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Journal articles on the topic 'Range problem'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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1

Choi, Woosung, Soon-Young Jung, Jaehwa Chung, Kyeong-Seok Hyun, and Kinam Park. "Scalable Algorithms for Maximizing Spatiotemporal Range Sum and Range Sum Change in Spatiotemporal Datasets." Electronics 9, no. 3 (2020): 514. http://dx.doi.org/10.3390/electronics9030514.

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In this paper, we introduce the three-dimensional Maximum Range-Sum (3D MaxRS) problem and the Maximum Spatiotemporal Range-Sum Change (MaxStRSC) problem. The 3D MaxRS problem tries to find the 3D range where the sum of weights across all objects inside is maximized, and the MaxStRSC problem tries to find the spatiotemporal range where the sum of weights across all objects inside is maximally increased. The goal of this paper is to provide efficient methods for data analysts to find interesting spatiotemporal regions in a large historical spatiotemporal dataset by addressing two problems. We p

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2

Kwon Kim, Sung. "The range co-minima problem." Information Processing Letters 49, no. 3 (1994): 117–21. http://dx.doi.org/10.1016/0020-0190(94)90087-6.

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3

Bebiano, N., J. da Providência, A. Nata, and J. P. da Providência. "An inverse indefinite numerical range problem." Linear Algebra and its Applications 470 (April 2015): 200–215. http://dx.doi.org/10.1016/j.laa.2014.07.038.

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4

Takaoka, Tadao. "The Reverse Problem of Range Query." Electronic Notes in Theoretical Computer Science 78 (April 2003): 281–92. http://dx.doi.org/10.1016/s1571-0661(04)81018-1.

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5

Lim, Andrew. "Offset range problem for two blocks." Journal of Information and Optimization Sciences 18, no. 1 (1997): 183–87. http://dx.doi.org/10.1080/02522667.1997.10699323.

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6

Bender, Michael A., Rezaul A. Chowdhury, Pramod Ganapathi, Samuel McCauley, and Yuan Tang. "The range 1 query (R1Q) problem." Theoretical Computer Science 743 (September 2018): 130–47. http://dx.doi.org/10.1016/j.tcs.2015.12.040.

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7

Thompson, Robert C. "Research problem the matrix numerical range." Linear and Multilinear Algebra 21, no. 3 (1987): 321–23. http://dx.doi.org/10.1080/03081088708817807.

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8

Yu, Vincent F., Panca Jodiawan, Yi-Hsuan Ho, and Shih-Wei Lin. "Location-Routing Problem With Demand Range." IEEE Access 7 (2019): 149142–55. http://dx.doi.org/10.1109/access.2019.2946219.

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9

Davies, Simon, Christopher Bauer, Peter Barker, and Ray Freeman. "The dynamic range problem in NMR." Journal of Magnetic Resonance (1969) 64, no. 1 (1985): 155–59. http://dx.doi.org/10.1016/0022-2364(85)90045-9.

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10

Wang, Xiao Dong, and Jun Tian. "Efficient Data Structures for Range Selections Problem." Advanced Materials Research 756-759 (September 2013): 1387–91. http://dx.doi.org/10.4028/www.scientific.net/amr.756-759.1387.

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Building an efficient data structure for range selection problems is considered. While there are several theoretical solutions to the problem, only a few have been tried out, and there is little idea on how the others would perform. The computation model used in this paper is the RAM model with word-size . Our data structure is a practical linear space data structure that supports range selection queries in time with preprocessing time.

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11

D’Ambrosio, C., M. Gentili, and R. Cerulli. "The optimal value range problem for the Interval (immune) Transportation Problem." Omega 95 (September 2020): 102059. http://dx.doi.org/10.1016/j.omega.2019.04.002.

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12

Davoodi, Pooya, Gonzalo Navarro, Rajeev Raman, and S. Srinivasa Rao. "Encoding range minima and range top-2 queries." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 372, no. 2016 (2014): 20130131. http://dx.doi.org/10.1098/rsta.2013.0131.

