Dataset Information

Application of a genetic algorithm to the keyboard layout problem.

ABSTRACT: The number of people who use computers for business and personal purposes increases as technology grows. The application of ergonomic practices on computer workstations reduces the musculoskeletal discomfort experienced and increases the overall satisfaction of the users. Keyboards are available in various systems, from computers to mobile devices, and have difference shapes and sizes. The keyboard size and shape is known to influence the user's upper extremities. Alternative keyboard designs help diminish the pain in the arms that occurs due to awkward arm postures. Most previous studies tried to optimize the keyboard layout based on ergonomic typing and the frequency of letters' co-occurrence. This research considers the frequency of the appearance of the most used 3,000 words in the English language. First, the frequency of each letter pair is calculated by the Text Analyzer. Then, a genetic algorithm is applied to design an ergonomically optimized keyboard to minimize the total distance of finger travel among the selected alphanumeric characters. The results showed that the distance travelled obtained by the proposed keyboard layout is less than that for the QWERTY keyboard in all different types of texts, in which an average of 6.04% improvement was achieved. Therefore, the proposed design can be used for keyboards to reduce time and fatigue.

SUBMITTER: Onsorodi AHH

PROVIDER: S-EPMC6946161 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Application of a genetic algorithm to the keyboard layout problem.

Onsorodi Amir Hosein Habibi AHH Korhan Orhan O

PloS one 20200107 1

The number of people who use computers for business and personal purposes increases as technology grows. The application of ergonomic practices on computer workstations reduces the musculoskeletal discomfort experienced and increases the overall satisfaction of the users. Keyboards are available in various systems, from computers to mobile devices, and have difference shapes and sizes. The keyboard size and shape is known to influence the user's upper extremities. Alternative keyboard designs he ...[more]

PMID: 31910214

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Project description:BackgroundGraph drawing is one of the important techniques for understanding biological regulations in a cell or among cells at the pathway level. Among many available layout algorithms, the spring embedder algorithm is widely used not only for pathway drawing but also for circuit placement and www visualization and so on because of the harmonized appearance of its results. For pathway drawing, location information is essential for its comprehension. However, complex shapes need to be taken into account when torus-shaped location information such as nuclear inner membrane, nuclear outer membrane, and plasma membrane is considered. Unfortunately, the spring embedder algorithm cannot easily handle such information. In addition, crossings between edges and nodes are usually not considered explicitly.ResultsWe proposed a new grid-layout algorithm based on the spring embedder algorithm that can handle location information and provide layouts with harmonized appearance. In grid-layout algorithms, the mapping of nodes to grid points that minimizes a cost function is searched. By imposing positional constraints on grid points, location information including complex shapes can be easily considered. Our layout algorithm includes the spring embedder cost as a component of the cost function. We further extend the layout algorithm to enable dynamic update of the positions and sizes of compartments at each step.ConclusionsThe new spring embedder-based grid-layout algorithm and a spring embedder algorithm are applied to three biological pathways; endothelial cell model, Fas-induced apoptosis model, and C. elegans cell fate simulation model. From the positional constraints, all the results of our algorithm satisfy location information, and hence, more comprehensible layouts are obtained as compared to the spring embedder algorithm. From the comparison of the number of crossings, the results of the grid-layout-based algorithm tend to contain more crossings than those of the spring embedder algorithm due to the positional constraints. For a fair comparison, we also apply our proposed method without positional constraints. This comparison shows that these results contain less crossings than those of the spring embedder algorithm. We also compared layouts of the proposed algorithm with and without compartment update and verified that latter can reach better local optima.

Dataset Information

Application of a genetic algorithm to the keyboard layout problem.

Publications

Application of a genetic algorithm to the keyboard layout problem.

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