from a priori classifiers into contextual knowledge for impervious surface classification." ISPRS Journal of Photogrammetry and Remote Sensing 66, no. 5 (2011): 579–87. http://dx.doi.org/10.1016/j.isprsjprs.2011.03.002.

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Feng, J., L. Bai, S. Liu, X. Su, and H. Hu. "OPTIMIZATION OF DECISION-MAKING FOR SPATIAL SAMPLING IN THE NORTH CHINA PLAIN, BASED ON REMOTE-SENSING A PRIORI KNOWLEDGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B7 (July 31, 2012): 197–202. http://dx.doi.org/10.5194/isprsarchives-xxxix-b7-197-2012.

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Feng, J., L. Bai, S. Liu, X. Su, and H. Hu. "OPTIMIZATION OF DECISION-MAKING FOR SPATIAL SAMPLING IN THE NORTH CHINA PLAIN, BASED ON REMOTE-SENSING A PRIORI KNOWLEDGE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B8 (July 27, 2012): 103–8. http://dx.doi.org/10.5194/isprsarchives-xxxix-b8-103-2012.

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Al Takash, Ahmad, Marianne Beringhier, Mohammad Hammoud, and Jean-Claude Grandidier. "A mixed PGD-a priori time basis strategy for the simulation of cyclic transient thermal behavior." Mechanics & Industry 21, no. 6 (2020): 606. http://dx.doi.org/10.1051/meca/2020082.

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The knowledge of the service life of polymers under cyclic loading, widely used in industrial applications, is required and usually based on the use of methods necessitating an accurate prediction of the stabilized cycle. This implies a large computation time using the Finite Element Method (FEM) since it requires a large number of cycles for polymers. To alleviate this difficulty, a model order reduction method can be used. In this paper, a mixed strategy is investigated. Through the Proper Generalized Decomposition Method (PGD) framework, this strategy combines the Fast Fourier Transform (FFT) to create a priori time basis and the FEM to compute the related spatial modes. The method is applied to 3D thermal problems under cyclic loadings. The robustness of the proposed strategy is discussed for various boundary conditions, multi-times, and different cyclic loadings. A large time saving is obtained proving the interest of this alternative strategy to deal with fatigue simulations.
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Aryal, Jagannath, and Didier Josselin. "Environmental Object Recognition in a Natural Image." International Journal of Agricultural and Environmental Information Systems 5, no. 1 (2014): 1–18. http://dx.doi.org/10.4018/ijaeis.2014010101.

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Natural images, which are filled with intriguing stimuli of spatial objects, represent our cognition and are rich in spatial information. Accurate extraction of spatial objects is challenging due to the associated spatial and spectral complexities in object recognition. In this paper, the authors tackle the problem of spatial object extraction in a GEOgraphic Object Based Image Analysis framework taking psychological and mathematical complexities into account. In doing so, the authors experimented with human and GEOBIA based recognition and segmentation in an image of an area of natural importance, the Ventoux Mountain, France. Focus was given to scales, color, and texture properties at multiple levels in delineating the candidate spatial objects from the natural image. Such objects along with the original image were provided to the human subjects in two stages and three different groups of samples. The results of two stages were collated and analyzed. The analysis showed that there exist different ways to comprehend the geographical objects according to priori knowledge.
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Hashemi, Meysam, Anirudh N. Vattikonda, Viktor Sip, et al. "On the influence of prior information evaluated by fully Bayesian criteria in a personalized whole-brain model of epilepsy spread." PLOS Computational Biology 17, no. 7 (2021): e1009129. http://dx.doi.org/10.1371/journal.pcbi.1009129.