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We consider the problem of encoding range minimum queries (RMQs): given an array A [1.. n ] of distinct totally ordered values, to pre-process A and create a data structure that can answer the query RMQ( i , j ), which returns the index containing the smallest element in A [ i .. j ], without access to the array A at query time. We give a data structure whose space usage is 2 n + o ( n ) bits, which is asymptotically optimal for worst-case data, and answers RMQs in O (1) worst-case time. This matches the previous result of Fischer and Heun, but is obtained in a more natural way. Furthermore, o

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13

Han, Bing, Jimmy Leblet, and Gwendal Simon. "Query range problem in wireless sensor networks." IEEE Communications Letters 13, no. 1 (2009): 55–57. http://dx.doi.org/10.1109/lcomm.2009.081546.

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14

Fialkow, Lawrence A. "The range inclusion problem for elementary operators." Michigan Mathematical Journal 34, no. 3 (1987): 451–59. http://dx.doi.org/10.1307/mmj/1029003624.

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15

Andrievskii, Vladimir. "The maximal range problem for a quasidisk." Journal of Approximation Theory 123, no. 1 (2003): 52–67. http://dx.doi.org/10.1016/s0021-9045(03)00071-6.

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16

YAGI, Toshiro, Masao ARAKAWA, Hirotaka NAKAYAMA, and Hiroshi ISHIKAWA. "Adaptive Range Genetic Algorithms for Scheduling Problem." Proceedings of Design & Systems Conference 2002.12 (2002): 119–22. http://dx.doi.org/10.1299/jsmedsd.2002.12.119.

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17

Campbell, Ann Melissa. "The Vehicle Routing Problem with Demand Range." Annals of Operations Research 144, no. 1 (2006): 99–110. http://dx.doi.org/10.1007/s10479-006-0057-0.

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18

Viemeister, Neal F. "Intensity coding and the dynamic range problem." Hearing Research 34, no. 3 (1988): 267–74. http://dx.doi.org/10.1016/0378-5955(88)90007-x.

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19

Yu, Fang, and Jin-chuan Cui. "The Efficient Computation of Aircraft Range Problem." Acta Mathematicae Applicatae Sinica, English Series 35, no. 4 (2019): 862–72. http://dx.doi.org/10.1007/s10255-019-0858-y.

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20

Mashreghi, Javad, Marek Ptak, and William T. Ross. "A common range problem for model spaces." Forum Mathematicum 33, no. 4 (2021): 987–96. http://dx.doi.org/10.1515/forum-2021-0092.

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Abstract We refine a result of [J. E. McCarthy, Common range of co-analytic Toeplitz operators, J. Amer. Math. Soc. 3 1990, 4, 793–799] and explore the common range of the co-analytic Toeplitz operators on a model space. The tools used to do this also yield information about when one can interpolate with an outer function.

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21

MONGELLI, H., and S. W. SONG. "PARALLEL RANGE MINIMA ON COARSE GRAINED MULTICOMPUTERS." International Journal of Foundations of Computer Science 10, no. 04 (1999): 375–89. http://dx.doi.org/10.1142/s0129054199000277.

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Given an array of n real numbers A=(a0, a1, …, an-1), define MIN(i,j)= min {ai,…,aj}. The range minima problem consists of preprocessing array A such that queries MIN(i,j), for any 0≤i≤n-1 can be answered in constant time. Range minima is a basic problem that appears in many other important graph problems such as lowest common ancestor, Euler tour, etc. In this work we present a parallel algorithm under the CGM model (coarse grained multicomputer), that solves the range minima problem in O(n/p) time and constant number of communication rounds. The communication overhead involves the transmissi

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22

Wu and Feng. "On-Off Control of Range Extender in Extended-Range Electric Vehicle using Bird Swarm Intelligence." Electronics 8, no. 11 (2019): 1223. http://dx.doi.org/10.3390/electronics8111223.

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The bird swarm algorithm (BSA) is a bio-inspired evolution approach to solving optimization problems. It is derived from the foraging, defense, and flying behavior of bird swarm. This paper proposed a novel version of BSA, named as BSAII. In this version, the spatial distance from the center of the bird swarm instead of fitness function value is used to stand for their intimacy of relationship. We examined the performance of two different representations of defense behavior for BSA algorithms, and compared their experimental results with those of other bio-inspired algorithms. It is evident fr

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23

Intrigila, Benedetto, and Richard Statman. "Solution to the Range Problem for Combinatory Logic." Fundamenta Informaticae 111, no. 2 (2011): 203–22. http://dx.doi.org/10.3233/fi-2011-560.

