Conceptual Model and Design of Semantic Trajectory Data Warehouse

The trajectory patterns of a moving object in a spatio-temporal domain offers varied information in terms of the management of the data generated from the movement. The query results of trajectory objects from the data warehouse are usually not enough to answer certain trend behaviours and meaningful inferences without the associated semantic information of the trajectory object or the geospatial environment within a specified purpose or context. This article formulates and designs a generic ontology modelling framework that serves as the background model platform for the design of a semantic data warehouse for trajectories. The methodology underpins on higher granularity of data as a result of pre-processed and extract-transformed-load (ETL) data so as to offer efficient semantic inference to the underlying trajectory data. Moreover, the modelling approach outlines the thematic dimensions that offer a design platform for predictive trend analysis and knowledge discovery in the trajectory dynamics and data processing for moving objects.

Modelling the ballistic-to-diffusive transition in nematode motility reveals variation in exploratory behaviour across species

A quantitative understanding of organism-level behaviour requires predictive models that can capture the richness of behavioural phenotypes, yet are simple enough to connect with underlying mechanistic processes. Here, we investigate the motile behaviour of nematodes at the level of their translational motion on surfaces driven by undulatory propulsion. We broadly sample the nematode behavioural repertoire by measuring motile trajectories of the canonical laboratory strain Caenorhabditis elegans N2 as well as wild strains and distant species. We focus on trajectory dynamics over time scales spanning the transition from ballistic (straight) to diffusive (random) movement and find that salient features of the motility statistics are captured by a random walk model with independent dynamics in the speed, bearing and reversal events. We show that the model parameters vary among species in a correlated, low-dimensional manner suggestive of a common mode of behavioural control and a trade-off between exploration and exploitation. The distribution of phenotypes along this primary mode of variation reveals that not only the mean but also the variance varies considerably across strains, suggesting that these nematode lineages employ contrasting ‘bet-hedging’ strategies for foraging.

Modeling the ballistic-to-diffusive transition in nematode motility reveals variation in exploratory behavior across species

A quantitative understanding of organism-level behavior requires predictive models that can capture the richness of behavioral phenotypes, yet are simple enough to connect with underlying mechanistic processes. Here we investigate the motile behavior of nematodes at the level of their translational motion on surfaces driven by undulatory propulsion. We broadly sample the nematode behavioral repertoire by measuring motile trajectories of the canonical lab strainC. elegansN2 as well as wild strains and distant species. We focus on trajectory dynamics over timescales spanning the transition from ballistic (straight) to diffusive (random) movement and find that salient features of the motility statistics are captured by a random walk model with independent dynamics in the speed, bearing and reversal events. We show that the model parameters vary among species in a correlated, low-dimensional manner suggestive of a common mode of behavioral control and a trade-off between exploration and exploitation. The distribution of phenotypes along this primary mode of variation reveals that not only the mean but also the variance varies considerably across strains, suggesting that these nematode lineages employ contrasting “bet-hedging” strategies for foraging.

Probing the π → π* photoisomerization mechanism of trans-azobenzene by multi-state ab initio on-the-fly trajectory dynamics simulations

Global nonadiabatic switching on-the-fly trajectory surface hopping simulations at the 5SA-CASSCF(6,6)/6-31G quantum level have been employed to probe the photoisomerization mechanism of trans-azobenzene upon ππ* excitation within four coupled singlet low-lying electronic states (S0, S1, S2, and S3).

An accurate full-dimensional potential energy surface and quasiclassical trajectory dynamics of the H + H2O2 two-channel reaction

Quasiclassical trajectory calculations reveal interesting dynamics features based on an accurate FI-NN PES for the H + H2O2 two-channel reaction.

A framework of comparative urban trajectory analysis

The increasing availability of urban trajectory data from the GPS-enabled devices has provided scholars with opportunities to study urban dynamics at a finer spatiotemporal scale. Yet given the multi-dimensionality of urban trajectory dynamics, current research faces challenges of systematically uncovering spatiotemporal and societal implications of human movement patterns. Particularly, a data-driven policy-making process may need to use data from various sources with varying resolutions, analyze data at different levels, and compare the results with different scenarios. As such, a synthesis of varying spatiotemporal and network methods is needed to provide researchers and planning specialists a foundation for studying complex social and spatial processes. In this paper, we propose a framework that combines various spatiotemporal and network analysis units. By customizing the combination of analysis units, the researcher can employ trajectory data to evaluate urban built environment dynamically and comparatively. Two case studies of Chinese cities are carried out to evaluate the usefulness of proposed conceptual framework. Our results suggest that the proposed framework can comprehensively quantify the variation of urban trajectory across various scales and dimensions.