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Individualized anatomical information has been used as prior knowledge in Bayesian inference paradigms of whole-brain network models. However, the actual sensitivity to such personalized information in priors is still unknown. In this study, we introduce the use of fully Bayesian information criteria and leave-one-out cross-validation technique on the subject-specific information to assess different epileptogenicity hypotheses regarding the location of pathological brain areas based on a priori knowledge from dynamical system properties. The Bayesian Virtual Epileptic Patient (BVEP) model, which relies on the fusion of structural data of individuals, a generative model of epileptiform discharges, and a self-tuning Monte Carlo sampling algorithm, is used to infer the spatial map of epileptogenicity across different brain areas. Our results indicate that measuring the out-of-sample prediction accuracy of the BVEP model with informative priors enables reliable and efficient evaluation of potential hypotheses regarding the degree of epileptogenicity across different brain regions. In contrast, while using uninformative priors, the information criteria are unable to provide strong evidence about the epileptogenicity of brain areas. We also show that the fully Bayesian criteria correctly assess different hypotheses about both structural and functional components of whole-brain models that differ across individuals. The fully Bayesian information-theory based approach used in this study suggests a patient-specific strategy for epileptogenicity hypothesis testing in generative brain network models of epilepsy to improve surgical outcomes.
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Feng, Liang, Paul I. Palmer, Robyn Butler, et al. "Surface fluxes of bromoform and dibromomethane over the tropical western Pacific inferred from airborne in situ measurements." Atmospheric Chemistry and Physics 18, no. 20 (2018): 14787–98. http://dx.doi.org/10.5194/acp-18-14787-2018.

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Abstract. We infer surface fluxes of bromoform (CHBr3) and dibromoform (CH2Br2) from aircraft observations over the western Pacific using a tagged version of the GEOS-Chem global 3-D atmospheric chemistry model and a maximum a posteriori inverse model. Using GEOS-Chem (GC) as an intermediary, we find that the distribution of a priori ocean emissions of these gases are reasonably consistent with observed atmospheric mole fractions of CHBr3 (r=0.62) and CH2Br2 (r=0.38). These a priori emissions result in a positive model bias in CHBr3 peaking in the marine boundary layer, but reproduce observed values of CH2Br2 with no significant bias by virtue of its longer atmospheric lifetime. Using GEOS-Chem, we find that observed variations in atmospheric CHBr3 are determined equally by sources over the western Pacific and those outside the study region, but observed variations in CH2Br2 are determined mainly by sources outside the western Pacific. Numerical closed-loop experiments show that the spatial and temporal distribution of boundary layer aircraft data have the potential to substantially improve current knowledge of these fluxes, with improvements related to data density. Using the aircraft data, we estimate aggregated regional fluxes of 3.6±0.3×108 and 0.7±0.1×108 g month−1 for CHBr3 and CH2Br2 over 130–155∘E and 0–12∘ N, respectively, which represent reductions of 20 %–40 % of the prior inventories by Ordóñez et al. (2012) and substantial spatial deviations from different a priori inventories. We find no evidence to support a robust linear relationship between CHBr3 and CH2Br2 oceanic emissions, as used by previous studies. We find that over regions with dense observation coverage, our choice of a priori inventory does not significantly impact our reported a posteriori flux estimates.
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Zheng, Yi, Cheng Yi Wang, Jing Bo Chen, and Dong Xu He. "A Method of Bridge Outline Extraction Based on Airborne LiDAR Data." Applied Mechanics and Materials 303-306 (February 2013): 1048–55. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.1048.

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Automatic and quickly extraction of bridge information from LiDAR data is of great significance in building 3D digital city and virtual earth. Especially the extraction of bridge outline is a crucial problem. It is a concern of many scholars research focus. This paper presented a method of bridge extraction using airborne LiDAR data. The biggest advantage of the method is based on priori-knowledge and by analyzing the spatial structural characteristics and geometric characteristics of the bridge. Experiments show that this method has a good accuracy compared with the result of expert interpretation.
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Yu, Jingjing, Fang Liu, L. C. Jiao, Shuyuan Yang, and Xiaowei He. "A Finite Element Mesh Aggregating Approach to Multiple-Source Reconstruction in Bioluminescence Tomography." International Journal of Biomedical Imaging 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/210428.

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A finite element mesh aggregating approach is presented to reconstruct images of multiple internal bioluminescence sources. Rather than assuming independence between mesh nodes, the proposed reconstruction strategy exploits spatial structure of nodes and aggregation feature of density distribution on the finite element mesh to adaptively determine the number of sources and to improve the quality of reconstructed images. With the proposed strategy integrated in the regularization-based reconstruction process, reconstruction algorithms need no a priori knowledge of source number; even more importantly, they can automatically reconstruct multiple sources that differ greatly in density or power.
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Books on the topic "A-priori spatial knowledge"

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Bolton, Martha Brandt. Locke’s Essay and Leibniz’s Nouveaux Essais. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190608040.003.0010.