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24

Oksengendler, B. L., and N. N. Turaeva. "Periodic Landau-Zener problem in long-range migration." Journal of Experimental and Theoretical Physics 103, no. 3 (2006): 411–14. http://dx.doi.org/10.1134/s106377610609010x.

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25

Mash, V. A. "THE MULTISECTORAL INTERREGIONAL LONG-RANGE OPTIMAL PLANNING PROBLEM." Papers in Regional Science 18, no. 1 (2005): 87–90. http://dx.doi.org/10.1111/j.1435-5597.1967.tb01356.x.

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26

Nielsen, E. "The three-body problem with short-range interactions." Physics Reports 347, no. 5 (2001): 373–459. http://dx.doi.org/10.1016/s0370-1573(00)00107-1.

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27

Khodakarami, Farnoosh, Farzad Didehvar, and Ali Mohades. "1.5D terrain guarding problem parameterized by guard range." Theoretical Computer Science 661 (January 2017): 65–69. http://dx.doi.org/10.1016/j.tcs.2016.11.015.

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28

Szeląg, A., J. Rubacha, and T. Kamisiński. "Narrow Frequency Range Problem of Sound Reflector Arrays." Acta Physica Polonica A 123, no. 5 (2013): 1059–63. http://dx.doi.org/10.12693/aphyspola.123.1059.

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29

Takahashi, Emiko, Masao ARAKAWA, Hiroshi ISHIKAWA, Kozo NAKAMURA, and Hirosuke KURIHARA. "3301 Adaptive Range Genetic Algorithms for Scheduling Problem." Proceedings of Design & Systems Conference 2001.11 (2001): 308–11. http://dx.doi.org/10.1299/jsmedsd.2001.11.308.

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30

YAGI, Toshiro, Masao ARAKAWA, Motoaki SHIBAYAMA, Hirotaka NAKAYAMA, Ye Boon YUN, and Hiroshi ISHIKAWA. "2101 Adaptive Range Genetic Algorithms for Scheduling Problem." Proceedings of Design & Systems Conference 2001.11 (2001): 80–83. http://dx.doi.org/10.1299/jsmedsd.2001.11.80.

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31

Simenog, I. V., and D. V. Shapoval. "Interaction range perturbation theory for three-particle problem." Theoretical and Mathematical Physics 75, no. 2 (1988): 522–31. http://dx.doi.org/10.1007/bf01017493.

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32

Andrievskii, Vladimir, and Stephan Ruscheweyh. "The maximal range problem for a bounded domain." Journal of Approximation Theory 158, no. 2 (2009): 151–69. http://dx.doi.org/10.1016/j.jat.2008.08.002.

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33

Chen, Kuan-Yu, and Kun-Mao Chao. "On the range maximum-sum segment query problem." Discrete Applied Mathematics 155, no. 16 (2007): 2043–52. http://dx.doi.org/10.1016/j.dam.2007.05.018.

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34

Li, Yu Qing, Ri Xin Wang, and Min Qiang Xu. "An Evolution Algorithm for Satellite Range Scheduling Problem with Priority Constraint." Applied Mechanics and Materials 568-570 (June 2014): 775–80. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.775.

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The satellite range scheduling problem is one of the most important problems in the field of the satellite operation. The purpose of this problem is finding the optimal feasible schedules, scheduling the communications between satellites and ground stations effectively, in another word. The problem is known for its high complexity and is an over-constrained problem. This paper present the resolution of the problem through a Station Coding Based Evolution Algorithm, particularly with the priority constraint, which adopting a new chromosome encoding method based on arranging the tasks in the gro

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35

Bint, Gregory, Anil Maheshwari, Michiel Smid, and Subhas C. Nandy. "Partial Enclosure Range Searching." International Journal of Computational Geometry & Applications 29, no. 01 (2019): 73–93. http://dx.doi.org/10.1142/s0218195919500018.

