Journal articles: 'Time-map'

1

Govedar, Nina. "Designing a Time Map." Филолог – часопис за језик књижевност и културу, no. 16 (December 30, 2017): 367–70. http://dx.doi.org/10.21618/fil1716367g.

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WILLEBOORDSE, FREDERICK H. "TIME-DELAYED MAP PHENOMENOLOGICAL EQUIVALENCY WITH A COUPLED MAP LATTICE." International Journal of Bifurcation and Chaos 02, no. 03 (September 1992): 721–25. http://dx.doi.org/10.1142/s0218127492000847.

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It is shown that, what so far were considered to be purely spatiotemporal, phenomena in a model for a Coupled Map Lattice can be obtained through a newly introduced Time-Delayed Map with only one chaotic element, thereby effectively eliminating the spatial dimension.

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3

Shams, Ahmed. "Time for a New Sinai Map?" Cartographica: The International Journal for Geographic Information and Geovisualization 56, no. 3 (September 29, 2021): 208–25. http://dx.doi.org/10.3138/cart-2020-0018.

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Il est temps qu’une nouvelle carte vienne compléter le relevé britannique du Sinaï, inachevé depuis 150 ans. À la fin du 19e siècle et au début du 20e siècle, le passage de l’individualité à institutionnalisation (chez les autorités responsables des levés) et la transformation du sud de l’histoire (biblique) en nord géopolitique (champ de bataille) conduisent à la détérioration des données cartographiques. Ces deux faits, révélés par le groupe Sinai Peninsula Research (SPR) à la suite de vingt années de travail de terrain, soulèvent une question cruciale sur la réalité des cartes postcoloniales au Moyen-Orient. Ils contredisent, en effet, le présupposé géopolitique selon lequel la péninsule est une région bien cartographiée, du fait de la production intensive de cartes par différentes autorités coloniales (pendant leur mandat) et postcoloniales (nationales : britanniques, étatsuniennes, soviétiques, israéliennes et égyptiennes). En fait, peu de ces cartes sont fondées sur des levés de terrain, ce qui a des conséquences à plusieurs niveaux, dans la mesure où l’absence de compatibilité entre les données cartographiques ne permet pas de prendre des décisions éclairées. La gouvernance, l’usage des terres et la propriété sont les questions les plus problématiques, car elles ont des conséquences sur tous les secteurs, toutes les industries et toutes les disciplines scientifiques.

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Georgoulas, Christos, Leonidas Kotoulas, Georgios Ch Sirakoulis, Ioannis Andreadis, and Antonios Gasteratos. "Real-time disparity map computation module." Microprocessors and Microsystems 32, no. 3 (May 2008): 159–70. http://dx.doi.org/10.1016/j.micpro.2007.10.002.

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Davies, J. J., A. R. Beresford, and A. Hopper. "Scalable, Distributed, Real-Time Map Generation." IEEE Pervasive Computing 5, no. 4 (October 2006): 47–54. http://dx.doi.org/10.1109/mprv.2006.83.

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6

Deshmukh, Sharief. "A Harmonic Map of Space-Time." International Journal of Theoretical Physics 50, no. 6 (February 8, 2011): 1837–45. http://dx.doi.org/10.1007/s10773-011-0698-x.

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7

Moustafa, Khaled. "MAP kinases nomenclature: Time for curation." Plant Signaling & Behavior 12, no. 12 (December 2, 2017): e1388974. http://dx.doi.org/10.1080/15592324.2017.1388974.

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HIROSE, Shigeo, Kazuhiro YOSHIDA, and Yasumasa TORATANI. "The study of map realization system. (Consideration on real-time map generation)." Journal of the Robotics Society of Japan 6, no. 1 (1988): 14–25. http://dx.doi.org/10.7210/jrsj.6.14.

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9

Pontius, Robert Gilmore, and Christopher D. Lippitt. "Can Error Explain Map Differences Over Time?" Cartography and Geographic Information Science 33, no. 2 (January 2006): 159–71. http://dx.doi.org/10.1559/152304006777681706.