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This chapter traces competing theories of universal natures found in Locke’s Essay and Leibniz’s Nouveaux Essais. Locke maintains that kinds must be defined more or less as we see fit, because nature does not exhibit a reasonably precise or fully determinate division of things and there are no eternal archetypes. His theory of kinds is homocentric. It cedes no authority or priority to general truths or ideas over particular ones. By contrast, Leibniz argues that similarity relations are objective eternal essences of kinds. Their reality consists in being possible entities known by God. Concepts are formed by human minds in virtue of innate tendencies to construct sensible representations of essences. He maintains that knowledge of general principles is prior to knowledge of their particular instances. Leibniz considers dimensions (space, time) to be sort of universals with reality like that of essences. For Locke, ideas of space and time are constructed from particular ideas of spatial and temporal qualities.
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Book chapters on the topic "A-priori spatial knowledge"

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Hughes, Fiona. "A Priori Knowledge as the Anticipation of a Material Given and the Need for a Spatial Schematism." In Kant's Aesthetic EpistemologyForm and World. Edinburgh University Press, 2007. http://dx.doi.org/10.3366/edinburgh/9780748621224.003.0006.

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Aryal, Jagannath, and Didier Josselin. "Environmental Object Recognition in a Natural Image." In Geospatial Intelligence. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8054-6.ch059.

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Natural images, which are filled with intriguing stimuli of spatial objects, represent our cognition and are rich in spatial information. Accurate extraction of spatial objects is challenging due to the associated spatial and spectral complexities in object recognition. In this paper, the authors tackle the problem of spatial object extraction in a GEOgraphic Object Based Image Analysis framework taking psychological and mathematical complexities into account. In doing so, the authors experimented with human and GEOBIA based recognition and segmentation in an image of an area of natural importance, the Ventoux Mountain, France. Focus was given to scales, color, and texture properties at multiple levels in delineating the candidate spatial objects from the natural image. Such objects along with the original image were provided to the human subjects in two stages and three different groups of samples. The results of two stages were collated and analyzed. The analysis showed that there exist different ways to comprehend the geographical objects according to priori knowledge.
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Charbonneau, Paul. "Iterated Growth." In Natural Complexity. Princeton University Press, 2017. http://dx.doi.org/10.23943/princeton/9780691176840.003.0002.

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This chapter shows how complex shapes and forms encountered in the natural world result from a growth process driven by the repeated action of simple “rules.” To examine this general idea, the chapter focuses on cellular automata, arguably the simplest type of computer programs conceivable yet can sometimes exhibit behaviors that are extremely complex. Cellular automata are also a classic example of simple rules being able to produce complex global “patterns” that cannot be inferred or predicted even if we have complete, a priori knowledge of these rules. The chapter first considers cellular automata in one and two spatial dimensions before discussing a zoo of two-dimensional structures from simple rules. It then describes the role of agents in iterated growth as well as emergent structures and behaviors that can be produced by cellular automata. The chapter includes exercises and further computational explorations, along with suggested materials for further reading.
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Bull, Prince Hycy. "Using Spatial Constructivist Thinking Theory to Enhance Classroom Instruction for Students with Special Needs." In Communication Technology for Students in Special Education and Gifted Programs. IGI Global, 2012. http://dx.doi.org/10.4018/978-1-60960-878-1.ch005.

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Spatial constructivist thinking theory is an alternative method of presenting digital materials to enhance the learning process of special needs students in a 21st Century classroom. Spatial constructivist thinking is the integration of pictures, animations, videos, color schemes, abstract plans, applets, graphics, and formatted texts in a presentation to represent text and verbal concepts. Concepts can be simple or complex, literary or symbolic representations of the concepts. This representation addresses Bloom’s revised taxonomy to challenge students’ thinking to create knowledge. Spatial constructivist thinking also posits that spatial representation is influenced by ones visual and verbal knowledge, and prior experiences. Spatial constructivist thinking is also influenced by the multiple intelligences theory. Presentations done by an instructor or knowledgeable peer using spatial constructivist thinking theory reflect the best spatial representation of the presenter’s visual and verbal repertoire for concepts presented. For each spatial representation there is a corresponding verbal representation.
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Santoianni, Flavia, and Alessandro Ciasullo. "Digital and Spatial Education Intertwining in the Evolution of Technology Resources for Educational Curriculum Reshaping and Skills Enhancement." In Virtual Reality in Education. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8179-6.ch016.

