Browsing by Author "Dayama, Niraj Ramesh"

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  • AdaM: Adapting Multi-User Interfaces for Collaborative Environments in Real-Time
    (2018-04) Park, Seonwook; Gebhardt, Christoph; Rädle, Roman; Feit, Anna Maria; Vrzakova, Hana; Dayama, Niraj Ramesh; Yeo, Hui-Shyong; Klokmose, Clemens N; Quigley, Aaron; Oulasvirta, Antti
     A4 Artikkeli konferenssijulkaisussa
    Developing cross-device multi-user interfaces (UIs) is a challenging problem. There are numerous ways in which content and interactivity can be distributed. However, good solutions must consider multiple users, their roles, their preferences and access rights, as well as device capabilities. Manual and rule-based solutions are tedious to create and do not scale to larger problems nor do they adapt to dynamic changes, such as users leaving or joining an activity. In this paper, we cast the problem of UI distribution as an assignment problem and propose to solve it using combinatorial optimization. We present a mixed integer programming formulation which allows real-time applications in dynamically changing collaborative settings. It optimizes the allocation of UI elements based on device capabilities, user roles, preferences, and access rights. We present a proof-of-concept designer-in-the-loop tool, allowing for quick solution exploration. Finally, we compare our approach to traditional paper prototyping in a lab study.
  • CoColor: Interactive Exploration of Color Designs
    (2023-03-27) Hegemann, Lena; Dayama, Niraj Ramesh; Iyer, Abhishek; Farhadi, Erfan; Marchenko, Ekaterina; Oulasvirta, Antti
     A4 Artikkeli konferenssijulkaisussa
    Choosing colors is a pivotal but challenging component of graphic design. The paper presents an intelligent interaction technique supporting designers' creativity in color design. It fills a gap in the literature by proposing an integrated technique for color exploration, assignment, and refinement: CoColor. Our design goals were 1) let designers focus on color choice by freeing them from pixel-level editing and 2) support rapid flow between low- and high-level decisions. Our interaction technique utilizes three steps - choice of focus, choice of suitable colors, and the colors' application to designs - wherein the choices are interlinked and computer-assisted, thus supporting divergent and convergent thinking. It considers color harmony, visual saliency, and elementary accessibility requirements. The technique was incorporated into the popular design tool Figma and evaluated in a study with 16 designers. Participants explored the coloring options more easily with CoColor and considered it helpful.
  • Foraging-based Optimization of Menu Systems
    (2021-07) Dayama, Niraj Ramesh; Shiripour, Morteza; Oulasvirta, Antti; Ivanko, Evgeny; Karrenbauer, Andreas
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The problem of computational design for menu systems has been addressed in some specific cases such as the linear menu (list). The classical approach has been to model this problem as an assignment task, where commands are assigned to menu positions while optimizing for users’ selection performance and grouping of associated items. However, we show that this approach fails with larger, hierarchically organized menus because it does not take into account the ways in which users navigate hierarchical structures. This paper addresses the computational menu design problem by presenting a novel integer programming formulation that yields usable, well-ordered command hierarchies from a single model. First, it introduces a novel objective function based on information foraging theory, which minimizes navigation time in a hierarchical structure. Second, it models the hierarchical menu design problem as a combination of the exact set covering problem and the assignment problem, organizing commands into ordered groups of ordered groups. The approach is efficient for large, representative instances of the problem. In a controlled usability evaluation, the performance of computationally designed menus was ∼25% faster to use than existing commercial designs. We discuss applications of this approach for personalization and adaptation.
  • Foraging-based optimization of pervasive displays
    (2019-04-01) Montoya Freire, Maria L.; Potts, Dominic; Dayama, Niraj Ramesh; Oulasvirta, Antti; Di Francesco, Mario
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    The article addresses a key challenge in the design of content for pervasive displays: how to engage passers-by who have limited time and attention? To achieve this, we apply a novel approach for computational design of interesting display content using tiled layouts. We present a model of display foraging based on information foraging theory to describe the behavior of a rational but time-limited user looking at a display. Accordingly, our work aims to maximize the information gain for tiled displays. This complex problem is divided into two phases: (1) generating designs of tiled layouts and (2) assigning content options to individual tiles based on what predicted by display foraging. Accordingly, a proof-of-concept system was realized then evaluated computationally and empirically with a control study and field study. The results show that the proposed system can engage significantly more people than typical digital signage.
  • Grid-based Genetic Operators for Graphical Layout Generation
    (2021-06) Shiripour, Morteza; Dayama, Niraj Ramesh; Oulasvirta, Antti
     A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
    Graphical user interfaces (GUIs) have gained primacy among the means of interacting with computing systems, thanks to the way they leverage human perceptual and motor capabilities. However, the design of GUIs has mostly been a manual activity. To design a GUI, the designer must select its visual, spatial, textual, and interaction properties such that the combination strikes a balance among the relevant human factors. While emerging computational-design techniques have addressed some problems related to grid layouts, no general approach has been proposed that can also produce good and complete results covering color-related decisions and other nonlinear design objectives. Evolutionary algorithms are promising and demonstrate good handling of similar problems in other conditions, genetic operators, depending on how they are designed. But even these approaches struggle with elements' overlap and hence produce too many infeasible candidate solutions. This paper presents a new approach based on grid-based genetic operators demonstrated in a non-dominated sorting genetic algorithm (NSGA-III) setting. The operators use grid lines for element positions in a novel manner to satisfy overlap-related constraints and intrinsically improve the alignment of elements. This approach can be used for crossovers and mutations. Its core benefit is that all the solutions generated satisfy the no-overlap requirement and represent well-formed layouts. The new operators permit using genetic algorithms for increasingly realistic task instances, responding to more design objectives than could be considered before. Specifically, we address grid quality, alignment, selection time, clutter minimization, saliency control, color harmony, and grouping of elements.