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10

Habibi, Roya, and Ali Asghar Alesheikh. "A time-driven symbology for map visualization." Abstracts of the ICA 5 (September 14, 2022): 1–2. http://dx.doi.org/10.5194/ica-abs-5-125-2022.

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11

Rutten, Eric, and Joachim Hertzberg. "Temporal Planner = Nonlinear Planner + Time Map Management." AI Communications 6, no. 1 (1993): 18–26. http://dx.doi.org/10.3233/aic-1993-6102.

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12

Xu, Mengxi, Junlin Qiu, Bin Zhu, and Zhe Chen. "Time–Frequency Map-Based Abnormal Signal Detection." IEEE Access 7 (2019): 172350–61. http://dx.doi.org/10.1109/access.2019.2956264.

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13

Antoniou, I. "The time operator of the cusp map." Chaos, Solitons & Fractals 12, no. 9 (July 2001): 1619–27. http://dx.doi.org/10.1016/s0960-0779(00)00170-3.

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14

Leonel, Edson D., J. Kamphorst Leal da Silva, and S. Oliffson Kamphorst. "Transients in a time-dependent logistic map." Physica A: Statistical Mechanics and its Applications 295, no. 1-2 (June 2001): 280–84. http://dx.doi.org/10.1016/s0378-4371(01)00088-7.

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15

Shah-Hosseini, Hamed. "Binary tree time adaptive self-organizing map." Neurocomputing 74, no. 11 (May 2011): 1823–39. http://dx.doi.org/10.1016/j.neucom.2010.07.037.

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16

Sarlin, Peter, and Zhiyuan Yao. "Clustering of the Self-Organizing Time Map." Neurocomputing 121 (December 2013): 317–27. http://dx.doi.org/10.1016/j.neucom.2013.04.007.

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17

Smoller, J., and A. Wasserman. "On the monotonicity of the time-map." Journal of Differential Equations 77, no. 2 (February 1989): 287–303. http://dx.doi.org/10.1016/0022-0396(89)90145-9.

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18

Borgonovi, F., I. Guarneri, and P. Sempio. "Long-time decay properties of Kepler map." Il Nuovo Cimento B Series 11 102, no. 2 (August 1988): 151–58. http://dx.doi.org/10.1007/bf02726564.

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19

Zhang, Qing-nian, and Lars Harrie. "Real-time map labelling for mobile applications." Computers, Environment and Urban Systems 30, no. 6 (November 2006): 773–83. http://dx.doi.org/10.1016/j.compenvurbsys.2006.02.004.

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20

Choi, Bong Dae, Bara Kim, and Dongbi Zhu. "MAP/M/cQueue with Constant Impatient Time." Mathematics of Operations Research 29, no. 2 (May 2004): 309–25. http://dx.doi.org/10.1287/moor.1030.0081.

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21

Adamowicz, Tomasz, and Philip Korman. "Remarks on time map for quasilinear equations." Journal of Mathematical Analysis and Applications 376, no. 2 (April 2011): 686–95. http://dx.doi.org/10.1016/j.jmaa.2010.11.010.

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22

Willeboordse, Frederick H. "Time-Delayed Map extension to n-dimensions." Chaos, Solitons & Fractals 2, no. 4 (July 1992): 411–20. http://dx.doi.org/10.1016/0960-0779(92)90016-g.

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23

이성호 and KIMChangHun. "Real-time Soft Shadowing of Dynamic Height Map Using a Shadow Height Map." Journal of the Korea Computer Graphics Society 14, no. 1 (March 2008): 11–16. http://dx.doi.org/10.15701/kcgs.2008.14.1.11.

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24

Hirose, Shigeo, Kazuhiro Yoshida, and Yasumasa Toratani. "The study of a map realization system: consideration of real-time map generation." Advanced Robotics 4, no. 3 (January 1989): 223–42. http://dx.doi.org/10.1163/156855390x00279.