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The aim of this research is to deepen how digital education has been intertwined with spatial education throughout the evolution of technology resources. In the last years, the user experience has been improved by open-source, collaborative user-generated, and immersive content – starting from multimedia/hypermedia architectures to synthetic learning environments. This research analyses which spatial design principles have influenced multimedia/hypermedia, collaborative web 2.0 interfaces, and more recently the synthetic environments of virtual worlds. The evolution of technology resources supports the hypothesis of a continuous intertwining between digital and spatial education since multimedia/hypermedia architectures, in which spatial knowledge may play a significant role in web-based design according to individual differences in hypermedia fruition, prior knowledge in the field, and personal experience in web-based instruction. In collaborative user-generated content technology, visual presentation facilitates learning co-construction and spaces are intended as synchronous and asynchronous virtual knowledge spaces of communication. In 3D virtual learning environments, spatial interaction is really developed and may open full accessibility to further studies on digital and spatial education. In the joined field of learning and ICT, the main scope of digital technology knowledge sharing, and re-shaping, is the enhancement of digital skills based on experiences in educational activities and the re-thinking of the nature and the format of educational curriculum to implement more experiences in the digital – and, possibly, spatial – fields.
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Bogorny, Vania, Paulo Martins Engel, and Luis Otavio Alavares. "Enhancing the Process of Knowledge Discovery in Geographic Databases Using Geo-Ontologies." In Database Technologies. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-60566-058-5.ch147.

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This chapter introduces the problem of mining frequent geographic patterns and spatial association rules from geographic databases. In the geographic domain most discovered patterns are trivial, non-novel, and noninteresting, which simply represent natural geographic associations intrinsic to geographic data. A large amount of natural geographic associations are explicitly represented in geographic database schemas and geo-ontologies, which have not been used so far in frequent geographic pattern mining. Therefore, this chapter presents a novel approach to extract patterns from geographic databases using geoontologies as prior knowledge. The main goal of this chapter is to show how the large amount of knowledge represented in geo-ontologies can be used to avoid the extraction of patterns that are previously known as noninteresting.
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Papakostas, Christos, Christos Troussas, Akrivi Krouska, and Cleo Sgouropoulou. "On the Development of a Personalized Augmented Reality Spatial Ability Training Mobile Application." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210078.

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Augmented Reality has been integrated in educational settings in the field of engineering. Prior research has examined the learning outcomes and the pedagogical affordances of this technology. However, training undergraduate engineers, from diverse knowledge level, requires customized training approach, tailored to the individual learning pace. In this paper, we present PARSAT (Personalized Augmented Reality Spatial Ability Training), which is a mobile Augmented Reality application for the enhancement of students’ spatial visualization skills. The application takes into account the theoretical contents of engineering design, deployed through video tutorials, and student-computer interaction with 3D objects. Students interpret different views of a 3D object, which are represented on their mobile screen. PARSAT efficaciously strengthens students’ recognition of spatial structures and views, adjusted to the fulfillment of their personal needs. In terms of personalization, PARSAT consists of different levels, which do not follow a linear flow, as each student takes part in a different sequence of activities, according to their time spent in the 3D object manipulation, and their assessment scores at the end of each level. Furthermore, an agent is used to analyze students’ knowledge level, and send them feedback. The system reduces unnecessary cognitive load and, at the same time, improves students learning experience in learning engineering drawing.
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"Advances in Fish Tagging and Marking Technology." In Advances in Fish Tagging and Marking Technology, edited by Russell Bradford. American Fisheries Society, 2012. http://dx.doi.org/10.47886/9781934874271.ch2.

