scholarly journals Modalflow: Cross-Origin Flow Data Visualization for Urban Mobility

Algorithms ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 298
Author(s):  
Ignacio Pérez-Messina ◽  
Eduardo Graells-Garrido ◽  
María Jesús Lobo ◽  
Christophe Hurter
Keyword(s):  
Survey Data ◽  
Visual Analysis ◽  
Ground Truth ◽  
Secondary Source ◽  
Urban Mobility ◽  
Flow Maps ◽  
Partial View ◽  
Visualization Techniques ◽  
Unsupervised Algorithms ◽  
Source Of Information

Pervasive data have become a key source of information for mobility and transportation analyses. However, as a secondary source, it has a different methodological origin than travel survey data, usually relying on unsupervised algorithms, and so it requires to be assessed as a dataset. This assessment is challenging, because, in general, there is not a benchmark dataset or a ground truth scenario available, as travel surveys only represent a partial view of the phenomenon and suffer from their own biases. For this critical task, which involves urban planners and data scientists, we study the design space of the visualization of cross-origin, multivariate flow datasets. For this purpose, we introduce the Modalflow system, which incorporates and adapts different visualization techniques in a notebook-like setting, presenting novel visual encodings and interactions for flows with modal partition into scatterplots, flow maps, origin-destination matrices, and ternary plots. Using this system, we extract general insights on visual analysis of pervasive and survey data for urban mobility and assess a mobile phone network dataset for one metropolitan area.

TV-MV Analytics: A visual analytics framework to explore time-varying multivariate data

2019 ◽  
Vol 19 (1) ◽  
pp. 3-23
Author(s):  
Aurea Soriano-Vargas ◽  
Bernd Hamann ◽  
Maria Cristina F de Oliveira
Keyword(s):  
Visual Analytics ◽  
Visual Analysis ◽  
Multivariate Data ◽  
Visual Exploration ◽  
Data Sets ◽  
Time Varying ◽  
Domain Experts ◽  
Data Mining Algorithms ◽  
Temporal Relationships ◽  
Visualization Techniques

We present an integrated interactive framework for the visual analysis of time-varying multivariate data sets. As part of our research, we performed in-depth studies concerning the applicability of visualization techniques to obtain valuable insights. We consolidated the considered analysis and visualization methods in one framework, called TV-MV Analytics. TV-MV Analytics effectively combines visualization and data mining algorithms providing the following capabilities: (1) visual exploration of multivariate data at different temporal scales, and (2) a hierarchical small multiples visualization combined with interactive clustering and multidimensional projection to detect temporal relationships in the data. We demonstrate the value of our framework for specific scenarios, by studying three use cases that were validated and discussed with domain experts.

scholarly journals The Qatar crisis: Challenges and opportunities

2021 ◽  
Vol 10 (1) ◽  
pp. 158-167
Author(s):  
Hani Albasoos ◽  
Gubara Hassan ◽  
Sara Al Zadjali
Keyword(s):  
Crisis Management ◽  
United Arab Emirates ◽  
Soft Power ◽  
Academic Research ◽  
Secondary Source ◽  
Challenges And Opportunities ◽  
Accelerated Growth ◽  
Negative Impacts ◽  
Source Of Information ◽  
Positive Force

This study reviews the challenges and opportunities encountered by Qatar because of the blockade imposed by the neighboring countries, namely Saudi Arabia, the United Arab Emirates (UAE), Bahrain, and Egypt. It endeavors to highlight potential scenarios of the crisis. This paper employs a secondary source of information to achieve the objectives, such as books, articles, reports, and academic research, which were later subjected to thematic analysis. The findings of this research reveal that crisis management was an effective strategy implemented by the Qatari Government. It helped Qatari officials to change and transfer the negative impacts to a positive force. The crisis management strategy encouraged Qatar to rely on their local industries, improve education and media institutes, and use Qatar’s soft power internationally. Although 2017 was a challenging year for Qatar due to the crisis, yet the national economy showed an accelerated growth of 5% in the second half of the same year. 

