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The transformation technique for spatial objects revisited
[chapter]
1993
Lecture Notes in Computer Science
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_The basic idea is to transform the bounding boxes into points in higher dimensional space in order to apply data structures for points which are better understood and easier to handle. ...
The transformation technique is one of the earliest approaches for storing a set of bounding boxes of arbitrary geometric objects such that insertion, deletion and proximity queries can be carried out ...
The idea is to map the bounding boxes of geometric objects into points in higher dimensional space in order to directly reuse well-understood point data structures. ...
doi:10.1007/3-540-56869-7_5
fatcat:wtf6235hybb3rgusfh35l2xuti
Towards real-time middleware for vehicular ad hoc networks
2004
Proceedings of the first ACM workshop on Vehicular ad hoc networks - VANET '04
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This Space-Elastic model is the first to directly address adaptation in the space domain to maintain real-time guarantees. ...
The dynamics of a VANET impact the real-time guarantees available within the proximity bound. In this case, we dynamically adapt the proximity bound to maintain the required real-time guarantees. ...
The PMRR, attempts to discover and maintain real-time constrained routes within a proximity-bound, e.g., as specified by the Space-Elastic Model, utilizing the cellular structure of TBMAC coupled with ...
doi:10.1145/1023875.1023894
dblp:conf/mobicom/HughesMCC04
fatcat:sygf5ulfyjed7b3j43vkre2sfa
Three-dimensional MR Cholangiopancreatography in a Breath Hold with Sparsity-based Reconstruction of Highly Undersampled Data
2016
Radiology
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Overall image quality scores were higher for BH SPARSE-SPACE than for RT SPACE images for both readers for the proximal, middle, and distal pancreatic duct, but the difference was not statistically significant ...
BH SPACE images were reconstructed by enforcing joint multicoil sparsity in the wavelet domain (SPARSE-SPACE). ...
Results
Acquisition Time
Pancreatic Duct Overall image quality scores were higher for BH SPARSE-SPACE than for RT SPACE in the proximal, middle, and Note. ...
doi:10.1148/radiol.2016151935
pmid:26982678
pmcid:PMC4949145
fatcat:dvgpz32aundy7gd3zpwzez4zva
Effect of shape and coating of a subretinal prosthesis on its integration with the retina
2009
Experimental Eye Research
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A trans-scleral implantation technique was developed to place microfabricated structures in the subretinal space of RCS rats. ...
Flat implants coated with parylene and iridium oxide were generally well tolerated in the subretinal space, inducing only a mild gliotic response. ...
Functional restoration of the central vision in these patients will likely require a higher resolution implant. ...
doi:10.1016/j.exer.2008.09.018
pmid:18955050
fatcat:hptl7bfesfanfilmq7rlkddx2m
Establishing Multi-Criteria Context Relations Supporting Ubiquitous Immersive Participation
2013
International Journal of Ad Hoc, Sensor and Ubiquitous Computing
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This in turn presupposes the existence of models for establishing and maintaining context relations. ...
Additionally, wederive a measure of context proximity that considers the situation, attributes, relations, accuracy and heterogeneity of both the underlying information and the vast array of requirements ...
The Earth Movers distance evaluates the similarity between two multi-dimensional distributions in some feature space, in our case the activity space. ...
doi:10.5121/ijasuc.2013.4205
fatcat:xvzvq5hidrgatnxowb4xoji5ye
A self-organizing principle for learning nonlinear manifolds
2002
Proceedings of the National Academy of Sciences of the United States of America
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Select two points, i and j, at random, retrieve (or evaluate) their proximity in the input space, r ij , and compute their Euclidean distance on the D-dimensional map, d ij ϭ ʈy i Ϫ y j ʈ. 4. ...
The embedding is carried out by minimizing the stress function, where r ij is the input proximity between the ith and jth points, d ij is their Euclidean distance in the low-dimensional space, f(d ij , ...
The Euclidean distance in the resulting 26-dimensional principal component space was used as a proximity measure between two compounds. ...
doi:10.1073/pnas.242424399
pmid:12444256
pmcid:PMC138530
fatcat:a777f2eshvac3kj3ujme77op6m
Page 856 of Psychological Abstracts Vol. 55, Issue 5
[page]
1976
Psychological Abstracts
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The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
Horn’s Leistungspriifsystem (1962) to determine whether it reflects ability to visualize
EXPERIMENTAL PSYCHOLOGY (HUMAN)
problems in 2-dimensional space or, as maintained by Horn, in 3-dimensional space ...
Space-average luminance was held constant. RT increased with the higher spatial frequency and was intermediate in value for the combination stimulus at each level of contrast. ...
Wideband electrical modeling of large three-dimensional interconnects using accelerated generation of partial impedances with cylindrical conduction mode basis functions
2008
2008 IEEE MTT-S International Microwave Symposium Digest
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From the modeling examples of throughhole vias and bonding wires in stacked Ie's, the proposed method is verified for application to real three-dimensional interconnects. ...