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<i>Abstract</i>.—Tagging studies have been a fundamental tool in fisheries science for over 100 years. During this time tags have progressed from simple markers through to sophisticated miniature computers capable of storing large amounts of data. Making sense of large amounts of spatial and temporal tagging data lends itself well to graphical interpretation. The Electronic Tag Support Systems (ETSS) team at CSIRO has developed a comprehensive visualization system to suit researcher and stakeholder (funding agencies, fishers, public) needs. Researchers are able to access and visualize the data through a proprietary (MapInfo) GIS package; stakeholders can visualize the data without the need for prior GIS knowledge through a menu-driven graphical web portal.
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"Landscape Influences on Stream Habitats and Biological Assemblages." In Landscape Influences on Stream Habitats and Biological Assemblages, edited by Paul W. Seelbach, Michael J. Wiley, Matthew E. Baker, and Kevin E. Wehrly. American Fisheries Society, 2006. http://dx.doi.org/10.47886/9781888569766.ch2.

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<em>Abstract.</em>—–Describing the unique spatial context of any river unit requires integrating catchment and local valley characters. We believe that adding hydrologic regime and key fish species to standard geomorphic variables improves the delineation and characterization of river valley segments as ecological units. Valley segments constrain habitat units, and several segments together can encompass home ranges of mobile fishes. Segments can be accurately defined and characterized using maps and then analyzed across large geographic areas, making them practical for statewide planning and management. By incorporating prior knowledge from modeling landscape–river relationships, we interpreted multiple landscape maps to delineate and assign initial attributes to river valley segments. The resulting classification system provides a new, ecologically informed view of Michigan’s rivers that has helped managers better perceive and consider environmental patterns that constrain habitat and biological variation within and among individual rivers. It is being used throughout Michigan and regionally as a framework for fisheries and water management, conservation planning, and education.
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Boechler, Patricia M. "Supporting Navigation and Learning in Educational Hypermedia." In Encyclopedia of Human Computer Interaction. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-562-7.ch085.

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Computers have become commonplace tools in educational environments and are used to provide both basic and supplemental instruction to students on a variety of topics. Searching for information in hypermedia documents, whether on the Web or through individual educational sites, is a common task in learning activities. Previous research has identified a number of variables that impact how students use electronic documents. Individual differences such as learning style or cognitive style (Andris, 1996; Fitzgerald & Semrau, 1998), prior topic knowledge (Ford & Chen, 2000), level of interest (Lawless & Kulikowich, 1998), and gender (Beasley & Vila, 1992) all influence performance. Additionally, characteristics of the document such as the inherent structure of the material, the linking structure (Korthauer & Koubek, 1994), and the types of navigation tools that accompany the document can affect student performance and behaviour (Boechler & Dawson, 2002; McDonald & Stevenson, 1998, 1999). In short, the effective use of hypermedia documents in educational settings depends on complex interactions between individual skills (e.g., spatial and reading skills) and the features of the document itself.
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Conference papers on the topic "A-priori spatial knowledge"

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Ettaieb, Said, Kamel Hamrouni, and Su Ruan. "Myocardium segmentation using a priori knowledge of shape and a spatial relation." In 2014 International Conference on Multimedia Computing and Systems (ICMCS). IEEE, 2014. http://dx.doi.org/10.1109/icmcs.2014.6911266.

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Mueschke, Nicholas J., and Malcolm J. Andrews. "Investigation of Scalar Measurement Error in Diffusion and Mixing Processes." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60993.

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In variable density, multi-fluid and reacting flows, a quantitative measure of the degree of molecular mixing is crucial to the development of turbulent transfer and mixing models. In a buoyancy-driven miscible mixing layer, we have found that the initial entrainment of unmixed fluid into the mixing layer causes a decrease in the measure of molecular mixedness at the centerplane of the mixing layer. Following the period of initial entrainment, the fluids within the mixing layer exhibits an increase in the degree of molecular mixing. Characterization of this and other mixing processes require scalar measurement devices with an adequate probe volume size. Spatial averaging, which occurs due to the finite probe volume size, can lead to errors in resolving the density or scalar gradients between pockets of unmixed fluids. Given a probe volume size and a priori knowledge of the functional profile of the diffusion layer being measured, we obtain an estimate for the measurement error due to spatial averaging that has occurred and make corrections accordingly. An analytical model for the measure of scalar mixing is developed as a predictor for the growth of scalar gradients in a variable scalar flow. The model is applied to a buoyancy-driven mixing layer with a Prandtl number of 7.
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Shi, C., J. Park, L. Manuel, and M. A. Tognarelli. "A Data-Driven Mode Identification Algorithm for Fatigue Damage Assessment in Instrumented Marine Risers." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-50231.