Visualization of Big Data Sets Using Computer Graphics

2018 ◽  
pp. 578-603
Author(s):  
Anna Ursyn ◽  
Edoardo L'Astorina
Keyword(s):  
Big Data ◽  
Data Visualization ◽  
Visual Analysis ◽  
Data Sets ◽  
Arrival Times ◽  
Learning And Teaching ◽  
Knowledge Domains ◽  
Visualization Of Data ◽  
And Mathematics ◽  
Visualization Techniques

This chapter discusses some possible ways of how professionals, researchers and users representing various knowledge domains are collecting and visualizing big data sets. First it describes communication through senses as a basis for visualization techniques, computational solutions for enhancing senses and ways of enhancing senses by technology. The next part discusses ideas behind visualization of data sets and ponders what is and what not visualization is. Further discussion relates to data visualization through art as visual solutions of science and mathematics related problems, documentation objects and events, and a testimony to thoughts, knowledge and meaning. Learning and teaching through data visualization is the concluding theme of the chapter. Edoardo L'Astorina provides visual analysis of best practices in visualization: An overlay of Google Maps that showed all the arrival times - in real time - of all the buses in your area based on your location and visual representation of all the Tweets in the world about TfL (Transport for London) tube lines to predict disruptions.

scholarly journals Automated fall risk assessment of elderly using wearable devices

2020 ◽  
Vol 7 ◽  
pp. 205566832094620
Author(s):  
Marian Haescher ◽  
Wencke Chodan ◽  
Florian Höpfner ◽  
Gerald Bieber ◽  
Mario Aehnelt ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Fall Risk ◽  
Human Error ◽  
Visual Analysis ◽  
Ground Truth ◽  
Wearable Devices ◽  
Healthcare Sector ◽  
Observational Assessment ◽  
Timed Up And Go ◽  
Fall Risk Assessment

Introduction Falls cause major expenses in the healthcare sector. We investigate the ability of supporting a fall risk assessment by introducing algorithms for automated assessments of standardized fall risk-related tests via wearable devices. Methods In a study, 13 participants conducted the standardized 6-Minutes Walk Test, the Timed-Up-and-Go Test, the 30-Second Sit-to-Stand Test, and the 4-Stage Balance Test repeatedly, producing 226 tests in total. Automated algorithms computed by wearable devices, as well as a visual analysis of the recorded data streams, were compared to the observational results conducted by physiotherapists. Results There was a high congruence between automated assessments and the ground truth for all four test types (ranging from 78.15% to 96.55%), with deviations ranging all well within one standard deviation of the ground truth. Fall risk (assessed by questionnaire) correlated with the individual tests. Conclusions The automated fall risk assessment using wearable devices and algorithms matches the validity of the ground truth, thus providing a resourceful alternative to the effortful observational assessment, while minimizing the risk of human error. No single test can predict overall fall risk; instead, a much more complex model with additional input parameters (e.g., fall history, medication etc.) is needed.

Updating Existing Travel Simulation Models with Small-Sample Survey Data Using Parameter Scaling Methods

1997 ◽  
Vol 1607 (1) ◽  
pp. 55-61
Author(s):  
W. Thomas Walker ◽  
Scott H. Brady ◽  
Charles Taylor
Keyword(s):  
Survey Data ◽  
Primary Source ◽  
Simulation Models ◽  
Small Sample ◽  
Sample Survey ◽  
Secondary Source ◽  
Sample Surveys ◽  
Large Sample ◽  
Scaling Methods ◽  
Home Interview

The travel simulation models for many metropolitan areas were originally developed and calibrated with older large-sample travel surveys that can no longer be undertaken given today’s funding constraints. Small-sample travel surveys have been collected as part of model update activities required by the Intermodal Surface Transportation Efficiency Act and the Clean Air Act Amendments. Although providing useful information, these surveys are inadequate for calibrating elaborate simulation models by traditional techniques. Parameter transfer scaling based on small-sample surveys and other secondary source data can be a cost-effective alternative to large-sample surveys when existing models are being updated, particularly when the models tend to be robust and the required changes are relatively small. The use of parameter scaling methods to update the Delaware Valley Planning Commission’s existing travel simulation models is demonstrated. All available sources of data are incorporated into the update process including current survey data, census work trips from the Census Transportation Planning Package (CTPP), transit ridership checks, highway screenline counts, and Highway Performance Monitoring System travel estimates. A synopsis of experience with parameter scaling techniques including the model changes and resulting accuracy is provided. Overall, small-sample-based parameter scaling techniques were judged to be effective. The census CTPP data were evaluated versus the home interview and were found to be useful in the model recalibration effort as a source of small-area employment data by place of work and as a supplement to home interview data for model validation. However, a home interview survey is required as the primary source of travel data for both work and nonwork trips.