For wideband modeling of large and complicated three-dimensional interconnects, this paper proposes an efficiency improvement in solving electric field integral equation with cylindrical conduction mode ...
Figure 3 shows the relative error of the coupling coefficients with adding higher-order proximity effect modes in two-parallel-conductor problem. ...
doi:10.1109/mwsym.2008.4633300
fatcat:mc244qgxpnhnti2q5sgnszha6i
FSPE: Visualization of Hyperspectral Imagery Using Faithful Stochastic Proximity Embedding
2015
IEEE Geoscience and Remote Sensing Letters
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We propose faithful stochastic proximity embedding (FSPE), which is a scalable and nonlinear dimensionality reduction method. ...
FSPE outperforms the state-of-art methods by at least 12% on average and up to 25% in the qualitative measure. ...
The quality of the dimensionality reduction is measured with a correlation metric between interpoint distances in the input data space and the projected space [1] , [9] ; the higher the correlation, ...
doi:10.1109/lgrs.2014.2324631
fatcat:ounqfmvqdnh6dlujttpny5wc34
Information-theoretical label embeddings for large-scale image classification
[article]
2016
arXiv
pre-print
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Our method consists in embedding high-dimensional sparse labels onto a lower-dimensional dense sphere of unit-normed vectors, and treating the classification problem as a cosine proximity regression problem ...
We test our method on a dataset of 300 million high-resolution images with 17,000 labels, where it yields considerably faster convergence, as well as a 7% higher mean average precision compared to logistic ...
For this reason, the highest achievable MAP@100 in our experiments is higher than 1 (typical values are in the 5-7 range). ...
arXiv:1607.05691v1
fatcat:xvk6nhfqgne2zf4p5crrkk26n4
Proximity-based visualization of movement trace data
2009
2009 IEEE Symposium on Visual Analytics Science and Technology
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We present proximity-based visualization as a novel approach to the visualization of movement traces in an abstract space rather than the given spatial layout. ...
The increasing availability of motion sensors and video cameras in living spaces has made possible the analysis of motion patterns and collective behavior in a number of situations. ...
ACKNOWLEDGEMENTS This research was supported in part by the U.S. National Science Foundation through grants CCF-0938114, CCF-0808896 and CCF-0811422 and by Hewlett-Packard Laboratories. ...
doi:10.1109/vast.2009.5332593
dblp:conf/ieeevast/CrnovrsaninMCM09
fatcat:q3i6bew6g5b3je2cmgxyw6ji7a
Design and printing of a coplanar capacitive proximity sensor to detect the gap between dielectric foils edges
2022
Sensors and Actuators A-Physical
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Moreover, the optimum sensor performance is observed for the foil edge gap positioned centered with the sensing electrodes and the target foil remaining in contact with its surface. ...
The capacitive proximity sensor with optimum set of parameters is fabricated on a polyimide foil by the inkjet of the sensing electrodes. ...
Amongst the dimensional parameters, the width of the electrodes and the spacing between them has a higher influence on the sensitivity, whereas the edge gap detection range was mainly affected by the electrode ...
doi:10.1016/j.sna.2022.113424
fatcat:rso634mg7fcjfk4vfvltft2ggm
Dynamic security border identification using enhanced particle swarm optimization
2002
IEEE Transactions on Power Systems
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The high-dimensional nature of power systems' operating space makes this difficult. ...
However, new multiagent search techniques such as particle swarm optimization have shown great promise in handling high-dimensional nonlinear problems. ...
For the speed of PSO convergence, it should be noted that a higher-dimensional feature space causes both slower convergence and decreased accuracy. ...
doi:10.1109/tpwrs.2002.800942
fatcat:stknrxstfbeulfikoez6p5am5i
Dynamic Security Border Identification Using Enhanced Particle Swarm Optimization
2002
IEEE Power Engineering Review
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The high-dimensional nature of power systems' operating space makes this difficult. ...
However, new multiagent search techniques such as particle swarm optimization have shown great promise in handling high-dimensional nonlinear problems. ...
For the speed of PSO convergence, it should be noted that a higher-dimensional feature space causes both slower convergence and decreased accuracy. ...
doi:10.1109/mper.2002.4312295
fatcat:h33jhtspibge3kjsigxw3xwlxm
Graph Force Learning
[article]
2021
arXiv
pre-print
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Unfortunately, current studies fail to fully preserve the structural information in the feature space due to random negative sampling strategy during training. ...
Recently, increasing attention has been paid on network feature learning, which could map discrete features to continued space. ...
In the feature space, the distance between nodes approximates to the real distribution of the original space, maintaining first-order proximity, second-order proximity or high-order proximity. ...
arXiv:2103.04344v1
fatcat:yfywxe2nq5eqzasok5pmwbg2ry
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