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A well-established empirical procedure, which we refer to as Weighted Waveform Analysis (WWA), is employed to reconstruct a model riser’s response over its entire length using a limited number of strain measurements. The quality of the response reconstruction is controlled largely by identification of the participating riser response modes (waveforms); hence, mode selection is vital in WWA application. Instead of selecting a set of consecutive riser vibratory modes, we propose a procedure that automatically identifies a set of non-consecutive riser modes that can thus account for higher harmonics in the riser response (at multiplies of the Strouhal frequency). Using temporal data analysis of the discrete time-stamped samples, significant response frequencies are identified on the basis of power spectrum peaks; similarly using spatial data analysis of the sparse non-uniformly sampled data, significant wavenumbers are identified using Lomb-Scargle periodograms. Knowing the riser length, the most important wavenumber is related to a specific mode number; this dominant mode is in turn related to the dominant peak in power spectra based on the temporal data analysis. The riser’s fundamental frequency is estimated as the ratio of the empirically estimated dominant spectral frequency to the dominant mode number. Additional mode numbers are also identified as spectral peak frequencies divided by the fundamental frequency. This mode selection technique is an improvement over similar WWA procedures that rely on a priori knowledge of the risers fundamental frequency or on knowledge of physical properties and assumptions on added mass contributions. At selected target locations, we compare fatigue damage rates, estimated based on the riser response reconstructed using the WWA method with the proposed automated mode selection technique (we refer to this as “improved” WWA) and those based on the “original” WWA method (that relies on a theoretically computed fundamental natural frequency of the riser). In both cases, predicted fatigue damage rates based on the empirical methods and data at various locations (other than the target) are cross-validated against damage rates based directly on measurements at the target location. Results show that the improved WWA method, which empirically estimates the riser’s fundamental natural frequency and automatically selects significant modes of vibration, may be employed to estimate fatigue damage rates quite well from limited strain measurements.
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Kane, S. C., S. Croft, P. McClay, R. Venkataraman, and M. F. Villani. "Relative Performance of a TGS for the Assay of Drummed Waste as Function of Collimator Opening." In The 11th International Conference on Environmental Remediation and Radioactive Waste Management. ASMEDC, 2007. http://dx.doi.org/10.1115/icem2007-7174.

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Improving the safety, accuracy and overall cost effectiveness of the processes and methods used to characterize and handle radioactive waste is an on-going mission for the nuclear industry. An important contributor to this goal is the development of superior non-destructive assay instruments. The Tomographic Gamma Scanner (TGS) is a case in point. The TGS applies low spatial resolution experimental computed tomograghy (CT) linear attenuation coefficient maps with three-dimensional high-energy resolution single photon emission reconstructions. The results are presented as quantitative matrix attenuation corrected images and assay values for gamma-emitting radionuclides. Depending on a number of operational factors, this extends the diversity of waste forms that can be assayed, to a given accuracy, to items containing more heterogeneous matrix distributions and less uniform emission activity distributions. Recent advances have significantly extended the capability to a broader range of matrix density and to a wider dynamic range of surface dose rate. Automated systems sense the operational conditions, including the container type, and configure themselves accordingly. The TGS also provides a flexible data acquisition platform and can be used to perform far-field style measurements, classical segmented gamma scanner measurements, or to implement hybrid methods, such as reconstructions that use a priori knowledge to constrain the image reconstruction or the underlying energy dependence of the attenuation. A single, yet flexible, general purpose instrument of this kind adds several tiers of strategic and tactical value to facilities challenged by a diverse and difficult to assay waste streams. The TGS is still in the early phase of industrial uptake. There are only a small number of general purpose TGS systems operating worldwide, most being configured to automatically select between a few configurations appropriate for routine operations. For special investigations, one may wish to widen the repertoire but there is currently little guidance as to the trade-offs involved. In this work, we address this weakness by studying the performance of a typical TGS arrangement as a function of collimator opening, scan pattern and scan time for a representative selection of simulated waste forms. Our focus is on assessing the impact on the precision and accuracy of the quantitative assay result but we also report the utility of the imaging information in confirming acceptable knowledge about the packages.
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Vennelakanti, Ravigopal, Malarvizhi Sankaranarayanasamy, Ramyar Saeedi, et al. "Multimodal Mobility Framework: Towards Seamless Mobility Experience." In 2021 Joint Rail Conference. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/jrc2021-58377.

