A Coloring Algorithm for Disambiguating Graph and Map Drawings

Drawings of non-planar graphs always result in edge crossings. When there are many edges crossing at small angles, it is often difficult to follow these edges, because of the multiple visual paths resulted from the crossings that slow down eye movements. In this paper we propose an algorithm that disambiguates the edges with automatic selection of distinctive colors. Our proposed algorithm computes a near optimal color assignment of a dual collision graph, using a novel branch-and-bound procedure applied to a space decomposition of the color gamut. We give examples demonstrating the effectiveness of this approach in clarifying drawings of real world graphs and maps

Exploring the effects of colouring graph diagrams on people of various backgrounds

Colour is one of the primary aesthetic elements of a visualization. It is often used successfully to encode information such as the importance of a particular part of the diagram or the relationship between two parts. Even so, there are few investigations into the human reading of colour coding on diagrams from the scientific community. In this paper we report on an experiment with graph diagrams comparing a black and white composition with two other colour treatments. We drew our subjects from engineering, art, visual design, physical education, tourism, psychology and social science disciplines. We found that colouring the nodes of interest reduced the time taken to find the shortest path between the two nodes for all subjects. Engineers, tourism and social scientists proved significantly faster with artist/designers just below the overall average speed. From this study, we contribute that adding particular colour treatments to diagrams increases legibility. In addition, preliminary work investigating colour treatments and schemes indicates potential for future gains. © 2014 Springer-Verlag

Outerplanar graphs and Delaunay triangulations

Over 20 years ago, Dillencourt [1] showed that all outerplanar graphs can be realized as Delaunay triangulations of points in convex position. His proof is elementary, constructive and leads to a simple algorithm for obtaining a concrete Delaunay realization. In this note, we provide two new, alternate, also quite elementary proofs.

Untangling Road Trip Experiences with Conected Car : Planning and bringing it to the car

With developing technologies and growing infrastructures, connected experiences are expanding their realms towards various devices and scenarios in our lives. One of the areas, which is going under a big change due to this connectivity is the car related experiences. As connectivity is intrinsically enabler of different experiences and services, it is foreseen that it will bring a different dimension to car and driving related experiences as well.By investigating the future trends and possibilities that connectivity can provide to car and driving related experiences, this thesis aims for imagining the near future scenarios with an explorative approach, focusing on one and addressing to the rising issues with a design proposal that is meaningful to both users and the industry.The result, Tripcloud, contributes to the future scenario of having a road trip with the car, with a new digital platform that aims for supporting the users throughout the planning and bringing the plans into the car experience seamlessly and safely. It aims for reducing today’s existing complexity in terms of interaction and cognition to provide a better experience and avoid driver distraction. With providing organised information pieces, information exchange between people and automated links with mobile devices and car, Tripcloud offers easier an more convenient alternative for road trip planing and bringing the plans into car experiences for the near future

A Learning Trajectory for Developing Computational Thinking and Programming

A learning trajectory for developing computational thinking and programming This research study identifies the relationship between students’ prior experiences with programming and their development of computational thinking and programming during their first year engineering experience. Many first year programs teach students basic programming constructs using languages like MATLAB or LABView. The reason for this is because the disciplinary schools expect students to transform the constitutive properties that model a system’s behavior into a computer model they can use to analyze a system’s performance. Some undergraduate engineering students are entering college with strong computational backgrounds, while others are not. Peer learning has been used to accommodate the variance is skills between students; however, more needs to be known about the opportunities and issues with helping students develop these skills. This study is the first in a series to better identify students’ transition into developing and reasoning with analytical tools. The initial conjecture is that well balanced teams of novice and expert programmers can have a positive effect on the novice programmer’s development. Further the learning progression across two programming languages is critical to developing a student’s ability to generalize across various computational tools. Self-report background survey, students’ performance on academic assessments and an end of semester exit survey are being analyzed to identify a pattern in the development of novice programmers’ ability to design algorithms and implement them in code. This paper will be of interest to instructors with the objective of developing computational thinking and programming in classrooms with a large variance in students’ backgrounds with programming

Approximate Proximity Drawings

We introduce and study a generalization of the well-known region of influence proximity drawings, called (ε1, ε2)-proximity drawings. Intuitively, given a definition of proximity and two real numbers ε1 ≥ 0 and ε2 ≥ 0, an (ε1, ε2)-proximity drawing of a graph is a planar straight-line drawing Γ such that: (i) for every pair of adjacent vertices u, v, their proximity region “shrunk ” by the multiplicative factor