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25

Wiemer, Jan C. "The Time-Organized Map Algorithm: Extending the Self-Organizing Map to Spatiotemporal Signals." Neural Computation 15, no. 5 (May 1, 2003): 1143–71. http://dx.doi.org/10.1162/089976603765202695.

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The new time-organized map (TOM) is presented for a better understanding of the self-organization and geometric structure of cortical signal representations. The algorithm extends the common self-organizing map (SOM) from the processing of purely spatial signals to the processing of spatiotemporal signals. The main additional idea of the TOM compared with the SOM is the functionally reasonable transfer of temporal signal distances into spatial signal distances in topographic neural representations. This is achieved by neural dynamics of propagating waves, allowing current and former signals to interact spatiotemporally in the neural network. Within a biologically plausible framework, the TOM algorithm (1) reveals how dynamic neural networks can self-organize to embed spatial signals in temporal context in order to realize functional meaningful invariances, (2) predicts time-organized representational structures in cortical areas representing signals with systematic temporal relation, and (3) suggests that the strength with which signals interact in the cortex determines the type of signal topology realized in topographic maps (e.g., spatially or temporally defined signal topology). Moreover, the TOM algorithm supports the explanation of topographic reorganizations based on time-to-space transformations (Wiemer, Spengler, Joublin, Stagge, & Wacquant, 2000).

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26

Beirami, A., H. Nejati, and W. H. Ali. "Zigzag map: a variability-aware discrete-time chaotic-map truly random number generator." Electronics Letters 48, no. 24 (November 22, 2012): 1537–38. http://dx.doi.org/10.1049/el.2012.2762.

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27

Xie, Wen-Jie, Rui-Qi Han, and Wei-Xing Zhou. "Time series classification based on triadic time series motifs." International Journal of Modern Physics B 33, no. 21 (August 20, 2019): 1950237. http://dx.doi.org/10.1142/s0217979219502370.

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It is of great significance to identify the characteristics of time series to quantify their similarity and classify different classes of time series. We define six types of triadic time-series motifs and investigate the motif occurrence profiles extracted from the time series. Based on triadic time series motif profiles, we further propose to estimate the similarity coefficients between different time series and classify these time series with high accuracy. We validate the method with time series generated from nonlinear dynamic systems (logistic map, chaotic logistic map, chaotic Henon map, chaotic Ikeda map, hyperchaotic generalized Henon map and hyperchaotic folded-tower map) and retrieved from the UCR Time Series Classification Archive. Our analysis shows that the proposed triadic time series motif analysis performs better than the classic dynamic time wrapping method in classifying time series for certain datasets investigated in this work.

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28

Laskowski-Jones, Linda. "When it is time for a new map." Nursing 51, no. 6 (June 2021): 6. http://dx.doi.org/10.1097/01.nurse.0000751692.67724.fd.

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29

Zhao, Haifeng, and Stephan Winter. "A Time-Aware Routing Map for Indoor Evacuation." Sensors 16, no. 1 (January 18, 2016): 112. http://dx.doi.org/10.3390/s16010112.

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30

ÇIKCI, Sevgi, and Ayşe ERZAN. "Scaling in Time Series from Coupled Map Lattices." Turkish Journal of Physics 21, no. 1 (January 1, 1997): 150. http://dx.doi.org/10.55730/1300-0101.2451.

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31

Kusak, H., and A. Caliskan. "The parameter map and velocity on time scales." Applied Mathematical Sciences 7 (2013): 5279–86. http://dx.doi.org/10.12988/ams.2013.37356.

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32

Kumar, Rahul, Noémie Globus, David Eichler, and Martin Pohl. "Time variability of TeV cosmic ray sky map." Monthly Notices of the Royal Astronomical Society 483, no. 1 (November 21, 2018): 896–900. http://dx.doi.org/10.1093/mnras/sty3141.

