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Construction
Published in Richard Reed, Property Development, 2021
The bar chart can be used to indicate the timing of when specific information or decisions are required by the project manager, the developer and also the contractor. This is absolutely essential as lack of information or instructions is one of the main causes of delay. The bar chart also confirms any delay in one particular activity can affect the entire programme. After a potential delay is identified then it is important for the project manager to advise the developer about what potential effect it will have on the overall programme and how then time gains can be achieved via other activities. It is vital for the project manager to distribute the bar chart to the entire professional team allowing each member of the team to identify the target dates they must work to.
Visual displays
Published in Konrad Baumann, Bruce Thomas, User Interface Design for Electronic Appliances, 2001
However, with a row of elements it is possible to display an approxima-tion to the intensity envelope simultaneously with the momentary value. This is achieved by the uppermost element staying active after a peak value, even if the column has already dropped and, only after some time (2-4 seconds for audio signals), returning to the column. With several rows a dynamical bar chart may be formed. Even if a single row is not well suited for precise reading, a bar chart enables the reader quickly to picture the relative magnitudes of several variables for himself (e.g. the intensity dis-tribution of an audio signal over different frequency ranges).
Introduction to R
Published in Jan Žižka, František Dařena, Arnošt Svoboda, Text Mining with Machine Learning, 2019
Jan Žižka, František Dařena, Arnošt Svoboda
A simple bar chart can be created using the barplot() function. If the first(or the height) parameter is a vector, a sequence of bars representing the numeric values of the vector will be created. > barplot(articles[, 1])
A systematic meta-Review and analysis of learning analytics research
Published in Behaviour & Information Technology, 2021
Xu Du, Juan Yang, Brett E. Shelton, Jui-Long Hung, Mingyan Zhang
Schwendimann et al. (2017) examined educational dashboards in order to categorise learning contexts, data sources, visualisations and analysis types in both LA and EDM by reviewing 55 journal papers between 2010–2015. The authors found that most of the learning dashboards were designed for students’ self-monitoring and for instructors to monitor students in formal higher education settings. The data sources of dashboards were heavily relied on behaviour logs from a single LMS platform. The visualisation types, which were similar to that of traditional dashboards, utilised bar chart, line graph, table, pie chart, and network graph. In terms of analysis type, the authors revealed that most of studies in their review were exploratory or proof-of-concept without authentic evaluations, therefore, it was difficult to evaluate the actual impacts of learning dashboard on learning effects.
Review of simulation-based life cycle assessment in manufacturing industry
Published in Production & Manufacturing Research, 2019
Yu Liu, Anna Syberfeldt, Mattias Strand
Graphic presentation is the most common communication approach as it is the most intuitive, and it is often used in presenting results at the LCIA level. Of the different types of graphic representation, the bar chart is the most preferred in the reviewed studies. Results can be shown in the stacked bar format to represent the environmental contributions of different life cycle phases, materials used, machine states, etc., to help identify the significant items, as shown in Figure 2, a typical bar chart. Tables are the most effective way to present extensive detailed data, and they are used in one quarter of the reviewed studies, mostly to present LCI-level data. Only one study uses text to communicate the results, an approach that limits the efficiency of the data presentation. In addition, 29% of the studies do not present any quantitative results, as they are mostly conceptual in nature and present their methodologies without any quantitative analysis.