Spatio-Temporal Modeling and Prediction of Visual Attention in Graphical User Interfaces

This chapter examines the scope of protection to which graphical user interfaces may be eligible under various intellectual property rights: namely, trade marks, unfair-competition laws, design rights, copyright, and patents. It first considers the extent of copyright protection over a software product’s ‘look-and-feel’ elements, with particular emphasis on graphical user interfaces protection under US and EU laws. It then discusses trade-mark, trade-dress, and unfair-competition protection for graphical user interfaces, along with intellectual property rights protection for design patents and registered designs. Finally, it describes the patent protection for graphical user interfaces in the United States and at the European Patent Office.

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Pyramidal Framework: Guidance for the Next Generation of GIS Spatial-Temporal Models

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10030188 ◽

2021 ◽

Vol 10 (3) ◽

pp. 188

Author(s):

Cyril Carré ◽

Younes Hamdani

Keyword(s):

Conceptual Models ◽

Future Generations ◽

Temporal Data ◽

Temporal Modeling ◽

Temporal Models ◽

Gis Data ◽

Spatio Temporal ◽

New Interpretation ◽

Conventional Literature

Over the last decade, innovative computer technologies and the multiplication of geospatial data acquisition solutions have transformed the geographic information systems (GIS) landscape and opened up new opportunities to close the gap between GIS and the dynamics of geographic phenomena. There is a demand to further develop spatio-temporal conceptual models to comprehensively represent the nature of the evolution of geographic objects. The latter involves a set of considerations like those related to managing changes and object identities, modeling possible causal relations, and integrating multiple interpretations. While conventional literature generally presents these concepts separately and rarely approaches them from a holistic perspective, they are in fact interrelated. Therefore, we believe that the semantics of modeling would be improved by considering these concepts jointly. In this work, we propose to represent these interrelationships in the form of a hierarchical pyramidal framework and to further explore this set of concepts. The objective of this framework is to provide a guideline to orient the design of future generations of GIS data models, enabling them to achieve a better representation of available spatio-temporal data. In addition, this framework aims at providing keys for a new interpretation and classification of spatio-temporal conceptual models. This work can be beneficial for researchers, students, and developers interested in advanced spatio-temporal modeling.

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An architectural model for Improving the reusability of graphical user interfaces

Proceedings of the 31st Conference on l'Interaction Homme-Machine Adjunct - IHM '19 ◽

10.1145/3366551.3370352 ◽

2019 ◽

Author(s):

Eric Lecolinet

Keyword(s):

User Interfaces ◽

Graphical User Interfaces ◽

Architectural Model

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epiTracker: A Framework for Highly Reliable Particle Tracking for the Quantitative Analysis of Fish Movements in Tanks

SLAS TECHNOLOGY Translating Life Sciences Innovation ◽

10.1177/2472630320977454 ◽

2020 ◽

pp. 247263032097745

Author(s):

Roman Bruch ◽

Paul M. Scheikl ◽

Ralf Mikut ◽

Felix Loosli ◽

Markus Reischl

Keyword(s):

Social Interactions ◽

User Interfaces ◽

Particle Tracking ◽

Group Behavior ◽

Correction Method ◽

Graphical User Interfaces ◽

Study Group ◽

Automated Tracking ◽

User Friendly ◽

Track Analysis

Behavioral analysis of moving animals relies on a faithful recording and track analysis to extract relevant parameters of movement. To study group behavior and social interactions, often simultaneous analyses of individuals are required. To detect social interactions, for example to identify the leader of a group as opposed to followers, one needs an error-free segmentation of individual tracks throughout time. While automated tracking algorithms exist that are quick and easy to use, inevitable errors will occur during tracking. To solve this problem, we introduce a robust algorithm called epiTracker for segmentation and tracking of multiple animals in two-dimensional (2D) videos along with an easy-to-use correction method that allows one to obtain error-free segmentation. We have implemented two graphical user interfaces to allow user-friendly control of the functions. Using six labeled 2D datasets, the effort to obtain accurate labels is quantified and compared to alternative available software solutions. Both the labeled datasets and the software are publicly available.

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