scholarly journals Detecting Classic Maya Settlements with Lidar-Derived Relief Visualizations

2020 ◽  
Vol 12 (17) ◽  
pp. 2838 ◽  
Author(s):  
Amy E. Thompson
Keyword(s):  
Agricultural Practices ◽  
Ground Truth ◽  
Classic Maya ◽  
View Factor ◽  
Human Environment ◽  
Archaeological Prospection ◽  
Settlement Systems ◽  
Pedestrian Survey ◽  
Visualization Techniques ◽  
The Impact

In the past decade, Light Detection and Ranging (lidar) has fundamentally changed our ability to remotely detect archaeological features and deepen our understanding of past human-environment interactions, settlement systems, agricultural practices, and monumental constructions. Across archaeological contexts, lidar relief visualization techniques test how local environments impact archaeological prospection. This study used a 132 km2 lidar dataset to assess three relief visualization techniques—sky-view factor (SVF), topographic position index (TPI), and simple local relief model (SLRM)—and object-based image analysis (OBIA) on a slope model for the non-automated visual detection of small hinterland Classic (250–800 CE) Maya settlements near the polities of Uxbenká and Ix Kuku’il in Southern Belize. Pedestrian survey in the study area identified 315 plazuelas across a 35 km2 area; the remaining 90 km2 in the lidar dataset is yet to be surveyed. The previously surveyed plazuelas were compared to the plazuelas visually identified on the TPI and SLRM. In total, an additional 563 new possible plazuelas were visually identified across the lidar dataset, using TPI and SLRM. Larger plazuelas, and especially plazuelas located in disturbed environments, are often more likely to be detected in a visual assessment of the TPI and SLRM. These findings emphasize the extent and density of Classic Maya settlements and highlight the continued need for pedestrian survey to ground-truth remotely identified archaeological features and the impact of modern anthropogenic behaviors for archaeological prospection. Remote sensing and lidar have deepened our understanding of past human settlement systems and low-density urbanism, processes that we experience today as humans residing in modern cities.

scholarly journals Financial Leverage Determinants on the Financial Performance of a Company

2019 ◽  
Vol 8 (4) ◽  
pp. 11039-11042
Keyword(s):  
Financial Performance ◽  
Performance Assessment ◽  
Research Methodology ◽  
Financial Ratios ◽  
Annual Reports ◽  
Secondary Source ◽  
Financial Leverage ◽  
The Relationship ◽  
A Company ◽  
Source Of Information

The focus of the researchers is to examine the relationship between different financial leverage ratios like profitability, tangibility, growth and size to know the strength of the variables to justify financial performance of the company. The study is based on the secondary source of information collected from annual reports, websites, RBI bulletins, money control and CMIE reports. It is understood that the financial ratios are the strength of the financial performance assessment of a company for particular period of time which can be done through a well defined and designed research methodology basing on the facts and figures.

scholarly journals Role of Visualization in a Knowledge Transfer Process

2019 ◽  
Vol 10 (1) ◽  
pp. 164-179
Author(s):  
Janusz Opiła
Keyword(s):  
Knowledge Transfer ◽  
Knowledge Sharing ◽  
Transfer Process ◽  
Visual Analysis ◽  
Optimal Level ◽  
Information Density ◽  
Efficient Management ◽  
Level Of Details ◽  
Visualization Techniques

Abstract Background: Efficient management of the knowledge requires implementation of new tools and refinement of the old ones - one of them is visualization. As visualization turns out to be an efficient tool for transfer of acquired knowledge, understanding of the influence of visualization techniques on the process of knowledge sharing is a necessity. Objectives: The main objective of the paper is to deepen the understanding of the relation of visualization to other knowledge sharing paths. The supplementary goal is a discussion of constraints on visualization styles in relation to readability and efficiency. Methods/Approach: Due to the ambiguous nature of the problem, case analysis was selected as a research method. Two research papers have been selected for that. The first one focused on agrotourism, introduces a general use theoretical tool suitable for various purposes, such as consumer sentiment analysis. The second one evaluates possibilities of revealing an implicit organizational structure of an organization by means of visual analysis using interaction graphs. Results: Visualization is an important part of data analysis and knowledge transfer process. Hybrid visualization styles enhance information density but may decrease clarity. Conclusions: In order to maximise the role of visualization in a knowledg tranfer process, the special care must be devoted to clarity, the optimal level of details and information density in order to avoid obfuscation.

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