Results 41 to 50 of about 42,049,725 (376)
, 1990 Publisher Summary This chapter discusses data structures. Data structuring is the study of concrete implementations of frequently occurring abstract data types. An abstract data type is a set together with a collection of operations on the elements of the set. In the data type dictionary, the set is the power set of a universe U and the operations are
Mehlhorn, Kurt, Tsakalidis, A.
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Bloom Filter Trie: an alignment-free and reference-free data structure for pan-genome storage
Algorithms for Molecular Biology, 2016 High throughput sequencing technologies have become fast and cheap in the past years. As a result, large-scale projects started to sequence tens to several thousands of genomes per species, producing a high number of sequences sampled from each genome ...
Guillaume Holley +2 more
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CONSTRUCTIVE MODEL OF DATA STRUCTURES ADAPTATION IN RAM: PART I. PROGRAM TEXT CONSTRUCTING
Nauka ta progres transportu, 2016 Purpose. Rapidly growing volumes of information systems data being manipulated significantly reduce the temporary algorithms effeciency of their processing . Effective data layout in RAM is one of the directions of solving this problem.
V. I. Shynkarenko, H. V. Zabula
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Surface network extraction from high resolution digital terrain models
Journal of Spatial Information Science, 2021 A surface network is a topological data structure formed by a set of thalwegs and ridges on a digital terrain model. Its computation relies on the detection of saddles on the terrain.
Eric Guilbert
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IEEE Access, 2022 A binary time series can be transformed into a Branch Length Similarity (BLS) entropy profile by being mapped to a circumference called a time-circle. In this study, we explored how peaks and cliffs are formed and how they relate to time series.
Sang-Hee Lee, Cheol-Min Park
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Static Data Structure Lower Bounds Imply Rigidity
, 2019 We show that static data structure lower bounds in the group (linear) model imply semi-explicit lower bounds on matrix rigidity. In particular, we prove that an explicit lower bound of $t \geq \omega(\log^2 n)$ on the cell-probe complexity of linear data
Agarwal Pankaj K. +9 more
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, 2017 This paper presents a new paradigm of explicitly modeling and harnessing the data structure to address the inverse problems in structural dynamics, identification, and data‐driven health monitoring.
Satish Nagarajaiah, Yongchao Yang
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UCSF ChimeraX: Structure visualization for researchers, educators, and developers
Protein Science, 2020 UCSF ChimeraX is the next‐generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera.
E. Pettersen +7 more
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, 2020 Very recently, the unexpected combination of data structures and machine learning has led to the development of a new area of research, called learned data structures. Their distinguishing trait is the ability to reveal and exploit patterns and trends in the input data for achieving more efficiency in time and space, compared to previously known data ...
Paolo Ferragina, Giorgio Vinciguerra
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Nauka ta progres transportu, 2016 Purpose.The second part of the paper completes presentation of constructive and the productive structures (CPS), modeling adaptation of data structures in memory (RAM).
V. I. Shynkarenko, H. V. Zabula
doaj +1 more source