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A new type of range searching problem, called the partial enclosure range searching problem, is introduced in this paper. Given a set of geometric objects [Formula: see text] and a query region [Formula: see text], our goal is to identify those objects in [Formula: see text] which intersect the query region [Formula: see text] by at least a fixed proportion of their original size. Two variations of this problem are studied. In the first variation, the objects in [Formula: see text] are axis-parallel line segments and the goal is to count the total number of members of [Formula: see text] so th

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36

Smirnova, Nina, and Oleg Cherkasov. "Range maximization problem with a penalty on fuel consumption in the modified Brachistochrone problem." Applied Mathematical Modelling 91 (March 2021): 581–89. http://dx.doi.org/10.1016/j.apm.2020.10.001.

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37

Nemoto, Toshio. "AN EFFICIENT ALGORITHM FOR THE MINIMUM-RANGE IDEAL PROBLEM." Journal of the Operations Research Society of Japan 42, no. 1 (1999): 88–97. http://dx.doi.org/10.15807/jorsj.42.88.

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38

SAGAL, PAUL, and GUNNAR BORG. "The Range Principle and the Problem of Other Minds." British Journal for the Philosophy of Science 44, no. 3 (1993): 477–91. http://dx.doi.org/10.1093/bjps/44.3.477.

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39

Szeftel, Jacob. "Short-range correlated eigenstates in the many-electron problem." Physica B: Condensed Matter 230-232 (February 1997): 482–85. http://dx.doi.org/10.1016/s0921-4526(96)00621-7.

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40

Wei, Peng-xin, Chang-sheng Gao, and Wu-xing Jing. "Roll control problem for the long-range maneuverable warhead." Aircraft Engineering and Aerospace Technology 86, no. 5 (2014): 440–46. http://dx.doi.org/10.1108/aeat-10-2012-0170.

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41

Sogo, T., O. Sørensen, A. S. Jensen, and D. V. Fedorov. "The zero-range approximation applied to theN-boson problem." Journal of Physics B: Atomic, Molecular and Optical Physics 38, no. 7 (2005): 1051–75. http://dx.doi.org/10.1088/0953-4075/38/7/021.

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42

Szeftel, J. "Off-Diagonal Long-Range Order in Many-Electron Problem." Acta Physica Polonica A 91, no. 2 (1997): 341–45. http://dx.doi.org/10.12693/aphyspola.91.341.

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43

Gross, Alan L., and Mary L. McGanney. "The restriction of range problem and nonignorable selection processes." Journal of Applied Psychology 72, no. 4 (1987): 604–10. http://dx.doi.org/10.1037/0021-9010.72.4.604.

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44

Messori, Gabriele. "The long-range forecasting problem - mythology, science and progress." Weather 68, no. 7 (2013): 193–94. http://dx.doi.org/10.1002/wea.2140.

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45

Katsouleas, Georgios, and John Maroulas. "An Inverse Problem for the $k$-Rank Numerical Range." SIAM Journal on Matrix Analysis and Applications 37, no. 3 (2016): 1022–37. http://dx.doi.org/10.1137/15m1009342.

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46

Gao, Kaifeng, Jiang Zhu, and Zhiwei Xu. "Majorization–Minimization-Based Target Localization Problem From Range Measurements." IEEE Communications Letters 24, no. 3 (2020): 558–62. http://dx.doi.org/10.1109/lcomm.2019.2963834.

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47

Hallefjord, Åsa, Kurt Jörnsten, and Ola Eriksson. "A long range forestry planning problem with multiple objectives." European Journal of Operational Research 26, no. 1 (1986): 123–33. http://dx.doi.org/10.1016/0377-2217(86)90164-5.

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48

Mur, V. D., and V. S. Popov. "Coulomb problem with short-range interaction: Exactly solvable model." Theoretical and Mathematical Physics 65, no. 2 (1985): 1132–40. http://dx.doi.org/10.1007/bf01017937.

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49

Yu, Chih-Chiang, Wing-Kai Hon, and Biing-Feng Wang. "Improved data structures for the orthogonal range successor problem." Computational Geometry 44, no. 3 (2011): 148–59. http://dx.doi.org/10.1016/j.comgeo.2010.09.001.

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50

Burkert, Andreas. "The Fuel Cell still Suffers from a Range Problem." MTZ worldwide 80, no. 11 (2019): 6–7. http://dx.doi.org/10.1007/s38313-019-0138-5.

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