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33

Baguenard, B., J. B. Wills, F. Pagliarulo, F. Lépine, B. Climen, M. Barbaire, C. Clavier, M. A. Lebeault, and C. Bordas. "Velocity-map imaging electron spectrometer with time resolution." Review of Scientific Instruments 75, no. 2 (February 2004): 324–28. http://dx.doi.org/10.1063/1.1642749.

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34

Shah-Hosseini, H., and R. Safabakhsh. "TASOM: a new time adaptive self-organizing map." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 33, no. 2 (April 2003): 271–82. http://dx.doi.org/10.1109/tsmcb.2003.810442.

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35

Kang, Yeonsik, Derek S. Caveney, and J. Karl Hedrick. "Real-time Obstacle Map Building with Target Tracking." Journal of Aerospace Computing, Information, and Communication 5, no. 5 (May 2008): 120–34. http://dx.doi.org/10.2514/1.29210.

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36

Mohamed, Reham, Heba Aly, and Moustafa Youssef. "Accurate Real-time Map Matching for Challenging Environments." IEEE Transactions on Intelligent Transportation Systems 18, no. 4 (April 2017): 847–57. http://dx.doi.org/10.1109/tits.2016.2591958.

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37

Antoniou, I., and S. A. Shkarin. "Resonances and time operator for the cusp map." Chaos, Solitons & Fractals 17, no. 2-3 (July 2003): 445–48. http://dx.doi.org/10.1016/s0960-0779(02)00386-7.

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38

Zhao, G. F., and M. G. Rodd. "MAP for real-time distributed computer control systems." IFAC Proceedings Volumes 25, no. 26 (September 1992): 89–94. http://dx.doi.org/10.1016/b978-0-08-041708-0.50024-6.

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39

Fukuda, Kanao, and Masanori Ueki. "Friction Force-Time Map in Repeated Sliding Test." Bulletin of the Japan Institute of Metals 32, no. 6 (1993): 435–37. http://dx.doi.org/10.2320/materia1962.32.435.

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40

Ahern, Patrick, Franc Forstneric, and Dror Varolin. "Flows on C2 with polynomial time one map." Complex Variables, Theory and Application: An International Journal 29, no. 4 (May 1996): 363–66. http://dx.doi.org/10.1080/17476939608814903.

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41

Dambrosio, Walter. "Time-Map Techniques for Some Boundary Value Problems." Rocky Mountain Journal of Mathematics 28, no. 3 (September 1998): 885–926. http://dx.doi.org/10.1216/rmjm/1181071745.

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42

Radons, G., G. C. Hartmann, H. H. Diebner, and O. E. Rossler. "Staircase baker's map generates flaring-type time series." Discrete Dynamics in Nature and Society 5, no. 2 (2000): 107–20. http://dx.doi.org/10.1155/s1026022600000467.

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The baker’s map, invented by Eberhard Hopf in 1937, is an intuitively accesible, two-dimensional chaos-generating discrete dynamical system. This map, which describes the transformation of an idealized two-dimensional dough by stretching, cutting and piling, is non-dissipative. Nevertheless the “x” variable is identical with the dissipative, one-dimensional Bernoulli-shift-generating map. The generalization proposed here takes up ideas of Yaacov Sinai in a modified form. It has a staircase-like shape, with every next step half as high as the preceding one. Each pair of neighboring elements exchanges an equal volume (area) during every iteration step in a scaled manner. Since the density of iterated points is constant, the thin tail (to the right, say) is visited only exponentially rarely. This observation already explains the map's main qualitative behavior: The “x” variable shows “flares”. The time series of this variable is closely analogous to that of a flaring-type dissipative dynamical system – like those recently described in an abstract economic model. An initial point starting its journey in the tale (or “antenna”, if we tilt the map upwards by 90 degrees) is predictably attracted by the broad left hand (bottom) part, in order to only very rarely venture out again to the tip. Yet whenever it does so, it thereby creates, with the top of a flare, a new “far-from-equilibrium” initial condition, in this reversible system. The system therefore qualifies as a discrete analogue to a far-from-equilibrium multiparticle Hamiltonian system. The height of the flare hereby corresponds to the momentary height of theHfunction of a gas. An observable which is even more closely related to the momentary negative entropy was recently described. Dependent on the numerical accuracy chosen, “Poincaré cycles” of two different types (periodic and nonperiodic) can be observed for the first time.

