Using Soft Systems Methodology to Improve the Colour Forecasting Process

Colour forecasting is a process where attempts are made to accurately forecast colour for fashion-related products that consumers will purchase in the near future, usually two years ahead. Seasonal colours are recognised as a powerful driver of sales. Currently trend forecasts are marketed and sold globally. The information is broad and generalised and does not take into account colour preferences. In the study the anticipation of consumer acceptance was identified as the weakness of the process and an improved system model was developed replacing the anticipation stage with consumer colour acceptance data. The improved model is considered highly beneficial for fashion-related industries to adopt in order to increase their competitiveness in the global market and to assist waste reduction (unwanted products) that impact on the environment. In this paper the development of the two models is presented and discussed in an attempt to purposely promote the usefulness of soft systems methodology for design research

Scene extraction in motion pictures

This paper addresses the challenge of bridging the semantic gap between the rich meaning users desire when they query to locate and browse media and the shallowness of media descriptions that can be computed in today\u27s content management systems. To facilitate high-level semantics-based content annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from fill production to determine when a scene change occurs. We then investigate different rules and conventions followed as part of Fill Grammar that would guide and shape an algorithmic solution for determining a scene. Two different techniques using intershot analysis are proposed as solutions in this paper. In addition, we present different refinement mechanisms, such as film-punctuation detection founded on Film Grammar, to further improve the results. These refinement techniques demonstrate significant improvements in overall performance. Furthermore, we analyze errors in the context of film-production techniques, which offer useful insights into the limitations of our method

A visual language to characterise transitions in narrative visualization

We use a taxonomy of panel-to-panel transitions in comics, refined the definition of its components to reflect the nature of data-stories in information visualization, and then, use the taxonomy in coding a number of VAST challenges videos from the last four years. We represent the use of transitions in each video graphically with a diagram that shows how the information was added incrementally in order to tell a story that answers a particular question. A number of issues have been taken into account when coding transitions in each video as well as in designing and creating the visual diagram such as, nested transitions, the use of sub-topics, and delayed transitions

Text spacing considerations for children’s on-screen reading

This investigation seeks to uncover the insights of three integral and inter-related participants in the creation and use of on-screen reading material for children’s learning. This is an effort to discover what factors are perceived to influence children’s comprehension. Through a design-analyse-refine methodology this researcher discusses a series of typographical considerations relating to space which bear further empirical investigation in the literature. This methodology involved discussion of ideas garnered from four experts. The results of each iteration of the experiment influenced further refinement of the ideas until suitable conclusions were able to be developed by the writer. Testing materials in this experiment adjusted variables for visual separation, including margins, separation of image and type, as well as line spacing, letter spacing and word spacing