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Abstract Mobility is no longer just a necessity for travelers, but choices among several possible routes and transportation modes. Urban passenger rail transport plays an essential role because it is affordable, convenient, safe, and fast. On the other hand, rail lines are limited to high passenger density corridors. Inevitably, rail has to be placed together with different transport modes, forming a multimodal network. However, to enable this integration with other modes of transport, numerous practical problems remain, such as making a smooth transition from the existing siloed, mode specific operational structure towards an interconnected system of transportation modes and business models for a seamless connected journey. The current isolated operational structure lacks a single truth and accurate visibility, which further discourages participation from augmenting transportation modes and leads to the extended reaction time for new technology integration. This research article introduces a Multimodal Mobility (MMM) solution framework that provides a functional interface to integrate and synchronize the railroad operations with other public transit networks (including train-bus-rapid transits) and micro-mobility services. The known approach to addressing the users’ seamless mobility experience entails a centralized, prearranged, a priori knowledge and mechanism for operating intermodal transport systems. In contrast, the method defined in this paper focuses on a market-driven demand-responsive system that allows for dis-intermediation in a network of peer-level transportation modes operations. The framework facilitates blockchain-based decentralized and multi-organizational engagement. The focus here is the role of railroad in the multimodal ecosystem and its performance advancements in this integrated solutions framework. Leveraging a combination of graph analytics and machine learning algorithms, we provide methods to address challenges in encoding spatial and temporal dependencies of multimodal transit networks and handle complex optimization problems such as mixed time window and volume variation for resource allocation and transit operational analytics. This enables operation of different transit modes with varied resolution and flexibility for operational parameters like time, capacity, ridership, revenue management, etc. The analytics enable solutions for recommendations on synchronizing and integrating operations of transportation systems. Further, the network’s decentralization and modular handling enable market-driven co-optimization of operational resources across various transportation modes to ensure seamless transit experience for users.
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6

Yu, Tan, Jingjing Meng, and Junsong Yuan. "Is My Object in This Video? Reconstruction-based Object Search in Videos." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/635.

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This paper addresses the problem of video-level object instance search, which aims to retrieve the videos in the database that contain a given query object instance. Without prior knowledge about "when" and "where" an object of interest may appear in a video, determining "whether" a video contains the target object is computationally prohibitive, as it requires exhaustively matching the query against all possible spatial-temporal locations in each video that an object may appear. To alleviate the computational and memory cost, we propose the Reconstruction-based Object SEarch (ROSE) method.It characterizes a huge corpus of features of possible spatial-temporal locations in the video into the parameters of the reconstruction model. Since the memory cost of storing reconstruction model is much less than that of storing features of possible spatial-temporal locations in the video, the efficiency of the search is significantly boosted. Comprehensive experiments on three benchmark datasets demonstrate the promising performance of the proposed ROSE method.
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7

Schneider, C., M. G. Rose, S. Staudacher, A. Heisler, F. Lippl, and I. Raab. "On the Assessment of Turbine Efficiency From Experimental Data for Low Pressure Turbines at Low Reynolds Numbers." In ASME Turbo Expo 2012: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/gt2012-69435.