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43

Dittes, F. M., E. Doron, and U. Smilansky. "Long-time behavior of the semiclassical baker’s map." Physical Review E 49, no. 2 (February 1, 1994): R963—R966. http://dx.doi.org/10.1103/physreve.49.r963.

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44

SHIN, B. S., D. R. OH, and D. KANG. "Real-Time Point-Based Rendering Using Visibility Map." IEICE Transactions on Information and Systems E91-D, no. 1 (January 1, 2008): 124–31. http://dx.doi.org/10.1093/ietisy/e91-d.1.124.

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45

Graham, Ian D., Jo Logan, Margaret B. Harrison, Sharon E. Straus, Jacqueline Tetroe, Wenda Caswell, and Nicole Robinson. "Lost in knowledge translation: Time for a map?" Journal of Continuing Education in the Health Professions 26, no. 1 (2006): 13–24. http://dx.doi.org/10.1002/chp.47.

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46

Alford, Fred. "The Scattering Map on Oppenheimer–Snyder Space-Time." Annales Henri Poincaré 21, no. 6 (March 13, 2020): 2031–92. http://dx.doi.org/10.1007/s00023-020-00905-5.

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47

Iqbal, Jameel, and Mone Zaidi. "TNF-induced MAP kinase activation oscillates in time." Biochemical and Biophysical Research Communications 371, no. 4 (July 2008): 906–11. http://dx.doi.org/10.1016/j.bbrc.2008.03.113.

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48

Pire, Taihú, Rodrigo Baravalle, Ariel D'Alessandro, and Javier Civera. "Real-time dense map fusion for stereo SLAM." Robotica 36, no. 10 (June 20, 2018): 1510–26. http://dx.doi.org/10.1017/s0263574718000528.

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SUMMARYA robot should be able to estimate an accurate and dense 3D model of its environment (a map), along with its pose relative to it, all of it in real time, in order to be able to navigate autonomously without collisions.As the robot moves from its starting position and the estimated map grows, the computational and memory footprint of a dense 3D map increases and might exceed the robot capabilities in a short time. However, a global map is still needed to maintain its consistency and plan for distant goals, possibly out of the robot field of view.In this work, we address such problem by proposing a real-time stereo mapping pipeline, feasible for standard CPUs, which is locally dense and globally sparse and accurate. Our algorithm is based on a graph relating poses and salient visual points, in order to maintain a long-term accuracy with a small cost. Within such framework, we propose an efficient dense fusion of several stereo depths in the locality of the current robot pose.We evaluate the performance and the accuracy of our algorithm in the public datasets of Tsukuba and KITTI, and demonstrate that it outperforms single-view stereo depth. We release the code as open-source, in order to facilitate the system use and comparisons.

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49

Fränti, Pasi, Eugene Ageenko, Pavel Kopylov, Sami Gröhn, and Florian Berger. "Compression of map images for real-time applications." Image and Vision Computing 22, no. 13 (November 2004): 1105–15. http://dx.doi.org/10.1016/j.imavis.2004.05.009.

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50

Zaim, S. "Noncommutative Space-Time of the Relativistic Equations with a Coulomb Potential Using Seiberg-Witten Map." Zurnal matematiceskoj fiziki, analiza, geometrii 12, no. 4 (December 25, 2016): 359–73. http://dx.doi.org/10.15407/mag12.04.359.

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Journal articles on the topic 'Time-map'

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