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Gamifying Computer Science Education for Z Generation
Information, 2021 Generation Z members use their smart devices as part of their everyday routine. Teaching methods may need to be updated to make learning materials more interesting for this generation.
Hadeel Mohammed Jawad, Samir Tout
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Data Structures for Mobile Data [PDF]
Journal of Algorithms, 1999 The authors present a set of novel data structures for the efficient maintenance of various continuous and discrete attributes of mobile data. A Kinetic Data Structure (KDS) maintains an attribute of interest in a system of geometric objects undergoing continuous motion.
John Hershberger +2 more
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Dynamic Data Structures for Document Collections and Graphs [PDF]
, 2015 In the dynamic indexing problem, we must maintain a changing collection of text documents so that we can efficiently support insertions, deletions, and pattern matching queries.
Munro, J. Ian +2 more
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Lightweight Dual-Attention Network for Concrete Crack Segmentation
SensorsStructural health monitoring in resource-constrained environments demands crack segmentation models that match the accuracy of heavyweight convolutional networks while conforming to the power, memory, and latency limits of watt-level edge devices.
Min Feng, Juncai Xu
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Practical guidelines and the EMLN R package for handling ecological multilayer networks
Methods in Ecology and Evolution, 2023 Network analysis provides a powerful framework to study the complexity underlying the structure, dynamics and function of ecological systems. By now, analysing single‐layered networks is a common practice with clear guidelines and well‐established ...
Noa Frydman +3 more
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Predicate Abstraction for Linked Data Structures
, 2015 We present Alias Refinement Types (ART), a new approach to the verification of correctness properties of linked data structures. While there are many techniques for checking that a heap-manipulating program adheres to its specification, they often ...
A Ahmed +18 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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IEEE Journal of Selected Topics in Signal Processing, 2015 We present structured data fusion (SDF) as a framework for the rapid prototyping of knowledge discovery in one or more possibly incomplete data sets. In SDF, each data set—stored as a dense, sparse, or incomplete tensor—is factorized with a matrix or tensor decomposition.
Sorber, Laurent +2 more
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Optimising Simulation Data Structures for the Xeon Phi [PDF]
, 2016 In this paper, we propose a lock-free architecture to accelerate logic gate circuit simulation using SIMD multi-core machines. We evaluate its performance on different test circuits simulated on the Intel Xeon Phi and 2 other machines.
Chimeh, Mozhgan K., Cockshott, Paul
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Data Autodiscovery—The Role of the OPD
ISPRS International Journal of Geo-Information, 2016 The importance of open data and the benefits it can offer have received recognition on the international stage with the signing of the G8 Open Data Charter in June 2013.
Adrian J. M. Cox +2 more
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