An index for moving objects with constant-time access to their compressed trajectories

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Geographical Information Science in 2021, available at: https://doi.org/10.1080/13658816.2020.1833015Versión final aceptada de: Nieves R. Brisaboa, Travis Gagie, Adrián Gómez-Brandón, Gonzalo Navarro & José R. Paramá (2021) An index for moving objects with constant-time access to their compressed trajectories, International Journal of Geographical Information Science, 35:7, 1392-1424, DOI: 10.1080/13658816.2020.1833015[Abstract]: As the number of vehicles and devices equipped with GPS technology has grown explosively, an urgent need has arisen for time- and space-efficient data structures to represent their trajectories. The most commonly desired queries are the following: queries about an object’s trajectory, range queries, and nearest neighbor queries. In this paper, we consider that the objects can move freely and we present a new compressed data structure for storing their trajectories, based on a combination of logs and snapshots, with the logs storing sequences of the objects’ relative movements and the snapshots storing their absolute positions sampled at regular time intervals. We call our data structure ContaCT because it provides Constant- time access to Compressed Trajectories. Its logs are based on a compact partial-sums data structure that returns cumulative displacement in constant time, and allows us to compute in constant time any object’s position at any instant, enabling a speedup when processing several other queries. We have compared ContaCT experimentally with another compact data structure for trajectories, called GraCT, and with a classic spatio-temporal index, the MVR-tree. Our results show that ContaCT outperforms the MVR-tree by orders of magnitude in space and also outperforms the compressed representation in time performance.This work was supported by Xunta de Galicia/FEDER-UE under Grants [IN848D-2017-2350417; IN852A 2018/14; ED431C 2017/58]; Xunta de Galicia and European Union (European Regional Development Fund- Galicia 2014-2020 Program) with the support of CITIC research center under Grant [ED431G 2019/01]; Ministerio de Ciencia, Innovación y Universidades under Grants [TIN2016-78011-C4-1-R; RTC-2017-5908-7]; A.G. was supported by Ministerio de Educación y Formación Profesional (FPU) [grant number FPU16/02914]; G.N. was supported by ANID - Millennium Science Initiative Program under Grant [ICN17_002]; and Fondecyt under Grant [1-200038]. T.G. was supported by NSERC under grant [RGPIN-2020-07185].Xunta de Galicia; IN848D-2017-2350417Xunta de Galicia; IN852A 2018/14Xunta de Galicia; ED431C 2017/58Xunta de Galicia; ED431G 2019/0

Systems Theory Based Framework for Competency Models

The purpose of this research was to develop and apply a systems theoretic framework for design, analysis and transformation of competency models using an inductive research design. This research examines the origins and development of competency models from a systems theoretic perspective. Competency models have been largely developed by a comparative method first proposed by McClelland, or the use of Delphi method survey techniques. The assumption that a population containing an exemplar and fully successful members would enable population of a holistic competency model has reported numerous failures. Similarly, reporting on the use of Delphi methods has focused on attempting to refine or augment Delphi methods to fill gaps in the competency models that are already in use. Rothwell and Lindholm called for methods that will reduce the backward looking bias of current competency development models. The literature of systems theory is applied to the concept of competency models via inductive theory building using Whewell\u27s Discoverer\u27s Induction supported by the structure of grounded theory. A competency model framework was developed that represents a distillation and synthesis of systems theory literature. The resulting framework can be used to design, assess and transform new or existing competency models. A single extant model was examined with the competency model framework revealing competency model inconsistencies that can be closed in a transformation effort. This research represents a fundamentally new approach to the construction of competency models, focused on a theoretical outlook rather than the dominant pragmatic approaches in use today. Additionally, the use of Discoverer\u27s Induction as the methodology in conjunction with the methods of grounded theory represents a methodological contribution to theory building due to the rarity of the combination