Computational Movement Analysis

Laube, Patrick

doi:10.1007/978-3-319-10268-9

Cited by 55 publications

(28 citation statements)

References 85 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, before being able to model the observed behavior, the challenge is to review large amounts of records containing large amounts of moving entities over longer time spans, while looking for general behavior as well as unusual events like unexpected outliers or loss of coherence in a group. Characterizing interactions and extracting behavior from movements is an established field, and an extensive introduction and overview is given by Laube [33]. Still, algorithmic approaches are based on assumptions that have to be established first exploratively -and thus, visually.…”

Section: Related Workmentioning

confidence: 99%

MotionRugs: Visualizing Collective Trends in Space and Time

Buchmüller

Jäckle

Cakmak

et al. 2019

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

Understanding the movement patterns of collectives, such as flocks of birds or fish swarms, is an interesting open research question. The collectives are driven by mutual objectives or react to individual direction changes and external influence factors and stimuli. The challenge in visualizing collective movement data is to show space and time of hundreds of movements at the same time to enable the detection of spatiotemporal patterns. In this paper, we propose MotionRugs, a novel space efficient technique for visualizing moving groups of entities. Building upon established space-partitioning strategies, our approach reduces the spatial dimensions in each time step to a one-dimensional ordered representation of the individual entities. By design, MotionRugs provides an overlap-free, compact overview of the development of group movements over time and thus, enables analysts to visually identify and explore group-specific temporal patterns. We demonstrate the usefulness of our approach in the field of fish swarm analysis and report on initial feedback of domain experts from the field of collective behavior.

show abstract

Section: Related Workmentioning

confidence: 99%

MotionRugs: Visualizing Collective Trends in Space and Time

Buchmüller

Jäckle

Cakmak

et al. 2019

IEEE Trans. Visual. Comput. Graphics

View full text Add to dashboard Cite

show abstract

“…Computational movement analysis, a term coined by Laube (2014), relates to computational methods to detect patterns structures in movement data. These methods provide the foundation to developing insight into the behavior of moving phenomena from raw movement data.…”

Section: Computational Movement Analysismentioning

confidence: 99%

“…The framework relies on an iterative validation process, where analytics and models are parameterized, calibrated, and improved using real movement observations. Understanding movement, shown on the right side of Figure 1, entails development of methods for quantification of movement and its parameters (Dodge et al 2008, Long and Nelson 2012, Laube 2014, Demšar et al 2015; analysis of its context and external influences on movement (Schick et al 2008, Andrienko et al 2011, Dodge et al 2013, Miller 2015; and detection of movement patterns through computational movement analysis (Long and Nelson 2012, Laube 2014, Purves et al 2014, Soleymani et al 2014. Modeling movement, shown on the left side of Figure 1, consists of creating models, developing simulations and making predictions (Ahearn et al 2001, Hornsby and Egenhofer 2002, Schick et al 2008, Torrens et al 2012, Song and Miller 2014, Technitis et al 2015.…”

Section: Introductionmentioning

confidence: 99%

Analysis of movement data

Dodge

Weibel

Ahearn

et al. 2016

International Journal of Geographical Information Science

View full text Add to dashboard Cite

“…The main assessment detail from CFD analyses was the performance of heat exchanger, which was expressed by the ratio between incomes from the heat distribution and operating costs for circulation of heat transfer fluid. In the calculation were considered the cost of electricity 150 € MWh ) from heat distribution [10,11,12].…”

Section: Hydraulic Calculationmentioning

confidence: 99%

Optimization principle of operating parameters of heat exchanger by using CFD simulation

Mičieta

Vondál

Jandačka

et al. 2016

EPJ Web of Conferences

View full text Add to dashboard Cite

Abstract. Design of effective heat transfer devices and minimizing costs are desired sections in industry and they are important for both engineers and users due to the wide-scale use of heat exchangers. Traditional approach to design is based on iterative process in which is gradually changed design parameters, until a satisfactory solution is achieved. The design process of the heat exchanger is very dependent on the experience of the engineer, thereby the use of computational software is a major advantage in view of time. Determination of operating parameters of the heat exchanger and the subsequent estimation of operating costs have a major impact on the expected profitability of the device. There are on the one hand the material and production costs, which are immediately reflected in the cost of device. But on the other hand, there are somewhat hidden costs in view of economic operation of the heat exchanger. The economic balance of operation significantly affects the technical solution and accompanies the design of the heat exchanger since its inception. Therefore, there is important not underestimate the choice of operating parameters. The article describes an optimization procedure for choice of cost-effective operational parameters for a simple double pipe heat exchanger by using CFD software and the subsequent proposal to modify its design for more economical operation.

show abstract

Computational Movement Analysis

Cited by 55 publications

References 85 publications

MotionRugs: Visualizing Collective Trends in Space and Time

MotionRugs: Visualizing Collective Trends in Space and Time

Analysis of movement data

Optimization principle of operating parameters of heat exchanger by using CFD simulation

Contact Info

Product

Resources

About