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The isentropic efficiency of a turbo machinery device is assessed using a defined control volume. Representative stagnation pressures and temperatures are measured at inlet and exit of the volume. This task is mainly accomplished by radial rake measurements. It is assumed to measure a representative flow quantity for an area with a defined number of circumferentially and radially distributed probes. The assumption incorporates biases into the assessed efficiency. The sensitivities of a radial rake measurement at the exit of a two-stage turbine to the unresolved area, the spatial resolution, and the averaging method are studied at a low Reynolds number working point (ReV1 = 75000). A method of analysis has been developed to assess the changes in turbine efficiency. For the case studied, the results show that the applied averaging method represents a minor contributor to the overall uncertainty. The effects of the spatial resolution and the unresolved area constitute up to ∼0.6% of turbine efficiency. Methods are presented to reduce the bias of the unresolved area significantly. The circumferential and the radial direction are observed separately which allows drawing conclusions for the design of rake measurement systems. The method of analysis is based on CFD completely, and thus it can be used to optimize or to design rake measurement systems prior to turbine testing. Additionally, the knowledge gained of the remaining biases can be used for an improved uncertainty analysis.
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Guo, Shangwei, Tianwei Zhang, Han Qiu, Yi Zeng, Tao Xiang, and Yang Liu. "Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/500.

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Watermarking has become the tendency in protecting the intellectual property of DNN models. Recent works, from the adversary's perspective, attempted to subvert watermarking mechanisms by designing watermark removal attacks. However, these attacks mainly adopted sophisticated fine-tuning techniques, which have certain fatal drawbacks or unrealistic assumptions. In this paper, we propose a novel watermark removal attack from a different perspective. Instead of just fine-tuning the watermarked models, we design a simple yet powerful transformation algorithm by combining imperceptible pattern embedding and spatial-level transformations, which can effectively and blindly destroy the memorization of watermarked models to the watermark samples. We also introduce a lightweight fine-tuning strategy to preserve the model performance. Our solution requires much less resource or knowledge about the watermarking scheme than prior works. Extensive experimental results indicate that our attack can bypass state-of-the-art watermarking solutions with very high success rates. Based on our attack, we propose watermark augmentation techniques to enhance the robustness of existing watermarks.
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Lin, Weixuan, and Di Wu. "Residential Electric Load Forecasting via Attentive Transfer of Graph Neural Networks." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/374.

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An accurate short-term electric load forecasting is critical for modern electric power systems' safe and economical operation. Electric load forecasting can be formulated as a multi-variate time series problem. Residential houses in the same neighborhood may be affected by similar factors and share some latent spatial dependencies. However, most of the existing works on electric load forecasting fail to explore such dependencies. In recent years, graph neural networks (GNNs) have shown impressive success in modeling such dependencies. However, such GNN based models usually would require a large amount of training data. We may have a minimal amount of data available to train a reliable forecasting model for houses in a new neighborhood area. At the same time, we may have a large amount of historical data collected from other houses that can be leveraged to improve the new neighborhood's prediction performance. In this paper, we propose an attentive transfer learning-based GNN model that can utilize the learned prior knowledge to improve the learning process in a new area. The transfer process is achieved by an attention network, which generically avoids negative transfer by leveraging knowledge from multiple sources. Extensive experiments have been conducted on real-world data sets. Results have shown that the proposed framework can consistently outperform baseline models in different areas.
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Whitney, Jon, Harry Dorn, Chris Rylander, Tom Campbell, David Geohegan, and Marissa Nichole Rylander. "Spatiotemporal Temperature and Cell Viability Measurement Following Laser Therapy in Combination With Carbon Nanohorns." In ASME 2010 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2010. http://dx.doi.org/10.1115/sbc2010-19619.

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Cancer remains one of the most deadly diseases today. Laser-induced photothermal therapy can provide a minimally invasive treatment alternative to surgical resection. The selectivity and effectiveness of laser therapy can be greatly enhanced when photoabsorbing nanoparticles such as nanoshells, single walled carbon nanotubes, multi-walled carbon nanotubes, or single wall carbon nanohorns (SWNHs) are introduced into the tissue. Prior studies have effectively used SWNHs combined with near infrared (NIR) laser light to target and destroy microbes [1]. We have previously reported increased tumor cell destruction when SWNHs were used in combination with laser therapy. The present work provides more extensive characterization of cell viability in response to laser therapy alone or in combination with SWNHs. Furthermore, the spatiotemporal temperature and cell viability in vitro in response to combinatorial SWNH-mediated laser therapies is determined using infrared thermometry and a novel viability algorithm, respectively. These new measurements will be critical for planning SWNH-mediated laser treatments where knowledge of the geometric distribution of temperature and cell death are critical to achieving the goal of selectively eliminating a tumor with specific spatial margins with minimal damage to surrounding healthy tissue.
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